Reset23/the-stack-v2-processed · Datasets at Hugging Face

4f13c5d285c91f061fa8460aadb0cd6e1bdff63c

7971b92edf291a48ed578fb8ac85803161762036

/textbook/_build/jupyter_execute/ch_05.py

414064255e710176ea11bc9a4001e1c1eb2f284b

[]

no_license

paulsavala/Introduction-to-Data-Science

b9e84627fb3faf9a2acf519553aa72f35a1e9b7e

677337f9e0aa5aeb4c7de8b83a95449e79c7d746

refs/heads/main

2023-01-15T17:01:49.722008

2020-11-14T15:25:34

312,834,750

1

0

null

UTF-8

Python

false

27,867

py

#!/usr/bin/env python # coding: utf-8 # # Training models # ### Imports # In[ ]: import pandas as pd import numpy as np from matplotlib import pyplot as plt from sklearn.linear_model import LinearRegression # ### Data loading # # We'll start by using the Boston housing dataset again. # In[ ]: df = pd.read_csv('data/boston.csv') # ### Data cleaning # # Change all column names to lowercase, convert spaces to underscores, replace "%" with "pct", replace "-" with an underscore, check for missing values. # In[ ]: df.columns = [x.lower().replace(' ', '_').replace('%', 'pct').replace('-', '_') for x in df.columns] # In[ ]: df.head() # ## Training models <a id="training"></a> # # As we learned last week, linear regression is the process of fitting a line to data in the "best" way possible. We measured "best" in terms of mean squared error (MSE), given specifically by # $$ # \displaystyle\sum_i (y_i - (mx_i + b))^2 # $$ # where $y_i$ are the values to be predicted (median home value in our example last week) and $x_i$ are the data being used to make predictions (things like poverty rate, distance to downtown, etc). We then showed that you could simply take derivatives and find critical points to solve for what values of $m$ and $b$ will make this "error" as small as possible, i.e. minimize it. # # None of this is common in machine learning. In fact, linear regression is largely the only case of machine learning where we can actually *solve* for what value of the **model parameters**, the variables used in the model, will give the smallest error. Instead, we do what is called "model training". # # Model training works like this: # 1. Find data which you want your model to predict. # 2. Pick a model. Last week this was linear regression. As the semester goes on you'll learn about several other models. # 3. Do gradient descent (covered last week) to optimize your parameters. # # Let's do a brief overview of each step. # ### Finding data to train your model on # The first step is to find data. Normally you've got a general problem in mind that you want to answer. Your first step should be looking for data related to that problem. If you don't have data then you can't do anything else either. # # Let's define a few terms that we will be using throughout the rest of this semester: # - **features:** Features are simply the "inputs" in your data. So in the Titanic example, this would be things like age, fare, sex, etc. # - **labels:** Labels are the values you want to predict. The term "label" comes from when you are trying to predict a categorical variable, such as the breed of a dog, or the survival or death of a passenger. However we also use it for numerical variables, such as home value. # - **ground truth:** This refers to the "correct" values of the labels. For instance, suppose we collected data on passengers on the Titanic. We could build a machine learning model to predict whether or not each person survived, and the model would predict a label ("survived" or "died"). However, these are just *predictions*. By "ground truth" we mean the actual correct labels. That is, for each person described in the data, did they *actually* survive or die? Whatever the answer to this is is called the ground truth. # # So we want data with features and ground truth. Once we have that, we can move on to step 3. # ### Picking a model # # Machine learning "models" are simply functions. Linear regression is an especially simple function represented by a simple equation ($y=mx+b$). When dealing with inputs with many features then $m$, $x$ and $b$ are all vectors, which makes things seem complicated. But in reality it's just a line. Another model we will deal with extensively this semester is called a "decision tree". We will hold off on the details for now, but a decision tree is simply a function that repeated asks "yes/no" questions of the data. For instance, suppose we want to use a decision tree to determine whether or not a passenger on the titanic survives. Below is a possible decision tree: # # ![Titanic decision tree](images/titanic_decision_tree.png) # You can see that the first question is about the person's gender, then if they are a female the model predicts they will survive. If they are a male, the model then asks about their age, and so forth. This may not *look* like a function, but it is. Recall that a function is simply something that takes in input and returns a single output (think about the "vertical line test"). We could write this as an *equation* (which is probably how you typically think about functions) as follows: # $$ # f(\text{sex}, \text{age}, \text{sibsp}) = \text{piecewise function} # $$ # In this decision tree we have the following model parameters: # - Which columns should we ask questions about? # - What order should we ask these questions? Do we start with sex, age, or sibsp? # - When we ask about a numerical column (such as "is age > 9.5" or "is sibsp > 2.5"), what value should be our cutoff? That is why aren't we asking "is age > 14", or "is sibsp < 5"? # - After each question, what should we do next? Should we predict a value or go to another question? # - Whenever we decide to predict a value, what value should we predict? # # As you can see, model parameters can be quite complicated. It is impossible to setup an equation and "solve" for each of these like we did for linear regression. So instead, we train the model. That leads us to step 3. # ### Gradient descent # # We saw last class that gradient descent allows us to find values of the model parameters which make the loss function (mean squared error) as small as possible. By doing gradient descent we are able to find model parameters that make our model "fit" our data very well. By "fit", we mean that the loss function is very small. # ### Putting it all together # # In practice, the first two steps are done by you, and the final step is done automatically using sklearn. Let's do a couple examples. You may remember from last week that when doing linear regression there were a few options, in particular `fit_intercept` and `normalize`. How do these affect our model? Let's try doing one of each of the four possibilities (True/False for each of the two options) and see what we get. # In[ ]: lr1 = LinearRegression(fit_intercept=False, normalize=False) lr2 = LinearRegression(fit_intercept=True, normalize=False) lr3 = LinearRegression(fit_intercept=False, normalize=True) lr4 = LinearRegression(fit_intercept=True, normalize=True) # In[ ]: X = df[['crime_rate', 'avg_num_rooms', 'pct_below_poverty_line']] y = df['median_home_value'] # In[ ]: lr1.fit(X, y) lr2.fit(X, y) lr3.fit(X, y) lr4.fit(X, y) # We've now trained four models. That's great (and simple!), but how do we know which one is best? That is, which one makes the best predictions? Or, said more formally, how do we *evaluate* our models? # ## Evaluating your model <a id="model_evaluation"></a> # # Now that we have trained our model and used it to make predictions, how can we tell if it's making "good" predictions? Let's start with the simplest way, which is just comparing the predicted values to the actual values, which were stored in `y`. We'll loop through the first ten predictions. # In[ ]: lr1_pred = lr1.predict(X) for i in range(10): print(f'Actual = {y[i]}, Predicted = {lr1_pred[i]:.2f}') # We can see that most predictions seem reasonable, though definitely not perfect. It's a little annoying to look through the predictions this way. Let's plot both the predicted and actual values and see what we get. The problem is, how can we do this? To plot we put the `X` on the x-axis and the `y` on the y-axis. The problem is that our `X` is three dimensional, which means we're plotting in four dimensions! That won't work. Instead, what we'll do is just plot our y's (both `y` and `y_pred`) against each other. Let's do it then discuss it. # In[ ]: fig = plt.figure(figsize=(12, 10)) plt.scatter(y, lr1_pred) plt.xlabel('Actual home prices') plt.ylabel('Predicted home prices') plt.title('Actual vs predicted using linear regression'); # What are we looking at? Each point represents a home. The x value is the actual home price, and the y value is the predicted home price using our linear regression model. Let's look at a single point to make this clear. I'll do this by plotting twice: once for all except the first prediction, and once for the first prediction (in a different color to make it easy to see). I'll also make the size bigger using `s`. # In[ ]: fig = plt.figure(figsize=(12, 10)) plt.scatter(y[1:], lr1_pred[1:], color='gray') plt.scatter(y[0], lr1_pred[0], color='red', s=100) plt.xlabel('Actual home prices') plt.ylabel('Predicted home prices') plt.title('Actual vs predicted using linear regression'); # What is this red point? # In[ ]: print(f'Actual home value = {y[0]}, Predicted home value = {lr1_pred[0]}') # It is a home which cost \\$24,000 and had a predicted home price of a little over \\$28,857. We can see the information on it by looking at the data. # In[ ]: X.iloc[0] # So how should we make sense of the scatter plot above? Think about the following: suppose the regression line made perfect predictions. That is, suppose that for every single home, the regression line could predict exactly the correct value. Here is a simple example: # In[ ]: y = df['median_home_value'] y_pred_fake = y # The (fake) predicted values are exactly the real values. # Make the scatterplot fig = plt.figure(figsize=(12, 10)) plt.scatter(y, y_pred_fake) plt.xlabel('Actual home prices') plt.ylabel('(Fake) Predicted home prices') plt.title('Actual vs (fake) predicted using linear regression'); # A perfect line! that is because both the x and y values are identical. So a model which returned perfect predictions would have this scatter plot being a perfect line. # # Because of this, a common way to measure how strong a model's predictions are is by making this scatter plot and computing the correlation coefficient $R^2$. Let's do that now using what we learned last homework. # In[ ]: fig = plt.figure(figsize=(12, 10)) plt.scatter(y, lr1_pred) plt.xlabel('Actual home prices') plt.ylabel('Predicted home prices') plt.title(f'Actual vs predicted using linear regression: R^2 = {np.corrcoef(y, lr1_pred)[0,1]**2:.3f}'); # Not bad! That is a high correlation coefficient, as reflected by the fact that the scatterplot is quite linear. This means that our predictions are generally pretty good. # # At this point you don't really have a grasp on what's "good" and "not good". We'll do one more example below, but I highly encourage you to play with all of this on your own. Use both this dataset and others to try it all out. # # Let's pick some columns that probably *aren't* that useful in predicting home value and see what we get. # In[ ]: lr_weak = LinearRegression() X_weak = df[['pct_industrial', 'distance_to_downtown', 'pupil_teacher_ratio']] y = df['median_home_value'] # y is the same regardless, it's just the home prices lr_weak.fit(X_weak, y) y_weak_pred = lr_weak.predict(X_weak) # In[ ]: fig = plt.figure(figsize=(12, 10)) plt.scatter(y, y_weak_pred) plt.xlabel('Actual home prices') plt.ylabel('Predicted home prices') plt.title(f'Actual vs predicted using linear regression: R^2 = {np.corrcoef(y, y_weak_pred)[0, 1]**2:.3f}'); # A much lower $R^2$ value, and a much less linear graph. We can see that generally higher actual home prices seem to match with higher predicted home prices, and similarly for lower-priced homes. But the correlation is pretty weak. # # Since computing the correlation coefficient between the actual and predicted y values is so common and important, sklearn has it built-in. You can access the $R^2$ value using the `.score(...)` method. Go look at the documentation on it now on the sklearn page. At this point you should be comfortable enough reading that documentation to try it on your own. # In[ ]: lr1.score(X, y) # This shows one particular way to compare how "good" different models' predictions are. That is, we can compare their $R^2$ value by using `.score()`. # In[ ]: print(f'Score for lr1 (fit_intercept=False, normalize=False): {lr1.score(X, y)}') print(f'Score for lr2 (fit_intercept=True, normalize=False): {lr2.score(X, y)}') print(f'Score for lr3 (fit_intercept=False, normalize=True): {lr3.score(X, y)}') print(f'Score for lr4 (fit_intercept=True, normalize=True): {lr4.score(X, y)}') # It ends up that all three have very similar scores! In other words, it seens like those changes are making only very minor differences. Perhaps normalizing (*without* fitting the intercept) is very slightly the worst, but the difference is so small it likely isn't statistically significant. # ## Training vs testing <a id="train_test"></a> # # Now that you know how model training works, let's do some more examples. Suppose you go back through your old exams and you find what score you got. You then estimate how many hours you studied alone, how many hours you studied with a group, and how many hours you were studying for other courses that week. You then decide to build a linear model that will predict your score on your next exam, given how many hours you studied each way. # In[ ]: # Hours studied exam_df = pd.DataFrame({'score': [56, 86, 84], 'hours_alone': [3, 8, 4], 'hours_group': [3, 6, 10], 'hours_other': [7, 2, 5]}) X = exam_df[['hours_alone', 'hours_group', 'hours_other']] y = exam_df['score'] lr = LinearRegression() lr.fit(X, y) # Let's now look at the $R^2$ value (the score) to see how well this model fits the data. # In[ ]: lr.score(X, y) # My god, it's perfect! We have a perfect model that can determine exactly what score we will get based on knowing this study info! Let's confirm that. # In[ ]: exam_df # In[ ]: print(f'Actual score for first exam: {y[0]}, Predicted score for first exam: {lr.predict(X)[0]:.2f}') print(f'Actual score for second exam: {y[1]}, Predicted score for first exam: {lr.predict(X)[1]:.2f}') print(f'Actual score for third exam: {y[2]}, Predicted score for first exam: {lr.predict(X)[2]:.2f}') # We've done it! Let's go publish our results and become heroes to every student who wants to know how long they need to study! # # Okay, enough sarcasm, obviously something is wrong here. The numbers above are just made up (go ahead, try tweaking them and see that your model is essentially always perfect), and yet it can perfectly predict our scores? That doesn't make sense. What's happening is that *we are testing our model and the same data that we are training it with*. To understand this, consider the following real-world situation: Suppose your professor tells you your next exam is in a week. She gives you a practice exam, but you're too busy to really spend much time with it. However, just because you've seen it, you memorized the answers. You don't know how to do the problems, but you remember that the answer to the first problem is 42, the second is $x^2+y$, and so forth. Finally, the day of the test arrives. You sit down nervous about how much your grade is going to tank after this exam. She passes out the exams and you flip it over only to find...it's exactly the same as the practice test! Thrilled, you write down the correct answers and turn in the test after just 30 seconds. You come back next week to see that you got a perfect score! # # Does this mean that you *understand* the material? Of course not! You simply memorized the answers. More importantly, you don't know how to *generalize* to other topics. For example, perhaps you memorized that if $f(x)=2x^3$ then $f'(1) = 6$. However, if you got a new question "$f(x)=2x^4$, compute $f'(1)$" you would have no idea how to do it. This is exactly what happened with our model above. We trained it using some data for which it "memorized" the answers by choosing values of $m$ and $b$ which would produce perfect results. It then simply spit those back out when asked for predictions. Let's illustrate this by putting in the data for another exam you studied for. # In[ ]: # Create a DataFrame for this single exam next_exam_df = pd.DataFrame({'score': [76], 'hours_alone': [7], 'hours_group': [4], 'hours_other': [19]}) # Concatenate it to the already existing DataFrame exam_df = pd.concat([exam_df, next_exam_df]) exam_df = exam_df.reset_index(drop=True) exam_df.head() # In[ ]: X = exam_df[['hours_alone', 'hours_group', 'hours_other']] y = exam_df['score'] print(f'Actual score for fourth exam: {y[3]}, Predicted score for fourth exam: {lr.predict(X)[3]:.2f}') # Not even close! The reason is that our model did not learn to *generalize* what it learned. In reality, there's a bit more going on here. This is a linear system with three columns (variables) and three rows (exams). So it just solved the system and found a solution. However, in general models are *underdetermined*, meaning there are more rows than columns. Thus they cannot solve for a solution, they always have to approximate it. Regardless, the idea is the same: it is a mistake to *test* a model on the same data that you *trained* it on. Said in simple terms, the professor should have given you a real exam which was different (but similar) to the practice exam. # ## Train-test split <a id="train_test_split"></a> # # The fix to this is to take your data and **split** it into training and testing sets. The idea is that you will *train* your model on the **training set**, and *test* (or *evaluate*) your model on the **test set**. # # Splitting is very simple--it just consists of randomly putting some rows aside as the test set, and leaving the rest as the training set. Let's use some data on avocado sales to do this. # In[ ]: df = pd.read_csv(drive_dir + 'data/avocado.csv') df.head() # Here is a brief rundown of the columns: # - **Date:** The week when sales were measured # - **AveragePrice:** The average price of a single avocado # - **Total Volume:** The total number of avocado's sold in that week # - **4046:** The number of small avocados sold (4046 is the PLU code) # - **4225:** The number of large avocados sold # - **4770:** The number of extra-large avocados sold # - **Total Bags:** The total number of bags of avocados sold # - **Small Bags/Large Bags/XLarge Bags:** The total number of small/large/xlarge bags sold # - **type:** Whether the avocados were conventional or organic # - **year:** The year # - **region:** The region of sales # We'll start by quickly cleaning and checking the data, and renaming some columns. # In[ ]: df = df.drop('Unnamed: 0', axis='columns') df.columns = ['date', 'avg_price', 'total_volume', 'small', 'large', 'xlarge', 'total_bags', 'small_bags', 'large_bags', 'xlarge_bags', 'type', 'year', 'region'] df['date'] = pd.to_datetime(df['date']) # In[ ]: df.head() # In[ ]: df.isna().sum() # In[ ]: df.dtypes # Let's now split into training and testing sets. One way would be to just take the first rows and set them aside. # In[ ]: num_rows = df.shape[0] print(f'# rows = {num_rows}') # In[ ]: # Keep 30% of the data for testing first_30_pct = int(0.3 * num_rows) # Make the test set be the first 30%... test_df = df.iloc[:first_30_pct] # ... and the training set the last 70% train_df = df.iloc[first_30_pct:] # In[ ]: test_df.shape # In[ ]: train_df.shape # While this may seem reasonable, there are potential problems here. For example, what if your data was sorted by date? Or by neighborhood? Or by home value? By taking the first 30% we're potentially taking the first 30% of the dates or lowest 30% of home values, or only certain neighborhoods. We always want our samples to be representative of the population, so this could be a problem. # # The simplest fix is just to take a random sample. If you happen to know that your data has some other structure that you want to preserve (like neighborhoods), perhaps you could sample from those neighborhoods instead and be fancier. But 99% of the time the best idea is just to take a random sample. # # The simplest way to take a random sample is by using sklearn. They have a helper function called `train_test_split()`. You just need to supply your data, and what percentage of the data you want to be in the training set. The function will handle the rest. # In[ ]: from sklearn.model_selection import train_test_split # In[ ]: train_df, test_df = train_test_split(df, test_size=0.3) # In[ ]: test_df.shape # In[ ]: train_df.shape # Now that we have our data split into a training and testing set let's train on that train set and test on the test set. We'll try to predict the number of large avocados sold based on information about the small avocados. # In[ ]: # Split into training and testing data (30% test) train_df, test_df = train_test_split(df, test_size=0.3) # Grab the columns we want for X and y for both train and test X_train = train_df[['small', 'small_bags', 'avg_price']] y_train = train_df['large'] X_test = test_df[['small', 'small_bags', 'avg_price']] y_test = test_df['large'] # Create the linear regression object lr = LinearRegression() # Fit (i.e. train) the model on the training data lr.fit(X_train, y_train) # See how well it did (R^2 score) by looking at the test data lr.score(X_test, y_test) # ## Examining your predictions <a id="examining_predictions"></a> # # That's a really strong score! Let's look at the prediction vs ground truth scatterplot to see how it lines up. # In[ ]: fig = plt.figure(figsize=(12, 10)) # Note that we look at the predictions on the _test_ set test_pred = lr.predict(X_test) plt.scatter(y_test, test_pred) plt.xlabel('Actual large avocado sales') plt.ylabel('Predicted large avocado sales') plt.title(f'Actual vs predicted using linear regression: R^2 = {np.corrcoef(y_test, test_pred)[0,1]**2:.3f}'); # Hmm, that's interesting. It looks like the majority of the actual large avocado sales are fairly low (the bottom-left). There's also a small set of outliers with large sales. # # This example shows why you always need to actually *look at* what your model is predicting. While it returns a very high $R^2$ value, the actual scatterplot of predictions doesn't look great. It seems like the majority of the avocados are in the clump in the lower-left, and it doesn't look like the predictions are great there. # # Let's dive into this further. First we want to see how "large" prices are distributed. A boxplot seems like a good choice for this. # In[ ]: ax = df.boxplot('large', figsize=(12, 8), vert=False) ax.set_title('Large avocado sales'); # So the avocado sales are almost entirely in the smaller side, with a bunch of outliers. Let's try grouping by a few different factors, and see if we can figure out if some partial factor (organic vs conventional, a certain region, a certain year) is where all of those high sales are located. # In[ ]: # Group by type df.groupby('type')['large'].mean() # Yes, organic are sold in far lower numbers, but the "conventional" sales of 574805 is in scientific notation $5.7 \cdot 10^5$, which is still way, way on the left of the boxplot. So that's not the issue. Let's try regions. # In[ ]: # Group by region df.groupby('region')['large'].mean() # Skimming through the regions, the sales seem to be reasonably similar across the board. In the boxplot the outlier sales are on the order of $2 \cdot 10^7$, and we're not seeing anything like that here. California is about $10^6$, which is $0.1 \cdot 10^7$, so also not an outlier. Let's try year. # In[ ]: # Group by year df.groupby('year')['large'].mean() # Nope, still nothing jumping out. Let's try just directly grabbing those outliers and looking at them, maybe something will jump out. # In[ ]: outlier_df = df[df['large'] > 0.5 * 10**7] # In[ ]: outlier_df.head() # In[ ]: df.head() # That's interesting, the first few in `outlier_df` all have a region of `TotalUS`. Is that a coincidence? # In[ ]: outlier_df['region'].value_counts() # Doesn't look like it! Let's see how many `TotalUS` rows there are all together in the original data. # In[ ]: df[df['region'] == 'TotalUS'].shape[0] # Let's directly look at those. # In[ ]: df[df['region'] == 'TotalUS']['large'].plot(kind='hist', figsize=(12, 8)) # So that's why, when we grouped by region, `TotalUS` didn't jump out. Yes, there are plenty of outliers, but there are also plenty on the low range which "cancel out" the outliers. # # Regardless, it seems silly to compare individual regions (Albany, Boise, etc.) to the entire US. Let's remove those and just work with actual regions. # In[ ]: region_df = df[df['region'] != 'TotalUS'] # In[ ]: region_lr = LinearRegression() # Split into training and testing data (30% test) train_df, test_df = train_test_split(region_df, test_size=0.3) # Wait a second, we're duplicating code from above! That means we should make a function. # In[ ]: def lr_train_test_split(df, X_cols, y_col, test_size=0.3): # Split into training and testing data (30% test) train_df, test_df = train_test_split(df, test_size=0.3) # Grab the columns we want for X and y for both train and test X_train = train_df[X_cols] y_train = train_df[y_col] X_test = test_df[X_cols] y_test = test_df[y_col] # Create the linear regression object lr = LinearRegression() # Fit (i.e. train) the model on the training data lr.fit(X_train, y_train) return lr, X_train, y_train, X_test, y_test # In[ ]: region_lr, X_train, y_train, X_test, y_test = lr_train_test_split(region_df, X_cols=['small', 'small_bags', 'avg_price'], y_col='large') # In[ ]: region_lr.score(X_test, y_test) # We have a lower, but still strong $R^2$ value. Let's look at the scatterplot. # In[ ]: def lr_scatterplot(lr, X_test, y_test): fig = plt.figure(figsize=(12, 10)) test_pred = lr.predict(X_test) plt.scatter(y_test, test_pred) plt.xlabel('Actual sales') plt.ylabel('Predicted sales') plt.title(f'Actual vs predicted using linear regression: R^2 = {np.corrcoef(y_test, test_pred)[0,1]**2:.3f}'); # In[ ]: lr_scatterplot(region_lr, X_test, y_test) # That looks decent. The cone shape is not great, as it means that there is a range of predicted values corresponding to any actual value. But regardless, we have a model that does decently well. # # This sort of "inspecting your model" is absolutely necessary. If you ever train a model and then stop, you are doing data science wrong. What makes a good data scientist is *not* how many models you know or how quickly you write code, it's how well you understand your model and data. Someone who is able to dive into and understand their model and data is far more useful as a data scientist than someone who simply knows commands. Make it a habit to spent several multiples more time *analyzing* your model and data than *modeling* your data. # ## Exercises # # 1. Repeat the models comparing small sales to large sales, but with different columns. For instance, use medium to predict large. Try to not just copy-paste the code above. First, do as much as you can from memory. Then, when you get stuck, go up and see how to proceed. Type that part, and then again try to do the next step on your own. Repeat. # 2. Do exercise 1 again, but with new columns. This sort of "try on your own, look for help when you're stuck" process is the best way to learn these things, so do it over and over. # 3. Use more or less columns. # 4. Get another dataset and do linear regression on it. As you may have guessed from these exercises, linear regression is incredibly important, and the best thing you can do right now is to practice it.

[ "paulsavala@gmail.com" ]

paulsavala@gmail.com

cbbeb20bd3aaffb49646955091a89e5d16fedd2f

c149f1263b41f89eb03201044c16e47476f7e79f

/Rootfs/usr/bin/pildriver.py

89afaca15e58319d9e272337f88ac2c93b3cd9a0

[]

no_license

BasJ93/Zybo_Ubuntu

d596511dd7820aeb545a426e9c395b27b60028f9

2a50f4171a5469e0e96f0c0e75c528af0908758c

refs/heads/master

2022-12-22T00:17:54.522038

2017-02-02T13:15:16

72,639,835

2

1

null

2022-12-16T08:57:26

2016-11-02T12:54:53

C++

UTF-8

Python

false

15,600

py

#! /usr/bin/python """PILdriver, an image-processing calculator using PIL. An instance of class PILDriver is essentially a software stack machine (Polish-notation interpreter) for sequencing PIL image transformations. The state of the instance is the interpreter stack. The only method one will normally invoke after initialization is the `execute' method. This takes an argument list of tokens, pushes them onto the instance's stack, and then tries to clear the stack by successive evaluation of PILdriver operators. Any part of the stack not cleaned off persists and is part of the evaluation context for the next call of the execute method. PILDriver doesn't catch any exceptions, on the theory that these are actually diagnostic information that should be interpreted by the calling code. When called as a script, the command-line arguments are passed to a PILDriver instance. If there are no command-line arguments, the module runs an interactive interpreter, each line of which is split into space-separated tokens and passed to the execute method. In the method descriptions below, a first line beginning with the string `usage:' means this method can be invoked with the token that follows it. Following <>-enclosed arguments describe how the method interprets the entries on the stack. Each argument specification begins with a type specification: either `int', `float', `string', or `image'. All operations consume their arguments off the stack (use `dup' to keep copies around). Use `verbose 1' to see the stack state displayed before each operation. Usage examples: `show crop 0 0 200 300 open test.png' loads test.png, crops out a portion of its upper-left-hand corner and displays the cropped portion. `save rotated.png rotate 30 open test.tiff' loads test.tiff, rotates it 30 degrees, and saves the result as rotated.png (in PNG format). """ # by Eric S. Raymond <esr@thyrsus.com> # $Id$ # TO DO: # 1. Add PILFont capabilities, once that's documented. # 2. Add PILDraw operations. # 3. Add support for composing and decomposing multiple-image files. # from __future__ import print_function from PIL import Image class PILDriver: verbose = 0 def do_verbose(self): """usage: verbose <int:num> Set verbosity flag from top of stack. """ self.verbose = int(self.do_pop()) # The evaluation stack (internal only) stack = [] # Stack of pending operations def push(self, item): "Push an argument onto the evaluation stack." self.stack = [item] + self.stack def top(self): "Return the top-of-stack element." return self.stack[0] # Stack manipulation (callable) def do_clear(self): """usage: clear Clear the stack. """ self.stack = [] def do_pop(self): """usage: pop Discard the top element on the stack. """ top = self.stack[0] self.stack = self.stack[1:] return top def do_dup(self): """usage: dup Duplicate the top-of-stack item. """ if hasattr(self, 'format'): # If it's an image, do a real copy dup = self.stack[0].copy() else: dup = self.stack[0] self.stack = [dup] + self.stack def do_swap(self): """usage: swap Swap the top-of-stack item with the next one down. """ self.stack = [self.stack[1], self.stack[0]] + self.stack[2:] # Image module functions (callable) def do_new(self): """usage: new <int:xsize> <int:ysize> <int:color>: Create and push a greyscale image of given size and color. """ xsize = int(self.do_pop()) ysize = int(self.do_pop()) color = int(self.do_pop()) self.push(Image.new("L", (xsize, ysize), color)) def do_open(self): """usage: open <string:filename> Open the indicated image, read it, push the image on the stack. """ self.push(Image.open(self.do_pop())) def do_blend(self): """usage: blend <image:pic1> <image:pic2> <float:alpha> Replace two images and an alpha with the blended image. """ image1 = self.do_pop() image2 = self.do_pop() alpha = float(self.do_pop()) self.push(Image.blend(image1, image2, alpha)) def do_composite(self): """usage: composite <image:pic1> <image:pic2> <image:mask> Replace two images and a mask with their composite. """ image1 = self.do_pop() image2 = self.do_pop() mask = self.do_pop() self.push(Image.composite(image1, image2, mask)) def do_merge(self): """usage: merge <string:mode> <image:pic1> [<image:pic2> [<image:pic3> [<image:pic4>]]] Merge top-of stack images in a way described by the mode. """ mode = self.do_pop() bandlist = [] for band in mode: bandlist.append(self.do_pop()) self.push(Image.merge(mode, bandlist)) # Image class methods def do_convert(self): """usage: convert <string:mode> <image:pic1> Convert the top image to the given mode. """ mode = self.do_pop() image = self.do_pop() self.push(image.convert(mode)) def do_copy(self): """usage: copy <image:pic1> Make and push a true copy of the top image. """ self.dup() def do_crop(self): """usage: crop <int:left> <int:upper> <int:right> <int:lower> <image:pic1> Crop and push a rectangular region from the current image. """ left = int(self.do_pop()) upper = int(self.do_pop()) right = int(self.do_pop()) lower = int(self.do_pop()) image = self.do_pop() self.push(image.crop((left, upper, right, lower))) def do_draft(self): """usage: draft <string:mode> <int:xsize> <int:ysize> Configure the loader for a given mode and size. """ mode = self.do_pop() xsize = int(self.do_pop()) ysize = int(self.do_pop()) self.push(self.draft(mode, (xsize, ysize))) def do_filter(self): """usage: filter <string:filtername> <image:pic1> Process the top image with the given filter. """ from PIL import ImageFilter filter = eval("ImageFilter." + self.do_pop().upper()) image = self.do_pop() self.push(image.filter(filter)) def do_getbbox(self): """usage: getbbox Push left, upper, right, and lower pixel coordinates of the top image. """ bounding_box = self.do_pop().getbbox() self.push(bounding_box[3]) self.push(bounding_box[2]) self.push(bounding_box[1]) self.push(bounding_box[0]) def do_getextrema(self): """usage: extrema Push minimum and maximum pixel values of the top image. """ extrema = self.do_pop().extrema() self.push(extrema[1]) self.push(extrema[0]) def do_offset(self): """usage: offset <int:xoffset> <int:yoffset> <image:pic1> Offset the pixels in the top image. """ xoff = int(self.do_pop()) yoff = int(self.do_pop()) image = self.do_pop() self.push(image.offset(xoff, yoff)) def do_paste(self): """usage: paste <image:figure> <int:xoffset> <int:yoffset> <image:ground> Paste figure image into ground with upper left at given offsets. """ figure = self.do_pop() xoff = int(self.do_pop()) yoff = int(self.do_pop()) ground = self.do_pop() if figure.mode == "RGBA": ground.paste(figure, (xoff, yoff), figure) else: ground.paste(figure, (xoff, yoff)) self.push(ground) def do_resize(self): """usage: resize <int:xsize> <int:ysize> <image:pic1> Resize the top image. """ ysize = int(self.do_pop()) xsize = int(self.do_pop()) image = self.do_pop() self.push(image.resize((xsize, ysize))) def do_rotate(self): """usage: rotate <int:angle> <image:pic1> Rotate image through a given angle """ angle = int(self.do_pop()) image = self.do_pop() self.push(image.rotate(angle)) def do_save(self): """usage: save <string:filename> <image:pic1> Save image with default options. """ filename = self.do_pop() image = self.do_pop() image.save(filename) def do_save2(self): """usage: save2 <string:filename> <string:options> <image:pic1> Save image with specified options. """ filename = self.do_pop() options = self.do_pop() image = self.do_pop() image.save(filename, None, options) def do_show(self): """usage: show <image:pic1> Display and pop the top image. """ self.do_pop().show() def do_thumbnail(self): """usage: thumbnail <int:xsize> <int:ysize> <image:pic1> Modify the top image in the stack to contain a thumbnail of itself. """ ysize = int(self.do_pop()) xsize = int(self.do_pop()) self.top().thumbnail((xsize, ysize)) def do_transpose(self): """usage: transpose <string:operator> <image:pic1> Transpose the top image. """ transpose = self.do_pop().upper() image = self.do_pop() self.push(image.transpose(transpose)) # Image attributes def do_format(self): """usage: format <image:pic1> Push the format of the top image onto the stack. """ self.push(self.do_pop().format) def do_mode(self): """usage: mode <image:pic1> Push the mode of the top image onto the stack. """ self.push(self.do_pop().mode) def do_size(self): """usage: size <image:pic1> Push the image size on the stack as (y, x). """ size = self.do_pop().size self.push(size[0]) self.push(size[1]) # ImageChops operations def do_invert(self): """usage: invert <image:pic1> Invert the top image. """ from PIL import ImageChops self.push(ImageChops.invert(self.do_pop())) def do_lighter(self): """usage: lighter <image:pic1> <image:pic2> Pop the two top images, push an image of the lighter pixels of both. """ from PIL import ImageChops image1 = self.do_pop() image2 = self.do_pop() self.push(ImageChops.lighter(image1, image2)) def do_darker(self): """usage: darker <image:pic1> <image:pic2> Pop the two top images, push an image of the darker pixels of both. """ from PIL import ImageChops image1 = self.do_pop() image2 = self.do_pop() self.push(ImageChops.darker(image1, image2)) def do_difference(self): """usage: difference <image:pic1> <image:pic2> Pop the two top images, push the difference image """ from PIL import ImageChops image1 = self.do_pop() image2 = self.do_pop() self.push(ImageChops.difference(image1, image2)) def do_multiply(self): """usage: multiply <image:pic1> <image:pic2> Pop the two top images, push the multiplication image. """ from PIL import ImageChops image1 = self.do_pop() image2 = self.do_pop() self.push(ImageChops.multiply(image1, image2)) def do_screen(self): """usage: screen <image:pic1> <image:pic2> Pop the two top images, superimpose their inverted versions. """ from PIL import ImageChops image2 = self.do_pop() image1 = self.do_pop() self.push(ImageChops.screen(image1, image2)) def do_add(self): """usage: add <image:pic1> <image:pic2> <int:offset> <float:scale> Pop the two top images, produce the scaled sum with offset. """ from PIL import ImageChops image1 = self.do_pop() image2 = self.do_pop() scale = float(self.do_pop()) offset = int(self.do_pop()) self.push(ImageChops.add(image1, image2, scale, offset)) def do_subtract(self): """usage: subtract <image:pic1> <image:pic2> <int:offset> <float:scale> Pop the two top images, produce the scaled difference with offset. """ from PIL import ImageChops image1 = self.do_pop() image2 = self.do_pop() scale = float(self.do_pop()) offset = int(self.do_pop()) self.push(ImageChops.subtract(image1, image2, scale, offset)) # ImageEnhance classes def do_color(self): """usage: color <image:pic1> Enhance color in the top image. """ from PIL import ImageEnhance factor = float(self.do_pop()) image = self.do_pop() enhancer = ImageEnhance.Color(image) self.push(enhancer.enhance(factor)) def do_contrast(self): """usage: contrast <image:pic1> Enhance contrast in the top image. """ from PIL import ImageEnhance factor = float(self.do_pop()) image = self.do_pop() enhancer = ImageEnhance.Contrast(image) self.push(enhancer.enhance(factor)) def do_brightness(self): """usage: brightness <image:pic1> Enhance brightness in the top image. """ from PIL import ImageEnhance factor = float(self.do_pop()) image = self.do_pop() enhancer = ImageEnhance.Brightness(image) self.push(enhancer.enhance(factor)) def do_sharpness(self): """usage: sharpness <image:pic1> Enhance sharpness in the top image. """ from PIL import ImageEnhance factor = float(self.do_pop()) image = self.do_pop() enhancer = ImageEnhance.Sharpness(image) self.push(enhancer.enhance(factor)) # The interpreter loop def execute(self, list): "Interpret a list of PILDriver commands." list.reverse() while len(list) > 0: self.push(list[0]) list = list[1:] if self.verbose: print("Stack: " + repr(self.stack)) top = self.top() if not isinstance(top, str): continue; funcname = "do_" + top if not hasattr(self, funcname): continue else: self.do_pop() func = getattr(self, funcname) func() if __name__ == '__main__': import sys try: import readline except ImportError: pass # not available on all platforms # If we see command-line arguments, interpret them as a stack state # and execute. Otherwise go interactive. driver = PILDriver() if len(sys.argv[1:]) > 0: driver.execute(sys.argv[1:]) else: print("PILDriver says hello.") while True: try: if sys.version_info[0] >= 3: line = input('pildriver> '); else: line = raw_input('pildriver> '); except EOFError: print("\nPILDriver says goodbye.") break driver.execute(line.split()) print(driver.stack) # The following sets edit modes for GNU EMACS # Local Variables: # mode:python # End:

[ "r.halvaei@gmail.com" ]

r.halvaei@gmail.com

0abd0228cbd16d4d2350bd9c779f9884e2e9aa4a

e1bdbd08afec39c1ee56a3885a837ec966543a2d

/Section_07_code/extract_freq_features.py

00d66469084172389834335b106181bd1cd6dc6e

[ "MIT" ]

permissive

PacktPublishing/Python-Machine-Learning-Solutions-V-

507bd8b285f051d2761a5348e4a8c9a50329287a

8bb80a43a7c64032c25c1023faaa29bbfbd39d45

refs/heads/master

2023-02-28T05:19:49.782472

2021-01-20T09:11:09

188,817,647

0

2

null

UTF-8

Python

false

836

py

import numpy as np import matplotlib.pyplot as plt from scipy.io import wavfile from python_speech_features import mfcc, logfbank # Read input sound file sampling_freq, audio = wavfile.read("input_freq.wav") # Extract MFCC and Filter bank features mfcc_features = mfcc(audio, sampling_freq) filterbank_features = logfbank(audio, sampling_freq) # Print parameters print('\nMFCC:\nNumber of windows =', mfcc_features.shape[0]) print('Length of each feature =', mfcc_features.shape[1]) print('\nFilter bank:\nNumber of windows =', filterbank_features.shape[0]) print('Length of each feature =', filterbank_features.shape[1] # Plot the features mfcc_features= mfcc_features.T plt.matshow(mfcc_features) plt.title('MFCC') filterbank_features = filterbank_features.T plt.matshow(filterbank_features) plt.title('Filter bank') plt.show()

[ "sonalis@packtpub.com" ]

sonalis@packtpub.com

443bfea7bc2081899d1ca87933fdcd6b88ff3423

d71d30383eddf30df781b5d13aeb311957beda4f

/edure_env/lib/python2.7/site-packages/dropbox/base.py

0ae39821426fa62f4f911888a89eb5b280c68c4b

[]

no_license

priyabrata88/EDURE

34ef0e0bf9f4525a9f4f495ed06d8c127485a547

9733b1b2985a658ce3e31951037a6ed5e47d4cb7

refs/heads/master

2022-12-13T21:01:41.338849

2019-05-14T08:16:59

186,575,492

0

null

2022-12-08T00:48:19

2019-05-14T08:10:29

Python

UTF-8

Python

false

164,944

py

# -*- coding: utf-8 -*- # Auto-generated by Stone, do not modify. # flake8: noqa # pylint: skip-file from abc import ABCMeta, abstractmethod import warnings from . import ( async, auth, common, file_properties, file_requests, files, paper, sharing, team, team_common, team_log, team_policies, users, users_common, ) class DropboxBase(object): __metaclass__ = ABCMeta @abstractmethod def request(self, route, namespace, arg, arg_binary=None): pass # ------------------------------------------ # Routes in auth namespace def auth_token_from_oauth1(self, oauth1_token, oauth1_token_secret): """ Creates an OAuth 2.0 access token from the supplied OAuth 1.0 access token. :param str oauth1_token: The supplied OAuth 1.0 access token. :param str oauth1_token_secret: The token secret associated with the supplied access token. :rtype: :class:`dropbox.auth.TokenFromOAuth1Result` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.auth.TokenFromOAuth1Error` """ arg = auth.TokenFromOAuth1Arg(oauth1_token, oauth1_token_secret) r = self.request( auth.token_from_oauth1, 'auth', arg, None, ) return r def auth_token_revoke(self): """ Disables the access token used to authenticate the call. :rtype: None """ arg = None r = self.request( auth.token_revoke, 'auth', arg, None, ) return None # ------------------------------------------ # Routes in file_properties namespace def file_properties_properties_add(self, path, property_groups): """ Add property groups to a Dropbox file. See :meth:`file_properties_templates_add_for_user` or :meth:`file_properties_templates_add_for_team` to create new templates. :param str path: A unique identifier for the file or folder. :param list property_groups: The property groups which are to be added to a Dropbox file. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.AddPropertiesError` """ arg = file_properties.AddPropertiesArg(path, property_groups) r = self.request( file_properties.properties_add, 'file_properties', arg, None, ) return None def file_properties_properties_overwrite(self, path, property_groups): """ Overwrite property groups associated with a file. This endpoint should be used instead of :meth:`file_properties_properties_update` when property groups are being updated via a "snapshot" instead of via a "delta". In other words, this endpoint will delete all omitted fields from a property group, whereas :meth:`file_properties_properties_update` will only delete fields that are explicitly marked for deletion. :param str path: A unique identifier for the file or folder. :param list property_groups: The property groups "snapshot" updates to force apply. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.InvalidPropertyGroupError` """ arg = file_properties.OverwritePropertyGroupArg(path, property_groups) r = self.request( file_properties.properties_overwrite, 'file_properties', arg, None, ) return None def file_properties_properties_remove(self, path, property_template_ids): """ Permanently removes the specified property group from the file. To remove specific property field key value pairs, see :meth:`file_properties_properties_update`. To update a template, see :meth:`file_properties_templates_update_for_user` or :meth:`file_properties_templates_update_for_team`. Templates can't be removed once created. :param str path: A unique identifier for the file or folder. :param list property_template_ids: A list of identifiers for a template created by :meth:`file_properties_templates_add_for_user` or :meth:`file_properties_templates_add_for_team`. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.RemovePropertiesError` """ arg = file_properties.RemovePropertiesArg(path, property_template_ids) r = self.request( file_properties.properties_remove, 'file_properties', arg, None, ) return None def file_properties_properties_search(self, queries, template_filter=file_properties.TemplateFilter.filter_none): """ Search across property templates for particular property field values. :param list queries: Queries to search. :param template_filter: Filter results to contain only properties associated with these template IDs. :type template_filter: :class:`dropbox.file_properties.TemplateFilter` :rtype: :class:`dropbox.file_properties.PropertiesSearchResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.PropertiesSearchError` """ arg = file_properties.PropertiesSearchArg(queries, template_filter) r = self.request( file_properties.properties_search, 'file_properties', arg, None, ) return r def file_properties_properties_search_continue(self, cursor): """ Once a cursor has been retrieved from :meth:`file_properties_properties_search`, use this to paginate through all search results. :param str cursor: The cursor returned by your last call to :meth:`file_properties_properties_search` or :meth:`file_properties_properties_search_continue`. :rtype: :class:`dropbox.file_properties.PropertiesSearchResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.PropertiesSearchContinueError` """ arg = file_properties.PropertiesSearchContinueArg(cursor) r = self.request( file_properties.properties_search_continue, 'file_properties', arg, None, ) return r def file_properties_properties_update(self, path, update_property_groups): """ Add, update or remove properties associated with the supplied file and templates. This endpoint should be used instead of :meth:`file_properties_properties_overwrite` when property groups are being updated via a "delta" instead of via a "snapshot" . In other words, this endpoint will not delete any omitted fields from a property group, whereas :meth:`file_properties_properties_overwrite` will delete any fields that are omitted from a property group. :param str path: A unique identifier for the file or folder. :param list update_property_groups: The property groups "delta" updates to apply. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.UpdatePropertiesError` """ arg = file_properties.UpdatePropertiesArg(path, update_property_groups) r = self.request( file_properties.properties_update, 'file_properties', arg, None, ) return None def file_properties_templates_add_for_team(self, name, description, fields): """ Add a template associated with a team. See :meth:`file_properties_properties_add` to add properties to a file or folder. Note: this endpoint will create team-owned templates. :rtype: :class:`dropbox.file_properties.AddTemplateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.ModifyTemplateError` """ arg = file_properties.AddTemplateArg(name, description, fields) r = self.request( file_properties.templates_add_for_team, 'file_properties', arg, None, ) return r def file_properties_templates_add_for_user(self, name, description, fields): """ Add a template associated with a user. See :meth:`file_properties_properties_add` to add properties to a file. This endpoint can't be called on a team member or admin's behalf. :rtype: :class:`dropbox.file_properties.AddTemplateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.ModifyTemplateError` """ arg = file_properties.AddTemplateArg(name, description, fields) r = self.request( file_properties.templates_add_for_user, 'file_properties', arg, None, ) return r def file_properties_templates_get_for_team(self, template_id): """ Get the schema for a specified template. :param str template_id: An identifier for template added by route See :meth:`file_properties_templates_add_for_user` or :meth:`file_properties_templates_add_for_team`. :rtype: :class:`dropbox.file_properties.GetTemplateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.TemplateError` """ arg = file_properties.GetTemplateArg(template_id) r = self.request( file_properties.templates_get_for_team, 'file_properties', arg, None, ) return r def file_properties_templates_get_for_user(self, template_id): """ Get the schema for a specified template. This endpoint can't be called on a team member or admin's behalf. :param str template_id: An identifier for template added by route See :meth:`file_properties_templates_add_for_user` or :meth:`file_properties_templates_add_for_team`. :rtype: :class:`dropbox.file_properties.GetTemplateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.TemplateError` """ arg = file_properties.GetTemplateArg(template_id) r = self.request( file_properties.templates_get_for_user, 'file_properties', arg, None, ) return r def file_properties_templates_list_for_team(self): """ Get the template identifiers for a team. To get the schema of each template use :meth:`file_properties_templates_get_for_team`. :rtype: :class:`dropbox.file_properties.ListTemplateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.TemplateError` """ arg = None r = self.request( file_properties.templates_list_for_team, 'file_properties', arg, None, ) return r def file_properties_templates_list_for_user(self): """ Get the template identifiers for a team. To get the schema of each template use :meth:`file_properties_templates_get_for_user`. This endpoint can't be called on a team member or admin's behalf. :rtype: :class:`dropbox.file_properties.ListTemplateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.TemplateError` """ arg = None r = self.request( file_properties.templates_list_for_user, 'file_properties', arg, None, ) return r def file_properties_templates_remove_for_team(self, template_id): """ Permanently removes the specified template created from :meth:`file_properties_templates_add_for_user`. All properties associated with the template will also be removed. This action cannot be undone. :param str template_id: An identifier for a template created by :meth:`file_properties_templates_add_for_user` or :meth:`file_properties_templates_add_for_team`. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.TemplateError` """ arg = file_properties.RemoveTemplateArg(template_id) r = self.request( file_properties.templates_remove_for_team, 'file_properties', arg, None, ) return None def file_properties_templates_remove_for_user(self, template_id): """ Permanently removes the specified template created from :meth:`file_properties_templates_add_for_user`. All properties associated with the template will also be removed. This action cannot be undone. :param str template_id: An identifier for a template created by :meth:`file_properties_templates_add_for_user` or :meth:`file_properties_templates_add_for_team`. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.TemplateError` """ arg = file_properties.RemoveTemplateArg(template_id) r = self.request( file_properties.templates_remove_for_user, 'file_properties', arg, None, ) return None def file_properties_templates_update_for_team(self, template_id, name=None, description=None, add_fields=None): """ Update a template associated with a team. This route can update the template name, the template description and add optional properties to templates. :param str template_id: An identifier for template added by See :meth:`file_properties_templates_add_for_user` or :meth:`file_properties_templates_add_for_team`. :param Nullable name: A display name for the template. template names can be up to 256 bytes. :param Nullable description: Description for the new template. Template descriptions can be up to 1024 bytes. :param Nullable add_fields: Property field templates to be added to the group template. There can be up to 32 properties in a single template. :rtype: :class:`dropbox.file_properties.UpdateTemplateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.ModifyTemplateError` """ arg = file_properties.UpdateTemplateArg(template_id, name, description, add_fields) r = self.request( file_properties.templates_update_for_team, 'file_properties', arg, None, ) return r def file_properties_templates_update_for_user(self, template_id, name=None, description=None, add_fields=None): """ Update a template associated with a user. This route can update the template name, the template description and add optional properties to templates. This endpoint can't be called on a team member or admin's behalf. :param str template_id: An identifier for template added by See :meth:`file_properties_templates_add_for_user` or :meth:`file_properties_templates_add_for_team`. :param Nullable name: A display name for the template. template names can be up to 256 bytes. :param Nullable description: Description for the new template. Template descriptions can be up to 1024 bytes. :param Nullable add_fields: Property field templates to be added to the group template. There can be up to 32 properties in a single template. :rtype: :class:`dropbox.file_properties.UpdateTemplateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_properties.ModifyTemplateError` """ arg = file_properties.UpdateTemplateArg(template_id, name, description, add_fields) r = self.request( file_properties.templates_update_for_user, 'file_properties', arg, None, ) return r # ------------------------------------------ # Routes in file_requests namespace def file_requests_create(self, title, destination, deadline=None, open=True): """ Creates a file request for this user. :param str title: The title of the file request. Must not be empty. :param str destination: The path of the folder in the Dropbox where uploaded files will be sent. For apps with the app folder permission, this will be relative to the app folder. :param Nullable deadline: The deadline for the file request. Deadlines can only be set by Pro and Business accounts. :param bool open: Whether or not the file request should be open. If the file request is closed, it will not accept any file submissions, but it can be opened later. :rtype: :class:`dropbox.file_requests.FileRequest` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.file_requests.CreateFileRequestError` """ arg = file_requests.CreateFileRequestArgs(title, destination, deadline, open) r = self.request( file_requests.create, 'file_requests', arg, None, ) return r def file_requests_get(self, id): """ Returns the specified file request. :param str id: The ID of the file request to retrieve. :rtype: :class:`dropbox.file_requests.FileRequest` """ arg = file_requests.GetFileRequestArgs(id) r = self.request( file_requests.get, 'file_requests', arg, None, ) return r def file_requests_list(self): """ Returns a list of file requests owned by this user. For apps with the app folder permission, this will only return file requests with destinations in the app folder. :rtype: :class:`dropbox.file_requests.ListFileRequestsResult` """ arg = None r = self.request( file_requests.list, 'file_requests', arg, None, ) return r def file_requests_update(self, id, title=None, destination=None, deadline=file_requests.UpdateFileRequestDeadline.no_update, open=None): """ Update a file request. :param str id: The ID of the file request to update. :param Nullable title: The new title of the file request. Must not be empty. :param Nullable destination: The new path of the folder in the Dropbox where uploaded files will be sent. For apps with the app folder permission, this will be relative to the app folder. :param deadline: The new deadline for the file request. :type deadline: :class:`dropbox.file_requests.UpdateFileRequestDeadline` :param Nullable open: Whether to set this file request as open or closed. :rtype: :class:`dropbox.file_requests.FileRequest` """ arg = file_requests.UpdateFileRequestArgs(id, title, destination, deadline, open) r = self.request( file_requests.update, 'file_requests', arg, None, ) return r # ------------------------------------------ # Routes in files namespace def files_alpha_get_metadata(self, path, include_media_info=False, include_deleted=False, include_has_explicit_shared_members=False, include_property_groups=None, include_property_templates=None): """ Returns the metadata for a file or folder. This is an alpha endpoint compatible with the properties API. Note: Metadata for the root folder is unsupported. :param Nullable include_property_templates: If set to a valid list of template IDs, ``FileMetadata.property_groups`` is set for files with custom properties. :rtype: :class:`dropbox.files.Metadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.AlphaGetMetadataError` """ warnings.warn( 'alpha/get_metadata is deprecated. Use get_metadata.', DeprecationWarning, ) arg = files.AlphaGetMetadataArg(path, include_media_info, include_deleted, include_has_explicit_shared_members, include_property_groups, include_property_templates) r = self.request( files.alpha_get_metadata, 'files', arg, None, ) return r def files_alpha_upload(self, f, path, mode=files.WriteMode.add, autorename=False, client_modified=None, mute=False, property_groups=None): """ Create a new file with the contents provided in the request. Note that this endpoint is part of the properties API alpha and is slightly different from :meth:`files_upload`. Do not use this to upload a file larger than 150 MB. Instead, create an upload session with :meth:`files_upload_session_start`. :param bytes f: Contents to upload. :rtype: :class:`dropbox.files.FileMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.UploadErrorWithProperties` """ warnings.warn( 'alpha/upload is deprecated. Use alpha/upload.', DeprecationWarning, ) arg = files.CommitInfoWithProperties(path, mode, autorename, client_modified, mute, property_groups) r = self.request( files.alpha_upload, 'files', arg, f, ) return r def files_copy(self, from_path, to_path, allow_shared_folder=False, autorename=False, allow_ownership_transfer=False): """ Copy a file or folder to a different location in the user's Dropbox. If the source path is a folder all its contents will be copied. :param bool allow_shared_folder: If true, :meth:`files_copy` will copy contents in shared folder, otherwise ``RelocationError.cant_copy_shared_folder`` will be returned if ``from_path`` contains shared folder. This field is always true for :meth:`files_move`. :param bool autorename: If there's a conflict, have the Dropbox server try to autorename the file to avoid the conflict. :param bool allow_ownership_transfer: Allow moves by owner even if it would result in an ownership transfer for the content being moved. This does not apply to copies. :rtype: :class:`dropbox.files.Metadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.RelocationError` """ warnings.warn( 'copy is deprecated. Use copy_v2.', DeprecationWarning, ) arg = files.RelocationArg(from_path, to_path, allow_shared_folder, autorename, allow_ownership_transfer) r = self.request( files.copy, 'files', arg, None, ) return r def files_copy_batch(self, entries, allow_shared_folder=False, autorename=False, allow_ownership_transfer=False): """ Copy multiple files or folders to different locations at once in the user's Dropbox. If ``RelocationBatchArg.allow_shared_folder`` is false, this route is atomic. If on entry failes, the whole transaction will abort. If ``RelocationBatchArg.allow_shared_folder`` is true, not atomicity is guaranteed, but you will be able to copy the contents of shared folders to new locations. This route will return job ID immediately and do the async copy job in background. Please use :meth:`files_copy_batch_check` to check the job status. :param list entries: List of entries to be moved or copied. Each entry is :class:`dropbox.files.RelocationPath`. :param bool allow_shared_folder: If true, :meth:`files_copy_batch` will copy contents in shared folder, otherwise ``RelocationError.cant_copy_shared_folder`` will be returned if ``RelocationPath.from_path`` contains shared folder. This field is always true for :meth:`files_move_batch`. :param bool autorename: If there's a conflict with any file, have the Dropbox server try to autorename that file to avoid the conflict. :param bool allow_ownership_transfer: Allow moves by owner even if it would result in an ownership transfer for the content being moved. This does not apply to copies. :rtype: :class:`dropbox.files.RelocationBatchLaunch` """ arg = files.RelocationBatchArg(entries, allow_shared_folder, autorename, allow_ownership_transfer) r = self.request( files.copy_batch, 'files', arg, None, ) return r def files_copy_batch_check(self, async_job_id): """ Returns the status of an asynchronous job for :meth:`files_copy_batch`. If success, it returns list of results for each entry. :param str async_job_id: Id of the asynchronous job. This is the value of a response returned from the method that launched the job. :rtype: :class:`dropbox.files.RelocationBatchJobStatus` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.PollError` """ arg = async.PollArg(async_job_id) r = self.request( files.copy_batch_check, 'files', arg, None, ) return r def files_copy_reference_get(self, path): """ Get a copy reference to a file or folder. This reference string can be used to save that file or folder to another user's Dropbox by passing it to :meth:`files_copy_reference_save`. :param str path: The path to the file or folder you want to get a copy reference to. :rtype: :class:`dropbox.files.GetCopyReferenceResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.GetCopyReferenceError` """ arg = files.GetCopyReferenceArg(path) r = self.request( files.copy_reference_get, 'files', arg, None, ) return r def files_copy_reference_save(self, copy_reference, path): """ Save a copy reference returned by :meth:`files_copy_reference_get` to the user's Dropbox. :param str copy_reference: A copy reference returned by :meth:`files_copy_reference_get`. :param str path: Path in the user's Dropbox that is the destination. :rtype: :class:`dropbox.files.SaveCopyReferenceResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.SaveCopyReferenceError` """ arg = files.SaveCopyReferenceArg(copy_reference, path) r = self.request( files.copy_reference_save, 'files', arg, None, ) return r def files_copy_v2(self, from_path, to_path, allow_shared_folder=False, autorename=False, allow_ownership_transfer=False): """ Copy a file or folder to a different location in the user's Dropbox. If the source path is a folder all its contents will be copied. :param bool allow_shared_folder: If true, :meth:`files_copy` will copy contents in shared folder, otherwise ``RelocationError.cant_copy_shared_folder`` will be returned if ``from_path`` contains shared folder. This field is always true for :meth:`files_move`. :param bool autorename: If there's a conflict, have the Dropbox server try to autorename the file to avoid the conflict. :param bool allow_ownership_transfer: Allow moves by owner even if it would result in an ownership transfer for the content being moved. This does not apply to copies. :rtype: :class:`dropbox.files.RelocationResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.RelocationError` """ arg = files.RelocationArg(from_path, to_path, allow_shared_folder, autorename, allow_ownership_transfer) r = self.request( files.copy_v2, 'files', arg, None, ) return r def files_create_folder(self, path, autorename=False): """ Create a folder at a given path. :param str path: Path in the user's Dropbox to create. :param bool autorename: If there's a conflict, have the Dropbox server try to autorename the folder to avoid the conflict. :rtype: :class:`dropbox.files.FolderMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.CreateFolderError` """ warnings.warn( 'create_folder is deprecated. Use create_folder_v2.', DeprecationWarning, ) arg = files.CreateFolderArg(path, autorename) r = self.request( files.create_folder, 'files', arg, None, ) return r def files_create_folder_v2(self, path, autorename=False): """ Create a folder at a given path. :param str path: Path in the user's Dropbox to create. :param bool autorename: If there's a conflict, have the Dropbox server try to autorename the folder to avoid the conflict. :rtype: :class:`dropbox.files.CreateFolderResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.CreateFolderError` """ arg = files.CreateFolderArg(path, autorename) r = self.request( files.create_folder_v2, 'files', arg, None, ) return r def files_delete(self, path): """ Delete the file or folder at a given path. If the path is a folder, all its contents will be deleted too. A successful response indicates that the file or folder was deleted. The returned metadata will be the corresponding :class:`dropbox.files.FileMetadata` or :class:`dropbox.files.FolderMetadata` for the item at time of deletion, and not a :class:`dropbox.files.DeletedMetadata` object. :param str path: Path in the user's Dropbox to delete. :rtype: :class:`dropbox.files.Metadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.DeleteError` """ warnings.warn( 'delete is deprecated. Use delete_v2.', DeprecationWarning, ) arg = files.DeleteArg(path) r = self.request( files.delete, 'files', arg, None, ) return r def files_delete_batch(self, entries): """ Delete multiple files/folders at once. This route is asynchronous, which returns a job ID immediately and runs the delete batch asynchronously. Use :meth:`files_delete_batch_check` to check the job status. :type entries: list :rtype: :class:`dropbox.files.DeleteBatchLaunch` """ arg = files.DeleteBatchArg(entries) r = self.request( files.delete_batch, 'files', arg, None, ) return r def files_delete_batch_check(self, async_job_id): """ Returns the status of an asynchronous job for :meth:`files_delete_batch`. If success, it returns list of result for each entry. :param str async_job_id: Id of the asynchronous job. This is the value of a response returned from the method that launched the job. :rtype: :class:`dropbox.files.DeleteBatchJobStatus` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.PollError` """ arg = async.PollArg(async_job_id) r = self.request( files.delete_batch_check, 'files', arg, None, ) return r def files_delete_v2(self, path): """ Delete the file or folder at a given path. If the path is a folder, all its contents will be deleted too. A successful response indicates that the file or folder was deleted. The returned metadata will be the corresponding :class:`dropbox.files.FileMetadata` or :class:`dropbox.files.FolderMetadata` for the item at time of deletion, and not a :class:`dropbox.files.DeletedMetadata` object. :param str path: Path in the user's Dropbox to delete. :rtype: :class:`dropbox.files.DeleteResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.DeleteError` """ arg = files.DeleteArg(path) r = self.request( files.delete_v2, 'files', arg, None, ) return r def files_download(self, path, rev=None): """ Download a file from a user's Dropbox. :param str path: The path of the file to download. :param Nullable rev: Please specify revision in ``path`` instead. :rtype: (:class:`dropbox.files.FileMetadata`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.DownloadError` If you do not consume the entire response body, then you must call close on the response object, otherwise you will max out your available connections. We recommend using the `contextlib.closing <https://docs.python.org/2/library/contextlib.html#contextlib.closing>`_ context manager to ensure this. """ arg = files.DownloadArg(path, rev) r = self.request( files.download, 'files', arg, None, ) return r def files_download_to_file(self, download_path, path, rev=None): """ Download a file from a user's Dropbox. :param str download_path: Path on local machine to save file. :param str path: The path of the file to download. :param Nullable rev: Please specify revision in ``path`` instead. :rtype: (:class:`dropbox.files.FileMetadata`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.DownloadError` """ arg = files.DownloadArg(path, rev) r = self.request( files.download, 'files', arg, None, ) self._save_body_to_file(download_path, r[1]) return r[0] def files_get_metadata(self, path, include_media_info=False, include_deleted=False, include_has_explicit_shared_members=False, include_property_groups=None): """ Returns the metadata for a file or folder. Note: Metadata for the root folder is unsupported. :param str path: The path of a file or folder on Dropbox. :param bool include_media_info: If true, ``FileMetadata.media_info`` is set for photo and video. :param bool include_deleted: If true, :class:`dropbox.files.DeletedMetadata` will be returned for deleted file or folder, otherwise ``LookupError.not_found`` will be returned. :param bool include_has_explicit_shared_members: If true, the results will include a flag for each file indicating whether or not that file has any explicit members. :param Nullable include_property_groups: If set to a valid list of template IDs, ``FileMetadata.property_groups`` is set if there exists property data associated with the file and each of the listed templates. :rtype: :class:`dropbox.files.Metadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.GetMetadataError` """ arg = files.GetMetadataArg(path, include_media_info, include_deleted, include_has_explicit_shared_members, include_property_groups) r = self.request( files.get_metadata, 'files', arg, None, ) return r def files_get_preview(self, path, rev=None): """ Get a preview for a file. Currently, PDF previews are generated for files with the following extensions: .ai, .doc, .docm, .docx, .eps, .odp, .odt, .pps, .ppsm, .ppsx, .ppt, .pptm, .pptx, .rtf. HTML previews are generated for files with the following extensions: .csv, .ods, .xls, .xlsm, .xlsx. Other formats will return an unsupported extension error. :param str path: The path of the file to preview. :param Nullable rev: Please specify revision in ``path`` instead. :rtype: (:class:`dropbox.files.FileMetadata`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.PreviewError` If you do not consume the entire response body, then you must call close on the response object, otherwise you will max out your available connections. We recommend using the `contextlib.closing <https://docs.python.org/2/library/contextlib.html#contextlib.closing>`_ context manager to ensure this. """ arg = files.PreviewArg(path, rev) r = self.request( files.get_preview, 'files', arg, None, ) return r def files_get_preview_to_file(self, download_path, path, rev=None): """ Get a preview for a file. Currently, PDF previews are generated for files with the following extensions: .ai, .doc, .docm, .docx, .eps, .odp, .odt, .pps, .ppsm, .ppsx, .ppt, .pptm, .pptx, .rtf. HTML previews are generated for files with the following extensions: .csv, .ods, .xls, .xlsm, .xlsx. Other formats will return an unsupported extension error. :param str download_path: Path on local machine to save file. :param str path: The path of the file to preview. :param Nullable rev: Please specify revision in ``path`` instead. :rtype: (:class:`dropbox.files.FileMetadata`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.PreviewError` """ arg = files.PreviewArg(path, rev) r = self.request( files.get_preview, 'files', arg, None, ) self._save_body_to_file(download_path, r[1]) return r[0] def files_get_temporary_link(self, path): """ Get a temporary link to stream content of a file. This link will expire in four hours and afterwards you will get 410 Gone. Content-Type of the link is determined automatically by the file's mime type. :param str path: The path to the file you want a temporary link to. :rtype: :class:`dropbox.files.GetTemporaryLinkResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.GetTemporaryLinkError` """ arg = files.GetTemporaryLinkArg(path) r = self.request( files.get_temporary_link, 'files', arg, None, ) return r def files_get_thumbnail(self, path, format=files.ThumbnailFormat.jpeg, size=files.ThumbnailSize.w64h64): """ Get a thumbnail for an image. This method currently supports files with the following file extensions: jpg, jpeg, png, tiff, tif, gif and bmp. Photos that are larger than 20MB in size won't be converted to a thumbnail. :param str path: The path to the image file you want to thumbnail. :param format: The format for the thumbnail image, jpeg (default) or png. For images that are photos, jpeg should be preferred, while png is better for screenshots and digital arts. :type format: :class:`dropbox.files.ThumbnailFormat` :param size: The size for the thumbnail image. :type size: :class:`dropbox.files.ThumbnailSize` :rtype: (:class:`dropbox.files.FileMetadata`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.ThumbnailError` If you do not consume the entire response body, then you must call close on the response object, otherwise you will max out your available connections. We recommend using the `contextlib.closing <https://docs.python.org/2/library/contextlib.html#contextlib.closing>`_ context manager to ensure this. """ arg = files.ThumbnailArg(path, format, size) r = self.request( files.get_thumbnail, 'files', arg, None, ) return r def files_get_thumbnail_to_file(self, download_path, path, format=files.ThumbnailFormat.jpeg, size=files.ThumbnailSize.w64h64): """ Get a thumbnail for an image. This method currently supports files with the following file extensions: jpg, jpeg, png, tiff, tif, gif and bmp. Photos that are larger than 20MB in size won't be converted to a thumbnail. :param str download_path: Path on local machine to save file. :param str path: The path to the image file you want to thumbnail. :param format: The format for the thumbnail image, jpeg (default) or png. For images that are photos, jpeg should be preferred, while png is better for screenshots and digital arts. :type format: :class:`dropbox.files.ThumbnailFormat` :param size: The size for the thumbnail image. :type size: :class:`dropbox.files.ThumbnailSize` :rtype: (:class:`dropbox.files.FileMetadata`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.ThumbnailError` """ arg = files.ThumbnailArg(path, format, size) r = self.request( files.get_thumbnail, 'files', arg, None, ) self._save_body_to_file(download_path, r[1]) return r[0] def files_get_thumbnail_batch(self, entries): """ Get thumbnails for a list of images. We allow up to 25 thumbnails in a single batch. This method currently supports files with the following file extensions: jpg, jpeg, png, tiff, tif, gif and bmp. Photos that are larger than 20MB in size won't be converted to a thumbnail. :param list entries: List of files to get thumbnails. :rtype: :class:`dropbox.files.GetThumbnailBatchResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.GetThumbnailBatchError` """ arg = files.GetThumbnailBatchArg(entries) r = self.request( files.get_thumbnail_batch, 'files', arg, None, ) return r def files_list_folder(self, path, recursive=False, include_media_info=False, include_deleted=False, include_has_explicit_shared_members=False, include_mounted_folders=True, limit=None, shared_link=None, include_property_groups=None): """ Starts returning the contents of a folder. If the result's ``ListFolderResult.has_more`` field is ``True``, call :meth:`files_list_folder_continue` with the returned ``ListFolderResult.cursor`` to retrieve more entries. If you're using ``ListFolderArg.recursive`` set to ``True`` to keep a local cache of the contents of a Dropbox account, iterate through each entry in order and process them as follows to keep your local state in sync: For each :class:`dropbox.files.FileMetadata`, store the new entry at the given path in your local state. If the required parent folders don't exist yet, create them. If there's already something else at the given path, replace it and remove all its children. For each :class:`dropbox.files.FolderMetadata`, store the new entry at the given path in your local state. If the required parent folders don't exist yet, create them. If there's already something else at the given path, replace it but leave the children as they are. Check the new entry's ``FolderSharingInfo.read_only`` and set all its children's read-only statuses to match. For each :class:`dropbox.files.DeletedMetadata`, if your local state has something at the given path, remove it and all its children. If there's nothing at the given path, ignore this entry. Note: :class:`dropbox.auth.RateLimitError` may be returned if multiple :meth:`files_list_folder` or :meth:`files_list_folder_continue` calls with same parameters are made simultaneously by same API app for same user. If your app implements retry logic, please hold off the retry until the previous request finishes. :param str path: A unique identifier for the file. :param bool recursive: If true, the list folder operation will be applied recursively to all subfolders and the response will contain contents of all subfolders. :param bool include_media_info: If true, ``FileMetadata.media_info`` is set for photo and video. :param bool include_deleted: If true, the results will include entries for files and folders that used to exist but were deleted. :param bool include_has_explicit_shared_members: If true, the results will include a flag for each file indicating whether or not that file has any explicit members. :param bool include_mounted_folders: If true, the results will include entries under mounted folders which includes app folder, shared folder and team folder. :param Nullable limit: The maximum number of results to return per request. Note: This is an approximate number and there can be slightly more entries returned in some cases. :param Nullable shared_link: A shared link to list the contents of. If the link is password-protected, the password must be provided. If this field is present, ``ListFolderArg.path`` will be relative to root of the shared link. Only non-recursive mode is supported for shared link. :param Nullable include_property_groups: If set to a valid list of template IDs, ``FileMetadata.property_groups`` is set if there exists property data associated with the file and each of the listed templates. :rtype: :class:`dropbox.files.ListFolderResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.ListFolderError` """ arg = files.ListFolderArg(path, recursive, include_media_info, include_deleted, include_has_explicit_shared_members, include_mounted_folders, limit, shared_link, include_property_groups) r = self.request( files.list_folder, 'files', arg, None, ) return r def files_list_folder_continue(self, cursor): """ Once a cursor has been retrieved from :meth:`files_list_folder`, use this to paginate through all files and retrieve updates to the folder, following the same rules as documented for :meth:`files_list_folder`. :param str cursor: The cursor returned by your last call to :meth:`files_list_folder` or :meth:`files_list_folder_continue`. :rtype: :class:`dropbox.files.ListFolderResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.ListFolderContinueError` """ arg = files.ListFolderContinueArg(cursor) r = self.request( files.list_folder_continue, 'files', arg, None, ) return r def files_list_folder_get_latest_cursor(self, path, recursive=False, include_media_info=False, include_deleted=False, include_has_explicit_shared_members=False, include_mounted_folders=True, limit=None, shared_link=None, include_property_groups=None): """ A way to quickly get a cursor for the folder's state. Unlike :meth:`files_list_folder`, :meth:`files_list_folder_get_latest_cursor` doesn't return any entries. This endpoint is for app which only needs to know about new files and modifications and doesn't need to know about files that already exist in Dropbox. :param str path: A unique identifier for the file. :param bool recursive: If true, the list folder operation will be applied recursively to all subfolders and the response will contain contents of all subfolders. :param bool include_media_info: If true, ``FileMetadata.media_info`` is set for photo and video. :param bool include_deleted: If true, the results will include entries for files and folders that used to exist but were deleted. :param bool include_has_explicit_shared_members: If true, the results will include a flag for each file indicating whether or not that file has any explicit members. :param bool include_mounted_folders: If true, the results will include entries under mounted folders which includes app folder, shared folder and team folder. :param Nullable limit: The maximum number of results to return per request. Note: This is an approximate number and there can be slightly more entries returned in some cases. :param Nullable shared_link: A shared link to list the contents of. If the link is password-protected, the password must be provided. If this field is present, ``ListFolderArg.path`` will be relative to root of the shared link. Only non-recursive mode is supported for shared link. :param Nullable include_property_groups: If set to a valid list of template IDs, ``FileMetadata.property_groups`` is set if there exists property data associated with the file and each of the listed templates. :rtype: :class:`dropbox.files.ListFolderGetLatestCursorResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.ListFolderError` """ arg = files.ListFolderArg(path, recursive, include_media_info, include_deleted, include_has_explicit_shared_members, include_mounted_folders, limit, shared_link, include_property_groups) r = self.request( files.list_folder_get_latest_cursor, 'files', arg, None, ) return r def files_list_folder_longpoll(self, cursor, timeout=30): """ A longpoll endpoint to wait for changes on an account. In conjunction with :meth:`files_list_folder_continue`, this call gives you a low-latency way to monitor an account for file changes. The connection will block until there are changes available or a timeout occurs. This endpoint is useful mostly for client-side apps. If you're looking for server-side notifications, check out our `webhooks documentation <https://www.dropbox.com/developers/reference/webhooks>`_. :param str cursor: A cursor as returned by :meth:`files_list_folder` or :meth:`files_list_folder_continue`. Cursors retrieved by setting ``ListFolderArg.include_media_info`` to ``True`` are not supported. :param long timeout: A timeout in seconds. The request will block for at most this length of time, plus up to 90 seconds of random jitter added to avoid the thundering herd problem. Care should be taken when using this parameter, as some network infrastructure does not support long timeouts. :rtype: :class:`dropbox.files.ListFolderLongpollResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.ListFolderLongpollError` """ arg = files.ListFolderLongpollArg(cursor, timeout) r = self.request( files.list_folder_longpoll, 'files', arg, None, ) return r def files_list_revisions(self, path, mode=files.ListRevisionsMode.path, limit=10): """ Returns revisions for files based on a file path or a file id. The file path or file id is identified from the latest file entry at the given file path or id. This end point allows your app to query either by file path or file id by setting the mode parameter appropriately. In the ``ListRevisionsMode.path`` (default) mode, all revisions at the same file path as the latest file entry are returned. If revisions with the same file id are desired, then mode must be set to ``ListRevisionsMode.id``. The ``ListRevisionsMode.id`` mode is useful to retrieve revisions for a given file across moves or renames. :param str path: The path to the file you want to see the revisions of. :param mode: Determines the behavior of the API in listing the revisions for a given file path or id. :type mode: :class:`dropbox.files.ListRevisionsMode` :param long limit: The maximum number of revision entries returned. :rtype: :class:`dropbox.files.ListRevisionsResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.ListRevisionsError` """ arg = files.ListRevisionsArg(path, mode, limit) r = self.request( files.list_revisions, 'files', arg, None, ) return r def files_move(self, from_path, to_path, allow_shared_folder=False, autorename=False, allow_ownership_transfer=False): """ Move a file or folder to a different location in the user's Dropbox. If the source path is a folder all its contents will be moved. :param bool allow_shared_folder: If true, :meth:`files_copy` will copy contents in shared folder, otherwise ``RelocationError.cant_copy_shared_folder`` will be returned if ``from_path`` contains shared folder. This field is always true for :meth:`files_move`. :param bool autorename: If there's a conflict, have the Dropbox server try to autorename the file to avoid the conflict. :param bool allow_ownership_transfer: Allow moves by owner even if it would result in an ownership transfer for the content being moved. This does not apply to copies. :rtype: :class:`dropbox.files.Metadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.RelocationError` """ warnings.warn( 'move is deprecated. Use move_v2.', DeprecationWarning, ) arg = files.RelocationArg(from_path, to_path, allow_shared_folder, autorename, allow_ownership_transfer) r = self.request( files.move, 'files', arg, None, ) return r def files_move_batch(self, entries, allow_shared_folder=False, autorename=False, allow_ownership_transfer=False): """ Move multiple files or folders to different locations at once in the user's Dropbox. This route is 'all or nothing', which means if one entry fails, the whole transaction will abort. This route will return job ID immediately and do the async moving job in background. Please use :meth:`files_move_batch_check` to check the job status. :param list entries: List of entries to be moved or copied. Each entry is :class:`dropbox.files.RelocationPath`. :param bool allow_shared_folder: If true, :meth:`files_copy_batch` will copy contents in shared folder, otherwise ``RelocationError.cant_copy_shared_folder`` will be returned if ``RelocationPath.from_path`` contains shared folder. This field is always true for :meth:`files_move_batch`. :param bool autorename: If there's a conflict with any file, have the Dropbox server try to autorename that file to avoid the conflict. :param bool allow_ownership_transfer: Allow moves by owner even if it would result in an ownership transfer for the content being moved. This does not apply to copies. :rtype: :class:`dropbox.files.RelocationBatchLaunch` """ arg = files.RelocationBatchArg(entries, allow_shared_folder, autorename, allow_ownership_transfer) r = self.request( files.move_batch, 'files', arg, None, ) return r def files_move_batch_check(self, async_job_id): """ Returns the status of an asynchronous job for :meth:`files_move_batch`. If success, it returns list of results for each entry. :param str async_job_id: Id of the asynchronous job. This is the value of a response returned from the method that launched the job. :rtype: :class:`dropbox.files.RelocationBatchJobStatus` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.PollError` """ arg = async.PollArg(async_job_id) r = self.request( files.move_batch_check, 'files', arg, None, ) return r def files_move_v2(self, from_path, to_path, allow_shared_folder=False, autorename=False, allow_ownership_transfer=False): """ Move a file or folder to a different location in the user's Dropbox. If the source path is a folder all its contents will be moved. :param bool allow_shared_folder: If true, :meth:`files_copy` will copy contents in shared folder, otherwise ``RelocationError.cant_copy_shared_folder`` will be returned if ``from_path`` contains shared folder. This field is always true for :meth:`files_move`. :param bool autorename: If there's a conflict, have the Dropbox server try to autorename the file to avoid the conflict. :param bool allow_ownership_transfer: Allow moves by owner even if it would result in an ownership transfer for the content being moved. This does not apply to copies. :rtype: :class:`dropbox.files.RelocationResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.RelocationError` """ arg = files.RelocationArg(from_path, to_path, allow_shared_folder, autorename, allow_ownership_transfer) r = self.request( files.move_v2, 'files', arg, None, ) return r def files_permanently_delete(self, path): """ Permanently delete the file or folder at a given path (see https://www.dropbox.com/en/help/40). Note: This endpoint is only available for Dropbox Business apps. :param str path: Path in the user's Dropbox to delete. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.DeleteError` """ arg = files.DeleteArg(path) r = self.request( files.permanently_delete, 'files', arg, None, ) return None def files_properties_add(self, path, property_groups): """ :param str path: A unique identifier for the file or folder. :param list property_groups: The property groups which are to be added to a Dropbox file. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.AddPropertiesError` """ warnings.warn( 'properties/add is deprecated.', DeprecationWarning, ) arg = file_properties.AddPropertiesArg(path, property_groups) r = self.request( files.properties_add, 'files', arg, None, ) return None def files_properties_overwrite(self, path, property_groups): """ :param str path: A unique identifier for the file or folder. :param list property_groups: The property groups "snapshot" updates to force apply. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.InvalidPropertyGroupError` """ warnings.warn( 'properties/overwrite is deprecated.', DeprecationWarning, ) arg = file_properties.OverwritePropertyGroupArg(path, property_groups) r = self.request( files.properties_overwrite, 'files', arg, None, ) return None def files_properties_remove(self, path, property_template_ids): """ :param str path: A unique identifier for the file or folder. :param list property_template_ids: A list of identifiers for a template created by :meth:`files_templates_add_for_user` or :meth:`files_templates_add_for_team`. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.RemovePropertiesError` """ warnings.warn( 'properties/remove is deprecated.', DeprecationWarning, ) arg = file_properties.RemovePropertiesArg(path, property_template_ids) r = self.request( files.properties_remove, 'files', arg, None, ) return None def files_properties_template_get(self, template_id): """ :param str template_id: An identifier for template added by route See :meth:`files_templates_add_for_user` or :meth:`files_templates_add_for_team`. :rtype: :class:`dropbox.files.GetTemplateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.TemplateError` """ warnings.warn( 'properties/template/get is deprecated.', DeprecationWarning, ) arg = file_properties.GetTemplateArg(template_id) r = self.request( files.properties_template_get, 'files', arg, None, ) return r def files_properties_template_list(self): warnings.warn( 'properties/template/list is deprecated.', DeprecationWarning, ) arg = None r = self.request( files.properties_template_list, 'files', arg, None, ) return r def files_properties_update(self, path, update_property_groups): """ :param str path: A unique identifier for the file or folder. :param list update_property_groups: The property groups "delta" updates to apply. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.UpdatePropertiesError` """ warnings.warn( 'properties/update is deprecated.', DeprecationWarning, ) arg = file_properties.UpdatePropertiesArg(path, update_property_groups) r = self.request( files.properties_update, 'files', arg, None, ) return None def files_restore(self, path, rev): """ Restore a file to a specific revision. :param str path: The path to the file you want to restore. :param str rev: The revision to restore for the file. :rtype: :class:`dropbox.files.FileMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.RestoreError` """ arg = files.RestoreArg(path, rev) r = self.request( files.restore, 'files', arg, None, ) return r def files_save_url(self, path, url): """ Save a specified URL into a file in user's Dropbox. If the given path already exists, the file will be renamed to avoid the conflict (e.g. myfile (1).txt). :param str path: The path in Dropbox where the URL will be saved to. :param str url: The URL to be saved. :rtype: :class:`dropbox.files.SaveUrlResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.SaveUrlError` """ arg = files.SaveUrlArg(path, url) r = self.request( files.save_url, 'files', arg, None, ) return r def files_save_url_check_job_status(self, async_job_id): """ Check the status of a :meth:`files_save_url` job. :param str async_job_id: Id of the asynchronous job. This is the value of a response returned from the method that launched the job. :rtype: :class:`dropbox.files.SaveUrlJobStatus` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.PollError` """ arg = async.PollArg(async_job_id) r = self.request( files.save_url_check_job_status, 'files', arg, None, ) return r def files_search(self, path, query, start=0, max_results=100, mode=files.SearchMode.filename): """ Searches for files and folders. Note: Recent changes may not immediately be reflected in search results due to a short delay in indexing. :param str path: The path in the user's Dropbox to search. Should probably be a folder. :param str query: The string to search for. The search string is split on spaces into multiple tokens. For file name searching, the last token is used for prefix matching (i.e. "bat c" matches "bat cave" but not "batman car"). :param long start: The starting index within the search results (used for paging). :param long max_results: The maximum number of search results to return. :param mode: The search mode (filename, filename_and_content, or deleted_filename). Note that searching file content is only available for Dropbox Business accounts. :type mode: :class:`dropbox.files.SearchMode` :rtype: :class:`dropbox.files.SearchResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.SearchError` """ arg = files.SearchArg(path, query, start, max_results, mode) r = self.request( files.search, 'files', arg, None, ) return r def files_upload(self, f, path, mode=files.WriteMode.add, autorename=False, client_modified=None, mute=False, property_groups=None): """ Create a new file with the contents provided in the request. Do not use this to upload a file larger than 150 MB. Instead, create an upload session with :meth:`files_upload_session_start`. :param bytes f: Contents to upload. :param str path: Path in the user's Dropbox to save the file. :param mode: Selects what to do if the file already exists. :type mode: :class:`dropbox.files.WriteMode` :param bool autorename: If there's a conflict, as determined by ``mode``, have the Dropbox server try to autorename the file to avoid conflict. :param Nullable client_modified: The value to store as the ``client_modified`` timestamp. Dropbox automatically records the time at which the file was written to the Dropbox servers. It can also record an additional timestamp, provided by Dropbox desktop clients, mobile clients, and API apps of when the file was actually created or modified. :param bool mute: Normally, users are made aware of any file modifications in their Dropbox account via notifications in the client software. If ``True``, this tells the clients that this modification shouldn't result in a user notification. :param Nullable property_groups: List of custom properties to add to file. :rtype: :class:`dropbox.files.FileMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.UploadError` """ arg = files.CommitInfo(path, mode, autorename, client_modified, mute, property_groups) r = self.request( files.upload, 'files', arg, f, ) return r def files_upload_session_append(self, f, session_id, offset): """ Append more data to an upload session. A single request should not upload more than 150 MB. :param bytes f: Contents to upload. :param str session_id: The upload session ID (returned by :meth:`files_upload_session_start`). :param long offset: The amount of data that has been uploaded so far. We use this to make sure upload data isn't lost or duplicated in the event of a network error. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.UploadSessionLookupError` """ warnings.warn( 'upload_session/append is deprecated. Use upload_session/append_v2.', DeprecationWarning, ) arg = files.UploadSessionCursor(session_id, offset) r = self.request( files.upload_session_append, 'files', arg, f, ) return None def files_upload_session_append_v2(self, f, cursor, close=False): """ Append more data to an upload session. When the parameter close is set, this call will close the session. A single request should not upload more than 150 MB. :param bytes f: Contents to upload. :param cursor: Contains the upload session ID and the offset. :type cursor: :class:`dropbox.files.UploadSessionCursor` :param bool close: If true, the current session will be closed, at which point you won't be able to call :meth:`files_upload_session_append_v2` anymore with the current session. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.UploadSessionLookupError` """ arg = files.UploadSessionAppendArg(cursor, close) r = self.request( files.upload_session_append_v2, 'files', arg, f, ) return None def files_upload_session_finish(self, f, cursor, commit): """ Finish an upload session and save the uploaded data to the given file path. A single request should not upload more than 150 MB. :param bytes f: Contents to upload. :param cursor: Contains the upload session ID and the offset. :type cursor: :class:`dropbox.files.UploadSessionCursor` :param commit: Contains the path and other optional modifiers for the commit. :type commit: :class:`dropbox.files.CommitInfo` :rtype: :class:`dropbox.files.FileMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.UploadSessionFinishError` """ arg = files.UploadSessionFinishArg(cursor, commit) r = self.request( files.upload_session_finish, 'files', arg, f, ) return r def files_upload_session_finish_batch(self, entries): """ This route helps you commit many files at once into a user's Dropbox. Use :meth:`files_upload_session_start` and :meth:`files_upload_session_append_v2` to upload file contents. We recommend uploading many files in parallel to increase throughput. Once the file contents have been uploaded, rather than calling :meth:`files_upload_session_finish`, use this route to finish all your upload sessions in a single request. ``UploadSessionStartArg.close`` or ``UploadSessionAppendArg.close`` needs to be true for the last :meth:`files_upload_session_start` or :meth:`files_upload_session_append_v2` call. This route will return a job_id immediately and do the async commit job in background. Use :meth:`files_upload_session_finish_batch_check` to check the job status. For the same account, this route should be executed serially. That means you should not start the next job before current job finishes. We allow up to 1000 entries in a single request. :param list entries: Commit information for each file in the batch. :rtype: :class:`dropbox.files.UploadSessionFinishBatchLaunch` """ arg = files.UploadSessionFinishBatchArg(entries) r = self.request( files.upload_session_finish_batch, 'files', arg, None, ) return r def files_upload_session_finish_batch_check(self, async_job_id): """ Returns the status of an asynchronous job for :meth:`files_upload_session_finish_batch`. If success, it returns list of result for each entry. :param str async_job_id: Id of the asynchronous job. This is the value of a response returned from the method that launched the job. :rtype: :class:`dropbox.files.UploadSessionFinishBatchJobStatus` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.files.PollError` """ arg = async.PollArg(async_job_id) r = self.request( files.upload_session_finish_batch_check, 'files', arg, None, ) return r def files_upload_session_start(self, f, close=False): """ Upload sessions allow you to upload a single file in one or more requests, for example where the size of the file is greater than 150 MB. This call starts a new upload session with the given data. You can then use :meth:`files_upload_session_append_v2` to add more data and :meth:`files_upload_session_finish` to save all the data to a file in Dropbox. A single request should not upload more than 150 MB. An upload session can be used for a maximum of 48 hours. Attempting to use an ``UploadSessionStartResult.session_id`` with :meth:`files_upload_session_append_v2` or :meth:`files_upload_session_finish` more than 48 hours after its creation will return a ``UploadSessionLookupError.not_found``. :param bytes f: Contents to upload. :param bool close: If true, the current session will be closed, at which point you won't be able to call :meth:`files_upload_session_append_v2` anymore with the current session. :rtype: :class:`dropbox.files.UploadSessionStartResult` """ arg = files.UploadSessionStartArg(close) r = self.request( files.upload_session_start, 'files', arg, f, ) return r # ------------------------------------------ # Routes in paper namespace def paper_docs_archive(self, doc_id): """ Marks the given Paper doc as archived. Note: This action can be performed or undone by anyone with edit permissions to the doc. :param str doc_id: The Paper doc ID. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.RefPaperDoc(doc_id) r = self.request( paper.docs_archive, 'paper', arg, None, ) return None def paper_docs_create(self, f, import_format, parent_folder_id=None): """ Creates a new Paper doc with the provided content. :param bytes f: Contents to upload. :param Nullable parent_folder_id: The Paper folder ID where the Paper document should be created. The API user has to have write access to this folder or error is thrown. :param import_format: The format of provided data. :type import_format: :class:`dropbox.paper.ImportFormat` :rtype: :class:`dropbox.paper.PaperDocCreateUpdateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.PaperDocCreateError` """ arg = paper.PaperDocCreateArgs(import_format, parent_folder_id) r = self.request( paper.docs_create, 'paper', arg, f, ) return r def paper_docs_download(self, doc_id, export_format): """ Exports and downloads Paper doc either as HTML or markdown. :type export_format: :class:`dropbox.paper.ExportFormat` :rtype: (:class:`dropbox.paper.PaperDocExportResult`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` If you do not consume the entire response body, then you must call close on the response object, otherwise you will max out your available connections. We recommend using the `contextlib.closing <https://docs.python.org/2/library/contextlib.html#contextlib.closing>`_ context manager to ensure this. """ arg = paper.PaperDocExport(doc_id, export_format) r = self.request( paper.docs_download, 'paper', arg, None, ) return r def paper_docs_download_to_file(self, download_path, doc_id, export_format): """ Exports and downloads Paper doc either as HTML or markdown. :param str download_path: Path on local machine to save file. :type export_format: :class:`dropbox.paper.ExportFormat` :rtype: (:class:`dropbox.paper.PaperDocExportResult`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.PaperDocExport(doc_id, export_format) r = self.request( paper.docs_download, 'paper', arg, None, ) self._save_body_to_file(download_path, r[1]) return r[0] def paper_docs_folder_users_list(self, doc_id, limit=1000): """ Lists the users who are explicitly invited to the Paper folder in which the Paper doc is contained. For private folders all users (including owner) shared on the folder are listed and for team folders all non-team users shared on the folder are returned. :param int limit: Size limit per batch. The maximum number of users that can be retrieved per batch is 1000. Higher value results in invalid arguments error. :rtype: :class:`dropbox.paper.ListUsersOnFolderResponse` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.ListUsersOnFolderArgs(doc_id, limit) r = self.request( paper.docs_folder_users_list, 'paper', arg, None, ) return r def paper_docs_folder_users_list_continue(self, doc_id, cursor): """ Once a cursor has been retrieved from :meth:`paper_docs_folder_users_list`, use this to paginate through all users on the Paper folder. :param str cursor: The cursor obtained from :meth:`paper_docs_folder_users_list` or :meth:`paper_docs_folder_users_list_continue`. Allows for pagination. :rtype: :class:`dropbox.paper.ListUsersOnFolderResponse` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.ListUsersCursorError` """ arg = paper.ListUsersOnFolderContinueArgs(doc_id, cursor) r = self.request( paper.docs_folder_users_list_continue, 'paper', arg, None, ) return r def paper_docs_get_folder_info(self, doc_id): """ Retrieves folder information for the given Paper doc. This includes: - folder sharing policy; permissions for subfolders are set by the top-level folder. - full 'filepath', i.e. the list of folders (both folderId and folderName) from the root folder to the folder directly containing the Paper doc. Note: If the Paper doc is not in any folder (aka unfiled) the response will be empty. :param str doc_id: The Paper doc ID. :rtype: :class:`dropbox.paper.FoldersContainingPaperDoc` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.RefPaperDoc(doc_id) r = self.request( paper.docs_get_folder_info, 'paper', arg, None, ) return r def paper_docs_list(self, filter_by=paper.ListPaperDocsFilterBy.docs_accessed, sort_by=paper.ListPaperDocsSortBy.accessed, sort_order=paper.ListPaperDocsSortOrder.ascending, limit=1000): """ Return the list of all Paper docs according to the argument specifications. To iterate over through the full pagination, pass the cursor to :meth:`paper_docs_list_continue`. :param filter_by: Allows user to specify how the Paper docs should be filtered. :type filter_by: :class:`dropbox.paper.ListPaperDocsFilterBy` :param sort_by: Allows user to specify how the Paper docs should be sorted. :type sort_by: :class:`dropbox.paper.ListPaperDocsSortBy` :param sort_order: Allows user to specify the sort order of the result. :type sort_order: :class:`dropbox.paper.ListPaperDocsSortOrder` :param int limit: Size limit per batch. The maximum number of docs that can be retrieved per batch is 1000. Higher value results in invalid arguments error. :rtype: :class:`dropbox.paper.ListPaperDocsResponse` """ arg = paper.ListPaperDocsArgs(filter_by, sort_by, sort_order, limit) r = self.request( paper.docs_list, 'paper', arg, None, ) return r def paper_docs_list_continue(self, cursor): """ Once a cursor has been retrieved from :meth:`paper_docs_list`, use this to paginate through all Paper doc. :param str cursor: The cursor obtained from :meth:`paper_docs_list` or :meth:`paper_docs_list_continue`. Allows for pagination. :rtype: :class:`dropbox.paper.ListPaperDocsResponse` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.ListDocsCursorError` """ arg = paper.ListPaperDocsContinueArgs(cursor) r = self.request( paper.docs_list_continue, 'paper', arg, None, ) return r def paper_docs_permanently_delete(self, doc_id): """ Permanently deletes the given Paper doc. This operation is final as the doc cannot be recovered. Note: This action can be performed only by the doc owner. :param str doc_id: The Paper doc ID. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.RefPaperDoc(doc_id) r = self.request( paper.docs_permanently_delete, 'paper', arg, None, ) return None def paper_docs_sharing_policy_get(self, doc_id): """ Gets the default sharing policy for the given Paper doc. :param str doc_id: The Paper doc ID. :rtype: :class:`dropbox.paper.SharingPolicy` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.RefPaperDoc(doc_id) r = self.request( paper.docs_sharing_policy_get, 'paper', arg, None, ) return r def paper_docs_sharing_policy_set(self, doc_id, sharing_policy): """ Sets the default sharing policy for the given Paper doc. The default 'team_sharing_policy' can be changed only by teams, omit this field for personal accounts. Note: 'public_sharing_policy' cannot be set to the value 'disabled' because this setting can be changed only via the team admin console. :param sharing_policy: The default sharing policy to be set for the Paper doc. :type sharing_policy: :class:`dropbox.paper.SharingPolicy` :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.PaperDocSharingPolicy(doc_id, sharing_policy) r = self.request( paper.docs_sharing_policy_set, 'paper', arg, None, ) return None def paper_docs_update(self, f, doc_id, doc_update_policy, revision, import_format): """ Updates an existing Paper doc with the provided content. :param bytes f: Contents to upload. :param doc_update_policy: The policy used for the current update call. :type doc_update_policy: :class:`dropbox.paper.PaperDocUpdatePolicy` :param long revision: The latest doc revision. This value must match the head revision or an error code will be returned. This is to prevent colliding writes. :param import_format: The format of provided data. :type import_format: :class:`dropbox.paper.ImportFormat` :rtype: :class:`dropbox.paper.PaperDocCreateUpdateResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.PaperDocUpdateError` """ arg = paper.PaperDocUpdateArgs(doc_id, doc_update_policy, revision, import_format) r = self.request( paper.docs_update, 'paper', arg, f, ) return r def paper_docs_users_add(self, doc_id, members, custom_message=None, quiet=False): """ Allows an owner or editor to add users to a Paper doc or change their permissions using their email address or Dropbox account ID. Note: The Doc owner's permissions cannot be changed. :param list members: User which should be added to the Paper doc. Specify only email address or Dropbox account ID. :param Nullable custom_message: A personal message that will be emailed to each successfully added member. :param bool quiet: Clients should set this to true if no email message shall be sent to added users. :rtype: list :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.AddPaperDocUser(doc_id, members, custom_message, quiet) r = self.request( paper.docs_users_add, 'paper', arg, None, ) return r def paper_docs_users_list(self, doc_id, limit=1000, filter_by=paper.UserOnPaperDocFilter.shared): """ Lists all users who visited the Paper doc or users with explicit access. This call excludes users who have been removed. The list is sorted by the date of the visit or the share date. The list will include both users, the explicitly shared ones as well as those who came in using the Paper url link. :param int limit: Size limit per batch. The maximum number of users that can be retrieved per batch is 1000. Higher value results in invalid arguments error. :param filter_by: Specify this attribute if you want to obtain users that have already accessed the Paper doc. :type filter_by: :class:`dropbox.paper.UserOnPaperDocFilter` :rtype: :class:`dropbox.paper.ListUsersOnPaperDocResponse` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.ListUsersOnPaperDocArgs(doc_id, limit, filter_by) r = self.request( paper.docs_users_list, 'paper', arg, None, ) return r def paper_docs_users_list_continue(self, doc_id, cursor): """ Once a cursor has been retrieved from :meth:`paper_docs_users_list`, use this to paginate through all users on the Paper doc. :param str cursor: The cursor obtained from :meth:`paper_docs_users_list` or :meth:`paper_docs_users_list_continue`. Allows for pagination. :rtype: :class:`dropbox.paper.ListUsersOnPaperDocResponse` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.ListUsersCursorError` """ arg = paper.ListUsersOnPaperDocContinueArgs(doc_id, cursor) r = self.request( paper.docs_users_list_continue, 'paper', arg, None, ) return r def paper_docs_users_remove(self, doc_id, member): """ Allows an owner or editor to remove users from a Paper doc using their email address or Dropbox account ID. Note: Doc owner cannot be removed. :param member: User which should be removed from the Paper doc. Specify only email address or Dropbox account ID. :type member: :class:`dropbox.paper.MemberSelector` :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.paper.DocLookupError` """ arg = paper.RemovePaperDocUser(doc_id, member) r = self.request( paper.docs_users_remove, 'paper', arg, None, ) return None # ------------------------------------------ # Routes in sharing namespace def sharing_add_file_member(self, file, members, custom_message=None, quiet=False, access_level=sharing.AccessLevel.viewer, add_message_as_comment=False): """ Adds specified members to a file. :param str file: File to which to add members. :param list members: Members to add. Note that even an email address is given, this may result in a user being directy added to the membership if that email is the user's main account email. :param Nullable custom_message: Message to send to added members in their invitation. :param bool quiet: Whether added members should be notified via device notifications of their invitation. :param access_level: AccessLevel union object, describing what access level we want to give new members. :type access_level: :class:`dropbox.sharing.AccessLevel` :param bool add_message_as_comment: If the custom message should be added as a comment on the file. :rtype: list :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.AddFileMemberError` """ arg = sharing.AddFileMemberArgs(file, members, custom_message, quiet, access_level, add_message_as_comment) r = self.request( sharing.add_file_member, 'sharing', arg, None, ) return r def sharing_add_folder_member(self, shared_folder_id, members, quiet=False, custom_message=None): """ Allows an owner or editor (if the ACL update policy allows) of a shared folder to add another member. For the new member to get access to all the functionality for this folder, you will need to call :meth:`sharing_mount_folder` on their behalf. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :param list members: The intended list of members to add. Added members will receive invites to join the shared folder. :param bool quiet: Whether added members should be notified via email and device notifications of their invite. :param Nullable custom_message: Optional message to display to added members in their invitation. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.AddFolderMemberError` """ arg = sharing.AddFolderMemberArg(shared_folder_id, members, quiet, custom_message) r = self.request( sharing.add_folder_member, 'sharing', arg, None, ) return None def sharing_change_file_member_access(self, file, member, access_level): """ Identical to update_file_member but with less information returned. :param str file: File for which we are changing a member's access. :param member: The member whose access we are changing. :type member: :class:`dropbox.sharing.MemberSelector` :param access_level: The new access level for the member. :type access_level: :class:`dropbox.sharing.AccessLevel` :rtype: :class:`dropbox.sharing.FileMemberActionResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.FileMemberActionError` """ warnings.warn( 'change_file_member_access is deprecated. Use update_file_member.', DeprecationWarning, ) arg = sharing.ChangeFileMemberAccessArgs(file, member, access_level) r = self.request( sharing.change_file_member_access, 'sharing', arg, None, ) return r def sharing_check_job_status(self, async_job_id): """ Returns the status of an asynchronous job. Apps must have full Dropbox access to use this endpoint. :param str async_job_id: Id of the asynchronous job. This is the value of a response returned from the method that launched the job. :rtype: :class:`dropbox.sharing.JobStatus` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.PollError` """ arg = async.PollArg(async_job_id) r = self.request( sharing.check_job_status, 'sharing', arg, None, ) return r def sharing_check_remove_member_job_status(self, async_job_id): """ Returns the status of an asynchronous job for sharing a folder. Apps must have full Dropbox access to use this endpoint. :param str async_job_id: Id of the asynchronous job. This is the value of a response returned from the method that launched the job. :rtype: :class:`dropbox.sharing.RemoveMemberJobStatus` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.PollError` """ arg = async.PollArg(async_job_id) r = self.request( sharing.check_remove_member_job_status, 'sharing', arg, None, ) return r def sharing_check_share_job_status(self, async_job_id): """ Returns the status of an asynchronous job for sharing a folder. Apps must have full Dropbox access to use this endpoint. :param str async_job_id: Id of the asynchronous job. This is the value of a response returned from the method that launched the job. :rtype: :class:`dropbox.sharing.ShareFolderJobStatus` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.PollError` """ arg = async.PollArg(async_job_id) r = self.request( sharing.check_share_job_status, 'sharing', arg, None, ) return r def sharing_create_shared_link(self, path, short_url=False, pending_upload=None): """ Create a shared link. If a shared link already exists for the given path, that link is returned. Note that in the returned :class:`dropbox.sharing.PathLinkMetadata`, the ``PathLinkMetadata.url`` field is the shortened URL if ``CreateSharedLinkArg.short_url`` argument is set to ``True``. Previously, it was technically possible to break a shared link by moving or renaming the corresponding file or folder. In the future, this will no longer be the case, so your app shouldn't rely on this behavior. Instead, if your app needs to revoke a shared link, use :meth:`sharing_revoke_shared_link`. :param str path: The path to share. :param bool short_url: Whether to return a shortened URL. :param Nullable pending_upload: If it's okay to share a path that does not yet exist, set this to either ``PendingUploadMode.file`` or ``PendingUploadMode.folder`` to indicate whether to assume it's a file or folder. :rtype: :class:`dropbox.sharing.PathLinkMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.CreateSharedLinkError` """ warnings.warn( 'create_shared_link is deprecated. Use create_shared_link_with_settings.', DeprecationWarning, ) arg = sharing.CreateSharedLinkArg(path, short_url, pending_upload) r = self.request( sharing.create_shared_link, 'sharing', arg, None, ) return r def sharing_create_shared_link_with_settings(self, path, settings=None): """ Create a shared link with custom settings. If no settings are given then the default visibility is ``RequestedVisibility.public`` (The resolved visibility, though, may depend on other aspects such as team and shared folder settings). :param str path: The path to be shared by the shared link. :param Nullable settings: The requested settings for the newly created shared link. :rtype: :class:`dropbox.sharing.SharedLinkMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.CreateSharedLinkWithSettingsError` """ arg = sharing.CreateSharedLinkWithSettingsArg(path, settings) r = self.request( sharing.create_shared_link_with_settings, 'sharing', arg, None, ) return r def sharing_get_file_metadata(self, file, actions=None): """ Returns shared file metadata. :param str file: The file to query. :param Nullable actions: A list of `FileAction`s corresponding to `FilePermission`s that should appear in the response's ``SharedFileMetadata.permissions`` field describing the actions the authenticated user can perform on the file. :rtype: :class:`dropbox.sharing.SharedFileMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.GetFileMetadataError` """ arg = sharing.GetFileMetadataArg(file, actions) r = self.request( sharing.get_file_metadata, 'sharing', arg, None, ) return r def sharing_get_file_metadata_batch(self, files, actions=None): """ Returns shared file metadata. :param list files: The files to query. :param Nullable actions: A list of `FileAction`s corresponding to `FilePermission`s that should appear in the response's ``SharedFileMetadata.permissions`` field describing the actions the authenticated user can perform on the file. :rtype: list :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.SharingUserError` """ arg = sharing.GetFileMetadataBatchArg(files, actions) r = self.request( sharing.get_file_metadata_batch, 'sharing', arg, None, ) return r def sharing_get_folder_metadata(self, shared_folder_id, actions=None): """ Returns shared folder metadata by its folder ID. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :param Nullable actions: A list of `FolderAction`s corresponding to `FolderPermission`s that should appear in the response's ``SharedFolderMetadata.permissions`` field describing the actions the authenticated user can perform on the folder. :rtype: :class:`dropbox.sharing.SharedFolderMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.SharedFolderAccessError` """ arg = sharing.GetMetadataArgs(shared_folder_id, actions) r = self.request( sharing.get_folder_metadata, 'sharing', arg, None, ) return r def sharing_get_shared_link_file(self, url, path=None, link_password=None): """ Download the shared link's file from a user's Dropbox. :param str url: URL of the shared link. :param Nullable path: If the shared link is to a folder, this parameter can be used to retrieve the metadata for a specific file or sub-folder in this folder. A relative path should be used. :param Nullable link_password: If the shared link has a password, this parameter can be used. :rtype: (:class:`dropbox.sharing.SharedLinkMetadata`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.GetSharedLinkFileError` If you do not consume the entire response body, then you must call close on the response object, otherwise you will max out your available connections. We recommend using the `contextlib.closing <https://docs.python.org/2/library/contextlib.html#contextlib.closing>`_ context manager to ensure this. """ arg = sharing.GetSharedLinkMetadataArg(url, path, link_password) r = self.request( sharing.get_shared_link_file, 'sharing', arg, None, ) return r def sharing_get_shared_link_file_to_file(self, download_path, url, path=None, link_password=None): """ Download the shared link's file from a user's Dropbox. :param str download_path: Path on local machine to save file. :param str url: URL of the shared link. :param Nullable path: If the shared link is to a folder, this parameter can be used to retrieve the metadata for a specific file or sub-folder in this folder. A relative path should be used. :param Nullable link_password: If the shared link has a password, this parameter can be used. :rtype: (:class:`dropbox.sharing.SharedLinkMetadata`, :class:`requests.models.Response`) :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.GetSharedLinkFileError` """ arg = sharing.GetSharedLinkMetadataArg(url, path, link_password) r = self.request( sharing.get_shared_link_file, 'sharing', arg, None, ) self._save_body_to_file(download_path, r[1]) return r[0] def sharing_get_shared_link_metadata(self, url, path=None, link_password=None): """ Get the shared link's metadata. :param str url: URL of the shared link. :param Nullable path: If the shared link is to a folder, this parameter can be used to retrieve the metadata for a specific file or sub-folder in this folder. A relative path should be used. :param Nullable link_password: If the shared link has a password, this parameter can be used. :rtype: :class:`dropbox.sharing.SharedLinkMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.SharedLinkError` """ arg = sharing.GetSharedLinkMetadataArg(url, path, link_password) r = self.request( sharing.get_shared_link_metadata, 'sharing', arg, None, ) return r def sharing_get_shared_links(self, path=None): """ Returns a list of :class:`dropbox.sharing.LinkMetadata` objects for this user, including collection links. If no path is given, returns a list of all shared links for the current user, including collection links, up to a maximum of 1000 links. If a non-empty path is given, returns a list of all shared links that allow access to the given path. Collection links are never returned in this case. Note that the url field in the response is never the shortened URL. :param Nullable path: See :meth:`sharing_get_shared_links` description. :rtype: :class:`dropbox.sharing.GetSharedLinksResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.GetSharedLinksError` """ warnings.warn( 'get_shared_links is deprecated. Use list_shared_links.', DeprecationWarning, ) arg = sharing.GetSharedLinksArg(path) r = self.request( sharing.get_shared_links, 'sharing', arg, None, ) return r def sharing_list_file_members(self, file, actions=None, include_inherited=True, limit=100): """ Use to obtain the members who have been invited to a file, both inherited and uninherited members. :param str file: The file for which you want to see members. :param Nullable actions: The actions for which to return permissions on a member. :param bool include_inherited: Whether to include members who only have access from a parent shared folder. :param long limit: Number of members to return max per query. Defaults to 100 if no limit is specified. :rtype: :class:`dropbox.sharing.SharedFileMembers` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.ListFileMembersError` """ arg = sharing.ListFileMembersArg(file, actions, include_inherited, limit) r = self.request( sharing.list_file_members, 'sharing', arg, None, ) return r def sharing_list_file_members_batch(self, files, limit=10): """ Get members of multiple files at once. The arguments to this route are more limited, and the limit on query result size per file is more strict. To customize the results more, use the individual file endpoint. Inherited users and groups are not included in the result, and permissions are not returned for this endpoint. :param list files: Files for which to return members. :param long limit: Number of members to return max per query. Defaults to 10 if no limit is specified. :rtype: list :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.SharingUserError` """ arg = sharing.ListFileMembersBatchArg(files, limit) r = self.request( sharing.list_file_members_batch, 'sharing', arg, None, ) return r def sharing_list_file_members_continue(self, cursor): """ Once a cursor has been retrieved from :meth:`sharing_list_file_members` or :meth:`sharing_list_file_members_batch`, use this to paginate through all shared file members. :param str cursor: The cursor returned by your last call to :meth:`sharing_list_file_members`, :meth:`sharing_list_file_members_continue`, or :meth:`sharing_list_file_members_batch`. :rtype: :class:`dropbox.sharing.SharedFileMembers` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.ListFileMembersContinueError` """ arg = sharing.ListFileMembersContinueArg(cursor) r = self.request( sharing.list_file_members_continue, 'sharing', arg, None, ) return r def sharing_list_folder_members(self, shared_folder_id, actions=None, limit=1000): """ Returns shared folder membership by its folder ID. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :rtype: :class:`dropbox.sharing.SharedFolderMembers` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.SharedFolderAccessError` """ arg = sharing.ListFolderMembersArgs(shared_folder_id, actions, limit) r = self.request( sharing.list_folder_members, 'sharing', arg, None, ) return r def sharing_list_folder_members_continue(self, cursor): """ Once a cursor has been retrieved from :meth:`sharing_list_folder_members`, use this to paginate through all shared folder members. Apps must have full Dropbox access to use this endpoint. :param str cursor: The cursor returned by your last call to :meth:`sharing_list_folder_members` or :meth:`sharing_list_folder_members_continue`. :rtype: :class:`dropbox.sharing.SharedFolderMembers` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.ListFolderMembersContinueError` """ arg = sharing.ListFolderMembersContinueArg(cursor) r = self.request( sharing.list_folder_members_continue, 'sharing', arg, None, ) return r def sharing_list_folders(self, limit=1000, actions=None): """ Return the list of all shared folders the current user has access to. Apps must have full Dropbox access to use this endpoint. :param long limit: The maximum number of results to return per request. :param Nullable actions: A list of `FolderAction`s corresponding to `FolderPermission`s that should appear in the response's ``SharedFolderMetadata.permissions`` field describing the actions the authenticated user can perform on the folder. :rtype: :class:`dropbox.sharing.ListFoldersResult` """ arg = sharing.ListFoldersArgs(limit, actions) r = self.request( sharing.list_folders, 'sharing', arg, None, ) return r def sharing_list_folders_continue(self, cursor): """ Once a cursor has been retrieved from :meth:`sharing_list_folders`, use this to paginate through all shared folders. The cursor must come from a previous call to :meth:`sharing_list_folders` or :meth:`sharing_list_folders_continue`. Apps must have full Dropbox access to use this endpoint. :param str cursor: The cursor returned by the previous API call specified in the endpoint description. :rtype: :class:`dropbox.sharing.ListFoldersResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.ListFoldersContinueError` """ arg = sharing.ListFoldersContinueArg(cursor) r = self.request( sharing.list_folders_continue, 'sharing', arg, None, ) return r def sharing_list_mountable_folders(self, limit=1000, actions=None): """ Return the list of all shared folders the current user can mount or unmount. Apps must have full Dropbox access to use this endpoint. :param long limit: The maximum number of results to return per request. :param Nullable actions: A list of `FolderAction`s corresponding to `FolderPermission`s that should appear in the response's ``SharedFolderMetadata.permissions`` field describing the actions the authenticated user can perform on the folder. :rtype: :class:`dropbox.sharing.ListFoldersResult` """ arg = sharing.ListFoldersArgs(limit, actions) r = self.request( sharing.list_mountable_folders, 'sharing', arg, None, ) return r def sharing_list_mountable_folders_continue(self, cursor): """ Once a cursor has been retrieved from :meth:`sharing_list_mountable_folders`, use this to paginate through all mountable shared folders. The cursor must come from a previous call to :meth:`sharing_list_mountable_folders` or :meth:`sharing_list_mountable_folders_continue`. Apps must have full Dropbox access to use this endpoint. :param str cursor: The cursor returned by the previous API call specified in the endpoint description. :rtype: :class:`dropbox.sharing.ListFoldersResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.ListFoldersContinueError` """ arg = sharing.ListFoldersContinueArg(cursor) r = self.request( sharing.list_mountable_folders_continue, 'sharing', arg, None, ) return r def sharing_list_received_files(self, limit=100, actions=None): """ Returns a list of all files shared with current user. Does not include files the user has received via shared folders, and does not include unclaimed invitations. :param long limit: Number of files to return max per query. Defaults to 100 if no limit is specified. :param Nullable actions: A list of `FileAction`s corresponding to `FilePermission`s that should appear in the response's ``SharedFileMetadata.permissions`` field describing the actions the authenticated user can perform on the file. :rtype: :class:`dropbox.sharing.ListFilesResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.SharingUserError` """ arg = sharing.ListFilesArg(limit, actions) r = self.request( sharing.list_received_files, 'sharing', arg, None, ) return r def sharing_list_received_files_continue(self, cursor): """ Get more results with a cursor from :meth:`sharing_list_received_files`. :param str cursor: Cursor in ``ListFilesResult.cursor``. :rtype: :class:`dropbox.sharing.ListFilesResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.ListFilesContinueError` """ arg = sharing.ListFilesContinueArg(cursor) r = self.request( sharing.list_received_files_continue, 'sharing', arg, None, ) return r def sharing_list_shared_links(self, path=None, cursor=None, direct_only=None): """ List shared links of this user. If no path is given, returns a list of all shared links for the current user. If a non-empty path is given, returns a list of all shared links that allow access to the given path - direct links to the given path and links to parent folders of the given path. Links to parent folders can be suppressed by setting direct_only to true. :param Nullable path: See :meth:`sharing_list_shared_links` description. :param Nullable cursor: The cursor returned by your last call to :meth:`sharing_list_shared_links`. :param Nullable direct_only: See :meth:`sharing_list_shared_links` description. :rtype: :class:`dropbox.sharing.ListSharedLinksResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.ListSharedLinksError` """ arg = sharing.ListSharedLinksArg(path, cursor, direct_only) r = self.request( sharing.list_shared_links, 'sharing', arg, None, ) return r def sharing_modify_shared_link_settings(self, url, settings, remove_expiration=False): """ Modify the shared link's settings. If the requested visibility conflict with the shared links policy of the team or the shared folder (in case the linked file is part of a shared folder) then the ``LinkPermissions.resolved_visibility`` of the returned :class:`dropbox.sharing.SharedLinkMetadata` will reflect the actual visibility of the shared link and the ``LinkPermissions.requested_visibility`` will reflect the requested visibility. :param str url: URL of the shared link to change its settings. :param settings: Set of settings for the shared link. :type settings: :class:`dropbox.sharing.SharedLinkSettings` :param bool remove_expiration: If set to true, removes the expiration of the shared link. :rtype: :class:`dropbox.sharing.SharedLinkMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.ModifySharedLinkSettingsError` """ arg = sharing.ModifySharedLinkSettingsArgs(url, settings, remove_expiration) r = self.request( sharing.modify_shared_link_settings, 'sharing', arg, None, ) return r def sharing_mount_folder(self, shared_folder_id): """ The current user mounts the designated folder. Mount a shared folder for a user after they have been added as a member. Once mounted, the shared folder will appear in their Dropbox. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID of the shared folder to mount. :rtype: :class:`dropbox.sharing.SharedFolderMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.MountFolderError` """ arg = sharing.MountFolderArg(shared_folder_id) r = self.request( sharing.mount_folder, 'sharing', arg, None, ) return r def sharing_relinquish_file_membership(self, file): """ The current user relinquishes their membership in the designated file. Note that the current user may still have inherited access to this file through the parent folder. Apps must have full Dropbox access to use this endpoint. :param str file: The path or id for the file. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.RelinquishFileMembershipError` """ arg = sharing.RelinquishFileMembershipArg(file) r = self.request( sharing.relinquish_file_membership, 'sharing', arg, None, ) return None def sharing_relinquish_folder_membership(self, shared_folder_id, leave_a_copy=False): """ The current user relinquishes their membership in the designated shared folder and will no longer have access to the folder. A folder owner cannot relinquish membership in their own folder. This will run synchronously if leave_a_copy is false, and asynchronously if leave_a_copy is true. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :param bool leave_a_copy: Keep a copy of the folder's contents upon relinquishing membership. :rtype: :class:`dropbox.sharing.LaunchEmptyResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.RelinquishFolderMembershipError` """ arg = sharing.RelinquishFolderMembershipArg(shared_folder_id, leave_a_copy) r = self.request( sharing.relinquish_folder_membership, 'sharing', arg, None, ) return r def sharing_remove_file_member(self, file, member): """ Identical to remove_file_member_2 but with less information returned. :param str file: File from which to remove members. :param member: Member to remove from this file. Note that even if an email is specified, it may result in the removal of a user (not an invitee) if the user's main account corresponds to that email address. :type member: :class:`dropbox.sharing.MemberSelector` :rtype: :class:`dropbox.sharing.FileMemberActionIndividualResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.RemoveFileMemberError` """ warnings.warn( 'remove_file_member is deprecated. Use remove_file_member_2.', DeprecationWarning, ) arg = sharing.RemoveFileMemberArg(file, member) r = self.request( sharing.remove_file_member, 'sharing', arg, None, ) return r def sharing_remove_file_member_2(self, file, member): """ Removes a specified member from the file. :param str file: File from which to remove members. :param member: Member to remove from this file. Note that even if an email is specified, it may result in the removal of a user (not an invitee) if the user's main account corresponds to that email address. :type member: :class:`dropbox.sharing.MemberSelector` :rtype: :class:`dropbox.sharing.FileMemberRemoveActionResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.RemoveFileMemberError` """ arg = sharing.RemoveFileMemberArg(file, member) r = self.request( sharing.remove_file_member_2, 'sharing', arg, None, ) return r def sharing_remove_folder_member(self, shared_folder_id, member, leave_a_copy): """ Allows an owner or editor (if the ACL update policy allows) of a shared folder to remove another member. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :param member: The member to remove from the folder. :type member: :class:`dropbox.sharing.MemberSelector` :param bool leave_a_copy: If true, the removed user will keep their copy of the folder after it's unshared, assuming it was mounted. Otherwise, it will be removed from their Dropbox. Also, this must be set to false when kicking a group. :rtype: :class:`dropbox.sharing.LaunchResultBase` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.RemoveFolderMemberError` """ arg = sharing.RemoveFolderMemberArg(shared_folder_id, member, leave_a_copy) r = self.request( sharing.remove_folder_member, 'sharing', arg, None, ) return r def sharing_revoke_shared_link(self, url): """ Revoke a shared link. Note that even after revoking a shared link to a file, the file may be accessible if there are shared links leading to any of the file parent folders. To list all shared links that enable access to a specific file, you can use the :meth:`sharing_list_shared_links` with the file as the ``ListSharedLinksArg.path`` argument. :param str url: URL of the shared link. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.RevokeSharedLinkError` """ arg = sharing.RevokeSharedLinkArg(url) r = self.request( sharing.revoke_shared_link, 'sharing', arg, None, ) return None def sharing_share_folder(self, path, acl_update_policy=None, force_async=False, member_policy=None, shared_link_policy=None, viewer_info_policy=None, actions=None, link_settings=None): """ Share a folder with collaborators. Most sharing will be completed synchronously. Large folders will be completed asynchronously. To make testing the async case repeatable, set `ShareFolderArg.force_async`. If a ``ShareFolderLaunch.async_job_id`` is returned, you'll need to call :meth:`sharing_check_share_job_status` until the action completes to get the metadata for the folder. Apps must have full Dropbox access to use this endpoint. :param Nullable actions: A list of `FolderAction`s corresponding to `FolderPermission`s that should appear in the response's ``SharedFolderMetadata.permissions`` field describing the actions the authenticated user can perform on the folder. :param Nullable link_settings: Settings on the link for this folder. :rtype: :class:`dropbox.sharing.ShareFolderLaunch` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.ShareFolderError` """ arg = sharing.ShareFolderArg(path, acl_update_policy, force_async, member_policy, shared_link_policy, viewer_info_policy, actions, link_settings) r = self.request( sharing.share_folder, 'sharing', arg, None, ) return r def sharing_transfer_folder(self, shared_folder_id, to_dropbox_id): """ Transfer ownership of a shared folder to a member of the shared folder. User must have ``AccessLevel.owner`` access to the shared folder to perform a transfer. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :param str to_dropbox_id: A account or team member ID to transfer ownership to. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.TransferFolderError` """ arg = sharing.TransferFolderArg(shared_folder_id, to_dropbox_id) r = self.request( sharing.transfer_folder, 'sharing', arg, None, ) return None def sharing_unmount_folder(self, shared_folder_id): """ The current user unmounts the designated folder. They can re-mount the folder at a later time using :meth:`sharing_mount_folder`. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.UnmountFolderError` """ arg = sharing.UnmountFolderArg(shared_folder_id) r = self.request( sharing.unmount_folder, 'sharing', arg, None, ) return None def sharing_unshare_file(self, file): """ Remove all members from this file. Does not remove inherited members. :param str file: The file to unshare. :rtype: None :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.UnshareFileError` """ arg = sharing.UnshareFileArg(file) r = self.request( sharing.unshare_file, 'sharing', arg, None, ) return None def sharing_unshare_folder(self, shared_folder_id, leave_a_copy=False): """ Allows a shared folder owner to unshare the folder. You'll need to call :meth:`sharing_check_job_status` to determine if the action has completed successfully. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :param bool leave_a_copy: If true, members of this shared folder will get a copy of this folder after it's unshared. Otherwise, it will be removed from their Dropbox. The current user, who is an owner, will always retain their copy. :rtype: :class:`dropbox.sharing.LaunchEmptyResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.UnshareFolderError` """ arg = sharing.UnshareFolderArg(shared_folder_id, leave_a_copy) r = self.request( sharing.unshare_folder, 'sharing', arg, None, ) return r def sharing_update_file_member(self, file, member, access_level): """ Changes a member's access on a shared file. :rtype: :class:`dropbox.sharing.MemberAccessLevelResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.FileMemberActionError` """ arg = sharing.UpdateFileMemberArgs(file, member, access_level) r = self.request( sharing.update_file_member, 'sharing', arg, None, ) return r def sharing_update_folder_member(self, shared_folder_id, member, access_level): """ Allows an owner or editor of a shared folder to update another member's permissions. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :param member: The member of the shared folder to update. Only the ``MemberSelector.dropbox_id`` may be set at this time. :type member: :class:`dropbox.sharing.MemberSelector` :param access_level: The new access level for ``member``. ``AccessLevel.owner`` is disallowed. :type access_level: :class:`dropbox.sharing.AccessLevel` :rtype: :class:`dropbox.sharing.MemberAccessLevelResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.UpdateFolderMemberError` """ arg = sharing.UpdateFolderMemberArg(shared_folder_id, member, access_level) r = self.request( sharing.update_folder_member, 'sharing', arg, None, ) return r def sharing_update_folder_policy(self, shared_folder_id, member_policy=None, acl_update_policy=None, viewer_info_policy=None, shared_link_policy=None, link_settings=None, actions=None): """ Update the sharing policies for a shared folder. User must have ``AccessLevel.owner`` access to the shared folder to update its policies. Apps must have full Dropbox access to use this endpoint. :param str shared_folder_id: The ID for the shared folder. :param Nullable member_policy: Who can be a member of this shared folder. Only applicable if the current user is on a team. :param Nullable acl_update_policy: Who can add and remove members of this shared folder. :param Nullable viewer_info_policy: Who can enable/disable viewer info for this shared folder. :param Nullable shared_link_policy: The policy to apply to shared links created for content inside this shared folder. The current user must be on a team to set this policy to ``SharedLinkPolicy.members``. :param Nullable link_settings: Settings on the link for this folder. :param Nullable actions: A list of `FolderAction`s corresponding to `FolderPermission`s that should appear in the response's ``SharedFolderMetadata.permissions`` field describing the actions the authenticated user can perform on the folder. :rtype: :class:`dropbox.sharing.SharedFolderMetadata` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.sharing.UpdateFolderPolicyError` """ arg = sharing.UpdateFolderPolicyArg(shared_folder_id, member_policy, acl_update_policy, viewer_info_policy, shared_link_policy, link_settings, actions) r = self.request( sharing.update_folder_policy, 'sharing', arg, None, ) return r # ------------------------------------------ # Routes in team_log namespace def team_log_get_events(self, limit=1000, account_id=None, time=None, category=None): """ Retrieves team events. Permission : Team Auditing. :param long limit: Number of results to return per call. :param Nullable account_id: Filter the events by account ID. Return ony events with this account_id as either Actor, Context, or Participants. :param Nullable time: Filter by time range. :param Nullable category: Filter the returned events to a single category. :rtype: :class:`dropbox.team_log.GetTeamEventsResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.team_log.GetTeamEventsError` """ arg = team_log.GetTeamEventsArg(limit, account_id, time, category) r = self.request( team_log.get_events, 'team_log', arg, None, ) return r def team_log_get_events_continue(self, cursor): """ Once a cursor has been retrieved from :meth:`team_log_get_events`, use this to paginate through all events. Permission : Team Auditing. :param str cursor: Indicates from what point to get the next set of events. :rtype: :class:`dropbox.team_log.GetTeamEventsResult` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.team_log.GetTeamEventsContinueError` """ arg = team_log.GetTeamEventsContinueArg(cursor) r = self.request( team_log.get_events_continue, 'team_log', arg, None, ) return r # ------------------------------------------ # Routes in users namespace def users_get_account(self, account_id): """ Get information about a user's account. :param str account_id: A user's account identifier. :rtype: :class:`dropbox.users.BasicAccount` :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.users.GetAccountError` """ arg = users.GetAccountArg(account_id) r = self.request( users.get_account, 'users', arg, None, ) return r def users_get_account_batch(self, account_ids): """ Get information about multiple user accounts. At most 300 accounts may be queried per request. :param list account_ids: List of user account identifiers. Should not contain any duplicate account IDs. :rtype: list :raises: :class:`dropbox.exceptions.ApiError` If this raises, ApiError.reason is of type: :class:`dropbox.users.GetAccountBatchError` """ arg = users.GetAccountBatchArg(account_ids) r = self.request( users.get_account_batch, 'users', arg, None, ) return r def users_get_current_account(self): """ Get information about the current user's account. :rtype: :class:`dropbox.users.FullAccount` """ arg = None r = self.request( users.get_current_account, 'users', arg, None, ) return r def users_get_space_usage(self): """ Get the space usage information for the current user's account. :rtype: :class:`dropbox.users.SpaceUsage` """ arg = None r = self.request( users.get_space_usage, 'users', arg, None, ) return r

[ "ubuntu@ip-172-31-91-159.ec2.internal" ]

ubuntu@ip-172-31-91-159.ec2.internal

02dd1640ec63d777df0a4a38be03877dc2b326dc

df64b9d1851d3b5770ef4cd726bb6898911d8aff

/protos/final_tree.py

66152b4264328ecb47431aed5f8376566a9027e7

[]

no_license

lampts/kaggle_quora

10bbd5e16f659719bb4eee5bd5adaf2cc9a08737

d35d2619e8f2762cc648eb0829a4c54e698871ea

refs/heads/master

2021-07-11T04:33:46.640082

2017-05-28T08:43:01

108,620,557

0

1

null

2017-10-28T04:49:50

null

UTF-8

Python

false

4,147

py

from sklearn.model_selection import cross_val_predict from sklearn.tree.tree import DecisionTreeClassifier from sklearn.linear_model import LogisticRegression from lightgbm.sklearn import LGBMClassifier import pandas import pickle import numpy as np from tqdm import tqdm from sklearn.model_selection import GridSearchCV, ParameterGrid, StratifiedKFold, cross_val_predict from tfidf_k import calc_weight from sklearn.metrics import log_loss, roc_auc_score from logging import StreamHandler, DEBUG, Formatter, FileHandler log_fmt = Formatter('%(asctime)s %(name)s %(lineno)d [%(levelname)s][%(funcName)s] %(message)s ') from logging import getLogger logger = getLogger(__name__) handler = StreamHandler() handler.setLevel('INFO') handler.setFormatter(log_fmt) logger.setLevel('INFO') logger.addHandler(handler) aaa = pandas.read_csv('clique_data.csv') sample_weight = calc_weight(aaa['label'].values) # , 'emax', 'emin'] # , # 'l_score', 'r_score', 'm_score'] # use_cols = ['cnum', 'pred', 'new', 'vmax', 'vmin', 'vavg'] # , 'emax', 'emin'] use_cols = ['cnum', 'pred', 'vmax', 'vmin', 'vavg'] # , 'emax', 'emin'] #'l_num', 'r_num', 'm_num'] x_train = aaa[use_cols].values y_train = aaa['label'].values all_params = {'max_depth': [5], # [14], 'learning_rate': [0.02], # [0.06, 0.1, 0.2], 'n_estimators': [10000], 'min_child_weight': [1], 'colsample_bytree': [0.7], 'boosting_type': ['gbdt'], #'num_leaves': [32, 100, 200], # [1300, 1500, 2000], 'subsample': [0.99], 'min_child_samples': [5], 'reg_alpha': [0], 'reg_lambda': [0], 'max_bin': [500], 'min_split_gain': [0.1], 'silent': [True], 'seed': [2261] } cv = StratifiedKFold(n_splits=5, shuffle=True, random_state=871) min_score = (100, 100, 100) min_params = None use_score = 0 logger.info('x size {}'.format(x_train.shape)) for params in tqdm(list(ParameterGrid(all_params))): cnt = 0 list_score = [] list_score2 = [] list_best_iter = [] all_pred = np.zeros(y_train.shape[0]) for train, test in cv.split(x_train, y_train): trn_x = x_train[train] val_x = x_train[test] trn_y = y_train[train] val_y = y_train[test] trn_w = sample_weight[train] val_w = sample_weight[test] clf = LGBMClassifier(**params) clf.fit(trn_x, trn_y, sample_weight=trn_w, eval_sample_weight=[val_w], eval_set=[(val_x, val_y)], verbose=False, # eval_metric='logloss', early_stopping_rounds=100 ) pred = clf.predict_proba(val_x)[:, 1] _score = log_loss(val_y, pred, sample_weight=val_w) _score2 = - roc_auc_score(val_y, pred, sample_weight=val_w) list_score.append(_score) list_score2.append(_score2) if clf.best_iteration != -1: list_best_iter.append(clf.best_iteration) else: list_best_iter.append(params['n_estimators']) logger.info('trees: {}'.format(list_best_iter)) params['n_estimators'] = np.mean(list_best_iter, dtype=int) score = (np.mean(list_score), np.min(list_score), np.max(list_score)) score2 = (np.mean(list_score2), np.min(list_score2), np.max(list_score2)) logger.info('param: %s' % (params)) logger.info('loss: {} (avg min max {})'.format(score[use_score], score)) logger.info('score: {} (avg min max {})'.format(score2[use_score], score2)) if min_score[use_score] > score[use_score]: min_score = score min_score2 = score2 min_params = params logger.info('best score: {} {}'.format(min_score[use_score], min_score)) logger.info('best score2: {} {}'.format(min_score2[use_score], min_score2)) logger.info('best_param: {}'.format(min_params)) final_tree = LGBMClassifier(**min_params) final_tree.fit(x_train, y_train, sample_weight=sample_weight) with open('final_tree.pkl', 'wb') as f: pickle.dump(final_tree, f, -1)

[ "you@example.com" ]

you@example.com

c519d75ba0c468f9c100a50c6b1a7cdb34ba4573

f1679e8c872e7e5d12d947a47920d5bad4d3b92a

/paciente/migrations/0002_paciente_imagem.py

7ed0e6a8112b42ff40c7a8f125867af6457ec1e6

[]

no_license

lldenisll/doctor_backend

d03e6090fae704bae9eabd002aefeb63de5a9d78

071911186b1f2940feff7549ca9c49b9f8c7ce22

refs/heads/master

2023-03-27T21:28:49.571818

2021-04-04T22:27:45

354,152,189

0

null

UTF-8

Python

false

390

py

# Generated by Django 3.1.7 on 2021-04-03 19:23 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('paciente', '0001_initial'), ] operations = [ migrations.AddField( model_name='paciente', name='imagem', field=models.ImageField(null=True, upload_to='img'), ), ]

[ "namorado@TFGcos-MacBook-Pro.local" ]

namorado@TFGcos-MacBook-Pro.local

e88613a1e28d2556c2ad8050f5e8ab0266b4c4d4

53fab060fa262e5d5026e0807d93c75fb81e67b9

/backup/user_282/ch23_2020_03_04_22_50_49_571106.py

e8af7c8bab6de99ba6d7382438bd6a574da48447

[]

no_license

gabriellaec/desoft-analise-exercicios

b77c6999424c5ce7e44086a12589a0ad43d6adca

01940ab0897aa6005764fc220b900e4d6161d36b

refs/heads/main

2023-01-31T17:19:42.050628

2020-12-16T05:21:31

306,735,108

0

null

UTF-8

Python

false

161

py

velocidade = int(input('qual eh a velocidade? ')) if velocidade>80: print('multa de R${0:.2f}'.format((velocidade-80)*5)) else: print('Não foi multado')

[ "you@example.com" ]

you@example.com

931ad54b3f9cc8bcf4700cad46f9d5985056e646

bd435e3ff491d13c3cb1ffcf34771ac1c80f7859

/code/flask/bookshare/app/views.py

a4a2b0f8c1669efd4097e629e116ff3682494636

[]

no_license

luningcowboy/PythonTutorial

8f4b6d16e0fad99a226540a6f12639ccdff402ff

9024efe8ed22aca0a1271a2c1c388d3ffe1e6690

refs/heads/master

2021-06-16T23:03:22.153473

2020-04-09T13:52:12

187,571,993

0

null

2021-03-25T23:02:36

2019-05-20T05:16:13

Python

UTF-8

Python

false

2,211

py

from flask import render_template, url_for, redirect from app import app books = [ {'name':'呐喊1','author':'鲁迅1','id':0,'desc':'这是一本关于呐喊的书','contents':['xxxxx','xxxx','xxxx'],'download':['https://www.baidu.com','https://www.baidu.com'],'pic_url':'http://haodoo.net/covers/17Z7.jpg'}, {'name':'呐喊2','author':'鲁迅2','id':1,'desc':'这是一本关于呐喊的书','contents':['xxxxx','xxxx','xxxx'],'download':['https://www.baidu.com','https://www.baidu.com'],'pic_url':'http://haodoo.net/covers/17Z7.jpg'}, {'name':'呐喊3','author':'鲁迅3','id':2,'desc':'这是一本关于呐喊的书','contents':['xxxxx','xxxx','xxxx'],'download':['https://www.baidu.com','https://www.baidu.com'],'pic_url':'http://haodoo.net/covers/17Z7.jpg'}, {'name':'呐喊4','author':'鲁迅4','id':3,'desc':'这是一本关于呐喊的书','contents':['xxxxx','xxxx','xxxx'],'download':['https://www.baidu.com','https://www.baidu.com'],'pic_url':'http://haodoo.net/covers/17Z7.jpg'} ] types = [ {'name':'计算机','tag':'1'}, {'name':'小说','tag':'2'}, {'name':'小说1','tag':'3'}, {'name':'小说2','tag':'4'}, {'name':'计算机','tag':'5'}, {'name':'小说','tag':'6'}, {'name':'小说1','tag':'7'}, {'name':'小说2','tag':'8'}] def getTypes(): ret = [] for t in types: print('getTypes', t) t['url'] = url_for('type', type=t['tag']) ret.append(t) return ret def getBooks(): ret = [] for b in books: b['url'] = url_for('book_desc', book_id=b['id']) ret.append(b) return ret @app.route("/") @app.route("/index/") def index(): return render_template('index.html',types=getTypes(),books=getBooks()) @app.route("/type/<type>") def type(type): tmpBooks = getBooks() return render_template('type.html', type=type,books=books,types=getTypes()) @app.route("/book_desc/<book_id>") def book_desc(book_id): if not book_id: return redirect(url_for('index.html')) tmpBooks = getBooks() bookInfo = tmpBooks[int(book_id)] return render_template('book_desc.html', bookInfo=bookInfo, types=getTypes())

[ "luningcowboy@gmail.com" ]

luningcowboy@gmail.com

0c8df35d0cfa2f012fb8cb0c40d18fabd7622a0c

3c94e96486a7e3616e3656b60abb4a53690fe216

/tools/workspace/libjpeg/repository.bzl

b515b9136476b75092076de7375ec4ddcf61cd12

[]

no_license

doubleyou/bazel_deps

da499f26d357739a4558225fc3e371497565eb37

06b595fd79d1f6dd85a399e61b3f8ae97c859194

refs/heads/master

2022-02-05T15:47:37.630661

2019-03-11T19:40:11

178,992,654

0

null

2019-04-02T03:34:00

null

UTF-8

Python

false

1,067

bzl

# -*- python -*- # Copyright 2018 Josh Pieper, jjp@pobox.com. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. load("@bazel_tools//tools/build_defs/repo:http.bzl", "http_archive") def libjpeg_repository(name): http_archive( name = name, urls = [ "https://svwh.dl.sourceforge.net/project/libjpeg/libjpeg/6b/jpegsrc.v6b.tar.gz", ], sha256 = "75c3ec241e9996504fe02a9ed4d12f16b74ade713972f3db9e65ce95cd27e35d", strip_prefix = "jpeg-6b", build_file = Label("//tools/workspace/libjpeg:package.BUILD"), )

[ "jjp@pobox.com" ]

jjp@pobox.com

b64950b1af04cca69d274f053c5afa6d6f3e0f6e

8957f0b42ba945399a2eeb71f796c11c9eb35b06

/lib/test/test_array.py

6a4474329970ed63b14d7ca2a2b7e0423d700513

[]

no_license

notro/tmp_CircuitPython_stdlib

4de177cbb45b2209f07171c27f844c7d377dffc9

641727294039a9441c35ba1a1d22de403664b710

refs/heads/master

2020-03-27T18:26:33.544047

2019-02-15T20:49:34

146,922,496

1

null

UTF-8

Python

false

48,142

py

"""Test the arraymodule. Roger E. Masse """ import unittest from test import support #import weakref #import pickle #import operator import io #import math import struct import sys #import warnings import array #from array import _array_reconstructor as array_reconstructor try: # Try to determine availability of long long independently # of the array module under test struct.calcsize('@q') have_long_long = True except struct.error: have_long_long = False #sizeof_wchar = array.array('u').itemsize class ArraySubclass(array.array): pass class ArraySubclassWithKwargs(array.array): def __init__(self, typecode, newarg=None): # array.array.__init__(self) super().__init__(typecode) ### #typecodes = "ubBhHiIlLfd" typecodes = "bBhHiIlLfd" ### if have_long_long: typecodes += 'qQ' class BadConstructorTest(unittest.TestCase): def test_constructor(self): self.assertRaises(TypeError, array.array) self.assertRaises(TypeError, array.array, spam=42) # self.assertRaises(TypeError, array.array, 'xx') # self.assertRaises(ValueError, array.array, 'x') ## Machine format codes. ## ## Search for "enum machine_format_code" in Modules/arraymodule.c to get the ## authoritative values. #UNKNOWN_FORMAT = -1 #UNSIGNED_INT8 = 0 #SIGNED_INT8 = 1 #UNSIGNED_INT16_LE = 2 #UNSIGNED_INT16_BE = 3 #SIGNED_INT16_LE = 4 #SIGNED_INT16_BE = 5 #UNSIGNED_INT32_LE = 6 #UNSIGNED_INT32_BE = 7 #SIGNED_INT32_LE = 8 #SIGNED_INT32_BE = 9 #UNSIGNED_INT64_LE = 10 #UNSIGNED_INT64_BE = 11 #SIGNED_INT64_LE = 12 #SIGNED_INT64_BE = 13 #IEEE_754_FLOAT_LE = 14 #IEEE_754_FLOAT_BE = 15 #IEEE_754_DOUBLE_LE = 16 #IEEE_754_DOUBLE_BE = 17 #UTF16_LE = 18 #UTF16_BE = 19 #UTF32_LE = 20 #UTF32_BE = 21 # #class ArrayReconstructorTest(unittest.TestCase): # # def test_error(self): # self.assertRaises(TypeError, array_reconstructor, # "", "b", 0, b"") # self.assertRaises(TypeError, array_reconstructor, # str, "b", 0, b"") # self.assertRaises(TypeError, array_reconstructor, # array.array, "b", '', b"") # self.assertRaises(TypeError, array_reconstructor, # array.array, "b", 0, "") # self.assertRaises(ValueError, array_reconstructor, # array.array, "?", 0, b"") # self.assertRaises(ValueError, array_reconstructor, # array.array, "b", UNKNOWN_FORMAT, b"") # self.assertRaises(ValueError, array_reconstructor, # array.array, "b", 22, b"") # self.assertRaises(ValueError, array_reconstructor, # array.array, "d", 16, b"a") # # def test_numbers(self): # testcases = ( # (['B', 'H', 'I', 'L'], UNSIGNED_INT8, '=BBBB', # [0x80, 0x7f, 0, 0xff]), # (['b', 'h', 'i', 'l'], SIGNED_INT8, '=bbb', # [-0x80, 0x7f, 0]), # (['H', 'I', 'L'], UNSIGNED_INT16_LE, '<HHHH', # [0x8000, 0x7fff, 0, 0xffff]), # (['H', 'I', 'L'], UNSIGNED_INT16_BE, '>HHHH', # [0x8000, 0x7fff, 0, 0xffff]), # (['h', 'i', 'l'], SIGNED_INT16_LE, '<hhh', # [-0x8000, 0x7fff, 0]), # (['h', 'i', 'l'], SIGNED_INT16_BE, '>hhh', # [-0x8000, 0x7fff, 0]), # (['I', 'L'], UNSIGNED_INT32_LE, '<IIII', # [1<<31, (1<<31)-1, 0, (1<<32)-1]), # (['I', 'L'], UNSIGNED_INT32_BE, '>IIII', # [1<<31, (1<<31)-1, 0, (1<<32)-1]), # (['i', 'l'], SIGNED_INT32_LE, '<iii', # [-1<<31, (1<<31)-1, 0]), # (['i', 'l'], SIGNED_INT32_BE, '>iii', # [-1<<31, (1<<31)-1, 0]), # (['L'], UNSIGNED_INT64_LE, '<QQQQ', # [1<<31, (1<<31)-1, 0, (1<<32)-1]), # (['L'], UNSIGNED_INT64_BE, '>QQQQ', # [1<<31, (1<<31)-1, 0, (1<<32)-1]), # (['l'], SIGNED_INT64_LE, '<qqq', # [-1<<31, (1<<31)-1, 0]), # (['l'], SIGNED_INT64_BE, '>qqq', # [-1<<31, (1<<31)-1, 0]), # # The following tests for INT64 will raise an OverflowError # # when run on a 32-bit machine. The tests are simply skipped # # in that case. # (['L'], UNSIGNED_INT64_LE, '<QQQQ', # [1<<63, (1<<63)-1, 0, (1<<64)-1]), # (['L'], UNSIGNED_INT64_BE, '>QQQQ', # [1<<63, (1<<63)-1, 0, (1<<64)-1]), # (['l'], SIGNED_INT64_LE, '<qqq', # [-1<<63, (1<<63)-1, 0]), # (['l'], SIGNED_INT64_BE, '>qqq', # [-1<<63, (1<<63)-1, 0]), # (['f'], IEEE_754_FLOAT_LE, '<ffff', # [16711938.0, float('inf'), float('-inf'), -0.0]), # (['f'], IEEE_754_FLOAT_BE, '>ffff', # [16711938.0, float('inf'), float('-inf'), -0.0]), # (['d'], IEEE_754_DOUBLE_LE, '<dddd', # [9006104071832581.0, float('inf'), float('-inf'), -0.0]), # (['d'], IEEE_754_DOUBLE_BE, '>dddd', # [9006104071832581.0, float('inf'), float('-inf'), -0.0]) # ) # for testcase in testcases: # valid_typecodes, mformat_code, struct_fmt, values = testcase # arraystr = struct.pack(struct_fmt, *values) # for typecode in valid_typecodes: # try: # a = array.array(typecode, values) # except OverflowError: # continue # Skip this test case. # b = array_reconstructor( # array.array, typecode, mformat_code, arraystr) # self.assertEqual(a, b, # msg="{0!r} != {1!r}; testcase={2!r}".format(a, b, testcase)) # # def test_unicode(self): # teststr = "Bonne Journ\xe9e \U0002030a\U00020347" # testcases = ( # (UTF16_LE, "UTF-16-LE"), # (UTF16_BE, "UTF-16-BE"), # (UTF32_LE, "UTF-32-LE"), # (UTF32_BE, "UTF-32-BE") # ) # for testcase in testcases: # mformat_code, encoding = testcase # a = array.array('u', teststr) # b = array_reconstructor( # array.array, 'u', mformat_code, teststr.encode(encoding)) # self.assertEqual(a, b, # msg="{0!r} != {1!r}; testcase={2!r}".format(a, b, testcase)) # # class BaseTest: # Required class attributes (provided by subclasses # typecode: the typecode to test # example: an initializer usable in the constructor for this type # smallerexample: the same length as example, but smaller # biggerexample: the same length as example, but bigger # outside: An entry that is not in example # minitemsize: the minimum guaranteed itemsize def assertEntryEqual(self, entry1, entry2): self.assertEqual(entry1, entry2) def badtypecode(self): # Return a typecode that is different from our own return typecodes[(typecodes.index(self.typecode)+1) % len(typecodes)] def test_constructor(self): a = array.array(self.typecode) # self.assertEqual(a.typecode, self.typecode) # self.assertGreaterEqual(a.itemsize, self.minitemsize) self.assertRaises(TypeError, array.array, self.typecode, None) def test_len(self): a = array.array(self.typecode) a.append(self.example[0]) self.assertEqual(len(a), 1) a = array.array(self.typecode, self.example) self.assertEqual(len(a), len(self.example)) # def test_buffer_info(self): # a = array.array(self.typecode, self.example) # self.assertRaises(TypeError, a.buffer_info, 42) # bi = a.buffer_info() # self.assertIsInstance(bi, tuple) # self.assertEqual(len(bi), 2) # self.assertIsInstance(bi[0], int) # self.assertIsInstance(bi[1], int) # self.assertEqual(bi[1], len(a)) # # def test_byteswap(self): # if self.typecode == 'u': # example = '\U00100100' # else: # example = self.example # a = array.array(self.typecode, example) # self.assertRaises(TypeError, a.byteswap, 42) # if a.itemsize in (1, 2, 4, 8): # b = array.array(self.typecode, example) # b.byteswap() # if a.itemsize==1: # self.assertEqual(a, b) # else: # self.assertNotEqual(a, b) # b.byteswap() # self.assertEqual(a, b) # # def test_copy(self): # import copy # a = array.array(self.typecode, self.example) # b = copy.copy(a) # self.assertNotEqual(id(a), id(b)) # self.assertEqual(a, b) # # def test_deepcopy(self): # import copy # a = array.array(self.typecode, self.example) # b = copy.deepcopy(a) # self.assertNotEqual(id(a), id(b)) # self.assertEqual(a, b) # # def test_reduce_ex(self): # a = array.array(self.typecode, self.example) # for protocol in range(3): # self.assertIs(a.__reduce_ex__(protocol)[0], array.array) # for protocol in range(3, pickle.HIGHEST_PROTOCOL): # self.assertIs(a.__reduce_ex__(protocol)[0], array_reconstructor) # # def test_pickle(self): # for protocol in range(pickle.HIGHEST_PROTOCOL + 1): # a = array.array(self.typecode, self.example) # b = pickle.loads(pickle.dumps(a, protocol)) # self.assertNotEqual(id(a), id(b)) # self.assertEqual(a, b) # # a = ArraySubclass(self.typecode, self.example) # a.x = 10 # b = pickle.loads(pickle.dumps(a, protocol)) # self.assertNotEqual(id(a), id(b)) # self.assertEqual(a, b) # self.assertEqual(a.x, b.x) # self.assertEqual(type(a), type(b)) # # def test_pickle_for_empty_array(self): # for protocol in range(pickle.HIGHEST_PROTOCOL + 1): # a = array.array(self.typecode) # b = pickle.loads(pickle.dumps(a, protocol)) # self.assertNotEqual(id(a), id(b)) # self.assertEqual(a, b) # # a = ArraySubclass(self.typecode) # a.x = 10 # b = pickle.loads(pickle.dumps(a, protocol)) # self.assertNotEqual(id(a), id(b)) # self.assertEqual(a, b) # self.assertEqual(a.x, b.x) # self.assertEqual(type(a), type(b)) # # def test_iterator_pickle(self): # data = array.array(self.typecode, self.example) # for proto in range(pickle.HIGHEST_PROTOCOL + 1): # orgit = iter(data) # d = pickle.dumps(orgit, proto) # it = pickle.loads(d) # self.assertEqual(type(orgit), type(it)) # self.assertEqual(list(it), list(data)) # # if len(data): # it = pickle.loads(d) # next(it) # d = pickle.dumps(it, proto) # self.assertEqual(list(it), list(data)[1:]) # # def test_insert(self): # a = array.array(self.typecode, self.example) # a.insert(0, self.example[0]) # self.assertEqual(len(a), 1+len(self.example)) # self.assertEqual(a[0], a[1]) # self.assertRaises(TypeError, a.insert) # self.assertRaises(TypeError, a.insert, None) # self.assertRaises(TypeError, a.insert, 0, None) # # a = array.array(self.typecode, self.example) # a.insert(-1, self.example[0]) # self.assertEqual( # a, # array.array( # self.typecode, # self.example[:-1] + self.example[:1] + self.example[-1:] # ) # ) # # a = array.array(self.typecode, self.example) # a.insert(-1000, self.example[0]) # self.assertEqual( # a, # array.array(self.typecode, self.example[:1] + self.example) # ) # # a = array.array(self.typecode, self.example) # a.insert(1000, self.example[0]) # self.assertEqual( # a, # array.array(self.typecode, self.example + self.example[:1]) # ) # # def test_tofromfile(self): # a = array.array(self.typecode, 2*self.example) # self.assertRaises(TypeError, a.tofile) # support.unlink(support.TESTFN) # f = open(support.TESTFN, 'wb') # try: # a.tofile(f) # f.close() # b = array.array(self.typecode) # f = open(support.TESTFN, 'rb') # self.assertRaises(TypeError, b.fromfile) # b.fromfile(f, len(self.example)) # self.assertEqual(b, array.array(self.typecode, self.example)) # self.assertNotEqual(a, b) # self.assertRaises(EOFError, b.fromfile, f, len(self.example)+1) # self.assertEqual(a, b) # f.close() # finally: # if not f.closed: # f.close() # support.unlink(support.TESTFN) # # def test_fromfile_ioerror(self): # # Issue #5395: Check if fromfile raises a proper OSError # # instead of EOFError. # a = array.array(self.typecode) # f = open(support.TESTFN, 'wb') # try: # self.assertRaises(OSError, a.fromfile, f, len(self.example)) # finally: # f.close() # support.unlink(support.TESTFN) # # def test_filewrite(self): # a = array.array(self.typecode, 2*self.example) # f = open(support.TESTFN, 'wb') # try: # f.write(a) # f.close() # b = array.array(self.typecode) # f = open(support.TESTFN, 'rb') # b.fromfile(f, len(self.example)) # self.assertEqual(b, array.array(self.typecode, self.example)) # self.assertNotEqual(a, b) # b.fromfile(f, len(self.example)) # self.assertEqual(a, b) # f.close() # finally: # if not f.closed: # f.close() # support.unlink(support.TESTFN) # # def test_tofromlist(self): # a = array.array(self.typecode, 2*self.example) # b = array.array(self.typecode) # self.assertRaises(TypeError, a.tolist, 42) # self.assertRaises(TypeError, b.fromlist) # self.assertRaises(TypeError, b.fromlist, 42) # self.assertRaises(TypeError, b.fromlist, [None]) # b.fromlist(a.tolist()) # self.assertEqual(a, b) # # def test_tofromstring(self): # nb_warnings = 4 # with warnings.catch_warnings(record=True) as r: # warnings.filterwarnings("always", # message=r"(to|from)string is deprecated", # category=DeprecationWarning) # a = array.array(self.typecode, 2*self.example) # b = array.array(self.typecode) # self.assertRaises(TypeError, a.tostring, 42) # self.assertRaises(TypeError, b.fromstring) # self.assertRaises(TypeError, b.fromstring, 42) # b.fromstring(a.tostring()) # self.assertEqual(a, b) # if a.itemsize>1: # self.assertRaises(ValueError, b.fromstring, "x") # nb_warnings += 1 # self.assertEqual(len(r), nb_warnings) # # def test_tofrombytes(self): # a = array.array(self.typecode, 2*self.example) # b = array.array(self.typecode) # self.assertRaises(TypeError, a.tobytes, 42) # self.assertRaises(TypeError, b.frombytes) # self.assertRaises(TypeError, b.frombytes, 42) # b.frombytes(a.tobytes()) # c = array.array(self.typecode, bytearray(a.tobytes())) # self.assertEqual(a, b) # self.assertEqual(a, c) # if a.itemsize>1: # self.assertRaises(ValueError, b.frombytes, b"x") # def test_fromarray(self): a = array.array(self.typecode, self.example) b = array.array(self.typecode, a) self.assertEqual(a, b) def test_repr(self): a = array.array(self.typecode, 2*self.example) self.assertEqual(a, eval(repr(a), {"array": array.array})) a = array.array(self.typecode) self.assertEqual(repr(a), "array('%s')" % self.typecode) def test_str(self): a = array.array(self.typecode, 2*self.example) str(a) def test_cmp(self): a = array.array(self.typecode, self.example) self.assertIs(a == 42, False) self.assertIs(a != 42, True) self.assertIs(a == a, True) self.assertIs(a != a, False) # self.assertIs(a < a, False) # self.assertIs(a <= a, True) # self.assertIs(a > a, False) # self.assertIs(a >= a, True) al = array.array(self.typecode, self.smallerexample) ab = array.array(self.typecode, self.biggerexample) # self.assertIs(a == 2*a, False) self.assertIs(a == a*2, False) ### # self.assertIs(a != 2*a, True) self.assertIs(a != a*2, True) ### # self.assertIs(a < 2*a, True) # self.assertIs(a <= 2*a, True) # self.assertIs(a > 2*a, False) # self.assertIs(a >= 2*a, False) self.assertIs(a == al, False) self.assertIs(a != al, True) # self.assertIs(a < al, False) # self.assertIs(a <= al, False) # self.assertIs(a > al, True) # self.assertIs(a >= al, True) self.assertIs(a == ab, False) self.assertIs(a != ab, True) # self.assertIs(a < ab, True) # self.assertIs(a <= ab, True) # self.assertIs(a > ab, False) # self.assertIs(a >= ab, False) def test_add(self): a = array.array(self.typecode, self.example) \ + array.array(self.typecode, self.example[::-1]) self.assertEqual( a, array.array(self.typecode, self.example + self.example[::-1]) ) # b = array.array(self.badtypecode()) # self.assertRaises(TypeError, a.__add__, b) # # self.assertRaises(TypeError, a.__add__, "bad") # def test_iadd(self): a = array.array(self.typecode, self.example[::-1]) b = a a += array.array(self.typecode, 2*self.example) self.assertIs(a, b) self.assertEqual( a, array.array(self.typecode, self.example[::-1]+2*self.example) ) a = array.array(self.typecode, self.example) a += a self.assertEqual( a, array.array(self.typecode, self.example + self.example) ) # b = array.array(self.badtypecode()) # self.assertRaises(TypeError, a.__add__, b) # # self.assertRaises(TypeError, a.__iadd__, "bad") # def test_mul(self): # a = 5*array.array(self.typecode, self.example) # self.assertEqual( # a, # array.array(self.typecode, 5*self.example) # ) # a = array.array(self.typecode, self.example)*5 self.assertEqual( a, array.array(self.typecode, self.example*5) ) # a = 0*array.array(self.typecode, self.example) a = array.array(self.typecode, self.example) * 0 ### self.assertEqual( a, array.array(self.typecode) ) # a = (-1)*array.array(self.typecode, self.example) # self.assertEqual( # a, # array.array(self.typecode) # ) # # a = 5 * array.array(self.typecode, self.example[:1]) a = array.array(self.typecode, self.example[:1]) * 5 ### self.assertEqual( a, array.array(self.typecode, [a[0]] * 5) ) # self.assertRaises(TypeError, a.__mul__, "bad") # def test_imul(self): a = array.array(self.typecode, self.example) b = a a *= 5 self.assertIs(a, b) self.assertEqual( a, array.array(self.typecode, 5*self.example) ) a *= 0 self.assertIs(a, b) self.assertEqual(a, array.array(self.typecode)) # a *= 1000 a *= 10 ### self.assertIs(a, b) self.assertEqual(a, array.array(self.typecode)) # a *= -1 # self.assertIs(a, b) # self.assertEqual(a, array.array(self.typecode)) # # a = array.array(self.typecode, self.example) # a *= -1 # self.assertEqual(a, array.array(self.typecode)) # # self.assertRaises(TypeError, a.__imul__, "bad") # def test_getitem(self): a = array.array(self.typecode, self.example) self.assertEntryEqual(a[0], self.example[0]) self.assertEntryEqual(a[0], self.example[0]) self.assertEntryEqual(a[-1], self.example[-1]) self.assertEntryEqual(a[-1], self.example[-1]) self.assertEntryEqual(a[len(self.example)-1], self.example[-1]) self.assertEntryEqual(a[-len(self.example)], self.example[0]) # self.assertRaises(TypeError, a.__getitem__) # self.assertRaises(IndexError, a.__getitem__, len(self.example)) # self.assertRaises(IndexError, a.__getitem__, -len(self.example)-1) def test_setitem(self): a = array.array(self.typecode, self.example) a[0] = a[-1] self.assertEntryEqual(a[0], a[-1]) a = array.array(self.typecode, self.example) a[0] = a[-1] self.assertEntryEqual(a[0], a[-1]) a = array.array(self.typecode, self.example) a[-1] = a[0] self.assertEntryEqual(a[0], a[-1]) a = array.array(self.typecode, self.example) a[-1] = a[0] self.assertEntryEqual(a[0], a[-1]) a = array.array(self.typecode, self.example) a[len(self.example)-1] = a[0] self.assertEntryEqual(a[0], a[-1]) a = array.array(self.typecode, self.example) a[-len(self.example)] = a[-1] self.assertEntryEqual(a[0], a[-1]) # self.assertRaises(TypeError, a.__setitem__) # self.assertRaises(TypeError, a.__setitem__, None) # self.assertRaises(TypeError, a.__setitem__, 0, None) # self.assertRaises( # IndexError, # a.__setitem__, # len(self.example), self.example[0] # ) # self.assertRaises( # IndexError, # a.__setitem__, # -len(self.example)-1, self.example[0] # ) # # def test_delitem(self): # a = array.array(self.typecode, self.example) # del a[0] # self.assertEqual( # a, # array.array(self.typecode, self.example[1:]) # ) # # a = array.array(self.typecode, self.example) # del a[-1] # self.assertEqual( # a, # array.array(self.typecode, self.example[:-1]) # ) # # a = array.array(self.typecode, self.example) # del a[len(self.example)-1] # self.assertEqual( # a, # array.array(self.typecode, self.example[:-1]) # ) # # a = array.array(self.typecode, self.example) # del a[-len(self.example)] # self.assertEqual( # a, # array.array(self.typecode, self.example[1:]) # ) # # self.assertRaises(TypeError, a.__delitem__) # self.assertRaises(TypeError, a.__delitem__, None) # self.assertRaises(IndexError, a.__delitem__, len(self.example)) # self.assertRaises(IndexError, a.__delitem__, -len(self.example)-1) # def test_getslice(self): a = array.array(self.typecode, self.example) self.assertEqual(a[:], a) self.assertEqual( a[1:], array.array(self.typecode, self.example[1:]) ) self.assertEqual( a[:1], array.array(self.typecode, self.example[:1]) ) self.assertEqual( a[:-1], array.array(self.typecode, self.example[:-1]) ) self.assertEqual( a[-1:], array.array(self.typecode, self.example[-1:]) ) self.assertEqual( a[-1:-1], array.array(self.typecode) ) self.assertEqual( a[2:1], array.array(self.typecode) ) self.assertEqual( a[1000:], array.array(self.typecode) ) self.assertEqual(a[-1000:], a) self.assertEqual(a[:1000], a) self.assertEqual( a[:-1000], array.array(self.typecode) ) self.assertEqual(a[-1000:1000], a) self.assertEqual( a[2000:1000], array.array(self.typecode) ) def test_extended_getslice(self): # Test extended slicing by comparing with list slicing # (Assumes list conversion works correctly, too) a = array.array(self.typecode, self.example) indices = (0, None, 1, 3, 19, 100, -1, -2, -31, -100) for start in indices: for stop in indices: # Everything except the initial 0 (invalid step) # for step in indices[1:]: for step in [1]: ### self.assertEqual(list(a[start:stop:step]), list(a)[start:stop:step]) def test_setslice(self): a = array.array(self.typecode, self.example) a[:1] = a self.assertEqual( a, array.array(self.typecode, self.example + self.example[1:]) ) a = array.array(self.typecode, self.example) a[:-1] = a self.assertEqual( a, array.array(self.typecode, self.example + self.example[-1:]) ) a = array.array(self.typecode, self.example) a[-1:] = a self.assertEqual( a, array.array(self.typecode, self.example[:-1] + self.example) ) a = array.array(self.typecode, self.example) a[1:] = a self.assertEqual( a, array.array(self.typecode, self.example[:1] + self.example) ) a = array.array(self.typecode, self.example) a[1:-1] = a self.assertEqual( a, array.array( self.typecode, self.example[:1] + self.example + self.example[-1:] ) ) a = array.array(self.typecode, self.example) a[1000:] = a self.assertEqual( a, array.array(self.typecode, 2*self.example) ) a = array.array(self.typecode, self.example) a[-1000:] = a self.assertEqual( a, array.array(self.typecode, self.example) ) a = array.array(self.typecode, self.example) a[:1000] = a self.assertEqual( a, array.array(self.typecode, self.example) ) a = array.array(self.typecode, self.example) a[:-1000] = a self.assertEqual( a, array.array(self.typecode, 2*self.example) ) a = array.array(self.typecode, self.example) a[1:0] = a self.assertEqual( a, array.array(self.typecode, self.example[:1] + self.example + self.example[1:]) ) a = array.array(self.typecode, self.example) a[2000:1000] = a self.assertEqual( a, array.array(self.typecode, 2*self.example) ) # a = array.array(self.typecode, self.example) # self.assertRaises(TypeError, a.__setitem__, slice(0, 0), None) # self.assertRaises(TypeError, a.__setitem__, slice(0, 1), None) # # b = array.array(self.badtypecode()) # self.assertRaises(TypeError, a.__setitem__, slice(0, 0), b) # self.assertRaises(TypeError, a.__setitem__, slice(0, 1), b) # # def test_extended_set_del_slice(self): # indices = (0, None, 1, 3, 19, 100, -1, -2, -31, -100) # for start in indices: # for stop in indices: # # Everything except the initial 0 (invalid step) # for step in indices[1:]: # a = array.array(self.typecode, self.example) # L = list(a) # # Make sure we have a slice of exactly the right length, # # but with (hopefully) different data. # data = L[start:stop:step] # data.reverse() # L[start:stop:step] = data # a[start:stop:step] = array.array(self.typecode, data) # self.assertEqual(a, array.array(self.typecode, L)) # # del L[start:stop:step] # del a[start:stop:step] # self.assertEqual(a, array.array(self.typecode, L)) # # def test_index(self): # example = 2*self.example # a = array.array(self.typecode, example) # self.assertRaises(TypeError, a.index) # for x in example: # self.assertEqual(a.index(x), example.index(x)) # self.assertRaises(ValueError, a.index, None) # self.assertRaises(ValueError, a.index, self.outside) # # def test_count(self): # example = 2*self.example # a = array.array(self.typecode, example) # self.assertRaises(TypeError, a.count) # for x in example: # self.assertEqual(a.count(x), example.count(x)) # self.assertEqual(a.count(self.outside), 0) # self.assertEqual(a.count(None), 0) # # def test_remove(self): # for x in self.example: # example = 2*self.example # a = array.array(self.typecode, example) # pos = example.index(x) # example2 = example[:pos] + example[pos+1:] # a.remove(x) # self.assertEqual(a, array.array(self.typecode, example2)) # # a = array.array(self.typecode, self.example) # self.assertRaises(ValueError, a.remove, self.outside) # # self.assertRaises(ValueError, a.remove, None) # # def test_pop(self): # a = array.array(self.typecode) # self.assertRaises(IndexError, a.pop) # # a = array.array(self.typecode, 2*self.example) # self.assertRaises(TypeError, a.pop, 42, 42) # self.assertRaises(TypeError, a.pop, None) # self.assertRaises(IndexError, a.pop, len(a)) # self.assertRaises(IndexError, a.pop, -len(a)-1) # # self.assertEntryEqual(a.pop(0), self.example[0]) # self.assertEqual( # a, # array.array(self.typecode, self.example[1:]+self.example) # ) # self.assertEntryEqual(a.pop(1), self.example[2]) # self.assertEqual( # a, # array.array(self.typecode, self.example[1:2]+self.example[3:]+self.example) # ) # self.assertEntryEqual(a.pop(0), self.example[1]) # self.assertEntryEqual(a.pop(), self.example[-1]) # self.assertEqual( # a, # array.array(self.typecode, self.example[3:]+self.example[:-1]) # ) # # def test_reverse(self): # a = array.array(self.typecode, self.example) # self.assertRaises(TypeError, a.reverse, 42) # a.reverse() # self.assertEqual( # a, # array.array(self.typecode, self.example[::-1]) # ) # def test_extend(self): a = array.array(self.typecode, self.example) self.assertRaises(TypeError, a.extend) # a.extend(array.array(self.typecode, self.example[::-1])) # self.assertEqual( # a, # array.array(self.typecode, self.example+self.example[::-1]) # ) a = array.array(self.typecode, self.example) a.extend(a) self.assertEqual( a, array.array(self.typecode, self.example+self.example) ) # b = array.array(self.badtypecode()) # self.assertRaises(TypeError, a.extend, b) # # a = array.array(self.typecode, self.example) # a.extend(self.example[::-1]) # self.assertEqual( # a, # array.array(self.typecode, self.example+self.example[::-1]) # ) # def test_constructor_with_iterable_argument(self): a = array.array(self.typecode, iter(self.example)) b = array.array(self.typecode, self.example) self.assertEqual(a, b) # non-iterable argument self.assertRaises(TypeError, array.array, self.typecode, 10) # pass through errors raised in __iter__ class A: def __iter__(self): raise UnicodeError self.assertRaises(UnicodeError, array.array, self.typecode, A()) # pass through errors raised in next() def B(): raise UnicodeError yield None self.assertRaises(UnicodeError, array.array, self.typecode, B()) def test_coveritertraverse(self): try: import gc except ImportError: self.skipTest('gc module not available') a = array.array(self.typecode) l = [iter(a)] l.append(l) gc.collect() # def test_buffer(self): # a = array.array(self.typecode, self.example) # m = memoryview(a) # expected = m.tobytes() # self.assertEqual(a.tobytes(), expected) # self.assertEqual(a.tobytes()[0], expected[0]) # # Resizing is forbidden when there are buffer exports. # # For issue 4509, we also check after each error that # # the array was not modified. # self.assertRaises(BufferError, a.append, a[0]) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, a.extend, a[0:1]) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, a.remove, a[0]) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, a.pop, 0) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, a.fromlist, a.tolist()) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, a.frombytes, a.tobytes()) # self.assertEqual(m.tobytes(), expected) # if self.typecode == 'u': # self.assertRaises(BufferError, a.fromunicode, a.tounicode()) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, operator.imul, a, 2) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, operator.imul, a, 0) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, operator.setitem, a, slice(0, 0), a) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, operator.delitem, a, 0) # self.assertEqual(m.tobytes(), expected) # self.assertRaises(BufferError, operator.delitem, a, slice(0, 1)) # self.assertEqual(m.tobytes(), expected) # # def test_weakref(self): # s = array.array(self.typecode, self.example) # p = weakref.proxy(s) # self.assertEqual(p.tobytes(), s.tobytes()) # s = None # self.assertRaises(ReferenceError, len, p) # # @unittest.skipUnless(hasattr(sys, 'getrefcount'), # 'test needs sys.getrefcount()') # def test_bug_782369(self): # for i in range(10): # b = array.array('B', range(64)) # rc = sys.getrefcount(10) # for i in range(10): # b = array.array('B', range(64)) # self.assertEqual(rc, sys.getrefcount(10)) # def test_subclass_with_kwargs(self): # SF bug #1486663 -- this used to erroneously raise a TypeError ArraySubclassWithKwargs('b', newarg=1) # def test_create_from_bytes(self): # # XXX This test probably needs to be moved in a subclass or # # generalized to use self.typecode. # a = array.array('H', b"1234") # self.assertEqual(len(a) * a.itemsize, 4) # # @support.cpython_only # def test_sizeof_with_buffer(self): # a = array.array(self.typecode, self.example) # basesize = support.calcvobjsize('Pn2Pi') # buffer_size = a.buffer_info()[1] * a.itemsize # support.check_sizeof(self, a, basesize + buffer_size) # # @support.cpython_only # def test_sizeof_without_buffer(self): # a = array.array(self.typecode) # basesize = support.calcvobjsize('Pn2Pi') # support.check_sizeof(self, a, basesize) # # def test_initialize_with_unicode(self): # if self.typecode != 'u': # with self.assertRaises(TypeError) as cm: # a = array.array(self.typecode, 'foo') # self.assertIn("cannot use a str", str(cm.exception)) # with self.assertRaises(TypeError) as cm: # a = array.array(self.typecode, array.array('u', 'foo')) # self.assertIn("cannot use a unicode array", str(cm.exception)) # else: # a = array.array(self.typecode, "foo") # a = array.array(self.typecode, array.array('u', 'foo')) class StringTest(BaseTest): def test_setitem(self): super().test_setitem() a = array.array(self.typecode, self.example) self.assertRaises(TypeError, a.__setitem__, 0, self.example[:2]) #class UnicodeTest(StringTest, unittest.TestCase): # typecode = 'u' # example = '\x01\u263a\x00\ufeff' # smallerexample = '\x01\u263a\x00\ufefe' # biggerexample = '\x01\u263a\x01\ufeff' # outside = str('\x33') # minitemsize = 2 # # def test_unicode(self): # self.assertRaises(TypeError, array.array, 'b', 'foo') # # a = array.array('u', '\xa0\xc2\u1234') # a.fromunicode(' ') # a.fromunicode('') # a.fromunicode('') # a.fromunicode('\x11abc\xff\u1234') # s = a.tounicode() # self.assertEqual(s, '\xa0\xc2\u1234 \x11abc\xff\u1234') # self.assertEqual(a.itemsize, sizeof_wchar) # # s = '\x00="\'a\\b\x80\xff\u0000\u0001\u1234' # a = array.array('u', s) # self.assertEqual( # repr(a), # "array('u', '\\x00=\"\\'a\\\\b\\x80\xff\\x00\\x01\u1234')") # # self.assertRaises(TypeError, a.fromunicode) # # def test_issue17223(self): # # this used to crash # if sizeof_wchar == 4: # # U+FFFFFFFF is an invalid code point in Unicode 6.0 # invalid_str = b'\xff\xff\xff\xff' # else: # # PyUnicode_FromUnicode() cannot fail with 16-bit wchar_t # self.skipTest("specific to 32-bit wchar_t") # a = array.array('u', invalid_str) # self.assertRaises(ValueError, a.tounicode) # self.assertRaises(ValueError, str, a) # class NumberTest(BaseTest): # def test_extslice(self): # a = array.array(self.typecode, range(5)) # self.assertEqual(a[::], a) # self.assertEqual(a[::2], array.array(self.typecode, [0,2,4])) # self.assertEqual(a[1::2], array.array(self.typecode, [1,3])) # self.assertEqual(a[::-1], array.array(self.typecode, [4,3,2,1,0])) # self.assertEqual(a[::-2], array.array(self.typecode, [4,2,0])) # self.assertEqual(a[3::-2], array.array(self.typecode, [3,1])) # self.assertEqual(a[-100:100:], a) # self.assertEqual(a[100:-100:-1], a[::-1]) # self.assertEqual(a[-100:100:2], array.array(self.typecode, [0,2,4])) # self.assertEqual(a[1000:2000:2], array.array(self.typecode, [])) # self.assertEqual(a[-1000:-2000:-2], array.array(self.typecode, [])) # # def test_delslice(self): # a = array.array(self.typecode, range(5)) # del a[::2] # self.assertEqual(a, array.array(self.typecode, [1,3])) # a = array.array(self.typecode, range(5)) # del a[1::2] # self.assertEqual(a, array.array(self.typecode, [0,2,4])) # a = array.array(self.typecode, range(5)) # del a[1::-2] # self.assertEqual(a, array.array(self.typecode, [0,2,3,4])) # a = array.array(self.typecode, range(10)) # del a[::1000] # self.assertEqual(a, array.array(self.typecode, [1,2,3,4,5,6,7,8,9])) # # test issue7788 # a = array.array(self.typecode, range(10)) # del a[9::1<<333] # def test_assignment(self): # a = array.array(self.typecode, range(10)) # a[::2] = array.array(self.typecode, [42]*5) # self.assertEqual(a, array.array(self.typecode, [42, 1, 42, 3, 42, 5, 42, 7, 42, 9])) # a = array.array(self.typecode, range(10)) # a[::-4] = array.array(self.typecode, [10]*3) # self.assertEqual(a, array.array(self.typecode, [0, 10, 2, 3, 4, 10, 6, 7, 8 ,10])) # a = array.array(self.typecode, range(4)) # a[::-1] = a # self.assertEqual(a, array.array(self.typecode, [3, 2, 1, 0])) a = array.array(self.typecode, range(10)) b = a[:] c = a[:] ins = array.array(self.typecode, range(2)) a[2:3] = ins b[slice(2,3)] = ins c[2:3:] = ins def test_iterationcontains(self): a = array.array(self.typecode, range(10)) self.assertEqual(list(a), list(range(10))) # b = array.array(self.typecode, [20]) # self.assertEqual(a[-1] in a, True) # self.assertEqual(b[0] not in a, True) def check_overflow(self, lower, upper): # method to be used by subclasses # should not overflow assigning lower limit a = array.array(self.typecode, [lower]) a[0] = lower # should overflow assigning less than lower limit self.assertRaises(OverflowError, array.array, self.typecode, [lower-1]) self.assertRaises(OverflowError, a.__setitem__, 0, lower-1) # should not overflow assigning upper limit a = array.array(self.typecode, [upper]) a[0] = upper # should overflow assigning more than upper limit self.assertRaises(OverflowError, array.array, self.typecode, [upper+1]) self.assertRaises(OverflowError, a.__setitem__, 0, upper+1) # def test_subclassing(self): # typecode = self.typecode # class ExaggeratingArray(array.array): # __slots__ = ['offset'] # # def __new__(cls, typecode, data, offset): # return array.array.__new__(cls, typecode, data) # # def __init__(self, typecode, data, offset): # self.offset = offset # # def __getitem__(self, i): # return array.array.__getitem__(self, i) + self.offset # # a = ExaggeratingArray(self.typecode, [3, 6, 7, 11], 4) # self.assertEntryEqual(a[0], 7) # # self.assertRaises(AttributeError, setattr, a, "color", "blue") # # def test_frombytearray(self): # a = array.array('b', range(10)) # b = array.array(self.typecode, a) # self.assertEqual(a, b) # class SignedNumberTest(NumberTest): example = [-1, 0, 1, 42, 0x7f] smallerexample = [-1, 0, 1, 42, 0x7e] biggerexample = [-1, 0, 1, 43, 0x7f] outside = 23 # def test_overflow(self): # a = array.array(self.typecode) # lower = -1 * int(pow(2, a.itemsize * 8 - 1)) # upper = int(pow(2, a.itemsize * 8 - 1)) - 1 # self.check_overflow(lower, upper) # class UnsignedNumberTest(NumberTest): example = [0, 1, 17, 23, 42, 0xff] smallerexample = [0, 1, 17, 23, 42, 0xfe] biggerexample = [0, 1, 17, 23, 43, 0xff] outside = 0xaa # def test_overflow(self): # a = array.array(self.typecode) # lower = 0 # upper = int(pow(2, a.itemsize * 8)) - 1 # self.check_overflow(lower, upper) # # def test_bytes_extend(self): # s = bytes(self.example) # # a = array.array(self.typecode, self.example) # a.extend(s) # self.assertEqual( # a, # array.array(self.typecode, self.example+self.example) # ) # # a = array.array(self.typecode, self.example) # a.extend(bytearray(reversed(s))) # self.assertEqual( # a, # array.array(self.typecode, self.example+self.example[::-1]) # ) # class ByteTest(SignedNumberTest, unittest.TestCase): typecode = 'b' minitemsize = 1 class UnsignedByteTest(UnsignedNumberTest, unittest.TestCase): typecode = 'B' minitemsize = 1 class ShortTest(SignedNumberTest, unittest.TestCase): typecode = 'h' minitemsize = 2 class UnsignedShortTest(UnsignedNumberTest, unittest.TestCase): typecode = 'H' minitemsize = 2 class IntTest(SignedNumberTest, unittest.TestCase): typecode = 'i' minitemsize = 2 class UnsignedIntTest(UnsignedNumberTest, unittest.TestCase): typecode = 'I' minitemsize = 2 class LongTest(SignedNumberTest, unittest.TestCase): typecode = 'l' minitemsize = 4 class UnsignedLongTest(UnsignedNumberTest, unittest.TestCase): typecode = 'L' minitemsize = 4 @unittest.skipIf(not have_long_long, 'need long long support') class LongLongTest(SignedNumberTest, unittest.TestCase): typecode = 'q' minitemsize = 8 ### # -1 ends up as 65535 in these tests ### # We can't mark using expectedFailure since function name is used as key ### # and all functions with that name would be marked (no function properties) ### def test_fromarray(self): ### raise unittest.SkipTest('FAILS on -1') ### ### def test_mul(self): ### raise unittest.SkipTest('FAILS on -1') ### ### def test_setitem(self): ### raise unittest.SkipTest('FAILS on -1') ### @unittest.skipIf(not have_long_long, 'need long long support') class UnsignedLongLongTest(UnsignedNumberTest, unittest.TestCase): typecode = 'Q' minitemsize = 8 class FPTest(NumberTest): example = [-42.0, 0, 42, 1e5, -1e10] smallerexample = [-42.0, 0, 42, 1e5, -2e10] biggerexample = [-42.0, 0, 42, 1e5, 1e10] outside = 23 def assertEntryEqual(self, entry1, entry2): self.assertAlmostEqual(entry1, entry2) # def test_byteswap(self): # a = array.array(self.typecode, self.example) # self.assertRaises(TypeError, a.byteswap, 42) # if a.itemsize in (1, 2, 4, 8): # b = array.array(self.typecode, self.example) # b.byteswap() # if a.itemsize==1: # self.assertEqual(a, b) # else: # # On alphas treating the byte swapped bit patters as # # floats/doubles results in floating point exceptions # # => compare the 8bit string values instead # self.assertNotEqual(a.tobytes(), b.tobytes()) # b.byteswap() # self.assertEqual(a, b) # class FloatTest(FPTest, unittest.TestCase): typecode = 'f' minitemsize = 4 class DoubleTest(FPTest, unittest.TestCase): typecode = 'd' minitemsize = 8 # def test_alloc_overflow(self): # from sys import maxsize # a = array.array('d', [-1]*65536) # try: # a *= maxsize//65536 + 1 # except MemoryError: # pass # else: # self.fail("Array of size > maxsize created - MemoryError expected") # b = array.array('d', [ 2.71828183, 3.14159265, -1]) # try: # b * (maxsize//3 + 1) # except MemoryError: # pass # else: # self.fail("Array of size > maxsize created - MemoryError expected") # # #if __name__ == "__main__": # unittest.main()

[ "noralf@tronnes.org" ]

noralf@tronnes.org

0b099bf370ff65eb2b99e6e3a29c31e8d1e4e3b5

5d1892f6db3c7bba1699455d934b6193840346c6

/swig/swig_example/cppfunctions.py

09785e80b6dd21e7d3ccd60aaa2a23f80b3096e8

[]

no_license

sylvaus/python_bindings

ecd6595324e73ec66753cb5c12d86788b10beaa8

ddf3ed7a59497c2f73fc47dfaa752d629ae98d99

refs/heads/master

2021-03-22T09:07:54.492561

2020-03-14T20:49:41

247,351,299

0

null

UTF-8

Python

false

7,024

py

# This file was automatically generated by SWIG (http://www.swig.org). # Version 4.0.1 # # Do not make changes to this file unless you know what you are doing--modify # the SWIG interface file instead. from sys import version_info as _swig_python_version_info if _swig_python_version_info < (2, 7, 0): raise RuntimeError("Python 2.7 or later required") # Import the low-level C/C++ module if __package__ or "." in __name__: from . import _cppfunctions else: import _cppfunctions try: import builtins as __builtin__ except ImportError: import __builtin__ def _swig_repr(self): try: strthis = "proxy of " + self.this.__repr__() except __builtin__.Exception: strthis = "" return "<%s.%s; %s >" % (self.__class__.__module__, self.__class__.__name__, strthis,) def _swig_setattr_nondynamic_instance_variable(set): def set_instance_attr(self, name, value): if name == "thisown": self.this.own(value) elif name == "this": set(self, name, value) elif hasattr(self, name) and isinstance(getattr(type(self), name), property): set(self, name, value) else: raise AttributeError("You cannot add instance attributes to %s" % self) return set_instance_attr def _swig_setattr_nondynamic_class_variable(set): def set_class_attr(cls, name, value): if hasattr(cls, name) and not isinstance(getattr(cls, name), property): set(cls, name, value) else: raise AttributeError("You cannot add class attributes to %s" % cls) return set_class_attr def _swig_add_metaclass(metaclass): """Class decorator for adding a metaclass to a SWIG wrapped class - a slimmed down version of six.add_metaclass""" def wrapper(cls): return metaclass(cls.__name__, cls.__bases__, cls.__dict__.copy()) return wrapper class _SwigNonDynamicMeta(type): """Meta class to enforce nondynamic attributes (no new attributes) for a class""" __setattr__ = _swig_setattr_nondynamic_class_variable(type.__setattr__) class SwigPyIterator(object): thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag") def __init__(self, *args, **kwargs): raise AttributeError("No constructor defined - class is abstract") __repr__ = _swig_repr __swig_destroy__ = _cppfunctions.delete_SwigPyIterator def value(self): return _cppfunctions.SwigPyIterator_value(self) def incr(self, n=1): return _cppfunctions.SwigPyIterator_incr(self, n) def decr(self, n=1): return _cppfunctions.SwigPyIterator_decr(self, n) def distance(self, x): return _cppfunctions.SwigPyIterator_distance(self, x) def equal(self, x): return _cppfunctions.SwigPyIterator_equal(self, x) def copy(self): return _cppfunctions.SwigPyIterator_copy(self) def next(self): return _cppfunctions.SwigPyIterator_next(self) def __next__(self): return _cppfunctions.SwigPyIterator___next__(self) def previous(self): return _cppfunctions.SwigPyIterator_previous(self) def advance(self, n): return _cppfunctions.SwigPyIterator_advance(self, n) def __eq__(self, x): return _cppfunctions.SwigPyIterator___eq__(self, x) def __ne__(self, x): return _cppfunctions.SwigPyIterator___ne__(self, x) def __iadd__(self, n): return _cppfunctions.SwigPyIterator___iadd__(self, n) def __isub__(self, n): return _cppfunctions.SwigPyIterator___isub__(self, n) def __add__(self, n): return _cppfunctions.SwigPyIterator___add__(self, n) def __sub__(self, *args): return _cppfunctions.SwigPyIterator___sub__(self, *args) def __iter__(self): return self # Register SwigPyIterator in _cppfunctions: _cppfunctions.SwigPyIterator_swigregister(SwigPyIterator) class IntVector(object): thisown = property(lambda x: x.this.own(), lambda x, v: x.this.own(v), doc="The membership flag") __repr__ = _swig_repr def iterator(self): return _cppfunctions.IntVector_iterator(self) def __iter__(self): return self.iterator() def __nonzero__(self): return _cppfunctions.IntVector___nonzero__(self) def __bool__(self): return _cppfunctions.IntVector___bool__(self) def __len__(self): return _cppfunctions.IntVector___len__(self) def __getslice__(self, i, j): return _cppfunctions.IntVector___getslice__(self, i, j) def __setslice__(self, *args): return _cppfunctions.IntVector___setslice__(self, *args) def __delslice__(self, i, j): return _cppfunctions.IntVector___delslice__(self, i, j) def __delitem__(self, *args): return _cppfunctions.IntVector___delitem__(self, *args) def __getitem__(self, *args): return _cppfunctions.IntVector___getitem__(self, *args) def __setitem__(self, *args): return _cppfunctions.IntVector___setitem__(self, *args) def pop(self): return _cppfunctions.IntVector_pop(self) def append(self, x): return _cppfunctions.IntVector_append(self, x) def empty(self): return _cppfunctions.IntVector_empty(self) def size(self): return _cppfunctions.IntVector_size(self) def swap(self, v): return _cppfunctions.IntVector_swap(self, v) def begin(self): return _cppfunctions.IntVector_begin(self) def end(self): return _cppfunctions.IntVector_end(self) def rbegin(self): return _cppfunctions.IntVector_rbegin(self) def rend(self): return _cppfunctions.IntVector_rend(self) def clear(self): return _cppfunctions.IntVector_clear(self) def get_allocator(self): return _cppfunctions.IntVector_get_allocator(self) def pop_back(self): return _cppfunctions.IntVector_pop_back(self) def erase(self, *args): return _cppfunctions.IntVector_erase(self, *args) def __init__(self, *args): _cppfunctions.IntVector_swiginit(self, _cppfunctions.new_IntVector(*args)) def push_back(self, x): return _cppfunctions.IntVector_push_back(self, x) def front(self): return _cppfunctions.IntVector_front(self) def back(self): return _cppfunctions.IntVector_back(self) def assign(self, n, x): return _cppfunctions.IntVector_assign(self, n, x) def resize(self, *args): return _cppfunctions.IntVector_resize(self, *args) def insert(self, *args): return _cppfunctions.IntVector_insert(self, *args) def reserve(self, n): return _cppfunctions.IntVector_reserve(self, n) def capacity(self): return _cppfunctions.IntVector_capacity(self) __swig_destroy__ = _cppfunctions.delete_IntVector # Register IntVector in _cppfunctions: _cppfunctions.IntVector_swigregister(IntVector) def plus_two_list(v): return _cppfunctions.plus_two_list(v)

[ "pierreyves.breches74@gmail.com" ]

pierreyves.breches74@gmail.com

49df7f342de48948163f94f572a958289a1e794f

442fd46c2647d4988d409563d50a841fc1cdf259

/tasks/__init__.py

1412a06ab5b6c8a385eaddc2bf7482c04fd97226

[ "MIT" ]

permissive

pycontw/mail_handler

211278ac64facd106e8a85c40d0b3b3e56ba3603

5181d7ded2a8e43c11798ceb2e77bf87b6218276

refs/heads/master

2022-12-09T15:34:21.031968

2022-04-22T22:53:16

203,540,182

10

16

MIT

2022-12-09T06:15:13

2019-08-21T08:25:24

Python

UTF-8

Python

false

308

py

from invoke import Collection from tasks import doc, env, git, secure, style, test from tasks.build import build_ns ns = Collection() ns.add_collection(env) ns.add_collection(git) ns.add_collection(test) ns.add_collection(style) ns.add_collection(build_ns) ns.add_collection(doc) ns.add_collection(secure)

[ "weilee.rx@gmail.com" ]

weilee.rx@gmail.com

e4656b2fa445618865fe0cc04e2b7a95eaf810e5

1d928c3f90d4a0a9a3919a804597aa0a4aab19a3

/python/core/2017/4/unifi.py

42b5070b0461bc90cbbea23482de85c0cd25bb7f

[]

no_license

rosoareslv/SED99

d8b2ff5811e7f0ffc59be066a5a0349a92cbb845

a062c118f12b93172e31e8ca115ce3f871b64461

refs/heads/main

2023-02-22T21:59:02.703005

2021-01-28T19:40:51

306,497,459

1

null

2020-11-24T20:56:18

2020-10-23T01:18:07

null

UTF-8

Python

false

3,383

py

""" Support for Unifi WAP controllers. For more details about this platform, please refer to the documentation at https://home-assistant.io/components/device_tracker.unifi/ """ import logging import urllib import voluptuous as vol import homeassistant.helpers.config_validation as cv import homeassistant.loader as loader from homeassistant.components.device_tracker import ( DOMAIN, PLATFORM_SCHEMA, DeviceScanner) from homeassistant.const import CONF_HOST, CONF_USERNAME, CONF_PASSWORD from homeassistant.const import CONF_VERIFY_SSL REQUIREMENTS = ['pyunifi==2.0'] _LOGGER = logging.getLogger(__name__) CONF_PORT = 'port' CONF_SITE_ID = 'site_id' DEFAULT_HOST = 'localhost' DEFAULT_PORT = 8443 DEFAULT_VERIFY_SSL = True NOTIFICATION_ID = 'unifi_notification' NOTIFICATION_TITLE = 'Unifi Device Tracker Setup' PLATFORM_SCHEMA = PLATFORM_SCHEMA.extend({ vol.Optional(CONF_HOST, default=DEFAULT_HOST): cv.string, vol.Optional(CONF_SITE_ID, default='default'): cv.string, vol.Required(CONF_PASSWORD): cv.string, vol.Required(CONF_USERNAME): cv.string, vol.Required(CONF_PORT, default=DEFAULT_PORT): cv.port, vol.Optional(CONF_VERIFY_SSL, default=DEFAULT_VERIFY_SSL): cv.boolean, }) def get_scanner(hass, config): """Set up the Unifi device_tracker.""" from pyunifi.controller import Controller host = config[DOMAIN].get(CONF_HOST) username = config[DOMAIN].get(CONF_USERNAME) password = config[DOMAIN].get(CONF_PASSWORD) site_id = config[DOMAIN].get(CONF_SITE_ID) port = config[DOMAIN].get(CONF_PORT) verify_ssl = config[DOMAIN].get(CONF_VERIFY_SSL) persistent_notification = loader.get_component('persistent_notification') try: ctrl = Controller(host, username, password, port, version='v4', site_id=site_id, ssl_verify=verify_ssl) except urllib.error.HTTPError as ex: _LOGGER.error("Failed to connect to Unifi: %s", ex) persistent_notification.create( hass, 'Failed to connect to Unifi. ' 'Error: {}<br />' 'You will need to restart hass after fixing.' ''.format(ex), title=NOTIFICATION_TITLE, notification_id=NOTIFICATION_ID) return False return UnifiScanner(ctrl) class UnifiScanner(DeviceScanner): """Provide device_tracker support from Unifi WAP client data.""" def __init__(self, controller): """Initialize the scanner.""" self._controller = controller self._update() def _update(self): """Get the clients from the device.""" try: clients = self._controller.get_clients() except urllib.error.HTTPError as ex: _LOGGER.error("Failed to scan clients: %s", ex) clients = [] self._clients = {client['mac']: client for client in clients} def scan_devices(self): """Scan for devices.""" self._update() return self._clients.keys() def get_device_name(self, mac): """Return the name (if known) of the device. If a name has been set in Unifi, then return that, else return the hostname if it has been detected. """ client = self._clients.get(mac, {}) name = client.get('name') or client.get('hostname') _LOGGER.debug("Device %s name %s", mac, name) return name

[ "rodrigosoaresilva@gmail.com" ]

rodrigosoaresilva@gmail.com

e549afef111dba3869240fa2b3c410db40d5f07c

e6fea6eb27c169642454674f20e6b2db0dc2f738

/word2vec/get_close_words.py

8cd7902e4b7dc56529a133344553ebabbe2ca9bd

[]

no_license

muntakimrafi/insbcn

1db79e03cf6440f57da90a6e4fa8f047bee63d38

25e1b8394d1727a792591f5fb3f9e309e245cc50

refs/heads/master

2021-03-25T13:45:17.047609

2018-08-03T10:40:12

null

0

null

UTF-8

Python

false

1,245

py

from gensim import models lans = ['en','es','ca'] model_name = 'word2vec_model_instaBarcelona_lan.model' model_path = '../../../datasets/instaBarcelona/models/word2vec/' + model_name models_list = [] print "Loading models ... " for l in lans: models_list.append(models.Word2Vec.load(model_path.replace('lan',l))) # districts = ['surf','ciutatvella', 'eixample', 'santsmontjuic', 'lescorts', 'sarria', 'gracia', 'hortaguinardo', 'noubarris', 'santandreu', 'santmarti'] # districts += ['poblenou','poblesec','sagradafamilia','barceloneta','gothic','vallcarca','gotic','gotico','viladegracia','viladegracia','vallvidrera','diagonalmar','raval','born','borne'] # districts = ['elborn','santmarti','poblesec','barceloneta','gothic','vallcarca','gotic','gotico','born','raval','sants','poblenou','vallcarca','viladegracia','gracia','sagradafamilia','vallvidrera'] districts = ['poblesec','poblenou','born'] print "Checking models" for d in districts: print '\n' + d for m in models_list: try: topw = m.wv.most_similar(positive=[d], topn=30) except: topw = [('Not in voc','')] toprint = '' for w in topw: toprint += str(w[0]) + ' ' print toprint print "DONE"

[ "raulgombru@gmail.com" ]

raulgombru@gmail.com

ac2872f4a29ec3412b06173421e13d01004ea1da

3536c71ef08e52088a10e1b62e943386e32ccc1e

/docs/conf.py

6feb5b7f670bbd6f19eb7ad996857aa5ed817a20

[ "Apache-2.0" ]

permissive

Aspire1Inspire2/tdameritrade

66698ef9a1444f930bf9a57f29d233d3f1e5215a

00d93ca355b7f4f9a7f5041ea5096e9b6f3bb228

refs/heads/master

2020-05-17T11:30:48.443511

2019-04-03T21:29:42

null

0

null

UTF-8

Python

false

5,287

py

#!/usr/bin/env python3 # -*- coding: utf-8 -*- # # tdameritrade documentation build configuration file, created by # sphinx-quickstart on Fri Jan 12 22:07:11 2018. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All configuration values have a default; values that are commented out # serve to show the default. # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # # import os # import sys # sys.path.insert(0, os.path.abspath('.')) import sphinx_rtd_theme # -- General configuration ------------------------------------------------ # If your documentation needs a minimal Sphinx version, state it here. # # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = ['sphinx.ext.coverage', 'sphinx.ext.viewcode'] # Add any paths that contain templates here, relative to this directory. templates_path = ['_templates'] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # # source_suffix = ['.rst', '.md'] source_suffix = '.rst' # The master toctree document. master_doc = 'index' # General information about the project. project = 'tdameritrade' copyright = '2018, Tim Paine' author = 'Tim Paine' # The version info for the project you're documenting, acts as replacement for # |version| and |release|, also used in various other places throughout the # built documents. # # The short X.Y version. version = 'v0.0.8' # The full version, including alpha/beta/rc tags. release = 'v0.0.8' # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This patterns also effect to html_static_path and html_extra_path exclude_patterns = ['_build', 'Thumbs.db', '.DS_Store'] # The name of the Pygments (syntax highlighting) style to use. pygments_style = 'sphinx' # If true, `todo` and `todoList` produce output, else they produce nothing. todo_include_todos = False # -- Options for HTML output ---------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # # html_theme = 'alabaster' html_theme = "sphinx_rtd_theme" html_theme_path = [sphinx_rtd_theme.get_html_theme_path()] # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # # html_theme_options = {} # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ['_static'] # Custom sidebar templates, must be a dictionary that maps document names # to template names. # # This is required for the alabaster theme # refs: http://alabaster.readthedocs.io/en/latest/installation.html#sidebars html_sidebars = { '**': [ 'relations.html', # needs 'show_related': True theme option to display 'searchbox.html', ] } # -- Options for HTMLHelp output ------------------------------------------ # Output file base name for HTML help builder. htmlhelp_basename = 'tdameritradedoc' # -- Options for LaTeX output --------------------------------------------- latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ (master_doc, 'tdameritrade.tex', 'tdameritrade Documentation', 'Tim Paine', 'manual'), ] # -- Options for manual page output --------------------------------------- # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [ (master_doc, 'tdameritrade', 'tdameritrade Documentation', [author], 1) ] # -- Options for Texinfo output ------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ (master_doc, 'tdameritrade', 'tdameritrade Documentation', author, 'tdameritrade', 'One line description of project.', 'Miscellaneous'), ]

[ "t.paine154@gmail.com" ]

t.paine154@gmail.com

5f8e18df7e9043614b5b0ecf4d2dfbb9fdbba54b

a0dda8be5892a390836e19bf04ea1d098e92cf58

/叶常春视频例题/chap07/7-3-1-用while检测列表为空.py

07d112954fbb6a310ba170b0ffbb0422ca5eee39

[]

no_license

wmm98/homework1

d9eb67c7491affd8c7e77458ceadaf0357ea5e6b

cd1f7f78e8dbd03ad72c7a0fdc4a8dc8404f5fe2

refs/heads/master

2020-04-14T19:22:21.733111

2019-01-08T14:09:58

164,055,018

1

0

null

UTF-8

Python

false

722

py

#例7-3-1 用while语句检测列表是否为空 # 首先，创建一个待验证用户列表 # 和一个用于存储已验证用户的空列表 unconfirmed_users = ['alice', 'brian', 'candace'] confirmed_users = [] # 验证每个用户，直到没有未验证用户为止 # 将每个经过验证的列表都移到已验证用户列表中 while unconfirmed_users: #当unconfirmed_users列表不为空，则... current_user = unconfirmed_users.pop() print("正在验证用户: " + current_user.title()) #模仿验证用户动作 confirmed_users.append(current_user) # 显示所有已验证的用户 print("\n以下用户验证通过:") for confirmed_user in confirmed_users: print(confirmed_user.title())

[ "792545884@qq.com" ]

792545884@qq.com

34d2334c3931b648f94be9e0a25b6ca4b2b4d527

0042c37405a7865c50b7bfa19ca531ec36070318

/20_selenium/test_incontrol/incontrol_picture.py

b06cfca4773c8ba95547cdb313b520192666e3fb

[]

no_license

lu-judong/untitled1

b7d6e1ad86168673283917976ef0f5c2ad97d9e0

aa158e7541bae96332633079d67b5ab19ea29e71

refs/heads/master

2022-05-23T18:55:45.272216

2020-04-28T09:55:38

257,822,681

0

null

UTF-8

Python

false

5,831

py

from selenium import webdriver from new_selenium.bin.login import Login from new_selenium.bin.main import Method import time from new_selenium.tech_incontrol.incontrol_config import * from config.config import path_dir from config.log_config import logger class Fault: def log_file_out(self,msg): fo = open(r'{}/usecase.txt'.format(path_dir), mode='a', encoding='utf-8') fo.write(msg + '\r\n') fo.close() def picture(self,url,username,password): driver = webdriver.Chrome() Login().login(url,username, password, driver) self.log_file_out('-----内控指标图表点击-----') for i in contents: try: Method(driver).contains_xpath('click',i) time.sleep(2) self.log_file_out('点击'+i+'成功') except Exception as e: logger.error(e) self.log_file_out('点击' + i + '失败') try: Method(driver).switch_out() Method(driver).switch_iframe( driver.find_element_by_xpath("//iframe[contains(@src,'/darams/a/inControl')]")) self.log_file_out('切入内控指标成功') except: self.log_file_out('切入内控指标失败') driver.find_element_by_xpath("//a[contains(text(),\'{}\')]/../../td[7]/a[1]".format('111')).click() time.sleep(2) Method(driver).switch_out() driver.find_element_by_class_name('layui-layer-btn0').click() time.sleep(2) Method(driver).switch_out() Method(driver).switch_iframe( driver.find_element_by_xpath("//iframe[contains(@src,'/darams/a/inControl')]")) time.sleep(5) driver.find_element_by_xpath("//a[contains(text(),\'{}\')]/../../td[7]/a[2]".format('111')).click() Method(driver).switch_out() incontrol_p = Method(driver).get_attr('css', "[class='layui-layer layui-layer-iframe']", 'times') Method(driver).switch_iframe('layui-layer-iframe' + incontrol_p) home_handles = driver.current_window_handle time.sleep(2) value_com = driver.execute_script('var aa = echarts.getInstanceByDom($("#myChart2")[0]);' \ 'var option = aa.getOption();' \ 'return [option.series[0].data[0].value[0]]') js1 = 'myChart2.trigger("dblclick",{"data":{"path":"苏州华兴致远电子科技有限公司"},"componentType":"series","seriesType":"treemap"})' try: driver.execute_script(js1) self.log_file_out('点击供应商内控指标图表成功') except: self.log_file_out('点击供应商内控指标图表失败') time.sleep(2) all_handle = driver.window_handles for i in all_handle: if i != home_handles: driver.switch_to.window(i) driver.find_element_by_xpath('/html/body/div[1]/div/div[2]/div[2]/div[1]/div[2]/button[1]').click() time.sleep(10) # for i in range(0,len(driver.find_elements_by_xpath('//*[@id="opFaultOrderTable"]/tbody/tr/td[12]'))): # print(driver.find_elements_by_xpath('//*[@id="opFaultOrderTable"]/tbody/tr/td[12]')[i].text) status_aa = driver.execute_script( 'return $("#opFaultOrderTable").bootstrapTable("getData").map(function(row){return $(row).attr("mainResponsibility")}).some(function(item){return item !="苏州华兴致远电子科技有限公司"})') value_com1 = driver.execute_script('return $("#opFaultOrderTable").bootstrapTable("getData").map(function(row){return $(row).attr("mainResponsibility")}).length') if status_aa is False and value_com[0] == value_com1: self.log_file_out('主要责任单位数值正确') else: self.log_file_out('主要责任单位数值不正确') for i in all_handle: if i != home_handles: driver.close() driver.switch_to.window(home_handles) time.sleep(2) # Method(driver).click('id','chart2') # js1 = 'var aa = echarts.getInstanceByDom($("#chart2")[0]);' \ # 'var option = aa.getOption();' \ # 'param = {componentType:"series",name:option.yAxis[0].data[0],seriesName:"关联故障",seriesType:"bar",value:option.series[0].data[0]}; ' \ # 'skipTo(param, "RAILWAY_BUREAU");' js2 = 'var title = "2017-07责任部室故障统计";' \ 'var dateString = title.substring(0,title.length-8);' \ 'if (dateString.length > 7){' \ 'window.open ("/darams/a/fault/opFaultOrder/qList?confModelId=ed42931a637744a0a11141ccaccfd40b000 &chartType=INSIDE&depart=" + "转向架开发部");}else{window.open("/darams/a/fault/opFaultOrder/qList?confModelId=ed42931a637744a0a11141ccaccfd40b000&chartType=INSIDE&depart=" + "转向架开发部" + "&octMonthFrom=" + dateString + "&octMonthTo=" + dateString);}' try: driver.execute_script(js2) self.log_file_out('点击责任部室图表成功') except: self.log_file_out('点击责任部室图表失败') time.sleep(2) all_handle1 = driver.window_handles for i in all_handle1: if i != home_handles: driver.switch_to.window(i) status_bb = driver.execute_script( 'return $("#opFaultOrderTable").bootstrapTable("getData").map(function(row){return $(row).attr("mainResponsibility")}).some(function(item){return item !="技术中心"})') if status_bb is False: self.log_file_out('责任部室验证正确') else: self.log_file_out('责任部室验证不正确') url = 'http://192.168.1.115:8080/darams/a?login' Fault().picture(url, 'test', '1234')

[ "ljd_python@163.com" ]

ljd_python@163.com

d5acc9da01fcf37cdad10fb33e9391c39115bb87

b68c92fe89b701297f76054b0f284df5466eb698

/Sorting/InsertionSort.py

c42a74592fdfb36e35685e6e8cbc61a47c65daaa

[]

no_license

makrandp/python-practice

32381a8c589f9b499ab6bde8184a847b066112f8

60218fd79248bf8138158811e6e1b03261fb38fa

refs/heads/master

2023-03-27T18:11:56.066535

2021-03-28T04:02:00

null

0

null

UTF-8

Python

false

690

py

# Insertion sort is an algorithm that functions by iterating from 0 to n where n is the size of the input dataset # For every iteration of i from 0 to n, we then swap from i to 0 given a situation where the variable is swappable ## Best ## Avrg ## Wrst ## Spce ## ## n # n^2 # n^2 # 1 ## # Insertion sort is still bad, but it is stable and has a best case time complexity of n and a space complexity of 1 from typing import List def insertionSort(arr: List[int]): for i in range(1,len(arr)): for j in range(i,0,-1): if arr[j] < arr[j - 1]: arr[j], arr[j-1] = arr[j-1], arr[j] a = [5,2,7,9,0,1,3,4,2,15,25,35] insertionSort(a) print(a)

[ "awalexweber99@gmail.com" ]

awalexweber99@gmail.com

f74f921086196d7e6c01a153fed48f3f0806ffdb

d1ff466d7a230409020ebc88aa2f2ffac8c45c15

/cournot/pages.py

68eecd9c2f47d2ed52156f48cc24aadc29827df9

[ "MIT" ]

permissive

Muhammadahmad06/oTree

224ef99a2ca55c8f2d7e67fec944b8efd0b21884

789fb2c2681aa5fbb8385f2f65a633e02592b225

refs/heads/master

2020-08-25T19:12:36.929702

2019-10-03T09:29:54

null

0

null

UTF-8

Python

false

641

py

from ._builtin import Page, WaitPage from otree.api import Currency as c, currency_range from .models import Constants class Introduction(Page): pass class Decide(Page): form_model = 'player' form_fields = ['units'] class ResultsWaitPage(WaitPage): body_text = "Waiting for the other participant to decide." def after_all_players_arrive(self): self.group.set_payoffs() class Results(Page): def vars_for_template(self): return dict( other_player_units=self.player.other_player().units, ) page_sequence = [ Introduction, Decide, ResultsWaitPage, Results ]

[ "chris@otree.org" ]

chris@otree.org

2a321a878b13ab2bbf4750762e7d6976c44ab082

98b4aeadab444eaf6f0d5b469c199e6d24a52f7f

/step14/1904-2.py

b257545f762791c40187c81b554b1391356d7d8d

[]

no_license

kwr0113/BOJ_Python

7a9dc050bb3bb42ae2b03671c5d6fa76cc0d6d99

27bafdaafc44115f55f0b058829cb36b8c79469a

refs/heads/master

2023-06-10T23:22:20.639613

2021-06-25T07:25:53

328,057,859

0

null

UTF-8

Python

false

104

py

# 1904-2.py n = int(input()) a, b = 1, 2 for _ in range(n-1): a, b = b, (a + b) % 15746 print(a)

[ "kwr0113@gmail.com" ]

kwr0113@gmail.com

cff5b0ce9bad60d2be0a2346e00bfc63ed894ca8

6eea60bcbf206dafc5fe578b996267ce2bc9ae6e

/interviewbit/Magician_and_Chocolates.py

5949fe44831449b74974a2e3381a8c91ec4d1949

[]

no_license

SueAli/cs-problems

491fef79f3e352d7712cd622d3b80ec15d38642b

b321116d135f868d88bd849b5ea7172feb74fb4c

refs/heads/master

2023-08-31T10:46:30.374394

2023-08-24T20:14:04

95,930,918

0

null

UTF-8

Python

false

725

py

import heapq import math class Solution: # @param A : integer # @param B : list of integers # @return an integer # Time complexity is O(n) + k * log (n) # Space Complexity if we can not make any changes in the input array, extra space memory of O(n) will be # required to build the heap def nchoc(self, A, B): r =0 m = ((10**9)+7) h = [ item * -1 for item in B] # O(n) heapq.heapify(h) # O(n) for i in range(0,A): curr = h[0] * -1 r = r + curr heapq.heapreplace(h,-1 *int(math.floor(curr/2.))) #(log n) return int(r) % m s = Solution() print s.nchoc(10, [ 2147483647, 2000000014, 2147483647 ]) #284628164

[ "souad.hassanien@gmail.com" ]

souad.hassanien@gmail.com

19a0fd4d3939243857e88c8327c49561837841ab

d05a59feee839a4af352b7ed2fd6cf10a288a3cb

/xlsxwriter/test/comparison/test_textbox29.py

46aabfa9a927938c6129ee8a9c355269cb61109c

[ "BSD-2-Clause-Views" ]

permissive

elessarelfstone/XlsxWriter

0d958afd593643f990373bd4d8a32bafc0966534

bb7b7881c7a93c89d6eaac25f12dda08d58d3046

refs/heads/master

2020-09-24T06:17:20.840848

2019-11-24T23:43:01

225,685,272

1

0

NOASSERTION

2019-12-03T18:09:06

2019-12-03T18:09:05

null

UTF-8

Python

false

798

py

############################################################################### # # Tests for XlsxWriter. # # Copyright (c), 2013-2019, John McNamara, jmcnamara@cpan.org # from ..excel_comparsion_test import ExcelComparisonTest from ...workbook import Workbook class TestCompareXLSXFiles(ExcelComparisonTest): """ Test file created by XlsxWriter against a file created by Excel. """ def setUp(self): self.set_filename('textbox29.xlsx') def test_create_file(self): """Test the creation of a simple XlsxWriter file with textbox(s).""" workbook = Workbook(self.got_filename) worksheet = workbook.add_worksheet() worksheet.insert_textbox('E9', None, {'textlink': '=$A$1'}) workbook.close() self.assertExcelEqual()

[ "jmcnamara@cpan.org" ]

jmcnamara@cpan.org

bd23ea04dc04e328739dd86a97a65296c5e7aa4e

3d91c09bca4e68bf7a527cb40ed70ac208495b93

/library/templatetags/get_lended.py

dc9e1d23ec96ed29f427b8fd2cf57aa40028802e

[]

no_license

Kaik-a/OCR-Projet13

02e9d8c9228d6d7a09013b4ab2570304c01dfc28

ac339002279397f43316e33a869cce797b5d92b2

refs/heads/main

2023-02-17T09:39:11.184120

2021-01-11T15:50:58

311,875,691

0

null

2021-01-11T15:50:59

2020-11-11T05:51:34

CSS

UTF-8

Python

false

590

py

"""Get lended games""" from typing import Union from django import template from django.core.exceptions import ObjectDoesNotExist from library.models import LendedGame register = template.Library() @register.filter(name="get_lended") def get_lended(owned_game_id) -> Union[LendedGame, bool]: """ Get lended games. :param owned_game_id: id of game owned :rtype: Union[LendedGame, bool] """ try: lended_game = LendedGame.objects.get(owned_game=owned_game_id, returned=False) return lended_game except ObjectDoesNotExist: return False

[ "mehdi.bichari@outscale.com" ]

mehdi.bichari@outscale.com

a73af9fd8e5bfce2037b80001cd6b910eba5b8f4

ca7aa979e7059467e158830b76673f5b77a0f5a3

/Python_codes/p03272/s726182121.py

b242fec41d8d3b81d3bed6415bd6e16cc9349c97

[]

no_license

Aasthaengg/IBMdataset

7abb6cbcc4fb03ef5ca68ac64ba460c4a64f8901

f33f1c5c3b16d0ea8d1f5a7d479ad288bb3f48d8

refs/heads/main

2023-04-22T10:22:44.763102

2021-05-13T17:27:22

367,112,348

0

null

UTF-8

Python

false

59

py

n ,i = map(int, input().split()) res = n - i + 1 print(res)

[ "66529651+Aastha2104@users.noreply.github.com" ]

66529651+Aastha2104@users.noreply.github.com

87a207a046ec88b78484e7b0c816fccf6e4be3bc

ea05a89f4df49323eb630960c31bfbf3eb812e48

/events/migrations/0001_initial.py

7bae2e4599ed9154b47d3475390f388f1749a0db

[]

no_license

psteichen/aperta-cms-lts

3dff06fbf17e4a8c4a124c826b36f083451d613e

cf46e82cd71e7acddb900e558bc155cdd7999d9c

refs/heads/master

2021-01-20T00:08:06.012978

2017-08-11T13:58:10

89,083,140

0

null

UTF-8

Python

false

1,654

py

# -*- coding: utf-8 -*- # Generated by Django 1.11 on 2017-04-23 16:28 from __future__ import unicode_literals from django.db import migrations, models import django.db.models.deletion import events.models class Migration(migrations.Migration): initial = True dependencies = [ ('locations', '0001_initial'), ] operations = [ migrations.CreateModel( name='Event', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=100, verbose_name='Titre')), ('when', models.DateField(verbose_name='Date')), ('time', models.TimeField(verbose_name='Heure de début')), ('deadline', models.DateTimeField(verbose_name='Deadline')), ('location', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='locations.Location', verbose_name='Lieu')), ], ), migrations.CreateModel( name='Invitation', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('message', models.CharField(blank=True, max_length=5000, null=True)), ('attachement', models.FileField(blank=True, null=True, upload_to=events.models.rename_attach, verbose_name='Annexe(s)')), ('sent', models.DateTimeField(blank=True, null=True)), ('event', models.ForeignKey(on_delete=django.db.models.deletion.CASCADE, to='events.Event')), ], ), ]

[ "pst@libre.lu" ]

pst@libre.lu

6ccd0fd80e07bc2409e0b4c4d5708a7161fb5fa9

6b1b506139088aa30de9fd65cff9e3b6a3a36874

/sofia_redux/instruments/hawc/steps/__init__.py

dac31389261c9c2edcb7bfdcbb30788994698992

[ "BSD-3-Clause", "LicenseRef-scancode-unknown-license-reference" ]

permissive

SOFIA-USRA/sofia_redux

df2e6ad402b50eb014b574ea561734334d70f84d

493700340cd34d5f319af6f3a562a82135bb30dd

refs/heads/main

2023-08-17T11:11:50.559987

2023-08-13T19:52:37

311,773,000

12

2

null

UTF-8

Python

false

3,262

py

# Licensed under a 3-clause BSD style license - see LICENSE.rst __all__ = ['StepBinPixels', 'StepBgSubtract', 'StepCalibrate', 'StepCheckhead', 'StepCombine', 'StepDemodulate', 'StepDmdCut', 'StepDmdPlot', 'StepFlat', 'StepFluxjump', 'StepFocus', 'StepImgMap', 'StepIP', 'StepLabChop', 'StepLabPolPlots', 'StepMerge', 'StepMkflat', 'StepNodPolSub', 'StepNoiseFFT', 'StepNoisePlots', 'StepOpacity', 'StepPolDip', 'StepPolMap', 'StepPolVec', 'StepPrepare', 'StepRegion', 'StepRotate', 'StepScanMap', 'StepScanMapFlat', 'StepScanMapFocus', 'StepScanMapPol', 'StepScanStokes', 'StepShift', 'StepSkycal', 'StepSkydip', 'StepSplit', 'StepStdPhotCal', 'StepStokes', 'StepWcs', 'StepZeroLevel'] from sofia_redux.instruments.hawc.steps.stepbinpixels import * from sofia_redux.instruments.hawc.steps.stepbgsubtract import * from sofia_redux.instruments.hawc.steps.stepcalibrate import * from sofia_redux.instruments.hawc.steps.stepcheckhead import * from sofia_redux.instruments.hawc.steps.stepcombine import * from sofia_redux.instruments.hawc.steps.stepdemodulate import * from sofia_redux.instruments.hawc.steps.stepdmdcut import * from sofia_redux.instruments.hawc.steps.stepdmdplot import * from sofia_redux.instruments.hawc.steps.stepflat import * from sofia_redux.instruments.hawc.steps.stepfluxjump import * from sofia_redux.instruments.hawc.steps.stepfocus import * from sofia_redux.instruments.hawc.steps.stepimgmap import * from sofia_redux.instruments.hawc.steps.stepip import * from sofia_redux.instruments.hawc.steps.steplabchop import * from sofia_redux.instruments.hawc.steps.steplabpolplots import * from sofia_redux.instruments.hawc.steps.stepmerge import * from sofia_redux.instruments.hawc.steps.stepmkflat import * from sofia_redux.instruments.hawc.steps.stepnodpolsub import * from sofia_redux.instruments.hawc.steps.stepnoisefft import * from sofia_redux.instruments.hawc.steps.stepnoiseplots import * from sofia_redux.instruments.hawc.steps.stepopacity import * from sofia_redux.instruments.hawc.steps.steppoldip import * from sofia_redux.instruments.hawc.steps.steppolmap import * from sofia_redux.instruments.hawc.steps.steppolvec import * from sofia_redux.instruments.hawc.steps.stepprepare import * from sofia_redux.instruments.hawc.steps.stepregion import * from sofia_redux.instruments.hawc.steps.steprotate import * from sofia_redux.instruments.hawc.steps.stepscanstokes import * from sofia_redux.instruments.hawc.steps.stepscanmap import * from sofia_redux.instruments.hawc.steps.stepscanmapflat import * from sofia_redux.instruments.hawc.steps.stepscanmapfocus import * from sofia_redux.instruments.hawc.steps.stepscanmappol import * from sofia_redux.instruments.hawc.steps.stepshift import * from sofia_redux.instruments.hawc.steps.stepskycal import * from sofia_redux.instruments.hawc.steps.stepskydip import * from sofia_redux.instruments.hawc.steps.stepsplit import * from sofia_redux.instruments.hawc.steps.stepstdphotcal import * from sofia_redux.instruments.hawc.steps.stepstokes import * from sofia_redux.instruments.hawc.steps.stepwcs import * from sofia_redux.instruments.hawc.steps.stepzerolevel import *

[ "melanie.j.clarke@nasa.gov" ]

melanie.j.clarke@nasa.gov

5aa75852540563db657a5c4fe15b75e585fcdfa2

37dd16e4e48511e5dab789c57d97ab47ccffd561

/src/apps/domain/engagement_assignment/admin.py

b5e547f63e46b70a8c0c61b622b47c81dc3b62fd

[]

no_license

willow/scone-api

c9473a043996639024ae028bb3d7bf420eb3d75b

c786915bc0535cb0ed78726afa4ee3c0772a8c0e

refs/heads/production

2016-09-05T18:43:22.953283

2014-08-18T23:16:47

2014-08-18T23:18:23

18,448,114

1

0

null

2014-08-08T16:40:35

2014-04-04T18:21:18

Python

UTF-8

Python

false

769

py

from django.contrib import admin from src.apps.domain.engagement_assignment.models import AssignedProspect class AssignedProspectAdmin(admin.ModelAdmin): actions = None def has_delete_permission(self, request, obj=None): return False def has_add_permission(self, request): return False # Allow viewing objects but not actually changing them # https://gist.github.com/aaugustin/1388243 def has_change_permission(self, request, obj=None): if request.method not in ('GET', 'HEAD'): return False return super().has_change_permission(request, obj) def get_readonly_fields(self, request, obj=None): return (self.fields or [f.name for f in self.model._meta.fields]) admin.site.register(AssignedProspect, AssignedProspectAdmin)

[ "scoarescoare@gmail.com" ]

scoarescoare@gmail.com

122fdbad2d4235c0448a9c191ffe41de3a7b7478

fa064f5ef48b29dcf2e90d9e4e30199a32c5e2af

/case/theater/myparser/legacy.py

97480ea593d418b0cf66e9aafc17bc502f89c3bf

[]

no_license

gsrr/Crawler

ed05971bf6be31f6dae32d6e82bbae9cb93a8d02

1e109eeaaf518e699e591fa8e72909e6f965be0c

refs/heads/master

2020-04-07T06:40:08.492069

2017-06-13T03:42:04

44,025,883

27

5

null

UTF-8

Python

false

5,099

py

# -*- coding: utf-8 -*- import mylib import re import urlparse import urllib import parseplatform import copy def getContent(data, item): if item == "price": return data.replace("<span class='ticket_content'></span>", ",").replace("<br />", "\n") return data class Parser: def __init__(self, paras): self.url = paras['url'] self.queue = [] def extractTitle(self, data): searchObj = re.search(r'alt="(.*?)"', data , re.M|re.I|re.S) return searchObj.group(1) def extractImage(self, data): searchObj = re.search(r'src="(.*?)"', data , re.M|re.I|re.S) return searchObj.group(1) def extractURL(self, data): searchObj = re.search(r'href="(.*?)"', data , re.M|re.I|re.S) return urlparse.urljoin(self.url, searchObj.group(1)) def download(self, url_content, url_image): file_id = url_content.split("/")[-1] with open("image/%s"%file_id, "w") as fw: fr = urllib.urlopen(url_image) data = fr.read() fw.write(data) return file_id def extractPoster(self, data): contents = [] items = re.findall(r'<a class="poster"(.*?)</a>', data , re.M|re.I|re.S) for item in items: content = {} content['url_content'] = self.extractURL(item) content['title'] = self.extractTitle(item) content['url_image'] = self.extractImage(item) #download image content['image_id'] = self.download(content['url_content'], content['url_image']) contents.append(copy.deepcopy(content)) return contents def extractPrice(self, data, contents): data_dic = { "票價" : "price", "場地" : "place", "開始" : "start_time", } items = re.findall(r'<th>(.*?)</th><td>(.*?)</td>', data , re.M|re.I|re.S) cnt = 0 for item in items: if item[0] in data_dic.keys(): content = contents[cnt/3] content[data_dic[item[0]]] = getContent(item[1], data_dic[item[0]]) cnt += 1 else: pass def extractDate(self, data, contents): items = re.findall(r'<div class="m">(.*?)</div>(.*?)<div class="d">(.*?)</div>(.*?)<div class="week">(.*?)</div>', data , re.M|re.I|re.S) cnt = 0 for item in items: content = contents[cnt] content["start_date"] = item[0] + "/" + item[2] cnt += 1 def _parse_content(self, url, content): print url data = mylib.myurl(url) data_ret = "" place = 0 price = 0 start_date = 0 start_time = 0 for line in data: if "<title>" in line: searchObj = re.search(r'<title>(.*?)</title>', line , re.M|re.I|re.S) if searchObj: content['title'] = searchObj.group(1) if "alignnone" in line: searchObj = re.search(r'src="(.*?)"', line , re.M|re.I|re.S) if searchObj: content['url_image'] = searchObj.group(1) content['image_id'] = searchObj.group(1).split("/")[-1] if place == 1 and "</p>" in line: content['place'] = line.strip().rstrip("</p>") place = 0 if price == 1 and '</p>' in line: content['price'] = line.strip().rstrip("</p>") price = 0 if start_date == 1 and '</p>' in line: content['start_date'] = line.strip().rstrip("</p>") start_date = 0 if start_time == 1 and '</p>' in line: content['start_time'] = line.strip().rstrip("</p>") start_time = 0 if "演出場地" in line: place = 1 if "演出票價" in line: price = 1 if "演出日期" in line: start_date = 1 if "演出開始" in line: start_time = 1 def parse(self): data = mylib.myurl(self.url) data_ret = "" contents = [] for line in data: if "galleries-slide-sub-title1" in line: concert = {} concert['url_content'] = self.extractURL(line) self._parse_content(concert['url_content'], concert) contents.append(copy.deepcopy(concert)) self.write(contents) def write(self, data): with open("result/legacy.result", "a") as fw: for content in data: fw.write("--start--\n") for key in content.keys(): if key == "price": fw.write(key + "=" + content[key].replace("\n", "::") + "\n") else: fw.write(key + "=" + content[key] + "\n") fw.write("--end--\n\n") def start(self): return self.parse()

[ "jerrycheng1128@gmail.com" ]

jerrycheng1128@gmail.com

b0e8975a3841436d1056fbc76ca39921dc2e3f5b

ad13583673551857615498b9605d9dcab63bb2c3

/output/instances/nistData/atomic/token/Schema+Instance/NISTXML-SV-IV-atomic-token-enumeration-3-2.py

617a90346e1a437b02be47eb86f0aa348ed0dd9c

[ "MIT" ]

permissive

tefra/xsdata-w3c-tests

397180205a735b06170aa188f1f39451d2089815

081d0908382a0e0b29c8ee9caca6f1c0e36dd6db

refs/heads/main

2023-08-03T04:25:37.841917

2023-07-29T17:10:13

2023-07-30T12:11:13

239,622,251

2

0

MIT

2023-07-25T14:19:04

2020-02-10T21:59:47

Python

UTF-8

Python

false

511

py

from output.models.nist_data.atomic.token.schema_instance.nistschema_sv_iv_atomic_token_enumeration_3_xsd.nistschema_sv_iv_atomic_token_enumeration_3 import NistschemaSvIvAtomicTokenEnumeration3 from output.models.nist_data.atomic.token.schema_instance.nistschema_sv_iv_atomic_token_enumeration_3_xsd.nistschema_sv_iv_atomic_token_enumeration_3 import NistschemaSvIvAtomicTokenEnumeration3Type obj = NistschemaSvIvAtomicTokenEnumeration3( value=NistschemaSvIvAtomicTokenEnumeration3Type.STANDARDIZATION )

[ "tsoulloftas@gmail.com" ]

tsoulloftas@gmail.com

d61c6018bc90c2c057e06d9f8d891a4a72b7b642

77f63e447ef93bd77ce4315b6d4220da86abffdf

/setup.py

cf8f789dcd9fdad981b8de82177b1b99dc6dbd2a

[ "WTFPL" ]

permissive

wsxxhx/TorchSUL

8d1625989b5f5ef5aeb879e01019ddf850848961

46ee6aab4367d8a02ddb6de66d24455dbfa465c4

refs/heads/master

2023-05-25T16:52:10.321801

2021-06-12T09:34:56

null

0

null

UTF-8

Python

false

657

py

from setuptools import setup, find_packages with open("README.md", "r") as fh: long_description = fh.read() setup_args = dict( name='TorchSUL', version='0.1.26', description='Simple but useful layers for Pytorch', packages=find_packages(), long_description=long_description, long_description_content_type="text/markdown", author='Cheng Yu', author_email='chengyu996@gmail.com', url='https://github.com/ddddwee1/TorchSUL', install_requires = [ 'tqdm', 'progressbar2', 'opencv-python', 'matplotlib', ] ) install_requires = [] if __name__ == '__main__': setup(**setup_args)

[ "cy960823@outlook.com" ]

cy960823@outlook.com

11abbb227113c1d595e49225fb3b0db9a9fcde37

1d928c3f90d4a0a9a3919a804597aa0a4aab19a3

/python/spaCy/2016/12/setup.py

2a1d56a5eb1afee77dd993bc1b23ef7ca3b18273

[ "MIT" ]

permissive

rosoareslv/SED99

d8b2ff5811e7f0ffc59be066a5a0349a92cbb845

a062c118f12b93172e31e8ca115ce3f871b64461

refs/heads/main

2023-02-22T21:59:02.703005

2021-01-28T19:40:51

306,497,459

1

null

2020-11-24T20:56:18

2020-10-23T01:18:07

null

UTF-8

Python

false

8,194

py

#!/usr/bin/env python from __future__ import print_function import io import os import subprocess import sys import contextlib from distutils.command.build_ext import build_ext from distutils.sysconfig import get_python_inc from distutils import ccompiler, msvccompiler try: from setuptools import Extension, setup except ImportError: from distutils.core import Extension, setup PACKAGE_DATA = {'': ['*.pyx', '*.pxd', '*.txt', '*.tokens']} PACKAGES = [ 'spacy', 'spacy.tokens', 'spacy.en', 'spacy.de', 'spacy.zh', 'spacy.es', 'spacy.fr', 'spacy.it', 'spacy.hu', 'spacy.pt', 'spacy.nl', 'spacy.sv', 'spacy.language_data', 'spacy.serialize', 'spacy.syntax', 'spacy.munge', 'spacy.tests', 'spacy.tests.matcher', 'spacy.tests.morphology', 'spacy.tests.munge', 'spacy.tests.parser', 'spacy.tests.print', 'spacy.tests.serialize', 'spacy.tests.spans', 'spacy.tests.tagger', 'spacy.tests.tokenizer', 'spacy.tests.tokens', 'spacy.tests.vectors', 'spacy.tests.vocab', 'spacy.tests.website'] MOD_NAMES = [ 'spacy.parts_of_speech', 'spacy.strings', 'spacy.lexeme', 'spacy.vocab', 'spacy.attrs', 'spacy.morphology', 'spacy.tagger', 'spacy.pipeline', 'spacy.syntax.stateclass', 'spacy.syntax._state', 'spacy.tokenizer', 'spacy.syntax.parser', 'spacy.syntax.nonproj', 'spacy.syntax.transition_system', 'spacy.syntax.arc_eager', 'spacy.syntax._parse_features', 'spacy.gold', 'spacy.orth', 'spacy.tokens.doc', 'spacy.tokens.span', 'spacy.tokens.token', 'spacy.serialize.packer', 'spacy.serialize.huffman', 'spacy.serialize.bits', 'spacy.cfile', 'spacy.matcher', 'spacy.syntax.ner', 'spacy.symbols', 'spacy.syntax.iterators'] # TODO: This is missing a lot of modules. Does it matter? COMPILE_OPTIONS = { 'msvc': ['/Ox', '/EHsc'], 'mingw32' : ['-O3', '-Wno-strict-prototypes', '-Wno-unused-function'], 'other' : ['-O3', '-Wno-strict-prototypes', '-Wno-unused-function'] } LINK_OPTIONS = { 'msvc' : [], 'mingw32': [], 'other' : [] } # I don't understand this very well yet. See Issue #267 # Fingers crossed! #if os.environ.get('USE_OPENMP') == '1': # compile_options['msvc'].append('/openmp') # # #if not sys.platform.startswith('darwin'): # compile_options['other'].append('-fopenmp') # link_options['other'].append('-fopenmp') # USE_OPENMP_DEFAULT = '1' if sys.platform != 'darwin' else None if os.environ.get('USE_OPENMP', USE_OPENMP_DEFAULT) == '1': if sys.platform == 'darwin': COMPILE_OPTIONS['other'].append('-fopenmp') LINK_OPTIONS['other'].append('-fopenmp') PACKAGE_DATA['spacy.platform.darwin.lib'] = ['*.dylib'] PACKAGES.append('spacy.platform.darwin.lib') elif sys.platform == 'win32': COMPILE_OPTIONS['msvc'].append('/openmp') else: COMPILE_OPTIONS['other'].append('-fopenmp') LINK_OPTIONS['other'].append('-fopenmp') # By subclassing build_extensions we have the actual compiler that will be used which is really known only after finalize_options # http://stackoverflow.com/questions/724664/python-distutils-how-to-get-a-compiler-that-is-going-to-be-used class build_ext_options: def build_options(self): for e in self.extensions: e.extra_compile_args += COMPILE_OPTIONS.get( self.compiler.compiler_type, COMPILE_OPTIONS['other']) for e in self.extensions: e.extra_link_args += LINK_OPTIONS.get( self.compiler.compiler_type, LINK_OPTIONS['other']) class build_ext_subclass(build_ext, build_ext_options): def build_extensions(self): build_ext_options.build_options(self) build_ext.build_extensions(self) def generate_cython(root, source): print('Cythonizing sources') p = subprocess.call([sys.executable, os.path.join(root, 'bin', 'cythonize.py'), source]) if p != 0: raise RuntimeError('Running cythonize failed') def is_source_release(path): return os.path.exists(os.path.join(path, 'PKG-INFO')) def clean(path): for name in MOD_NAMES: name = name.replace('.', '/') for ext in ['.so', '.html', '.cpp', '.c']: file_path = os.path.join(path, name + ext) if os.path.exists(file_path): os.unlink(file_path) @contextlib.contextmanager def chdir(new_dir): old_dir = os.getcwd() try: os.chdir(new_dir) sys.path.insert(0, new_dir) yield finally: del sys.path[0] os.chdir(old_dir) def setup_package(): root = os.path.abspath(os.path.dirname(__file__)) if len(sys.argv) > 1 and sys.argv[1] == 'clean': return clean(root) with chdir(root): with io.open(os.path.join(root, 'spacy', 'about.py'), encoding='utf8') as f: about = {} exec(f.read(), about) with io.open(os.path.join(root, 'README.rst'), encoding='utf8') as f: readme = f.read() include_dirs = [ get_python_inc(plat_specific=True), os.path.join(root, 'include')] if (ccompiler.new_compiler().compiler_type == 'msvc' and msvccompiler.get_build_version() == 9): include_dirs.append(os.path.join(root, 'include', 'msvc9')) ext_modules = [] for mod_name in MOD_NAMES: mod_path = mod_name.replace('.', '/') + '.cpp' extra_link_args = [] # ??? # Imported from patch from @mikepb # See Issue #267. Running blind here... if sys.platform == 'darwin': dylib_path = ['..' for _ in range(mod_name.count('.'))] dylib_path = '/'.join(dylib_path) dylib_path = '@loader_path/%s/spacy/platform/darwin/lib' % dylib_path extra_link_args.append('-Wl,-rpath,%s' % dylib_path) ext_modules.append( Extension(mod_name, [mod_path], language='c++', include_dirs=include_dirs, extra_link_args=extra_link_args)) if not is_source_release(root): generate_cython(root, 'spacy') setup( name=about['__title__'], zip_safe=False, packages=PACKAGES, package_data=PACKAGE_DATA, description=about['__summary__'], long_description=readme, author=about['__author__'], author_email=about['__email__'], version=about['__version__'], url=about['__uri__'], license=about['__license__'], ext_modules=ext_modules, install_requires=[ 'numpy>=1.7', 'murmurhash>=0.26,<0.27', 'cymem>=1.30,<1.32', 'preshed>=0.46.0,<0.47.0', 'thinc>=5.0.0,<5.1.0', 'plac', 'six', 'cloudpickle', 'pathlib', 'sputnik>=0.9.2,<0.10.0', 'ujson>=1.35'], classifiers=[ 'Development Status :: 5 - Production/Stable', 'Environment :: Console', 'Intended Audience :: Developers', 'Intended Audience :: Science/Research', 'License :: OSI Approved :: MIT License', 'Operating System :: POSIX :: Linux', 'Operating System :: MacOS :: MacOS X', 'Operating System :: Microsoft :: Windows', 'Programming Language :: Cython', 'Programming Language :: Python :: 2.6', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3.3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Topic :: Scientific/Engineering'], cmdclass = { 'build_ext': build_ext_subclass}, ) if __name__ == '__main__': setup_package()

[ "rodrigosoaresilva@gmail.com" ]

rodrigosoaresilva@gmail.com

f9018da09e837ffe4443e04232a0b7cf548b49d9

472905e7a5f26465af4eee0fcfaa592de52eed17

/server/apps/memories/migrations/0002_auto_20191201_1010.py

824245ab101e92788bc10412075f16655229495e

[]

no_license

backpropogation/memories

7c72bfeca8a4ab07a2c19960c5af91ed4da24304

0da75bcffccbe5d3f4e2d5b30ee3f224f70aa81b

refs/heads/master

2022-12-24T08:27:24.838744

2019-12-01T16:14:04

225,188,993

0

null

2019-12-01T16:06:24

2019-12-01T16:03:37

JavaScript

UTF-8

Python

false

756

py

# Generated by Django 2.2.1 on 2019-12-01 10:10 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('memories', '0001_initial'), ] operations = [ migrations.AlterModelOptions( name='memory', options={'ordering': ('-posted_at',)}, ), migrations.AlterField( model_name='memory', name='latitude', field=models.DecimalField(decimal_places=20, max_digits=22, verbose_name='Latitude'), ), migrations.AlterField( model_name='memory', name='longitude', field=models.DecimalField(decimal_places=20, max_digits=23, verbose_name='Longitude'), ), ]

[ "jack.moriarty@mail.ru" ]

jack.moriarty@mail.ru

cca39d38965f0f35ece283739d54c15e3e72d4d9

563274d0bfb720b2d8c4dfe55ce0352928e0fa66

/TestProject/src/sqlalchemy-default/lib/sqlalchemy/dialects/oracle/cx_oracle.py

bee7308005ea28044d35e31dc0bed1e0b5d8adfd

[ "MIT" ]

permissive

wangzhengbo1204/Python

30488455637ad139abc2f173a0a595ecaf28bcdc

63f7488d9df9caf1abec2cab7c59cf5d6358b4d0

refs/heads/master

2020-05-19T19:48:27.092764

2013-05-11T06:49:41

6,544,357

1

0

null

UTF-8

Python

false

31,002

py

# oracle/cx_oracle.py # Copyright (C) 2005-2012 the SQLAlchemy authors and contributors <see AUTHORS file> # # This module is part of SQLAlchemy and is released under # the MIT License: http://www.opensource.org/licenses/mit-license.php """ .. dialect:: oracle+cx_oracle :name: cx-Oracle :dbapi: cx_oracle :connectstring: oracle+cx_oracle://user:pass@host:port/dbname[?key=value&key=value...] :url: http://cx-oracle.sourceforge.net/ Additional Connect Arguments ---------------------------- When connecting with ``dbname`` present, the host, port, and dbname tokens are converted to a TNS name using the cx_oracle :func:`makedsn()` function. Otherwise, the host token is taken directly as a TNS name. Additional arguments which may be specified either as query string arguments on the URL, or as keyword arguments to :func:`~sqlalchemy.create_engine()` are: * allow_twophase - enable two-phase transactions. Defaults to ``True``. * arraysize - set the cx_oracle.arraysize value on cursors, in SQLAlchemy it defaults to 50. See the section on "LOB Objects" below. * auto_convert_lobs - defaults to True, see the section on LOB objects. * auto_setinputsizes - the cx_oracle.setinputsizes() call is issued for all bind parameters. This is required for LOB datatypes but can be disabled to reduce overhead. Defaults to ``True``. Specific types can be excluded from this process using the ``exclude_setinputsizes`` parameter. * exclude_setinputsizes - a tuple or list of string DBAPI type names to be excluded from the "auto setinputsizes" feature. The type names here must match DBAPI types that are found in the "cx_Oracle" module namespace, such as cx_Oracle.UNICODE, cx_Oracle.NCLOB, etc. Defaults to ``(STRING, UNICODE)``. .. versionadded:: 0.8 specific DBAPI types can be excluded from the auto_setinputsizes feature via the exclude_setinputsizes attribute. * mode - This is given the string value of SYSDBA or SYSOPER, or alternatively an integer value. This value is only available as a URL query string argument. * threaded - enable multithreaded access to cx_oracle connections. Defaults to ``True``. Note that this is the opposite default of the cx_Oracle DBAPI itself. Unicode ------- cx_oracle 5 fully supports Python unicode objects. SQLAlchemy will pass all unicode strings directly to cx_oracle, and additionally uses an output handler so that all string based result values are returned as unicode as well. Generally, the ``NLS_LANG`` environment variable determines the nature of the encoding to be used. Note that this behavior is disabled when Oracle 8 is detected, as it has been observed that issues remain when passing Python unicodes to cx_oracle with Oracle 8. LOB Objects ----------- cx_oracle returns oracle LOBs using the cx_oracle.LOB object. SQLAlchemy converts these to strings so that the interface of the Binary type is consistent with that of other backends, and so that the linkage to a live cursor is not needed in scenarios like result.fetchmany() and result.fetchall(). This means that by default, LOB objects are fully fetched unconditionally by SQLAlchemy, and the linkage to a live cursor is broken. To disable this processing, pass ``auto_convert_lobs=False`` to :func:`create_engine()`. Two Phase Transaction Support ----------------------------- Two Phase transactions are implemented using XA transactions. Success has been reported with this feature but it should be regarded as experimental. Precision Numerics ------------------ The SQLAlchemy dialect goes through a lot of steps to ensure that decimal numbers are sent and received with full accuracy. An "outputtypehandler" callable is associated with each cx_oracle connection object which detects numeric types and receives them as string values, instead of receiving a Python ``float`` directly, which is then passed to the Python ``Decimal`` constructor. The :class:`.Numeric` and :class:`.Float` types under the cx_oracle dialect are aware of this behavior, and will coerce the ``Decimal`` to ``float`` if the ``asdecimal`` flag is ``False`` (default on :class:`.Float`, optional on :class:`.Numeric`). Because the handler coerces to ``Decimal`` in all cases first, the feature can detract significantly from performance. If precision numerics aren't required, the decimal handling can be disabled by passing the flag ``coerce_to_decimal=False`` to :func:`.create_engine`:: engine = create_engine("oracle+cx_oracle://dsn", coerce_to_decimal=False) .. versionadded:: 0.7.6 Add the ``coerce_to_decimal`` flag. Another alternative to performance is to use the `cdecimal <http://pypi.python.org/pypi/cdecimal/>`_ library; see :class:`.Numeric` for additional notes. The handler attempts to use the "precision" and "scale" attributes of the result set column to best determine if subsequent incoming values should be received as ``Decimal`` as opposed to int (in which case no processing is added). There are several scenarios where OCI_ does not provide unambiguous data as to the numeric type, including some situations where individual rows may return a combination of floating point and integer values. Certain values for "precision" and "scale" have been observed to determine this scenario. When it occurs, the outputtypehandler receives as string and then passes off to a processing function which detects, for each returned value, if a decimal point is present, and if so converts to ``Decimal``, otherwise to int. The intention is that simple int-based statements like "SELECT my_seq.nextval() FROM DUAL" continue to return ints and not ``Decimal`` objects, and that any kind of floating point value is received as a string so that there is no floating point loss of precision. The "decimal point is present" logic itself is also sensitive to locale. Under OCI_, this is controlled by the NLS_LANG environment variable. Upon first connection, the dialect runs a test to determine the current "decimal" character, which can be a comma "," for european locales. From that point forward the outputtypehandler uses that character to represent a decimal point. Note that cx_oracle 5.0.3 or greater is required when dealing with numerics with locale settings that don't use a period "." as the decimal character. .. versionchanged:: 0.6.6 The outputtypehandler uses a comma "," character to represent a decimal point. .. _OCI: http://www.oracle.com/technetwork/database/features/oci/index.html """ from .base import OracleCompiler, OracleDialect, \ RESERVED_WORDS, OracleExecutionContext from . import base as oracle from ...engine import result as _result from sqlalchemy import types as sqltypes, util, exc, processors import random import collections from sqlalchemy.util.compat import decimal import re class _OracleNumeric(sqltypes.Numeric): def bind_processor(self, dialect): # cx_oracle accepts Decimal objects and floats return None def result_processor(self, dialect, coltype): # we apply a cx_oracle type handler to all connections # that converts floating point strings to Decimal(). # However, in some subquery situations, Oracle doesn't # give us enough information to determine int or Decimal. # It could even be int/Decimal differently on each row, # regardless of the scale given for the originating type. # So we still need an old school isinstance() handler # here for decimals. if dialect.supports_native_decimal: if self.asdecimal: if self.scale is None: fstring = "%.10f" else: fstring = "%%.%df" % self.scale def to_decimal(value): if value is None: return None elif isinstance(value, decimal.Decimal): return value else: return decimal.Decimal(fstring % value) return to_decimal else: if self.precision is None and self.scale is None: return processors.to_float elif not getattr(self, '_is_oracle_number', False) \ and self.scale is not None: return processors.to_float else: return None else: # cx_oracle 4 behavior, will assume # floats return super(_OracleNumeric, self).\ result_processor(dialect, coltype) class _OracleDate(sqltypes.Date): def bind_processor(self, dialect): return None def result_processor(self, dialect, coltype): def process(value): if value is not None: return value.date() else: return value return process class _LOBMixin(object): def result_processor(self, dialect, coltype): if not dialect.auto_convert_lobs: # return the cx_oracle.LOB directly. return None def process(value): if value is not None: return value.read() else: return value return process class _NativeUnicodeMixin(object): # Py3K #pass # Py2K def bind_processor(self, dialect): if dialect._cx_oracle_with_unicode: def process(value): if value is None: return value else: return unicode(value) return process else: return super(_NativeUnicodeMixin, self).bind_processor(dialect) # end Py2K # we apply a connection output handler that returns # unicode in all cases, so the "native_unicode" flag # will be set for the default String.result_processor. class _OracleChar(_NativeUnicodeMixin, sqltypes.CHAR): def get_dbapi_type(self, dbapi): return dbapi.FIXED_CHAR class _OracleNVarChar(_NativeUnicodeMixin, sqltypes.NVARCHAR): def get_dbapi_type(self, dbapi): return getattr(dbapi, 'UNICODE', dbapi.STRING) class _OracleText(_LOBMixin, sqltypes.Text): def get_dbapi_type(self, dbapi): return dbapi.CLOB class _OracleString(_NativeUnicodeMixin, sqltypes.String): pass class _OracleUnicodeText(_LOBMixin, _NativeUnicodeMixin, sqltypes.UnicodeText): def get_dbapi_type(self, dbapi): return dbapi.NCLOB def result_processor(self, dialect, coltype): lob_processor = _LOBMixin.result_processor(self, dialect, coltype) if lob_processor is None: return None string_processor = sqltypes.UnicodeText.result_processor(self, dialect, coltype) if string_processor is None: return lob_processor else: def process(value): return string_processor(lob_processor(value)) return process class _OracleInteger(sqltypes.Integer): def result_processor(self, dialect, coltype): def to_int(val): if val is not None: val = int(val) return val return to_int class _OracleBinary(_LOBMixin, sqltypes.LargeBinary): def get_dbapi_type(self, dbapi): return dbapi.BLOB def bind_processor(self, dialect): return None class _OracleInterval(oracle.INTERVAL): def get_dbapi_type(self, dbapi): return dbapi.INTERVAL class _OracleRaw(oracle.RAW): pass class _OracleRowid(oracle.ROWID): def get_dbapi_type(self, dbapi): return dbapi.ROWID class OracleCompiler_cx_oracle(OracleCompiler): def bindparam_string(self, name, quote=None, **kw): if quote is True or quote is not False and \ self.preparer._bindparam_requires_quotes(name): quoted_name = '"%s"' % name self._quoted_bind_names[name] = quoted_name return OracleCompiler.bindparam_string(self, quoted_name, **kw) else: return OracleCompiler.bindparam_string(self, name, **kw) class OracleExecutionContext_cx_oracle(OracleExecutionContext): def pre_exec(self): quoted_bind_names = \ getattr(self.compiled, '_quoted_bind_names', None) if quoted_bind_names: if not self.dialect.supports_unicode_statements: # if DBAPI doesn't accept unicode statements, # keys in self.parameters would have been encoded # here. so convert names in quoted_bind_names # to encoded as well. quoted_bind_names = \ dict( (fromname.encode(self.dialect.encoding), toname.encode(self.dialect.encoding)) for fromname, toname in quoted_bind_names.items() ) for param in self.parameters: for fromname, toname in quoted_bind_names.items(): param[toname] = param[fromname] del param[fromname] if self.dialect.auto_setinputsizes: # cx_oracle really has issues when you setinputsizes # on String, including that outparams/RETURNING # breaks for varchars self.set_input_sizes(quoted_bind_names, exclude_types=self.dialect.exclude_setinputsizes ) # if a single execute, check for outparams if len(self.compiled_parameters) == 1: for bindparam in self.compiled.binds.values(): if bindparam.isoutparam: dbtype = bindparam.type.dialect_impl(self.dialect).\ get_dbapi_type(self.dialect.dbapi) if not hasattr(self, 'out_parameters'): self.out_parameters = {} if dbtype is None: raise exc.InvalidRequestError( "Cannot create out parameter for parameter " "%r - it's type %r is not supported by" " cx_oracle" % (bindparam.key, bindparam.type) ) name = self.compiled.bind_names[bindparam] self.out_parameters[name] = self.cursor.var(dbtype) self.parameters[0][quoted_bind_names.get(name, name)] = \ self.out_parameters[name] def create_cursor(self): c = self._dbapi_connection.cursor() if self.dialect.arraysize: c.arraysize = self.dialect.arraysize return c def get_result_proxy(self): if hasattr(self, 'out_parameters') and self.compiled.returning: returning_params = dict( (k, v.getvalue()) for k, v in self.out_parameters.items() ) return ReturningResultProxy(self, returning_params) result = None if self.cursor.description is not None: for column in self.cursor.description: type_code = column[1] if type_code in self.dialect._cx_oracle_binary_types: result = _result.BufferedColumnResultProxy(self) if result is None: result = _result.ResultProxy(self) if hasattr(self, 'out_parameters'): if self.compiled_parameters is not None and \ len(self.compiled_parameters) == 1: result.out_parameters = out_parameters = {} for bind, name in self.compiled.bind_names.items(): if name in self.out_parameters: type = bind.type impl_type = type.dialect_impl(self.dialect) dbapi_type = impl_type.get_dbapi_type(self.dialect.dbapi) result_processor = impl_type.\ result_processor(self.dialect, dbapi_type) if result_processor is not None: out_parameters[name] = \ result_processor(self.out_parameters[name].getvalue()) else: out_parameters[name] = self.out_parameters[name].getvalue() else: result.out_parameters = dict( (k, v.getvalue()) for k, v in self.out_parameters.items() ) return result class OracleExecutionContext_cx_oracle_with_unicode(OracleExecutionContext_cx_oracle): """Support WITH_UNICODE in Python 2.xx. WITH_UNICODE allows cx_Oracle's Python 3 unicode handling behavior under Python 2.x. This mode in some cases disallows and in other cases silently passes corrupted data when non-Python-unicode strings (a.k.a. plain old Python strings) are passed as arguments to connect(), the statement sent to execute(), or any of the bind parameter keys or values sent to execute(). This optional context therefore ensures that all statements are passed as Python unicode objects. """ def __init__(self, *arg, **kw): OracleExecutionContext_cx_oracle.__init__(self, *arg, **kw) self.statement = unicode(self.statement) def _execute_scalar(self, stmt): return super(OracleExecutionContext_cx_oracle_with_unicode, self).\ _execute_scalar(unicode(stmt)) class ReturningResultProxy(_result.FullyBufferedResultProxy): """Result proxy which stuffs the _returning clause + outparams into the fetch.""" def __init__(self, context, returning_params): self._returning_params = returning_params super(ReturningResultProxy, self).__init__(context) def _cursor_description(self): returning = self.context.compiled.returning return [ ("ret_%d" % i, None) for i, col in enumerate(returning) ] def _buffer_rows(self): return collections.deque([tuple(self._returning_params["ret_%d" % i] for i, c in enumerate(self._returning_params))]) class OracleDialect_cx_oracle(OracleDialect): execution_ctx_cls = OracleExecutionContext_cx_oracle statement_compiler = OracleCompiler_cx_oracle driver = "cx_oracle" colspecs = colspecs = { sqltypes.Numeric: _OracleNumeric, sqltypes.Date: _OracleDate, # generic type, assume datetime.date is desired oracle.DATE: oracle.DATE, # non generic type - passthru sqltypes.LargeBinary: _OracleBinary, sqltypes.Boolean: oracle._OracleBoolean, sqltypes.Interval: _OracleInterval, oracle.INTERVAL: _OracleInterval, sqltypes.Text: _OracleText, sqltypes.String: _OracleString, sqltypes.UnicodeText: _OracleUnicodeText, sqltypes.CHAR: _OracleChar, # this is only needed for OUT parameters. # it would be nice if we could not use it otherwise. sqltypes.Integer: _OracleInteger, oracle.RAW: _OracleRaw, sqltypes.Unicode: _OracleNVarChar, sqltypes.NVARCHAR: _OracleNVarChar, oracle.ROWID: _OracleRowid, } execute_sequence_format = list def __init__(self, auto_setinputsizes=True, exclude_setinputsizes=("STRING", "UNICODE"), auto_convert_lobs=True, threaded=True, allow_twophase=True, coerce_to_decimal=True, arraysize=50, **kwargs): OracleDialect.__init__(self, **kwargs) self.threaded = threaded self.arraysize = arraysize self.allow_twophase = allow_twophase self.supports_timestamp = self.dbapi is None or \ hasattr(self.dbapi, 'TIMESTAMP') self.auto_setinputsizes = auto_setinputsizes self.auto_convert_lobs = auto_convert_lobs if hasattr(self.dbapi, 'version'): self.cx_oracle_ver = tuple([int(x) for x in self.dbapi.version.split('.')]) else: self.cx_oracle_ver = (0, 0, 0) def types(*names): return set( getattr(self.dbapi, name, None) for name in names ).difference([None]) self.exclude_setinputsizes = types(*(exclude_setinputsizes or ())) self._cx_oracle_string_types = types("STRING", "UNICODE", "NCLOB", "CLOB") self._cx_oracle_unicode_types = types("UNICODE", "NCLOB") self._cx_oracle_binary_types = types("BFILE", "CLOB", "NCLOB", "BLOB") self.supports_unicode_binds = self.cx_oracle_ver >= (5, 0) self.supports_native_decimal = ( self.cx_oracle_ver >= (5, 0) and coerce_to_decimal ) self._cx_oracle_native_nvarchar = self.cx_oracle_ver >= (5, 0) if self.cx_oracle_ver is None: # this occurs in tests with mock DBAPIs self._cx_oracle_string_types = set() self._cx_oracle_with_unicode = False elif self.cx_oracle_ver >= (5,) and not hasattr(self.dbapi, 'UNICODE'): # cx_Oracle WITH_UNICODE mode. *only* python # unicode objects accepted for anything self.supports_unicode_statements = True self.supports_unicode_binds = True self._cx_oracle_with_unicode = True # Py2K # There's really no reason to run with WITH_UNICODE under Python 2.x. # Give the user a hint. util.warn("cx_Oracle is compiled under Python 2.xx using the " "WITH_UNICODE flag. Consider recompiling cx_Oracle without " "this flag, which is in no way necessary for full support of Unicode. " "Otherwise, all string-holding bind parameters must " "be explicitly typed using SQLAlchemy's String type or one of its subtypes," "or otherwise be passed as Python unicode. Plain Python strings " "passed as bind parameters will be silently corrupted by cx_Oracle." ) self.execution_ctx_cls = OracleExecutionContext_cx_oracle_with_unicode # end Py2K else: self._cx_oracle_with_unicode = False if self.cx_oracle_ver is None or \ not self.auto_convert_lobs or \ not hasattr(self.dbapi, 'CLOB'): self.dbapi_type_map = {} else: # only use this for LOB objects. using it for strings, dates # etc. leads to a little too much magic, reflection doesn't know if it should # expect encoded strings or unicodes, etc. self.dbapi_type_map = { self.dbapi.CLOB: oracle.CLOB(), self.dbapi.NCLOB: oracle.NCLOB(), self.dbapi.BLOB: oracle.BLOB(), self.dbapi.BINARY: oracle.RAW(), } @classmethod def dbapi(cls): import cx_Oracle return cx_Oracle def initialize(self, connection): super(OracleDialect_cx_oracle, self).initialize(connection) if self._is_oracle_8: self.supports_unicode_binds = False self._detect_decimal_char(connection) def _detect_decimal_char(self, connection): """detect if the decimal separator character is not '.', as is the case with european locale settings for NLS_LANG. cx_oracle itself uses similar logic when it formats Python Decimal objects to strings on the bind side (as of 5.0.3), as Oracle sends/receives string numerics only in the current locale. """ if self.cx_oracle_ver < (5,): # no output type handlers before version 5 return cx_Oracle = self.dbapi conn = connection.connection # override the output_type_handler that's # on the cx_oracle connection with a plain # one on the cursor def output_type_handler(cursor, name, defaultType, size, precision, scale): return cursor.var( cx_Oracle.STRING, 255, arraysize=cursor.arraysize) cursor = conn.cursor() cursor.outputtypehandler = output_type_handler cursor.execute("SELECT 0.1 FROM DUAL") val = cursor.fetchone()[0] cursor.close() char = re.match(r"([\.,])", val).group(1) if char != '.': _detect_decimal = self._detect_decimal self._detect_decimal = \ lambda value: _detect_decimal(value.replace(char, '.')) self._to_decimal = \ lambda value: decimal.Decimal(value.replace(char, '.')) def _detect_decimal(self, value): if "." in value: return decimal.Decimal(value) else: return int(value) _to_decimal = decimal.Decimal def on_connect(self): if self.cx_oracle_ver < (5,): # no output type handlers before version 5 return cx_Oracle = self.dbapi def output_type_handler(cursor, name, defaultType, size, precision, scale): # convert all NUMBER with precision + positive scale to Decimal # this almost allows "native decimal" mode. if self.supports_native_decimal and \ defaultType == cx_Oracle.NUMBER and \ precision and scale > 0: return cursor.var( cx_Oracle.STRING, 255, outconverter=self._to_decimal, arraysize=cursor.arraysize) # if NUMBER with zero precision and 0 or neg scale, this appears # to indicate "ambiguous". Use a slower converter that will # make a decision based on each value received - the type # may change from row to row (!). This kills # off "native decimal" mode, handlers still needed. elif self.supports_native_decimal and \ defaultType == cx_Oracle.NUMBER \ and not precision and scale <= 0: return cursor.var( cx_Oracle.STRING, 255, outconverter=self._detect_decimal, arraysize=cursor.arraysize) # allow all strings to come back natively as Unicode elif defaultType in (cx_Oracle.STRING, cx_Oracle.FIXED_CHAR): return cursor.var(unicode, size, cursor.arraysize) def on_connect(conn): conn.outputtypehandler = output_type_handler return on_connect def create_connect_args(self, url): dialect_opts = dict(url.query) for opt in ('use_ansi', 'auto_setinputsizes', 'auto_convert_lobs', 'threaded', 'allow_twophase'): if opt in dialect_opts: util.coerce_kw_type(dialect_opts, opt, bool) setattr(self, opt, dialect_opts[opt]) if url.database: # if we have a database, then we have a remote host port = url.port if port: port = int(port) else: port = 1521 dsn = self.dbapi.makedsn(url.host, port, url.database) else: # we have a local tnsname dsn = url.host opts = dict( user=url.username, password=url.password, dsn=dsn, threaded=self.threaded, twophase=self.allow_twophase, ) # Py2K if self._cx_oracle_with_unicode: for k, v in opts.items(): if isinstance(v, str): opts[k] = unicode(v) else: for k, v in opts.items(): if isinstance(v, unicode): opts[k] = str(v) # end Py2K if 'mode' in url.query: opts['mode'] = url.query['mode'] if isinstance(opts['mode'], basestring): mode = opts['mode'].upper() if mode == 'SYSDBA': opts['mode'] = self.dbapi.SYSDBA elif mode == 'SYSOPER': opts['mode'] = self.dbapi.SYSOPER else: util.coerce_kw_type(opts, 'mode', int) return ([], opts) def _get_server_version_info(self, connection): return tuple( int(x) for x in connection.connection.version.split('.') ) def is_disconnect(self, e, connection, cursor): error, = e.args if isinstance(e, self.dbapi.InterfaceError): return "not connected" in str(e) elif hasattr(error, 'code'): # ORA-00028: your session has been killed # ORA-03114: not connected to ORACLE # ORA-03113: end-of-file on communication channel # ORA-03135: connection lost contact # ORA-01033: ORACLE initialization or shutdown in progress # TODO: Others ? return error.code in (28, 3114, 3113, 3135, 1033) else: return False def create_xid(self): """create a two-phase transaction ID. this id will be passed to do_begin_twophase(), do_rollback_twophase(), do_commit_twophase(). its format is unspecified.""" id = random.randint(0, 2 ** 128) return (0x1234, "%032x" % id, "%032x" % 9) def do_begin_twophase(self, connection, xid): connection.connection.begin(*xid) def do_prepare_twophase(self, connection, xid): connection.connection.prepare() def do_rollback_twophase(self, connection, xid, is_prepared=True, recover=False): self.do_rollback(connection.connection) def do_commit_twophase(self, connection, xid, is_prepared=True, recover=False): self.do_commit(connection.connection) def do_recover_twophase(self, connection): pass dialect = OracleDialect_cx_oracle

[ "wangzhengbo1204@gmail.com" ]

wangzhengbo1204@gmail.com

64ba6ec501d975d541fea1dd55faa1b766c24658

6444622ad4a150993955a0c8fe260bae1af7f8ce

/djangoenv/bin/django-admin

b9210326fb809c5ec6c08d9923a99c16f9a46121

[]

no_license

jeremyrich/Lesson_RestAPI_jeremy

ca965ef017c53f919c0bf97a4a23841818e246f9

a44263e45b1cc1ba812059f6984c0f5be25cd234

refs/heads/master

2020-04-25T23:13:47.237188

2019-03-22T09:26:58

173,138,073

0

null

2019-03-22T09:26:59

2019-02-28T15:34:19

Python

UTF-8

Python

false

349

#!/home/mymy/Desktop/Python_agility/cours/Hugo/Lessons_RestAPI/Lesson_RestAPI/djangoenv/bin/python2.7 # -*- coding: utf-8 -*- import re import sys from django.core.management import execute_from_command_line if __name__ == '__main__': sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0]) sys.exit(execute_from_command_line())

[ "jeremyrich@free.fr" ]

jeremyrich@free.fr

2401aaa2a42cd0e7892df3be26c15c536640cfef

ccb81eef3cd4f5562cab89b51695756ab8dbc736

/message_ler_17076/wsgi.py

f1c921791698157a52064050940c5b21f2e0dd40

[]

no_license

crowdbotics-apps/message-ler-17076

4e847a2ccd333b77414bf9b913e7705c203accbb

135b68325e04caf669fd9fe281244c460e71068c

refs/heads/master

2023-05-16T11:16:10.937234

2020-05-16T19:12:53

264,508,470

0

null

2021-06-10T11:01:47

2020-05-16T19:11:07

Python

UTF-8

Python

false

411

py

""" WSGI config for message_ler_17076 project. It exposes the WSGI callable as a module-level variable named ``application``. For more information on this file, see https://docs.djangoproject.com/en/2.2/howto/deployment/wsgi/ """ import os from django.core.wsgi import get_wsgi_application os.environ.setdefault("DJANGO_SETTINGS_MODULE", "message_ler_17076.settings") application = get_wsgi_application()

[ "team@crowdbotics.com" ]

team@crowdbotics.com

24ce83491fbb7e1866d1b8b4a18150fc82c28ee5

79479634cd8da72fc912b11ec43e237726f7c5e5

/scripts/subreddit_submissions.py

5d74fcf29545b78a2ba70950c7140671f3e4f73d

[ "MIT" ]

permissive

PhantomInsights/subreddit-analyzer

594235169f58d5b2c9de886625464ced5be02790

ba5e6250797515d664d6cfa6df011f8cec1b2729

refs/heads/master

2020-11-25T10:46:13.771188

2020-04-02T12:50:12

228,625,357

513

47

MIT

2019-12-24T13:35:32

2019-12-17T13:42:42

Python

UTF-8

Python

false

2,915

py

""" This script uses the Pushshift API to download posts from the specified subreddits. By default it downloads 10,000 posts starting from the newest one. """ import csv import time from datetime import datetime import requests import tldextract SUBREDDITS = ["mexico"] HEADERS = {"User-Agent": "Submissions Downloader v0.2"} SUBMISSIONS_LIST = list() MAX_SUBMISSIONS = 10000 def init(): """Iterates over all the subreddits and creates their csv files.""" for subreddit in SUBREDDITS: writer = csv.writer(open("./{}-submissions.csv".format(subreddit), "w", newline="", encoding="utf-8")) # Adding the header. writer.writerow(["datetime", "author", "title", "url", "domain"]) print("Downloading:", subreddit) download_submissions(subreddit=subreddit) writer.writerows(SUBMISSIONS_LIST) SUBMISSIONS_LIST.clear() def download_submissions(subreddit, latest_timestamp=None): """Keeps downloading submissions using recursion, it downloads them 500 at a time. Parameters ---------- subreddit : str The desired subreddit. latest_timestamp: int The timestampf of the latest comment. """ base_url = "https://api.pushshift.io/reddit/submission/search/" params = {"subreddit": subreddit, "sort": "desc", "sort_type": "created_utc", "size": 500} # After the first call of this function we will use the 'before' parameter. if latest_timestamp != None: params["before"] = latest_timestamp with requests.get(base_url, params=params, headers=HEADERS) as response: json_data = response.json() total_submissions = len(json_data["data"]) latest_timestamp = 0 print("Downloading: {} submissions".format(total_submissions)) for item in json_data["data"]: # We will only take 3 properties, the timestamp, author and url. latest_timestamp = item["created_utc"] iso_date = datetime.fromtimestamp(latest_timestamp) tld = tldextract.extract(item["url"]) domain = tld.domain + "." + tld.suffix if item["is_self"] == True: domain = "self-post" if domain == "youtu.be": domain = "youtube.com" if domain == "redd.it": domain = "reddit.com" SUBMISSIONS_LIST.append( [iso_date, item["author"], item["title"], item["url"], domain]) if len(SUBMISSIONS_LIST) >= MAX_SUBMISSIONS: break if total_submissions < 500: print("No more results.") elif len(SUBMISSIONS_LIST) >= MAX_SUBMISSIONS: print("Download complete.") else: time.sleep(1.2) download_submissions(subreddit, latest_timestamp) if __name__ == "__main__": init()

[ "phantom@phantom.im" ]

phantom@phantom.im

1e189ea6efb35bf1d8f0ab74b3f558a83fc5ab98

35b460a5e72e3cb40681861c38dc6d5df1ae9b92

/CodeFights/Arcade/Intro/throughTheFog/circleOfNumbers.py

aef33d190af0cb87515c13db64c6284b45fdb0e4

[]

no_license

robgoyal/CodingChallenges

9c5f3457a213cf54193a78058f74fcf085ef25bc

0aa99d1aa7b566a754471501945de26644558d7c

refs/heads/master

2021-06-23T09:09:17.085873

2019-03-04T04:04:59

94,391,412

0

null

UTF-8

Python

false

274

py

# Name: circleOfNumbers.py # Author: Robin Goyal # Last-Modified: July 13, 2017 # Purpose: Given a circular radius n and an input number, # find the number which is opposite the input number def circleOfNumbers(n, firstNumber): return (firstNumber + n / 2) % n

[ "goyal.rob@gmail.com" ]

goyal.rob@gmail.com

2e6d663e1f9f0847d490f1af6ae277c83881bfaa

96dcea595e7c16cec07b3f649afd65f3660a0bad

/homeassistant/components/twentemilieu/calendar.py

f4d1e51b171eedd978a3de9419f2265296cd7c7b

[ "Apache-2.0" ]

permissive

home-assistant/core

3455eac2e9d925c92d30178643b1aaccf3a6484f

80caeafcb5b6e2f9da192d0ea6dd1a5b8244b743

refs/heads/dev

2023-08-31T15:41:06.299469

2023-08-31T14:50:53

12,888,993

35,501

20,617

Apache-2.0

2023-09-14T21:50:15

2013-09-17T07:29:48

Python

UTF-8

Python

false

3,653

py

"""Support for Twente Milieu Calendar.""" from __future__ import annotations from datetime import date, datetime, timedelta from twentemilieu import WasteType from homeassistant.components.calendar import CalendarEntity, CalendarEvent from homeassistant.config_entries import ConfigEntry from homeassistant.const import CONF_ID from homeassistant.core import HomeAssistant, callback from homeassistant.helpers.entity_platform import AddEntitiesCallback from homeassistant.helpers.update_coordinator import DataUpdateCoordinator import homeassistant.util.dt as dt_util from .const import DOMAIN, WASTE_TYPE_TO_DESCRIPTION from .entity import TwenteMilieuEntity async def async_setup_entry( hass: HomeAssistant, entry: ConfigEntry, async_add_entities: AddEntitiesCallback, ) -> None: """Set up Twente Milieu calendar based on a config entry.""" coordinator = hass.data[DOMAIN][entry.data[CONF_ID]] async_add_entities([TwenteMilieuCalendar(coordinator, entry)]) class TwenteMilieuCalendar(TwenteMilieuEntity, CalendarEntity): """Defines a Twente Milieu calendar.""" _attr_has_entity_name = True _attr_icon = "mdi:delete-empty" _attr_name = None def __init__( self, coordinator: DataUpdateCoordinator[dict[WasteType, list[date]]], entry: ConfigEntry, ) -> None: """Initialize the Twente Milieu entity.""" super().__init__(coordinator, entry) self._attr_unique_id = str(entry.data[CONF_ID]) self._event: CalendarEvent | None = None @property def event(self) -> CalendarEvent | None: """Return the next upcoming event.""" return self._event async def async_get_events( self, hass: HomeAssistant, start_date: datetime, end_date: datetime ) -> list[CalendarEvent]: """Return calendar events within a datetime range.""" events: list[CalendarEvent] = [] for waste_type, waste_dates in self.coordinator.data.items(): events.extend( CalendarEvent( summary=WASTE_TYPE_TO_DESCRIPTION[waste_type], start=waste_date, end=waste_date + timedelta(days=1), ) for waste_date in waste_dates if start_date.date() <= waste_date <= end_date.date() ) return events @callback def _handle_coordinator_update(self) -> None: """Handle updated data from the coordinator.""" next_waste_pickup_type = None next_waste_pickup_date = None for waste_type, waste_dates in self.coordinator.data.items(): if ( waste_dates and ( next_waste_pickup_date is None or waste_dates[0] # type: ignore[unreachable] < next_waste_pickup_date ) and waste_dates[0] >= dt_util.now().date() ): next_waste_pickup_date = waste_dates[0] next_waste_pickup_type = waste_type self._event = None if next_waste_pickup_date is not None and next_waste_pickup_type is not None: self._event = CalendarEvent( summary=WASTE_TYPE_TO_DESCRIPTION[next_waste_pickup_type], start=next_waste_pickup_date, end=next_waste_pickup_date + timedelta(days=1), ) super()._handle_coordinator_update() async def async_added_to_hass(self) -> None: """When entity is added to hass.""" await super().async_added_to_hass() self._handle_coordinator_update()

[ "noreply@github.com" ]

home-assistant.noreply@github.com

032a5183b2f4f23432281cb1bdb5b8dbd83c594d

0ee329d7c2de6783dccf3a5fa128930a000c672d

/Final_loop_for_X_Test_and_predictions_Soros_167.py

078aa9cbae41c35805972f545b365c4e837638dd

[]

no_license

rsc2143/ViteosModel

2df5788def1a2c9531b050932c94ca04227bdef6

9be8a03fcd3528de1db3d801d11875a60779dd20

refs/heads/master

2023-05-09T03:25:26.818465

2021-06-07T11:31:31

374,601,477

0

null

UTF-8

Python

false

87,818

py

#!/usr/bin/env python # coding: utf-8 # In[1]: import numpy as np import pandas as pd from datetime import datetime #from sklearn.metrics import accuracy_score from sklearn.metrics import classification_report from tqdm import tqdm import pickle import os import sys #from sklearn.metrics import confusion_matrix # In[4709]: print(os.getcwd()) os.chdir('C:\\Users\\consultant138\\Downloads\\Viteos_Rohit\\ViteosModel') print(os.getcwd()) orig_stdout = sys.stdout f = open('153_model_run_' + str(datetime.now().strftime("%d_%m_%Y_%H_%M")) + '.txt', 'w') sys.stdout = f print(datetime.now()) def equals_fun(a,b): if a == b: return 1 else: return 0 vec_equals_fun = np.vectorize(equals_fun) def mhreplaced(item): word1 = [] word2 = [] if (type(item) == str): for items in item.split(' '): if (type(items) == str): items = items.lower() if items.isdigit() == False: word1.append(items) for c in word1: if c.endswith('MH')==False: word2.append(c) words = ' '.join(word2) return words else: return item vec_tt_match = np.vectorize(mhreplaced) def fundmatch(item): items = item.lower() items = item.replace(' ','') return items vec_fund_match = np.vectorize(fundmatch) def nan_fun(x): if x=='nan': return 1 else: return 0 vec_nan_fun = np.vectorize(nan_fun) def a_keymatch(a_cusip, a_isin): pb_nan = 0 a_common_key = 'NA' if a_cusip=='nan' and a_isin =='nan': pb_nan =1 elif(a_cusip!='nan' and a_isin == 'nan'): a_common_key = a_cusip elif(a_cusip =='nan' and a_isin !='nan'): a_common_key = a_isin else: a_common_key = a_isin return (pb_nan, a_common_key) def b_keymatch(b_cusip, b_isin): accounting_nan = 0 b_common_key = 'NA' if b_cusip =='nan' and b_isin =='nan': accounting_nan =1 elif (b_cusip!='nan' and b_isin == 'nan'): b_common_key = b_cusip elif(b_cusip =='nan' and b_isin !='nan'): b_common_key = b_isin else: b_common_key = b_isin return (accounting_nan, b_common_key) vec_a_key_match_fun = np.vectorize(a_keymatch) vec_b_key_match_fun = np.vectorize(b_keymatch) def nan_equals_fun(a,b): if a==1 and b==1: return 1 else: return 0 vec_nan_equal_fun = np.vectorize(nan_equals_fun) def new_key_match_fun(a,b,c): if a==b and c==0: return 1 else: return 0 vec_new_key_match_fun = np.vectorize(new_key_match_fun) cols = ['Currency','Account Type','Accounting Net Amount', #'Accounting Net Amount Difference','Accounting Net Amount Difference Absolute ', #'Activity Code', 'Age','Age WK', 'Asset Type Category','Base Currency','Base Net Amount', #'Bloomberg_Yellow_Key', 'B-P Net Amount', #'B-P Net Amount Difference','B-P Net Amount Difference Absolute', 'BreakID', 'Business Date','Cancel Amount','Cancel Flag','CUSIP','Custodian', 'Custodian Account', 'Derived Source','Description','ExpiryDate','ExternalComment1','ExternalComment2', 'ExternalComment3','Fund', #'FX Rate', #'Interest Amount', 'InternalComment1','InternalComment2', 'InternalComment3','Investment Type','Is Combined Data','ISIN','Keys', 'Mapped Custodian Account','Net Amount Difference','Net Amount Difference Absolute','Non Trade Description', #'OTE Custodian Account', #'Predicted Action','Predicted Status','Prediction Details', 'Price','Prime Broker', 'Quantity','SEDOL','Settle Date','SPM ID','Status', #'Strike Price', 'System Comments','Ticker','Trade Date','Trade Expenses','Transaction Category','Transaction ID','Transaction Type', 'Underlying Cusip','Underlying Investment ID','Underlying ISIN','Underlying Sedol','Underlying Ticker','Source Combination','_ID'] #'UnMapped'] add = ['ViewData.Side0_UniqueIds', 'ViewData.Side1_UniqueIds', # 'MetaData.0._RecordID','MetaData.1._RecordID', 'ViewData.Task Business Date'] # In[4710]: new_cols = ['ViewData.' + x for x in cols] + add cols_to_show = [ 'Account Type', 'Accounting Net Amount', #'Accounting Net Amount Difference', #'Activity Code', 'Age', 'Alt ID 1', 'Asset Type Category', #'Bloomberg_Yellow_Key', 'B-P Net Amount', #'B-P Net Amount Difference', #'B-P Net Amount Difference Absolute', 'BreakID', 'Business Date', #'Call Put Indicator', 'Cancel Amount', 'Cancel Flag', 'Commission', 'Currency', 'CUSIP', 'Custodian', 'Custodian Account', 'Department', 'Description', 'ExpiryDate', 'ExternalComment2', 'Fund', #'FX Rate', #'Interest Amount', 'InternalComment2', 'Investment ID', 'Investment Type', 'Is Combined Data', 'ISIN', 'Keys', 'Knowledge Date', 'Mapped Custodian Account', 'Net Amount Difference', 'Non Trade Description', #'OTE Custodian Account', #'OTE Ticker', 'PB Account Numeric', 'Portfolio ID', 'Portolio', 'Price', 'Prime Broker', #'Principal Amount', 'Quantity', #'Sec Fees', 'SEDOL', 'Settle Date', 'Status', #'Strike Price', 'System Comments', 'Ticker', 'Trade Date', 'Trade Expenses', 'Transaction Category', 'Transaction ID', 'Transaction Type', 'Underlying Cusip', 'Underlying Investment ID', 'Underlying ISIN', 'Underlying Sedol', 'Underlying Ticker', 'UserTran1', 'UserTran2', 'Value Date', ] add_cols_to_show = ['ViewData.Side0_UniqueIds', 'ViewData.Side1_UniqueIds'] viewdata_cols_to_show = ['ViewData.' + x for x in cols_to_show] + add_cols_to_show common_cols = ['ViewData.Accounting Net Amount', 'ViewData.Age', 'ViewData.Age WK', 'ViewData.Asset Type Category', 'ViewData.B-P Net Amount', 'ViewData.Base Net Amount','ViewData.CUSIP', 'ViewData.Cancel Amount', 'ViewData.Cancel Flag', #'ViewData.Commission', 'ViewData.Currency', 'ViewData.Custodian', 'ViewData.Custodian Account', 'ViewData.Description', 'ViewData.ExpiryDate', 'ViewData.Fund', 'ViewData.ISIN', 'ViewData.Investment Type', # 'ViewData.Keys', 'ViewData.Mapped Custodian Account', 'ViewData.Net Amount Difference', 'ViewData.Net Amount Difference Absolute', #'ViewData.OTE Ticker', 'ViewData.Price', 'ViewData.Prime Broker', 'ViewData.Quantity', 'ViewData.SEDOL', 'ViewData.SPM ID', 'ViewData.Settle Date', # 'ViewData.Strike Price', 'Date', 'ViewData.Ticker', 'ViewData.Trade Date', 'ViewData.Transaction Category', 'ViewData.Transaction Type', 'ViewData.Underlying Cusip', 'ViewData.Underlying ISIN', 'ViewData.Underlying Sedol','filter_key','ViewData.Status','ViewData.BreakID', 'ViewData.Side0_UniqueIds','ViewData.Side1_UniqueIds','ViewData._ID'] date_numbers_list = [1,2,3,4, 7,8,9,10,11, 14,15,16,17,18, 21,22,23,24,25, 28,29,30] filepaths_X_test = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Soros/JuneData/X_Test_153/x_test_153_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] filepaths_no_pair_id_data = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Soros/JuneData/X_Test_153/no_pair_ids_153_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] filepaths_no_pair_id_no_data_warning = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Soros/JuneData/X_Test_153/WARNING_no_pair_ids_153_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] filepaths_AUA = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Soros/JuneData/AUA/AUACollections_SOROS.AUA_HST_RecData_153_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] filepaths_MEO = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Soros/JuneData/MEO/MeoCollections_SOROS.MEO_HST_RecData_153_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] filepaths_final_prediction_table = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Soros/JuneData/Final_Predictions_153/Final_Predictions_Table_HST_RecData_153_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] filepaths_accuracy_table = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Soros/JuneData/Final_Predictions_153/Accuracy_Table_HST_RecData_153_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] filepaths_crosstab_table = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Soros/JuneData/Final_Predictions_153/Crosstab_Table_HST_RecData_153_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] # In[4711]: #df_170.shape # ## Read testing data # In[4712]: i = 0 for i in range(0,len(date_numbers_list)): meo = pd.read_csv(filepaths_MEO[i],usecols=new_cols) df1 = meo[~meo['ViewData.Status'].isin(['SMT','HST', 'OC', 'CT', 'Archive','SMR'])] #df = df[df['MatchStatus'] != 21] df1 = df1[~df1['ViewData.Status'].isnull()] df1 = df1.reset_index() df1 = df1.drop('index',1) # ## Machine generated output # In[4716]: df = df1.copy() # In[4717]: df = df.reset_index() df = df.drop('index',1) # In[4720]: df['Date'] = pd.to_datetime(df['ViewData.Task Business Date']) # In[4721]: #df['Date'] = pd.to_datetime(df['ViewData.Task Business Date']) # In[4722]: df = df[~df['Date'].isnull()] df = df.reset_index() df = df.drop('index',1) # In[4723]: pd.to_datetime(df['Date']) # In[4724]: df['Date'] = pd.to_datetime(df['Date']).dt.date # In[4725]: df['Date'] = df['Date'].astype(str) # In[4726]: # In[4727]: df = df[df['ViewData.Status'].isin(['OB','SPM','SDB','UOB','UDB','SMB'])] df = df.reset_index() df = df.drop('index',1) # In[4728]: df['ViewData.Side0_UniqueIds'] = df['ViewData.Side0_UniqueIds'].astype(str) df['ViewData.Side1_UniqueIds'] = df['ViewData.Side1_UniqueIds'].astype(str) df['flag_side0'] = df.apply(lambda x: len(x['ViewData.Side0_UniqueIds'].split(',')), axis=1) df['flag_side1'] = df.apply(lambda x: len(x['ViewData.Side1_UniqueIds'].split(',')), axis=1) # In[4729]: #df_170[(df_170['ViewData.Status']=='UMR')] # In[4730]: print('The Date value count is:') print(df['Date'].value_counts()) date_i = df['Date'].mode()[0] print('Choosing the date : ' + date_i) df = df.rename(columns= {'ViewData.B-P Net Amount':'ViewData.B-P Net Amount'}) sample = df[df['Date'] == date_i] sample = sample.reset_index() sample = sample.drop('index',1) # In[4945]: smb = sample[sample['ViewData.Status']=='SMB'].reset_index() smb = smb.drop('index',1) # In[4946]: #import glob #df_list = [] #path = "//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/AUA/*.csv" #for fname in glob.glob(path): # print(fname) # if "125" in fname: # df_list.append(pd.read_csv(fname)) # In[4947]: #dfff = pd.concat(df_list, axis=0) #dfff['Date'] = pd.to_datetime(dfff['ViewData.Task Business Date']) #dfff[dfff['ViewData.Status']=='UCB'].shape # In[4948]: #dfff[dfff['ViewData.Status']=='UCB'].groupby('Date')['ViewData.Age'].size() # In[4949]: #dfff[(dfff['ViewData.Status']=='UCB') & (dfff['Date']=='2020-06-30')]['ViewData.Side1_UniqueIds'].nunique() # In[4950]: smb_pb = smb.copy() smb_acc = smb.copy() # In[4951]: smb_pb['ViewData.Accounting Net Amount'] = np.nan smb_pb['ViewData.Side0_UniqueIds'] = np.nan smb_pb['ViewData.Status'] ='SMB-OB' smb_acc['ViewData.B-P Net Amount'] = np.nan smb_acc['ViewData.Side1_UniqueIds'] = np.nan smb_acc['ViewData.Status'] ='SMB-OB' # In[4952]: sample = sample[sample['ViewData.Status']!='SMB'] sample = sample.reset_index() sample = sample.drop('index',1) # In[4953]: # In[4954]: sample = pd.concat([sample,smb_pb,smb_acc],axis=0) sample = sample.reset_index() sample = sample.drop('index',1) # In[4955]: # In[4958]: sample['ViewData.Side0_UniqueIds'] = sample['ViewData.Side0_UniqueIds'].astype(str) sample['ViewData.Side1_UniqueIds'] = sample['ViewData.Side1_UniqueIds'].astype(str) # In[4959]: sample.loc[sample['ViewData.Side0_UniqueIds']=='nan','flag_side0'] = 0 sample.loc[sample['ViewData.Side1_UniqueIds']=='nan','flag_side1'] = 0 # In[4960]: # In[4961]: # In[4962]: sample.loc[sample['ViewData.Side1_UniqueIds']=='nan','Trans_side'] = 'B_side' sample.loc[sample['ViewData.Side0_UniqueIds']=='nan','Trans_side'] = 'A_side' sample.loc[sample['Trans_side']=='A_side','ViewData.B-P Currency'] = sample.loc[sample['Trans_side']=='A_side','ViewData.Currency'] sample.loc[sample['Trans_side']=='B_side','ViewData.Accounting Currency'] = sample.loc[sample['Trans_side']=='B_side','ViewData.Currency'] sample['ViewData.B-P Currency'] = sample['ViewData.B-P Currency'].astype(str) sample['ViewData.Accounting Currency'] = sample['ViewData.Accounting Currency'].astype(str) sample['ViewData.Mapped Custodian Account'] = sample['ViewData.Mapped Custodian Account'].astype(str) #sample['ViewData.Mapped Custodian Account'] = sample['ViewData.Mapped Custodian Account'].astype(str) sample['filter_key'] = sample.apply(lambda x: x['ViewData.Mapped Custodian Account'] + x['ViewData.B-P Currency'] if x['Trans_side']=='A_side' else x['ViewData.Mapped Custodian Account'] + x['ViewData.Accounting Currency'], axis=1) sample1 = sample[(sample['flag_side0']<=1) & (sample['flag_side1']<=1) & (sample['ViewData.Status'].isin(['OB','SPM','SDB','UDB','UOB','SMB-OB']))] sample1 = sample1.reset_index() sample1 = sample1.drop('index', 1) # In[4963]: sample1['ViewData.BreakID'] = sample1['ViewData.BreakID'].astype(int) # In[4964]: sample1 = sample1[sample1['ViewData.BreakID']!=-1] sample1 = sample1.reset_index() sample1 = sample1.drop('index',1) # In[4965]: sample1 = sample1.sort_values(['ViewData.BreakID','Date'], ascending =[True, False]) sample1 = sample1.reset_index() sample1 = sample1.drop('index',1) # In[4966]: # In[5252]: #sample1[sample1['ViewData.Status']=='SMB-OB'] # In[4968]: aa = sample1[sample1['Trans_side']=='A_side'] bb = sample1[sample1['Trans_side']=='B_side'] # In[4969]: aa['filter_key'] = aa['ViewData.Source Combination'].astype(str) + aa['ViewData.Mapped Custodian Account'].astype(str) + aa['ViewData.B-P Currency'].astype(str) bb['filter_key'] = bb['ViewData.Source Combination'].astype(str) + bb['ViewData.Mapped Custodian Account'].astype(str) + bb['ViewData.Accounting Currency'].astype(str) # In[4971]: aa = aa.reset_index() aa = aa.drop('index', 1) bb = bb.reset_index() bb = bb.drop('index', 1) # In[4972]: #'ViewData.Side0_UniqueIds', 'ViewData.Side1_UniqueIds' # In[4973]: bb = bb[~bb['ViewData.Accounting Net Amount'].isnull()] bb = bb.reset_index() bb = bb.drop('index',1) # In[4974]: # In[4975]: ###################### loop 3 ############################### pool =[] key_index =[] training_df =[] no_pair_ids = [] #max_rows = 5 for d in tqdm(aa['Date'].unique()): aa1 = aa.loc[aa['Date']==d,:][common_cols] bb1 = bb.loc[bb['Date']==d,:][common_cols] aa1 = aa1.reset_index() aa1 = aa1.drop('index',1) bb1 = bb1.reset_index() bb1 = bb1.drop('index', 1) bb1 = bb1.sort_values(by='filter_key',ascending =True) for key in (list(np.unique(np.array(list(aa1['filter_key'].values) + list(bb1['filter_key'].values))))): df1 = aa1[aa1['filter_key']==key] df2 = bb1[bb1['filter_key']==key] if df1.empty == False and df2.empty == False: #aa_df = pd.concat([aa1[aa1.index==i]]*repeat_num, ignore_index=True) #bb_df = bb1.loc[pool[len(pool)-1],:][common_cols].reset_index() #bb_df = bb_df.drop('index', 1) df1 = df1.rename(columns={'ViewData.BreakID':'ViewData.BreakID_A_side'}) df2 = df2.rename(columns={'ViewData.BreakID':'ViewData.BreakID_B_side'}) #dff = pd.concat([aa[aa.index==i],bb.loc[pool[i],:][accounting_vars]],axis=1) df1 = df1.reset_index() df2 = df2.reset_index() df1 = df1.drop('index', 1) df2 = df2.drop('index', 1) df1.columns = ['SideA.' + x for x in df1.columns] df2.columns = ['SideB.' + x for x in df2.columns] df1 = df1.rename(columns={'SideA.filter_key':'filter_key'}) df2 = df2.rename(columns={'SideB.filter_key':'filter_key'}) #dff = pd.concat([aa_df,bb_df],axis=1) dff = pd.merge(df1, df2, on='filter_key') training_df.append(dff) #key_index.append(i) #else: #no_pair_ids.append([aa1[(aa1['filter_key']=='key') & (aa1['ViewData.Status'].isin(['OB','SDB']))]['ViewData.Side1_UniqueIds'].values[0]]) # no_pair_ids.append(aa1[(aa1['filter_key']== key) & (aa1['ViewData.Status'].isin(['OB','SDB']))]['ViewData.Side1_UniqueIds'].values[0]) else: no_pair_ids.append([aa1[(aa1['filter_key']==key) & (aa1['ViewData.Status'].isin(['OB','SDB']))]['ViewData.Side1_UniqueIds'].values]) no_pair_ids.append([bb1[(bb1['filter_key']==key) & (bb1['ViewData.Status'].isin(['OB','SDB']))]['ViewData.Side0_UniqueIds'].values]) # In[4976]: #no_pair_ids = np.unique(np.concatenate(no_pair_ids,axis=1)[0]) # In[4977]: #pd.DataFrame(no_pair_ids).rename # In[4978]: if len(no_pair_ids) != 0: no_pair_ids = np.unique(np.concatenate(no_pair_ids,axis=1)[0]) no_pair_ids_df = pd.DataFrame(no_pair_ids) #no_pair_ids_df = no_pair_ids_df.rename(columns={'0':'filter_key'}) no_pair_ids_df.columns = ['filter_key'] no_pair_ids_df.to_csv(filepaths_no_pair_id_data[i]) else: with open(filepaths_no_pair_id_no_data_warning[i], 'w') as f: f.write('No no pair ids found for this setup and date combination') # In[4981]: # In[4980]: test_file = pd.concat(training_df) # In[4982]: test_file = test_file.reset_index() test_file = test_file.drop('index',1) # In[4983]: test_file['SideB.ViewData.BreakID_B_side'] = test_file['SideB.ViewData.BreakID_B_side'].astype('int64') test_file['SideA.ViewData.BreakID_A_side'] = test_file['SideA.ViewData.BreakID_A_side'].astype('int64') # In[4984]: model_cols = [ 'SideA.ViewData.Accounting Net Amount', 'SideA.ViewData.B-P Net Amount', 'SideA.ViewData.CUSIP', 'SideA.ViewData.Currency', #'SideA.ViewData.Description', 'SideA.ViewData.ISIN', 'SideB.ViewData.Accounting Net Amount', 'SideB.ViewData.B-P Net Amount', 'SideB.ViewData.CUSIP', 'SideB.ViewData.Currency', #'SideB.ViewData.Description', 'SideB.ViewData.ISIN', 'SideB.ViewData.Status','SideB.ViewData.BreakID_B_side', 'SideA.ViewData.Status','SideA.ViewData.BreakID_A_side', 'label'] y_col = ['label'] # In[4985]: test_file['SideB.ViewData.CUSIP'] = test_file['SideB.ViewData.CUSIP'].str.split(".",expand=True)[0] test_file['SideA.ViewData.CUSIP'] = test_file['SideA.ViewData.CUSIP'].str.split(".",expand=True)[0] # In[4986]: test_file['SideA.ViewData.ISIN'] = test_file['SideA.ViewData.ISIN'].astype(str) test_file['SideB.ViewData.ISIN'] = test_file['SideB.ViewData.ISIN'].astype(str) test_file['SideA.ViewData.CUSIP'] = test_file['SideA.ViewData.CUSIP'].astype(str) test_file['SideB.ViewData.CUSIP'] = test_file['SideB.ViewData.CUSIP'].astype(str) test_file['SideA.ViewData.Currency'] = test_file['SideA.ViewData.Currency'].astype(str) test_file['SideB.ViewData.Currency'] = test_file['SideB.ViewData.Currency'].astype(str) test_file['SideA.ViewData.Trade Date'] = test_file['SideA.ViewData.Trade Date'].astype(str) test_file['SideB.ViewData.Trade Date'] = test_file['SideB.ViewData.Trade Date'].astype(str) test_file['SideA.ViewData.Settle Date'] = test_file['SideA.ViewData.Settle Date'].astype(str) test_file['SideB.ViewData.Settle Date'] = test_file['SideB.ViewData.Settle Date'].astype(str) test_file['SideA.ViewData.Fund'] = test_file['SideA.ViewData.Fund'].astype(str) test_file['SideB.ViewData.Fund'] = test_file['SideB.ViewData.Fund'].astype(str) # In[4987]: #test_file[['SideA.ViewData.ISIN','SideB.ViewData.ISIN']] values_ISIN_A_Side = test_file['SideA.ViewData.ISIN'].values values_ISIN_B_Side = test_file['SideB.ViewData.ISIN'].values #test_file['ISIN_match'] = vec_equals_fun(values_ISIN_A_Side,values_ISIN_B_Side) values_CUSIP_A_Side = test_file['SideA.ViewData.CUSIP'].values values_CUSIP_B_Side = test_file['SideB.ViewData.CUSIP'].values # # values_CUSIP_A_Side = test_file['SideA.ViewData.Currency'].values # values_CUSIP_B_Side = test_file['SideB.ViewData.Currency'].values values_Currency_match_A_Side = test_file['SideA.ViewData.Currency'].values values_Currency_match_B_Side = test_file['SideA.ViewData.Currency'].values values_Trade_Date_match_A_Side = test_file['SideA.ViewData.Trade Date'].values values_Trade_Date_match_B_Side = test_file['SideB.ViewData.Trade Date'].values values_Settle_Date_match_A_Side = test_file['SideA.ViewData.Settle Date'].values values_Settle_Date_match_B_Side = test_file['SideB.ViewData.Settle Date'].values values_Fund_match_A_Side = test_file['SideA.ViewData.Fund'].values values_Fund_match_B_Side = test_file['SideB.ViewData.Fund'].values test_file['ISIN_match'] = vec_equals_fun(values_ISIN_A_Side,values_ISIN_B_Side) test_file['CUSIP_match'] = vec_equals_fun(values_CUSIP_A_Side,values_CUSIP_B_Side) test_file['Currency_match'] = vec_equals_fun(values_Currency_match_A_Side,values_Currency_match_B_Side) test_file['Trade_Date_match'] = vec_equals_fun(values_Trade_Date_match_A_Side,values_Trade_Date_match_B_Side) test_file['Settle_Date_match'] = vec_equals_fun(values_Settle_Date_match_A_Side,values_Settle_Date_match_B_Side) test_file['Fund_match'] = vec_equals_fun(values_Fund_match_A_Side,values_Fund_match_B_Side) # In[4988]: #test_file['ISIN_match'] = test_file.apply(lambda x: 1 if x['SideA.ViewData.ISIN']==x['SideB.ViewData.ISIN'] else 0, axis=1) #test_file['CUSIP_match'] = test_file.apply(lambda x: 1 if x['SideA.ViewData.CUSIP']==x['SideB.ViewData.CUSIP'] else 0, axis=1) #test_file['Currency_match'] = test_file.apply(lambda x: 1 if x['SideA.ViewData.Currency']==x['SideB.ViewData.Currency'] else 0, axis=1) # In[4989]: #test_file['Trade_Date_match'] = test_file.apply(lambda x: 1 if x['SideA.ViewData.Trade Date']==x['SideB.ViewData.Trade Date'] else 0, axis=1) #test_file['Settle_Date_match'] = test_file.apply(lambda x: 1 if x['SideA.ViewData.Settle Date']==x['SideB.ViewData.Settle Date'] else 0, axis=1) #test_file['Fund_match'] = test_file.apply(lambda x: 1 if x['SideA.ViewData.Fund']==x['SideB.ViewData.Fund'] else 0, axis=1) # In[4990]: test_file['Amount_diff_1'] = test_file['SideA.ViewData.Accounting Net Amount'] - test_file['SideB.ViewData.B-P Net Amount'] test_file['Amount_diff_2'] = test_file['SideB.ViewData.Accounting Net Amount'] - test_file['SideA.ViewData.B-P Net Amount'] # In[4991]: #test_file = pd.read_csv('//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/OakTree/X_test_files_after_loop/meo_testing_HST_RecData_379_06_19_2020_test_file_with_ID.csv') # In[4992]: #test_file = test_file.drop('Unnamed: 0',1) # In[4993]: test_file['Trade_date_diff'] = (pd.to_datetime(test_file['SideA.ViewData.Trade Date']) - pd.to_datetime(test_file['SideB.ViewData.Trade Date'])).dt.days test_file['Settle_date_diff'] = (pd.to_datetime(test_file['SideA.ViewData.Settle Date']) - pd.to_datetime(test_file['SideB.ViewData.Settle Date'])).dt.days # In[4994]: # In[4995]: ############ Fund match new ######## values_Fund_match_A_Side = test_file['SideA.ViewData.Fund'].values values_Fund_match_B_Side = test_file['SideB.ViewData.Fund'].values #test_file['ISIN_match'] = vec_(values_ISIN_A_Side,values_ISIN_B_Side) #test_file['SideA.ViewData.Fund'] = test_file.apply(lambda x : fundmatch(x['SideA.ViewData.Fund']), axis=1) test_file['SideA.ViewData.Fund'] = vec_fund_match(values_Fund_match_A_Side) #test_file['SideB.ViewData.Fund'] = test_file.apply(lambda x : fundmatch(x['SideB.ViewData.Fund']), axis=1) test_file['SideB.ViewData.Fund'] = vec_fund_match(values_Fund_match_B_Side) # In[ ]: # In[4996]: #test_file['SideA.ViewData.Fund'] # In[4997]: #test_file['SideB.ViewData.Transaction Type'] = test_file['SideB.ViewData.Transaction Type'].apply(lambda x : mhreplaced(x)) # In[4998]: #test_file['SideA.ViewData.Transaction Type'] = test_file['SideA.ViewData.Transaction Type'].apply(lambda x : mhreplaced(x)) # In[4999]: ############## values_transaction_type_match_A_Side = test_file['SideA.ViewData.Transaction Type'].values values_transaction_type_match_B_Side = test_file['SideB.ViewData.Transaction Type'].values #test_file['ISIN_match'] = vec_(values_ISIN_A_Side,values_ISIN_B_Side) #test_file['SideA.ViewData.Fund'] = test_file.apply(lambda x : fundmatch(x['SideA.ViewData.Fund']), axis=1) test_file['SideA.ViewData.Transaction Type'] = vec_tt_match(values_transaction_type_match_A_Side) #test_file['SideB.ViewData.Fund'] = test_file.apply(lambda x : fundmatch(x['SideB.ViewData.Fund']), axis=1) test_file['SideB.ViewData.Transaction Type'] = vec_tt_match(values_transaction_type_match_B_Side) # In[5000]: test_file['ViewData.Combined Transaction Type'] = test_file['SideA.ViewData.Transaction Type'].astype(str) + test_file['SideB.ViewData.Transaction Type'].astype(str) # In[5001]: #train_full_new1['ViewData.Combined Transaction Type'] = train_full_new1['SideA.ViewData.Transaction Type'].astype(str) + train_full_new1['SideB.ViewData.Transaction Type'].astype(str) test_file['ViewData.Combined Fund'] = test_file['SideA.ViewData.Fund'].astype(str) + test_file['SideB.ViewData.Fund'].astype(str) # In[ ]: # In[5002]: values_ISIN_A_Side = test_file['SideA.ViewData.ISIN'].values values_ISIN_B_Side = test_file['SideB.ViewData.ISIN'].values test_file['SideA.ISIN_NA'] = vec_nan_fun(values_ISIN_A_Side) test_file['SideB.ISIN_NA'] = vec_nan_fun(values_ISIN_A_Side) #test_file['SideA.ISIN_NA'] = test_file.apply(lambda x: 1 if x['SideA.ViewData.ISIN']=='nan' else 0, axis=1) #test_file['SideB.ISIN_NA'] = test_file.apply(lambda x: 1 if x['SideB.ViewData.ISIN']=='nan' else 0, axis=1) # In[5666]: # In[ ]: # In[5669]: values_ISIN_A_Side = test_file['SideA.ViewData.ISIN'].values values_ISIN_B_Side = test_file['SideB.ViewData.ISIN'].values values_CUSIP_A_Side = test_file['SideA.ViewData.CUSIP'].values values_CUSIP_B_Side = test_file['SideB.ViewData.CUSIP'].values test_file['SideB.ViewData.key_NAN']= vec_a_key_match_fun(values_CUSIP_B_Side,values_ISIN_B_Side)[0] test_file['SideB.ViewData.Common_key'] = vec_a_key_match_fun(values_CUSIP_B_Side,values_ISIN_B_Side)[1] test_file['SideA.ViewData.key_NAN'] = vec_b_key_match_fun(values_CUSIP_A_Side,values_ISIN_A_Side)[0] test_file['SideA.ViewData.Common_key'] = vec_b_key_match_fun(values_CUSIP_A_Side,values_ISIN_A_Side)[1] # In[ ]: #test_file[['SideB.ViewData.key_NAN','SideB.ViewData.Common_key']] = test_file.apply(lambda x: b_keymatch(x['SideB.ViewData.CUSIP'], x['SideB.ViewData.ISIN']), axis=1) #test_file[['SideA.ViewData.key_NAN','SideA.ViewData.Common_key']] = test_file.apply(lambda x: a_keymatch(x['SideA.ViewData.CUSIP'],x['SideA.ViewData.ISIN']), axis=1) # In[ ]: values_key_NAN_B_Side = test_file['SideB.ViewData.key_NAN'].values values_key_NAN_A_Side = test_file['SideA.ViewData.key_NAN'].values test_file['All_key_nan'] = vec_nan_equal_fun(values_key_NAN_B_Side,values_key_NAN_A_Side ) #test_file['All_key_nan'] = test_file.apply(lambda x: 1 if x['SideB.ViewData.key_NAN']==1 and x['SideA.ViewData.key_NAN']==1 else 0, axis=1) # In[5005]: test_file['SideB.ViewData.Common_key'] = test_file['SideB.ViewData.Common_key'].astype(str) test_file['SideA.ViewData.Common_key'] = test_file['SideA.ViewData.Common_key'].astype(str) values_Common_key_B_Side = test_file['SideB.ViewData.Common_key'].values values_Common_key_A_Side = test_file['SideA.ViewData.Common_key'].values values_All_key_NAN = test_file['All_key_nan'].values #values_accounting_nan = np.where((values_CUSIP_B_Side == 'nan') & (values_ISIN_B_Side == 'nan'),1,0) #values_b_common_key = np.where((values_CUSIP_B_Side == 'nan') & (values_ISIN_B_Side == 'nan'),'NA', # np.where((values_CUSIP_B_Side != 'nan') & (values_ISIN_B_Side == 'nan'), values_CUSIP_B_Side, # np.where((values_CUSIP_B_Side == 'nan') & (values_ISIN_B_Side != 'nan'),values_ISIN_B_Side,values_ISIN_B_Side))) test_file['new_key_match']= vec_new_key_match_fun(values_Common_key_B_Side,values_Common_key_A_Side,values_All_key_NAN) # In[5006]: #test_file['new_key_match'] = test_file.apply(lambda x: 1 if x['SideB.ViewData.Common_key']==x['SideA.ViewData.Common_key'] and x['All_key_nan']==0 else 0, axis=1) # In[5007]: # In[5008]: model_cols = [ # 'SideA.ViewData.Accounting Net Amount', 'SideA.ViewData.B-P Net Amount', 'SideA.ViewData.Price', 'SideA.ViewData.Quantity', 'SideB.ViewData.Accounting Net Amount', # 'SideB.ViewData.B-P Net Amount', 'SideB.ViewData.Price', 'SideB.ViewData.Quantity', 'Trade_Date_match', 'Settle_Date_match', # 'Fund_match', 'Amount_diff_2', 'Trade_date_diff', 'Settle_date_diff', 'SideA.ISIN_NA', 'SideB.ISIN_NA', 'ViewData.Combined Fund', 'ViewData.Combined Transaction Type', 'All_key_nan', 'new_key_match', 'SideA.ViewData._ID', 'SideB.ViewData._ID', 'SideB.ViewData.Status', 'SideB.ViewData.BreakID_B_side', 'SideA.ViewData.Status', 'SideA.ViewData.BreakID_A_side', 'SideB.ViewData.Side0_UniqueIds', 'SideA.ViewData.Side1_UniqueIds'] # In[4933]: test_file.to_csv(filepaths_X_test[i]) # In[930]: #test_file['SideA.ViewData.BreakID_A_side'].value_counts() # In[4299]: print('Done till X_Test creation') print(datetime.now()) #test_file = pd.read_csv("//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/X_Test/x_test_125_2020-06-8.csv") # # ## In[4300]: # # #test_file = test_file.drop('Unnamed: 0',1) # ## Test file served into the model # In[5009]: X_test = test_file[model_cols] # In[5010]: X_test = X_test.reset_index() X_test = X_test.drop('index',1) # In[5011]: X_test = X_test.fillna(0) # In[5012]: # In[5013]: X_test = X_test.drop_duplicates() X_test = X_test.reset_index() X_test = X_test.drop('index',1) # In[5014]: # ## Model Pickle file import # In[5015]: # In[5016]: #filename = 'Oak_W125_model_with_umb.sav' #filename = '125_with_umb_without_des_and_many_to_many.sav' #filename = '125_with_umb_and_price_without_des_and_many_to_many_tdsd2.sav' filename = 'Soros_new_model_V1.sav' clf = pickle.load(open(filename, 'rb')) # In[5017]: # In[5018]: # ## Predictions # In[5019]: # Actual class predictions rf_predictions = clf.predict(X_test.drop(['SideB.ViewData.Status','SideB.ViewData.BreakID_B_side', 'SideA.ViewData.Status','SideA.ViewData.BreakID_A_side','SideA.ViewData._ID','SideB.ViewData._ID','SideB.ViewData.Side0_UniqueIds','SideA.ViewData.Side1_UniqueIds'],1)) # Probabilities for each class rf_probs = clf.predict_proba(X_test.drop(['SideB.ViewData.Status','SideB.ViewData.BreakID_B_side', 'SideA.ViewData.Status','SideA.ViewData.BreakID_A_side','SideA.ViewData._ID','SideB.ViewData._ID','SideB.ViewData.Side0_UniqueIds','SideA.ViewData.Side1_UniqueIds'],1))[:, 1] # In[5020]: probability_class_0 = clf.predict_proba(X_test.drop(['SideB.ViewData.Status','SideB.ViewData.BreakID_B_side','SideA.ViewData.Status','SideA.ViewData.BreakID_A_side','SideA.ViewData._ID','SideB.ViewData._ID','SideB.ViewData.Side0_UniqueIds','SideA.ViewData.Side1_UniqueIds'],1))[:, 0] probability_class_1 = clf.predict_proba(X_test.drop(['SideB.ViewData.Status','SideB.ViewData.BreakID_B_side', 'SideA.ViewData.Status','SideA.ViewData.BreakID_A_side','SideA.ViewData._ID','SideB.ViewData._ID','SideB.ViewData.Side0_UniqueIds','SideA.ViewData.Side1_UniqueIds'],1))[:, 1] probability_class_2 = clf.predict_proba(X_test.drop(['SideB.ViewData.Status','SideB.ViewData.BreakID_B_side','SideA.ViewData.Status','SideA.ViewData.BreakID_A_side','SideA.ViewData._ID','SideB.ViewData._ID','SideB.ViewData.Side0_UniqueIds','SideA.ViewData.Side1_UniqueIds'],1))[:, 2] probability_class_3 = clf.predict_proba(X_test.drop(['SideB.ViewData.Status','SideB.ViewData.BreakID_B_side', 'SideA.ViewData.Status','SideA.ViewData.BreakID_A_side','SideA.ViewData._ID','SideB.ViewData._ID','SideB.ViewData.Side0_UniqueIds','SideA.ViewData.Side1_UniqueIds'],1))[:, 3] #probability_class_4 = clf1.predict_proba(X_test.drop(['SideB.ViewData.Status','SideB.ViewData.BreakID_B_side', 'SideA.ViewData.Status','SideA.ViewData.BreakID_A_side','SideA.ViewData._ID','SideB.ViewData._ID','SideB.ViewData.Side0_UniqueIds','SideA.ViewData.Side1_UniqueIds'],1))[:, 4] # In[5021]: X_test['Predicted_action'] = rf_predictions #X_test['Predicted_action_probabilty'] = rf_probs X_test['probability_No_pair'] = probability_class_0 #X_test['probability_Partial_match'] = probability_class_1 #X_test['probability_UMB'] = probability_class_1 X_test['probability_UMB'] = probability_class_1 X_test['probability_UMR'] = probability_class_2 X_test['probability_UMT'] = probability_class_3 # In[5022]: # ## Prediction Table # In[5023]: X_test.loc[(X_test['Predicted_action']=='UMR_One_to_One') & ((X_test['Amount_diff_2']!=0) | (X_test['Amount_diff_2']!=0)),'Predicted_action'] = 'Unrecognized' # In[5024]: # In[5025]: # In[5026]: ###### Probability filter for UMT and UMB ################ #X_test.loc[(X_test['Predicted_action']=='UMT_One_to_One') & (X_test['probability_UMT']<0.90) & (X_test['probability_No_pair']>0.05),'Predicted_action'] = 'No-Pair' #X_test.loc[(X_test['Predicted_action']=='UMB_One_to_One') & (X_test['probability_UMB']<0.75) & (X_test['probability_No_pair']>0.2),'Predicted_action'] = 'No-Pair' #X_test.loc[(X_test['Predicted_action']=='UMR_One_to_One') & (X_test['probability_UMR']<0.90) & (X_test['probability_No_pair']>0.05),'Predicted_actionX_test.loc[(X_test['Predicted_action']=='No-Pair') & (X_test['probability_No_pair']<0.9) & (X_test['probability_UMB']>0.05),'Predicted_action'] = 'UMB_One_to_One' #X_test.loc[(X_test['Predicted_action']=='No-Pair') & (X_test['probability_No_pair']<0.95) & (X_test['probability_UMB']>0.05),'Predicted_action'] = 'UMB_One_to_One' #X_test.loc[(X_test['Predicted_action']=='UMR_One_to_One') & (X_test['Settle_date_diff']>4),'Predicted_action'] = 'No-Pair' #X_test.loc[(X_test['Predicted_action']=='UMR_One_to_One') & (X_test['Settle_date_diff']<-4),'Predicted_action'] = 'No-Pair' # In[5027]: #X_test.loc[(X_test['SideB.ViewData.Status']=='SDB') & (X_test['SideA.ViewData.Status']=='OB') & (X_test['Predicted_action']=='No-Pair'),'Predicted_action'] = 'SDB/Open Break' # In[5028]: prediction_table = X_test.groupby('SideB.ViewData.BreakID_B_side')['Predicted_action'].unique().reset_index() # In[5029]: #prob1 = X_test.groupby('SideB.ViewData.BreakID_B_side')['probability_No_pair'].mean().reset_index() # In[5030]: prediction_table['len'] = prediction_table['Predicted_action'].str.len() # In[5031]: prediction_table['No_Pair_flag'] = prediction_table['Predicted_action'].apply(lambda x: 1 if 'No-Pair' in x else 0) # In[5032]: prediction_table['UMB_flag'] = prediction_table['Predicted_action'].apply(lambda x: 1 if 'UMB_One_to_One' in x else 0) prediction_table['UMT_flag'] = prediction_table['Predicted_action'].apply(lambda x: 1 if 'UMT_One_to_One' in x else 0) prediction_table['UMR_flag'] = prediction_table['Predicted_action'].apply(lambda x: 1 if 'UMR_One_to_One' in x else 0) # In[5033]: # In[5034]: # In[5035]: umr_array = X_test[X_test['Predicted_action']=='UMR_One_to_One'].groupby(['SideB.ViewData.BreakID_B_side'])['SideA.ViewData.BreakID_A_side'].unique().reset_index() umt_array = X_test[X_test['Predicted_action']=='UMT_One_to_One'].groupby(['SideB.ViewData.BreakID_B_side'])['SideA.ViewData.BreakID_A_side'].unique().reset_index() umb_array = X_test[X_test['Predicted_action']=='UMB_One_to_One'].groupby(['SideB.ViewData.BreakID_B_side'])['SideA.ViewData.BreakID_A_side'].unique().reset_index() # In[5036]: umr_array.columns = ['SideB.ViewData.BreakID_B_side', 'Predicted_UMR_array'] umt_array.columns = ['SideB.ViewData.BreakID_B_side', 'Predicted_UMT_array'] umb_array.columns = ['SideB.ViewData.BreakID_B_side', 'Predicted_UMB_array'] # In[5037]: prediction_table = pd.merge(prediction_table,umr_array, on='SideB.ViewData.BreakID_B_side', how='left' ) prediction_table = pd.merge(prediction_table,umt_array, on='SideB.ViewData.BreakID_B_side', how='left' ) prediction_table = pd.merge(prediction_table,umb_array, on='SideB.ViewData.BreakID_B_side', how='left' ) # In[5038]: #prediction_table #X_test[X_test['SideB.ViewData.Side0_UniqueIds']=='2495_125897734_Advent Geneva'] # In[5039]: prediction_table['Final_prediction'] = prediction_table.apply(lambda x: 'UMR_One_to_One' if x['UMR_flag']==1 else('UMT_One_to_One' if x['len']==1 and x['UMT_flag']==1 else('UMB_One_to_UMB' if x['len']==1 and x['UMB_flag']==1 else('No-Pair' if x['len']==1 else 'Undecided'))), axis=1) # In[5040]: # In[5042]: prediction_table['UMT_flag'] = prediction_table['Predicted_action'].apply(lambda x: 1 if 'UMT_One_to_One' in x else 0) prediction_table['UMB_flag'] = prediction_table['Predicted_action'].apply(lambda x: 1 if 'UMB_One_to_One' in x else 0) # In[5043]: prediction_table.loc[(prediction_table['UMB_flag']==1) & (prediction_table['len']==2),'Final_prediction']='UMB_One_to_One' prediction_table.loc[(prediction_table['UMT_flag']==1) & (prediction_table['len']==2),'Final_prediction']='UMT_One_to_One' # In[5044]: prediction_table.loc[(prediction_table['Final_prediction']=='Undecided') & (prediction_table['len']==2),'Final_prediction']='No-Pair/Unrecognized' # In[5045]: prediction_table.loc[(prediction_table['Final_prediction']=='Undecided') & (prediction_table['UMT_flag']==1),'Final_prediction']='UMT_One_to_One' # In[5046]: prediction_table.loc[(prediction_table['Final_prediction']=='Undecided') & (prediction_table['UMB_flag']==1),'Final_prediction']='UMB_One_to_One' # In[5047]: # In[5049]: #X_test[(X_test['Predicted_action']=='UMR_One_to_One') & (X_test['SideB.ViewData.BreakID_B_side']==1346769635)] # In[5050]: prediction_table.loc[prediction_table['Final_prediction']=='UMR_One_to_One', 'Final_predicted_break'] = prediction_table.loc[prediction_table['Final_prediction']=='UMR_One_to_One', 'Predicted_UMR_array'] # In[5051]: prediction_table.loc[prediction_table['Final_prediction']=='UMT_One_to_One', 'Final_predicted_break'] = prediction_table.loc[prediction_table['Final_prediction']=='UMT_One_to_One', 'Predicted_UMT_array'] prediction_table.loc[prediction_table['Final_prediction']=='UMB_One_to_One', 'Final_predicted_break'] = prediction_table.loc[prediction_table['Final_prediction']=='UMB_One_to_One', 'Predicted_UMB_array'] #prediction_table.loc[prediction_table['Final_prediction']=='No-Pair', 'Final_predicted_break'] = prediction_table.loc[prediction_table['Final_prediction']=='No-Pair', ''] # In[5052]: prediction_table['predicted_break_len'] = prediction_table['Final_predicted_break'].str.len() # In[5053]: # In[5054]: #prediction_table[(prediction_table['predicted_break_len']>1) & (prediction_table['Final_prediction']=='UMT_One_to_One')] # In[5055]: #prediction_table[['SideB.ViewData.BreakID_B_side', 'Final_prediction', 'Final_predicted_break']] # In[5056]: X_test['prob_key'] = X_test['SideB.ViewData.BreakID_B_side'].astype(str) + X_test['Predicted_action'] prediction_table['prob_key'] = prediction_table['SideB.ViewData.BreakID_B_side'].astype(str) + prediction_table['Final_prediction'] # In[5057]: user_prob = X_test.groupby('prob_key')[['probability_UMR','probability_UMT','probability_UMB']].max().reset_index() open_prob = X_test.groupby('prob_key')['probability_No_pair'].mean().reset_index() # In[5058]: #prediction_table = prediction_table.drop(,1) prediction_table = pd.merge(prediction_table,user_prob, on='prob_key', how='left') prediction_table = pd.merge(prediction_table,open_prob, on='prob_key', how='left') # In[5059]: prediction_table = prediction_table.drop('prob_key',1) # In[5060]: # In[5062]: prediction_table = pd.merge(prediction_table, X_test[['SideB.ViewData.BreakID_B_side','SideA.ViewData._ID','SideB.ViewData._ID']].drop_duplicates(['SideB.ViewData.BreakID_B_side','SideB.ViewData._ID']), on ='SideB.ViewData.BreakID_B_side', how='left') # In[5063]: # ## Merging PB side Break ID's # In[5065]: #pb_break_ids = prediction_table[~prediction_table['Final_predicted_break'].isnull()][['Final_prediction','Final_predicted_break']] # In[4358]: #pb_break_ids = pb_break_ids.reset_index() #pb_break_ids = pb_break_ids.drop('index',1) # In[1706]: #pb_break_ids['Final_predicted_break'] = pb_break_ids['Final_predicted_break'].apply(lambda x: str(x).replace("[",'')) #pb_break_ids['Final_predicted_break'] = pb_break_ids['Final_predicted_break'].apply(lambda x: str(x).replace("]",'')) # In[2444]: #pb_break_ids['Final_predicted_break'].unique() # In[1708]: #id_list = [] #id_list2 = [] #for i in pb_break_ids['Final_predicted_break'].unique(): # id_list.append(i.split(' ')) #for j in np.concatenate(id_list,axis=0): # if j!='': # id_list2.append(j.replace("\n",'')) # In[1709]: #new_ob_ids =[] # #for i in X_test['SideA.ViewData.BreakID_A_side'].astype(str).unique(): # if i not in np.array(id_list2,dtype="O"): # new_ob_ids.append(i) # In[1710]: #prediction_table2 = pd.DataFrame(np.array(new_ob_ids)) # In[1711]: #prediction_table2.columns = ['SideB.ViewData.BreakID_B_side'] # In[1712]: #prediction_table2['Final_prediction'] = 'No-Pair' # In[1713]: #prediction_table2['Side'] = 'P-B Side' # In[1714]: #prediction_table['Side'] = 'Accounting Side' # In[2074]: #prediction_table3 = prediction_table # In[2442]: #prediction_table3 = pd.concat([prediction_table, prediction_table2], axis=0) # In[1716]: #prediction_table3 = prediction_table3.reset_index() #prediction_table3 = prediction_table3.drop('index',1) # In[1717]: #prediction_table3 = prediction_table3[prediction_table.columns] # In[2443]: #prediction_table3[['SideB.ViewData.BreakID_B_side', 'Final_prediction', 'Final_predicted_break','Side']] # In[1719]: #ids_for_comment = prediction_table3[['SideB.ViewData.BreakID_B_side', 'Final_prediction', 'Final_predicted_break','Side']] # In[2445]: #ids_for_comment # In[1721]: #ids_for_comment.to_csv('//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/Input for comment prediction/prediction_table_testing_HST_RecData_125_1159652110_06-19-2020.csv') # ## Merging with User Action Data # In[5474]: prediction_table3 = prediction_table # In[5475]: aua = pd.read_csv(filepaths_AUA[i]) # In[5476]: #test_file.to_csv("//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/OakTree/JuneData/X_Test/x_test_2020-06-29.csv") # In[5477]: # In[5478]: aua = aua[~((aua['LastPerformedAction']==0) & (aua['ViewData.Status']=='SDB'))] aua = aua.reset_index() aua = aua.drop('index',1) # In[5479]: # In[5480]: aua = aua[aua['ViewData.Status'].isin(['UMR','UMB','UMT','OB','SDB','UCB'])] aua = aua.reset_index() aua = aua.drop('index',1) # In[5481]: # In[5483]: if 'MetaData.0._ParentID' in aua.columns: aua_id_match = aua[['MetaData.0._ParentID','ViewData.Status','ViewData.Age','ViewData.BreakID','ViewData._ID','ViewData.Side0_UniqueIds','ViewData.Side1_UniqueIds']] print('MetaData.0._ParentID is present') else: aua_id_match = aua[['ViewData.Status','ViewData.Age','ViewData.BreakID','ViewData._ID','ViewData.Side0_UniqueIds','ViewData.Side1_UniqueIds']] aua_id_match['MetaData.0._ParentID'] = np.nan print('MetaData.0._ParentID is absent') # Set the order of columns aua_id_match['MetaData.0._ParentID'] = aua_id_match['MetaData.0._ParentID'].astype(str) aua_id_match = aua_id_match[['MetaData.0._ParentID','ViewData.Status','ViewData.Age','ViewData.BreakID','ViewData._ID','ViewData.Side0_UniqueIds','ViewData.Side1_UniqueIds']] aua_id_match.columns = ['SideB.ViewData._ID','Actual_Status','ViewData.Age','ViewData.BreakID','AUA_ViewData._ID','ViewData.Side0_UniqueIds','ViewData.Side1_UniqueIds'] aua_id_match = aua_id_match.drop_duplicates() aua_id_match = aua_id_match.reset_index() aua_id_match = aua_id_match.drop('index',1) ######################################################################################################## aua_open_status = aua[['ViewData.BreakID','ViewData.Status']] aua_open_status.columns = ['SideB.ViewData.BreakID_B_side','Actual_Status_Open'] aua_open_status = aua_open_status.drop_duplicates() aua_open_status = aua_open_status.reset_index() aua_open_status = aua_open_status.drop('index',1) # In[5484]: # In[5485]: aua_open_status['SideB.ViewData.BreakID_B_side'] = aua_open_status['SideB.ViewData.BreakID_B_side'].astype(int).astype(str) prediction_table3['SideB.ViewData.BreakID_B_side'] = prediction_table3['SideB.ViewData.BreakID_B_side'].astype(int).astype(str) # In[5486]: # In[5487]: prediction_table3['SideB.ViewData._ID'] = prediction_table3['SideB.ViewData._ID'].fillna('Not_generated') prediction_table3['SideA.ViewData._ID'] = prediction_table3['SideA.ViewData._ID'].fillna('Not_generated') # In[5488]: # In[5489]: #aua_id_match['len_side0'] = aua_id_match.apply(lambda x: len(x['Actual_Status'].split(',')), axis=1) #aua_id_match['len_side1'] = aua_id_match.apply(lambda x: len(x['Actual_Status'].split(',')), axis=1) # In[5490]: #aua_one_side = aua_id_match.groupby(['ViewData.Side1_UniqueIds'])['Actual_Status'].unique().reset_index() #aua_zero_side = aua_id_match.groupby(['ViewData.Side0_UniqueIds'])['Actual_Status'].unique().reset_index() # In[5491]: aua_id_match['combined_flag'] = aua_id_match.apply(lambda x: 1 if 'Combined' in x['AUA_ViewData._ID'] else 0,axis=1) # In[5492]: #aua_id_match[''.sort_values(['ViewData.Side0_UniqueIds']) # In[5493]: aua_id_match1 = aua_id_match[aua_id_match['combined_flag']!=1] aua_id_match1 = aua_id_match1.reset_index() aua_id_match1 = aua_id_match1.drop('index',1) # In[5494]: side1_repeat = aua_id_match1['ViewData.Side1_UniqueIds'].value_counts().reset_index() side0_repeat = aua_id_match1['ViewData.Side0_UniqueIds'].value_counts().reset_index() # In[5495]: # In[5497]: aua_id_match1['1_repeat_flag'] = aua_id_match1.apply(lambda x: 1 if x['ViewData.Side1_UniqueIds'] in side1_repeat[side1_repeat['ViewData.Side1_UniqueIds']>1]['index'].values else 0, axis=1) aua_id_match1['0_repeat_flag'] = aua_id_match1.apply(lambda x: 1 if x['ViewData.Side0_UniqueIds'] in side0_repeat[side0_repeat['ViewData.Side0_UniqueIds']>1]['index'].values else 0, axis=1) # In[5498]: aua_id_match2 = aua_id_match1[~((aua_id_match1['1_repeat_flag']==1) & (aua_id_match1['Actual_Status']=='OB'))] aua_id_match2 = aua_id_match2.reset_index() aua_id_match2 = aua_id_match2.drop('index',1) # In[5499]: aua_id_match3 = aua_id_match2[~((aua_id_match2['0_repeat_flag']==1) & (aua_id_match2['Actual_Status']=='OB'))] aua_id_match3 = aua_id_match3.reset_index() aua_id_match3 = aua_id_match3.drop('index',1) # In[5500]: #aua_zero_side['len_side0'].value_counts() #aua_open_status['SideB.ViewData.BreakID_B_side'].nunique() # In[5501]: #aua_sub99[aua_sub99['ViewData.Side0_UniqueIds'] == '789_125897734_Advent Geneva'] # In[5502]: # In[5505]: pb_side = X_test.groupby('SideA.ViewData.BreakID_A_side')['Predicted_action'].unique().reset_index() # In[5506]: pb_side['len'] = pb_side['Predicted_action'].apply(lambda x: len(x)) # In[5507]: pb_side['No_Pair_flag'] = pb_side.apply(lambda x: 1 if 'No-Pair' in x['Predicted_action'] else 0, axis=1) # In[5508]: pb_side_open_ids = pb_side[(pb_side['len']==1) & (pb_side['No_Pair_flag']==1)]['SideA.ViewData.BreakID_A_side'] # In[ ]: # In[5509]: # In[5510]: # In[5511]: prediction_table_new = pd.merge(prediction_table3, aua_id_match3, on='SideB.ViewData._ID', how='left') # In[5512]: # In[ ]: # In[5514]: aua_id_match4 = aua_id_match3.rename(columns = {'ViewData.BreakID': 'SideB.ViewData.BreakID_B_side'}) aua_id_match4 = aua_id_match4.rename(columns = {'Actual_Status': 'Actual_Status_Open'}) # In[5515]: aua_id_match4['SideB.ViewData.BreakID_B_side'] = aua_id_match4['SideB.ViewData.BreakID_B_side'].astype(str) # In[5516]: #prediction_table_new = pd.merge(prediction_table_new ,aua_open_status, on='SideB.ViewData.BreakID_B_side', how='left') prediction_table_new = pd.merge(prediction_table_new ,aua_id_match4[['SideB.ViewData.BreakID_B_side','Actual_Status_Open']], on='SideB.ViewData.BreakID_B_side', how='left') # In[5517]: #prediction_table_new # In[5518]: # In[5519]: prediction_table_new.loc[prediction_table_new['Final_prediction']=='No-Pair/Unrecognized','Final_prediction'] = 'No-Pair' # In[5520]: prediction_table_new.loc[prediction_table_new['Actual_Status'].isnull()] # In[5521]: prediction_table_new.loc[~prediction_table_new['Actual_Status_Open'].isnull(),'Actual_Status'] = prediction_table_new.loc[~prediction_table_new['Actual_Status_Open'].isnull(),'Actual_Status_Open'] # In[5522]: prediction_table_new.loc[~prediction_table_new['Actual_Status_Open'].isnull(),:] # In[5523]: # In[5524]: prediction_table_new.loc[prediction_table_new['Actual_Status']=='OB','Actual_Status'] = 'Open Break' # In[5525]: prediction_table_new.loc[prediction_table_new['Final_prediction']=='No-Pair','Final_prediction'] = 'Open Break' prediction_table_new.loc[prediction_table_new['Final_prediction']=='UMR_One_to_One','Final_prediction'] = 'UMR' prediction_table_new.loc[prediction_table_new['Final_prediction']=='UMT_One_to_One','Final_prediction'] = 'UMT' prediction_table_new.loc[prediction_table_new['Final_prediction']=='UMB_One_to_One','Final_prediction'] = 'UMB' # In[5526]: # In[5527]: prediction_table_new = prediction_table_new[~prediction_table_new['Actual_Status'].isnull()] prediction_table_new = prediction_table_new.reset_index() prediction_table_new = prediction_table_new.drop('index',1) # ## Final Actual vs Predicted Table - Process Initiation # In[5528]: meo = pd.read_csv(filepaths_MEO[i],usecols=new_cols) # In[5529]: meo = meo[['ViewData.BreakID','ViewData.Side1_UniqueIds','ViewData.Side0_UniqueIds','ViewData.Age','ViewData.Status']].drop_duplicates() # In[5530]: meo['key'] = meo['ViewData.Side0_UniqueIds'].astype(str) + meo['ViewData.Side1_UniqueIds'].astype(str) # In[5531]: aua_id_match5 = aua_id_match3.rename(columns ={'Actual_Status': 'ViewData.Status'}) # In[5532]: aua_sub = aua_id_match5[['ViewData.Side1_UniqueIds','ViewData.Side0_UniqueIds','ViewData.Age','ViewData.Status']].drop_duplicates() # In[5533]: aua_sub['key'] = aua_sub['ViewData.Side0_UniqueIds'].astype(str) + aua_sub['ViewData.Side1_UniqueIds'].astype(str) # In[5534]: prediction_table_new['ViewData.BreakID'] = prediction_table_new['SideB.ViewData.BreakID_B_side'] prediction_table_new['ViewData.BreakID'] = prediction_table_new['ViewData.BreakID'].astype(str) # In[5535]: meo['ViewData.BreakID'] = meo['ViewData.BreakID'].astype(str) # In[5536]: prediction_table_new1 = pd.merge(prediction_table_new, meo[['ViewData.BreakID','key']], on='ViewData.BreakID', how='left') # In[5537]: # In[5538]: # In[5539]: aua_sub1 = pd.merge(aua_sub, prediction_table_new1[['key','Final_prediction','probability_UMR','probability_No_pair','probability_UMT','probability_UMB','Final_predicted_break']], on='key', how='left') # In[5540]: # In[5541]: no_open = prediction_table_new1[prediction_table_new1['Final_prediction']!='Open Break'].reset_index() no_open = no_open.drop('index',1) no_open['key'] = no_open['ViewData.Side0_UniqueIds'].astype(str) + no_open['ViewData.Side1_UniqueIds'].astype(str) # In[5542]: #aua_sub1[aua_sub1['Final_prediction']=='UMR_One_to_One'] X_test['key'] = X_test['SideB.ViewData.Side0_UniqueIds'].astype(str) + X_test['SideA.ViewData.Side1_UniqueIds'].astype(str) # In[5543]: # In[5544]: aua_sub = pd.merge(aua_sub1, no_open[['key','Final_prediction']], on='key', how='left') # In[5545]: aua_sub11 = aua_sub1[aua_sub1['Final_prediction']=='Open Break'] aua_sub11 = aua_sub11.reset_index() aua_sub11 = aua_sub11.drop('index',1) # In[5546]: aua_sub11['probability_UMR'].fillna(0.00355,inplace=True) aua_sub11['probability_UMB'].fillna(0.003124,inplace=True) aua_sub11['probability_UMT'].fillna(0.00255,inplace=True) aua_sub11['probability_No_pair'].fillna(0.99034,inplace=True) # In[5547]: aua_sub22 = aua_sub1[aua_sub1['Final_prediction']!='Open Break'][['ViewData.Side1_UniqueIds', 'ViewData.Side0_UniqueIds', 'ViewData.Age','ViewData.Status', 'key']] aua_sub22 = aua_sub22.reset_index() aua_sub22 = aua_sub22.drop('index',1) aua_sub22 = pd.merge(aua_sub22, no_open[['key','Final_prediction','probability_UMR','probability_No_pair','probability_UMT','probability_UMB','Final_predicted_break']], on='key', how='left') aua_sub22 = aua_sub22.reset_index() aua_sub22 = aua_sub22.drop('index',1) # In[5548]: aua_sub33 = pd.concat([aua_sub11,aua_sub22], axis=0) aua_sub33 = aua_sub33.reset_index() aua_sub33 = aua_sub33.drop('index',1) # In[5549]: aua_sub33['ViewData.Side0_UniqueIds'] = aua_sub33['ViewData.Side0_UniqueIds'].astype(str) aua_sub33['ViewData.Side1_UniqueIds'] = aua_sub33['ViewData.Side1_UniqueIds'].astype(str) # In[5550]: aua_sub33['len_side0'] = aua_sub33.apply(lambda x: len(x['ViewData.Side0_UniqueIds'].split(',')), axis=1) aua_sub33['len_side1'] = aua_sub33.apply(lambda x: len(x['ViewData.Side1_UniqueIds'].split(',')), axis=1) # In[5551]: aua_sub33.loc[(aua_sub33['len_side0']>1) & (aua_sub33['len_side1']==1) & (aua_sub33['ViewData.Status']=='OB') ,'Type'] = 'One_side_aggregation' aua_sub33.loc[(aua_sub33['len_side0']>1) & (aua_sub33['len_side1']==1) & (aua_sub33['ViewData.Status']!='OB') ,'Type'] = 'One_to_Many' aua_sub33.loc[(aua_sub33['len_side0']==1) & (aua_sub33['len_side1']>1) & (aua_sub33['ViewData.Status']=='OB') ,'Type'] = 'One_side_aggregation' aua_sub33.loc[(aua_sub33['len_side0']==1) & (aua_sub33['len_side1']>1) & (aua_sub33['ViewData.Status']!='OB') ,'Type'] = 'One_to_Many' aua_sub33.loc[(aua_sub33['len_side0']>1) & (aua_sub33['len_side1']>1) & (aua_sub33['ViewData.Status']!='OB') ,'Type'] = 'Many_to_Many' aua_sub33.loc[(aua_sub33['len_side0']==1) & (aua_sub33['len_side1']==1) ,'Type'] = 'One_to_One/Open' # In[5552]: aua_sub44 = aua_sub33[(aua_sub33['ViewData.Status']=='UMB') & (aua_sub33['ViewData.Age']>1)] aua_sub44 = aua_sub44.reset_index() aua_sub44 = aua_sub44.drop('index',1) # In[5553]: aua_sub44['Final_prediction'].fillna('UMB-Carry-Forward',inplace= True) aua_sub44['probability_UMR'].fillna(0.0001,inplace= True) aua_sub44['probability_UMB'].fillna(0.9998,inplace= True) aua_sub44['probability_UMT'].fillna(0.0000,inplace= True) aua_sub44['probability_No_pair'].fillna(0.0000,inplace= True) # In[5554]: aua_sub55 = aua_sub33[~((aua_sub33['ViewData.Status']=='UMB') & (aua_sub33['ViewData.Age']>1))] aua_sub55 = aua_sub55.reset_index() aua_sub55 = aua_sub55.drop('index',1) # In[5555]: aua_sub66 = pd.concat([aua_sub55,aua_sub44], axis=0) aua_sub66 = aua_sub66.reset_index() aua_sub66 = aua_sub66.drop('index',1) # In[5556]: aua_sub66.loc[(aua_sub66['ViewData.Status']=='UMB') & (aua_sub66['ViewData.Age']>1),'ViewData.Status'] = 'UMB-Carry-Forward' aua_sub66.loc[(aua_sub66['ViewData.Status']=='OB'),'ViewData.Status'] = 'Open Break' # In[5557]: # In[ ]: # ## Read No-Pair Id File # In[5558]: #no_pair_id_data = pd.read_csv("//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/X_Test/no_pair_ids_125_2020-06-8.csv") # In[5559]: no_pair_ids = no_pair_ids_df['filter_key'].unique() # In[5560]: aua_sub66.loc[aua_sub66['ViewData.Side1_UniqueIds'].isin(no_pair_ids),'Final_prediction'] = aua_sub66.loc[aua_sub66['ViewData.Side1_UniqueIds'].isin(no_pair_ids),'ViewData.Status'] aua_sub66.loc[aua_sub66['ViewData.Side0_UniqueIds'].isin(no_pair_ids),'Final_prediction'] = aua_sub66.loc[aua_sub66['ViewData.Side0_UniqueIds'].isin(no_pair_ids),'ViewData.Status'] # In[5561]: # In[5672]: #aua_sub66 # In[5563]: pb_side_grp = X_test.groupby(['SideA.ViewData.Side1_UniqueIds'])['Predicted_action'].unique().reset_index() # In[5564]: # In[5565]: pb_side_grp_status = X_test.groupby(['SideA.ViewData.Side1_UniqueIds'])['SideA.ViewData.Status'].unique().reset_index() pb_side_grp_status['SideA.ViewData.Status'] = pb_side_grp_status['SideA.ViewData.Status'].apply(lambda x: str(x).replace("[","")) pb_side_grp_status['SideA.ViewData.Status'] = pb_side_grp_status['SideA.ViewData.Status'].apply(lambda x: str(x).replace("]","")) pb_side_grp['len'] = pb_side_grp.apply(lambda x: len(x['Predicted_action']), axis=1) pb_side_grp['No_pair_flag'] = pb_side_grp.apply(lambda x: 1 if x['len'] == 1 and "No-Pair" in x['Predicted_action'] else 0, axis=1) # In[5566]: pb_side_grp = pd.merge(pb_side_grp,pb_side_grp_status, on='SideA.ViewData.Side1_UniqueIds', how='left') # In[5567]: #pb_side_grp['SideA.ViewData.Status'].value_counts() # In[5568]: #pb_side_grp = pd.merge(pb_side_grp,pb_side_grp_status, on='SideA.ViewData.Side1_UniqueIds', how='left') pb_side_grp['Final_status'] = pb_side_grp.apply(lambda x: "Open Break" if x['SideA.ViewData.Status']=="'OB'" else("SDB" if x['SideA.ViewData.Status']=="'SDB'" else "NA"),axis=1) pb_side_grp = pb_side_grp.rename(columns = {'SideA.ViewData.Side1_UniqueIds':'ViewData.Side1_UniqueIds'}) pb_side_grp1 = pb_side_grp[pb_side_grp['No_pair_flag']==1] pb_side_grp1 = pb_side_grp1.reset_index() pb_side_grp1 = pb_side_grp1.drop('index',1) # In[5569]: aua_sub77 = pd.merge(aua_sub66 ,pb_side_grp1[['ViewData.Side1_UniqueIds','Final_status']], on ='ViewData.Side1_UniqueIds',how='left') # In[5570]: aua_sub77.loc[(~aua_sub77['Final_status'].isnull()) & (aua_sub77['ViewData.Side0_UniqueIds']=='nan'),'Final_prediction'] = aua_sub77.loc[(~aua_sub77['Final_status'].isnull()) & (aua_sub77['ViewData.Side0_UniqueIds']=='nan'),'Final_status'] # In[5571]: pb_side_grp_B = X_test.groupby(['SideB.ViewData.Side0_UniqueIds'])['Predicted_action'].unique().reset_index() # In[5572]: pb_side_grp_B_status = X_test.groupby(['SideB.ViewData.Side0_UniqueIds'])['SideB.ViewData.Status'].unique().reset_index() pb_side_grp_B_status['SideB.ViewData.Status'] = pb_side_grp_B_status['SideB.ViewData.Status'].apply(lambda x: str(x).replace("[","")) pb_side_grp_B_status['SideB.ViewData.Status'] = pb_side_grp_B_status['SideB.ViewData.Status'].apply(lambda x: str(x).replace("]","")) pb_side_grp_B['len'] = pb_side_grp_B.apply(lambda x: len(x['Predicted_action']), axis=1) pb_side_grp_B['No_pair_flag'] = pb_side_grp_B.apply(lambda x: 1 if x['len'] == 1 and "No-Pair" in x['Predicted_action'] else 0, axis=1) # In[5573]: pb_side_grp_B = pd.merge(pb_side_grp_B,pb_side_grp_B_status, on='SideB.ViewData.Side0_UniqueIds', how='left') pb_side_grp_B['Final_status_B'] = pb_side_grp_B.apply(lambda x: "Open Break" if x['SideB.ViewData.Status']=="'OB'" else("SDB" if x['SideB.ViewData.Status']=="'SDB'" else "NA"),axis=1) pb_side_grp_B = pb_side_grp_B.rename(columns = {'SideB.ViewData.Side0_UniqueIds':'ViewData.Side0_UniqueIds'}) pb_side_grp2 = pb_side_grp_B[pb_side_grp_B['No_pair_flag']==1] pb_side_grp2 = pb_side_grp2.reset_index() pb_side_grp2 = pb_side_grp2.drop('index',1) # In[5574]: aua_sub88 = pd.merge(aua_sub77 ,pb_side_grp2[['ViewData.Side0_UniqueIds','Final_status_B']], on ='ViewData.Side0_UniqueIds',how='left') # In[5575]: aua_sub88.loc[(~aua_sub88['Final_status_B'].isnull()) & (aua_sub88['ViewData.Side1_UniqueIds']=='nan'),'Final_prediction'] = aua_sub88.loc[(~aua_sub88['Final_status_B'].isnull()) & (aua_sub88['ViewData.Side1_UniqueIds']=='nan'),'Final_status_B'] # In[5576]: aua_sub99 = aua_sub88[(aua_sub88['ViewData.Status']!='SDB')] aua_sub99 = aua_sub99.reset_index() aua_sub99 = aua_sub99.drop('index',1) # In[5577]: aua_sub99['Final_prediction'] = aua_sub99['Final_prediction'].fillna('Open Break') aua_sub99 = aua_sub99.reset_index() aua_sub99 = aua_sub99.drop('index',1) # In[5578]: aua_sub99['ViewData.Status'] = aua_sub99['ViewData.Status'].astype(str) aua_sub99['Final_prediction'] = aua_sub99['Final_prediction'].astype(str) # In[5579]: #X_test # In[5580]: #aua[aua['ViewData.Side0_UniqueIds'] == '789_125897734_Advent Geneva'] # ## Summary file # In[5581]: break_id_merge = meo[meo['ViewData.Status'].isin(['OB','SDB','UOB','UDB','SPM'])][['ViewData.Side0_UniqueIds','ViewData.Side1_UniqueIds','ViewData.BreakID']].drop_duplicates() break_id_merge = break_id_merge.reset_index() break_id_merge = break_id_merge.drop('index',1) # In[5582]: # In[5583]: break_id_merge['key'] = break_id_merge['ViewData.Side0_UniqueIds'].astype(str) + break_id_merge['ViewData.Side1_UniqueIds'].astype(str) # In[5584]: final = pd.merge(aua_sub99,break_id_merge[['key','ViewData.BreakID']], on='key', how='left') # In[5585]: # In[5586]: # In[5587]: # In[5588]: #final[final['ViewData.BreakID'].isnull()] final = pd.merge(final,break_id_merge[['ViewData.Side0_UniqueIds','ViewData.BreakID']], on='ViewData.Side0_UniqueIds', how='left') # In[5589]: final.loc[final['ViewData.BreakID_x'].isnull(),'ViewData.BreakID_x'] = final.loc[final['ViewData.BreakID_x'].isnull(),'ViewData.BreakID_y'] # In[5590]: final = final.rename(columns={'ViewData.BreakID_x':'ViewData.BreakID'}) final = final.drop('ViewData.BreakID_y',1) # In[ ]: # In[5591]: final1 = final[(final['Type']=='One_to_One/Open') & (final['probability_No_pair'].isnull())] final1 = final1.reset_index() final1 = final1.drop('index',1) final2 = final[~((final['Type']=='One_to_One/Open') & (final['probability_No_pair'].isnull()))] final2 = final2.reset_index() final2 = final2.drop('index',1) # In[5592]: final1['probability_UMR'].fillna(0.0024,inplace=True) final1['probability_UMB'].fillna(0.004124,inplace=True) final1['probability_UMT'].fillna(0.00155,inplace=True) final1['probability_No_pair'].fillna(0.9922,inplace=True) # In[5593]: final3 = pd.concat([final1, final2], axis=0) # In[5594]: final3['ML_flag'] = final3.apply(lambda x: "ML" if x['Type']=='One_to_One/Open' else "Non-ML", axis=1) # In[5595]: prediction_cols = ['ViewData.BreakID', 'ViewData.Side1_UniqueIds', 'ViewData.Side0_UniqueIds','ViewData.Age' , 'probability_No_pair', 'probability_UMR','probability_UMB', 'probability_UMT', 'Final_predicted_break', 'Type', 'ML_flag','ViewData.Status', 'Final_prediction'] final4 = final3[prediction_cols] final4 = final4.rename(columns ={'ViewData.Status':'Actual_Status', 'Final_prediction': 'Predicted_Status'}) # In[5596]: # In[5597]: #crosstab_table # In[5598]: NA_status_file = final4[(final4['Type']=='One_to_One/Open') & (final4['Predicted_Status']=='NA')] NA_status_file = NA_status_file.reset_index() NA_status_file = NA_status_file.drop('index',1) # In[5599]: final5 = final4[~((final4['Type']=='One_to_One/Open') & (final4['Predicted_Status']=='NA'))] final5 = final5.reset_index() final5 = final5.drop('index',1) # In[5600]: NA_status_file_A_side = NA_status_file[NA_status_file['ViewData.Side0_UniqueIds']=='nan'] NA_status_file_B_side = NA_status_file[NA_status_file['ViewData.Side1_UniqueIds']=='nan'] # In[5601]: gg = X_test[X_test['SideA.ViewData.BreakID_A_side'].isin(NA_status_file_A_side['ViewData.BreakID'].unique())].groupby(['SideA.ViewData.BreakID_A_side'])['Predicted_action'].unique().reset_index() gg.columns = ['ViewData.BreakID','Predicted_action'] gg['NA_prediction_A'] = 'Open Break' kk = X_test[X_test['SideB.ViewData.BreakID_B_side'].isin(NA_status_file_B_side['ViewData.BreakID'].unique())].groupby(['SideB.ViewData.BreakID_B_side'])['Predicted_action'].unique().reset_index() kk.columns = ['ViewData.BreakID','Predicted_action'] kk['NA_prediction_B'] = 'Open Break' # In[5602]: gg['ViewData.BreakID'] = gg['ViewData.BreakID'].astype(str) kk['ViewData.BreakID'] = kk['ViewData.BreakID'].astype(str) # In[5603]: final6 = pd.merge(NA_status_file, gg[['ViewData.BreakID','NA_prediction_A']], on='ViewData.BreakID', how='left') final6 = pd.merge(final6, kk[['ViewData.BreakID','NA_prediction_B']], on='ViewData.BreakID', how='left') # In[5604]: final6.loc[final6['NA_prediction_A'].isnull(),'Predicted_Status'] = 'Open Break' final6.loc[final6['NA_prediction_B'].isnull(),'Predicted_Status'] = 'Open Break' # In[5605]: final6 = final6.drop(['NA_prediction_A','NA_prediction_B'],1) # In[5606]: final5[final5['ViewData.Side0_UniqueIds']=='789_125897734_Advent Geneva'] # In[5607]: final7 = pd.concat([final5, final6], axis=0) final7 = final7.reset_index() final7 = final7.drop('index',1) # In[5609]: # In[5610]: pair_match = X_test[X_test['Predicted_action']!='No-Pair'] pair_match = pair_match.reset_index() pair_match = pair_match.drop('index',1) # In[5611]: pair_match = pair_match[['Predicted_action', 'probability_No_pair', 'probability_UMB', 'probability_UMR', 'probability_UMT', 'key']] pair_match.columns = ['New_Predicted_action', 'New_probability_No_pair', 'New_probability_UMB', 'New_probability_UMR', 'New_probability_UMT','key'] # In[5612]: pair_match['New_Predicted_action'] = pair_match['New_Predicted_action'].apply(lambda x: 'UMR' if x=='UMR_One_to_One' else("UMT" if x=='UMT_One_to_One' else("UMB" if x== "UMB_One_to_One" else x))) # In[5613]: final7['key'] = final7['ViewData.Side0_UniqueIds'].astype(str) + final7['ViewData.Side1_UniqueIds'].astype(str) # In[5614]: final8 = pd.merge(final7,pair_match, on='key', how='left') # In[5615]: # In[5617]: # In[5618]: final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'Predicted_Status'] = final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'New_Predicted_action'] final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'probability_No_pair'] = final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'New_probability_No_pair'] final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'probability_UMB'] = final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'New_probability_UMB'] final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'probability_UMR'] = final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'New_probability_UMR'] final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'probability_UMT'] = final8.loc[(~final8['New_Predicted_action'].isnull()) & (final8['New_Predicted_action']!= final8['Predicted_Status']),'New_probability_UMT'] # In[5619]: final8.loc[(final8['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMT'),'probability_UMT'] = final8.loc[(final8['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMT'),'New_probability_UMT'] final8.loc[(final8['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMR'),'probability_UMR'] = final8.loc[(final8['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMR'),'New_probability_UMR'] final8.loc[(final8['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMB'),'probability_UMB'] = final8.loc[(final8['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMB'),'New_probability_UMB'] final8.loc[(final8['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMT'),'probability_No_pair'] = 0.002 final8.loc[(final8['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMR'),'probability_No_pair'] = 0.002 final8.loc[(final8['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMB'),'probability_No_pair'] = 0.002 # In[5620]: umr_break_array_match = prediction_table[prediction_table['Final_prediction']=='UMR_One_to_One'][['SideB.ViewData.BreakID_B_side','Final_predicted_break']] umt_break_array_match = prediction_table[prediction_table['Final_prediction']=='UMT_One_to_One'][['SideB.ViewData.BreakID_B_side','Final_predicted_break']] umb_break_array_match = prediction_table[prediction_table['Final_prediction']=='UMB_One_to_One'][['SideB.ViewData.BreakID_B_side','Final_predicted_break']] umr_break_array_match.columns = np.array(['ViewData.BreakID','New_Final_predicted_break_UMR']) umt_break_array_match.columns = np.array(['ViewData.BreakID','New_Final_predicted_break_UMT']) umb_break_array_match.columns = np.array(['ViewData.BreakID','New_Final_predicted_break_UMB']) # In[5621]: #umr_break_array_match['New_Final_predicted_break_UMR'] = umr_break_array_match['New_Final_predicted_break_UMR'].astype(str) #umb_break_array_match['New_Final_predicted_break_UMB'] = umb_break_array_match['New_Final_predicted_break_UMB'].astype(str) #umt_break_array_match['New_Final_predicted_break_UMT'] = umt_break_array_match['New_Final_predicted_break_UMT'].astype(str) # In[5622]: final9 = pd.merge(final8, umr_break_array_match, on ='ViewData.BreakID', how='left') final9 = pd.merge(final9, umt_break_array_match, on ='ViewData.BreakID', how='left') final9 = pd.merge(final9, umb_break_array_match, on ='ViewData.BreakID', how='left') # In[5623]: final9.loc[(final9['Final_predicted_break'].isnull()) & (final9['Predicted_Status']=='UMT'),'Final_predicted_break'] = final9.loc[(final9['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMT'),'New_Final_predicted_break_UMT'] final9.loc[(final9['Final_predicted_break'].isnull()) & (final9['Predicted_Status']=='UMR'),'Final_predicted_break'] = final9.loc[(final9['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMR'),'New_Final_predicted_break_UMR'] final9.loc[(final9['Final_predicted_break'].isnull()) & (final9['Predicted_Status']=='UMB'),'Final_predicted_break'] = final9.loc[(final9['Final_predicted_break'].isnull()) & (final8['Predicted_Status']=='UMB'),'New_Final_predicted_break_UMB'] # In[5624]: #final9[(final9['Actual_Status']=='UMB') & (final9['Predicted_Status']=='UMB') & (final9['ML_flag']=='ML')]['Final_predicted_break'] # In[5625]: # In[5626]: final9 = final9.drop(['key','New_Predicted_action', 'New_probability_No_pair', 'New_probability_UMB', 'New_probability_UMR', 'New_probability_UMT','New_Final_predicted_break_UMR', 'New_Final_predicted_break_UMT', 'New_Final_predicted_break_UMB'], 1) # In[5627]: # In[5628]: #final8['Type'].value_counts() # In[5629]: #meo1 = pd.read_csv("//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/MEO/MeoCollections.MEO_HST_RecData_125_2020-06-8.csv",usecols=new_cols) # In[5630]: #meo1[meo1['ViewData.Side1_UniqueIds']=='6_125858636_Goldman Sachs'] # ## Merging columns from the transaction table # In[5631]: # In[5632]: aua_final = pd.read_csv(filepaths_MEO[i],usecols = viewdata_cols_to_show) # In[5633]: #final_predictions = pd.read_csv('//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/Final_Predictions/Final_Predictions_Table_HST_RecData_125_2020-06-1.csv') # In[5634]: final_predictions = final9.copy() # In[5635]: #final_predictions.groupby(['Actual_Status'])['Predicted_Status'].value_counts() # In[5636]: #final_predictions[(final_predictions['Actual_Status'] == 'Open Break') & (final_predictions['Predicted_Status'] == 'UMR')][['ViewData.Side0_UniqueIds','ViewData.Side1_UniqueIds']] # In[5637]: #final_predictions.groupby(['ViewData.Side0_UniqueIds'])['ViewData.Side1_UniqueIds'].value_counts() # In[5638]: # In[5639]: final_predictions_both_present = final_predictions[(final_predictions['ViewData.Side0_UniqueIds'] !='nan') & (final_predictions['ViewData.Side1_UniqueIds']!='nan')] final_predictions_side0_only = final_predictions[(final_predictions['ViewData.Side0_UniqueIds']!='nan') & (final_predictions['ViewData.Side1_UniqueIds'] =='nan')] final_predictions_side1_only = final_predictions[(final_predictions['ViewData.Side0_UniqueIds']=='nan') & (final_predictions['ViewData.Side1_UniqueIds'] != 'nan')] final_predictions_both_null = final_predictions[(final_predictions['ViewData.Side0_UniqueIds']=='nan') & (final_predictions['ViewData.Side1_UniqueIds']=='nan')] # In[5640]: aua_final = aua_final.drop_duplicates() aua_final = aua_final.reset_index() aua_final = aua_final.drop('index',1) # In[5642]: final_predictions_both_present_aua_merge = pd.merge(final_predictions_both_present,aua_final, on=['ViewData.Side0_UniqueIds','ViewData.Side1_UniqueIds'], how='left' ) final_predictions_side0_only_aua_merge = pd.merge(final_predictions_side0_only,aua_final, on='ViewData.Side0_UniqueIds', how='left' ) final_predictions_side1_only_aua_merge = pd.merge(final_predictions_side1_only,aua_final, on='ViewData.Side1_UniqueIds', how='left' ) # In[5643]: #final_predictions_side1_only_aua_merge # In[5644]: final_predictions_side0_only_aua_merge = final_predictions_side0_only_aua_merge.drop(['ViewData.BreakID_y', 'ViewData.Side1_UniqueIds_y', 'ViewData.Age_y'], 1) final_predictions_side0_only_aua_merge = final_predictions_side0_only_aua_merge.rename(columns={'ViewData.BreakID_x': 'ViewData.BreakID'}) final_predictions_side0_only_aua_merge = final_predictions_side0_only_aua_merge.rename(columns={'ViewData.Side1_UniqueIds_x': 'ViewData.Side1_UniqueIds'}) final_predictions_side0_only_aua_merge = final_predictions_side0_only_aua_merge.rename(columns={'ViewData.Age_x': 'ViewData.Age'}) final_predictions_side1_only_aua_merge = final_predictions_side1_only_aua_merge.drop(['ViewData.BreakID_y', 'ViewData.Side0_UniqueIds_y', 'ViewData.Age_y'], 1) final_predictions_side1_only_aua_merge = final_predictions_side1_only_aua_merge.rename(columns={'ViewData.BreakID_x': 'ViewData.BreakID'}) final_predictions_side1_only_aua_merge = final_predictions_side1_only_aua_merge.rename(columns={'ViewData.Side0_UniqueIds_x': 'ViewData.Side0_UniqueIds'}) final_predictions_side1_only_aua_merge = final_predictions_side1_only_aua_merge.rename(columns={'ViewData.Age_x': 'ViewData.Age'}) final_predictions_both_present_aua_merge = final_predictions_both_present_aua_merge.drop(['ViewData.BreakID_y', 'ViewData.Age_y'], 1) final_predictions_both_present_aua_merge = final_predictions_both_present_aua_merge.rename(columns={'ViewData.BreakID_x': 'ViewData.BreakID'}) final_predictions_both_present_aua_merge = final_predictions_both_present_aua_merge.rename(columns={'ViewData.Age_x': 'ViewData.Age'}) # In[5645]: #final_prediction_show_cols = final_predictions_both_present_aua_merge.append([final_predictions_side0_only_aua_merge,final_predictions_side1_only_aua_merge]) # In[5655]: final11 = pd.concat([final_predictions_both_present_aua_merge, final_predictions_side0_only_aua_merge,final_predictions_side1_only_aua_merge], axis=0) # In[5656]: final11 = final11.reset_index() final11 = final11.drop('index',1) # In[5657]: final12 = final11.drop_duplicates(['ViewData.BreakID', 'ViewData.Side1_UniqueIds','ViewData.Side0_UniqueIds', 'ViewData.Age']) # In[5658]: final12.loc[(final12['Actual_Status']=='UCB'), 'ML_flag'] ='Non-ML' final12.loc[(final12['Actual_Status']=='UCB'), 'Type'] = 'Closed Breaks' # In[5673]: final12.loc[final12['Actual_Status']=='UCB','Predicted_Status'] = 'No-Prediction' # In[5246]: # In[5674]: print('classification_report') print(classification_report(final12[final12['Type']=='One_to_One/Open']['Actual_Status'], final12[final12['Type']=='One_to_One/Open']['Predicted_Status'])) # In[5675]: report = classification_report(final12[final12['Type']=='One_to_One/Open']['Actual_Status'], final12[final12['Type']=='One_to_One/Open']['Predicted_Status'], output_dict=True) accuracy_table = pd.DataFrame(report).transpose() print('accuracy_table') print(accuracy_table) # In[5676]: crosstab_table = pd.crosstab(final12[final12['Type']=='One_to_One/Open']['Actual_Status'], final12[final12['Type']=='One_to_One/Open']['Predicted_Status']) # In[5678]: print('crosstab_table') print(crosstab_table) print(datetime.now()) # ## Save results # In[ ]: # filepaths_final_prediction_table = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/Final_Predictions_2/Final_Predictions_Table_HST_RecData_125_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] # filepaths_accuracy_table = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/Final_Predictions_2/Accuracy_Table_HST_RecData_125_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] # filepaths_crosstab_table = ['//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/Final_Predictions_2/Crosstab_Table_HST_RecData_125_2020-06-' + str(date_numbers_list[i]) + '.csv' for i in range(0,len(date_numbers_list))] final12.to_csv(filepaths_final_prediction_table[i]) # In[ ]: accuracy_table.to_csv(filepaths_accuracy_table[i]) # In[ ]: crosstab_table.to_csv(filepaths_crosstab_table[i]) i = i+1 sys.stdout = orig_stdout f.close() # ## Enitre month prediction # In[4747]: #all_june_data = pd.read_csv('//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/Final_Predictions/All_June_predictions_123.csv') # # ## In[4694]: # # #from sklearn.metrics import accuracy_score #from sklearn.metrics import classification_report #print(classification_report(all_june_data[all_june_data['Type']=='One_to_One/Open']['Actual_Status'], all_june_data[all_june_data['Type']=='One_to_One/Open']['Predicted_Status'])) # # ## In[4748]: # # #from sklearn.metrics import accuracy_score #from sklearn.metrics import classification_report #print(classification_report(all_june_data[all_june_data['Type']=='One_to_One/Open']['Actual_Status'], all_june_data[all_june_data['Type']=='One_to_One/Open']['Predicted_Status'])) # # ## In[4695]: # # #report_all_june = classification_report(all_june_data[all_june_data['Type']=='One_to_One/Open']['Actual_Status'], all_june_data[all_june_data['Type']=='One_to_One/Open']['Predicted_Status'], output_dict=True) #accuracy_table_all_june = pd.DataFrame(report_all_june).transpose() # # ## In[4696]: # # #accuracy_table_all_june # # ## In[4697]: # # #from sklearn.metrics import confusion_matrix #crosstab_all_june = pd.crosstab(all_june_data[all_june_data['Type']=='One_to_One/Open']['Actual_Status'], all_june_data[all_june_data['Type']=='One_to_One/Open']['Predicted_Status']) # # ## In[4698]: # # #crosstab_all_june # # ## ## Save Results (Entire Month) # ## In[4702]: # # #accuracy_table_all_june.to_csv('//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/Final_Predictions/Accuracy_table_all_june.csv') # # ## In[4703]: # # #crosstab_all_june.to_csv('//vitblrdevcons01/Raman Strategy ML 2.0/All_Data/Weiss/JuneData/Final_Predictions/Crosstab_table_all_june.csv') #

[ "rohitschauhanitbhu@gmail.com" ]

rohitschauhanitbhu@gmail.com

0750081985acee30b91acb274a9231071fbedfeb

d531f502304f4f314a2e5d2e28a98d184b143e42

/elastic/documents.py

498ceec138557a0e21834f5db9bfdec2efd61514

[]

no_license

mikohan/djangoblogtest

6a0d4704fb51a8ca935ea329cb007b7e48fecb54

3af986cd8be3d83ad5b01d2583464e243309dd50

refs/heads/master

2020-06-13T15:39:13.686997

2019-07-02T05:25:06

194,696,685

0

null

UTF-8

Python

false

287

py

from django_elasticsearch_dsl import DocType, Index from elastic.models import Post post = Index('posts') @post.doc_type class PostDocument(DocType): class Meta: model = Post fields = [ 'title', 'content', 'timestamp' ]

[ "angara99@gmail.com" ]

angara99@gmail.com

ee3feed5831ec7b466639f24086daaf2f5a0b2b2

c1d4b1ab3d8949a34cdcfa7246a34fc102b5c8d1

/test10_4895_dev_16191/settings.py

33cb45d0fda1393aabf64214773df2aea414397f

[]

no_license

crowdbotics-apps/test10-4895-dev-16191

3b19a305c17f93e398e4a7a4e59bf5defa76d3e7

e796b9cd9bd64e91d436a6dade728e5b426cee04

refs/heads/master

2023-01-21T09:30:23.530979

2020-12-03T10:06:29

318,150,338

0

null

UTF-8

Python

false

6,781

py

""" Django settings for test10_4895_dev_16191 project. Generated by 'django-admin startproject' using Django 2.2.2. For more information on this file, see https://docs.djangoproject.com/en/2.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.2/ref/settings/ """ import os import environ import logging env = environ.Env() # SECURITY WARNING: don't run with debug turned on in production! DEBUG = env.bool("DEBUG", default=False) # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = env.str("SECRET_KEY") ALLOWED_HOSTS = env.list("HOST", default=["*"]) SITE_ID = 1 SECURE_PROXY_SSL_HEADER = ("HTTP_X_FORWARDED_PROTO", "https") SECURE_SSL_REDIRECT = env.bool("SECURE_REDIRECT", default=False) # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'django.contrib.sites' ] LOCAL_APPS = [ 'home', 'users.apps.UsersConfig', ] THIRD_PARTY_APPS = [ 'rest_framework', 'rest_framework.authtoken', 'rest_auth', 'rest_auth.registration', 'bootstrap4', 'allauth', 'allauth.account', 'allauth.socialaccount', 'allauth.socialaccount.providers.google', 'django_extensions', 'drf_yasg', 'storages', ] INSTALLED_APPS += LOCAL_APPS + THIRD_PARTY_APPS MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'test10_4895_dev_16191.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'test10_4895_dev_16191.wsgi.application' # Database # https://docs.djangoproject.com/en/2.2/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } if env.str("DATABASE_URL", default=None): DATABASES = { 'default': env.db() } # Password validation # https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = '/static/' MIDDLEWARE += ['whitenoise.middleware.WhiteNoiseMiddleware'] AUTHENTICATION_BACKENDS = ( 'django.contrib.auth.backends.ModelBackend', 'allauth.account.auth_backends.AuthenticationBackend' ) STATIC_ROOT = os.path.join(BASE_DIR, "staticfiles") STATICFILES_DIRS = [os.path.join(BASE_DIR, 'static')] STATICFILES_STORAGE = 'whitenoise.storage.CompressedManifestStaticFilesStorage' # allauth / users ACCOUNT_EMAIL_REQUIRED = True ACCOUNT_AUTHENTICATION_METHOD = 'email' ACCOUNT_USERNAME_REQUIRED = False ACCOUNT_EMAIL_VERIFICATION = "optional" ACCOUNT_CONFIRM_EMAIL_ON_GET = True ACCOUNT_LOGIN_ON_EMAIL_CONFIRMATION = True ACCOUNT_UNIQUE_EMAIL = True LOGIN_REDIRECT_URL = "users:redirect" ACCOUNT_ADAPTER = "users.adapters.AccountAdapter" SOCIALACCOUNT_ADAPTER = "users.adapters.SocialAccountAdapter" ACCOUNT_ALLOW_REGISTRATION = env.bool("ACCOUNT_ALLOW_REGISTRATION", True) SOCIALACCOUNT_ALLOW_REGISTRATION = env.bool("SOCIALACCOUNT_ALLOW_REGISTRATION", True) REST_AUTH_SERIALIZERS = { # Replace password reset serializer to fix 500 error "PASSWORD_RESET_SERIALIZER": "home.api.v1.serializers.PasswordSerializer", } REST_AUTH_REGISTER_SERIALIZERS = { # Use custom serializer that has no username and matches web signup "REGISTER_SERIALIZER": "home.api.v1.serializers.SignupSerializer", } # Custom user model AUTH_USER_MODEL = "users.User" EMAIL_HOST = env.str("EMAIL_HOST", "smtp.sendgrid.net") EMAIL_HOST_USER = env.str("SENDGRID_USERNAME", "") EMAIL_HOST_PASSWORD = env.str("SENDGRID_PASSWORD", "") EMAIL_PORT = 587 EMAIL_USE_TLS = True # AWS S3 config AWS_ACCESS_KEY_ID = env.str("AWS_ACCESS_KEY_ID", "") AWS_SECRET_ACCESS_KEY = env.str("AWS_SECRET_ACCESS_KEY", "") AWS_STORAGE_BUCKET_NAME = env.str("AWS_STORAGE_BUCKET_NAME", "") AWS_STORAGE_REGION = env.str("AWS_STORAGE_REGION", "") USE_S3 = ( AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY and AWS_STORAGE_BUCKET_NAME and AWS_STORAGE_REGION ) if USE_S3: AWS_S3_CUSTOM_DOMAIN = env.str("AWS_S3_CUSTOM_DOMAIN", "") AWS_S3_OBJECT_PARAMETERS = {"CacheControl": "max-age=86400"} AWS_DEFAULT_ACL = env.str("AWS_DEFAULT_ACL", "public-read") AWS_MEDIA_LOCATION = env.str("AWS_MEDIA_LOCATION", "media") AWS_AUTO_CREATE_BUCKET = env.bool("AWS_AUTO_CREATE_BUCKET", True) DEFAULT_FILE_STORAGE = env.str( "DEFAULT_FILE_STORAGE", "home.storage_backends.MediaStorage" ) MEDIA_URL = '/mediafiles/' MEDIA_ROOT = os.path.join(BASE_DIR, 'mediafiles') # Swagger settings for api docs SWAGGER_SETTINGS = { "DEFAULT_INFO": f"{ROOT_URLCONF}.api_info", } if DEBUG or not (EMAIL_HOST_USER and EMAIL_HOST_PASSWORD): # output email to console instead of sending if not DEBUG: logging.warning("You should setup `SENDGRID_USERNAME` and `SENDGRID_PASSWORD` env vars to send emails.") EMAIL_BACKEND = "django.core.mail.backends.console.EmailBackend"

[ "team@crowdbotics.com" ]

team@crowdbotics.com

07124bad1968e93498c2ffb7a7ec6a09847a9663

ba3d65019a8dc88a4da9b14b68e100cb204b8f55

/flask/repository/__init__.py

3d7e8db47ac89b642dd3b39806e0fd6d61cc19c6

[ "MIT" ]

permissive

geovote/geovote-main

b8cb37abd6e9cdeece18f38e05481c5fcda4076f

b848fba73c51c112cdc235f6d5240f5e8706332f

refs/heads/master

2020-04-13T23:35:09.538333

2019-02-08T14:32:00

163,510,538

0

null

UTF-8

Python

false

99

py

from repository.answers import * from repository.clean import * from repository.questions import *

[ "lawanledoux@gmail.com" ]

lawanledoux@gmail.com

d4f91e5b1100d8cab2d28287ffbeeb2921329d47

70e51fff2290cef405063d1a95ebd230ba0e05b1

/backend/tiny_fog_27865/settings.py

694713fb1f4315f07f1442ed44d027d3c12917f2

[]

no_license

crowdbotics-apps/tiny-fog-27865

ce252260efaeddbb67e4318648eda6201d2a2094

12ebe268be73391399415df8aa95c72fa36a5900

refs/heads/master

2023-05-17T15:14:18.187594

2021-06-09T04:40:08

375,227,417

0

null

UTF-8

Python

false

7,108

py

""" Django settings for tiny_fog_27865 project. Generated by 'django-admin startproject' using Django 2.2.2. For more information on this file, see https://docs.djangoproject.com/en/2.2/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/2.2/ref/settings/ """ import os import environ import logging env = environ.Env() # SECURITY WARNING: don't run with debug turned on in production! DEBUG = env.bool("DEBUG", default=False) # Build paths inside the project like this: os.path.join(BASE_DIR, ...) BASE_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__))) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/2.2/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = env.str("SECRET_KEY") ALLOWED_HOSTS = env.list("HOST", default=["*"]) SITE_ID = 1 SECURE_PROXY_SSL_HEADER = ("HTTP_X_FORWARDED_PROTO", "https") SECURE_SSL_REDIRECT = env.bool("SECURE_REDIRECT", default=False) # Application definition INSTALLED_APPS = [ 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'django.contrib.sites' ] LOCAL_APPS = [ 'home', 'modules', 'users.apps.UsersConfig', ] THIRD_PARTY_APPS = [ 'rest_framework', 'rest_framework.authtoken', 'rest_auth', 'rest_auth.registration', 'bootstrap4', 'allauth', 'allauth.account', 'allauth.socialaccount', 'allauth.socialaccount.providers.google', 'django_extensions', 'drf_yasg', 'storages', # start fcm_django push notifications 'fcm_django', # end fcm_django push notifications ] INSTALLED_APPS += LOCAL_APPS + THIRD_PARTY_APPS MIDDLEWARE = [ 'django.middleware.security.SecurityMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ] ROOT_URLCONF = 'tiny_fog_27865.urls' TEMPLATES = [ { 'BACKEND': 'django.template.backends.django.DjangoTemplates', 'DIRS': [os.path.join(BASE_DIR, 'web_build')], 'APP_DIRS': True, 'OPTIONS': { 'context_processors': [ 'django.template.context_processors.debug', 'django.template.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.contrib.messages.context_processors.messages', ], }, }, ] WSGI_APPLICATION = 'tiny_fog_27865.wsgi.application' # Database # https://docs.djangoproject.com/en/2.2/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } if env.str("DATABASE_URL", default=None): DATABASES = { 'default': env.db() } # Password validation # https://docs.djangoproject.com/en/2.2/ref/settings/#auth-password-validators AUTH_PASSWORD_VALIDATORS = [ { 'NAME': 'django.contrib.auth.password_validation.UserAttributeSimilarityValidator', }, { 'NAME': 'django.contrib.auth.password_validation.MinimumLengthValidator', }, { 'NAME': 'django.contrib.auth.password_validation.CommonPasswordValidator', }, { 'NAME': 'django.contrib.auth.password_validation.NumericPasswordValidator', }, ] # Internationalization # https://docs.djangoproject.com/en/2.2/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/2.2/howto/static-files/ STATIC_URL = '/static/' MIDDLEWARE += ['whitenoise.middleware.WhiteNoiseMiddleware'] AUTHENTICATION_BACKENDS = ( 'django.contrib.auth.backends.ModelBackend', 'allauth.account.auth_backends.AuthenticationBackend' ) STATIC_ROOT = os.path.join(BASE_DIR, "staticfiles") STATICFILES_DIRS = [os.path.join(BASE_DIR, 'static'), os.path.join(BASE_DIR, 'web_build/static')] STATICFILES_STORAGE = 'whitenoise.storage.CompressedManifestStaticFilesStorage' # allauth / users ACCOUNT_EMAIL_REQUIRED = True ACCOUNT_AUTHENTICATION_METHOD = 'email' ACCOUNT_USERNAME_REQUIRED = False ACCOUNT_EMAIL_VERIFICATION = "optional" ACCOUNT_CONFIRM_EMAIL_ON_GET = True ACCOUNT_LOGIN_ON_EMAIL_CONFIRMATION = True ACCOUNT_UNIQUE_EMAIL = True LOGIN_REDIRECT_URL = "users:redirect" ACCOUNT_ADAPTER = "users.adapters.AccountAdapter" SOCIALACCOUNT_ADAPTER = "users.adapters.SocialAccountAdapter" ACCOUNT_ALLOW_REGISTRATION = env.bool("ACCOUNT_ALLOW_REGISTRATION", True) SOCIALACCOUNT_ALLOW_REGISTRATION = env.bool("SOCIALACCOUNT_ALLOW_REGISTRATION", True) REST_AUTH_SERIALIZERS = { # Replace password reset serializer to fix 500 error "PASSWORD_RESET_SERIALIZER": "home.api.v1.serializers.PasswordSerializer", } REST_AUTH_REGISTER_SERIALIZERS = { # Use custom serializer that has no username and matches web signup "REGISTER_SERIALIZER": "home.api.v1.serializers.SignupSerializer", } # Custom user model AUTH_USER_MODEL = "users.User" EMAIL_HOST = env.str("EMAIL_HOST", "smtp.sendgrid.net") EMAIL_HOST_USER = env.str("SENDGRID_USERNAME", "") EMAIL_HOST_PASSWORD = env.str("SENDGRID_PASSWORD", "") EMAIL_PORT = 587 EMAIL_USE_TLS = True # AWS S3 config AWS_ACCESS_KEY_ID = env.str("AWS_ACCESS_KEY_ID", "") AWS_SECRET_ACCESS_KEY = env.str("AWS_SECRET_ACCESS_KEY", "") AWS_STORAGE_BUCKET_NAME = env.str("AWS_STORAGE_BUCKET_NAME", "") AWS_STORAGE_REGION = env.str("AWS_STORAGE_REGION", "") USE_S3 = ( AWS_ACCESS_KEY_ID and AWS_SECRET_ACCESS_KEY and AWS_STORAGE_BUCKET_NAME and AWS_STORAGE_REGION ) if USE_S3: AWS_S3_CUSTOM_DOMAIN = env.str("AWS_S3_CUSTOM_DOMAIN", "") AWS_S3_OBJECT_PARAMETERS = {"CacheControl": "max-age=86400"} AWS_DEFAULT_ACL = env.str("AWS_DEFAULT_ACL", "public-read") AWS_MEDIA_LOCATION = env.str("AWS_MEDIA_LOCATION", "media") AWS_AUTO_CREATE_BUCKET = env.bool("AWS_AUTO_CREATE_BUCKET", True) DEFAULT_FILE_STORAGE = env.str( "DEFAULT_FILE_STORAGE", "home.storage_backends.MediaStorage" ) MEDIA_URL = '/mediafiles/' MEDIA_ROOT = os.path.join(BASE_DIR, 'mediafiles') # start fcm_django push notifications FCM_DJANGO_SETTINGS = { "FCM_SERVER_KEY": env.str("FCM_SERVER_KEY", "") } # end fcm_django push notifications # Swagger settings for api docs SWAGGER_SETTINGS = { "DEFAULT_INFO": f"{ROOT_URLCONF}.api_info", } if DEBUG or not (EMAIL_HOST_USER and EMAIL_HOST_PASSWORD): # output email to console instead of sending if not DEBUG: logging.warning("You should setup `SENDGRID_USERNAME` and `SENDGRID_PASSWORD` env vars to send emails.") EMAIL_BACKEND = "django.core.mail.backends.console.EmailBackend"

[ "team@crowdbotics.com" ]

team@crowdbotics.com

09fc57573c94392a2bbb62397eb7ec5dc72fcdd3

04f83aab47940b739f13c1ba102c230372966c43

/EDSHyFT/test/run_8TeV_all_crab.py

5b675b953da5f3e41661d8a07451d4b8827c0046

[]

no_license

PerilousApricot/SUSHyFT-Analyzer

5a11909963d30c8ad7f19f499253a6753e78608a

9f5ba528a96203459c52a0434b32311a16e2ff3b

refs/heads/master

2016-09-15T15:31:30.617286

2016-03-14T20:32:09

2016-03-14T21:02:28

21,915,887

0

null

UTF-8

Python

false

49,829

py

import subprocess, os, ConfigParser dummy_config_name = 'crab_dummy_anashyft_ele.cfg' dummy_config = ConfigParser.RawConfigParser() dummy_config.read(dummy_config_name) pset = 'edmNtupleMaker.py' working_dir = os.environ['HOME'] + '/nobackup/BPrimeEDM_8TeV/Jan15/' dir_suffix = '_tlbsm_53x_v2' # one pset for all jobs dummy_config.set('CMSSW','pset',pset) joblist = [ # ========== MC ========== ## {'datasetpath':'/BprimeBprimeToBZTWinc_M-450_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBZTWinc_M-450_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_450', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToBZTWinc_M-500_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBZTWinc_M-500_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_500', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBZTWinc_M-500_TuneZ2star_8TeV-madgraph'}, ## {'datasetpath':'/BprimeBprimeToBZTWinc_M-550_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBZTWinc_M-550_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_550', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBZTWinc_M-550_TuneZ2star_8TeV-madgraph'}, ## {'datasetpath':'/BprimeBprimeToBZTWinc_M-600_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZTWinc_M-600_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2_A-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_600', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToBZTWinc_M-650_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZTWinc_M-650_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_650', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToBZTWinc_M-700_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZTWinc_M-700_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2_A-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_700', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToBZTWinc_M-750_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZTWinc_M-750_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_750', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToBZTWinc_M-800_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZTWinc_M-800_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_800', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, # {'datasetpath':'/BprimeBprimeToBZTWinc_M-900_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBZTWinc_M-900_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7C-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_900', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBZTWinc_M-900_TuneZ2star_8TeV-madgraph'}, # {'datasetpath':'/BprimeBprimeToBZTWinc_M-1000_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBZTWinc_M-1000_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7C-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_1000', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBZTWinc_M-1000_TuneZ2star_8TeV-madgraph'}, # {'datasetpath':'/BprimeBprimeToBZTWinc_M-1100_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBZTWinc_M-1100_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7C-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZTW_1100', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', ''btag_map':'BprimeBprimeToBZTWinc_M-1100_TuneZ2star_8TeV-madgraph'}, ## {'datasetpath':'/BprimeBprimeToTWTWinc_M-450_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToTWTWinc_M-450_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToTWTW_450', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, # {'datasetpath':'/BprimeBprimeToTWTWinc_M-500_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToTWTWinc_M-500_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToTWTW_500', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToTWTWinc_M-550_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToTWTWinc_M-550_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToTWTW_550', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToTWTWinc_M-600_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToTWTWinc_M-600_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToTWTW_600', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToTWTWinc_M-600_TuneZ2star_8TeV-madgraph'}, ## {'datasetpath':'/BprimeBprimeToTWTWinc_M-650_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToTWTWinc_M-650_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2_B-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToTWTW_650', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToTWTWinc_M-700_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToTWTWinc_M-700_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2_B-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToTWTW_700', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToTWTWinc_M-750_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToTWTWinc_M-750_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToTWTW_750', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/BprimeBprimeToTWTWinc_M-800_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToTWTWinc_M-800_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToTWTW_800', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath': '/BprimeBprimeToBHBHinc_M-450_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBHinc_M-450_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBH_450', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBHinc_M-500_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBHinc_M-500_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBH_500', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBHinc_M-550_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBHinc_M-550_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBH_550', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBHinc_M-600_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBHinc_M-600_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBH_600', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBHinc_M-650_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBHinc_M-650_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBH_650', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBHinc_M-700_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBHinc_M-700_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBH_700', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBHinc_M-750_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBHinc_M-750_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBH_750', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBHinc_M-800_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBHinc_M-800_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBH_800', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, # {'datasetpath': '/BprimeBprimeToBHBZinc_M-450_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBZinc_M-450_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBZ_450', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBHBZinc_M-450_TuneZ2star_8TeV-madgraph' }, ## {'datasetpath': '/BprimeBprimeToBHBZinc_M-500_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBZinc_M-500_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBZ_500', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBZinc_M-550_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBZinc_M-550_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBZ_550', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBZinc_M-600_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBZinc_M-600_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBZ_600', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBZinc_M-650_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBZinc_M-650_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBZ_650', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBZinc_M-700_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBZinc_M-700_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBZ_700', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBZinc_M-750_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBZinc_M-750_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBZ_750', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHBZinc_M-800_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHBZinc_M-800_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHBZ_800', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHTWinc_M-450_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBHTWinc_M-450_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHTW_450', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBHTWinc_M-450_TuneZ2star_8TeV-madgraph' }, ## {'datasetpath': '/BprimeBprimeToBHTWinc_M-500_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBHTWinc_M-500_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHTW_500', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBHTWinc_M-500_TuneZ2star_8TeV-madgraph' }, ## {'datasetpath': '/BprimeBprimeToBHTWinc_M-550_TuneZ2star_8TeV-madgraph/cjenkins-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHTW_550', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBHTWinc_M-550_TuneZ2star_8TeV-madgraph' }, ## {'datasetpath': '/BprimeBprimeToBHTWinc_M-600_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHTWinc_M-600_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHTW_600', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHTWinc_M-650_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHTWinc_M-650_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHTW_650', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHTWinc_M-700_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHTWinc_M-700_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHTW_700', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHTWinc_M-750_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBHTWinc_M-750_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHTW_750', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBHTWinc_M-800_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBHTWinc_M-800_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBHTW_800', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBHTWinc_M-800_TuneZ2star_8TeV-madgraph' }, ## {'datasetpath': '/BprimeBprimeToBZBZinc_M-450_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZBZinc_M-450_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZBZ_450', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBZBZinc_M-500_TuneZ2star_8TeV-madgraph/cjenkins-BprimeBprimeToBZBZinc_M-500_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZBZ_500', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'BprimeBprimeToBZBZinc_M-550_TuneZ2star_8TeV-madgraph' }, ## {'datasetpath': '/BprimeBprimeToBZBZinc_M-550_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZBZinc_M-550_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZBZ_550', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBZBZinc_M-600_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZBZinc_M-600_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZBZ_600', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBZBZinc_M-650_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZBZinc_M-650_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZBZ_650', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBZBZinc_M-700_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZBZinc_M-700_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZBZ_700', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBZBZinc_M-750_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZBZinc_M-750_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZBZ_750', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/BprimeBprimeToBZBZinc_M-800_TuneZ2star_8TeV-madgraph/StoreResults-BprimeBprimeToBZBZinc_M-800_TuneZ2star_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'BBToBZBZ_800', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, #### ========= To be submitted ============= ## {'datasetpath': '/TTJets_MassiveBinDECAY_TuneZ2star_8TeV-madgraph-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'200', 'pycfg_params':'runData=0', '#sample_name': 'Top', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/T_s-channel_TuneZ2star_8TeV-powheg-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'SingleTopS', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/T_t-channel_TuneZ2star_8TeV-powheg-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'SingleTopT', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/T_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'SingleToptW', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/Tbar_s-channel_TuneZ2star_8TeV-powheg-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'SingleTopbarS', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/Tbar_t-channel_TuneZ2star_8TeV-powheg-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'SingleTopbarT', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/Tbar_tW-channel-DR_TuneZ2star_8TeV-powheg-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'SingleTopbartW', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/DYJetsToLL_M-50_TuneZ2Star_8TeV-madgraph-tarball/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'300','pycfg_params':'runData=0', '#sample_name': 'ZJets', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v2_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'150', 'pycfg_params':'runData=0', '#sample_name': 'WJets_v2', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/WJetsToLNu_TuneZ2Star_8TeV-madgraph-tarball/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'WJets_v1', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, #not urgent ## {'datasetpath': '/TTWJets_8TeV-madgraph/avetisya-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'TopWJets', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet' }, ## {'datasetpath': '/TTZJets_8TeV-madgraph_v2/mmhl-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'TopZJets', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet' }, ## {'datasetpath': '/WW_TuneZ2star_8TeV_pythia6_tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'WW', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/ZZ_TuneZ2star_8TeV_pythia6_tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'ZZ', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/WZ_TuneZ2star_8TeV_pythia6_tauola/malik-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-3abcc3b1cd74b7b45c7ed2df0ee1e03c/USER', 'number_of_jobs':'50', 'pycfg_params':'runData=0', '#sample_name': 'WZ', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'WZ_TuneZ2star_8TeV_pythia6_tauola' }, ## {'datasetpath': '/TT_8TeV-mcatnlo/galank-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'450', 'pycfg_params':'runData=0', '#sample_name': 'Top_mcatnlo', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'TT_8TeV-mcatnlo' }, ## {'datasetpath': '/TT_CT10_TuneZ2star_8TeV-powheg-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v2_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'300', 'pycfg_params':'runData=0', '#sample_name': 'Top_powheg', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'TT_CT10_TuneZ2star_8TeV-powheg-tauola' }, ## {'datasetpath': '/TTJets_matchingdown_TuneZ2star_8TeV-madgraph-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0', '#sample_name': 'TopMatchdn', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/TTJets_matchingup_TuneZ2star_8TeV-madgraph-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0', '#sample_name': 'TopMatchup', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/TTJets_scaledown_TuneZ2star_8TeV-madgraph-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2_bugfix_v1-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0', '#sample_name': 'TopScaledn', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/TTJets_scaleup_TuneZ2star_8TeV-madgraph-tauola/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0', '#sample_name': 'TopScaleup', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ## {'datasetpath': '/QCD_Pt_20_30_BCtoE_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_20_30_BCtoE', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt_20_30_BCtoE_TuneZ2star_8TeV_pythia6' }, ## {'datasetpath': '/QCD_Pt_30_80_BCtoE_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_30_80_BCtoE', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt_30_80_BCtoE_TuneZ2star_8TeV_pythia6' }, ## {'datasetpath': '/QCD_Pt_80_170_BCtoE_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt_80_170_BCtoE_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_80_170_BCtoE', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'QCD_Pt_80_170_BCtoE_TuneZ2star_8TeV_pythia6'}, ## {'datasetpath': '/QCD_Pt_170_250_BCtoE_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt_170_250_BCtoE_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_170_250_BCtoE', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'QCD_Pt_170_250_BCtoE_TuneZ2star_8TeV_pythia6' }, ## {'datasetpath': '/QCD_Pt_250_350_BCtoE_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt_250_350_BCtoE_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_250_350_BCtoE', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet','btag_map':'QCD_Pt_250_350_BCtoE_TuneZ2star_8TeV_pythia6' }, ## {'datasetpath': '/QCD_Pt_350_BCtoE_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v2_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_350_BCtoE', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt_350_BCtoE_TuneZ2star_8TeV_pythia6' }, ## {'datasetpath': '/QCD_Pt_20_30_EMEnriched_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_20_30_EMEnriched', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt_20_30_EMEnriched_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt_30_80_EMEnriched_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt_30_80_EMEnriched_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_30_80_EMEnriched', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'QCD_Pt_30_80_EMEnriched_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt_80_170_EMEnriched_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_80_170_EMEnriched', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt_80_170_EMEnriched_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt_170_250_EMEnriched_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_170_250_EMEnriched', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt_170_250_EMEnriched_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt_250_350_EMEnriched_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_250_350_EMEnriched', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt_250_350_EMEnriched_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt_350_EMEnriched_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'QCD_Pt_350_EMEnriched', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt_350_EMEnriched_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/GJets_HT-200To400_8TeV-madgraph/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'GJets_HT-200To400', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'GJets_HT-200To400_8TeV-madgraph' }, {'datasetpath': '/GJets_HT-400ToInf_8TeV-madgraph/cjenkins-GJets_HT-400ToInf_8TeV-madgraph-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runEleQCDSamples=1', '#sample_name': 'GJets_HT-400ToInf', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'GJets_HT-400ToInf_8TeV-madgraph' }, {'datasetpath': '/QCD_Pt-15to20_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt-15to20_MuEnrichedPt5_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v2_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-15to20_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'QCD_Pt-15to20_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt-20to30_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-20to30_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt-20to30_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt-30to50_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-30to50_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt-30to50_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': 'QCD_Pt-50to80_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt-50to80_MuEnrichedPt5_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-50to80_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'QCD_Pt-50to80_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt-80to120_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-80to120_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt-80to120_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt-120to170_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt-120to170_MuEnrichedPt5_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-120to170_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'QCD_Pt-120to170_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt-170to300_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt-170to300_MuEnrichedPt5_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-170to300_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'QCD_Pt-170to300_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt-300to470_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt-300to470_MuEnrichedPt5_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-300to470_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'QCD_Pt-300to470_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt-470to600_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/cjenkins-QCD_Pt-470to600_MuEnrichedPt5_TuneZ2star_8TeV_pythia6-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-470to600_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet', 'btag_map':'QCD_Pt-470to600_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt-600to800_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-600to800_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt-600to800_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, {'datasetpath': '/QCD_Pt-800to1000_MuEnrichedPt5_TuneZ2star_8TeV_pythia6/StoreResults-Summer12_DR53X-PU_S10_START53_V7A-v1_TLBSM_53x_v2-c04f3b4fa74c8266c913b71e0c74901d/USER', 'number_of_jobs':'100', 'pycfg_params':'runData=0 runMuonQCDSamples=1', '#sample_name': 'QCD_Pt-800to1000_MuEnrichedPt5', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet', 'btag_map':'QCD_Pt-800to1000_MuEnrichedPt5_TuneZ2star_8TeV_pythia6' }, # ========== Data Electron ========== ## {'datasetpath':'/SingleElectron/StoreResults-Run2012A-13Jul2012-v1_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'50', 'pycfg_params':'runData=1','runselection':'190450-193621' ,'lumi_mask':'Cert_190456-196531_8TeV_13Jul2012ReReco_Collisions12_JSON_v2.txt' , ## '#sample_name': 'Data-Run2012A-13Jul2012-v1','dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleElectron/StoreResults-Run2012A-recover-06Aug2012-v1_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'30', 'pycfg_params':'runData=1','runselection':'190782-190949' ,'lumi_mask':'Cert_190782-190949_8TeV_06Aug2012ReReco_Collisions12_JSON.txt' , ## '#sample_name': 'Data-Run2012A-06Aug2012-v1','dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleElectron/StoreResults-Run2012B-13Jul2012-v1_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'300', 'pycfg_params':'runData=1', 'runselection':'193834-196531', 'lumi_mask':'Cert_190456-196531_8TeV_13Jul2012ReReco_Collisions12_JSON_v2.txt' , ## '#sample_name': 'Data_Run2012B-13Jul2012-v1', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global//servlet/DBSServlet'}, ## {'datasetpath':'/SingleElectron/StoreResults-Run2012C-24Aug2012-v1_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'50', 'pycfg_params':'runData=1','runselection':'198022-198523' ,'lumi_mask':'Cert_198022-198523_8TeV_24Aug2012ReReco_Collisions12_JSON.txt' , ## '#sample_name': 'Data-Run2012C-24Aug2012-v1', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleElectron/StoreResults-Run2012C-PromptReco-v2_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'150', 'pycfg_params':'runData=1','runselection':'198934-203755' ,'lumi_mask':'Cert_190456-203002_8TeV_PromptReco_Collisions12_JSON_v2.txt' , ## '#sample_name': 'Data-Run2012C-PromptReco-v2-a', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleElectron/StoreResults-Run2012C-PromptReco-v2_TLBSM_53x_v2_extension_v1-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'80', 'pycfg_params':'runData=1','runselection':'198934-203755' ,'lumi_mask':'Cert_190456-203002_8TeV_PromptReco_Collisions12_JSON_v2.txt' , ## '#sample_name': 'Data-Run2012C-PromptReco-v2-b', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleElectron/cjenkins-Run2012C-EcalRecover_11Dec2012-v1_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'5', 'pycfg_params':'runData=1','runselection':'201191-201191' ,'lumi_mask':'Cert_201191-201191_8TeV_11Dec2012ReReco-recover_Collisions12_JSON.txt' , ## '#sample_name': 'Data-Run2012C-EcalRecover_11Dec2012-v1', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_ph_analysis_02/servlet/DBSServlet'}, ## {'datasetpath':'/SingleElectron/StoreResults-Run2012D-PromptReco-v1_TLBSM_53x_v2_bugfix-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'300', 'pycfg_params':'runData=1','runselection':'203773-209465' ,'lumi_mask':'Cert_190456-208686_8TeV_PromptReco_Collisions12_JSON.txt' , ## '#sample_name': 'Data-Run2012D-PromptReco-v1-a', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleElectron/StoreResults-Run2012D-PromptReco-v1_TLBSM_53x_v2_extension_v1-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'100', 'pycfg_params':'runData=1','runselection':'203773-209465' ,'lumi_mask':'Cert_190456-208686_8TeV_PromptReco_Collisions12_JSON.txt' , ## '#sample_name': 'Data-Run2012D-PromptReco-v1-b', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ##=========== Data Muon =============== ## {'datasetpath':'/SingleMu/StoreResults-SingleMu_Run2012A-13Jul2012-v1_TLBSM_53x_v2_jsonfix-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'40', 'pycfg_params':'runData=1','runselection':'190456-193621','lumi_mask':'Cert_190456-196531_8TeV_13Jul2012ReReco_Collisions12_JSON_MuonPhys_v3.txt' , ## '#sample_name': 'Data-Run2012A-13Jul2012-v1', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleMu/StoreResults-Run2012A-recover-06Aug2012-v1_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'50', 'pycfg_params':'runData=1','runselection':'190782-190949','lumi_mask':'Cert_190782-190949_8TeV_06Aug2012ReReco_Collisions12_JSON_MuonPhys.txt' , ## '#sample_name': 'Data-Run2012A-06Aug2012-v1', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleMu/StoreResults-Run2012B-13Jul2012-v1_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'300', 'pycfg_params':'runData=1','runselection':'193834-196531','lumi_mask':'Cert_190456-196531_8TeV_13Jul2012ReReco_Collisions12_JSON_MuonPhys_v3.txt' , ## '#sample_name': 'Data-Run2012B-13Jul2012-v1', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleMu/StoreResults-Run2012C-24Aug2012-v1_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'50', 'pycfg_params':'runData=1','runselection':'197770-198913','lumi_mask':'Cert_198022-198523_8TeV_24Aug2012ReReco_Collisions12_JSON_MuonPhys.txt' , ## '#sample_name': 'Data-Run2012C-24Aug2012-v1', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleMu/StoreResults-Run2012C-PromptReco-v2_TLBSM_53x_v2-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'150', 'pycfg_params':'runData=1','runselection':'198934-203755','lumi_mask':'Cert_190456-203002_8TeV_PromptReco_Collisions12_JSON_MuonPhys_v2.txt' , ## '#sample_name': 'Data-Run2012C-PromptReco-v2-a', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleMu/StoreResults-Run2012C-PromptReco-v2_TLBSM_53x_v2-646f7563e9ae6f48814faa1c250f042a/USER', ## 'number_of_jobs':'150', 'pycfg_params':'runData=1','runselection':'198934-203755','lumi_mask':'Cert_190456-203002_8TeV_PromptReco_Collisions12_JSON_MuonPhys_v2.txt' , ## '#sample_name': 'Data-Run2012C-PromptReco-v2-b', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet'}, ## {'datasetpath':'/SingleMu/StoreResults-Run2012C-PromptReco-v2_TLBSM_53x_v2_extension_v1-e3fb55b810dc7a0811f4c66dfa2267c9/USER', ## 'number_of_jobs':'50', 'pycfg_params':'runData=1','runselection':'198934-203755','lumi_mask':'Cert_190456-203002_8TeV_PromptReco_Collisions12_JSON_MuonPhys_v2.txt' , ## '#sample_name': 'Data-Run2012C-PromptReco-v2-c', 'dbs_url':'http://cmsdbsprod.cern.ch/cms_dbs_prod_global/servlet/DBSServlet' }, ] for job in joblist: config = dummy_config # common input files config.set('USER', 'additional_input_files', 'Jec12_V3_L1FastJet_AK5PFchs.txt,Jec12_V3_L2Relative_AK5PFchs.txt,Jec12_V3_L3Absolute_AK5PFchs.txt,Jec12_V3_L2L3Residual_AK5PFchs.txt,Jec12_V3_Uncertainty_AK5PFchs.txt,Jec12_V3_MC_L1FastJet_AK5PFchs.txt,Jec12_V3_MC_L2Relative_AK5PFchs.txt,Jec12_V3_MC_L3Absolute_AK5PFchs.txt,Jec12_V3_MC_L2L3Residual_AK5PFchs.txt,Jec12_V3_MC_Uncertainty_AK5PFchs.txt,PUMC_dist_flat10.root,PUData_finebin_dist.root') # for MC we don't need this config.remove_option('CMSSW','runselection') config.remove_option('CMSSW','lumi_mask') # plug for data if 'Data' in job['#sample_name']: config.remove_option('CMSSW','total_number_of_events') config.set('CMSSW','total_number_of_lumis','-1') # set the CMSSW parameters for p in job: config.set('CMSSW', p, job[p]) #if 'cms_dbs_prod_global'in job[p]: #config.set('CRAB', 'scheduler', 'remoteGlidein') if 'Data' not in job['#sample_name']: btagMap = job['datasetpath'].split('/')[1] if 'btag_map' in job.keys(): btagMap = job['btag_map'] config.set('CMSSW', 'pycfg_params', config.get('CMSSW', 'pycfg_params')+" btagMap="+btagMap) # specify the name in case of data and signal if 'Data' in job['#sample_name'] or 'Bprime' in job['#sample_name']: ui_working_dir = working_dir + job['datasetpath'].split('/')[1] + '_' + job['#sample_name'] + dir_suffix if 'Data' in job['#sample_name']: publish_data_name = 'BPrimeEDMNtuples_53x_v2_'+job['#sample_name'] elif 'WJets_v2' in job['#sample_name']: publish_data_name = 'BPrimeEDMNtuples_53x_v2_WJets_v2' ui_working_dir = working_dir + job['datasetpath'].split('/')[1] + '_v2'+ dir_suffix elif 'WJets_v1' in job['#sample_name']: publish_data_name = 'BPrimeEDMNtuples_53x_v2_WJets_v1' ui_working_dir = working_dir + job['datasetpath'].split('/')[1] + '_v1'+ dir_suffix else: ui_working_dir = working_dir + job['datasetpath'].split('/')[1] + dir_suffix publish_data_name = 'BPrimeEDMNtuples_53x_v2' config.set('USER','ui_working_dir',ui_working_dir) config.set('USER','publish_data_name',publish_data_name) print 'ui', ui_working_dir print 'pub name', publish_data_name # write cfg file and run crab cfgname = 'crab_'+job['#sample_name']+'.cfg' with open(cfgname, 'wb') as configfile: config.write(configfile) s = 'crab -create -cfg ' + cfgname print s subprocess.call( [s], shell=True ) s = 'crab -submit -c ' + ui_working_dir print s subprocess.call( [s], shell=True )

[ "andrew.m.melo@vanderbilt.edu" ]

andrew.m.melo@vanderbilt.edu

44338e41bb946806695a6fb18d70a1d6fa64fd0e

5e989188eb0cfde46f57e033679bd7817eae6620

/liteeth/phy/common.py

a290dfb1bd84798bfb3c5ab3213b22d8bb6a7865

[ "BSD-2-Clause" ]

permissive

telantan/liteeth

1f85b086a7740013f4adfcecc92644fd147085e3

73bd27b506211f12f8c515ad93a3cc65a3624dc3

refs/heads/master

2020-12-13T16:37:47.229699

2020-01-16T14:29:49

2020-01-16T14:46:13

null

0

null

UTF-8

Python

false

1,186

py

# This file is Copyright (c) 2015-2018 Florent Kermarrec <florent@enjoy-digital.fr> # License: BSD from liteeth.common import * from migen.genlib.cdc import MultiReg from migen.fhdl.specials import Tristate class LiteEthPHYHWReset(Module): def __init__(self): self.reset = Signal() # # # counter = Signal(max=512) counter_done = Signal() counter_ce = Signal() self.sync += If(counter_ce, counter.eq(counter + 1)) self.comb += [ counter_done.eq(counter == 256), counter_ce.eq(~counter_done), self.reset.eq(~counter_done) ] class LiteEthPHYMDIO(Module, AutoCSR): def __init__(self, pads): self._w = CSRStorage(3, name="w") self._r = CSRStatus(1, name="r") # # # data_w = Signal() data_oe = Signal() data_r = Signal() self.comb +=[ pads.mdc.eq(self._w.storage[0]), data_oe.eq(self._w.storage[1]), data_w.eq(self._w.storage[2]) ] self.specials += [ MultiReg(data_r, self._r.status[0]), Tristate(pads.mdio, data_w, data_oe, data_r) ]

[ "florent@enjoy-digital.fr" ]

florent@enjoy-digital.fr

521703d00dde8fdf3755df816b625447ecc002e5

4a0c047f73458d089dc62bc2be7c3bd098a08ee2

/data_structor/datetime_format.py

b7c87e2848cb10ed5974e929f4beb7d26f13f2f4

[]

no_license

sunghyungi/pandas_study

b53e53d88abe733b292c06e2658e2fa21428ffca

b861724995914a4a4644c8b08b3b38070d5abc51

refs/heads/master

2020-11-28T02:05:22.565760

2020-01-08T03:09:37

229,675,769

0

null

UTF-8

Python

false

898

py

import pandas as pd df = pd.read_csv('stock-data.csv') pd.set_option('display.max_columns', 15) pd.set_option('display.max_colwidth', 20) pd.set_option('display.unicode.east_asian_width', True) pd.set_option('display.width', 600) print("# 문자열인 날짜 데이터를 판다스 Timestamp로 변환") df['new_Date'] = pd.to_datetime(df['Date']) print(df, '\n') print("# dt속성을 이용하여 new_Date 열의 년월일 정보를 년, 월, 일로 구분") df['Year'] = df['new_Date'].dt.year df['Month'] = df['new_Date'].dt.month df['Day'] = df['new_Date'].dt.day print(df, '\n') print("# Timestamp를 Period로 변환하여 년월일 표기 변경하기") df['Date_yr'] = df['new_Date'].dt.to_period(freq='A') df['Date_m'] = df['new_Date'].dt.to_period(freq='M') print(df, '\n') print("# 원하는 열을 새로운 행 인덱스로 지정") df.set_index('Date_m', inplace=True) print(df)

[ "tjdgusrlek@gmail.com" ]

tjdgusrlek@gmail.com

04f219dbbec76539a6aa9dbf1c473f2c37172866

f07a42f652f46106dee4749277d41c302e2b7406

/Data Set/bug-fixing-5/2c284017d48ab0534905f0d287f801db8ba2f673-<fit>-fix.py

351c29c0af4c2a5ffe9fd52cf6053301e08289d7

[]

no_license

wsgan001/PyFPattern

e0fe06341cc5d51b3ad0fe29b84098d140ed54d1

cc347e32745f99c0cd95e79a18ddacc4574d7faa

refs/heads/main

2023-08-25T23:48:26.112133

2021-10-23T14:11:22

null

0

null

UTF-8

Python

false

6,290

py

def fit(self, x=None, y=None, batch_size=32, epochs=1, verbose=1, callbacks=None, validation_split=0.0, validation_data=None, shuffle=True, class_weight=None, sample_weight=None, initial_epoch=0, **kwargs): 'Trains the model for a fixed number of epochs (iterations on a dataset).\n\n # Arguments\n x: Numpy array of training data,\n or list of Numpy arrays if the model has multiple inputs.\n If all inputs in the model are named,\n you can also pass a dictionary\n mapping input names to Numpy arrays.\n y: Numpy array of target data,\n or list of Numpy arrays if the model has multiple outputs.\n If all outputs in the model are named,\n you can also pass a dictionary\n mapping output names to Numpy arrays.\n batch_size: integer. Number of samples per gradient update.\n epochs: integer, the number of times to iterate\n over the training data arrays.\n verbose: 0, 1, or 2. Verbosity mode.\n 0 = silent, 1 = verbose, 2 = one log line per epoch.\n callbacks: list of callbacks to be called during training.\n See [callbacks](/callbacks).\n validation_split: float between 0 and 1:\n fraction of the training data to be used as validation data.\n The model will set apart this fraction of the training data,\n will not train on it, and will evaluate\n the loss and any model metrics\n on this data at the end of each epoch.\n validation_data: data on which to evaluate\n the loss and any model metrics\n at the end of each epoch. The model will not\n be trained on this data.\n This could be a tuple (x_val, y_val)\n or a tuple (x_val, y_val, val_sample_weights).\n shuffle: boolean, whether to shuffle the training data\n before each epoch.\n class_weight: optional dictionary mapping\n class indices (integers) to\n a weight (float) to apply to the model\'s loss for the samples\n from this class during training.\n This can be useful to tell the model to "pay more attention" to\n samples from an under-represented class.\n sample_weight: optional array of the same length as x, containing\n weights to apply to the model\'s loss for each sample.\n In the case of temporal data, you can pass a 2D array\n with shape (samples, sequence_length),\n to apply a different weight to every timestep of every sample.\n In this case you should make sure to specify\n sample_weight_mode="temporal" in compile().\n initial_epoch: epoch at which to start training\n (useful for resuming a previous training run)\n\n # Returns\n A `History` instance. Its `history` attribute contains\n all information collected during training.\n\n # Raises\n ValueError: In case of mismatch between the provided input data\n and what the model expects.\n ' if ('nb_epoch' in kwargs): warnings.warn('The `nb_epoch` argument in `fit` has been renamed `epochs`.', stacklevel=2) epochs = kwargs.pop('nb_epoch') if kwargs: raise TypeError(('Unrecognized keyword arguments: ' + str(kwargs))) (x, y, sample_weights) = self._standardize_user_data(x, y, sample_weight=sample_weight, class_weight=class_weight, check_batch_axis=False, batch_size=batch_size) if validation_data: do_validation = True if (len(validation_data) == 2): (val_x, val_y) = validation_data val_sample_weight = None elif (len(validation_data) == 3): (val_x, val_y, val_sample_weight) = validation_data else: raise ValueError(('When passing validation_data, it must contain 2 (x_val, y_val) or 3 (x_val, y_val, val_sample_weights) items, however it contains %d items' % len(validation_data))) (val_x, val_y, val_sample_weights) = self._standardize_user_data(val_x, val_y, sample_weight=val_sample_weight, check_batch_axis=False, batch_size=batch_size) self._make_test_function() val_f = self.test_function if (self.uses_learning_phase and (not isinstance(K.learning_phase(), int))): val_ins = (((val_x + val_y) + val_sample_weights) + [0.0]) else: val_ins = ((val_x + val_y) + val_sample_weights) elif (validation_split and (0.0 < validation_split < 1.0)): do_validation = True split_at = int((len(x[0]) * (1.0 - validation_split))) (x, val_x) = (_slice_arrays(x, 0, split_at), _slice_arrays(x, split_at)) (y, val_y) = (_slice_arrays(y, 0, split_at), _slice_arrays(y, split_at)) (sample_weights, val_sample_weights) = (_slice_arrays(sample_weights, 0, split_at), _slice_arrays(sample_weights, split_at)) self._make_test_function() val_f = self.test_function if (self.uses_learning_phase and (not isinstance(K.learning_phase(), int))): val_ins = (((val_x + val_y) + val_sample_weights) + [0.0]) else: val_ins = ((val_x + val_y) + val_sample_weights) else: do_validation = False val_f = None val_ins = None if (self.uses_learning_phase and (not isinstance(K.learning_phase(), int))): ins = (((x + y) + sample_weights) + [1.0]) else: ins = ((x + y) + sample_weights) self._make_train_function() f = self.train_function out_labels = self._get_deduped_metrics_names() if do_validation: callback_metrics = (copy.copy(out_labels) + [('val_' + n) for n in out_labels]) else: callback_metrics = copy.copy(out_labels) return self._fit_loop(f, ins, out_labels=out_labels, batch_size=batch_size, epochs=epochs, verbose=verbose, callbacks=callbacks, val_f=val_f, val_ins=val_ins, shuffle=shuffle, callback_metrics=callback_metrics, initial_epoch=initial_epoch)

[ "dg1732004@smail.nju.edu.cn" ]

dg1732004@smail.nju.edu.cn

63b51da8acb55197f2b5cf0b3f435534ad187add

bf21cd0ef7a94fa106ccd9f91a4bbfdcda7f94ed

/Deep-Learning/scratch/chapter02/ex01.py

2c5dc92731ed2fa6ccaecca539c46eeb6749499f

[]

no_license

juneglee/Deep_Learning

fdf8cae1b962aaa0ce557cb53f78a22b6d5ae1e8

17a448cf6a7c5b61b967dd78af3d328d63378205

refs/heads/master

2023-07-15T03:02:55.739619

2021-08-19T14:04:55

273,253,872

0

null

UTF-8

Python

false

350

py

# 시그모이드 함수 구현하기 import numpy as np import matplotlib.pylab as plt def sigmoid(x): return 1/(1 + np.exp(-x)) x = np.arange(-5.0, 5.0, 0.1) y = sigmoid(x) plt.plot(x, y) plt.ylim(-0.1, 1.1) plt.show() # 시그모이드 = s자 모양 함수 # 계단형 함수와 시그모이드 함수는 둘다 비선형 함수이다.

[ "klcpop1@gmail.com" ]

klcpop1@gmail.com

555f97472640862d217d8dc672bc2c246ae663fb

15f321878face2af9317363c5f6de1e5ddd9b749

/solutions_python/Problem_158/624.py

2a3abc64d2cdf70a551ac5e03e6ac90bbaed9216

[]

no_license

dr-dos-ok/Code_Jam_Webscraper

c06fd59870842664cd79c41eb460a09553e1c80a

26a35bf114a3aa30fc4c677ef069d95f41665cc0

refs/heads/master

2020-04-06T08:17:40.938460

2018-10-14T10:12:47

null

0

null

UTF-8

Python

false

1,118

py

#!/usr/bin/python import requests, logging, string, sys def createOutput(result): f = open(sys.argv[2], "w") for i in range(0, len(result)): f.write("Case #" + str(i + 1) + ": " + result[i] + "\n") f.close(); return def processResults(X, R, C): volume = R * C if volume % X != 0: return "RICHARD" if X == 1 or X == 2: return "GABRIEL" if X == 3: if R == 1 or C == 1: return "RICHARD" else: return "GABRIEL" if X == 4: if (R == 4 and C == 4) or (R == 4 and C == 3) or (R == 3 and C == 4): return "GABRIEL" else: return "RICHARD" def processInput(inputlines): result = [] for line in inputlines: values = line.split(' ') X = int(values[0]) R = int(values[1]) C = int(values[2]) result.append(processResults(X, R, C)) return result def readInput(): inputlines = [] f = open(sys.argv[1]) testcases = int(f.readline().strip()) for i in range(0, testcases): line = f.readline().strip() inputlines.append(line) f.close() return inputlines if __name__ == '__main__': inputlines = readInput() result = processInput(inputlines) createOutput(result) sys.exit()

[ "miliar1732@gmail.com" ]

miliar1732@gmail.com

cfd620bb6fbedecd779cce1cc00f2d22eddeb425

b22588340d7925b614a735bbbde1b351ad657ffc

/athena/Generators/MadGraphModels/python/models/HeavyHiggsTHDM/__init__.py

948b99c911ee93b63f7295fe1003ccaa5fc58319

[]

no_license

rushioda/PIXELVALID_athena

90befe12042c1249cbb3655dde1428bb9b9a42ce

22df23187ef85e9c3120122c8375ea0e7d8ea440

refs/heads/master

2020-12-14T22:01:15.365949

2020-01-19T03:59:35

234,836,993

1

0

null

UTF-8

Python

false

905

py

import particles import couplings import lorentz import parameters import vertices import coupling_orders import write_param_card import propagators all_particles = particles.all_particles all_vertices = vertices.all_vertices all_couplings = couplings.all_couplings all_lorentz = lorentz.all_lorentz all_parameters = parameters.all_parameters all_orders = coupling_orders.all_orders all_functions = function_library.all_functions all_propagators = propagators.all_propagators try: import decays except ImportError: pass else: all_decays = decays.all_decays try: import form_factors except ImportError: pass else: all_form_factors = form_factors.all_form_factors try: import CT_vertices except ImportError: pass else: all_CTvertices = CT_vertices.all_CTvertices gauge = [0] __author__ = "N. Christensen, C. Duhr, B. Fuks" __date__ = "21. 11. 2012" __version__= "1.4.5"

[ "rushioda@lxplus754.cern.ch" ]

rushioda@lxplus754.cern.ch

3f6b359aac70741087ee67c3d384da06abd1b2ac

ac45b55915e634815922329195c203b1e810458c

/minionOC1304_9.py

f7041853ece9ca31941c3cde8472cec562bb2397

[]

no_license

mj1e16lsst/iridisPeriodicNew

96a8bfef0d09f13e18adb81b89e25ae885e30bd9

dc0214b1e702b454e0cca67d4208b2113e1fbcea

refs/heads/master

2020-03-23T15:01:23.583944

2018-07-23T18:58:59

141,715,292

0

null

UTF-8

Python

false

12,180

py

from operator import add #from astropy import units as u #from astropy.coordinates import SkyCoord #from astropy.stats import LombScargle #from gatspy.periodic import LombScargleFast from functools import partial #from gatspy import periodic #import matplotlib.pyplot as plt #from matplotlib.font_manager import FontProperties import lomb_scargle_multiband as periodic from multiprocessing import Pool import numpy as np import os #from sqlite3 import * import random from random import shuffle from random import randint import Observations import Magnitudes # In[13]: #conn = connect('minion_1016_sqlite.db') #conn = connect('astro_lsst_01_1004_sqlite.db') #conn = connect('minion_1020_sqlite.db') # In[14]: # LSST zero points u,g,r,i,z,y zeroPoints = [0,26.5,28.3,28.13,27.79,27.4,26.58] FWHMeff = [0.8,0.92,0.87,0.83,0.80,0.78,0.76] # arcmins? pixelScale = 0.2 readOut = 12.7 sigSys = 0.005 flareperiod = 4096 flarecycles = 10 dayinsec=86400 background = 40 # sat mag u,g,r,i,z,y=14.7,15.7,15.8,15.8,15.3 and 13.9 # start date 59580.033829 end date + 10 years #maglist=[20]*7 lim = [0, 23.5, 24.8, 24.4, 23.9, 23.3, 22.1] # limiting magnitude ugry sat = [0, 14.7, 15.7, 15.8, 15.8, 15.3, 13.9] # sat mag as above # In[15]: looooops = 10000 maglength = 20 freqlength = 20 processors = 20 startnumber = 0 + 9 endnumber = startnumber + 1 #observingStrategy = 'minion' observingStrategy = 'astroD' #observingStrategy = 'panstars' inFile = '/home/mj1e16/periodic/in'+str(startnumber)+'.txt' outFile = '/home/mj1e16/periodic/outminionOC1304'+str(startnumber)+'.txt' #inFile = '/home/ubuntu/vagrant/'+observingStrategy+'/in'+observingStrategy+'KtypefullresultsFile'+str(startnumber)+'.txt' #outFile = '/home/ubuntu/vagrant/'+observingStrategy+'/out'+observingStrategy+'KtypefullresultsFile'+str(startnumber)+'.txt' obs = Observations.obsminionOC1304 for y in range(len(obs)): for x in range(len(obs[y])): obs[y][x] = obs[y][x] + ((random.random()*2.)-1.) # In[19]: def magUncertainy(Filter, objectmag, exposuretime,background, FWHM): # b is background counts per pixel countsPS = 10**((Filter-objectmag)/2.5) counts = countsPS * exposuretime uncertainty = 1/(counts/((counts/2.3)+(((background/2.3)+(12.7**2))*2.266*((FWHM/0.2)**2)))**0.5) # gain assumed to be 1 return uncertainty #from lsst should have got the website! https://smtn-002.lsst.io/ # In[20]: def averageFlux(observations, Frequency, exptime): b = [0]*len(observations) for seconds in range(0, exptime): a = [np.sin((2*np.pi*(Frequency))*(x+(seconds/(3600*24)))) for x in observations] # optical modulation b = map(add, a, b) c = [z/exptime for z in b] return c def Flux(observations,Frequency,exptime): a = [np.sin((2*np.pi*(Frequency)*x)) for x in observations] return a # In[21]: def ellipsoidalFlux(observations, Frequency,exptime): period = 1/(Frequency) phase = [(x % (2*period)) for x in observations] b = [0]*len(observations) for seconds in range(0, exptime): a = [np.sin((2*np.pi*(Frequency))*(x+(seconds/(3600*24)))) for x in observations] # optical modulation b = map(add, a, b) c = [z/exptime for z in b] for x in range(0,len(phase)): if (phase[x]+(1.5*period)) < (3*period): c[x] = c[x]*(1./3.) else: c[x] = c[x]*(2./3.) return c ## this is doing something but not the right something, come back to it # In[22]: def flaring(B, length, dayinsec=86400,amplitude=1): global flareMag, minutes fouriers = np.linspace(0.00001,0.05,(dayinsec/30)) logF = [np.log(x) for x in fouriers] # start at 30 go to a day in 30 sec increments real = [random.gauss(0,1)*((1/x)**(B/2)) for x in fouriers] #random.gauss(mu,sigma) to change for values from zurita # imaginary = [random.gauss(0,1)*((1/x)**(B/2)) for x in fouriers] IFT = np.fft.ifft(real) seconds = np.linspace(0,dayinsec, (dayinsec/30)) # the day in 30 sec increments minutes = [x for x in seconds] minimum = (np.max(-IFT)) positive = [x + minimum for x in IFT] # what did this even achieve? it helped with normalisation! normalised = [x/(np.mean(positive)) for x in positive] # find normalisation normalisedmin = minimum/(np.mean(positive)) normalised = [x - normalisedmin for x in normalised] flareMag = [amplitude * x for x in normalised] # normalise to amplitude logmins = [np.log(d) for d in minutes] # for plotting? # plt.plot(minutes,flareMag) # plt.title('lightcurve') # plt.show() return flareMag # In[55]: def lombScargle(frequencyRange,objectmag=20,loopNo=looooops,df=0.001,fmin=0.001,numsteps=100000,modulationAmplitude=0.1,Nquist=200): # frequency range and object mag in list #global totperiod, totmperiod, totpower, date, amplitude, frequency, periods, LSperiod, power, mag, error, SigLevel results = {} totperiod = [] totmperiod = [] totpower = [] # reset SigLevel = [] filterletter = ['o','u','g','r','i','z','y'] period = 1/(frequencyRange) if period > 0.5: numsteps = 10000 elif period > 0.01: numsteps = 100000 else: numsteps = 200000 freqs = fmin + df * np.arange(numsteps) # for manuel allobsy, uobsy, gobsy, robsy, iobsy, zobsy, yobsy = [], [], [], [], [], [], [] #reset measuredpower = [] # reset y = [allobsy, uobsy, gobsy, robsy, iobsy, zobsy, yobsy] # for looping only for z in range(1, len(y)): #y[z] = averageFlux(obs[z], frequencyRange[frange], 30) # amplitde calculation for observations, anf frequency range y[z] = ellipsoidalFlux(obs[z], frequencyRange,30) y[z] = [modulationAmplitude * t for t in y[z]] # scaling for G in range(0, len(y[z])): flareMinute = int(round((obs[z][G]*24*60*2)%((dayinsec/(30*2))*flarecycles))) y[z][G] = y[z][G] + longflare[flareMinute] # add flares swapped to second but not changing the name intrtoduces fewer bugs date = [] amplitude = [] mag = [] error = [] filts = [] for z in range(1, len(y)): if objectmag[z] > sat[z] and objectmag[z] < lim[z]: #date.extend([x for x in obs[z]]) date.extend(obs[z]) amplitude = [t + random.gauss(0,magUncertainy(zeroPoints[z],objectmag[z],30,background,FWHMeff[z])) for t in y[z]] # scale amplitude and add poisson noise mag.extend([objectmag[z] - t for t in amplitude]) # add actual mag error.extend([sigSys + magUncertainy(zeroPoints[z],objectmag[z],30,background,FWHMeff[z])+0.2]*len(amplitude)) filts.extend([filterletter[z]]*len(amplitude)) phase = [(day % (period*2))/(period*2) for day in obs[z]] pmag = [objectmag[z] - t for t in amplitude] # plt.plot(phase, pmag, 'o', markersize=4) # plt.xlabel('Phase') # plt.ylabel('Magnitude') # plt.gca().invert_yaxis() # plt.title('filter'+str(z)+', Period = '+str(period))#+', MeasuredPeriod = '+str(LSperiod)+', Periodx20 = '+(str(period*20))) # plt.show() # plt.plot(date, mag, 'o') # plt.xlim(lower,higher) # plt.xlabel('time (days)') # plt.ylabel('mag') # plt.gca().invert_yaxis() # plt.show() model = periodic.LombScargleMultibandFast(fit_period=False) model.fit(date, mag, error, filts) power = model.score_frequency_grid(fmin, df, numsteps) if period > 10.: model.optimizer.period_range=(10, 110) elif period > 0.51: model.optimizer.period_range=(0.5, 10) elif period > 0.011: model.optimizer.period_range=(0.01, 0.52) else: model.optimizer.period_range=(0.0029, 0.012) LSperiod = model.best_period if period < 10: higher = 10 else: higher = 100 # fig, ax = plt.subplots() # ax.plot(1./freqs, power) # ax.set(xlim=(0, higher), ylim=(0, 1.2), # xlabel='period (days)', # ylabel='Lomb-Scargle Power', # title='Period = '+str(period)+', MeasuredPeriod = '+str(LSperiod)+', Periodx20 = '+(str(period*20))); # plt.show() phase = [(day % (period*2))/(period*2) for day in date] #idealphase = [(day % (period*2))/(period*2) for day in dayZ] #print(len(phase),len(idealphase)) #plt.plot(idealphase,Zmag,'ko',) # plt.plot(phase, mag, 'o', markersize=4) # plt.xlabel('Phase') # plt.ylabel('Magnitude') # plt.gca().invert_yaxis() # plt.title('Period = '+str(period)+', MeasuredPeriod = '+str(LSperiod)+', Periodx20 = '+(str(period*20))) # plt.show() #print(period, LSperiod, period*20) # print('actualperiod', period, 'measured period', np.mean(LSperiod),power.max())# 'power',np.mean(power[maxpos])) # print(frequencyRange[frange], 'z', z) # totperiod.append(period) # totmperiod.append(np.mean(LSperiod)) # totpower.append(power.max()) mpower = power.max() measuredpower.append(power.max()) # should this correspond to period power and not max power? maxpower = [] counter = 0. for loop in range(0,loopNo): random.shuffle(date) model = periodic.LombScargleMultibandFast(fit_period=False) model.fit(date, mag, error, filts) power = model.score_frequency_grid(fmin, df, numsteps) maxpower.append(power.max()) for X in range(0, len(maxpower)): if maxpower[X] > measuredpower[-1]: counter = counter + 1. Significance = (1.-(counter/len(maxpower))) #print('sig', Significance, 'counter', counter) SigLevel.append(Significance) #freqnumber = FrangeLoop.index(frequencyRange) #magnumber = MagRange.index(objectmag) #print(fullmaglist) #listnumber = (magnumber*maglength)+freqnumber # print(listnumber) # measuredperiodlist[listnumber] = LSperiod # periodlist[listnumber] = period # powerlist[listnumber] = mpower # siglist[listnumber] = Significance # fullmaglist[listnumber] = objectmag # results order, 0=mag,1=period,2=measuredperiod,3=siglevel,4=power,5=listnumber results[0] = objectmag[3] results[1] = period results[2] = LSperiod results[3] = Significance results[4] = mpower results[5] = 0#listnumber return results # In[24]: #findObservations([(630,)]) #remove25(obs) #averageFlux(obs[0], 1, 30) longflare = [] for floop in range(0,flarecycles): flareone = flaring(-1, flareperiod, amplitude=0.3) flareone = flareone[0:1440] positiveflare = [abs(x) for x in flareone] longflare.extend(positiveflare) # In[25]: PrangeLoop = np.logspace(-2.5,2,freqlength) FrangeLoop = [(1/x) for x in PrangeLoop] # In[26]: # reset results file with open(inFile,'w') as f: f.write('fullmaglist \n\n periodlist \n\n measuredperiodlist \n\n siglist \n\n powerlist \n\n listnumberlist \n\n end of file') # In[57]: results = [] fullmeasuredPeriod = [] fullPeriod = [] fullPower = [] fullSigLevel = [] fullMag = [] MagRangearray = np.linspace(17,24,maglength) MagRange = [x for x in MagRangearray] maglist = [] for x in range(len(MagRange)): maglist.append([MagRange[x]]*7) newlist = Magnitudes.mag1304 pool = Pool(processors) for h in range(startnumber,endnumber): print(newlist[h]) results.append(pool.map(partial(lombScargle, objectmag=newlist[h]),FrangeLoop)) twoDlist = [[],[],[],[],[],[]] for X in range(len(results)): for Y in range(len(results[X])): twoDlist[0].append(results[X][Y][0]) twoDlist[1].append(results[X][Y][1]) twoDlist[2].append(results[X][Y][2]) twoDlist[3].append(results[X][Y][3]) twoDlist[4].append(results[X][Y][4]) twoDlist[5].append(results[X][Y][5]) with open(inFile, 'r') as istr: with open(outFile,'w') as ostr: for i, line in enumerate(istr): # Get rid of the trailing newline (if any). line = line.rstrip('\n') if i % 2 != 0: line += str(twoDlist[int((i-1)/2)])+',' ostr.write(line+'\n')

[ "mj1e16@soton.ac.uk" ]

mj1e16@soton.ac.uk

d36ac047086b61bb183185f54828352106cbdb9e

c7a94e7b1956c79f3c390508e60902a6bb56f3c5

/xlsxwriter/core.py

905736f039167206a9cfb1549c151f8e084c2bb7

[ "BSD-2-Clause" ]

permissive

alexander-beedie/XlsxWriter

635b68d98683efb8404d58f5d896f8e6d433e379

03f76666df9ce5ac0ab6bb8ff866d424dc8fea58

refs/heads/main

2023-05-27T15:33:36.911705

2023-05-04T00:00:04

144,862,072

0

null

2018-08-15T14:15:51

2018-08-15T14:15:50

null

UTF-8

Python

false

5,656

py

############################################################################### # # Core - A class for writing the Excel XLSX Worksheet file. # # SPDX-License-Identifier: BSD-2-Clause # Copyright 2013-2023, John McNamara, jmcnamara@cpan.org # # Standard packages. from datetime import datetime # Package imports. from . import xmlwriter class Core(xmlwriter.XMLwriter): """ A class for writing the Excel XLSX Core file. """ ########################################################################### # # Public API. # ########################################################################### def __init__(self): """ Constructor. """ super(Core, self).__init__() self.properties = {} ########################################################################### # # Private API. # ########################################################################### def _assemble_xml_file(self): # Assemble and write the XML file. # Write the XML declaration. self._xml_declaration() self._write_cp_core_properties() self._write_dc_title() self._write_dc_subject() self._write_dc_creator() self._write_cp_keywords() self._write_dc_description() self._write_cp_last_modified_by() self._write_dcterms_created() self._write_dcterms_modified() self._write_cp_category() self._write_cp_content_status() self._xml_end_tag("cp:coreProperties") # Close the file. self._xml_close() def _set_properties(self, properties): # Set the document properties. self.properties = properties def _datetime_to_iso8601_date(self, date): # Convert to a ISO 8601 style "2010-01-01T00:00:00Z" date. if not date: date = datetime.utcnow() return date.strftime("%Y-%m-%dT%H:%M:%SZ") ########################################################################### # # XML methods. # ########################################################################### def _write_cp_core_properties(self): # Write the <cp:coreProperties> element. xmlns_cp = ( "http://schemas.openxmlformats.org/package/2006/" + "metadata/core-properties" ) xmlns_dc = "http://purl.org/dc/elements/1.1/" xmlns_dcterms = "http://purl.org/dc/terms/" xmlns_dcmitype = "http://purl.org/dc/dcmitype/" xmlns_xsi = "http://www.w3.org/2001/XMLSchema-instance" attributes = [ ("xmlns:cp", xmlns_cp), ("xmlns:dc", xmlns_dc), ("xmlns:dcterms", xmlns_dcterms), ("xmlns:dcmitype", xmlns_dcmitype), ("xmlns:xsi", xmlns_xsi), ] self._xml_start_tag("cp:coreProperties", attributes) def _write_dc_creator(self): # Write the <dc:creator> element. data = self.properties.get("author", "") self._xml_data_element("dc:creator", data) def _write_cp_last_modified_by(self): # Write the <cp:lastModifiedBy> element. data = self.properties.get("author", "") self._xml_data_element("cp:lastModifiedBy", data) def _write_dcterms_created(self): # Write the <dcterms:created> element. date = self.properties.get("created", datetime.utcnow()) xsi_type = "dcterms:W3CDTF" date = self._datetime_to_iso8601_date(date) attributes = [ ( "xsi:type", xsi_type, ) ] self._xml_data_element("dcterms:created", date, attributes) def _write_dcterms_modified(self): # Write the <dcterms:modified> element. date = self.properties.get("created", datetime.utcnow()) xsi_type = "dcterms:W3CDTF" date = self._datetime_to_iso8601_date(date) attributes = [ ( "xsi:type", xsi_type, ) ] self._xml_data_element("dcterms:modified", date, attributes) def _write_dc_title(self): # Write the <dc:title> element. if "title" in self.properties: data = self.properties["title"] else: return self._xml_data_element("dc:title", data) def _write_dc_subject(self): # Write the <dc:subject> element. if "subject" in self.properties: data = self.properties["subject"] else: return self._xml_data_element("dc:subject", data) def _write_cp_keywords(self): # Write the <cp:keywords> element. if "keywords" in self.properties: data = self.properties["keywords"] else: return self._xml_data_element("cp:keywords", data) def _write_dc_description(self): # Write the <dc:description> element. if "comments" in self.properties: data = self.properties["comments"] else: return self._xml_data_element("dc:description", data) def _write_cp_category(self): # Write the <cp:category> element. if "category" in self.properties: data = self.properties["category"] else: return self._xml_data_element("cp:category", data) def _write_cp_content_status(self): # Write the <cp:contentStatus> element. if "status" in self.properties: data = self.properties["status"] else: return self._xml_data_element("cp:contentStatus", data)

[ "jmcnamara@cpan.org" ]

jmcnamara@cpan.org

c7f48720bb0d186381903465c450342a3c0e979a

2b82b45edf199488e45cef97571e57dff4a3e824

/programs/spectralnorm/spectralnorm-numba-2.py

e373f4c513a9114fd405c25ea2883f5c37f7a01e

[ "BSD-3-Clause" ]

permissive

abilian/python-benchmarks

cf8b82d97c0836c65ff00337b649a53bc9af965e

37a519a2ee835cf53ca0bb78e7e7c83da69d664e

refs/heads/main

2023-08-05T18:50:53.490042

2021-10-01T10:49:33

321,367,812

1

0

null

UTF-8

Python

false

686

py

# The Computer Language Benchmarks Game # http://benchmarksgame.alioth.debian.org/ # # Contributed by Sebastien Loisel # Fixed by Isaac Gouy # Sped up by Josh Goldfoot # Dirtily sped up by Simon Descarpentries # Sped up with numpy by Kittipong Piyawanno # 2to3 from numba import jit from sys import argv from numpy import * @jit def spectralnorm(n): u = matrix(ones(n)) j = arange(n) eval_func = lambda i: 1.0 / ((i + j) * (i + j + 1) / 2 + i + 1) M = matrix([eval_func(i) for i in arange(n)]) MT = M.T for i in range(10): v = (u * MT) * M u = (v * MT) * M print("%0.9f" % (sum(u * v.T) / sum(v * v.T)) ** 0.5) spectralnorm(int(argv[1]))

[ "sf@fermigier.com" ]

sf@fermigier.com

77066fd264e1194de5a270d36f268632b904b588

8d47d0bdf0f3bcc8c8f82e7624e391ba2353efe1

/hpcloud/networks/workflows.py

79377a368544c19952a6263b5713bcf7887182df

[ "Apache-2.0" ]

permissive

cosgrid001/cosgrid_hh

48328bbfae69f9978b82fe2c94799fbf8bc978b2

9b4dbf3c9c134f0c08c7d0330a3d0e69af12a8f4

refs/heads/master

2020-01-23T21:03:04.242315

2016-12-11T05:39:33

74,579,908

0

1

null

UTF-8

Python

false

16,524

py

# vim: tabstop=4 shiftwidth=4 softtabstop=4 # Copyright 2012 NEC Corporation # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import logging import netaddr from django.core.urlresolvers import reverse from django.utils.translation import ugettext_lazy as _ from horizon import exceptions,forms,messages,workflows from horizon.utils import fields from hpcloud import api LOG = logging.getLogger(__name__) class CreateNetworkInfoAction(workflows.Action): net_name = forms.CharField(max_length=255, label=_("Network Name"), required=False) if api.neutron.is_port_profiles_supported(): net_profile_id = forms.ChoiceField(label=_("Network Profile")) admin_state = forms.BooleanField(label=_("Admin State"), initial=True, required=False) if api.neutron.is_port_profiles_supported(): def __init__(self, request, *args, **kwargs): super(CreateNetworkInfoAction, self).__init__(request, *args, **kwargs) self.fields['net_profile_id'].choices = ( self.get_network_profile_choices(request)) def get_network_profile_choices(self, request): profile_choices = [('', _("Select a profile"))] for profile in self._get_profiles(request, 'network'): profile_choices.append((profile.id, profile.name)) return profile_choices def _get_profiles(self, request, type_p): try: profiles = api.neutron.profile_list(request, type_p) except Exception: profiles = [] msg = _('Network Profiles could not be retrieved.') exceptions.handle(request, msg) return profiles # TODO(absubram): Add ability to view network profile information # in the network detail if a profile is used. class Meta: name = _("Network") help_text = _("From here you can create a new network.\n" "In addition a subnet associated with the network " "can be created in the next panel.") class CreateNetworkInfo(workflows.Step): action_class = CreateNetworkInfoAction if api.neutron.is_port_profiles_supported(): contributes = ("net_name", "admin_state", "net_profile_id") else: contributes = ("net_name", "admin_state") class CreateSubnetInfoAction(workflows.Action): with_subnet = forms.BooleanField(label=_("Create Subnet"), initial=True, required=False) subnet_name = forms.CharField(max_length=255, label=_("Subnet Name"), required=False) cidr = fields.IPField(label=_("Network Address"), required=False, initial="", help_text=_("Network address in CIDR format " "(e.g. 192.168.0.0/24)"), version=fields.IPv4 | fields.IPv6, mask=True) ip_version = forms.ChoiceField(choices=[(4, 'IPv4'), (6, 'IPv6')], label=_("IP Version")) gateway_ip = fields.IPField( label=_("Gateway IP"), required=False, initial="", help_text=_("IP address of Gateway (e.g. 192.168.0.254) " "The default value is the first IP of the " "network address (e.g. 192.168.0.1 for " "192.168.0.0/24). " "If you use the default, leave blank. " "If you want to use no gateway, " "check 'Disable Gateway' below."), version=fields.IPv4 | fields.IPv6, mask=False) no_gateway = forms.BooleanField(label=_("Disable Gateway"), initial=False, required=False) class Meta: name = _("Subnet") help_text = _('You can create a subnet associated with the new ' 'network, in which case "Network Address" must be ' 'specified. If you wish to create a network WITHOUT a ' 'subnet, uncheck the "Create Subnet" checkbox.') def _check_subnet_data(self, cleaned_data, is_create=True): cidr = cleaned_data.get('cidr') ip_version = int(cleaned_data.get('ip_version')) gateway_ip = cleaned_data.get('gateway_ip') no_gateway = cleaned_data.get('no_gateway') if not cidr: msg = _('Specify "Network Address" or ' 'clear "Create Subnet" checkbox.') raise forms.ValidationError(msg) if cidr: subnet = netaddr.IPNetwork(cidr) if subnet.version != ip_version: msg = _('Network Address and IP version are inconsistent.') raise forms.ValidationError(msg) if (ip_version == 4 and subnet.prefixlen == 32) or \ (ip_version == 6 and subnet.prefixlen == 128): msg = _("The subnet in the Network Address is too small (/%s)." % subnet.prefixlen) raise forms.ValidationError(msg) if not no_gateway and gateway_ip: if netaddr.IPAddress(gateway_ip).version is not ip_version: msg = _('Gateway IP and IP version are inconsistent.') raise forms.ValidationError(msg) if not is_create and not no_gateway and not gateway_ip: msg = _('Specify IP address of gateway or ' 'check "Disable Gateway".') raise forms.ValidationError(msg) def clean(self): cleaned_data = super(CreateSubnetInfoAction, self).clean() with_subnet = cleaned_data.get('with_subnet') if not with_subnet: return cleaned_data self._check_subnet_data(cleaned_data) return cleaned_data class CreateSubnetInfo(workflows.Step): action_class = CreateSubnetInfoAction contributes = ("with_subnet", "subnet_name", "cidr", "ip_version", "gateway_ip", "no_gateway") class CreateSubnetDetailAction(workflows.Action): enable_dhcp = forms.BooleanField(label=_("Enable DHCP"), initial=True, required=False) allocation_pools = forms.CharField( widget=forms.Textarea(), label=_("Allocation Pools"), help_text=_("IP address allocation pools. Each entry is " "<start_ip_address>,<end_ip_address> " "(e.g., 192.168.1.100,192.168.1.120) " "and one entry per line."), required=False) dns_nameservers = forms.CharField( widget=forms.widgets.Textarea(), label=_("DNS Name Servers"), help_text=_("IP address list of DNS name servers for this subnet. " "One entry per line."), required=False) host_routes = forms.CharField( widget=forms.widgets.Textarea(), label=_("Host Routes"), help_text=_("Additional routes announced to the hosts. " "Each entry is <destination_cidr>,<nexthop> " "(e.g., 192.168.200.0/24,10.56.1.254) " "and one entry per line."), required=False) class Meta: name = _("Subnet Detail") help_text = _('You can specify additional attributes for the subnet.') def _convert_ip_address(self, ip, field_name): try: return netaddr.IPAddress(ip) except (netaddr.AddrFormatError, ValueError): msg = _('%(field_name)s: Invalid IP address ' '(value=%(ip)s)' % dict( field_name=field_name, ip=ip)) raise forms.ValidationError(msg) def _convert_ip_network(self, network, field_name): try: return netaddr.IPNetwork(network) except (netaddr.AddrFormatError, ValueError): msg = _('%(field_name)s: Invalid IP address ' '(value=%(network)s)' % dict( field_name=field_name, network=network)) raise forms.ValidationError(msg) def _check_allocation_pools(self, allocation_pools): for p in allocation_pools.split('\n'): p = p.strip() if not p: continue pool = p.split(',') if len(pool) != 2: msg = _('Start and end addresses must be specified ' '(value=%s)') % p raise forms.ValidationError(msg) start, end = [self._convert_ip_address(ip, "allocation_pools") for ip in pool] if start > end: msg = _('Start address is larger than end address ' '(value=%s)') % p raise forms.ValidationError(msg) def _check_dns_nameservers(self, dns_nameservers): for ns in dns_nameservers.split('\n'): ns = ns.strip() if not ns: continue self._convert_ip_address(ns, "dns_nameservers") def _check_host_routes(self, host_routes): for r in host_routes.split('\n'): r = r.strip() if not r: continue route = r.split(',') if len(route) != 2: msg = _('Host Routes format error: ' 'Destination CIDR and nexthop must be specified ' '(value=%s)') % r raise forms.ValidationError(msg) self._convert_ip_network(route[0], "host_routes") self._convert_ip_address(route[1], "host_routes") def clean(self): cleaned_data = super(CreateSubnetDetailAction, self).clean() self._check_allocation_pools(cleaned_data.get('allocation_pools')) self._check_host_routes(cleaned_data.get('host_routes')) self._check_dns_nameservers(cleaned_data.get('dns_nameservers')) return cleaned_data class CreateSubnetDetail(workflows.Step): action_class = CreateSubnetDetailAction contributes = ("enable_dhcp", "allocation_pools", "dns_nameservers", "host_routes") class CreateNetwork(workflows.Workflow): slug = "create_network" name = _("Create Network") finalize_button_name = _("Create") success_message = _('Created network "%s".') failure_message = _('Unable to create network "%s".') default_steps = (CreateNetworkInfo, CreateSubnetInfo, CreateSubnetDetail) def get_success_url(self): return reverse("horizon:hpcloud:networks:index") def get_failure_url(self): return reverse("horizon:hpcloud:networks:index") def format_status_message(self, message): name = self.context.get('net_name') or self.context.get('net_id', '') return message % name def _create_network(self, request, data): try: params = {'name': data['net_name'], 'admin_state_up': data['admin_state']} if api.neutron.is_port_profiles_supported(): params['net_profile_id'] = data['net_profile_id'] network = api.neutron.network_create(request, **params) network.set_id_as_name_if_empty() self.context['net_id'] = network.id msg = _('Network "%s" was successfully created.') % network.name LOG.debug(msg) return network except Exception as e: msg = (_('Failed to create network "%(network)s": %(reason)s') % {"network": data['net_name'], "reason": e}) LOG.info(msg) redirect = self.get_failure_url() exceptions.handle(request, msg, redirect=redirect) return False def _setup_subnet_parameters(self, params, data, is_create=True): """Setup subnet parameters This methods setups subnet parameters which are available in both create and update. """ is_update = not is_create params['enable_dhcp'] = data['enable_dhcp'] if is_create and data['allocation_pools']: pools = [dict(zip(['start', 'end'], pool.strip().split(','))) for pool in data['allocation_pools'].split('\n') if pool.strip()] params['allocation_pools'] = pools if data['host_routes'] or is_update: routes = [dict(zip(['destination', 'nexthop'], route.strip().split(','))) for route in data['host_routes'].split('\n') if route.strip()] params['host_routes'] = routes if data['dns_nameservers'] or is_update: nameservers = [ns.strip() for ns in data['dns_nameservers'].split('\n') if ns.strip()] params['dns_nameservers'] = nameservers def _create_subnet(self, request, data, network=None, tenant_id=None, no_redirect=False): if network: network_id = network.id network_name = network.name else: network_id = self.context.get('network_id') network_name = self.context.get('network_name') try: params = {'network_id': network_id, 'name': data['subnet_name'], 'cidr': data['cidr'], 'ip_version': int(data['ip_version'])} if tenant_id: params['tenant_id'] = tenant_id if data['no_gateway']: params['gateway_ip'] = None elif data['gateway_ip']: params['gateway_ip'] = data['gateway_ip'] self._setup_subnet_parameters(params, data) subnet = api.neutron.subnet_create(request, **params) self.context['subnet_id'] = subnet.id msg = _('Subnet "%s" was successfully created.') % data['cidr'] LOG.debug(msg) return subnet except Exception as e: msg = _('Failed to create subnet "%(sub)s" for network "%(net)s": ' ' %(reason)s') if no_redirect: redirect = None else: redirect = self.get_failure_url() exceptions.handle(request, msg % {"sub": data['cidr'], "net": network_name, "reason": e}, redirect=redirect) return False def _delete_network(self, request, network): """Delete the created network when subnet creation failed""" try: api.neutron.network_delete(request, network.id) msg = _('Delete the created network "%s" ' 'due to subnet creation failure.') % network.name LOG.debug(msg) redirect = self.get_failure_url() messages.info(request, msg) raise exceptions.Http302(redirect) #return exceptions.RecoverableError except Exception: msg = _('Failed to delete network "%s"') % network.name LOG.info(msg) redirect = self.get_failure_url() exceptions.handle(request, msg, redirect=redirect) def handle(self, request, data): network = self._create_network(request, data) if not network: return False # If we do not need to create a subnet, return here. if not data['with_subnet']: return True subnet = self._create_subnet(request, data, network, no_redirect=True) if subnet: return True else: self._delete_network(request, network) return False

[ "jayaprakash.r@cloudenablers.com" ]

jayaprakash.r@cloudenablers.com

7d21255d581e353aca38239ac109c88f33e37acd

13a5a2ab12a65d65a5bbefce5253c21c6bb8e780

/dnainfo/crimemaps/migrations/0024_nycschoolswatertesting.py

8679bb07a5f901d7e3c0d9f930f5754ade2f377c

[]

no_license

NiJeLorg/DNAinfo-CrimeMaps

535b62205fe1eb106d0f610d40f2f2a35e60a09e

63f3f01b83308294a82565f2dc8ef6f3fbcdb721

refs/heads/master

2021-01-23T19:28:12.642479

2017-05-11T06:04:08

34,847,724

2

0

null

2016-11-25T15:56:14

2015-04-30T10:02:41

JavaScript

UTF-8

Python

false

1,689

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('crimemaps', '0023_nyctrainsitstand'), ] operations = [ migrations.CreateModel( name='NYCschoolsWaterTesting', fields=[ ('id', models.AutoField(verbose_name='ID', serialize=False, auto_created=True, primary_key=True)), ('created', models.DateTimeField(auto_now=True)), ('lc', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('bc', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('ln', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('bn', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('add', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('cit', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('stc', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('zip', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('wtp', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('er', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('dohm', models.CharField(default=b'', max_length=255, null=True, blank=True)), ('note', models.CharField(default=b'', max_length=255, null=True, blank=True)), ], ), ]

[ "jd@nijel.org" ]

jd@nijel.org

5559ceb97c6a0b3e8d421323d1656c568b83aa72

912c4445e7041869d1c8535a493b78d7ee35424b

/status/tests.py

034f0f6f61543636b32a1de55226078cabb8a2f1

[]

no_license

maltezc/Udemy-DjangoRestAPI

3f243ec97ea5e8e9d6ddc2005986b6a05aa11097

de6f885cf0cddaf22fb6fd72d18fc805b9ce48d2

refs/heads/master

2022-12-14T06:04:43.011691

2018-08-05T01:10:17

140,590,753

0

null

2022-11-22T02:48:04

2018-07-11T14:56:08

Python

UTF-8

Python

false

602

py

from django.test import TestCase from django.contrib.auth import get_user_model from status.models import Status User = get_user_model() class StatusTestCase(TestCase): def setUp(self): user = User.objects.create(username='cfe', email='hello@cfe.com') user.set_password("yeahhhcfe") user.save() def test_creating_status(self): user = User.objects.get(username='cfe') obj = Status.objects.create(user=user, content='Some cool new content') self.assertEqual(obj.id, 1) qs = Status.objects.all() self.assertEqual(qs.count(), 1)

[ "cflux.maltez@live.com" ]

cflux.maltez@live.com

48c68f16180b5d0dff96e2b6800b16dfe4b6f958

ed559cbd80aa290f03ac9f1c8a08258fe051ed29

/model_r.py

1088010db9557932c1f80ff8c9f31c62616bb23f

[]

no_license

nmaypeter/project_nw_190424

70759e441a9f2782d97428cfac10c99bc0c052a2

07adfe85a9389d7a3ea8261ff62b181b2deff2c3

refs/heads/master

2020-05-16T17:24:28.658557

2019-04-29T14:32:24

183,194,312

0

null

UTF-8

Python

false

13,541

py

from SeedSelection_Random import * import os if __name__ == '__main__': model_name = 'mr' dataset_seq = [2] prod_seq, prod2_seq = [1, 2], [1, 2, 3] cm_seq = [1, 2] wallet_distribution_seq = [1, 2] total_budget = 10 wpiwp_seq = [bool(1), bool(0)] sample_number = 10 ppp_seq = [1, 2, 3] monte_carlo, eva_monte_carlo = 10, 100 for data_setting in dataset_seq: dataset_name = 'email_undirected' * (data_setting == 1) + 'dnc_email_directed' * (data_setting == 2) + 'email_Eu_core_directed' * (data_setting == 3) + \ 'WikiVote_directed' * (data_setting == 4) + 'NetPHY_undirected' * (data_setting == 5) for cm in cm_seq: cascade_model = 'ic' * (cm == 1) + 'wc' * (cm == 2) for prod_setting in prod_seq: for prod_setting2 in prod2_seq: product_name = 'item_lphc' * (prod_setting == 1) + 'item_hplc' * (prod_setting == 2) + '_ce' * (prod_setting2 == 2) + '_ee' * (prod_setting2 == 3) for wallet_distribution in wallet_distribution_seq: wallet_distribution_type = 'm50e25' * (wallet_distribution == 1) + 'm99e96' * (wallet_distribution == 2) for wpiwp in wpiwp_seq: iniG = IniGraph(dataset_name) iniP = IniProduct(product_name) seed_cost_dict = iniG.constructSeedCostDict() graph_dict = iniG.constructGraphDict(cascade_model) product_list = iniP.getProductList() num_node = len(seed_cost_dict) num_product = len(product_list) seed_set_sequence, ss_time_sequence = [[] for _ in range(total_budget)], [[] for _ in range(total_budget)] ssr_main = SeedSelectionRandom(graph_dict, seed_cost_dict, product_list) for sample_count in range(sample_number): ss_strat_time = time.time() begin_budget = 1 now_budget = 0.0 seed_set = [set() for _ in range(num_product)] random_node_set = ssr_main.constructRandomNodeSet() ss_acc_time = round(time.time() - ss_strat_time, 2) temp_sequence = [[begin_budget, now_budget, seed_set, random_node_set, ss_acc_time]] while len(temp_sequence) != 0: ss_strat_time = time.time() [begin_budget, now_budget, seed_set, random_node_set, ss_acc_time] = temp_sequence.pop(0) print('@ seed selection @ dataset_name = ' + dataset_name + '_' + cascade_model + ', dist = ' + str(wallet_distribution_type) + ', wpiwp = ' + str(wpiwp) + ', product_name = ' + product_name + ', budget = ' + str(begin_budget) + ', sample_count = ' + str(sample_count)) mep_g = selectRandomSeed(random_node_set) mep_k_prod, mep_i_node = mep_g[0], mep_g[1] while now_budget < begin_budget and mep_i_node != '-1': sc = seed_cost_dict[mep_i_node] if round(now_budget + sc, 2) >= begin_budget and begin_budget < total_budget and len(temp_sequence) == 0: ss_time = round(time.time() - ss_strat_time + ss_acc_time, 2) temp_random_node_set = copy.deepcopy(random_node_set) temp_random_node_set.add((mep_k_prod, mep_i_node)) temp_sequence.append([begin_budget + 1, now_budget, copy.deepcopy(seed_set), temp_random_node_set, ss_time]) if round(now_budget + sc, 2) >= begin_budget > begin_budget: mep_g = selectRandomSeed(random_node_set) mep_k_prod, mep_i_node = mep_g[0], mep_g[1] if mep_i_node == '-1': break continue seed_set[mep_k_prod].add(mep_i_node) now_budget += sc mep_g = selectRandomSeed(random_node_set) mep_k_prod, mep_i_node = mep_g[0], mep_g[1] ss_time = round(time.time() - ss_strat_time + ss_acc_time, 2) print('ss_time = ' + str(ss_time) + 'sec') seed_set_sequence[begin_budget - 1].append(seed_set) ss_time_sequence[begin_budget - 1].append(ss_time) for bud in range(total_budget): if len(seed_set_sequence[bud]) != sample_count + 1: seed_set_sequence[bud].append(0) ss_time_sequence[bud].append(ss_time_sequence[bud - 1][-1]) eva_start_time = time.time() result = [[[] for _ in range(len(ppp_seq))] for _ in range(total_budget)] for bud in range(1, total_budget + 1): for ppp in ppp_seq: ppp_strategy = 'random' * (ppp == 1) + 'expensive' * (ppp == 2) + 'cheap' * (ppp == 3) pps_start_time = time.time() eva_main = Evaluation(graph_dict, seed_cost_dict, product_list, ppp, wpiwp) iniW = IniWallet(dataset_name, product_name, wallet_distribution_type) wallet_list = iniW.getWalletList() personal_prob_list = eva_main.setPersonalPurchasingProbList(wallet_list) for sample_count, sample_seed_set in enumerate(seed_set_sequence[bud - 1]): if sample_seed_set != 0: print('@ evaluation @ dataset_name = ' + dataset_name + '_' + cascade_model + ', dist = ' + wallet_distribution_type + ', wpiwp = ' + str(wpiwp) + ', product_name = ' + product_name + ', budget = ' + str(bud) + ', ppp = ' + ppp_strategy + ', sample_count = ' + str(sample_count)) sample_pro_acc, sample_bud_acc = 0.0, 0.0 sample_sn_k_acc, sample_pnn_k_acc = [0.0 for _ in range(num_product)], [0 for _ in range(num_product)] sample_pro_k_acc, sample_bud_k_acc = [0.0 for _ in range(num_product)], [0.0 for _ in range(num_product)] for _ in range(eva_monte_carlo): pro, pro_k_list, pnn_k_list = eva_main.getSeedSetProfit(sample_seed_set, copy.deepcopy(wallet_list), copy.deepcopy(personal_prob_list)) sample_pro_acc += pro for kk in range(num_product): sample_pro_k_acc[kk] += pro_k_list[kk] sample_pnn_k_acc[kk] += pnn_k_list[kk] sample_pro_acc = round(sample_pro_acc / eva_monte_carlo, 4) for kk in range(num_product): sample_pro_k_acc[kk] = round(sample_pro_k_acc[kk] / eva_monte_carlo, 4) sample_pnn_k_acc[kk] = round(sample_pnn_k_acc[kk] / eva_monte_carlo, 2) sample_sn_k_acc[kk] = len(sample_seed_set[kk]) for sample_seed in sample_seed_set[kk]: sample_bud_acc = round(sample_bud_acc + seed_cost_dict[sample_seed], 2) sample_bud_k_acc[kk] = round(sample_bud_k_acc[kk] + seed_cost_dict[sample_seed], 2) result[bud - 1][ppp - 1].append([sample_pro_acc, sample_bud_acc, sample_sn_k_acc, sample_pnn_k_acc, sample_pro_k_acc, sample_bud_k_acc, sample_seed_set]) print('eva_time = ' + str(round(time.time() - eva_start_time, 2)) + 'sec') print(result[bud - 1][ppp - 1][sample_count]) print('------------------------------------------') else: result[bud - 1][ppp - 1].append(result[bud - 2][ppp - 1][sample_count]) avg_pro, avg_bud = 0.0, 0.0 avg_sn_k, avg_pnn_k = [0 for _ in range(num_product)], [0 for _ in range(num_product)] avg_pro_k, avg_bud_k = [0.0 for _ in range(num_product)], [0.0 for _ in range(num_product)] for r in result[bud - 1][ppp - 1]: avg_pro += r[0] avg_bud += r[1] for kk in range(num_product): avg_sn_k[kk] += r[2][kk] avg_pnn_k[kk] += r[3][kk] avg_pro_k[kk] += r[4][kk] avg_bud_k[kk] += r[5][kk] avg_pro = round(avg_pro / sample_number, 4) avg_bud = round(avg_bud / sample_number, 2) for kk in range(num_product): avg_sn_k[kk] = round(avg_sn_k[kk] / sample_number, 2) avg_pnn_k[kk] = round(avg_pnn_k[kk] / sample_number, 2) avg_pro_k[kk] = round(avg_pro_k[kk] / sample_number, 4) avg_bud_k[kk] = round(avg_bud_k[kk] / sample_number, 2) total_time = round(sum(ss_time_sequence[bud - 1]), 2) path1 = 'result/' + model_name + '_' + wallet_distribution_type + '_ppp' + str(ppp) + '_wpiwp' * wpiwp if not os.path.isdir(path1): os.mkdir(path1) path = path1 + '/' + dataset_name + '_' + cascade_model + '_' + product_name if not os.path.isdir(path): os.mkdir(path) fw = open(path + '/b' + str(bud) + '_i' + str(sample_number) + '.txt', 'w') fw.write(model_name + ', ppp = ' + str(ppp) + ', total_budget = ' + str(bud) + ', dist = ' + wallet_distribution_type + ', wpiwp = ' + str(wpiwp) + '\n' + 'dataset_name = ' + dataset_name + '_' + cascade_model + ', product_name = ' + product_name + '\n' + 'total_budget = ' + str(bud) + ', sample_count = ' + str(sample_number) + '\n' + 'avg_profit = ' + str(avg_pro) + ', avg_budget = ' + str(avg_bud) + '\n' + 'total_time = ' + str(total_time) + ', avg_time = ' + str(round(total_time / sample_number, 4)) + '\n') fw.write('\nprofit_ratio =') for kk in range(num_product): fw.write(' ' + str(avg_pro_k[kk])) fw.write('\nbudget_ratio =') for kk in range(num_product): fw.write(' ' + str(avg_bud_k[kk])) fw.write('\nseed_number =') for kk in range(num_product): fw.write(' ' + str(avg_sn_k[kk])) fw.write('\ncustomer_number =') for kk in range(num_product): fw.write(' ' + str(avg_pnn_k[kk])) fw.write('\n') for t, r in enumerate(result[bud - 1][ppp - 1]): fw.write('\n' + str(t) + '\t' + str(round(r[0], 4)) + '\t' + str(round(r[1], 4)) + '\t' + str(r[2]) + '\t' + str(r[3]) + '\t' + str(r[4]) + '\t' + str(r[5]) + '\t' + str(r[6])) fw.close()

[ "37822464+nmaypeter@users.noreply.github.com" ]

37822464+nmaypeter@users.noreply.github.com

a056f5ef70bc84e79e42928a38abb5e4257c531d

efde71fc3e296804a9e5cb6bc2ab48ad575b7faa

/applications/delivery/management/commands/processing_delivery_send_general.py

7cfebbccb447c1218e2618bf9fd5692286ff7bb2

[]

no_license

denispan1993/vitaliy

597cb546c9d1a14d7abc2931eb71fab38b878ec4

764d703ffc285f13a9f05e4c197bc75b495b5ff7

refs/heads/master

2021-04-29T21:54:45.095807

2018-02-10T19:05:23

121,627,169

0

null

UTF-8

Python

false

15,632

py

# -*- coding: utf-8 -*- __author__ = 'AlexStarov' from django.core.management.base import BaseCommand class Command(BaseCommand, ): from optparse import make_option option_list = BaseCommand.option_list + ( make_option('--id', '--pk', '--delivery_id', '--delivery_pk', action='store', type='int', dest='delivery_pk', help=''), make_option('--t', '--delivery_test', '--test', action='store_true', dest='delivery_test', help=''), make_option('--g', '--delivery_general', '--general', action='store_true', dest='delivery_test', help=''), ) #self.verbosity = int(options.get('verbosity')) #def add_arguments(self, parser): # parser.add_argument('delivery_id', nargs='+', type=int) def handle(self, *args, **options): from applications.delivery.models import Delivery try: deliveryes = Delivery.objects.filter(delivery_test=False, send_test=True, send_general=False, type__in=[1, 2, 3, ], ) except Delivery.DoesNotExist: deliveryes = None else: from applications.delivery.models import EmailMiddleDelivery for delivery in deliveryes: # print 'delivery', delivery try: EmailMiddleDelivery.objects.\ get(delivery=delivery, send_test=False, send_general=True, updated_at__lte=delivery.updated_at, ) except: """ Создаем ссылочку на отсылку рассылки """ email_middle_delivery = EmailMiddleDelivery() email_middle_delivery.delivery = delivery email_middle_delivery.delivery_test_send = False email_middle_delivery.delivery_send = True email_middle_delivery.save() """ Закрываем отсылку теста в самой рассылке """ delivery.send_general = True delivery.save() """ Отсылаем тестовое письмо """ from django.utils.html import strip_tags EMAIL_USE_TLS = True EMAIL_HOST = 'smtp.yandex.ru' EMAIL_PORT = 587 EMAIL_HOST_USER = 'subscribe@keksik.com.ua' EMAIL_HOST_PASSWORD = '' from django.core.mail import get_connection backend = get_connection(backend='django.core.mail.backends.smtp.EmailBackend', host=EMAIL_HOST, port=EMAIL_PORT, username=EMAIL_HOST_USER, password=EMAIL_HOST_PASSWORD, use_tls=EMAIL_USE_TLS, fail_silently=False, ) from django.core.mail import EmailMultiAlternatives from proj.settings import Email_MANAGER from applications.authModel.models import Email """ Создаем указатели на E-Mail адреса рассылки """ try: emails = Email.objects.filter(bad_email=False, ) except Email.DoesNotExist: emails = None """ Здесь нужно помудрить с коммитом """ from applications.delivery.models import EmailForDelivery from applications.delivery.utils import parsing i = 0 time = 0 for real_email in emails: i += 1 # if i < 125: # continue email = EmailForDelivery.objects.create(delivery=email_middle_delivery, email=real_email, ) """ Отсылка """ msg = EmailMultiAlternatives(subject=delivery.subject, body=strip_tags(parsing(value=delivery.html, key=email.key, ), ), from_email='subscribe@keksik.com.ua', to=[real_email.email, ], connection=backend, ) msg.attach_alternative(content=parsing(value=delivery.html, key=email.key, ), mimetype="text/html", ) msg.content_subtype = "html" try: msg.send(fail_silently=False, ) except Exception as e: msg = EmailMultiAlternatives(subject='Error for subject: %s' % delivery.subject, body='Error: %s - E-Mail: %s - real_email.pk: %d' % (e, real_email.email, real_email.pk, ), from_email='subscribe@keksik.com.ua', to=['subscribe@keksik.com.ua', ], connection=backend, ) msg.send(fail_silently=True, ) else: print 'i: ', i, 'Pk: ', real_email.pk, ' - ', real_email.email from random import randrange time1 = randrange(6, 12, ) time2 = randrange(6, 12, ) time += time1 + time2 print 'Time1: ', time1, ' Time2: ', time2, ' Time all: ', time1+time2, ' average time: ', time/i from time import sleep sleep(time1, ) print 'Next' sleep(time2, ) def hernya2(): try: deliveryes = Delivery.objects.filter(delivery_test=False, ) except Delivery.DoesNotExist: deliveryes = None else: for delivery in deliveryes: try: aaa=EmailMiddleDelivery.objects.\ get(delivery=delivery, updated_at__lte=delivery.updated_at, ) print aaa, delivery.updated_at except: email_middle_delivery = EmailMiddleDelivery() email_middle_delivery.delivery = delivery email_middle_delivery.delivery_test_send = False email_middle_delivery.delivery_send = True email_middle_delivery.save() from django.utils.html import strip_tags from django.core.mail import get_connection backend = get_connection(backend='django.core.mail.backends.smtp.EmailBackend', fail_silently=False, ) from django.core.mail import EmailMultiAlternatives from proj.settings import Email_MANAGER msg = EmailMultiAlternatives(subject=delivery.subject, body=strip_tags(delivery.html, ), from_email=u'site@keksik.com.ua', to=[real_email.email, ], connection=backend, ) msg.attach_alternative(content=delivery.html, mimetype="text/html", ) msg.content_subtype = "html" print real_email.email #try: # # msg.send(fail_silently=False, ) #except Exception as inst: # print type(inst, ) # print inst.args # print inst # else: # email.send # email.save() #try: # """ Берем 10 E-Mail адресов на которые мы еще не отсылали данную рассылку """ # emails = EmailForDelivery.objects.filter(delivery=email_middle_delivery, # send=False, )[10] #except EmailForDelivery.DoesNotExist: # """ E-Mail адреса в этой рассылке закончились """ # emails = None #else: # emails = ', '.join(emails, ) # """ Отсылаем E-Mail на 10 адресатов """ def hernya(): from datetime import datetime print datetime.now() from applications.product.models import Category try: action_category = Category.objects.get(url=u'акции', ) except Category.DoesNotExist: action_category = None from applications.discount.models import Action action_active = Action.objects.active() if action_active: print 'Action - ACTIVE:', action_active for action in action_active: products_of_action = action.product_in_action.all() print 'All products:', products_of_action # print action """ Если акция с автостартом, то мы еЁ стартуем. """ if action.auto_start: """ Включаем галочку 'Учавствует в акции' всем продуктам которые внесены в акцию исключая продукты 'отсутсвующие на складе' """ products_of_action = action.product_in_action.exclude(is_availability=4, ) if len(products_of_action, ) > 0: print 'Product auto_start:', products_of_action for product in products_of_action: """ Помечает товар как учавствующий в акции """ product.in_action = True """ Добавляем категорию 'Акция' в товар """ product.category.add(action_category, ) product.save() """ Удаляем товары учавствующие в активной акции но при этом 'отсутсвующие на складе' """ products_remove_from_action = action.product_in_action.exclude(is_availability__lt=4, ) if len(products_of_action, ) > 0: print 'Product auto_start:', products_of_action for product in products_remove_from_action: """ Помечает товар как учавствующий в акции """ product.in_action = False """ Добавляем категорию 'Акция' в товар """ product.category.remove(action_category, ) product.save() action_not_active = Action.objects.not_active() if action_not_active: print 'Action - NOT ACTIVE:', action_not_active for action in action_not_active: products_of_action = action.product_in_action.all() print 'All products:', products_of_action # print action """ Если акция с авто окончанием, то заканчиваем еЁ. """ if action.auto_end: products_of_action = action.product_in_action.in_action() if len(products_of_action, ) > 0: print 'Product auto_end:', products_of_action for product in products_of_action: print 'Del product from Action: ', product """ Помечает товар как не учавствующий в акции """ product.category.remove(action_category, ) product.in_action = False # """ # Меняем местами нынешнюю и акционные цены местами # """ # price = product.price # product.price = product.regular_price # if action.auto_del_action_price: # product.regular_price = 0 # else: # product.regular_price = price if action.auto_del_action_from_product: product.action.remove(action, ) product.save() if action.auto_del: action.deleted = True action.save() # from applications.product.models import Product # Product.objects.filter(is_availability=2, ).update(is_availability=5, ) # Product.objects.filter(is_availability=3, ).update(is_availability=2, ) # Product.objects.filter(is_availability=5, ).update(is_availability=3, ) """ Убираем галочку 'участвует в акции' всем продуктам у которых она почемуто установлена, но при этом отсутвует хоть какая то акция """ from applications.product.models import Product products = Product.objects.filter(in_action=True, action=None, ).update(in_action=False, ) print 'Товары удаленные из акции по причине вывода их из акции: ', products """ Убираем галочку 'участвует в акции' всем продуктам которые отсутсвуют на складе """ products = Product.objects.filter(in_action=True, is_availability=4, ).update(in_action=False, ) print 'Товары удаленные из акции по причине отсутсвия на складе: ', products """ Делаем активной акционную категорию, если есть хоть один акционный товар """ all_actions_products = action_category.products.all() if len(all_actions_products) != 0 and not action_category.is_active: action_category.is_active = True action_category.save() elif len(all_actions_products) == 0 and action_category.is_active: action_category.is_active = False action_category.save()

[ "alex.starov@gmail.com" ]

alex.starov@gmail.com

eea3d467d452081cbc8361a71b31783bd7c01f4d

3185bc3bf14cbcd06ff84b90deb56d5dd1557af0

/ptensor/include.py

b23c98b25fe219e46db53a37aac2fb2d22cc8b49

[]

no_license

vegaandagev/fPEPS

49ea1e910a14037b43b20c1be4e78e690aa9983f

bfb06082caae458b1b03e7586219a0f5413b7d14

refs/heads/master

2020-07-06T17:14:24.725570

2018-10-25T21:52:48

null

0

null

UTF-8

Python

false

91

py

import autograd np = autograd.numpy npeinsum = autograd.numpy.einsum dataType = np.float_

[ "zhendongli2008@gmail.com" ]

zhendongli2008@gmail.com

564a8dc4667af1a3fb616136ef6739ca876695e8

c9c94fcc33b25ebef73ce7c117ea20721a504701

/tests/spatial_operator/test_rectangle_knn.py

1f9a5b64d1da90b85cfa670891069534998dfa1b

[ "Apache-2.0" ]

permissive

Imbruced/geo_pyspark

46468cc95658fa156144246a45df32116d7ff20e

26da16d48168789c5f2bb75b5fdec1f515bf9cb1

refs/heads/master

2022-12-16T18:56:54.675038

2020-02-24T20:32:38

204,563,687

8

3

Apache-2.0

2022-12-08T03:32:18

2019-08-26T21:21:00

Python

UTF-8

Python

false

2,730

py

import os import pytest from shapely.geometry import Point from geo_pyspark.core.SpatialRDD import RectangleRDD from geo_pyspark.core.enums import IndexType, FileDataSplitter from geo_pyspark.core.geom_types import Envelope from geo_pyspark.core.spatialOperator import KNNQuery from tests.test_base import TestBase from tests.tools import tests_path, distance_sorting_functions inputLocation = os.path.join(tests_path, "resources/zcta510-small.csv") queryWindowSet = os.path.join(tests_path, "resources/zcta510-small.csv") offset = 0 splitter = FileDataSplitter.CSV gridType = "rtree" indexType = "rtree" numPartitions = 11 distance = 0.001 queryPolygonSet = os.path.join(tests_path, "resources/primaryroads-polygon.csv") inputCount = 3000 inputBoundary = Envelope(-171.090042, 145.830505, -14.373765, 49.00127) matchCount = 17599 matchWithOriginalDuplicatesCount = 17738 class TestRectangleKNN(TestBase): query_envelope = Envelope(-90.01, -80.01, 30.01, 40.01) loop_times = 5 query_point = Point(-84.01, 34.01) top_k = 100 def test_spatial_knn_query(self): rectangle_rdd = RectangleRDD(self.sc, inputLocation, offset, splitter, True) for i in range(self.loop_times): result = KNNQuery.SpatialKnnQuery(rectangle_rdd, self.query_point, self.top_k, False) assert result.__len__() > -1 assert result[0].getUserData() is not None def test_spatial_knn_query_using_index(self): rectangle_rdd = RectangleRDD(self.sc, inputLocation, offset, splitter, True) rectangle_rdd.buildIndex(IndexType.RTREE, False) for i in range(self.loop_times): result = KNNQuery.SpatialKnnQuery(rectangle_rdd, self.query_point, self.top_k, False) assert result.__len__() > -1 assert result[0].getUserData() is not None def test_spatial_knn_query_correctness(self): rectangle_rdd = RectangleRDD(self.sc, inputLocation, offset, splitter, True) result_no_index = KNNQuery.SpatialKnnQuery(rectangle_rdd, self.query_point, self.top_k, False) rectangle_rdd.buildIndex(IndexType.RTREE, False) result_with_index = KNNQuery.SpatialKnnQuery(rectangle_rdd, self.query_point, self.top_k, True) sorted_result_no_index = sorted(result_no_index, key=lambda geo_data: distance_sorting_functions( geo_data, self.query_point)) sorted_result_with_index = sorted(result_with_index, key=lambda geo_data: distance_sorting_functions( geo_data, self.query_point)) difference = 0 for x in range(self.top_k): difference += sorted_result_no_index[x].geom.distance(sorted_result_with_index[x].geom) assert difference == 0

[ "pawel93kocinski@gmail.com" ]

pawel93kocinski@gmail.com

c3b3b50d5ff7c5951e37fa4475abe2824058f619

140303e86eed46c9260da1a536077e884f809668

/phytoplankton_classification/resnet50_class.py

aacf1ae47286d7026a170749343aa47410706e50

[]

no_license

deephdc/phytoplankton-classification-theano

d0d9fae57ac20b2b6c716046e0bdc9e5386741b6

7e1da9a849fe137119182aa52bcd83c6325a3dac

refs/heads/master

2020-03-28T01:25:22.465535

2019-01-09T08:40:25

147,503,779

1

0

null

UTF-8

Python

false

11,660

py

""" Resnet50_class Author: Ignacio Heredia Date: October 2016 Description: Class for training a resnet50 for a new dataset by finetuning the weights already pretrained with ImageNet. """ import time import pickle import json import collections import inspect import os import sys import numpy as np import matplotlib.pyplot as plt import theano import theano.tensor as T import lasagne from plant_classification.data_utils import iterate_minibatches, data_augmentation from plant_classification.models.resnet50 import build_model theano.config.floatX = 'float32' class prediction_net(object): def __init__(self, output_dim=3680, lr=1e-3, lr_decay=0.1, lr_decay_rate=None, lr_decay_schedule=[0.7, 0.9], finetuning=1e-3, reg=1e-4, num_epochs=50, batchsize=32): """ Parameters ---------- output_dim : int output dimension (number of possible output classes) lr : float Base learning rate (1e-3 is the default for Adam update rule) lr_decay : float It's the ratio (new_lr / old_lr) lr_decay_rate : float, None Update the lr after this number of epochs lr_decay_schedule : list, numpy array, None Update at this % of training. Eg. [0.7,0.9] and 50 epochs --> update at epochs 35 and 45 This variable overwrites lr_decay_rate. finetuning : float Finetuning coefficient for learning the first layers Eg. layer_lr = finetuning * lr reg : float Regularization parameter num_epochs : int Number of epochs for training batchsize: int Size of each training batch (should fit in GPU) """ self.output_dim = output_dim self.lr_init = lr self.lr = theano.shared(np.float32(lr)) self.lr_decay = np.float32(lr_decay) if lr_decay_schedule is not None: self.lr_decay_schedule = (np.array(lr_decay_schedule) * num_epochs).astype(np.int) else: self.lr_decay_schedule = np.arange(0, num_epochs, lr_decay_rate)[1:].astype(np.int) self.reg = reg self.num_epochs = num_epochs self.batchsize = batchsize self.finetuning = finetuning def build_and_train(self, X_train, y_train, X_val=None, y_val=None, display=False, save_model=True, aug_params=None): """ Builds the model and runs the training loop. Parameters ---------- X_train : numpy array Training data y_train : numpy array Training targets. X_val : numpy array, None, optional Validation data y_val : numpy array, None, optional Validation targets Display : bool, optional Display on-fly plots of training and validation results. Save_model : bool, optional Save model weights. aug_params : dict, None, optional Dict containing the data augmentation parameters. Returns ------- Test function of the net. """ # ====================================================================== # Model compilation # ====================================================================== print("Building model and compiling functions...") # Create Theano variables for input and target minibatch input_var = T.tensor4('X', dtype=theano.config.floatX) # shape (batchsize,3,224,224) target_var = T.ivector('y') # shape (batchsize,) # Load model weights and metadata d = pickle.load(open(os.path.join(homedir, 'data', 'pretrained_weights', 'resnet50.pkl'))) # Build the network and fill with pretrained weights except for the last fc layer net = build_model(input_var, self.output_dim) lasagne.layers.set_all_param_values(net['pool5'], d['values'][:-2]) # create loss function and accuracy prediction = lasagne.layers.get_output(net['prob']) loss = lasagne.objectives.categorical_crossentropy(prediction, target_var) loss = loss.mean() + self.reg * lasagne.regularization.regularize_network_params( net['prob'], lasagne.regularization.l2) train_acc = T.mean(T.eq(T.argmax(prediction, axis=1), target_var), dtype=theano.config.floatX) # Create parameter update expressions with fine tuning updates = {} for name, layer in net.items(): layer_params = layer.get_params(trainable=True) if name == 'fc1000' or name == 'prob': layer_lr = self.lr else: layer_lr = self.lr * self.finetuning layer_updates = lasagne.updates.adam(loss, layer_params, learning_rate=layer_lr) updates.update(layer_updates) updates = collections.OrderedDict(updates) # Create a loss expression for validation/testing. test_prediction = lasagne.layers.get_output(net['prob'], deterministic=True) test_loss = lasagne.objectives.categorical_crossentropy(test_prediction, target_var) test_loss = test_loss.mean() test_acc = T.mean(T.eq(T.argmax(test_prediction, axis=1), target_var), dtype=theano.config.floatX) # Compile training and validation functions train_fn = theano.function([input_var, target_var], [loss, train_acc], updates=updates) val_fn = theano.function([input_var, target_var], [test_loss, test_acc]) test_fn = theano.function([input_var], test_prediction) # ====================================================================== # Training routine # ====================================================================== print("Starting training...") track = {'train_err': [], 'train_acc': [], 'val_err': [], 'val_acc': []} if display: fig, (ax1, ax2) = plt.subplots(1, 2) line1, = ax1.plot([], [], 'r-') line2, = ax2.plot([], [], 'r-') ax1.set_xlabel('Epochs') ax1.set_ylabel('Training loss') ax1.set_yscale('log') ax1.set_title('Training loss') ax2.set_xlabel('Epochs') ax2.set_ylabel('Validation loss') ax2.set_yscale('log') ax2.set_title('Validation loss') # Batchsize and augmentation parameters if aug_params is None: aug_params = {} train_batchsize = min(len(y_train), self.batchsize) train_aug_params = aug_params.copy() train_aug_params.update({'mode': 'standard'}) if X_val is not None: val_batchsize = min(len(y_val), self.batchsize) val_aug_params = aug_params.copy() val_aug_params.update({'mode': 'minimal', 'tags': None}) for epoch in range(self.num_epochs): start_time = time.time() # Learning rate schedule decay if epoch in self.lr_decay_schedule: self.lr.set_value(self.lr.get_value() * self.lr_decay) print('############# Leaning rate: {} ####################').format(self.lr.get_value()) # Full pass over training data train_err, train_batches = 0, 0 for batch in iterate_minibatches(X_train, y_train, train_batchsize, shuffle=True, **train_aug_params): inputs, targets = batch[0], batch[1] tmp_train_err, tmp_train_acc = train_fn(inputs, targets) track['train_err'].append(tmp_train_err) track['train_acc'].append(tmp_train_acc) train_err += tmp_train_err train_batches += 1 print 'Training epoch {} - {:.1f}% completed | Loss: {:.4f} ; Accuracy: {:.1f}%'.format(epoch, train_batches*self.batchsize*100./len(y_train), float(tmp_train_err), float(tmp_train_acc)*100) if np.isnan(train_err): print('Your net exploded, try decreasing the learning rate.') return None # Full pass over the validation data (if any) if X_val is not None: val_err, val_batches = 0, 0 for batch in iterate_minibatches(X_val, y_val, val_batchsize, shuffle=False, **val_aug_params): inputs, targets = batch[0], batch[1] tmp_val_err, tmp_val_acc = val_fn(inputs, targets) track['val_err'].append(tmp_val_err) track['val_acc'].append(tmp_val_acc) val_err += tmp_val_err val_batches += 1 print 'Validation epoch {} - {:.1f}% completed | Loss: {:.4f} ; Accuracy: {:.1f}%'.format(epoch, val_batches*self.batchsize*100./len(y_val), float(tmp_val_err), float(tmp_val_acc)*100) # Print the results for this epoch print("Epoch {} of {} took {:.3f}s".format(epoch + 1, self.num_epochs, time.time() - start_time)) print(" training loss:\t\t{:.6f}".format(train_err / train_batches)) if X_val is not None: print(" validation loss:\t\t{:.6f}".format(val_err / val_batches)) # Display training and validation accuracy in plot if display: line1.set_xdata(np.append(line1.get_xdata(), epoch)) line1.set_ydata(np.append(line1.get_ydata(), train_err / train_batches)) ax1.relim(), ax1.autoscale_view() if X_val is not None: line2.set_xdata(np.append(line2.get_xdata(), epoch)) line2.set_ydata(np.append(line2.get_ydata(), val_err / val_batches)) ax2.relim(), ax2.autoscale_view() fig.canvas.draw() # Save training information and net parameters print("Saving the model parameters and training information ...") train_info = {'training_params': {'output_dim': self.output_dim, 'lr_init': self.lr_init, 'lr_decay': float(self.lr_decay), 'lr_schedule': self.lr_decay_schedule.tolist(), 'reg': self.reg, 'num_epochs': self.num_epochs, 'batchsize': self.batchsize, 'finetuning': self.finetuning}} a = inspect.getargspec(data_augmentation) augmentation_params = dict(zip(a.args[-len(a.defaults):], a.defaults)) # default augmentation params augmentation_params.update(aug_params) # update with user's choice for k, v in augmentation_params.items(): if type(v) == np.ndarray: augmentation_params[k] = np.array(v).tolist() train_info.update({'augmentation_params': augmentation_params}) for k, v in track.items(): track[k] = np.array(v).tolist() train_info.update(track) if save_model: filename = 'resnet50_' + str(self.output_dim) + 'classes_' + str(self.num_epochs) + 'epochs' with open(os.path.join(homedir, 'plant_classification', 'training_info', filename + '.json'), 'w') as outfile: json.dump(train_info, outfile) np.savez(os.path.join(homedir, 'plant_classification', 'training_weights', filename + '.npz'), *lasagne.layers.get_all_param_values(net['prob'])) return test_fn

[ "lara.cern@gmail.com" ]

lara.cern@gmail.com

0cc4a2fbc3d553407bee5160d9a38847be8d9dd1

f3b233e5053e28fa95c549017bd75a30456eb50c

/bace_input/L3C/3C-7G_MD_NVT_rerun/set_7.py

0f46d20e708063854de9926a0271f971f5bca6db

[]

no_license

AnguseZhang/Input_TI

ddf2ed40ff1c0aa24eea3275b83d4d405b50b820

50ada0833890be9e261c967d00948f998313cb60

refs/heads/master

2021-05-25T15:02:38.858785

2020-02-18T16:57:04

null

0

null

UTF-8

Python

false

740

py

import os dir = '/mnt/scratch/songlin3/run/bace/L3C/MD_NVT_rerun/ti_one-step/3C_7G/' filesdir = dir + 'files/' temp_prodin = filesdir + 'temp_prod_7.in' temp_pbs = filesdir + 'temp_7.pbs' lambd = [ 0.00922, 0.04794, 0.11505, 0.20634, 0.31608, 0.43738, 0.56262, 0.68392, 0.79366, 0.88495, 0.95206, 0.99078] for j in lambd: os.chdir("%6.5f" %(j)) workdir = dir + "%6.5f" %(j) + '/' #prodin prodin = workdir + "%6.5f_prod_7.in" %(j) os.system("cp %s %s" %(temp_prodin, prodin)) os.system("sed -i 's/XXX/%6.5f/g' %s" %(j, prodin)) #PBS pbs = workdir + "%6.5f_7.pbs" %(j) os.system("cp %s %s" %(temp_pbs, pbs)) os.system("sed -i 's/XXX/%6.5f/g' %s" %(j, pbs)) #submit pbs #os.system("qsub %s" %(pbs)) os.chdir(dir)

[ "songlin3@msu.edu" ]

songlin3@msu.edu

e989e386a134506b91ae97587f771f0c11f17115

3fa8eead6e001c4d5a6dc5b1fd4c7b01d7693292

/ros_final_exam/src/path_exam/src/drone_takeoff.py

72614d2c3d72572785aac0f590f96c7dbe3cb835

[]

no_license

MarzanShuvo/Ros_from_the_construct

09261902841cdd832672658947790ec5fbba4cd3

4798234284d9d0bab3751e9d8ac2df95ae34a5bf

refs/heads/master

2023-08-24T17:28:09.182113

2021-10-23T07:57:02

339,105,075

0

null

UTF-8

Python

false

320

py

#! /usr/bin/env python import rospy from std_msgs.msg import Empty pub = rospy.Publisher('/drone/takeoff', Empty, queue_size=1) rospy.init_node('taking_off', anonymous=True) i=0 takeoff_msg = Empty() while not (i==3): rospy.loginfo("Taking off....... ") pub.publish(takeoff_msg) rospy.sleep(1) i +=1

[ "marzanalam3@gmail.com" ]

marzanalam3@gmail.com

4fc4e6b6c216cafeb53c0703782cfe3a9f1fdd53

730f89724aca038c15191f01d48e995cb94648bc

/entrances/migrations/0009_auto_20141110_1309.py

17928096718feb7f3db7ab280502d06f3d51621d

[]

no_license

Happyandhappy/django_email

14bc3f63376f2568754292708ec8ca7f2e2cf195

ea858c9fac79112542551b7ba6e899e348f24de3

refs/heads/master

2020-03-22T14:22:08.431334

2018-07-21T13:41:23

140,174,033

0

null

UTF-8

Python

false

699

py

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.db import models, migrations class Migration(migrations.Migration): dependencies = [ ('entrances', '0008_auto_20141110_1307'), ] operations = [ migrations.AddField( model_name='apartment', name='apartment_integer', field=models.IntegerField(null=True, editable=False, blank=True), preserve_default=True, ), migrations.AlterField( model_name='apartment', name='apartment', field=models.CharField(max_length=255, verbose_name='Apartment'), preserve_default=True, ), ]

[ "greyfrapp@gmail.com" ]

greyfrapp@gmail.com

4ee9e4930ad0c277ac82dc545653ba3ef880b7e6

8acffb8c4ddca5bfef910e58d3faa0e4de83fce8

/ml-flask/Lib/site-packages/sklearn/metrics/_scorer.py

4bc04f4d204ed29c114a974229d0a44f0ba6f1b8

[ "MIT" ]

permissive

YaminiHP/SimilitudeApp

8cbde52caec3c19d5fa73508fc005f38f79b8418

005c59894d8788c97be16ec420c0a43aaec99b80

refs/heads/master

2023-06-27T00:03:00.404080

2021-07-25T17:51:27

389,390,951

0

null

UTF-8

Python

false

130

py

version https://git-lfs.github.com/spec/v1 oid sha256:8f37b7f3b8da7123e4a98b2e1da0d724580dcc50f279d05bd2498a751b565c7c size 29542

[ "yamprakash130@gmail.com" ]

yamprakash130@gmail.com

7fe4fa0948b4b59a3b4f406c2ba089c3276a13f0

2e7bcb513d1ae368a7fa42fa41397b1e6f18ed80

/three.py

5d1b5ce84daee8af3f4f71806322b437c073f343

[]

no_license

Anjanaanjujsrr/anju-s-codekata

2826b3508a4e61a4f7d934bfdc7b626fa46b5fa1

f977392dd6c32e8256e2a9bb9ff873a2577e6a4f

refs/heads/master

2020-05-23T01:02:46.231105

2019-05-20T10:32:21

186,580,774

1

0

null

UTF-8

Python

false

72

py

x,y,z=input().split() x=int(x) y=int(y) z=int(z) print(max(x,y,z))

[ "noreply@github.com" ]

Anjanaanjujsrr.noreply@github.com

5078acc63f2d24dd99dc18787c02cd2665fb8670

48894ae68f0234e263d325470178d67ab313c73e

/sa/profiles/Alentis/NetPing/highlight.py

60164c4a96843307785a0cc7612ad8968ecfa497

[ "BSD-3-Clause" ]

permissive

DreamerDDL/noc

7f949f55bb2c02c15ac2cc46bc62d957aee43a86

2ab0ab7718bb7116da2c3953efd466757e11d9ce

refs/heads/master

2021-05-10T18:22:53.678588

2015-06-29T12:28:20

118,628,133

0

null

2018-01-23T15:19:51

null

UTF-8

Python

false

1,558

py

# -*- coding: utf-8 -*- ##---------------------------------------------------------------------- ## Alentis.NetPing highlight lexers ##---------------------------------------------------------------------- ## Copyright (C) 2007-2014 The NOC Project ## See LICENSE for details ##---------------------------------------------------------------------- from pygments.lexer import RegexLexer, bygroups, include from pygments.token import * class ConfigLexer(RegexLexer): name = "Alentis.NetPing" tokens = { "root": [ (r"^!.*", Comment), (r"(description)(.*?)$", bygroups(Keyword, Comment)), (r"(password|shared-secret|secret)(\s+[57]\s+)(\S+)", bygroups(Keyword, Number, String.Double)), (r"(ca trustpoint\s+)(\S+)", bygroups(Keyword, String.Double)), (r"^(interface|controller|router \S+|voice translation-\S+|voice-port)(.*?)$", bygroups(Keyword, Name.Attribute)), (r"^(dial-peer\s+\S+\s+)(\S+)(.*?)$", bygroups(Keyword, Name.Attribute, Keyword)), (r"^(vlan\s+)(\d+)$", bygroups(Keyword, Name.Attribute)), (r"(\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})(/\d{1,2})?", Number), # IPv4 Address/Prefix (r"49\.\d{4}\.\d{4}\.\d{4}\.\d{4}\.\d{2}", Number), # NSAP (r"(\s+[0-9a-f]{4}\.[0-9a-f]{4}\.[0-9a-f]{4}\s+)", Number), # MAC Address (r"^(?:no\s+)?\S+", Keyword), (r"\s+\d+\s+\d*|,\d+|-\d+", Number), (r".", Text) ] }

[ "dmitryluhtionov@gmail.com" ]

dmitryluhtionov@gmail.com

eadd7513a637a4fbfe75dbf5f146bd0eb9c4b2a3

e768a26a03283628ceccf98a021e9441101aae0c

/lstail/util/timestamp.py

937ec3dd3a7938b64cdc4058ff09eb367a7a4a9f

[ "MIT" ]

permissive

eht16/lstail

d8a4ecadf41b71c72bcc54ab59ce7229f7060d00

8fb61e9d07b05b27e3d45e988afe0c198010248d

refs/heads/master

2023-01-24T02:11:54.864001

2021-06-24T20:09:07

231,070,462

6

2

null

UTF-8

Python

false

1,881

py

# -*- coding: utf-8 -*- # # This software may be modified and distributed under the terms # of the MIT license. See the LICENSE file for details. from datetime import datetime, timedelta from lstail.constants import ELASTICSEARCH_TIMESTAMP_FORMATS from lstail.error import InvalidTimeRangeFormatError, InvalidTimestampFormatError # ---------------------------------------------------------------------- def parse_and_convert_time_range_to_start_date_time(time_range): error_message = 'Invalid time range specified: {}. ' \ 'Valid examples are: 60, 5m, 12h, 7d'.format(time_range) try: # try to parse the time range as integer, interpret the value as seconds seconds = value = int(time_range) except TypeError as exc_type: raise InvalidTimeRangeFormatError(error_message) from exc_type except ValueError as exc_value: try: suffix = time_range[-1] value = int(time_range[:-1]) except (ValueError, IndexError): raise InvalidTimeRangeFormatError(error_message) from exc_value if suffix == 'd': seconds = value * 86400 elif suffix == 'h': seconds = value * 3600 elif suffix == 'm': seconds = value * 60 else: raise InvalidTimeRangeFormatError(error_message) from exc_value if value < 0: raise InvalidTimeRangeFormatError(error_message) return datetime.now() - timedelta(seconds=seconds) # ---------------------------------------------------------------------- def parse_timestamp_from_elasticsearch(timestamp): for format_ in ELASTICSEARCH_TIMESTAMP_FORMATS: try: return datetime.strptime(timestamp, format_) except ValueError: continue # we didn't find any matching format, so cry raise InvalidTimestampFormatError(timestamp)

[ "enrico.troeger@uvena.de" ]

enrico.troeger@uvena.de

ded1616469cab5647a546b3d6712f5da6c57babf

0c3db34634cb85e778c95a4b4ff64514eca0477f

/lagtraj_aux/_version.py

3c268f304c8fbc69360ae05202fe04dfffbd8245

[]

no_license

EUREC4A-UK/lagtraj_aux

4efad4c94bcb9a2a367a6794abe0bc96e99a06af

da39ec1f6afa04a5a808130175b595c9bd9d01af

refs/heads/master

2023-03-05T17:06:14.938118

2021-02-09T12:17:51

2021-02-09T14:14:29

337,395,052

0

null

UTF-8

Python

false

18,685

py

# This file helps to compute a version number in source trees obtained from # git-archive tarball (such as those provided by githubs download-from-tag # feature). Distribution tarballs (built by setup.py sdist) and build # directories (produced by setup.py build) will contain a much shorter file # that just contains the computed version number. # This file is released into the public domain. Generated by # versioneer-0.19 (https://github.com/python-versioneer/python-versioneer) """Git implementation of _version.py.""" import errno import os import re import subprocess import sys def get_keywords(): """Get the keywords needed to look up the version information.""" # these strings will be replaced by git during git-archive. # setup.py/versioneer.py will grep for the variable names, so they must # each be defined on a line of their own. _version.py will just call # get_keywords(). git_refnames = "$Format:%d$" git_full = "$Format:%H$" git_date = "$Format:%ci$" keywords = {"refnames": git_refnames, "full": git_full, "date": git_date} return keywords class VersioneerConfig: """Container for Versioneer configuration parameters.""" def get_config(): """Create, populate and return the VersioneerConfig() object.""" # these strings are filled in when 'setup.py versioneer' creates # _version.py cfg = VersioneerConfig() cfg.VCS = "git" cfg.style = "pep440" cfg.tag_prefix = "" cfg.parentdir_prefix = "None" cfg.versionfile_source = "lagtraj_aux/_version.py" cfg.verbose = False return cfg class NotThisMethod(Exception): """Exception raised if a method is not valid for the current scenario.""" LONG_VERSION_PY = {} HANDLERS = {} def register_vcs_handler(vcs, method): # decorator """Create decorator to mark a method as the handler of a VCS.""" def decorate(f): """Store f in HANDLERS[vcs][method].""" if vcs not in HANDLERS: HANDLERS[vcs] = {} HANDLERS[vcs][method] = f return f return decorate def run_command(commands, args, cwd=None, verbose=False, hide_stderr=False, env=None): """Call the given command(s).""" assert isinstance(commands, list) p = None for c in commands: try: dispcmd = str([c] + args) # remember shell=False, so use git.cmd on windows, not just git p = subprocess.Popen( [c] + args, cwd=cwd, env=env, stdout=subprocess.PIPE, stderr=(subprocess.PIPE if hide_stderr else None), ) break except EnvironmentError: e = sys.exc_info()[1] if e.errno == errno.ENOENT: continue if verbose: print("unable to run %s" % dispcmd) print(e) return None, None else: if verbose: print("unable to find command, tried %s" % (commands,)) return None, None stdout = p.communicate()[0].strip().decode() if p.returncode != 0: if verbose: print("unable to run %s (error)" % dispcmd) print("stdout was %s" % stdout) return None, p.returncode return stdout, p.returncode def versions_from_parentdir(parentdir_prefix, root, verbose): """Try to determine the version from the parent directory name. Source tarballs conventionally unpack into a directory that includes both the project name and a version string. We will also support searching up two directory levels for an appropriately named parent directory """ rootdirs = [] for i in range(3): dirname = os.path.basename(root) if dirname.startswith(parentdir_prefix): return { "version": dirname[len(parentdir_prefix) :], "full-revisionid": None, "dirty": False, "error": None, "date": None, } else: rootdirs.append(root) root = os.path.dirname(root) # up a level if verbose: print( "Tried directories %s but none started with prefix %s" % (str(rootdirs), parentdir_prefix) ) raise NotThisMethod("rootdir doesn't start with parentdir_prefix") @register_vcs_handler("git", "get_keywords") def git_get_keywords(versionfile_abs): """Extract version information from the given file.""" # the code embedded in _version.py can just fetch the value of these # keywords. When used from setup.py, we don't want to import _version.py, # so we do it with a regexp instead. This function is not used from # _version.py. keywords = {} try: f = open(versionfile_abs, "r") for line in f.readlines(): if line.strip().startswith("git_refnames ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["refnames"] = mo.group(1) if line.strip().startswith("git_full ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["full"] = mo.group(1) if line.strip().startswith("git_date ="): mo = re.search(r'=\s*"(.*)"', line) if mo: keywords["date"] = mo.group(1) f.close() except EnvironmentError: pass return keywords @register_vcs_handler("git", "keywords") def git_versions_from_keywords(keywords, tag_prefix, verbose): """Get version information from git keywords.""" if not keywords: raise NotThisMethod("no keywords at all, weird") date = keywords.get("date") if date is not None: # Use only the last line. Previous lines may contain GPG signature # information. date = date.splitlines()[-1] # git-2.2.0 added "%cI", which expands to an ISO-8601 -compliant # datestamp. However we prefer "%ci" (which expands to an "ISO-8601 # -like" string, which we must then edit to make compliant), because # it's been around since git-1.5.3, and it's too difficult to # discover which version we're using, or to work around using an # older one. date = date.strip().replace(" ", "T", 1).replace(" ", "", 1) refnames = keywords["refnames"].strip() if refnames.startswith("$Format"): if verbose: print("keywords are unexpanded, not using") raise NotThisMethod("unexpanded keywords, not a git-archive tarball") refs = set([r.strip() for r in refnames.strip("()").split(",")]) # starting in git-1.8.3, tags are listed as "tag: foo-1.0" instead of # just "foo-1.0". If we see a "tag: " prefix, prefer those. TAG = "tag: " tags = set([r[len(TAG) :] for r in refs if r.startswith(TAG)]) if not tags: # Either we're using git < 1.8.3, or there really are no tags. We use # a heuristic: assume all version tags have a digit. The old git %d # expansion behaves like git log --decorate=short and strips out the # refs/heads/ and refs/tags/ prefixes that would let us distinguish # between branches and tags. By ignoring refnames without digits, we # filter out many common branch names like "release" and # "stabilization", as well as "HEAD" and "master". tags = set([r for r in refs if re.search(r"\d", r)]) if verbose: print("discarding '%s', no digits" % ",".join(refs - tags)) if verbose: print("likely tags: %s" % ",".join(sorted(tags))) for ref in sorted(tags): # sorting will prefer e.g. "2.0" over "2.0rc1" if ref.startswith(tag_prefix): r = ref[len(tag_prefix) :] if verbose: print("picking %s" % r) return { "version": r, "full-revisionid": keywords["full"].strip(), "dirty": False, "error": None, "date": date, } # no suitable tags, so version is "0+unknown", but full hex is still there if verbose: print("no suitable tags, using unknown + full revision id") return { "version": "0+unknown", "full-revisionid": keywords["full"].strip(), "dirty": False, "error": "no suitable tags", "date": None, } @register_vcs_handler("git", "pieces_from_vcs") def git_pieces_from_vcs(tag_prefix, root, verbose, run_command=run_command): """Get version from 'git describe' in the root of the source tree. This only gets called if the git-archive 'subst' keywords were *not* expanded, and _version.py hasn't already been rewritten with a short version string, meaning we're inside a checked out source tree. """ GITS = ["git"] if sys.platform == "win32": GITS = ["git.cmd", "git.exe"] out, rc = run_command(GITS, ["rev-parse", "--git-dir"], cwd=root, hide_stderr=True) if rc != 0: if verbose: print("Directory %s not under git control" % root) raise NotThisMethod("'git rev-parse --git-dir' returned error") # if there is a tag matching tag_prefix, this yields TAG-NUM-gHEX[-dirty] # if there isn't one, this yields HEX[-dirty] (no NUM) describe_out, rc = run_command( GITS, [ "describe", "--tags", "--dirty", "--always", "--long", "--match", "%s*" % tag_prefix, ], cwd=root, ) # --long was added in git-1.5.5 if describe_out is None: raise NotThisMethod("'git describe' failed") describe_out = describe_out.strip() full_out, rc = run_command(GITS, ["rev-parse", "HEAD"], cwd=root) if full_out is None: raise NotThisMethod("'git rev-parse' failed") full_out = full_out.strip() pieces = {} pieces["long"] = full_out pieces["short"] = full_out[:7] # maybe improved later pieces["error"] = None # parse describe_out. It will be like TAG-NUM-gHEX[-dirty] or HEX[-dirty] # TAG might have hyphens. git_describe = describe_out # look for -dirty suffix dirty = git_describe.endswith("-dirty") pieces["dirty"] = dirty if dirty: git_describe = git_describe[: git_describe.rindex("-dirty")] # now we have TAG-NUM-gHEX or HEX if "-" in git_describe: # TAG-NUM-gHEX mo = re.search(r"^(.+)-(\d+)-g([0-9a-f]+)$", git_describe) if not mo: # unparseable. Maybe git-describe is misbehaving? pieces["error"] = "unable to parse git-describe output: '%s'" % describe_out return pieces # tag full_tag = mo.group(1) if not full_tag.startswith(tag_prefix): if verbose: fmt = "tag '%s' doesn't start with prefix '%s'" print(fmt % (full_tag, tag_prefix)) pieces["error"] = "tag '%s' doesn't start with prefix '%s'" % ( full_tag, tag_prefix, ) return pieces pieces["closest-tag"] = full_tag[len(tag_prefix) :] # distance: number of commits since tag pieces["distance"] = int(mo.group(2)) # commit: short hex revision ID pieces["short"] = mo.group(3) else: # HEX: no tags pieces["closest-tag"] = None count_out, rc = run_command(GITS, ["rev-list", "HEAD", "--count"], cwd=root) pieces["distance"] = int(count_out) # total number of commits # commit date: see ISO-8601 comment in git_versions_from_keywords() date = run_command(GITS, ["show", "-s", "--format=%ci", "HEAD"], cwd=root)[ 0 ].strip() # Use only the last line. Previous lines may contain GPG signature # information. date = date.splitlines()[-1] pieces["date"] = date.strip().replace(" ", "T", 1).replace(" ", "", 1) return pieces def plus_or_dot(pieces): """Return a + if we don't already have one, else return a .""" if "+" in pieces.get("closest-tag", ""): return "." return "+" def render_pep440(pieces): """Build up version string, with post-release "local version identifier". Our goal: TAG[+DISTANCE.gHEX[.dirty]] . Note that if you get a tagged build and then dirty it, you'll get TAG+0.gHEX.dirty Exceptions: 1: no tags. git_describe was just HEX. 0+untagged.DISTANCE.gHEX[.dirty] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += plus_or_dot(pieces) rendered += "%d.g%s" % (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" else: # exception #1 rendered = "0+untagged.%d.g%s" % (pieces["distance"], pieces["short"]) if pieces["dirty"]: rendered += ".dirty" return rendered def render_pep440_pre(pieces): """TAG[.post0.devDISTANCE] -- No -dirty. Exceptions: 1: no tags. 0.post0.devDISTANCE """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += ".post0.dev%d" % pieces["distance"] else: # exception #1 rendered = "0.post0.dev%d" % pieces["distance"] return rendered def render_pep440_post(pieces): """TAG[.postDISTANCE[.dev0]+gHEX] . The ".dev0" means dirty. Note that .dev0 sorts backwards (a dirty tree will appear "older" than the corresponding clean one), but you shouldn't be releasing software with -dirty anyways. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += plus_or_dot(pieces) rendered += "g%s" % pieces["short"] else: # exception #1 rendered = "0.post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" rendered += "+g%s" % pieces["short"] return rendered def render_pep440_old(pieces): """TAG[.postDISTANCE[.dev0]] . The ".dev0" means dirty. Exceptions: 1: no tags. 0.postDISTANCE[.dev0] """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"] or pieces["dirty"]: rendered += ".post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" else: # exception #1 rendered = "0.post%d" % pieces["distance"] if pieces["dirty"]: rendered += ".dev0" return rendered def render_git_describe(pieces): """TAG[-DISTANCE-gHEX][-dirty]. Like 'git describe --tags --dirty --always'. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] if pieces["distance"]: rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render_git_describe_long(pieces): """TAG-DISTANCE-gHEX[-dirty]. Like 'git describe --tags --dirty --always -long'. The distance/hash is unconditional. Exceptions: 1: no tags. HEX[-dirty] (note: no 'g' prefix) """ if pieces["closest-tag"]: rendered = pieces["closest-tag"] rendered += "-%d-g%s" % (pieces["distance"], pieces["short"]) else: # exception #1 rendered = pieces["short"] if pieces["dirty"]: rendered += "-dirty" return rendered def render(pieces, style): """Render the given version pieces into the requested style.""" if pieces["error"]: return { "version": "unknown", "full-revisionid": pieces.get("long"), "dirty": None, "error": pieces["error"], "date": None, } if not style or style == "default": style = "pep440" # the default if style == "pep440": rendered = render_pep440(pieces) elif style == "pep440-pre": rendered = render_pep440_pre(pieces) elif style == "pep440-post": rendered = render_pep440_post(pieces) elif style == "pep440-old": rendered = render_pep440_old(pieces) elif style == "git-describe": rendered = render_git_describe(pieces) elif style == "git-describe-long": rendered = render_git_describe_long(pieces) else: raise ValueError("unknown style '%s'" % style) return { "version": rendered, "full-revisionid": pieces["long"], "dirty": pieces["dirty"], "error": None, "date": pieces.get("date"), } def get_versions(): """Get version information or return default if unable to do so.""" # I am in _version.py, which lives at ROOT/VERSIONFILE_SOURCE. If we have # __file__, we can work backwards from there to the root. Some # py2exe/bbfreeze/non-CPython implementations don't do __file__, in which # case we can only use expanded keywords. cfg = get_config() verbose = cfg.verbose try: return git_versions_from_keywords(get_keywords(), cfg.tag_prefix, verbose) except NotThisMethod: pass try: root = os.path.realpath(__file__) # versionfile_source is the relative path from the top of the source # tree (where the .git directory might live) to this file. Invert # this to find the root from __file__. for i in cfg.versionfile_source.split("/"): root = os.path.dirname(root) except NameError: return { "version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to find root of source tree", "date": None, } try: pieces = git_pieces_from_vcs(cfg.tag_prefix, root, verbose) return render(pieces, cfg.style) except NotThisMethod: pass try: if cfg.parentdir_prefix: return versions_from_parentdir(cfg.parentdir_prefix, root, verbose) except NotThisMethod: pass return { "version": "0+unknown", "full-revisionid": None, "dirty": None, "error": "unable to compute version", "date": None, }

[ "leif@denby.eu" ]

leif@denby.eu

21b40d08fed1635c5fe1d8ce52d30d0da90e50af

786de89be635eb21295070a6a3452f3a7fe6712c

/pyana_examples/tags/V00-00-22/src/myana_epics.py

43a50ac4ee210d95837b5b08f3fe499855f1f31f

[]

no_license

connectthefuture/psdmrepo

85267cfe8d54564f99e17035efe931077c8f7a37

f32870a987a7493e7bf0f0a5c1712a5a030ef199

refs/heads/master

2021-01-13T03:26:35.494026

2015-09-03T22:22:11

null

0

null

UTF-8

Python

false

3,275

py

#-------------------------------------------------------------------------- # File and Version Information: # $Id$ # # Description: # Pyana user analysis module myana_epics... # #------------------------------------------------------------------------ """User analysis module for pyana framework. This software was developed for the LCLS project. If you use all or part of it, please give an appropriate acknowledgment. @see RelatedModule @version $Id$ @author Andrei Salnikov """ #------------------------------ # Module's version from SVN -- #------------------------------ __version__ = "$Revision$" # $Source$ #-------------------------------- # Imports of standard modules -- #-------------------------------- import sys import logging #----------------------------- # Imports for other modules -- #----------------------------- #---------------------------------- # Local non-exported definitions -- #---------------------------------- # local definitions usually start with _ #--------------------- # Class definition -- #--------------------- class myana_epics (object) : """Example analysis module which accesses EPICS data. """ #---------------- # Constructor -- #---------------- def __init__ ( self, pv = "BEAM:LCLS:ELEC:Q") : """Class constructor. The parameters to the constructor are passed from pyana configuration file. If parameters do not have default values here then the must be defined in pyana.cfg. All parameters are passed as strings, convert to correct type before use. @param pv Name of the EPICS PV to dump """ self.m_pv = pv #------------------- # Public methods -- #------------------- def beginjob( self, evt, env ) : # Preferred way to log information is via logging package logging.info( "myana_epics.beginjob() called" ) # Use environment object to access EPICS data pv = env.epicsStore().value(self.m_pv) if not pv: logging.warning('EPICS PV %s does not exist', self.m_pv) else: # Returned value should be of the type epics.EpicsPvCtrl. # The code here demonstrates few members accessible for that type. # For full list of members see Pyana Ref. Manual. print "PV %s: id=%d type=%d size=%d status=%s severity=%s values=%s" % \ (self.m_pv, pv.iPvId, pv.iDbrType, pv.iNumElements, pv.status, pv.severity, pv.values) def event( self, evt, env ) : # Use environment object to access EPICS data pv = env.epicsStore().value(self.m_pv) if not pv: logging.warning('EPICS PV %s does not exist', self.m_pv) else: # Returned value should be of the type epics.EpicsPvTime. # The code here demonstrates few members accessible for that type. # For full list of members see Pyana Ref. Manual. print "PV %s: id=%d type=%d size=%d status=%s severity=%s values=%s stamp=%s" % \ (self.m_pv, pv.iPvId, pv.iDbrType, pv.iNumElements, pv.status, pv.severity, pv.values, pv.stamp) def endjob( self, env ) : pass

[ "salnikov@SLAC.STANFORD.EDU@b967ad99-d558-0410-b138-e0f6c56caec7" ]

salnikov@SLAC.STANFORD.EDU@b967ad99-d558-0410-b138-e0f6c56caec7

2493c1cc3a4b0fe3b2854c9e23fc45bfface1968

d50f50f455a2f96e7fbd9fb76fcdcdd71b8cc27c

/Day-23/Day23_Shahazada(ST).py

c48889980ab7f74e9d0a9c64863664893954a65a

[]

no_license

Rushi21-kesh/30DayOfPython

9b2cc734c553b81d98593031a334b9a556640656

d9741081716c3cf67823e2acf37f015b5906b913

refs/heads/main

2023-06-29T13:18:09.635799

2021-07-30T13:33:04

384,316,331

1

0

null

2021-07-09T04:01:24

2021-07-09T04:01:23

null

UTF-8

Python

false

695

py

'''This program rotate list cyclically by user choice''' if __name__ == '__main__': n=int(input("Enter the size of list:- ")) print("Enter element of list") elementList=[] for i in range(n): ele=int(input()) elementList.append(ele) rotatedlist=[] rotateBy=int(input("By how many element want to rotate:- ")) for i in range(n-1,n-rotateBy-1,-1): rotatedlist.append(elementList[i]) for i in range(n-rotateBy): rotatedlist.append(elementList[i]) print() print("Rotated cyclically list element are :-",end=" ") for i in range(n): print(rotatedlist[i],end=" ")

[ "noreply@github.com" ]

Rushi21-kesh.noreply@github.com

eca0c55b107bd3d4779cf6d82077c32e6d204a7c

d7d524d1c0ba1cf62cdbc2f9bf5b9c66fa56726b

/47high.py

7e7773c0544de60d34e249dd843254966da9d18b

[]

no_license

ramyasutraye/pythonproject

d997ca5ada024e211b6bf087d0d56684daf9df8b

38975a99eb3ee1ad9e79a9efd538cc992d249fc3

refs/heads/master

2020-04-23T19:30:10.128774

2018-05-25T06:18:53

null

0

null

UTF-8

Python

false

136

py

n=int(input("enter the number:")) a=[] for i in range(0,n): b=int(input("Enter number:")) a.append(b) a.sort() print(min(a),max(a))

[ "noreply@github.com" ]

ramyasutraye.noreply@github.com

e0a183e93aadcfada6ef5a4998601ae0e7797837

6f9a5717fed38b0a79c399f7e5da55c6a461de6d

/Baekjoon/CardPurchase.py

9a394075fa2e93607643af50ef1def9dbd576b48

[]

no_license

Alfred-Walker/pythonps

d4d3b0f7fe93c138d02651e05ca5165825676a5e

81ef8c712c36aa83d1c53aa50886eb845378d035

refs/heads/master

2022-04-16T21:34:39.316565

2020-04-10T07:50:46

254,570,527

1

null

UTF-8

Python

false

2,845

py

# 요즘 민규네 동네에서는 스타트링크에서 만든 PS카드를 모으는 것이 유행이다. # # PS카드는 PS(Problem Solving)분야에서 유명한 사람들의 아이디와 얼굴이 적혀있는 카드이다. # 각각의 카드에는 등급을 나타내는 색이 칠해져 있고, 다음과 같이 8가지가 있다. # # 전설카드 # 레드카드 # 오렌지카드 # 퍼플카드 # 블루카드 # 청록카드 # 그린카드 # 그레이카드 # 카드는 카드팩의 형태로만 구매할 수 있고, 카드팩의 종류는 카드 # 1개가 포함된 카드팩, 카드 2개가 포함된 카드팩, ... 카드 N개가 포함된 카드팩 # 과 같이 총 N가지가 존재한다. # # 민규는 카드의 개수가 적은 팩이더라도 가격이 비싸면 높은 등급의 카드가 많이 들어있을 것이라는 미신을 믿고 있다. # 따라서, 민규는 돈을 최대한 많이 지불해서 카드 N개 구매하려고 한다. 카드가 i개 포함된 카드팩의 가격은 Pi원이다. # # 예를 들어, 카드팩이 총 4가지 종류가 있고, P1 = 1, P2 = 5, P3 = 6, P4 = 7인 경우에 # 민규가 카드 4개를 갖기 위해 지불해야 하는 금액의 최댓값은 10원이다. 2개 들어있는 카드팩을 2번 사면 된다. # # P1 = 5, P2 = 2, P3 = 8, P4 = 10인 경우에는 # 카드가 1개 들어있는 카드팩을 4번 사면 20원이고, 이 경우가 민규가 지불해야 하는 금액의 최댓값이다. # # 마지막으로, P1 = 3, P2 = 5, P3 = 15, P4 = 16인 경우에는 # 3개 들어있는 카드팩과 1개 들어있는 카드팩을 구매해 18원을 지불하는 것이 최댓값이다. # # 카드 팩의 가격이 주어졌을 때, N개의 카드를 구매하기 위해 민규가 지불해야 하는 금액의 최댓값을 구하는 프로그램을 작성하시오. # N개보다 많은 개수의 카드를 산 다음, 나머지 카드를 버려서 N개를 만드는 것은 불가능하다. # 즉, 구매한 카드팩에 포함되어 있는 카드 개수의 합은 N과 같아야 한다. # # 입력 # 첫째 줄에 민규가 구매하려고 하는 카드의 개수 N이 주어진다. (1 ≤ N ≤ 1,000) # 둘째 줄에는 Pi가 P1부터 PN까지 순서대로 주어진다. (1 ≤ Pi ≤ 10,000) # # 출력 # 첫째 줄에 민규가 카드 N개를 갖기 위해 지불해야 하는 금액의 최댓값을 출력한다. import sys N = int(sys.stdin.readline().rstrip()) # 구입할 카드의 개수 P = [0] + list(map(int, sys.stdin.readline().rstrip().split())) # 편의상 0 추가 dp = dict() # dp[i]: 카드를 i개 갖기 위해 지불한 금액의 최댓값 dp[0] = 0 for i in range(1, N+1): dp[i] = 0 for j in range(1, i + 1): dp[i] = max(dp[i], dp[i - j] + P[j]) # j번째 카드팩에 대하여, dp[i] = dp[i-j] + P[j] print(dp[N])

[ "studio.alfred.walker@gmail.com" ]

studio.alfred.walker@gmail.com

97952047d650f3e84518e6583fe08909eb2da9a6

9ac19e6733e1f91bb9cb0fe47967491a5e856040

/test/test_revoke.py

8c0a82737e93f456dc810b7cc587fccd0bb78a27

[ "MIT" ]

permissive

DS4SD/project-mognet

7898b41046a31b82052b1424e6910cb65b14e5c5

9e415e88404da0a0eab3b379d6cd7b7d15ca71a6

refs/heads/main

2023-05-23T22:02:10.406590

2022-07-13T11:53:28

474,094,219

5

1

MIT

2022-07-13T11:53:29

2022-03-25T16:55:53

Python

UTF-8

Python

false

1,402

py

import asyncio import uuid from mognet.model.result import ResultFailed from mognet.model.result_state import ResultState import pytest from mognet import App, Request, Context, task @pytest.mark.asyncio async def test_revoke(test_app: App): req = Request(name="test.sleep", args=(10,)) await test_app.submit(req) await asyncio.sleep(2) await test_app.revoke(req.id) res = await test_app.result_backend.get(req.id) assert res is not None assert res.state == ResultState.REVOKED assert res.revoked with pytest.raises(ResultFailed): await res @task(name="test.recurses_after_wait") async def recurses_after_wait(context: Context, child_id: uuid.UUID): req = Request(name="test.add", id=child_id, args=(1, 2)) try: await asyncio.sleep(5) finally: await context.submit(req) @pytest.mark.asyncio async def test_revokes_children_if_parent_revoked(test_app: App): child_id = uuid.uuid4() req = Request(name="test.recurses_after_wait", args=(child_id,)) await test_app.submit(req) await asyncio.sleep(1) await test_app.revoke(req.id) await asyncio.sleep(1) child_res = await test_app.result_backend.get(child_id) assert child_res is not None assert child_res.state == ResultState.REVOKED assert child_res.revoked with pytest.raises(ResultFailed): await child_res

[ "dol@zurich.ibm.com" ]

dol@zurich.ibm.com

9c26d10ade54eaa70dce931bd5513bb7e4b1f601

1b5802806cdf2c3b6f57a7b826c3e064aac51d98

/tensorrt-basic-1.10-3rd-plugin/TensorRT-main/demo/HuggingFace/NNDF/general_utils.py

64717b1eb53c28be3c1809bc124766cc218189cd

[ "MIT", "BSD-3-Clause", "Apache-2.0", "ISC", "BSD-2-Clause" ]

permissive

jinmin527/learning-cuda-trt

def70b3b1b23b421ab7844237ce39ca1f176b297

81438d602344c977ef3cab71bd04995c1834e51c

refs/heads/main

2023-05-23T08:56:09.205628

2022-07-24T02:48:24

517,213,903

36

18

null

2022-07-24T03:05:05

null

UTF-8

Python

false

6,519

py

# # Copyright (c) 2021, NVIDIA CORPORATION. All rights reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # """Common utils used by demo folder.""" import os import shutil import timeit from shutil import rmtree from typing import Callable, Union, List from collections import defaultdict from statistics import mean, median from glob import glob # NNDF from NNDF.networks import NNConfig, NetworkResult, NetworkMetadata from NNDF.logger import G_LOGGER # Used for HuggingFace setting random seed RANDOM_SEED = 42 # Networks # def register_network_folders( root_dir: str, config_file_str: str = "*Config.py" ) -> List[str]: networks = [] for network_configs in glob(os.path.join(root_dir, "*", config_file_str)): network_name = os.path.split(os.path.split(network_configs)[0])[1] networks.append(network_name) return networks def process_results(category: List[str], results: List[NetworkResult], nconfig: NNConfig): """ Calculate and process results across multiple runs. """ general_stats = ["script", "accuracy"] runtime_result_row_names = list(nconfig.NETWORK_SEGMENTS) if nconfig.NETWORK_FULL_NAME not in nconfig.NETWORK_SEGMENTS: runtime_result_row_names.append(nconfig.NETWORK_FULL_NAME) rows = [] row_entry = [] for cat, result in zip(category, results): # Process runtime results for each group runtime_results = defaultdict(list) for runtimes in [nr.median_runtime for nr in result.network_results]: for runtime in runtimes: runtime_results[runtime.name].append(runtime.runtime) # Calculate average runtime for each group average_group_runtime = {k: mean(v) for k, v in runtime_results.items()} row_entry = [cat, result.accuracy] + [ average_group_runtime[n] for n in runtime_result_row_names ] rows.append(row_entry) headers = general_stats + [r + " (sec)" for r in runtime_result_row_names] return headers, rows def process_per_result_entries(script_category: List[str], results: List[NetworkResult], max_output_char:int = 30): """Prints tabulations for each entry returned by the runtime result.""" def _shorten_text(w): l = len(w) if l > max_output_char: return w[0:max_output_char // 2] + " ... " + w[-max_output_char//2:] return w headers = ["script", "network_part", "accuracy", "runtime", "input", "output"] row_data_by_input = defaultdict(list) for cat, result in zip(script_category, results): for nr in result.network_results: for runtime in nr.median_runtime: row_data_by_input[hash(nr.input)].append([ cat, runtime.name, result.accuracy, runtime.runtime, _shorten_text(nr.input), _shorten_text(nr.semantic_output) ]) return headers, dict(row_data_by_input) # IO # def confirm_folder_delete( fpath: str, prompt: str = "Confirm you want to delete entire folder?" ) -> None: """ Confirms whether or not user wants to delete given folder path. Args: fpath (str): Path to folder. prompt (str): Prompt to display Returns: None """ msg = prompt + " {} [Y/n] ".format(fpath) confirm = input(msg) if confirm == "Y": rmtree(fpath) else: G_LOGGER.info("Skipping file removal.") def remove_if_empty( fpath: str, success_msg: str = "Folder successfully removed.", error_msg: str = "Folder cannot be removed, there are files.", ) -> None: """ Removes an entire folder if folder is empty. Provides print info statements. Args: fpath: Location to folder success_msg: Success message. error_msg: Error message. Returns: None """ if len(os.listdir(fpath)) == 0: os.rmdir(fpath) G_LOGGER.info(success_msg + " {}".format(fpath)) else: G_LOGGER.info(error_msg + " {}".format(fpath)) def measure_python_inference_code( stmt: Union[Callable, str], warmup: int = 3, number: int = 10, iterations: int = 10 ) -> None: """ Measures the time it takes to run Pythonic inference code. Statement given should be the actual model inference like forward() in torch. See timeit for more details on how stmt works. Args: stmt (Union[Callable, str]): Callable or string for generating numbers. number (int): Number of times to call function per iteration. iterations (int): Number of measurement cycles. """ G_LOGGER.debug( "Measuring inference call with warmup: {} and number: {} and iterations {}".format( warmup, number, iterations ) ) # Warmup warmup_mintime = timeit.repeat(stmt, number=number, repeat=warmup) G_LOGGER.debug("Warmup times: {}".format(warmup_mintime)) return median(timeit.repeat(stmt, number=number, repeat=iterations)) / number class NNFolderWorkspace: """ For keeping track of workspace folder and for cleaning them up. Due to potential corruption of ONNX model conversion, the workspace is split up by model variants. """ def __init__( self, network_name: str, metadata: NetworkMetadata, working_directory: str ): self.rootdir = working_directory self.metadata = metadata self.network_name = network_name self.dpath = os.path.join(self.rootdir, self.network_name, metadata.variant) os.makedirs(self.dpath, exist_ok=True) def get_path(self) -> str: return self.dpath def cleanup(self, force_remove: bool = False) -> None: fpath = self.get_path() if force_remove: return shutil.rmtree(fpath) remove_if_empty( fpath, success_msg="Sucessfully removed workspace.", error_msg="Unable to remove workspace.", )

[ "dujw@deepblueai.com" ]

dujw@deepblueai.com

a202a75b98c1863c08432cd4589d7efbb80bd7d9

5e95083d63ce1e76385dd34c96c13c7ac382aa28

/Длина последовательности.py

c6500972c5eedee2ad6a125ce06bac0785b77950

[]

no_license

oOoSanyokoOo/Course-Python-Programming-Basics

1ee3bff98259951d87d8656af1519884fb089f41

88a8ada069da45a882942ef83dd3d3bcb9cb3b0d

refs/heads/main

2023-06-14T20:57:25.347205

2021-07-08T07:09:20

384,029,659

1

0

null

UTF-8

Python

false

95

py

i = 0 while True: n = int(input()) if n == 0: break i += 1 print(i)

[ "noreply@github.com" ]

oOoSanyokoOo.noreply@github.com

056c67711ce448d1738be23298e3ca357a3e5980

6800da49fb74cbc0079d3106762122ea102562be

/channel_manager.py

a7711d6079828cd8d5634f7a70a045f8e2856764

[]

no_license

legoktm/adminbots

8f9e03eb2002addf0e0589d627202cd977bafd7e

0b0a913c8b1ad3d92b77d6352660a05af54f5e06

refs/heads/master

2016-09-05T19:17:30.683600

2013-11-21T01:51:20

10,352,998

1

0

null

UTF-8

Python

false

903

py

# -*- coding: utf-8 -*- # (C) Legoktm, 2013 # Licensed under the MIT License # Assists with joining/parting channels import os import yaml from mtirc import hooks filename = os.path.expanduser('~/channels.yml') def get_channel_list(): with open(filename) as f: raw = f.read() data = yaml.load(raw) return data def on_connect(**kw): data = get_channel_list() if kw['server'] in data: for channel in data[kw['server']]: kw['bot'].servers[kw['server']].join(channel) def on_msg(**kw): if kw['text'] == '!reload channels': data = get_channel_list() for server in data: if server in kw['bot'].servers: for channel in data[server]: kw['bot'].servers[server].join(channel) hooks.add_hook('connected', 'channel_joiner', on_connect) hooks.add_hook('on_msg', 'channel_reloader', on_msg)

[ "legoktm@gmail.com" ]

legoktm@gmail.com

da01bc57ce96ce7a637d80966352e5dd5539954c

b2ff7365dda9fa9290c2eae04988e3bda9cae23a

/13_top_k/8.py

74578e1adccfe804dc3394e7b47b49305637cb5f

[]

no_license

terrifyzhao/educative3

cd6ccdb0fc4b9ba7f5058fe2e3d2707f022d8b16

5c7db9ef6cf58ca5e68bb5aec8ed95af1d5c0f47

refs/heads/master

2022-12-26T23:53:30.645339

2020-10-10T00:48:22

298,991,655

0

null

UTF-8

Python

false

637

py

from heapq import * def find_closest_elements(arr, K, X): result = [] min_heap = [] for i in range(len(arr)): heappush(min_heap, [abs(arr[i] - X), i]) for i in range(K): index = heappop(min_heap)[1] result.append(arr[index]) return result def main(): print("'K' closest numbers to 'X' are: " + str(find_closest_elements([5, 6, 7, 8, 9], 3, 7))) print("'K' closest numbers to 'X' are: " + str(find_closest_elements([2, 4, 5, 6, 9], 3, 6))) print("'K' closest numbers to 'X' are: " + str(find_closest_elements([2, 4, 5, 6, 9], 3, 10))) main()

[ "zjiuzhou@gmail.com" ]

zjiuzhou@gmail.com

aaacb65e368ef4189378c6a8e678963699b64664

8b8351c8d0431a95d2e1ad88a1ef42470ff6f66c

/python/exceptions_hierarchy.py

d02f55310a599e914c6972c208f5bba08b75fd07

[]

no_license

miso-belica/playground

2d771197cca8d8a0031466c97317bfa38bb2faff

6c68f648301801785db8b3b26cb3f31b782389ec

refs/heads/main

2022-11-29T09:17:24.661966

2022-11-23T22:19:50

2022-11-24T07:20:13

30,124,960

14

8

null

2022-11-24T07:20:14

2015-01-31T20:18:53

Python

UTF-8

Python

false

386

py

# -*- coding: utf-8 -*- import sys import time if __name__ == "__main__": try: # time.sleep(5) # sys.exit(1) raise ValueError("value") except Exception as e: print("Catched ValueError!", e) try: sys.exit(1) except Exception: print("Catched exit by Exception.") except: print("Catched exit by empty except")

[ "miso.belica@gmail.com" ]

miso.belica@gmail.com

40bb5c70b623f899a77f7317d99cbb2312d64a19

086ece6952b56602c20709bfa219037b0375ab0c

/ENGLISH_DETECTION.py

085150b7a9dbb3fd571fb2f0c15a3e22448c73fd

[]

no_license

pseudo11235813/Random-Python-Ciphers

71aca8561b003ab8818e4d934288aef8d2779e9c

48f04b2e6a32ea67a2bc88d0bb283a51fd5150e5

refs/heads/master

2022-12-20T03:53:04.643760

2020-09-21T19:16:41

null

0

null

UTF-8

Python

false

2,508

py

#Self-dev English Detector module #you need to download an English dictionary Text File to use this module #go to google or any search engine and download an English Dictionary File #a one you can use : #import eng #eng.isEnglish(message) ; will return false or true. #eng.DictLoader() ; will ask you for a the English dictionary file name then returns a dictionary that contains all the words in that dictionary file. #eng.countWords() ; will return the percentage of English words in the entered text . #eng.englishWords() ; will return the english words in the entered text in a list. Englishletters = "abcdefghijklmnopqrstuvwxyz" fullEnglishLetters = Englishletters + " \n\t" def DictLoader(): #loads the dictionary text File, if the function isn't called the program will automatically set the language to English. englishWords = {} dictFileName = input("enter the dictionary file name (make sure to specify the whole path or copy the dictionary file into the python32 folder and just type the File's name) : ") dictFile = open(dictFileName) EnglishWords = dictFile.read() for word in EnglishWords.split('\n'): englishWords[word] = None dictFile.close() return englishWords def countWords(text): #this function will remove all the non-letter characters and count how many real word(not gibberish) in the provided text. chars = [] counter = 0 for char in text: if char in fullEnglishLetters: chars.append(char) nonLetters = ''.join(chars) if chars == []: return 0 wordsDict = DictLoader() for word in nonLetters.split(): if word in wordsDict: counter += 1 return (counter/len(nonLetters.split())) * 100 def isEnglish(text , percantage = 35 , letterPercentage = 5): wordsMatch = countWords(text) >= percantage chars = [] for char in text: if char in fullEnglishLetters: chars.append(char) nonLetters = ''.join(chars) lettersPercentage = len(nonLetters)/len(text) * 100 lettersMatch = lettersPercentage >= letterPercentage return wordsMatch and lettersMatch def englishWords(text): chars = [] eng = [] counter = 0 for char in text: if char in fullEnglishLetters: chars.append(char) nonLetters = ''.join(chars) if chars == []: return 0 wordsDict = DictLoader() for word in nonLetters.split(): if word in wordsDict: eng.append(word) return eng

[ "=" ]

=

ab8c01014610afd428a0eac76f21e2d1ea9158de

8d43e69234f6d7df8ee66ed306d1b3efbea50fe7

/CMGTools/WMass/python/analyzers/WAnalyzer.py

b304278533ff77147d5db4c802d94f69affc189f

[]

no_license

mariadalfonso/cmg-wmass-44X

c484583c5dfa6af61cbb5f52c492644221c7bfd1

5c2051fc062354d26b78a7426f1541d377022ebb

refs/heads/master

2020-12-29T02:06:52.874006

2013-11-05T16:27:21

null

0

null

UTF-8

Python

false

23,424

py

import operator import copy import math from CMGTools.RootTools.fwlite.Analyzer import Analyzer from CMGTools.RootTools.statistics.Counter import Counter, Counters from CMGTools.RootTools.fwlite.AutoHandle import AutoHandle from CMGTools.RootTools.physicsobjects.PhysicsObjects import Muon, Jet, GenParticle from CMGTools.RootTools.utils.TriggerMatching import triggerMatched from CMGTools.RootTools.utils.DeltaR import bestMatch, deltaR, deltaR2 from CMGTools.WMass.analyzers.common_functions import * # from CMGTools.Utilities.mvaMET.mvaMet import MVAMet, PFMET # from WMass.analyzers.GetMVAMET import GetMVAMET class WAnalyzer( Analyzer ): MuonClass = Muon JetClass = Jet def beginLoop(self): super(WAnalyzer,self).beginLoop() self.counters.addCounter('WAna') count = self.counters.counter('WAna') count.register('W all events') count.register('W ev trig, good vertex and >= 1 lepton') count.register('W at least 1 lep trig matched') count.register('W only 1 lep trig matched') count.register('W non trg leading lepton pT < 10 GeV') count.register('W lep is MuIsTightAndIso') count.register('W Mu_eta<2.1 && Mu_pt>30') count.register('W pfmet>25') count.register('W pt<20') count.register('W Jet_leading_pt<30') # self.mvamet = MVAMet() # SHOULD BE MVAMet(0.1) # void Initialize(const edm::ParameterSet &iConfig, # TString iU1Weights ="$CMSSW_BASE/src/pharris/data/gbrmet_52.root", # TString iPhiWeights ="$CMSSW_BASE/src/pharris/data/gbrmetphi_52.root", # TString iCovU1Weights ="$CMSSW_BASE/src/pharris/data/gbrcovu1_52.root", # TString iCovU2Weights ="$CMSSW_BASE/src/pharris/data/gbrcovu2_52.root", # MVAMet::MVAType iType=kBaseline); # basePath = os.environ['CMSSW_BASE']+"/src/CMGTools/Utilities/data/mvaMET/"; # print ("Inputs are", # basePath+'gbrmet_42.root', # basePath+'gbrmetphi_42.root', # basePath+'gbru1cov_42.root', # basePath+'gbru2cov_42.root', # ) # self.mvamet.Initialize(0, # basePath+'gbrmet_42.root', # basePath+'gbrmetphi_42.root', # basePath+'gbrmetu1cov_42.root', # basePath+'gbrmetu2cov_42.root', # 0 # useless # ) def buildLeptons(self, cmgMuons, event): '''Creates python Leptons from the muons read from the disk. to be overloaded if needed.''' return map( self.__class__.MuonClass, cmgMuons ) def buildJets(self, cmgJets, event): '''Creates python Jets from the Jets read from the disk. to be overloaded if needed.''' return map( self.__class__.JetClass, cmgJets ) def buildGenParticles(self, cmgGenParticles, event): '''Creates python GenParticles from the di-leptons read from the disk. to be overloaded if needed.''' return map( GenParticle, cmgGenParticles ) def declareVariables(self): tr = self.tree var( tr, 'pfmet') def process(self, iEvent, event): # access event self.readCollections( iEvent ) # access muons event.muons = self.buildLeptons( self.handles['muons'].product(), event ) # access jets event.jets = self.buildJets( self.handles['jets'].product(), event ) # access MET event.pfmet = self.handles['pfmet'].product()[0] # access genP event.genParticles = [] event.LHEweights = [] if self.cfg_comp.isMC : event.genParticles = self.buildGenParticles( self.mchandles['genpart'].product(), event ) event.LHEweights = self.mchandles['LHEweights'].product() # define good event bool event.WGoodEvent = False # select event return self.selectionSequence(event, fillCounter=True ) def selectionSequence(self, event, fillCounter): if fillCounter: self.counters.counter('WAna').inc('W all events') # if self.cfg_comp.isMC : # print event.LHEweights.comments_size() # for i in range(0,event.LHEweights.comments_size()): # print i, event.LHEweights.getComment(i).split() # retrieve collections of interest (muons and jets) event.allMuons = copy.copy(event.muons) event.selMuons = copy.copy(event.muons) event.NoTriggeredMuonsLeadingPt = copy.copy(event.muons) event.allJets = copy.copy(event.jets) event.selJets = copy.copy(event.jets) # check if the event is MC and if genp must be saved event.savegenpW=False # event.savegenpW=True # if not (self.cfg_ana.savegenp and self.cfg_comp.isMC): # event.savegenpW=False # print 'event.savegenpW 1 ',event.savegenpW # save genp only for signal events # i.e. only one W is present and daughters are muon plus neutrino genW_dummy = [ genp for genp in event.genParticles if \ math.fabs(genp.pdgId())==24 if \ ( \ math.fabs(genp.daughter(0).pdgId())==11 or math.fabs(genp.daughter(1).pdgId())==11 or math.fabs(genp.daughter(0).pdgId())==13 or math.fabs(genp.daughter(1).pdgId())==13 or math.fabs(genp.daughter(0).pdgId())==15 or math.fabs(genp.daughter(1).pdgId())==15 ) ] # if len(genW_dummy)>0: # if the genp event is selected, associate gen muon and neutrino event.genMu = [] event.genMuStatus1 = [] event.genNu = [] event.genWLept = [] if self.cfg_ana.savegenp and self.cfg_comp.isMC: if len(genW_dummy)==1: # if len(genW_dummy)>0: event.genW = [ genp for genp in genW_dummy if \ ( \ ( math.fabs(genW_dummy[0].daughter(0).pdgId())==13 ) or \ ( math.fabs(genW_dummy[0].daughter(1).pdgId())==13 ) \ ) ] if len(event.genW)==1: event.savegenpW=True event.genW_mt = mT(self,event.genW[0].daughter(0).p4() , event.genW[0].daughter(1).p4()) event.muGenDeltaRgenP=1e6 event.genWLept.append(event.genW[0]) if [ math.fabs(event.genW[0].daughter(0).pdgId())==13 ]: event.genMu.append(event.genW[0].daughter(0)) event.genNu.append(event.genW[0].daughter(1)) else: event.genMu.append(event.genW[0].daughter(1)) event.genNu.append(event.genW[0].daughter(0)) if(len(event.genMu) >0): if(math.fabs(event.genW[0].mother(0).pdgId())!=6): event.genMuStatus1.append(returnMuonDaughterStatus1(self,event.genMu[0])) else: event.genMuStatus1.append(event.genMu[0]) if len(genW_dummy)>1: event.genW = [ genp for genp in genW_dummy if \ ( \ ( math.fabs(genW_dummy[0].daughter(0).pdgId())==11 ) or \ ( math.fabs(genW_dummy[0].daughter(1).pdgId())==11 ) or \ ( math.fabs(genW_dummy[0].daughter(0).pdgId())==13 ) or \ ( math.fabs(genW_dummy[0].daughter(1).pdgId())==13 ) or \ ( math.fabs(genW_dummy[0].daughter(0).pdgId())==15 ) or \ ( math.fabs(genW_dummy[0].daughter(1).pdgId())==15 ) or \ ( math.fabs(genW_dummy[1].daughter(0).pdgId())==11 ) or \ ( math.fabs(genW_dummy[1].daughter(1).pdgId())==11 ) or \ ( math.fabs(genW_dummy[1].daughter(0).pdgId())==13 ) or \ ( math.fabs(genW_dummy[1].daughter(1).pdgId())==13 ) or \ ( math.fabs(genW_dummy[1].daughter(0).pdgId())==15 ) or \ ( math.fabs(genW_dummy[1].daughter(1).pdgId())==15 ) \ ) ] if len(event.genW)==2: if ( math.fabs(event.genW[0].daughter(0).pdgId())==13. or math.fabs(event.genW[0].daughter(0).pdgId())==15. or math.fabs(event.genW[0].daughter(0).pdgId())==11. ): # print 'event.savegenpW 2 ',event.savegenpW event.savegenpW=False # print 'found leptonic W0 a' event.genWLept.append(event.genW[0]) if ( math.fabs(event.genW[0].daughter(0).pdgId())==13 ): event.genMu.append(event.genW[0].daughter(0)) event.genNu.append(event.genW[0].daughter(1)) event.genW_mt = mT(self,event.genMu[0].p4() , event.genNu[0].p4()) event.muGenDeltaRgenP=1e6 if(len(event.genMu) >0): event.genMuStatus1.append(returnMuonDaughterStatus1(self,event.genMu[0])) event.savegenpW=True if ( math.fabs(event.genW[0].daughter(1).pdgId())==13. or math.fabs(event.genW[0].daughter(1).pdgId())==15. or math.fabs(event.genW[0].daughter(1).pdgId())==11. ): # print 'event.savegenpW 3 ',event.savegenpW event.savegenpW=False # print 'found leptonic W0 b' event.genWLept.append(event.genW[0]) if ( math.fabs(event.genW[0].daughter(1).pdgId())==13 ): event.genMu.append(event.genW[0].daughter(1)) event.genNu.append(event.genW[0].daughter(0)) event.genW_mt = mT(self,event.genMu[0].p4() , event.genNu[0].p4()) event.muGenDeltaRgenP=1e6 if(len(event.genMu) >0): event.genMuStatus1.append(returnMuonDaughterStatus1(self,event.genMu[0])) # print 'event.savegenpW 4 ',event.savegenpW event.savegenpW=True if ( math.fabs(event.genW[1].daughter(0).pdgId())==13. or math.fabs(event.genW[1].daughter(0).pdgId())==15. or math.fabs(event.genW[1].daughter(0).pdgId())==11. ): # print 'event.savegenpW 5 ',event.savegenpW event.savegenpW=False # print 'found leptonic W1 c' event.genWLept.append(event.genW[1]) if ( math.fabs(event.genW[1].daughter(0).pdgId())==13 ): event.genMu.append(event.genW[1].daughter(0)) event.genNu.append(event.genW[1].daughter(1)) event.genW_mt = mT(self,event.genMu[0].p4() , event.genNu[0].p4()) event.muGenDeltaRgenP=1e6 if(len(event.genMu) >0): event.genMuStatus1.append(returnMuonDaughterStatus1(self,event.genMu[0])) event.savegenpW=True if ( math.fabs(event.genW[1].daughter(1).pdgId())==13. or math.fabs(event.genW[1].daughter(1).pdgId())==15. or math.fabs(event.genW[1].daughter(1).pdgId())==11. ): # print 'event.savegenpW 6 ',event.savegenpW event.savegenpW=False # print 'found leptonic W1 d' event.genWLept.append(event.genW[1]) if ( math.fabs(event.genW[1].daughter(1).pdgId())==13 ): event.genMu.append(event.genW[1].daughter(1)) event.genNu.append(event.genW[1].daughter(0)) event.genW_mt = mT(self,event.genMu[0].p4() , event.genNu[0].p4()) event.muGenDeltaRgenP=1e6 if(len(event.genMu) >0): event.genMuStatus1.append(returnMuonDaughterStatus1(self,event.genMu[0])) event.savegenpW=True # if the genp is not signal, don't save genp but do not exit # -----> events which will pass the reconstruction but are not signal # can be considered as background (for example, in W+Jets, from W decaying into electrons, taus) # else: # ## here put false for fully hadronic WW # print 'event.savegenpW 7 ',event.savegenpW # event.savegenpW=False # print 'genW found ', len(genW_dummy) # print 'genWLeptonic found ', len(event.genWLept) # store event number of muons, MET and jets in all gen events (necessary to make cuts in genp studies...) # total number of reco muons event.nMuons=len(event.selMuons) # clean jets by removing muons event.selJets = [ jet for jet in event.allJets if ( \ not (bestMatch( jet , event.selMuons ))[1] <0.5 \ and jet.looseJetId() and jet.pt()>30 \ ) ] # reco events must have good reco vertex and trigger fired... if not (event.passedVertexAnalyzer and event.passedTriggerAnalyzer): return True # ...and at lest one reco muon... if len(event.selMuons) == 0: return True if fillCounter: self.counters.counter('WAna').inc('W ev trig, good vertex and >= 1 lepton') #check if the event is triggered according to cfg_ana if len(self.cfg_comp.triggers)>0: # muon object trigger matching event.selMuons = [lep for lep in event.allMuons if \ trigMatched(self, event, lep)] # exit if there are no triggered muons if len(event.selMuons) == 0: return True, 'trigger matching failed' else: if fillCounter: self.counters.counter('WAna').inc('W at least 1 lep trig matched') # to select W impose only 1 triggering lepton in the event: # the number of triggering lepton is checked on the whole lepton collection # before any cut, otherwise could be a Z!!! if len(event.selMuons) != 1: return True, 'more than 1 lep trig matched' else: if fillCounter: self.counters.counter('WAna').inc('W only 1 lep trig matched') # store muons that did not fire the trigger event.NoTriggeredMuonsLeadingPt = [lep for lep in event.allMuons if \ not trigMatched(self, event, lep) ] # print "len(event.NoTriggeredMuonsLeadingPt)= ",len(event.NoTriggeredMuonsLeadingPt) # if len(event.NoTriggeredMuonsLeadingPt)>0 : print "event.NoTriggeredMuonsLeadingPt[0].pt() = ",event.NoTriggeredMuonsLeadingPt[0].pt() if len(event.NoTriggeredMuonsLeadingPt) > 0: if event.NoTriggeredMuonsLeadingPt[0].pt()>10: # if (event.NoTriggeredMuonsLeadingPt[0].pt()<10): print "ESISTE UN LEPTONE NON TRIGGERING WITH PT>10, event.NoTriggeredMuonsLeadingPt[0].pt() = ",event.NoTriggeredMuonsLeadingPt[0].pt() return True, 'rejecting event with non triggering lepton with pT > 10 GeV' else: if fillCounter: self.counters.counter('WAna').inc('W non trg leading lepton pT < 10 GeV') else: if fillCounter: self.counters.counter('WAna').inc('W non trg leading lepton pT < 10 GeV') # if the genp are saved, compute dR between gen and reco muon if (event.savegenpW and len(event.genW)==1): event.muGenDeltaRgenP = deltaR( event.selMuons[0].eta(), event.selMuons[0].phi(), event.genMu[0].eta(), event.genMu[0].phi() ) # associate good vertex to muon to compute dxy event.selMuons[0].associatedVertex = event.goodVertices[0] # testing offline muon cuts (tight+iso, no kinematical cuts) event.selMuonIsTightAndIso = testLeg(self, event.selMuons[0] ) event.selMuonIsTight = testLegID( self,event.selMuons[0] ) # START RETRIEVING MVAMET # INPUT DEFINITIONS AS OF HTT # mvaMETTauMu = cms.EDProducer( # "MVAMETProducerTauMu", # pfmetSrc = cms.InputTag('pfMetForRegression'), # tkmetSrc = cms.InputTag('tkMet'), # nopumetSrc = cms.InputTag('nopuMet'), # pucmetSrc = cms.InputTag('pcMet'), # pumetSrc = cms.InputTag('puMet'), # recBosonSrc = cms.InputTag('cmgTauMuSel'), # jetSrc = cms.InputTag('cmgPFJetSel'), # leadJetSrc = cms.InputTag('cmgPFBaseJetLead'), # vertexSrc = cms.InputTag('goodPVFilter'), # nJetsPtGt1Src = cms.InputTag('nJetsPtGt1'), # rhoSrc = cms.InputTag('kt6PFJets','rho'), # enable = cms.bool(True), # verbose = cms.untracked.bool( False ), # weights_gbrmet = cms.string(weights_gbrmet), # weights_gbrmetphi = cms.string(weights_gbrmetphi), # weights_gbrmetu1cov = cms.string(weights_gbrmetu1cov), # weights_gbrmetu2cov = cms.string(weights_gbrmetu2cov), # #COLIN: make delta R a parameter # ) # self.prepareObjectsForMVAMET(event) # self.mvamet.getMet( # event.cleanpfmetForRegression, #iPFMet, # event.cleantkmet, #iTKMet, # event.cleannopumet, #iNoPUMet, # event.pumet, #iPUMet, # event.cleanpucmet, #iPUCMet, # event.iLeadJet, #event.iLeadJet, # event.i2ndJet, #event.i2ndJet, # event.NJetsGt30, #iNJetsGt30, # event.nJetsPtGt1Clean, #iNJetsGt1, # len(event.goodVertices), #iNGoodVtx, # event.iJets_p4, #iJets, # event.iJets_mva, #iJets, # event.iJets_neutFrac, #iJets, # False, #iPrintDebug, # event.visObjectP4s_array #visObjectP4s # ) # event.mvamet = self.mvamet.GetMet_first(); # event.GetMVAMet_second = self.mvamet.GetMet_second(); # print 'AFTER MVAmet_test' # print 'event.pfmet.pt() ', event.pfmet.pt() # print 'event.selMuons[0].pt() ',event.selMuons[0].pt(),' event.mvamet.Pt() ',event.mvamet.Pt() # print '' # print 'event.GetMVAMet_second ',event.GetMVAMet_second,' event.GetMVAMet_second.significance() ',event.GetMVAMet_second.significance().Print() # define a W from lepton and MET event.W4V = event.selMuons[0].p4() + event.pfmet.p4() event.W4V_mt = mT(self,event.selMuons[0].p4() , event.pfmet.p4()) event.covMatrixMuon = [] RetrieveMuonMatrixIntoVector(self,event.selMuons[0],event.covMatrixMuon) # print event.covMatrixMuon # Code to study the recoil (not very useful for W...) metVect = event.pfmet.p4().Vect() metVect.SetZ(0.) # use only transverse info WVect = event.W4V.Vect() WVect.SetZ(0.) # use only transverse info recoilVect = - copy.deepcopy(metVect) ## FIXED (met sign inverted) # recoilVect -= WVect temp_recoil = event.selMuons[0].p4().Vect() temp_recoil.SetZ(0.) # use only transverse info recoilVect -= temp_recoil ## FIXED (subtract only lepton for consistent recoil definition) uWVect = WVect.Unit() zAxis = type(WVect)(0,0,1) uWVectPerp = WVect.Cross(zAxis).Unit() u1 = recoilVect.Dot(uWVect) # recoil parallel to W pt u2 = - recoilVect.Dot(uWVectPerp) # recoil perpendicular to W pt event.u1 = u1 event.u2 = u2 if fillCounter: if event.selMuonIsTightAndIso : self.counters.counter('WAna').inc('W lep is MuIsTightAndIso') if testLegKine( self, event.selMuons[0] , 30 , 2.1 ) : self.counters.counter('WAna').inc('W Mu_eta<2.1 && Mu_pt>30') if event.pfmet.pt() >25: self.counters.counter('WAna').inc('W pfmet>25') if event.W4V.Pt() < 20: self.counters.counter('WAna').inc('W pt<20') if len(event.selJets) > 0: if event.selJets[0].pt()<30: self.counters.counter('WAna').inc('W Jet_leading_pt<30') else: self.counters.counter('WAna').inc('W Jet_leading_pt<30') # event is fully considered as good # if fillCounter: self.counters.counter('WAna').inc('W pass') event.WGoodEvent = True return True def declareHandles(self): super(WAnalyzer, self).declareHandles() self.handles['cmgTriggerObjectSel'] = AutoHandle('cmgTriggerObjectSel','std::vector<cmg::TriggerObject>') self.handles['muons'] = AutoHandle('cmgMuonSel','std::vector<cmg::Muon>') self.handles['jets'] = AutoHandle('cmgPFJetSel','std::vector<cmg::PFJet>') self.handles['jetLead'] = AutoHandle('cmgPFBaseJetLead','vector<cmg::BaseJet>') self.handles['pfmet'] = AutoHandle('cmgPFMET','std::vector<cmg::BaseMET>' ) self.handles['pfMetForRegression'] = AutoHandle('pfMetForRegression','std::vector<reco::PFMET>' ) self.handles['tkmet'] = AutoHandle('tkMet','std::vector<reco::PFMET>' ) self.handles['nopumet'] = AutoHandle('nopuMet','std::vector<reco::PFMET>' ) self.handles['pumet'] = AutoHandle('puMet','std::vector<reco::PFMET>' ) self.handles['pucmet'] = AutoHandle('pcMet','std::vector<reco::PFMET>' ) self.mchandles['genpart'] = AutoHandle('genParticlesPruned','std::vector<reco::GenParticle>') self.handles['vertices'] = AutoHandle('offlinePrimaryVertices','std::vector<reco::Vertex>') self.handles['nJetsPtGt1'] = AutoHandle('nJetsPtGt1','int') self.handles['cmgTriggerObjectSel'] = AutoHandle('cmgTriggerObjectSel','std::vector<cmg::TriggerObject>') self.handles['muons'] = AutoHandle('cmgMuonSel','std::vector<cmg::Muon>') self.handles['jets'] = AutoHandle('cmgPFJetSel','std::vector<cmg::PFJet>') self.handles['pfmet'] = AutoHandle('cmgPFMET','std::vector<cmg::BaseMET>' ) self.mchandles['genpart'] = AutoHandle('genParticlesPruned','std::vector<reco::GenParticle>') self.mchandles['LHEweights'] = AutoHandle('source','LHEEventProduct')

[ "perrozzi@cern.ch" ]

perrozzi@cern.ch

42db80f31e7be0f63eda0be8f66f974d95ed6f61

dbd23b5c9ead096ea1b4c4ddd2acba3f6b4eb0db

/testing/test_delete_job_when_finished.py

62808bad32277674cc8859516c778e703e7e1ef6

[]

no_license

NGTS/real-time-transmission

b067b9572d02ae99c7cbd6c569c4ac36eb14bc25

f70901dbc9ae59515e7786d5d3a5978c46adc312

refs/heads/master

2020-06-07T16:11:45.860569

2018-02-26T11:15:49

42,189,235

0

null

UTF-8

Python

false

508

py

import pytest import pymysql from ngts_transmission.watching import fetch_transmission_jobs @pytest.yield_fixture def cursor(): connection = pymysql.connect(user='ops', db='ngts_ops') cursor = connection.cursor() try: yield cursor finally: connection.rollback() connection.close() def test_job_deleted(job_db, cursor): job = list(fetch_transmission_jobs(cursor))[0] job.remove_from_database(cursor) assert list(fetch_transmission_jobs(cursor)) == []

[ "s.r.walker101@googlemail.com" ]

s.r.walker101@googlemail.com

3a0df4406e2172b099f147aac840fbdf997001a3

620cd7d12a3d241da9fe59f30bbbc97c3ffa61e2

/apptools/apptools-android-tests/apptools/build_path.py

2ceabab85becaf578c47fac647bd2d36b0cc4829

[ "BSD-3-Clause" ]

permissive

playbar/crosswalk-test-suite

e46db96343f4a47f1a19fddaedc519818c10d992

29686407e8b3106cf2b0e87080f927609e745f8e

refs/heads/master

2021-05-29T15:33:01.099059

2015-10-09T06:03:22

null

0

null

UTF-8

Python

false

2,717

py

#!/usr/bin/env python # # Copyright (c) 2015 Intel Corporation. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of works must retain the original copyright notice, this # list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the original copyright # notice, this list of conditions and the following disclaimer in the # documentation and/or other materials provided with the distribution. # * Neither the name of Intel Corporation nor the names of its contributors # may be used to endorse or promote products derived from this work without # specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY INTEL CORPORATION "AS IS" # AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE # ARE DISCLAIMED. IN NO EVENT SHALL INTEL CORPORATION BE LIABLE FOR ANY DIRECT, # INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, # BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY # OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING # NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, # EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # # Authors: # Yun, Liu<yunx.liu@intel.com> import unittest import os import comm import shutil class TestCrosswalkApptoolsFunctions(unittest.TestCase): def test_build_path_normal(self): comm.setUp() comm.create(self) if os.path.exists("pkg"): shutil.rmtree("pkg") os.mkdir("pkg") os.chdir('pkg') buildcmd = comm.HOST_PREFIX + comm.PackTools + "crosswalk-app build " + comm.XwalkPath + "org.xwalk.test" comm.build(self, buildcmd) comm.run(self) os.chdir('../') shutil.rmtree("pkg") comm.clear("org.xwalk.test") os.system('adb start-server') def test_build_path_release(self): comm.setUp() comm.create(self) if os.path.exists("pkg"): shutil.rmtree("pkg") os.mkdir("pkg") os.chdir('pkg') buildcmd = comm.HOST_PREFIX + comm.PackTools + "crosswalk-app build release " + comm.XwalkPath + "org.xwalk.test" comm.build(self, buildcmd) comm.run(self) os.chdir('../') shutil.rmtree("pkg") comm.clear("org.xwalk.test") os.system('adb start-server') if __name__ == '__main__': unittest.main()

[ "yunx.liu@intel.com" ]

yunx.liu@intel.com

78e008b4a51cdbbb81dead7bc5945ee98ccad862

bf681fbd7edbf4f8f1e0b20cbd09b362f777c9c3

/matlab/mex_handle_example/stuff.py

55b253d58c48aa9d653944185b73a4b2aea17ae8

[ "BSD-3-Clause" ]

permissive

EricCousineau-TRI/repro

308d4a86f3c7da8be5811db2f3f68d39db60d7ed

9800f45e07f511c9a355ee90333955451b55559a

refs/heads/master

2023-08-31T13:49:23.540640

2023-08-25T19:18:33

87,116,976

24

13

NOASSERTION

2023-03-25T01:40:55

2017-04-03T20:19:28

Jupyter Notebook

UTF-8

Python

false

25

py

def test(x): print x

[ "eric.cousineau@tri.global" ]

eric.cousineau@tri.global

3bfdba7d4e743674ea2486e57020635bd9131403

b529da0623557e3271adbc148617000ca699ac08

/test/test_homepage_section.py

d2c2493adeb13b95ddddecfecc84b1800516f7eb

[ "MIT" ]

permissive

gustavs408650/looker_sdk_30

106dc73ac8949e06c68c6caf544123edabe6c5cc

8b52449f216b2cb3b84f09e2856bcea1ed4a2b0c

refs/heads/master

2020-09-08T16:42:02.224496

2019-11-13T14:59:12

221,186,703

0

MIT

2019-11-12T10:05:51

2019-11-12T10:05:50

null

UTF-8

Python

false

2,486

py

# coding: utf-8 """ Looker API 3.0 Reference ### Authorization The Looker API uses Looker **API3** credentials for authorization and access control. Looker admins can create API3 credentials on Looker's **Admin/Users** page. Pass API3 credentials to the **/login** endpoint to obtain a temporary access_token. Include that access_token in the Authorization header of Looker API requests. For details, see [Looker API Authorization](https://looker.com/docs/r/api/authorization) ### Client SDKs The Looker API is a RESTful system that should be usable by any programming language capable of making HTTPS requests. Client SDKs for a variety of programming languages can be generated from the Looker API's Swagger JSON metadata to streamline use of the Looker API in your applications. A client SDK for Ruby is available as an example. For more information, see [Looker API Client SDKs](https://looker.com/docs/r/api/client_sdks) ### Try It Out! The 'api-docs' page served by the Looker instance includes 'Try It Out!' buttons for each API method. After logging in with API3 credentials, you can use the \"Try It Out!\" buttons to call the API directly from the documentation page to interactively explore API features and responses. ### Versioning Future releases of Looker will expand this API release-by-release to securely expose more and more of the core power of Looker to API client applications. API endpoints marked as \"beta\" may receive breaking changes without warning. Stable (non-beta) API endpoints should not receive breaking changes in future releases. For more information, see [Looker API Versioning](https://looker.com/docs/r/api/versioning) # noqa: E501 OpenAPI spec version: 3.0.0 Generated by: https://github.com/swagger-api/swagger-codegen.git """ from __future__ import absolute_import import unittest import looker_client_30 from looker_client_30.looker_sdk.homepage_section import HomepageSection # noqa: E501 from looker_client_30.rest import ApiException class TestHomepageSection(unittest.TestCase): """HomepageSection unit test stubs""" def setUp(self): pass def tearDown(self): pass def testHomepageSection(self): """Test HomepageSection""" # FIXME: construct object with mandatory attributes with example values # model = looker_client_30.models.homepage_section.HomepageSection() # noqa: E501 pass if __name__ == '__main__': unittest.main()

[ "looker@MacBook-Pro.local" ]

looker@MacBook-Pro.local

2ba5addce7fd9b7cb325e48d5c45b3ce7fd59344

57fc5d54f5df359c7a53020fb903f36479d3a322

/controllers/.history/supervisor/test_20201127155537.py

e3b792d9d8e09cd6b8a393ddf0de55beb40da8d5

[]

no_license

shenwuyue-xie/webots_testrobots

929369b127258d85e66c5275c9366ce1a0eb17c7

56e476356f3cf666edad6449e2da874bb4fb4da3

refs/heads/master

2023-02-02T11:17:36.017289

2020-12-20T08:22:59

323,032,362

0

null

UTF-8

Python

false

3,372

py

import numpy import math import os # def normalize_to_range(value, min, max, newMin, newMax): # value = float(value) # min = float(min) # max = float(max) # newMin = float(newMin) # newMax = float(newMax) # return (newMax - newMin) / (max - min) * (value - max) + newMax # k = normalize_to_range(50,0,1000,0,1) # print(k) # x = [0.5 for i in range(12)] # y = numpy.random.normal(12) # """ better function """ # def robot_step(self,action): # flag_translation = False # flag_rotation = False # if action[-1] > 0.8 and action[-1] <= 1 and self.robot_num < Max_robotnum: # last_translation = self.robot_handles[-1].getField('translation').getSFVec3f() # last_angle = self.robot_handles[-1].getField('rotation').getSFRotation()[3] # last_rotation = self.robot_handles[-1].getField('rotation').getSFRotation() # delta_z = 0.23 * math.cos(last_angle) # delta_x = 0.23 * math.sin(last_angle) # new_translation = [] # new_translation.append(last_translation[0] - delta_x) # new_translation.append(last_translation[1]) # new_translation.append(last_translation[2] - delta_z) # robot_children = self.robot_handles[-1].getField('children') # rearjoint_node = robot_children.getMFNode(4) # joint = rearjoint_node.getField('jointParameters') # joint = joint.getSFNode() # para = joint.getField('position') # hingeposition = para.getSFFloat() # if hingeposition > 0.8 or hingeposition < -0.8: # delta = 0.03 - 0.03 * math.cos(hingeposition) # delta_z = delta * math.cos(last_angle) # delta_x = delta * math.sin(last_angle) # new_translation[0] = new_translation[0] + delta_x # new_translation[2] = new_translation[2] + delta_z # new_rotation = [] # for i in range(4): # new_rotation.append(last_rotation[i]) flag_translation = False flag_rotation = False new_file = [] with open ("Robot.wbo",'r+') as f: lines = f.readlines() for line in lines: if "translation" in line: if flag_translation == False: replace = "translation " + str(0) + " " + str(0) + " " + str(0) line = "\t" + replace +'\n' flag_translation = True if "rotation" in line: if flag_rotation == False: replace = "rotation " + str(0) + " " + str(0) + " " + str(0) + " " \ +str(0) line = "\t" + replace +'\n' flag_rotation = True new_file = [] # rootNode = self.supervisor.getRoot() # childrenField = rootNode.getField('children') # childrenField.importMFNode(-1,importname) # defname = 'robot_' + str(self.robot_num) # self.robot_handles.append(self.supervisor.getFromDef(defname)) # self.robot_num = self.robot_num + 1 # elif action[-1] >0 and action[-1] <= 0.2 and self.robot_num >1: # removerobot = self.robot_handles[-1] # removerobot.remove() # self.robot_num = self.robot_num - 1 # del(self.robot_handles[-1])

[ "1092673859@qq.com" ]

1092673859@qq.com

1d1b31629d7dcfd346475c36ac89b89bf2102260

fbbe424559f64e9a94116a07eaaa555a01b0a7bb

/Sklearn_scipy_numpy/source/scipy/signal/ltisys.py

1deabb3a11809ff2e91ff31f7f036a9b73dbc052

[ "MIT" ]

permissive

ryfeus/lambda-packs

6544adb4dec19b8e71d75c24d8ed789b785b0369

cabf6e4f1970dc14302f87414f170de19944bac2

refs/heads/master

2022-12-07T16:18:52.475504

2022-11-29T13:35:35

71,386,735

1,283

263

MIT

2022-11-26T05:02:14

2016-10-19T18:22:39

Python

UTF-8

Python

false

79,826

py

""" ltisys -- a collection of classes and functions for modeling linear time invariant systems. """ from __future__ import division, print_function, absolute_import # # Author: Travis Oliphant 2001 # # Feb 2010: Warren Weckesser # Rewrote lsim2 and added impulse2. # Aug 2013: Juan Luis Cano # Rewrote abcd_normalize. # Jan 2015: Irvin Probst irvin DOT probst AT ensta-bretagne DOT fr # Added pole placement # Mar 2015: Clancy Rowley # Rewrote lsim # May 2015: Felix Berkenkamp # Split lti class into subclasses # import warnings import numpy as np #np.linalg.qr fails on some tests with LinAlgError: zgeqrf returns -7 #use scipy's qr until this is solved from scipy.linalg import qr as s_qr import numpy from numpy import (r_, eye, real, atleast_1d, atleast_2d, poly, squeeze, asarray, product, zeros, array, dot, transpose, ones, zeros_like, linspace, nan_to_num) import copy from scipy import integrate, interpolate, linalg from scipy._lib.six import xrange from .filter_design import tf2zpk, zpk2tf, normalize, freqs __all__ = ['tf2ss', 'ss2tf', 'abcd_normalize', 'zpk2ss', 'ss2zpk', 'lti', 'TransferFunction', 'ZerosPolesGain', 'StateSpace', 'lsim', 'lsim2', 'impulse', 'impulse2', 'step', 'step2', 'bode', 'freqresp', 'place_poles'] def tf2ss(num, den): r"""Transfer function to state-space representation. Parameters ---------- num, den : array_like Sequences representing the numerator and denominator polynomials. The denominator needs to be at least as long as the numerator. Returns ------- A, B, C, D : ndarray State space representation of the system, in controller canonical form. Examples -------- Convert the transfer function: .. math:: H(s) = \frac{s^2 + 3s + 3}{s^2 + 2s + 1} >>> num = [1, 3, 3] >>> den = [1, 2, 1] to the state-space representation: .. math:: \dot{\textbf{x}}(t) = \begin{bmatrix} -2 & -1 \\ 1 & 0 \end{bmatrix} \textbf{x}(t) + \begin{bmatrix} 1 \\ 0 \end{bmatrix} \textbf{u}(t) \\ \textbf{y}(t) = \begin{bmatrix} 1 & 2 \end{bmatrix} \textbf{x}(t) + \begin{bmatrix} 1 \end{bmatrix} \textbf{u}(t) >>> from scipy.signal import tf2ss >>> A, B, C, D = tf2ss(num, den) >>> A array([[-2., -1.], [ 1., 0.]]) >>> B array([[ 1.], [ 0.]]) >>> C array([[ 1., 2.]]) >>> D array([ 1.]) """ # Controller canonical state-space representation. # if M+1 = len(num) and K+1 = len(den) then we must have M <= K # states are found by asserting that X(s) = U(s) / D(s) # then Y(s) = N(s) * X(s) # # A, B, C, and D follow quite naturally. # num, den = normalize(num, den) # Strips zeros, checks arrays nn = len(num.shape) if nn == 1: num = asarray([num], num.dtype) M = num.shape[1] K = len(den) if M > K: msg = "Improper transfer function. `num` is longer than `den`." raise ValueError(msg) if M == 0 or K == 0: # Null system return (array([], float), array([], float), array([], float), array([], float)) # pad numerator to have same number of columns has denominator num = r_['-1', zeros((num.shape[0], K - M), num.dtype), num] if num.shape[-1] > 0: D = num[:, 0] else: D = array([], float) if K == 1: return array([], float), array([], float), array([], float), D frow = -array([den[1:]]) A = r_[frow, eye(K - 2, K - 1)] B = eye(K - 1, 1) C = num[:, 1:] - num[:, 0] * den[1:] return A, B, C, D def _none_to_empty_2d(arg): if arg is None: return zeros((0, 0)) else: return arg def _atleast_2d_or_none(arg): if arg is not None: return atleast_2d(arg) def _shape_or_none(M): if M is not None: return M.shape else: return (None,) * 2 def _choice_not_none(*args): for arg in args: if arg is not None: return arg def _restore(M, shape): if M.shape == (0, 0): return zeros(shape) else: if M.shape != shape: raise ValueError("The input arrays have incompatible shapes.") return M def abcd_normalize(A=None, B=None, C=None, D=None): """Check state-space matrices and ensure they are two-dimensional. If enough information on the system is provided, that is, enough properly-shaped arrays are passed to the function, the missing ones are built from this information, ensuring the correct number of rows and columns. Otherwise a ValueError is raised. Parameters ---------- A, B, C, D : array_like, optional State-space matrices. All of them are None (missing) by default. See `ss2tf` for format. Returns ------- A, B, C, D : array Properly shaped state-space matrices. Raises ------ ValueError If not enough information on the system was provided. """ A, B, C, D = map(_atleast_2d_or_none, (A, B, C, D)) MA, NA = _shape_or_none(A) MB, NB = _shape_or_none(B) MC, NC = _shape_or_none(C) MD, ND = _shape_or_none(D) p = _choice_not_none(MA, MB, NC) q = _choice_not_none(NB, ND) r = _choice_not_none(MC, MD) if p is None or q is None or r is None: raise ValueError("Not enough information on the system.") A, B, C, D = map(_none_to_empty_2d, (A, B, C, D)) A = _restore(A, (p, p)) B = _restore(B, (p, q)) C = _restore(C, (r, p)) D = _restore(D, (r, q)) return A, B, C, D def ss2tf(A, B, C, D, input=0): r"""State-space to transfer function. A, B, C, D defines a linear state-space system with `p` inputs, `q` outputs, and `n` state variables. Parameters ---------- A : array_like State (or system) matrix of shape ``(n, n)`` B : array_like Input matrix of shape ``(n, p)`` C : array_like Output matrix of shape ``(q, n)`` D : array_like Feedthrough (or feedforward) matrix of shape ``(q, p)`` input : int, optional For multiple-input systems, the index of the input to use. Returns ------- num : 2-D ndarray Numerator(s) of the resulting transfer function(s). `num` has one row for each of the system's outputs. Each row is a sequence representation of the numerator polynomial. den : 1-D ndarray Denominator of the resulting transfer function(s). `den` is a sequence representation of the denominator polynomial. Examples -------- Convert the state-space representation: .. math:: \dot{\textbf{x}}(t) = \begin{bmatrix} -2 & -1 \\ 1 & 0 \end{bmatrix} \textbf{x}(t) + \begin{bmatrix} 1 \\ 0 \end{bmatrix} \textbf{u}(t) \\ \textbf{y}(t) = \begin{bmatrix} 1 & 2 \end{bmatrix} \textbf{x}(t) + \begin{bmatrix} 1 \end{bmatrix} \textbf{u}(t) >>> A = [[-2, -1], [1, 0]] >>> B = [[1], [0]] # 2-dimensional column vector >>> C = [[1, 2]] # 2-dimensional row vector >>> D = 1 to the transfer function: .. math:: H(s) = \frac{s^2 + 3s + 3}{s^2 + 2s + 1} >>> from scipy.signal import ss2tf >>> ss2tf(A, B, C, D) (array([[1, 3, 3]]), array([ 1., 2., 1.])) """ # transfer function is C (sI - A)**(-1) B + D # Check consistency and make them all rank-2 arrays A, B, C, D = abcd_normalize(A, B, C, D) nout, nin = D.shape if input >= nin: raise ValueError("System does not have the input specified.") # make SIMO from possibly MIMO system. B = B[:, input:input + 1] D = D[:, input:input + 1] try: den = poly(A) except ValueError: den = 1 if (product(B.shape, axis=0) == 0) and (product(C.shape, axis=0) == 0): num = numpy.ravel(D) if (product(D.shape, axis=0) == 0) and (product(A.shape, axis=0) == 0): den = [] return num, den num_states = A.shape[0] type_test = A[:, 0] + B[:, 0] + C[0, :] + D num = numpy.zeros((nout, num_states + 1), type_test.dtype) for k in range(nout): Ck = atleast_2d(C[k, :]) num[k] = poly(A - dot(B, Ck)) + (D[k] - 1) * den return num, den def zpk2ss(z, p, k): """Zero-pole-gain representation to state-space representation Parameters ---------- z, p : sequence Zeros and poles. k : float System gain. Returns ------- A, B, C, D : ndarray State space representation of the system, in controller canonical form. """ return tf2ss(*zpk2tf(z, p, k)) def ss2zpk(A, B, C, D, input=0): """State-space representation to zero-pole-gain representation. A, B, C, D defines a linear state-space system with `p` inputs, `q` outputs, and `n` state variables. Parameters ---------- A : array_like State (or system) matrix of shape ``(n, n)`` B : array_like Input matrix of shape ``(n, p)`` C : array_like Output matrix of shape ``(q, n)`` D : array_like Feedthrough (or feedforward) matrix of shape ``(q, p)`` input : int, optional For multiple-input systems, the index of the input to use. Returns ------- z, p : sequence Zeros and poles. k : float System gain. """ return tf2zpk(*ss2tf(A, B, C, D, input=input)) class lti(object): """ Linear Time Invariant system base class. Parameters ---------- *system : arguments The `lti` class can be instantiated with either 2, 3 or 4 arguments. The following gives the number of arguments and the corresponding subclass that is created: * 2: `TransferFunction`: (numerator, denominator) * 3: `ZerosPolesGain`: (zeros, poles, gain) * 4: `StateSpace`: (A, B, C, D) Each argument can be an array or a sequence. Notes ----- `lti` instances do not exist directly. Instead, `lti` creates an instance of one of its subclasses: `StateSpace`, `TransferFunction` or `ZerosPolesGain`. Changing the value of properties that are not directly part of the current system representation (such as the `zeros` of a `StateSpace` system) is very inefficient and may lead to numerical inaccuracies. """ def __new__(cls, *system): """Create an instance of the appropriate subclass.""" if cls is lti: N = len(system) if N == 2: return super(lti, cls).__new__(TransferFunction) elif N == 3: return super(lti, cls).__new__(ZerosPolesGain) elif N == 4: return super(lti, cls).__new__(StateSpace) else: raise ValueError('Needs 2, 3 or 4 arguments.') # __new__ was called from a subclass, let it call its own functions return super(lti, cls).__new__(cls) def __init__(self, *system): """ Initialize the `lti` baseclass. The heavy lifting is done by the subclasses. """ self.inputs = None self.outputs = None @property def num(self): """Numerator of the `TransferFunction` system.""" return self.to_tf().num @num.setter def num(self, num): obj = self.to_tf() obj.num = num source_class = type(self) self._copy(source_class(obj)) @property def den(self): """Denominator of the `TransferFunction` system.""" return self.to_tf().den @den.setter def den(self, den): obj = self.to_tf() obj.den = den source_class = type(self) self._copy(source_class(obj)) @property def zeros(self): """Zeros of the `ZerosPolesGain` system.""" return self.to_zpk().zeros @zeros.setter def zeros(self, zeros): obj = self.to_zpk() obj.zeros = zeros source_class = type(self) self._copy(source_class(obj)) @property def poles(self): """Poles of the `ZerosPolesGain` system.""" return self.to_zpk().poles @poles.setter def poles(self, poles): obj = self.to_zpk() obj.poles = poles source_class = type(self) self._copy(source_class(obj)) @property def gain(self): """Gain of the `ZerosPolesGain` system.""" return self.to_zpk().gain @gain.setter def gain(self, gain): obj = self.to_zpk() obj.gain = gain source_class = type(self) self._copy(source_class(obj)) @property def A(self): """State matrix of the `StateSpace` system.""" return self.to_ss().A @A.setter def A(self, A): obj = self.to_ss() obj.A = A source_class = type(self) self._copy(source_class(obj)) @property def B(self): """Input matrix of the `StateSpace` system.""" return self.to_ss().B @B.setter def B(self, B): obj = self.to_ss() obj.B = B source_class = type(self) self._copy(source_class(obj)) @property def C(self): """Output matrix of the `StateSpace` system.""" return self.to_ss().C @C.setter def C(self, C): obj = self.to_ss() obj.C = C source_class = type(self) self._copy(source_class(obj)) @property def D(self): """Feedthrough matrix of the `StateSpace` system.""" return self.to_ss().D @D.setter def D(self, D): obj = self.to_ss() obj.D = D source_class = type(self) self._copy(source_class(obj)) def impulse(self, X0=None, T=None, N=None): """ Return the impulse response of a continuous-time system. See `scipy.signal.impulse` for details. """ return impulse(self, X0=X0, T=T, N=N) def step(self, X0=None, T=None, N=None): """ Return the step response of a continuous-time system. See `scipy.signal.step` for details. """ return step(self, X0=X0, T=T, N=N) def output(self, U, T, X0=None): """ Return the response of a continuous-time system to input `U`. See `scipy.signal.lsim` for details. """ return lsim(self, U, T, X0=X0) def bode(self, w=None, n=100): """ Calculate Bode magnitude and phase data of a continuous-time system. Returns a 3-tuple containing arrays of frequencies [rad/s], magnitude [dB] and phase [deg]. See `scipy.signal.bode` for details. Notes ----- .. versionadded:: 0.11.0 Examples -------- >>> from scipy import signal >>> import matplotlib.pyplot as plt >>> s1 = signal.lti([1], [1, 1]) >>> w, mag, phase = s1.bode() >>> plt.figure() >>> plt.semilogx(w, mag) # Bode magnitude plot >>> plt.figure() >>> plt.semilogx(w, phase) # Bode phase plot >>> plt.show() """ return bode(self, w=w, n=n) def freqresp(self, w=None, n=10000): """ Calculate the frequency response of a continuous-time system. Returns a 2-tuple containing arrays of frequencies [rad/s] and complex magnitude. See `scipy.signal.freqresp` for details. """ return freqresp(self, w=w, n=n) class TransferFunction(lti): r"""Linear Time Invariant system class in transfer function form. Represents the system as the transfer function :math:`H(s)=\sum_{i=0}^N b[N-i] s^i / \sum_{j=0}^M a[M-j] s^j`, where :math:`b` are elements of the numerator `num`, :math:`a` are elements of the denominator `den`, and ``N == len(b) - 1``, ``M == len(a) - 1``. Parameters ---------- *system : arguments The `TransferFunction` class can be instantiated with 1 or 2 arguments. The following gives the number of input arguments and their interpretation: * 1: `lti` system: (`StateSpace`, `TransferFunction` or `ZerosPolesGain`) * 2: array_like: (numerator, denominator) See Also -------- ZerosPolesGain, StateSpace, lti tf2ss, tf2zpk, tf2sos Notes ----- Changing the value of properties that are not part of the `TransferFunction` system representation (such as the `A`, `B`, `C`, `D` state-space matrices) is very inefficient and may lead to numerical inaccuracies. Examples -------- Construct the transfer function: .. math:: H(s) = \frac{s^2 + 3s + 3}{s^2 + 2s + 1} >>> from scipy import signal >>> num = [1, 3, 3] >>> den = [1, 2, 1] >>> signal.TransferFunction(num, den) TransferFunction( array([ 1., 3., 3.]), array([ 1., 2., 1.]) ) """ def __new__(cls, *system): """Handle object conversion if input is an instance of lti.""" if len(system) == 1 and isinstance(system[0], lti): return system[0].to_tf() # No special conversion needed return super(TransferFunction, cls).__new__(cls) def __init__(self, *system): """Initialize the state space LTI system.""" # Conversion of lti instances is handled in __new__ if isinstance(system[0], lti): return super(TransferFunction, self).__init__(self, *system) self._num = None self._den = None self.num, self.den = normalize(*system) def __repr__(self): """Return representation of the system's transfer function""" return '{0}(\n{1},\n{2}\n)'.format( self.__class__.__name__, repr(self.num), repr(self.den), ) @property def num(self): """Numerator of the `TransferFunction` system.""" return self._num @num.setter def num(self, num): self._num = atleast_1d(num) # Update dimensions if len(self.num.shape) > 1: self.outputs, self.inputs = self.num.shape else: self.outputs = 1 self.inputs = 1 @property def den(self): """Denominator of the `TransferFunction` system.""" return self._den @den.setter def den(self, den): self._den = atleast_1d(den) def _copy(self, system): """ Copy the parameters of another `TransferFunction` object Parameters ---------- system : `TransferFunction` The `StateSpace` system that is to be copied """ self.num = system.num self.den = system.den def to_tf(self): """ Return a copy of the current `TransferFunction` system. Returns ------- sys : instance of `TransferFunction` The current system (copy) """ return copy.deepcopy(self) def to_zpk(self): """ Convert system representation to `ZerosPolesGain`. Returns ------- sys : instance of `ZerosPolesGain` Zeros, poles, gain representation of the current system """ return ZerosPolesGain(*tf2zpk(self.num, self.den)) def to_ss(self): """ Convert system representation to `StateSpace`. Returns ------- sys : instance of `StateSpace` State space model of the current system """ return StateSpace(*tf2ss(self.num, self.den)) class ZerosPolesGain(lti): """ Linear Time Invariant system class in zeros, poles, gain form. Represents the system as the transfer function :math:`H(s)=k \prod_i (s - z[i]) / \prod_j (s - p[j])`, where :math:`k` is the `gain`, :math:`z` are the `zeros` and :math:`p` are the `poles`. Parameters ---------- *system : arguments The `ZerosPolesGain` class can be instantiated with 1 or 3 arguments. The following gives the number of input arguments and their interpretation: * 1: `lti` system: (`StateSpace`, `TransferFunction` or `ZerosPolesGain`) * 3: array_like: (zeros, poles, gain) See Also -------- TransferFunction, StateSpace, lti zpk2ss, zpk2tf, zpk2sos Notes ----- Changing the value of properties that are not part of the `ZerosPolesGain` system representation (such as the `A`, `B`, `C`, `D` state-space matrices) is very inefficient and may lead to numerical inaccuracies. """ def __new__(cls, *system): """Handle object conversion if input is an instance of `lti`""" if len(system) == 1 and isinstance(system[0], lti): return system[0].to_zpk() # No special conversion needed return super(ZerosPolesGain, cls).__new__(cls) def __init__(self, *system): """Initialize the zeros, poles, gain LTI system.""" # Conversion of lti instances is handled in __new__ if isinstance(system[0], lti): return super(ZerosPolesGain, self).__init__(self, *system) self._zeros = None self._poles = None self._gain = None self.zeros, self.poles, self.gain = system def __repr__(self): """Return representation of the `ZerosPolesGain` system""" return '{0}(\n{1},\n{2},\n{3}\n)'.format( self.__class__.__name__, repr(self.zeros), repr(self.poles), repr(self.gain), ) @property def zeros(self): """Zeros of the `ZerosPolesGain` system.""" return self._zeros @zeros.setter def zeros(self, zeros): self._zeros = atleast_1d(zeros) # Update dimensions if len(self.zeros.shape) > 1: self.outputs, self.inputs = self.zeros.shape else: self.outputs = 1 self.inputs = 1 @property def poles(self): """Poles of the `ZerosPolesGain` system.""" return self._poles @poles.setter def poles(self, poles): self._poles = atleast_1d(poles) @property def gain(self): """Gain of the `ZerosPolesGain` system.""" return self._gain @gain.setter def gain(self, gain): self._gain = gain def _copy(self, system): """ Copy the parameters of another `ZerosPolesGain` system. Parameters ---------- system : instance of `ZerosPolesGain` The zeros, poles gain system that is to be copied """ self.poles = system.poles self.zeros = system.zeros self.gain = system.gain def to_tf(self): """ Convert system representation to `TransferFunction`. Returns ------- sys : instance of `TransferFunction` Transfer function of the current system """ return TransferFunction(*zpk2tf(self.zeros, self.poles, self.gain)) def to_zpk(self): """ Return a copy of the current 'ZerosPolesGain' system. Returns ------- sys : instance of `ZerosPolesGain` The current system (copy) """ return copy.deepcopy(self) def to_ss(self): """ Convert system representation to `StateSpace`. Returns ------- sys : instance of `StateSpace` State space model of the current system """ return StateSpace(*zpk2ss(self.zeros, self.poles, self.gain)) class StateSpace(lti): """ Linear Time Invariant system class in state-space form. Represents the system as the first order differential equation :math:`\dot{x} = A x + B u`. Parameters ---------- *system : arguments The `StateSpace` class can be instantiated with 1 or 4 arguments. The following gives the number of input arguments and their interpretation: * 1: `lti` system: (`StateSpace`, `TransferFunction` or `ZerosPolesGain`) * 4: array_like: (A, B, C, D) See Also -------- TransferFunction, ZerosPolesGain, lti ss2zpk, ss2tf, zpk2sos Notes ----- Changing the value of properties that are not part of the `StateSpace` system representation (such as `zeros` or `poles`) is very inefficient and may lead to numerical inaccuracies. """ def __new__(cls, *system): """Handle object conversion if input is an instance of `lti`""" if len(system) == 1 and isinstance(system[0], lti): return system[0].to_ss() # No special conversion needed return super(StateSpace, cls).__new__(cls) def __init__(self, *system): """Initialize the state space LTI system.""" # Conversion of lti instances is handled in __new__ if isinstance(system[0], lti): return super(StateSpace, self).__init__(self, *system) self._A = None self._B = None self._C = None self._D = None self.A, self.B, self.C, self.D = abcd_normalize(*system) def __repr__(self): """Return representation of the `StateSpace` system.""" return '{0}(\n{1},\n{2},\n{3},\n{4}\n)'.format( self.__class__.__name__, repr(self.A), repr(self.B), repr(self.C), repr(self.D), ) @property def A(self): """State matrix of the `StateSpace` system.""" return self._A @A.setter def A(self, A): self._A = _atleast_2d_or_none(A) @property def B(self): """Input matrix of the `StateSpace` system.""" return self._B @B.setter def B(self, B): self._B = _atleast_2d_or_none(B) self.inputs = self.B.shape[-1] @property def C(self): """Output matrix of the `StateSpace` system.""" return self._C @C.setter def C(self, C): self._C = _atleast_2d_or_none(C) self.outputs = self.C.shape[0] @property def D(self): """Feedthrough matrix of the `StateSpace` system.""" return self._D @D.setter def D(self, D): self._D = _atleast_2d_or_none(D) def _copy(self, system): """ Copy the parameters of another `StateSpace` system. Parameters ---------- system : instance of `StateSpace` The state-space system that is to be copied """ self.A = system.A self.B = system.B self.C = system.C self.D = system.D def to_tf(self, **kwargs): """ Convert system representation to `TransferFunction`. Parameters ---------- kwargs : dict, optional Additional keywords passed to `ss2zpk` Returns ------- sys : instance of `TransferFunction` Transfer function of the current system """ return TransferFunction(*ss2tf(self._A, self._B, self._C, self._D, **kwargs)) def to_zpk(self, **kwargs): """ Convert system representation to `ZerosPolesGain`. Parameters ---------- kwargs : dict, optional Additional keywords passed to `ss2zpk` Returns ------- sys : instance of `ZerosPolesGain` Zeros, poles, gain representation of the current system """ return ZerosPolesGain(*ss2zpk(self._A, self._B, self._C, self._D, **kwargs)) def to_ss(self): """ Return a copy of the current `StateSpace` system. Returns ------- sys : instance of `StateSpace` The current system (copy) """ return copy.deepcopy(self) def lsim2(system, U=None, T=None, X0=None, **kwargs): """ Simulate output of a continuous-time linear system, by using the ODE solver `scipy.integrate.odeint`. Parameters ---------- system : an instance of the LTI class or a tuple describing the system. The following gives the number of elements in the tuple and the interpretation: * 2: (num, den) * 3: (zeros, poles, gain) * 4: (A, B, C, D) U : array_like (1D or 2D), optional An input array describing the input at each time T. Linear interpolation is used between given times. If there are multiple inputs, then each column of the rank-2 array represents an input. If U is not given, the input is assumed to be zero. T : array_like (1D or 2D), optional The time steps at which the input is defined and at which the output is desired. The default is 101 evenly spaced points on the interval [0,10.0]. X0 : array_like (1D), optional The initial condition of the state vector. If `X0` is not given, the initial conditions are assumed to be 0. kwargs : dict Additional keyword arguments are passed on to the function `odeint`. See the notes below for more details. Returns ------- T : 1D ndarray The time values for the output. yout : ndarray The response of the system. xout : ndarray The time-evolution of the state-vector. Notes ----- This function uses `scipy.integrate.odeint` to solve the system's differential equations. Additional keyword arguments given to `lsim2` are passed on to `odeint`. See the documentation for `scipy.integrate.odeint` for the full list of arguments. """ if isinstance(system, lti): sys = system.to_ss() else: sys = lti(*system).to_ss() if X0 is None: X0 = zeros(sys.B.shape[0], sys.A.dtype) if T is None: # XXX T should really be a required argument, but U was # changed from a required positional argument to a keyword, # and T is after U in the argument list. So we either: change # the API and move T in front of U; check here for T being # None and raise an exception; or assign a default value to T # here. This code implements the latter. T = linspace(0, 10.0, 101) T = atleast_1d(T) if len(T.shape) != 1: raise ValueError("T must be a rank-1 array.") if U is not None: U = atleast_1d(U) if len(U.shape) == 1: U = U.reshape(-1, 1) sU = U.shape if sU[0] != len(T): raise ValueError("U must have the same number of rows " "as elements in T.") if sU[1] != sys.inputs: raise ValueError("The number of inputs in U (%d) is not " "compatible with the number of system " "inputs (%d)" % (sU[1], sys.inputs)) # Create a callable that uses linear interpolation to # calculate the input at any time. ufunc = interpolate.interp1d(T, U, kind='linear', axis=0, bounds_error=False) def fprime(x, t, sys, ufunc): """The vector field of the linear system.""" return dot(sys.A, x) + squeeze(dot(sys.B, nan_to_num(ufunc([t])))) xout = integrate.odeint(fprime, X0, T, args=(sys, ufunc), **kwargs) yout = dot(sys.C, transpose(xout)) + dot(sys.D, transpose(U)) else: def fprime(x, t, sys): """The vector field of the linear system.""" return dot(sys.A, x) xout = integrate.odeint(fprime, X0, T, args=(sys,), **kwargs) yout = dot(sys.C, transpose(xout)) return T, squeeze(transpose(yout)), xout def _cast_to_array_dtype(in1, in2): """Cast array to dtype of other array, while avoiding ComplexWarning. Those can be raised when casting complex to real. """ if numpy.issubdtype(in2.dtype, numpy.float): # dtype to cast to is not complex, so use .real in1 = in1.real.astype(in2.dtype) else: in1 = in1.astype(in2.dtype) return in1 def lsim(system, U, T, X0=None, interp=True): """ Simulate output of a continuous-time linear system. Parameters ---------- system : an instance of the LTI class or a tuple describing the system. The following gives the number of elements in the tuple and the interpretation: * 2: (num, den) * 3: (zeros, poles, gain) * 4: (A, B, C, D) U : array_like An input array describing the input at each time `T` (interpolation is assumed between given times). If there are multiple inputs, then each column of the rank-2 array represents an input. If U = 0 or None, a zero input is used. T : array_like The time steps at which the input is defined and at which the output is desired. Must be nonnegative, increasing, and equally spaced. X0 : array_like, optional The initial conditions on the state vector (zero by default). interp : bool, optional Whether to use linear (True, the default) or zero-order-hold (False) interpolation for the input array. Returns ------- T : 1D ndarray Time values for the output. yout : 1D ndarray System response. xout : ndarray Time evolution of the state vector. Examples -------- Simulate a double integrator y'' = u, with a constant input u = 1 >>> from scipy import signal >>> system = signal.lti([[0., 1.], [0., 0.]], [[0.], [1.]], [[1., 0.]], 0.) >>> t = np.linspace(0, 5) >>> u = np.ones_like(t) >>> tout, y, x = signal.lsim(system, u, t) >>> import matplotlib.pyplot as plt >>> plt.plot(t, y) """ if isinstance(system, lti): sys = system.to_ss() else: sys = lti(*system).to_ss() T = atleast_1d(T) if len(T.shape) != 1: raise ValueError("T must be a rank-1 array.") A, B, C, D = map(np.asarray, (sys.A, sys.B, sys.C, sys.D)) n_states = A.shape[0] n_inputs = B.shape[1] n_steps = T.size if X0 is None: X0 = zeros(n_states, sys.A.dtype) xout = zeros((n_steps, n_states), sys.A.dtype) if T[0] == 0: xout[0] = X0 elif T[0] > 0: # step forward to initial time, with zero input xout[0] = dot(X0, linalg.expm(transpose(A) * T[0])) else: raise ValueError("Initial time must be nonnegative") no_input = (U is None or (isinstance(U, (int, float)) and U == 0.) or not np.any(U)) if n_steps == 1: yout = squeeze(dot(xout, transpose(C))) if not no_input: yout += squeeze(dot(U, transpose(D))) return T, squeeze(yout), squeeze(xout) dt = T[1] - T[0] if not np.allclose((T[1:] - T[:-1]) / dt, 1.0): warnings.warn("Non-uniform timesteps are deprecated. Results may be " "slow and/or inaccurate.", DeprecationWarning) return lsim2(system, U, T, X0) if no_input: # Zero input: just use matrix exponential # take transpose because state is a row vector expAT_dt = linalg.expm(transpose(A) * dt) for i in xrange(1, n_steps): xout[i] = dot(xout[i-1], expAT_dt) yout = squeeze(dot(xout, transpose(C))) return T, squeeze(yout), squeeze(xout) # Nonzero input U = atleast_1d(U) if U.ndim == 1: U = U[:, np.newaxis] if U.shape[0] != n_steps: raise ValueError("U must have the same number of rows " "as elements in T.") if U.shape[1] != n_inputs: raise ValueError("System does not define that many inputs.") if not interp: # Zero-order hold # Algorithm: to integrate from time 0 to time dt, we solve # xdot = A x + B u, x(0) = x0 # udot = 0, u(0) = u0. # # Solution is # [ x(dt) ] [ A*dt B*dt ] [ x0 ] # [ u(dt) ] = exp [ 0 0 ] [ u0 ] M = np.vstack([np.hstack([A * dt, B * dt]), np.zeros((n_inputs, n_states + n_inputs))]) # transpose everything because the state and input are row vectors expMT = linalg.expm(transpose(M)) Ad = expMT[:n_states, :n_states] Bd = expMT[n_states:, :n_states] for i in xrange(1, n_steps): xout[i] = dot(xout[i-1], Ad) + dot(U[i-1], Bd) else: # Linear interpolation between steps # Algorithm: to integrate from time 0 to time dt, with linear # interpolation between inputs u(0) = u0 and u(dt) = u1, we solve # xdot = A x + B u, x(0) = x0 # udot = (u1 - u0) / dt, u(0) = u0. # # Solution is # [ x(dt) ] [ A*dt B*dt 0 ] [ x0 ] # [ u(dt) ] = exp [ 0 0 I ] [ u0 ] # [u1 - u0] [ 0 0 0 ] [u1 - u0] M = np.vstack([np.hstack([A * dt, B * dt, np.zeros((n_states, n_inputs))]), np.hstack([np.zeros((n_inputs, n_states + n_inputs)), np.identity(n_inputs)]), np.zeros((n_inputs, n_states + 2 * n_inputs))]) expMT = linalg.expm(transpose(M)) Ad = expMT[:n_states, :n_states] Bd1 = expMT[n_states+n_inputs:, :n_states] Bd0 = expMT[n_states:n_states + n_inputs, :n_states] - Bd1 for i in xrange(1, n_steps): xout[i] = (dot(xout[i-1], Ad) + dot(U[i-1], Bd0) + dot(U[i], Bd1)) yout = (squeeze(dot(xout, transpose(C))) + squeeze(dot(U, transpose(D)))) return T, squeeze(yout), squeeze(xout) def _default_response_times(A, n): """Compute a reasonable set of time samples for the response time. This function is used by `impulse`, `impulse2`, `step` and `step2` to compute the response time when the `T` argument to the function is None. Parameters ---------- A : ndarray The system matrix, which is square. n : int The number of time samples to generate. Returns ------- t : ndarray The 1-D array of length `n` of time samples at which the response is to be computed. """ # Create a reasonable time interval. # TODO: This could use some more work. # For example, what is expected when the system is unstable? vals = linalg.eigvals(A) r = min(abs(real(vals))) if r == 0.0: r = 1.0 tc = 1.0 / r t = linspace(0.0, 7 * tc, n) return t def impulse(system, X0=None, T=None, N=None): """Impulse response of continuous-time system. Parameters ---------- system : an instance of the LTI class or a tuple of array_like describing the system. The following gives the number of elements in the tuple and the interpretation: * 2 (num, den) * 3 (zeros, poles, gain) * 4 (A, B, C, D) X0 : array_like, optional Initial state-vector. Defaults to zero. T : array_like, optional Time points. Computed if not given. N : int, optional The number of time points to compute (if `T` is not given). Returns ------- T : ndarray A 1-D array of time points. yout : ndarray A 1-D array containing the impulse response of the system (except for singularities at zero). """ if isinstance(system, lti): sys = system.to_ss() else: sys = lti(*system).to_ss() if X0 is None: X = squeeze(sys.B) else: X = squeeze(sys.B + X0) if N is None: N = 100 if T is None: T = _default_response_times(sys.A, N) else: T = asarray(T) _, h, _ = lsim(sys, 0., T, X, interp=False) return T, h def impulse2(system, X0=None, T=None, N=None, **kwargs): """ Impulse response of a single-input, continuous-time linear system. Parameters ---------- system : an instance of the LTI class or a tuple of array_like describing the system. The following gives the number of elements in the tuple and the interpretation: * 2 (num, den) * 3 (zeros, poles, gain) * 4 (A, B, C, D) X0 : 1-D array_like, optional The initial condition of the state vector. Default: 0 (the zero vector). T : 1-D array_like, optional The time steps at which the input is defined and at which the output is desired. If `T` is not given, the function will generate a set of time samples automatically. N : int, optional Number of time points to compute. Default: 100. kwargs : various types Additional keyword arguments are passed on to the function `scipy.signal.lsim2`, which in turn passes them on to `scipy.integrate.odeint`; see the latter's documentation for information about these arguments. Returns ------- T : ndarray The time values for the output. yout : ndarray The output response of the system. See Also -------- impulse, lsim2, integrate.odeint Notes ----- The solution is generated by calling `scipy.signal.lsim2`, which uses the differential equation solver `scipy.integrate.odeint`. .. versionadded:: 0.8.0 Examples -------- Second order system with a repeated root: x''(t) + 2*x(t) + x(t) = u(t) >>> from scipy import signal >>> system = ([1.0], [1.0, 2.0, 1.0]) >>> t, y = signal.impulse2(system) >>> import matplotlib.pyplot as plt >>> plt.plot(t, y) """ if isinstance(system, lti): sys = system.to_ss() else: sys = lti(*system).to_ss() B = sys.B if B.shape[-1] != 1: raise ValueError("impulse2() requires a single-input system.") B = B.squeeze() if X0 is None: X0 = zeros_like(B) if N is None: N = 100 if T is None: T = _default_response_times(sys.A, N) # Move the impulse in the input to the initial conditions, and then # solve using lsim2(). ic = B + X0 Tr, Yr, Xr = lsim2(sys, T=T, X0=ic, **kwargs) return Tr, Yr def step(system, X0=None, T=None, N=None): """Step response of continuous-time system. Parameters ---------- system : an instance of the LTI class or a tuple of array_like describing the system. The following gives the number of elements in the tuple and the interpretation: * 2 (num, den) * 3 (zeros, poles, gain) * 4 (A, B, C, D) X0 : array_like, optional Initial state-vector (default is zero). T : array_like, optional Time points (computed if not given). N : int, optional Number of time points to compute if `T` is not given. Returns ------- T : 1D ndarray Output time points. yout : 1D ndarray Step response of system. See also -------- scipy.signal.step2 """ if isinstance(system, lti): sys = system.to_ss() else: sys = lti(*system).to_ss() if N is None: N = 100 if T is None: T = _default_response_times(sys.A, N) else: T = asarray(T) U = ones(T.shape, sys.A.dtype) vals = lsim(sys, U, T, X0=X0, interp=False) return vals[0], vals[1] def step2(system, X0=None, T=None, N=None, **kwargs): """Step response of continuous-time system. This function is functionally the same as `scipy.signal.step`, but it uses the function `scipy.signal.lsim2` to compute the step response. Parameters ---------- system : an instance of the LTI class or a tuple of array_like describing the system. The following gives the number of elements in the tuple and the interpretation: * 2 (num, den) * 3 (zeros, poles, gain) * 4 (A, B, C, D) X0 : array_like, optional Initial state-vector (default is zero). T : array_like, optional Time points (computed if not given). N : int, optional Number of time points to compute if `T` is not given. kwargs : various types Additional keyword arguments are passed on the function `scipy.signal.lsim2`, which in turn passes them on to `scipy.integrate.odeint`. See the documentation for `scipy.integrate.odeint` for information about these arguments. Returns ------- T : 1D ndarray Output time points. yout : 1D ndarray Step response of system. See also -------- scipy.signal.step Notes ----- .. versionadded:: 0.8.0 """ if isinstance(system, lti): sys = system.to_ss() else: sys = lti(*system).to_ss() if N is None: N = 100 if T is None: T = _default_response_times(sys.A, N) else: T = asarray(T) U = ones(T.shape, sys.A.dtype) vals = lsim2(sys, U, T, X0=X0, **kwargs) return vals[0], vals[1] def bode(system, w=None, n=100): """ Calculate Bode magnitude and phase data of a continuous-time system. Parameters ---------- system : an instance of the LTI class or a tuple describing the system. The following gives the number of elements in the tuple and the interpretation: * 2 (num, den) * 3 (zeros, poles, gain) * 4 (A, B, C, D) w : array_like, optional Array of frequencies (in rad/s). Magnitude and phase data is calculated for every value in this array. If not given a reasonable set will be calculated. n : int, optional Number of frequency points to compute if `w` is not given. The `n` frequencies are logarithmically spaced in an interval chosen to include the influence of the poles and zeros of the system. Returns ------- w : 1D ndarray Frequency array [rad/s] mag : 1D ndarray Magnitude array [dB] phase : 1D ndarray Phase array [deg] Notes ----- .. versionadded:: 0.11.0 Examples -------- >>> from scipy import signal >>> import matplotlib.pyplot as plt >>> s1 = signal.lti([1], [1, 1]) >>> w, mag, phase = signal.bode(s1) >>> plt.figure() >>> plt.semilogx(w, mag) # Bode magnitude plot >>> plt.figure() >>> plt.semilogx(w, phase) # Bode phase plot >>> plt.show() """ w, y = freqresp(system, w=w, n=n) mag = 20.0 * numpy.log10(abs(y)) phase = numpy.unwrap(numpy.arctan2(y.imag, y.real)) * 180.0 / numpy.pi return w, mag, phase def freqresp(system, w=None, n=10000): """Calculate the frequency response of a continuous-time system. Parameters ---------- system : an instance of the LTI class or a tuple describing the system. The following gives the number of elements in the tuple and the interpretation: * 2 (num, den) * 3 (zeros, poles, gain) * 4 (A, B, C, D) w : array_like, optional Array of frequencies (in rad/s). Magnitude and phase data is calculated for every value in this array. If not given a reasonable set will be calculated. n : int, optional Number of frequency points to compute if `w` is not given. The `n` frequencies are logarithmically spaced in an interval chosen to include the influence of the poles and zeros of the system. Returns ------- w : 1D ndarray Frequency array [rad/s] H : 1D ndarray Array of complex magnitude values Examples -------- # Generating the Nyquist plot of a transfer function >>> from scipy import signal >>> import matplotlib.pyplot as plt >>> s1 = signal.lti([], [1, 1, 1], [5]) # transfer function: H(s) = 5 / (s-1)^3 >>> w, H = signal.freqresp(s1) >>> plt.figure() >>> plt.plot(H.real, H.imag, "b") >>> plt.plot(H.real, -H.imag, "r") >>> plt.show() """ if isinstance(system, lti): sys = system.to_tf() else: sys = lti(*system).to_tf() if sys.inputs != 1 or sys.outputs != 1: raise ValueError("freqresp() requires a SISO (single input, single " "output) system.") if w is not None: worN = w else: worN = n # In the call to freqs(), sys.num.ravel() is used because there are # cases where sys.num is a 2-D array with a single row. w, h = freqs(sys.num.ravel(), sys.den, worN=worN) return w, h # This class will be used by place_poles to return its results # see http://code.activestate.com/recipes/52308/ class Bunch: def __init__(self, **kwds): self.__dict__.update(kwds) def _valid_inputs(A, B, poles, method, rtol, maxiter): """ Check the poles come in complex conjugage pairs Check shapes of A, B and poles are compatible. Check the method chosen is compatible with provided poles Return update method to use and ordered poles """ poles = np.asarray(poles) if poles.ndim > 1: raise ValueError("Poles must be a 1D array like.") # Will raise ValueError if poles do not come in complex conjugates pairs poles = _order_complex_poles(poles) if A.ndim > 2: raise ValueError("A must be a 2D array/matrix.") if B.ndim > 2: raise ValueError("B must be a 2D array/matrix") if A.shape[0] != A.shape[1]: raise ValueError("A must be square") if len(poles) > A.shape[0]: raise ValueError("maximum number of poles is %d but you asked for %d" % (A.shape[0], len(poles))) if len(poles) < A.shape[0]: raise ValueError("number of poles is %d but you should provide %d" % (len(poles), A.shape[0])) r = np.linalg.matrix_rank(B) for p in poles: if sum(p == poles) > r: raise ValueError("at least one of the requested pole is repeated " "more than rank(B) times") # Choose update method update_loop = _YT_loop if method not in ('KNV0','YT'): raise ValueError("The method keyword must be one of 'YT' or 'KNV0'") if method == "KNV0": update_loop = _KNV0_loop if not all(np.isreal(poles)): raise ValueError("Complex poles are not supported by KNV0") if maxiter < 1: raise ValueError("maxiter must be at least equal to 1") # We do not check rtol <= 0 as the user can use a negative rtol to # force maxiter iterations if rtol > 1: raise ValueError("rtol can not be greater than 1") return update_loop, poles def _order_complex_poles(poles): """ Check we have complex conjugates pairs and reorder P according to YT, ie real_poles, complex_i, conjugate complex_i, .... The lexicographic sort on the complex poles is added to help the user to compare sets of poles. """ ordered_poles = np.sort(poles[np.isreal(poles)]) im_poles = [] for p in np.sort(poles[np.imag(poles) < 0]): if np.conj(p) in poles: im_poles.extend((p, np.conj(p))) ordered_poles = np.hstack((ordered_poles, im_poles)) if poles.shape[0] != len(ordered_poles): raise ValueError("Complex poles must come with their conjugates") return ordered_poles def _KNV0(B, ker_pole, transfer_matrix, j, poles): """ Algorithm "KNV0" Kautsky et Al. Robust pole assignment in linear state feedback, Int journal of Control 1985, vol 41 p 1129->1155 http://la.epfl.ch/files/content/sites/la/files/ users/105941/public/KautskyNicholsDooren """ # Remove xj form the base transfer_matrix_not_j = np.delete(transfer_matrix, j, axis=1) # If we QR this matrix in full mode Q=Q0|Q1 # then Q1 will be a single column orthogonnal to # Q0, that's what we are looking for ! # After merge of gh-4249 great speed improvements could be achieved # using QR updates instead of full QR in the line below # To debug with numpy qr uncomment the line below # Q, R = np.linalg.qr(transfer_matrix_not_j, mode="complete") Q, R = s_qr(transfer_matrix_not_j, mode="full") mat_ker_pj = np.dot(ker_pole[j], ker_pole[j].T) yj = np.dot(mat_ker_pj, Q[:, -1]) # If Q[:, -1] is "almost" orthogonal to ker_pole[j] its # projection into ker_pole[j] will yield a vector # close to 0. As we are looking for a vector in ker_pole[j] # simply stick with transfer_matrix[:, j] (unless someone provides me with # a better choice ?) if not np.allclose(yj, 0): xj = yj/np.linalg.norm(yj) transfer_matrix[:, j] = xj # KNV does not support complex poles, using YT technique the two lines # below seem to work 9 out of 10 times but it is not reliable enough: # transfer_matrix[:, j]=real(xj) # transfer_matrix[:, j+1]=imag(xj) # Add this at the beginning of this function if you wish to test # complex support: # if ~np.isreal(P[j]) and (j>=B.shape[0]-1 or P[j]!=np.conj(P[j+1])): # return # Problems arise when imag(xj)=>0 I have no idea on how to fix this def _YT_real(ker_pole, Q, transfer_matrix, i, j): """ Applies algorithm from YT section 6.1 page 19 related to real pairs """ # step 1 page 19 u = Q[:, -2, np.newaxis] v = Q[:, -1, np.newaxis] # step 2 page 19 m = np.dot(np.dot(ker_pole[i].T, np.dot(u, v.T) - np.dot(v, u.T)), ker_pole[j]) # step 3 page 19 um, sm, vm = np.linalg.svd(m) # mu1, mu2 two first columns of U => 2 first lines of U.T mu1, mu2 = um.T[:2, :, np.newaxis] # VM is V.T with numpy we want the first two lines of V.T nu1, nu2 = vm[:2, :, np.newaxis] # what follows is a rough python translation of the formulas # in section 6.2 page 20 (step 4) transfer_matrix_j_mo_transfer_matrix_j = np.vstack(( transfer_matrix[:, i, np.newaxis], transfer_matrix[:, j, np.newaxis])) if not np.allclose(sm[0], sm[1]): ker_pole_imo_mu1 = np.dot(ker_pole[i], mu1) ker_pole_i_nu1 = np.dot(ker_pole[j], nu1) ker_pole_mu_nu = np.vstack((ker_pole_imo_mu1, ker_pole_i_nu1)) else: ker_pole_ij = np.vstack(( np.hstack((ker_pole[i], np.zeros(ker_pole[i].shape))), np.hstack((np.zeros(ker_pole[j].shape), ker_pole[j])) )) mu_nu_matrix = np.vstack( (np.hstack((mu1, mu2)), np.hstack((nu1, nu2))) ) ker_pole_mu_nu = np.dot(ker_pole_ij, mu_nu_matrix) transfer_matrix_ij = np.dot(np.dot(ker_pole_mu_nu, ker_pole_mu_nu.T), transfer_matrix_j_mo_transfer_matrix_j) if not np.allclose(transfer_matrix_ij, 0): transfer_matrix_ij = (np.sqrt(2)*transfer_matrix_ij / np.linalg.norm(transfer_matrix_ij)) transfer_matrix[:, i] = transfer_matrix_ij[ :transfer_matrix[:, i].shape[0], 0 ] transfer_matrix[:, j] = transfer_matrix_ij[ transfer_matrix[:, i].shape[0]:, 0 ] else: # As in knv0 if transfer_matrix_j_mo_transfer_matrix_j is orthogonal to # Vect{ker_pole_mu_nu} assign transfer_matrixi/transfer_matrix_j to # ker_pole_mu_nu and iterate. As we are looking for a vector in # Vect{Matker_pole_MU_NU} (see section 6.1 page 19) this might help # (that's a guess, not a claim !) transfer_matrix[:, i] = ker_pole_mu_nu[ :transfer_matrix[:, i].shape[0], 0 ] transfer_matrix[:, j] = ker_pole_mu_nu[ transfer_matrix[:, i].shape[0]:, 0 ] def _YT_complex(ker_pole, Q, transfer_matrix, i, j): """ Applies algorithm from YT section 6.2 page 20 related to complex pairs """ # step 1 page 20 ur = np.sqrt(2)*Q[:, -2, np.newaxis] ui = np.sqrt(2)*Q[:, -1, np.newaxis] u = ur + 1j*ui # step 2 page 20 ker_pole_ij = ker_pole[i] m = np.dot(np.dot(np.conj(ker_pole_ij.T), np.dot(u, np.conj(u).T) - np.dot(np.conj(u), u.T)), ker_pole_ij) # step 3 page 20 e_val, e_vec = np.linalg.eig(m) # sort eigenvalues according to their module e_val_idx = np.argsort(np.abs(e_val)) mu1 = e_vec[:, e_val_idx[-1], np.newaxis] mu2 = e_vec[:, e_val_idx[-2], np.newaxis] # what follows is a rough python translation of the formulas # in section 6.2 page 20 (step 4) # remember transfer_matrix_i has been split as # transfer_matrix[i]=real(transfer_matrix_i) and # transfer_matrix[j]=imag(transfer_matrix_i) transfer_matrix_j_mo_transfer_matrix_j = ( transfer_matrix[:, i, np.newaxis] + 1j*transfer_matrix[:, j, np.newaxis] ) if not np.allclose(np.abs(e_val[e_val_idx[-1]]), np.abs(e_val[e_val_idx[-2]])): ker_pole_mu = np.dot(ker_pole_ij, mu1) else: mu1_mu2_matrix = np.hstack((mu1, mu2)) ker_pole_mu = np.dot(ker_pole_ij, mu1_mu2_matrix) transfer_matrix_i_j = np.dot(np.dot(ker_pole_mu, np.conj(ker_pole_mu.T)), transfer_matrix_j_mo_transfer_matrix_j) if not np.allclose(transfer_matrix_i_j, 0): transfer_matrix_i_j = (transfer_matrix_i_j / np.linalg.norm(transfer_matrix_i_j)) transfer_matrix[:, i] = np.real(transfer_matrix_i_j[:, 0]) transfer_matrix[:, j] = np.imag(transfer_matrix_i_j[:, 0]) else: # same idea as in YT_real transfer_matrix[:, i] = np.real(ker_pole_mu[:, 0]) transfer_matrix[:, j] = np.imag(ker_pole_mu[:, 0]) def _YT_loop(ker_pole, transfer_matrix, poles, B, maxiter, rtol): """ Algorithm "YT" Tits, Yang. Globally Convergent Algorithms for Robust Pole Assignment by State Feedback http://drum.lib.umd.edu/handle/1903/5598 The poles P have to be sorted accordingly to section 6.2 page 20 """ # The IEEE edition of the YT paper gives useful information on the # optimal update order for the real poles in order to minimize the number # of times we have to loop over all poles, see page 1442 nb_real = poles[np.isreal(poles)].shape[0] # hnb => Half Nb Real hnb = nb_real // 2 # Stick to the indices in the paper and then remove one to get numpy array # index it is a bit easier to link the code to the paper this way even if it # is not very clean. The paper is unclear about what should be done when # there is only one real pole => use KNV0 on this real pole seem to work if nb_real > 0: #update the biggest real pole with the smallest one update_order = [[nb_real], [1]] else: update_order = [[],[]] r_comp = np.arange(nb_real+1, len(poles)+1, 2) # step 1.a r_p = np.arange(1, hnb+nb_real % 2) update_order[0].extend(2*r_p) update_order[1].extend(2*r_p+1) # step 1.b update_order[0].extend(r_comp) update_order[1].extend(r_comp+1) # step 1.c r_p = np.arange(1, hnb+1) update_order[0].extend(2*r_p-1) update_order[1].extend(2*r_p) # step 1.d if hnb == 0 and np.isreal(poles[0]): update_order[0].append(1) update_order[1].append(1) update_order[0].extend(r_comp) update_order[1].extend(r_comp+1) # step 2.a r_j = np.arange(2, hnb+nb_real % 2) for j in r_j: for i in range(1, hnb+1): update_order[0].append(i) update_order[1].append(i+j) # step 2.b if hnb == 0 and np.isreal(poles[0]): update_order[0].append(1) update_order[1].append(1) update_order[0].extend(r_comp) update_order[1].extend(r_comp+1) # step 2.c r_j = np.arange(2, hnb+nb_real % 2) for j in r_j: for i in range(hnb+1, nb_real+1): idx_1 = i+j if idx_1 > nb_real: idx_1 = i+j-nb_real update_order[0].append(i) update_order[1].append(idx_1) # step 2.d if hnb == 0 and np.isreal(poles[0]): update_order[0].append(1) update_order[1].append(1) update_order[0].extend(r_comp) update_order[1].extend(r_comp+1) # step 3.a for i in range(1, hnb+1): update_order[0].append(i) update_order[1].append(i+hnb) # step 3.b if hnb == 0 and np.isreal(poles[0]): update_order[0].append(1) update_order[1].append(1) update_order[0].extend(r_comp) update_order[1].extend(r_comp+1) update_order = np.array(update_order).T-1 stop = False nb_try = 0 while nb_try < maxiter and not stop: det_transfer_matrixb = np.abs(np.linalg.det(transfer_matrix)) for i, j in update_order: if i == j: assert i == 0, "i!=0 for KNV call in YT" assert np.isreal(poles[i]), "calling KNV on a complex pole" _KNV0(B, ker_pole, transfer_matrix, i, poles) else: transfer_matrix_not_i_j = np.delete(transfer_matrix, (i, j), axis=1) # after merge of gh-4249 great speed improvements could be # achieved using QR updates instead of full QR in the line below #to debug with numpy qr uncomment the line below #Q, _ = np.linalg.qr(transfer_matrix_not_i_j, mode="complete") Q, _ = s_qr(transfer_matrix_not_i_j, mode="full") if np.isreal(poles[i]): assert np.isreal(poles[j]), "mixing real and complex " + \ "in YT_real" + str(poles) _YT_real(ker_pole, Q, transfer_matrix, i, j) else: assert ~np.isreal(poles[i]), "mixing real and complex " + \ "in YT_real" + str(poles) _YT_complex(ker_pole, Q, transfer_matrix, i, j) det_transfer_matrix = np.max((np.sqrt(np.spacing(1)), np.abs(np.linalg.det(transfer_matrix)))) cur_rtol = np.abs( (det_transfer_matrix - det_transfer_matrixb) / det_transfer_matrix) if cur_rtol < rtol and det_transfer_matrix > np.sqrt(np.spacing(1)): # Convergence test from YT page 21 stop = True nb_try += 1 return stop, cur_rtol, nb_try def _KNV0_loop(ker_pole, transfer_matrix, poles, B, maxiter, rtol): """ Loop over all poles one by one and apply KNV method 0 algorithm """ # This method is useful only because we need to be able to call # _KNV0 from YT without looping over all poles, otherwise it would # have been fine to mix _KNV0_loop and _KNV0 in a single function stop = False nb_try = 0 while nb_try < maxiter and not stop: det_transfer_matrixb = np.abs(np.linalg.det(transfer_matrix)) for j in range(B.shape[0]): _KNV0(B, ker_pole, transfer_matrix, j, poles) det_transfer_matrix = np.max((np.sqrt(np.spacing(1)), np.abs(np.linalg.det(transfer_matrix)))) cur_rtol = np.abs((det_transfer_matrix - det_transfer_matrixb) / det_transfer_matrix) if cur_rtol < rtol and det_transfer_matrix > np.sqrt(np.spacing(1)): # Convergence test from YT page 21 stop = True nb_try += 1 return stop, cur_rtol, nb_try def place_poles(A, B, poles, method="YT", rtol=1e-3, maxiter=30): """ Compute K such that eigenvalues (A - dot(B, K))=poles. K is the gain matrix such as the plant described by the linear system ``AX+BU`` will have its closed-loop poles, i.e the eigenvalues ``A - B*K``, as close as possible to those asked for in poles. SISO, MISO and MIMO systems are supported. Parameters ---------- A, B : ndarray State-space representation of linear system ``AX + BU``. poles : array_like Desired real poles and/or complex conjugates poles. Complex poles are only supported with ``method="YT"`` (default). method: {'YT', 'KNV0'}, optional Which method to choose to find the gain matrix K. One of: - 'YT': Yang Tits - 'KNV0': Kautsky, Nichols, Van Dooren update method 0 See References and Notes for details on the algorithms. rtol: float, optional After each iteration the determinant of the eigenvectors of ``A - B*K`` is compared to its previous value, when the relative error between these two values becomes lower than `rtol` the algorithm stops. Default is 1e-3. maxiter: int, optional Maximum number of iterations to compute the gain matrix. Default is 30. Returns ------- full_state_feedback : Bunch object full_state_feedback is composed of: gain_matrix : 1-D ndarray The closed loop matrix K such as the eigenvalues of ``A-BK`` are as close as possible to the requested poles. computed_poles : 1-D ndarray The poles corresponding to ``A-BK`` sorted as first the real poles in increasing order, then the complex congugates in lexicographic order. requested_poles : 1-D ndarray The poles the algorithm was asked to place sorted as above, they may differ from what was achieved. X : 2-D ndarray The transfer matrix such as ``X * diag(poles) = (A - B*K)*X`` (see Notes) rtol : float The relative tolerance achieved on ``det(X)`` (see Notes). `rtol` will be NaN if it is possible to solve the system ``diag(poles) = (A - B*K)``, or 0 when the optimization algorithms can't do anything i.e when ``B.shape[1] == 1``. nb_iter : int The number of iterations performed before converging. `nb_iter` will be NaN if it is possible to solve the system ``diag(poles) = (A - B*K)``, or 0 when the optimization algorithms can't do anything i.e when ``B.shape[1] == 1``. Notes ----- The Tits and Yang (YT), [2]_ paper is an update of the original Kautsky et al. (KNV) paper [1]_. KNV relies on rank-1 updates to find the transfer matrix X such that ``X * diag(poles) = (A - B*K)*X``, whereas YT uses rank-2 updates. This yields on average more robust solutions (see [2]_ pp 21-22), furthermore the YT algorithm supports complex poles whereas KNV does not in its original version. Only update method 0 proposed by KNV has been implemented here, hence the name ``'KNV0'``. KNV extended to complex poles is used in Matlab's ``place`` function, YT is distributed under a non-free licence by Slicot under the name ``robpole``. It is unclear and undocumented how KNV0 has been extended to complex poles (Tits and Yang claim on page 14 of their paper that their method can not be used to extend KNV to complex poles), therefore only YT supports them in this implementation. As the solution to the problem of pole placement is not unique for MIMO systems, both methods start with a tentative transfer matrix which is altered in various way to increase its determinant. Both methods have been proven to converge to a stable solution, however depending on the way the initial transfer matrix is chosen they will converge to different solutions and therefore there is absolutely no guarantee that using ``'KNV0'`` will yield results similar to Matlab's or any other implementation of these algorithms. Using the default method ``'YT'`` should be fine in most cases; ``'KNV0'`` is only provided because it is needed by ``'YT'`` in some specific cases. Furthermore ``'YT'`` gives on average more robust results than ``'KNV0'`` when ``abs(det(X))`` is used as a robustness indicator. [2]_ is available as a technical report on the following URL: http://drum.lib.umd.edu/handle/1903/5598 References ---------- .. [1] J. Kautsky, N.K. Nichols and P. van Dooren, "Robust pole assignment in linear state feedback", International Journal of Control, Vol. 41 pp. 1129-1155, 1985. .. [2] A.L. Tits and Y. Yang, "Globally convergent algorithms for robust pole assignment by state feedback, IEEE Transactions on Automatic Control, Vol. 41, pp. 1432-1452, 1996. Examples -------- A simple example demonstrating real pole placement using both KNV and YT algorithms. This is example number 1 from section 4 of the reference KNV publication ([1]_): >>> from scipy import signal >>> import matplotlib.pyplot as plt >>> A = np.array([[ 1.380, -0.2077, 6.715, -5.676 ], ... [-0.5814, -4.290, 0, 0.6750 ], ... [ 1.067, 4.273, -6.654, 5.893 ], ... [ 0.0480, 4.273, 1.343, -2.104 ]]) >>> B = np.array([[ 0, 5.679 ], ... [ 1.136, 1.136 ], ... [ 0, 0, ], ... [-3.146, 0 ]]) >>> P = np.array([-0.2, -0.5, -5.0566, -8.6659]) Now compute K with KNV method 0, with the default YT method and with the YT method while forcing 100 iterations of the algorithm and print some results after each call. >>> fsf1 = signal.place_poles(A, B, P, method='KNV0') >>> fsf1.gain_matrix array([[ 0.20071427, -0.96665799, 0.24066128, -0.10279785], [ 0.50587268, 0.57779091, 0.51795763, -0.41991442]]) >>> fsf2 = signal.place_poles(A, B, P) # uses YT method >>> fsf2.computed_poles array([-8.6659, -5.0566, -0.5 , -0.2 ]) >>> fsf3 = signal.place_poles(A, B, P, rtol=-1, maxiter=100) >>> fsf3.X array([[ 0.52072442+0.j, -0.08409372+0.j, -0.56847937+0.j, 0.74823657+0.j], [-0.04977751+0.j, -0.80872954+0.j, 0.13566234+0.j, -0.29322906+0.j], [-0.82266932+0.j, -0.19168026+0.j, -0.56348322+0.j, -0.43815060+0.j], [ 0.22267347+0.j, 0.54967577+0.j, -0.58387806+0.j, -0.40271926+0.j]]) The absolute value of the determinant of X is a good indicator to check the robustness of the results, both ``'KNV0'`` and ``'YT'`` aim at maximizing it. Below a comparison of the robustness of the results above: >>> abs(np.linalg.det(fsf1.X)) < abs(np.linalg.det(fsf2.X)) True >>> abs(np.linalg.det(fsf2.X)) < abs(np.linalg.det(fsf3.X)) True Now a simple example for complex poles: >>> A = np.array([[ 0, 7/3., 0, 0 ], ... [ 0, 0, 0, 7/9. ], ... [ 0, 0, 0, 0 ], ... [ 0, 0, 0, 0 ]]) >>> B = np.array([[ 0, 0 ], ... [ 0, 0 ], ... [ 1, 0 ], ... [ 0, 1 ]]) >>> P = np.array([-3, -1, -2-1j, -2+1j]) / 3. >>> fsf = signal.place_poles(A, B, P, method='YT') We can plot the desired and computed poles in the complex plane: >>> t = np.linspace(0, 2*np.pi, 401) >>> plt.plot(np.cos(t), np.sin(t), 'k--') # unit circle >>> plt.plot(fsf.requested_poles.real, fsf.requested_poles.imag, ... 'wo', label='Desired') >>> plt.plot(fsf.computed_poles.real, fsf.computed_poles.imag, 'bx', ... label='Placed') >>> plt.grid() >>> plt.axis('image') >>> plt.axis([-1.1, 1.1, -1.1, 1.1]) >>> plt.legend(bbox_to_anchor=(1.05, 1), loc=2, numpoints=1) """ # Move away all the inputs checking, it only adds noise to the code update_loop, poles = _valid_inputs(A, B, poles, method, rtol, maxiter) # The current value of the relative tolerance we achieved cur_rtol = 0 # The number of iterations needed before converging nb_iter = 0 # Step A: QR decomposition of B page 1132 KN # to debug with numpy qr uncomment the line below # u, z = np.linalg.qr(B, mode="complete") u, z = s_qr(B, mode="full") rankB = np.linalg.matrix_rank(B) u0 = u[:, :rankB] u1 = u[:, rankB:] z = z[:rankB, :] # If we can use the identity matrix as X the solution is obvious if B.shape[0] == rankB: # if B is square and full rank there is only one solution # such as (A+BK)=inv(X)*diag(P)*X with X=eye(A.shape[0]) # i.e K=inv(B)*(diag(P)-A) # if B has as many lines as its rank (but not square) there are many # solutions and we can choose one using least squares # => use lstsq in both cases. # In both cases the transfer matrix X will be eye(A.shape[0]) and I # can hardly think of a better one so there is nothing to optimize # # for complex poles we use the following trick # # |a -b| has for eigenvalues a+b and a-b # |b a| # # |a+bi 0| has the obvious eigenvalues a+bi and a-bi # |0 a-bi| # # e.g solving the first one in R gives the solution # for the second one in C diag_poles = np.zeros(A.shape) idx = 0 while idx < poles.shape[0]: p = poles[idx] diag_poles[idx, idx] = np.real(p) if ~np.isreal(p): diag_poles[idx, idx+1] = -np.imag(p) diag_poles[idx+1, idx+1] = np.real(p) diag_poles[idx+1, idx] = np.imag(p) idx += 1 # skip next one idx += 1 gain_matrix = np.linalg.lstsq(B, diag_poles-A)[0] transfer_matrix = np.eye(A.shape[0]) cur_rtol = np.nan nb_iter = np.nan else: # step A (p1144 KNV) and begining of step F: decompose # dot(U1.T, A-P[i]*I).T and build our set of transfer_matrix vectors # in the same loop ker_pole = [] # flag to skip the conjugate of a complex pole skip_conjugate = False # select orthonormal base ker_pole for each Pole and vectors for # transfer_matrix for j in range(B.shape[0]): if skip_conjugate: skip_conjugate = False continue pole_space_j = np.dot(u1.T, A-poles[j]*np.eye(B.shape[0])).T # after QR Q=Q0|Q1 # only Q0 is used to reconstruct the qr'ed (dot Q, R) matrix. # Q1 is orthogonnal to Q0 and will be multiplied by the zeros in # R when using mode "complete". In default mode Q1 and the zeros # in R are not computed # To debug with numpy qr uncomment the line below # Q, _ = np.linalg.qr(pole_space_j, mode="complete") Q, _ = s_qr(pole_space_j, mode="full") ker_pole_j = Q[:, pole_space_j.shape[1]:] # We want to select one vector in ker_pole_j to build the transfer # matrix, however qr returns sometimes vectors with zeros on the # same line for each pole and this yields very long convergence # times. # Or some other times a set of vectors, one with zero imaginary # part and one (or several) with imaginary parts. After trying # many ways to select the best possible one (eg ditch vectors # with zero imaginary part for complex poles) I ended up summing # all vectors in ker_pole_j, this solves 100% of the problems and # is a valid choice for transfer_matrix. # This way for complex poles we are sure to have a non zero # imaginary part that way, and the problem of lines full of zeros # in transfer_matrix is solved too as when a vector from # ker_pole_j has a zero the other one(s) when # ker_pole_j.shape[1]>1) for sure won't have a zero there. transfer_matrix_j = np.sum(ker_pole_j, axis=1)[:, np.newaxis] transfer_matrix_j = (transfer_matrix_j / np.linalg.norm(transfer_matrix_j)) if ~np.isreal(poles[j]): # complex pole transfer_matrix_j = np.hstack([np.real(transfer_matrix_j), np.imag(transfer_matrix_j)]) ker_pole.extend([ker_pole_j, ker_pole_j]) # Skip next pole as it is the conjugate skip_conjugate = True else: # real pole, nothing to do ker_pole.append(ker_pole_j) if j == 0: transfer_matrix = transfer_matrix_j else: transfer_matrix = np.hstack((transfer_matrix, transfer_matrix_j)) if rankB > 1: # otherwise there is nothing we can optimize stop, cur_rtol, nb_iter = update_loop(ker_pole, transfer_matrix, poles, B, maxiter, rtol) if not stop and rtol > 0: # if rtol<=0 the user has probably done that on purpose, # don't annoy him err_msg = ( "Convergence was not reached after maxiter iterations.\n" "You asked for a relative tolerance of %f we got %f" % (rtol, cur_rtol) ) warnings.warn(err_msg) # reconstruct transfer_matrix to match complex conjugate pairs, # ie transfer_matrix_j/transfer_matrix_j+1 are # Re(Complex_pole), Im(Complex_pole) now and will be Re-Im/Re+Im after transfer_matrix = transfer_matrix.astype(complex) idx = 0 while idx < poles.shape[0]-1: if ~np.isreal(poles[idx]): rel = transfer_matrix[:, idx].copy() img = transfer_matrix[:, idx+1] # rel will be an array referencing a column of transfer_matrix # if we don't copy() it will changer after the next line and # and the line after will not yield the correct value transfer_matrix[:, idx] = rel-1j*img transfer_matrix[:, idx+1] = rel+1j*img idx += 1 # skip next one idx += 1 try: m = np.linalg.solve(transfer_matrix.T, np.dot(np.diag(poles), transfer_matrix.T)).T gain_matrix = np.linalg.solve(z, np.dot(u0.T, m-A)) except np.linalg.LinAlgError: raise ValueError("The poles you've chosen can't be placed. " "Check the controllability matrix and try " "another set of poles") # Beware: Kautsky solves A+BK but the usual form is A-BK gain_matrix = -gain_matrix # K still contains complex with ~=0j imaginary parts, get rid of them gain_matrix = np.real(gain_matrix) full_state_feedback = Bunch() full_state_feedback.gain_matrix = gain_matrix full_state_feedback.computed_poles = _order_complex_poles( np.linalg.eig(A - np.dot(B, gain_matrix))[0] ) full_state_feedback.requested_poles = poles full_state_feedback.X = transfer_matrix full_state_feedback.rtol = cur_rtol full_state_feedback.nb_iter = nb_iter return full_state_feedback

[ "master@MacBook-Pro-admin.local" ]

master@MacBook-Pro-admin.local

4282f0f0a003d44a67bb0595b6cc543a4271a345

4920b6c12dc2427036077d38ed8fa513130418a8

/bipad_api/bipad_api/models/inline_response20053.py

a52d1c5a3839994bdacc9f2ef436923135b09853

[]

no_license

laxmitimalsina/covid_dashboard

d51a43d3ba2ad8a9754f723383f6395c1dccdda5

ccba8a3f5dd6dbd2b28e2479bda6e581eb23805f

refs/heads/master

2023-05-29T15:07:32.524640

2021-05-03T11:15:43

273,698,762

0

null

UTF-8

Python

false

5,265

py

# coding: utf-8 """ BIPAD API No description provided (generated by Swagger Codegen https://github.com/swagger-api/swagger-codegen) # noqa: E501 OpenAPI spec version: v1 Generated by: https://github.com/swagger-api/swagger-codegen.git """ import pprint import re # noqa: F401 import six class InlineResponse20053(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. """ """ Attributes: swagger_types (dict): The key is attribute name and the value is attribute type. attribute_map (dict): The key is attribute name and the value is json key in definition. """ swagger_types = { 'count': 'int', 'next': 'str', 'previous': 'str', 'results': 'list[ReleaseStatus]' } attribute_map = { 'count': 'count', 'next': 'next', 'previous': 'previous', 'results': 'results' } def __init__(self, count=None, next=None, previous=None, results=None): # noqa: E501 """InlineResponse20053 - a model defined in Swagger""" # noqa: E501 self._count = None self._next = None self._previous = None self._results = None self.discriminator = None self.count = count if next is not None: self.next = next if previous is not None: self.previous = previous self.results = results @property def count(self): """Gets the count of this InlineResponse20053. # noqa: E501 :return: The count of this InlineResponse20053. # noqa: E501 :rtype: int """ return self._count @count.setter def count(self, count): """Sets the count of this InlineResponse20053. :param count: The count of this InlineResponse20053. # noqa: E501 :type: int """ if count is None: raise ValueError("Invalid value for `count`, must not be `None`") # noqa: E501 self._count = count @property def next(self): """Gets the next of this InlineResponse20053. # noqa: E501 :return: The next of this InlineResponse20053. # noqa: E501 :rtype: str """ return self._next @next.setter def next(self, next): """Sets the next of this InlineResponse20053. :param next: The next of this InlineResponse20053. # noqa: E501 :type: str """ self._next = next @property def previous(self): """Gets the previous of this InlineResponse20053. # noqa: E501 :return: The previous of this InlineResponse20053. # noqa: E501 :rtype: str """ return self._previous @previous.setter def previous(self, previous): """Sets the previous of this InlineResponse20053. :param previous: The previous of this InlineResponse20053. # noqa: E501 :type: str """ self._previous = previous @property def results(self): """Gets the results of this InlineResponse20053. # noqa: E501 :return: The results of this InlineResponse20053. # noqa: E501 :rtype: list[ReleaseStatus] """ return self._results @results.setter def results(self, results): """Sets the results of this InlineResponse20053. :param results: The results of this InlineResponse20053. # noqa: E501 :type: list[ReleaseStatus] """ if results is None: raise ValueError("Invalid value for `results`, must not be `None`") # noqa: E501 self._results = results def to_dict(self): """Returns the model properties as a dict""" result = {} for attr, _ in six.iteritems(self.swagger_types): value = getattr(self, attr) if isinstance(value, list): result[attr] = list(map( lambda x: x.to_dict() if hasattr(x, "to_dict") else x, value )) elif hasattr(value, "to_dict"): result[attr] = value.to_dict() elif isinstance(value, dict): result[attr] = dict(map( lambda item: (item[0], item[1].to_dict()) if hasattr(item[1], "to_dict") else item, value.items() )) else: result[attr] = value if issubclass(InlineResponse20053, dict): for key, value in self.items(): result[key] = value return result def to_str(self): """Returns the string representation of the model""" return pprint.pformat(self.to_dict()) def __repr__(self): """For `print` and `pprint`""" return self.to_str() def __eq__(self, other): """Returns true if both objects are equal""" if not isinstance(other, InlineResponse20053): return False return self.__dict__ == other.__dict__ def __ne__(self, other): """Returns true if both objects are not equal""" return not self == other

[ "laxmitimalsina2017@gmail.com" ]

laxmitimalsina2017@gmail.com

d5fef288e77bbef2f70188793ca31f94dd4b090c

d1fb8bb087564052674cb33ac6d75daca4ae586a

/Amazon 11月VO真题/1/1181. Diameter of Binary Tree.py

feaeae0a737d49417a450acd9d2dc1468f37fd6f

[]

no_license

YunsongZhang/lintcode-python

7db4ca48430a05331e17f4b79d05da585b1611ca

ea6a0ff58170499c76e9569074cb77f6bcef447a

refs/heads/master

2020-12-24T03:05:43.487532

2020-01-30T19:58:37

null

0

null

UTF-8

Python

false

638

py

class TreeNode: def __init__(self, val): self.val = val self.left, self.right = None, None class Solution: """ @param root: a root of binary tree @return: return a integer """ def __init__(self): self.diameter = 0 def diameterOfBinaryTree(self, root): if not root: return 0 self.dfs(root) return self.diameter def dfs(self, root): if not root: return 0 left = self.dfs(root.left) right = self.dfs(root.right) self.diameter = max(self.diameter, left + right) return max(left, right) + 1

[ "haixiang6123@gmail.com" ]

haixiang6123@gmail.com

d355b7ca1605808368bffb45037fb5f9c0de8c1b

31f5c200fbaded1f3670b94042b9c47182a160ca

/ch17/q17.py

9d33c61cbee9a9322dbd698c19e807c63a45bd91

[]

no_license

AeroX2/advent-of-code-2020

d86f15593ceea442515e2853003d3a1ec6527475

e47c02e4d746ac88f105bf5a8c55dcd519f4afe8

refs/heads/main

2023-02-03T02:24:58.494613

2020-12-22T10:15:29

317,873,883

0

null

UTF-8

Python

false

1,610

py

import sys data = open(sys.argv[1]).read().strip() data = [list(x) for x in data.split('\n')] print(data) cube = {} for y,v in enumerate(data): h = len(v)//2 for x,v2 in enumerate(v): cube[(x-h,y-h,0)] = v2 print(cube) width = len(data[0]) height = width depth = 0 print('Dimensions') print((width, height, depth)) def check_active(pos): active_count = 0 for x in range(-1,2): for y in range(-1,2): for z in range(-1,2): if (x == 0 and y == 0 and z == 0): continue new_pos = (pos[0]+x, pos[1]+y, pos[2]+z) active_count += 1 if cube.get(new_pos, '.') == '#' else 0 return active_count for i in range(6): #for z in range(-depth,depth+1): # print('z =',z) # for y in range(-height,height+1): # for x in range(-width,width+1): # print(cube.get((x,y,z),'.'),end='') # print() width += 1 height += 1 depth += 1 modify_list = [] for x in range(-width,width+1): for y in range(-height,height+1): for z in range(-depth,depth+1): is_active = cube.get((x,y,z), '.') == '#' active_count = check_active((x,y,z)) if (is_active and not (active_count == 2 or active_count == 3)): modify_list.append((x,y,z,'.')) elif (not is_active and (active_count == 3)): modify_list.append((x,y,z,'#')) for x,y,z,v in modify_list: cube[(x,y,z)] = v print(len([x for x in cube.values() if x == '#']))

[ "james@ridey.email" ]

james@ridey.email

aceeca9c2d8787ad6a846e833d5d569f4584213e

4a191e5aecd53c4cea28482a0179539eeb6cd74b

/comments/forms.py

5ba7334316083549b5600318794c46b4b51310b5

[]

no_license

jiangjingwei/blogproject

631a2e8e2f72420cce45ddaf152174852376d831

daf14e88092dc030a3ab0c295ee06fb6b2164372

refs/heads/master

2020-03-14T23:29:08.052253

2018-05-10T11:35:59

131,846,149

0

null

UTF-8

Python

false

191

py

from django import forms from comments.models import Comments class CommentForm(forms.ModelForm): class Meta: model = Comments fields = ['name', 'email', 'url', 'text']

[ "270159429@qq.com" ]

270159429@qq.com

852adc191b890bbcb734581a6f26bd32495378c8

ec21d4397a1939ac140c22eca12491c258ed6a92

/Zope-2.9/lib/python/Testing/dispatcher.py

a309a4937442b12ebedc1492329a89a0f71071bb

[]

no_license

wpjunior/proled

dc9120eaa6067821c983b67836026602bbb3a211

1c81471295a831b0970085c44e66172a63c3a2b0

refs/heads/master

2016-08-08T11:59:09.748402

2012-04-17T07:37:43

3,573,786

0

null

UTF-8

Python

false

5,469

py

############################################################################## # # Copyright (c) 2002 Zope Corporation and Contributors. All Rights Reserved. # # This software is subject to the provisions of the Zope Public License, # Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution. # THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED # WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS # FOR A PARTICULAR PURPOSE # ############################################################################## # Dispatcher for usage inside Zope test environment # Andreas Jung, andreas@digicool.com 03/24/2001 __version__ = '$Id: dispatcher.py 40222 2005-11-18 15:46:28Z andreasjung $' import os,sys,re,string import threading,time,commands,profile class Dispatcher: """ a multi-purpose thread dispatcher """ def __init__(self,func=''): self.fp = sys.stderr self.f_startup = [] self.f_teardown = [] self.lastlog = "" self.lock = threading.Lock() self.func = func self.profiling = 0 self.doc = getattr(self,self.func).__doc__ def setlog(self,fp): self.fp = fp def log(self,s): if s==self.lastlog: return self.fp.write(s) self.fp.flush() self.lastlog=s def logn(self,s): if s==self.lastlog: return self.fp.write(s + '\n') self.fp.flush() self.lastlog=s def profiling_on(): self.profiling = 1 def profiling_off(): self.profiling = 0 def dispatcher(self,name='', *params): """ dispatcher for threads The dispatcher expects one or several tupels: (functionname, number of threads to start , args, keyword args) """ self.mem_usage = [-1] mem_watcher = threading.Thread(None,self.mem_watcher,name='memwatcher') mem_watcher.start() self.start_test = time.time() self.name = name self.th_data = {} self.runtime = {} self._threads = [] s2s=self.s2s for func,numthreads,args,kw in params: f = getattr(self,func) for i in range(0,numthreads): kw['t_func'] = func th = threading.Thread(None,self.worker,name="TH_%s_%03d" % (func,i) ,args=args,kwargs=kw) self._threads.append(th) for th in self._threads: th.start() while threading.activeCount() > 1: time.sleep(1) self.logn('ID: %s ' % self.name) self.logn('FUNC: %s ' % self.func) self.logn('DOC: %s ' % self.doc) self.logn('Args: %s' % params) for th in self._threads: self.logn( '%-30s ........................ %9.3f sec' % (th.getName(), self.runtime[th.getName()]) ) for k,v in self.th_data[th.getName()].items(): self.logn ('%-30s %-15s = %s' % (' ',k,v) ) self.logn("") self.logn('Complete running time: %9.3f sec' % (time.time()-self.start_test) ) if len(self.mem_usage)>1: self.mem_usage.remove(-1) self.logn( "Memory: start: %s, end: %s, low: %s, high: %s" % \ (s2s(self.mem_usage[0]),s2s(self.mem_usage[-1]),s2s(min(self.mem_usage)), s2s(max(self.mem_usage)))) self.logn('') def worker(self,*args,**kw): for func in self.f_startup: f = getattr(self,func)() t_func = getattr(self,kw['t_func']) del kw['t_func'] ts = time.time() apply(t_func,args,kw) te = time.time() for func in self.f_teardown: getattr(self,func)() def th_setup(self): """ initalize thread with some environment data """ env = {'start': time.time() } return env def th_teardown(self,env,**kw): """ famous last actions of thread """ self.lock.acquire() self.th_data[ threading.currentThread().getName() ] = kw self.runtime [ threading.currentThread().getName() ] = time.time() - env['start'] self.lock.release() def getmem(self): """ try to determine the current memory usage """ if not sys.platform in ['linux2']: return None cmd = '/bin/ps --no-headers -o pid,vsize --pid %s' % os.getpid() outp = commands.getoutput(cmd) pid,vsize = filter(lambda x: x!="" , string.split(outp," ") ) data = open("/proc/%d/statm" % os.getpid()).read() fields = re.split(" ",data) mem = string.atoi(fields[0]) * 4096 return mem def mem_watcher(self): """ thread for watching memory usage """ running = 1 while running ==1: self.mem_usage.append( self.getmem() ) time.sleep(1) if threading.activeCount() == 2: running = 0 def register_startup(self,func): self.f_startup.append(func) def register_teardown(self,func): self.f_teardown.append(func) def s2s(self,n): import math if n <1024.0: return "%8.3lf Bytes" % n if n <1024.0*1024.0: return "%8.3lf KB" % (1.0*n/1024.0) if n <1024.0*1024.0*1024.0: return "%8.3lf MB" % (1.0*n/1024.0/1024.0) else: return n if __name__=="__main__": d=Dispatcher() print d.getmem() pass

[ "root@cpro5106.publiccloud.com.br" ]

root@cpro5106.publiccloud.com.br

d624d83e089f1a87248f66a4ca5b174c8b084b89

99a2d82d2a10c0af77731885f80307edcdc48535

/maildir-cat

c6e018e5ef5f707ebd50c8ae0030ce0ce56bf5cd

[ "WTFPL", "LicenseRef-scancode-public-domain" ]

permissive

mk-fg/fgtk

be60c102f6ad6cd0d0e364c3863c36a1902a15a3

90de180b0d4184f3040d85a4ff2ac38319a992af

refs/heads/master

2023-09-06T08:41:33.852815

2023-08-19T07:25:54

3,831,498

149

46

null

2017-08-15T19:23:59

2012-03-26T09:58:03

Python

UTF-8

Python

false

4,883

#!/usr/bin/env python3 import itertools as it, operator as op, functools as ft import mailbox, email, email.header, email.charset, email.errors import os, sys, re, pathlib as pl, collections as cs def bytes_decode(b, enc, errors='strict'): try: return b.decode(enc, errors) except LookupError as err: # Try to handle cp-850, unknown-8bit and such if enc == 'unknown-8bit': enc_sub = 'utf-8' else: enc_sub = enc.replace('-', '') if enc_sub == enc: raise try: return b.decode(enc_sub, errors) except LookupError: raise LookupError(enc, enc_sub) from None def _mail_header_decode_part(line): header = '' for part, enc in email.header.decode_header(line): if enc: part = bytes_decode(part, enc, 'replace') if isinstance(part, bytes): part = part.decode('utf-8', 'replace') # RFC2822#2.2.3 whitespace folding auto-adds spaces. # But extra space can also be encoded in base64 or such, # so this does not preserve exact number of encoded spaces. if not header.endswith(' '): header += ' ' header += part.lstrip() return header.strip() def mail_header_decode(val): res, header = list(), _mail_header_decode_part(val) while True: match = re.search('=\?[\w\d-]+(\*[\w\d-]+)?\?[QB]\?[^?]+\?=', header) if not match: res.append(header) break start, end = match.span(0) match = header[start:end] try: match = _mail_header_decode_part(match) except email.errors.HeaderParseError: pass res.extend([header[:start], match]) header = header[end:] return ''.join(res) def _mail_parse(msg): headers = MailMsgHeaders((k.lower(), mail_header_decode(v)) for k,v in msg.items()) payload = ( msg.get_payload(decode=True) if not msg.is_multipart() else list(map(_mail_parse, msg.get_payload())) ) if not headers.get('content-type'): headers['content-type'] = [msg.get_content_type()] if headers.get_core('content-disposition') == 'attachment': payload = '<attachment scrubbed>' elif isinstance(payload, bytes): payload = bytes_decode(payload, msg.get_content_charset() or 'utf-8', 'replace') return MailMsg(headers, payload) def mail_parse(msg): if isinstance(msg, (bytes, str)): msg = email.message_from_bytes(msg) return _mail_parse(msg) class MailMsg(cs.namedtuple('MailMsg', 'headers payload')): @property def all_parts(self): return [self] if isinstance(self.payload, str)\ else sorted(it.chain.from_iterable(m.all_parts for m in self.payload), key=len) def _text_ct_prio(self, part): ct = part.headers.get('content-type') if ct == 'text/plain': return 1 if ct.startswith('text/'): return 2 return 3 @property def text(self): return sorted(self.all_parts, key=self._text_ct_prio)[0].payload class MailMsgHeaders(cs.UserDict): def __init__(self, header_list): super().__init__() for k, v in header_list: if k not in self: self[k] = list() self[k].append(v) def get(self, k, default=None, proc=op.itemgetter(0)): hs = self.data.get(k) if not hs: return default return proc(hs) def get_core(self, k, default=None): return self.get(k, default, lambda hs: hs[0].split(';', 1)[0].strip()) def get_all(self, k, default=None): return self.get(k, default, lambda x: x) def dump_msg(pre, msg): msg = mail_parse(msg) header_list = 'from to subject date message-id reply-to sender'.split() # header_list = sorted(msg.headers.keys()) for k in header_list: for v in msg.headers.get_all(k, list()): print(f'{pre}{k.title()}: {v}') print(pre) for line in msg.text.strip().split('\n'): print(f'{pre}{line}') def main(args=None): import argparse parser = argparse.ArgumentParser( description='Tool to find all messages in the maildir, decode' ' MIME msg bodies and dump every line in these along with the filename' ' to stdout to run grep or any other search on them to find specific msg/file.') parser.add_argument('maildir', nargs='*', default=['~/.maildir'], help='Path to maildir(s) or individual msg file(s). Default: %(default)s.') opts = parser.parse_args(sys.argv[1:] if args is None else args) log_err = ft.partial(print, file=sys.stderr, flush=True) for p in opts.maildir: p_root_base = p = pl.Path(p) p_root = p_root_base.expanduser().resolve() if p_root.is_file(): try: msg = dump_msg(f'{p}: ', p_root.read_bytes()) except email.errors.MessageParseError: log_err('Malformed msg file: {p}') continue ps_root = str(p_root) maildir = mailbox.Maildir(ps_root) box_dirs = [maildir, *(maildir.get_folder(key) for key in maildir.list_folders())] for box in box_dirs: for key in box.keys(): ps = str((pl.Path(box._path) / box._lookup(key)).resolve()) assert ps.startswith(ps_root), [ps_root, ps] p = p_root_base / ps[len(ps_root)+1:] try: msg = box[key] except email.errors.MessageParseError: log_err('Malformed msg file: {p}') else: dump_msg(f'{p}: ', msg) if __name__ == '__main__': sys.exit(main())

[ "mk.fraggod@gmail.com" ]

mk.fraggod@gmail.com

0a22320d5ad8c6a27fe4569472cbc5867d672629

07b249d8b26fc49f1268798b3bd6bdcfd0b86447

/0x07-python-test_driven_development/testmod_.py

49bd0c640293d84da2e7e2965fdca8e0dc1c19a2

[]

no_license

leocjj/holbertonschool-higher_level_programming

544d6c40632fbcf721b1f39d2453ba3d033007d6

50cf2308d2c9eeca8b25c01728815d91e0a9b784

refs/heads/master

2020-09-28T23:21:13.378060

2020-08-30T23:45:11

226,889,413

0

1

null

UTF-8

Python

false

1,398

py

#!/usr/bin/python3 """ This is the "example" module. The example module supplies one function, factorial(). For example, >>> factorial(6) 720 """ def factorial(n): """Return the factorial of n, an exact integer >= 0. >>> [factorial(n) for n in range(6)] [1, 1, 2, 6, 24, 120] >>> factorial(30) 265252859812191058636308480000000 >>> factorial(-1) Traceback (most recent call last): ... ValueError: n must be >= 0 Factorials of floats are OK, but the float must be an exact integer: >>> factorial(30.1) Traceback (most recent call last): ... ValueError: n must be exact integer >>> factorial(30.0) 265252859812191058636308480000000 It must also not be ridiculously large: >>> factorial(1e100) Traceback (most recent call last): ... OverflowError: n too large """ import math if not n >= 0: raise ValueError("n must be >= 0") if math.floor(n) != n: raise ValueError("n must be exact integer") if n+1 == n: # catch a value like 1e300 raise OverflowError("n too large") result = 1 factor = 2 while factor <= n: result *= factor factor += 1 return result if __name__ == "__main__": #print(factorial(3)) import doctest doctest.testmod() #doctest.testmod(verbose=True) #Parameter to force vervose

[ "leocj@hotmail.com" ]

leocj@hotmail.com

5b8c78a5752cf5cdaa9f3f64037d7faeab7cad3f

659d41f0c737dffc2a6ebd5e773a6513da32e5ba

/scripts_OLD/PulseSequences/tests/turn_on_auto.py

e2444cebfe26f3413c0cf7aa2ce2c234bd956621

[]

no_license

HaeffnerLab/sqip

b3d4d570becb1022083ea01fea9472115a183ace

5d18f167bd9a5344dcae3c13cc5a84213fb7c199

refs/heads/master

2020-05-21T23:11:10.448549

2019-11-21T02:00:58

19,164,232

0

null

2019-11-04T04:39:37

2014-04-25T23:54:47

Python

UTF-8

Python

false

226

py

def main(): import labrad cxn = labrad.connect() cxn.dac_server.reset_queue() cxn.pulser.switch_auto('adv',True) cxn.pulser.switch_auto('rst',True) if __name__ == '__main__': main()

[ "haeffnerlab@gmail.com" ]

haeffnerlab@gmail.com

393d7ea4800d14b27bca6522be3500d2762cfe10

85a9ffeccb64f6159adbd164ff98edf4ac315e33

/pysnmp-with-texts/Wellfleet-MPLS-MLM-MIB.py

7cc3f54a6e31ffff8938d45ebeffda15c8aaebe6

[ "LicenseRef-scancode-warranty-disclaimer", "LicenseRef-scancode-proprietary-license", "LicenseRef-scancode-unknown-license-reference", "Apache-2.0" ]

permissive

agustinhenze/mibs.snmplabs.com

5d7d5d4da84424c5f5a1ed2752f5043ae00019fb

1fc5c07860542b89212f4c8ab807057d9a9206c7

refs/heads/master

2020-12-26T12:41:41.132395

2019-08-16T15:51:41

2019-08-16T15:53:57

237,512,469

0

Apache-2.0

2020-01-31T20:41:36

2020-01-31T20:41:35

null

UTF-8

Python

false

42,622

py

# # PySNMP MIB module Wellfleet-MPLS-MLM-MIB (http://snmplabs.com/pysmi) # ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/Wellfleet-MPLS-MLM-MIB # Produced by pysmi-0.3.4 at Wed May 1 15:40:59 2019 # On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4 # Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15) # ObjectIdentifier, OctetString, Integer = mibBuilder.importSymbols("ASN1", "ObjectIdentifier", "OctetString", "Integer") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ValueRangeConstraint, ValueSizeConstraint, SingleValueConstraint, ConstraintsUnion, ConstraintsIntersection = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueRangeConstraint", "ValueSizeConstraint", "SingleValueConstraint", "ConstraintsUnion", "ConstraintsIntersection") NotificationGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ModuleCompliance") ModuleIdentity, MibScalar, MibTable, MibTableRow, MibTableColumn, ObjectIdentity, Unsigned32, IpAddress, Counter64, Gauge32, TimeTicks, NotificationType, MibIdentifier, Bits, Integer32, iso, Counter32 = mibBuilder.importSymbols("SNMPv2-SMI", "ModuleIdentity", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "ObjectIdentity", "Unsigned32", "IpAddress", "Counter64", "Gauge32", "TimeTicks", "NotificationType", "MibIdentifier", "Bits", "Integer32", "iso", "Counter32") DisplayString, TextualConvention = mibBuilder.importSymbols("SNMPv2-TC", "DisplayString", "TextualConvention") wfMplsAtmGroup, = mibBuilder.importSymbols("Wellfleet-COMMON-MIB", "wfMplsAtmGroup") wfMplsAtm = MibIdentifier((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1)) wfMplsAtmIfConfTable = MibTable((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 1), ) if mibBuilder.loadTexts: wfMplsAtmIfConfTable.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfConfTable.setDescription('MPLS ATM interface configuration table - This tabulates the ATM interfaces within an mpls protocol group. All interfaces are indexed according to their line number. There is one ATM interface per MPLS LDP session, but there might be more LDP sessions per ATM interface.') wfMplsAtmIfConfEntry = MibTableRow((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 1, 1), ).setIndexNames((0, "Wellfleet-MPLS-MLM-MIB", "wfMplsAtmIfConfLineNumber")) if mibBuilder.loadTexts: wfMplsAtmIfConfEntry.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfConfEntry.setDescription('MPLS ATM interface configuration entries.') wfMplsAtmIfCreate = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 1, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("created", 1), ("deleted", 2))).clone('created')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmIfCreate.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfCreate.setDescription('Create/Delete parameter. Default is created. Users modify this object in order to create/delete MPLS ATM interfaces') wfMplsAtmIfAdminStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 1, 1, 2), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("enabled", 1), ("disabled", 2))).clone('enabled')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmIfAdminStatus.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfAdminStatus.setDescription('Enable/Disable parameter. Default is enabled.') wfMplsAtmIfConfLineNumber = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 1, 1, 3), Integer32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmIfConfLineNumber.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfConfLineNumber.setDescription('The line number of the driver line to which the interface belongs.') wfMplsAtmIfDebugLogMask = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 1, 1, 4), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 16, 128, 255))).clone(namedValues=NamedValues(("none", 1), ("fsm", 16), ("other", 128), ("all", 255))).clone('none')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmIfDebugLogMask.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfDebugLogMask.setDescription("Log bits for debug messages. This values above can be used separately, or OR'd together for a combination of debug levels.") wfMplsAtmIfStatusTable = MibTable((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 2), ) if mibBuilder.loadTexts: wfMplsAtmIfStatusTable.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfStatusTable.setDescription('MPLS ATM interface status table - This tabulates the ATM interfaces within an mpls protocol group. All interfaces are indexed according to their line number. There is one ATM interface per MPLS LDP session, but there might be multiple LDP sessions per ATM interface.') wfMplsAtmIfStatusEntry = MibTableRow((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 2, 1), ).setIndexNames((0, "Wellfleet-MPLS-MLM-MIB", "wfMplsAtmIfStatusLineNumber")) if mibBuilder.loadTexts: wfMplsAtmIfStatusEntry.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfStatusEntry.setDescription('MPLS ATM interface status entries.') wfMplsAtmIfOperStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 2, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5))).clone(namedValues=NamedValues(("down", 1), ("init", 2), ("up", 3), ("cleanup", 4), ("notpresent", 5))).clone('notpresent')).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmIfOperStatus.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfOperStatus.setDescription('The current state of the MPLS ATM interface') wfMplsAtmIfStatusLineNumber = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 2, 1, 2), Integer32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmIfStatusLineNumber.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfStatusLineNumber.setDescription('The line number of the driver line to which the interface belongs.') wfMplsAtmIfCircuit = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 2, 1, 3), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 1023))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmIfCircuit.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfCircuit.setDescription('The circuit number of the circuit to which the interface belongs.') wfMplsAtmIfTotalSess = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 2, 1, 4), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmIfTotalSess.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfTotalSess.setDescription('The total number of LDPs up running.') wfMplsAtmIfTotalVcs = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 2, 1, 5), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmIfTotalVcs.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfTotalVcs.setDescription('The total number of VCs either in use, or available on this interface.') wfMplsAtmIfAllocVcs = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 2, 1, 6), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmIfAllocVcs.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmIfAllocVcs.setDescription('The number of VCs which are currently allocated for different LDP sessions on this interface. wfMplsAtmTotalVcs minus the value of this object results in knowning how many VCs are still available to allocate to new LDP sessions on this interface.') wfMplsAtmSessConfTable = MibTable((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3), ) if mibBuilder.loadTexts: wfMplsAtmSessConfTable.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessConfTable.setDescription('This is the ATM related configuration table for every LDP session.') wfMplsAtmSessConfEntry = MibTableRow((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1), ).setIndexNames((0, "Wellfleet-MPLS-MLM-MIB", "wfMplsAtmSessConfLineNumber"), (0, "Wellfleet-MPLS-MLM-MIB", "wfMplsAtmSessConfIndex")) if mibBuilder.loadTexts: wfMplsAtmSessConfEntry.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessConfEntry.setDescription('Entry definition.') wfMplsAtmSessDelete = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("create", 1), ("delete", 2))).clone('create')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDelete.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDelete.setDescription('Create/delete MIB instance parameter.') wfMplsAtmSessAdminStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 2), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("enable", 1), ("disable", 2))).clone('enable')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessAdminStatus.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessAdminStatus.setDescription('Specifies the desired administrative state of the VCL. The up and down states indicate that the traffic flow is enabled and disabled respectively for the VCL.') wfMplsAtmSessConfLineNumber = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 3), Integer32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessConfLineNumber.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessConfLineNumber.setDescription('Uniquely identifies the interface (port) that contains the appropriate management information. We use line number here.') wfMplsAtmSessConfIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 4), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 65535))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessConfIndex.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessConfIndex.setDescription('LDP session index number.') wfMplsAtmSessConfDefVclVpi = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 5), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 255))).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessConfDefVclVpi.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessConfDefVclVpi.setDescription('The VPI value of the default VC.') wfMplsAtmSessConfDefVclVci = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 6), Integer32().subtype(subtypeSpec=ValueRangeConstraint(32, 65535)).clone(32)).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessConfDefVclVci.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessConfDefVclVci.setDescription('The VCI value of the default VC. It should not in the configured VC range for any LDP session.') wfMplsAtmSessConfVcRangeVpi = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 7), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 255))).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessConfVcRangeVpi.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessConfVcRangeVpi.setDescription('The VPI value of the VCs in this LDP session.') wfMplsAtmSessConfVcRangeMinVci = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 8), Integer32().subtype(subtypeSpec=ValueRangeConstraint(32, 65535)).clone(33)).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessConfVcRangeMinVci.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessConfVcRangeMinVci.setDescription('The minimum VCI value of the configured LDP session.') wfMplsAtmSessConfVcRangeMaxVci = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 9), Integer32().subtype(subtypeSpec=ValueRangeConstraint(32, 65535)).clone(65535)).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessConfVcRangeMaxVci.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessConfVcRangeMaxVci.setDescription('The maximum VCI value of the configured LDP session.') wfMplsAtmSessDefVclXmtPeakCellRate = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 10), Integer32()).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtPeakCellRate.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtPeakCellRate.setDescription('Transmit (Forward) Peak Cell Rate in cells/second. This specifies the upper bound on the traffic that can be submitted on an ATM connection. 0 means best effort peak cell rate.') wfMplsAtmSessDefVclXmtSustainableCellRate = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 11), Integer32()).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtSustainableCellRate.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtSustainableCellRate.setDescription("Transmit (Forward) Sustainable Cell Rate in cells/second. This specifies the upper bound on the conforming average rate of an ATM connection, where 'average rate' is the number of cells transmitted divided by the 'duration of the connection'. 0 means best effort sustainable cell rate.") wfMplsAtmSessDefVclXmtBurstSize = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 12), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(40))).clone(namedValues=NamedValues(("default", 40))).clone('default')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtBurstSize.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtBurstSize.setDescription('Transmit (Forward) Burst Size in cells.') wfMplsAtmSessDefVclXmtQosClass = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 13), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4))).clone(namedValues=NamedValues(("class0", 1), ("class1", 2), ("class2", 3), ("class3", 4))).clone('class3')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtQosClass.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtQosClass.setDescription('Transmit (Forward) Quality of Service as specified in Appendix A, Section 4 of the ATM Forum UNI Specification, Version 3.0') wfMplsAtmSessDefVclRcvPeakCellRate = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 14), Integer32()).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvPeakCellRate.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvPeakCellRate.setDescription('Receive (Backward) Peak Cell Rate in cells/second. This specifies the upper bound on the traffic that can be submitted on an ATM connection. 0 means best effort peak cell rate.') wfMplsAtmSessDefVclRcvSustainableCellRate = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 15), Integer32()).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvSustainableCellRate.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvSustainableCellRate.setDescription("Receive (Backward) Sustainable Cell Rate in cells/second. This specifies the upper bound on the conforming average rate of an ATM connection, where 'average rate' is the number of cells transmitted divided by the 'duration of the connection'. 0 means best effort sustainable cell rate.") wfMplsAtmSessDefVclRcvBurstSize = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 16), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(40))).clone(namedValues=NamedValues(("default", 40))).clone('default')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvBurstSize.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvBurstSize.setDescription('Receive (Backward) Burst Size in cells.') wfMplsAtmSessDefVclRcvQosClass = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 17), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4))).clone(namedValues=NamedValues(("class0", 1), ("class1", 2), ("class2", 3), ("class3", 4))).clone('class3')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvQosClass.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvQosClass.setDescription('Receive (Backward) Quality of Service as specified in Appendix A, Section 4 of the ATM Forum UNI Specification, Version 3.0') wfMplsAtmSessDefVclAalType = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 18), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5))).clone(namedValues=NamedValues(("type1", 1), ("type34", 2), ("type5", 3), ("other", 4), ("unknown", 5))).clone('type5')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclAalType.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclAalType.setDescription('The type of AAL used on the VCL.') wfMplsAtmSessDefVclAalCpcsTransmitSduSize = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 19), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 65535)).clone(4608)).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclAalCpcsTransmitSduSize.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclAalCpcsTransmitSduSize.setDescription('The maximum AAL CPCS SDU size in octets that is supported on the transmit direction of this VCC.') wfMplsAtmSessDefVclAalCpcsReceiveSduSize = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 20), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 65535)).clone(4608)).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclAalCpcsReceiveSduSize.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclAalCpcsReceiveSduSize.setDescription('The maximum AAL CPCS SDU size in octets that is supported on the receive direction of this VCC.') wfMplsAtmSessDefVclAalEncapsType = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 21), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4))).clone(namedValues=NamedValues(("unknown", 1), ("llcencaps", 2), ("null", 3), ("other", 4))).clone('llcencaps')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclAalEncapsType.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclAalEncapsType.setDescription('The type of data encapsulation used over both AAL3/4 and AAL5 SSCS layer. Currently, the only values supported are : ATM_VCLENCAPS_LLCENCAPS - RFC1483 ATM_VCLENCAPS_ROUTEDPROTO - NONE') wfMplsAtmSessDefVclCongestionIndication = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 22), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("off", 1), ("on", 2))).clone('off')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclCongestionIndication.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclCongestionIndication.setDescription('The desired state of the Congestion Indication (CI) bit in the payload field of each ATM cell for this VCL.') wfMplsAtmSessDefVclCellLossPriority = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 23), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("off", 1), ("on", 2))).clone('off')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclCellLossPriority.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclCellLossPriority.setDescription('The desired state of the Cell Loss Priority (CLP) bit in the ATM header of each cell for this VCL.') wfMplsAtmSessDefVclXmtTagging = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 24), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("on", 1), ("off", 2))).clone('off')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtTagging.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclXmtTagging.setDescription('Tagging forward VC messages if peak/sustainable rates exceeded') wfMplsAtmSessDefVclRcvTagging = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 3, 1, 25), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("on", 1), ("off", 2))).clone('off')).setMaxAccess("readwrite") if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvTagging.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessDefVclRcvTagging.setDescription('Tagging backward VC messages if peak/sustainable rates exceeded') wfMplsAtmSessStatusTable = MibTable((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4), ) if mibBuilder.loadTexts: wfMplsAtmSessStatusTable.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessStatusTable.setDescription('This is the ATM related status table for every LDP session.') wfMplsAtmSessStatusEntry = MibTableRow((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1), ).setIndexNames((0, "Wellfleet-MPLS-MLM-MIB", "wfMplsAtmSessStatusLineNumber"), (0, "Wellfleet-MPLS-MLM-MIB", "wfMplsAtmSessStatusIndex")) if mibBuilder.loadTexts: wfMplsAtmSessStatusEntry.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessStatusEntry.setDescription('Entry definition.') wfMplsAtmSessOperStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5))).clone(namedValues=NamedValues(("down", 1), ("init", 2), ("up", 3), ("cleanup", 4), ("notpresent", 5))).clone('notpresent')).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessOperStatus.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessOperStatus.setDescription('The ATM related LDP session state.') wfMplsAtmSessStatusLineNumber = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 2), Integer32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessStatusLineNumber.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessStatusLineNumber.setDescription('Uniquely identifies the interface (port) that contains the appropriate management information. We use line number here.') wfMplsAtmSessStatusIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 3), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 65535))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessStatusIndex.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessStatusIndex.setDescription('LDP session index number.') wfMplsAtmSessActualVcRangeVpi = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 4), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 255))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessActualVcRangeVpi.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessActualVcRangeVpi.setDescription('The VPI value of the actually allowable VC range for this session. The maximum VPI value cannot exceed the value allowable by the wfAtmInterfaceMaxActiveVpiBits.') wfMplsAtmSessActualVcRangeMinVci = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 5), Integer32().subtype(subtypeSpec=ValueRangeConstraint(32, 65535))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessActualVcRangeMinVci.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessActualVcRangeMinVci.setDescription('The minimum VCI value of the actually allowable VC range for LDP session. The maximum VCI value cannot exceed the value allowable by the wfAtmInterfaceMaxActiveVciBits.') wfMplsAtmSessActualVcRangeMaxVci = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 6), Integer32().subtype(subtypeSpec=ValueRangeConstraint(32, 65535))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessActualVcRangeMaxVci.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessActualVcRangeMaxVci.setDescription('The maximum VCI value of the actually allowable VC range for LDP session. The maximum VCI value cannot exceed the value allowable by the wfAtmInterfaceMaxActiveVciBits.') wfMplsAtmSessNegotiatedVcRangeVpi = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 7), Integer32().subtype(subtypeSpec=ValueRangeConstraint(-1, 255))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessNegotiatedVcRangeVpi.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessNegotiatedVcRangeVpi.setDescription('The VPI value of the VCs negotiated with LDP peer for this LDP session. The maximum VPI value cannot exceed the value allowable by the wfAtmInterfaceMaxActiveVpiBits. -1 means it is not possible.') wfMplsAtmSessNegotiatedVcRangeMinVci = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 8), Integer32().subtype(subtypeSpec=ValueRangeConstraint(32, 65535))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessNegotiatedVcRangeMinVci.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessNegotiatedVcRangeMinVci.setDescription('The minimum VCI value of VCs negotiated with LDP peer for this LDP session. The maximum VCI value cannot exceed the value allowable by the wfAtmInterfaceMaxActiveVciBits.') wfMplsAtmSessNegotiatedVcRangeMaxVci = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 9), Integer32().subtype(subtypeSpec=ValueRangeConstraint(32, 65535))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessNegotiatedVcRangeMaxVci.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessNegotiatedVcRangeMaxVci.setDescription('The maximum VCI value of VCs negotiated with LDP peer for this LDP session. The maximum VCI value cannot exceed the value allowable by the wfAtmInterfaceMaxActiveVciBits.') wfMplsAtmSessInboundInuseVcs = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 10), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessInboundInuseVcs.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessInboundInuseVcs.setDescription('number of VCs opened for inbound LSP.') wfMplsAtmSessOutboundInuseVcs = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 4, 1, 11), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmSessOutboundInuseVcs.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmSessOutboundInuseVcs.setDescription('number of VCs opened for outbound LSP.') wfMplsAtmVclTable = MibTable((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5), ) if mibBuilder.loadTexts: wfMplsAtmVclTable.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclTable.setDescription('Read-only per VC infomation.') wfMplsAtmVclEntry = MibTableRow((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1), ).setIndexNames((0, "Wellfleet-MPLS-MLM-MIB", "wfMplsAtmVclLineNumber"), (0, "Wellfleet-MPLS-MLM-MIB", "wfMplsAtmVclVpi"), (0, "Wellfleet-MPLS-MLM-MIB", "wfMplsAtmVclVci")) if mibBuilder.loadTexts: wfMplsAtmVclEntry.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclEntry.setDescription('Entry definition.') wfMplsAtmVclLineNumber = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 1), Integer32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclLineNumber.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclLineNumber.setDescription('Uniquely identifies the interface (port) that contains the appropriate management information. We use line number here.') wfMplsAtmVclVpi = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 2), Integer32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclVpi.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclVpi.setDescription('The VPI value of the VCL. The maximum VPI value cannot exceed the value allowable by the wfMplsAtmInterfaceMaxActiveVpiBits.') wfMplsAtmVclVci = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 3), Integer32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclVci.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclVci.setDescription('The VCI value of the VCL. The maximum VCI value cannot exceed the value allowable by the wfMplsAtmInterfaceMaxActiveVciBits.') wfMplsAtmVclLdpIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 4), Integer32()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclLdpIndex.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclLdpIndex.setDescription('Uniquely identifies the LDP session number in this interface.') wfMplsAtmVclDirection = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 5), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3))).clone(namedValues=NamedValues(("inbound", 1), ("outbound", 2), ("duplex", 3)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclDirection.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclDirection.setDescription('The direction of LSP') wfMplsAtmVclState = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 6), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5))).clone(namedValues=NamedValues(("down", 1), ("init", 2), ("up", 3), ("cleanup", 4), ("notpresent", 5)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclState.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclState.setDescription('The VC state.') wfMplsAtmVclType = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 7), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3))).clone(namedValues=NamedValues(("default", 1), ("lsp", 2), ("unknown", 3)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclType.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclType.setDescription('default VC or normal LSP VC.') wfMplsAtmVclLastChange = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 8), TimeTicks()).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclLastChange.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclLastChange.setDescription("The value of MIBII's sysUpTime at the time this VCL entered its current operational state.") wfMplsAtmVclXmtPeakCellRate = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 9), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(4716))).clone(namedValues=NamedValues(("default", 4716)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclXmtPeakCellRate.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclXmtPeakCellRate.setDescription('Transmit (Forward) Peak Cell Rate in cells/second. This specifies the upper bound on the traffic that can be submitted on an ATM connection.') wfMplsAtmVclXmtSustainableCellRate = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 10), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(4716))).clone(namedValues=NamedValues(("default", 4716)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclXmtSustainableCellRate.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclXmtSustainableCellRate.setDescription("Transmit (Forward) Sustainable Cell Rate in cells/second. This specifies the upper bound on the conforming average rate of an ATM connection, where 'average rate' is the number of cells transmitted divided by the 'duration of the connection'.") wfMplsAtmVclXmtBurstSize = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 11), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(40))).clone(namedValues=NamedValues(("default", 40)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclXmtBurstSize.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclXmtBurstSize.setDescription('Transmit (Forward) Burst Size in cells.') wfMplsAtmVclXmtQosClass = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 12), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4))).clone(namedValues=NamedValues(("class0", 1), ("class1", 2), ("class2", 3), ("class3", 4)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclXmtQosClass.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclXmtQosClass.setDescription('Transmit (Forward) Quality of Service as specified in Appendix A, Section 4 of the ATM Forum UNI Specification, Version 3.0') wfMplsAtmVclRcvPeakCellRate = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 13), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(4716))).clone(namedValues=NamedValues(("default", 4716)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclRcvPeakCellRate.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclRcvPeakCellRate.setDescription('Receive (Backward) Peak Cell Rate in cells/second. This specifies the upper bound on the traffic that can be submitted on an ATM connection.') wfMplsAtmVclRcvSustainableCellRate = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 14), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(4716))).clone(namedValues=NamedValues(("default", 4716)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclRcvSustainableCellRate.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclRcvSustainableCellRate.setDescription("Receive (Backward) Sustainable Cell Rate in cells/second. This specifies the upper bound on the conforming average rate of an ATM connection, where 'average rate' is the number of cells transmitted divided by the 'duration of the connection'.") wfMplsAtmVclRcvBurstSize = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 15), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(40))).clone(namedValues=NamedValues(("default", 40)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclRcvBurstSize.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclRcvBurstSize.setDescription('Receive (Backward) Burst Size in cells.') wfMplsAtmVclRcvQosClass = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 16), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4))).clone(namedValues=NamedValues(("class0", 1), ("class1", 2), ("class2", 3), ("class3", 4)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclRcvQosClass.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclRcvQosClass.setDescription('Receive (Backward) Quality of Service as specified in Appendix A, Section 4 of the ATM Forum UNI Specification, Version 3.0') wfMplsAtmVclAalType = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 17), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4, 5))).clone(namedValues=NamedValues(("type1", 1), ("type34", 2), ("type5", 3), ("other", 4), ("unknown", 5)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclAalType.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclAalType.setDescription('The type of AAL used on the VCL.') wfMplsAtmVclAalCpcsTransmitSduSize = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 18), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 65535))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclAalCpcsTransmitSduSize.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclAalCpcsTransmitSduSize.setDescription('The maximum AAL CPCS SDU size in octets that is supported on the transmit direction of this VCC.') wfMplsAtmVclAalCpcsReceiveSduSize = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 19), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 65535))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclAalCpcsReceiveSduSize.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclAalCpcsReceiveSduSize.setDescription('The maximum AAL CPCS SDU size in octets that is supported on the receive direction of this VCC.') wfMplsAtmVclAalEncapsType = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 20), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2, 3, 4))).clone(namedValues=NamedValues(("unknown", 1), ("llcencaps", 2), ("null", 3), ("other", 4)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclAalEncapsType.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclAalEncapsType.setDescription('The type of data encapsulation used over both AAL3/4 and AAL5 SSCS layer. Currently, the only values supported are : ATM_VCLENCAPS_LLCENCAPS - RFC1483 ATM_VCLENCAPS_ROUTEDPROTO - NONE') wfMplsAtmVclCongestionIndication = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 21), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("off", 1), ("on", 2)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclCongestionIndication.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclCongestionIndication.setDescription('The desired state of the Congestion Indication (CI) bit in the payload field of each ATM cell for this VCL.') wfMplsAtmVclCellLossPriority = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 22), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("off", 1), ("on", 2)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclCellLossPriority.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclCellLossPriority.setDescription('The desired state of the Cell Loss Priority (CLP) bit in the ATM header of each cell for this VCL.') wfMplsAtmVclXmtTagging = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 23), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("on", 1), ("off", 2)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclXmtTagging.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclXmtTagging.setDescription('Tagging forward VC messages if peak/sustainable rates exceeded') wfMplsAtmVclRcvTagging = MibTableColumn((1, 3, 6, 1, 4, 1, 18, 3, 5, 9, 16, 1, 5, 1, 24), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(1, 2))).clone(namedValues=NamedValues(("on", 1), ("off", 2)))).setMaxAccess("readonly") if mibBuilder.loadTexts: wfMplsAtmVclRcvTagging.setStatus('mandatory') if mibBuilder.loadTexts: wfMplsAtmVclRcvTagging.setDescription('Tagging backward VC messages if peak/sustainable rates exceeded') mibBuilder.exportSymbols("Wellfleet-MPLS-MLM-MIB", wfMplsAtmVclCellLossPriority=wfMplsAtmVclCellLossPriority, wfMplsAtmSessConfVcRangeMaxVci=wfMplsAtmSessConfVcRangeMaxVci, wfMplsAtmSessDelete=wfMplsAtmSessDelete, wfMplsAtmIfConfLineNumber=wfMplsAtmIfConfLineNumber, wfMplsAtmSessConfIndex=wfMplsAtmSessConfIndex, wfMplsAtmSessDefVclXmtPeakCellRate=wfMplsAtmSessDefVclXmtPeakCellRate, wfMplsAtmVclLastChange=wfMplsAtmVclLastChange, wfMplsAtmSessDefVclAalCpcsTransmitSduSize=wfMplsAtmSessDefVclAalCpcsTransmitSduSize, wfMplsAtmVclXmtTagging=wfMplsAtmVclXmtTagging, wfMplsAtmSessConfTable=wfMplsAtmSessConfTable, wfMplsAtmSessDefVclRcvSustainableCellRate=wfMplsAtmSessDefVclRcvSustainableCellRate, wfMplsAtmVclAalEncapsType=wfMplsAtmVclAalEncapsType, wfMplsAtmIfOperStatus=wfMplsAtmIfOperStatus, wfMplsAtmVclType=wfMplsAtmVclType, wfMplsAtmSessOperStatus=wfMplsAtmSessOperStatus, wfMplsAtmSessStatusIndex=wfMplsAtmSessStatusIndex, wfMplsAtmSessActualVcRangeVpi=wfMplsAtmSessActualVcRangeVpi, wfMplsAtmVclTable=wfMplsAtmVclTable, wfMplsAtmSessDefVclCongestionIndication=wfMplsAtmSessDefVclCongestionIndication, wfMplsAtmSessAdminStatus=wfMplsAtmSessAdminStatus, wfMplsAtmSessNegotiatedVcRangeMinVci=wfMplsAtmSessNegotiatedVcRangeMinVci, wfMplsAtmSessDefVclAalCpcsReceiveSduSize=wfMplsAtmSessDefVclAalCpcsReceiveSduSize, wfMplsAtmIfStatusLineNumber=wfMplsAtmIfStatusLineNumber, wfMplsAtmIfConfTable=wfMplsAtmIfConfTable, wfMplsAtmVclXmtSustainableCellRate=wfMplsAtmVclXmtSustainableCellRate, wfMplsAtmSessDefVclXmtBurstSize=wfMplsAtmSessDefVclXmtBurstSize, wfMplsAtmVclAalCpcsTransmitSduSize=wfMplsAtmVclAalCpcsTransmitSduSize, wfMplsAtmSessDefVclXmtTagging=wfMplsAtmSessDefVclXmtTagging, wfMplsAtmVclRcvTagging=wfMplsAtmVclRcvTagging, wfMplsAtmSessDefVclRcvQosClass=wfMplsAtmSessDefVclRcvQosClass, wfMplsAtmIfStatusEntry=wfMplsAtmIfStatusEntry, wfMplsAtmSessDefVclAalType=wfMplsAtmSessDefVclAalType, wfMplsAtmIfDebugLogMask=wfMplsAtmIfDebugLogMask, wfMplsAtmIfAllocVcs=wfMplsAtmIfAllocVcs, wfMplsAtmSessConfDefVclVci=wfMplsAtmSessConfDefVclVci, wfMplsAtmSessConfLineNumber=wfMplsAtmSessConfLineNumber, wfMplsAtmSessNegotiatedVcRangeMaxVci=wfMplsAtmSessNegotiatedVcRangeMaxVci, wfMplsAtmSessActualVcRangeMaxVci=wfMplsAtmSessActualVcRangeMaxVci, wfMplsAtmVclLdpIndex=wfMplsAtmVclLdpIndex, wfMplsAtmIfConfEntry=wfMplsAtmIfConfEntry, wfMplsAtmVclRcvPeakCellRate=wfMplsAtmVclRcvPeakCellRate, wfMplsAtm=wfMplsAtm, wfMplsAtmSessDefVclAalEncapsType=wfMplsAtmSessDefVclAalEncapsType, wfMplsAtmVclLineNumber=wfMplsAtmVclLineNumber, wfMplsAtmVclAalType=wfMplsAtmVclAalType, wfMplsAtmIfAdminStatus=wfMplsAtmIfAdminStatus, wfMplsAtmVclXmtPeakCellRate=wfMplsAtmVclXmtPeakCellRate, wfMplsAtmSessConfVcRangeMinVci=wfMplsAtmSessConfVcRangeMinVci, wfMplsAtmVclXmtBurstSize=wfMplsAtmVclXmtBurstSize, wfMplsAtmSessActualVcRangeMinVci=wfMplsAtmSessActualVcRangeMinVci, wfMplsAtmVclDirection=wfMplsAtmVclDirection, wfMplsAtmSessDefVclRcvPeakCellRate=wfMplsAtmSessDefVclRcvPeakCellRate, wfMplsAtmVclState=wfMplsAtmVclState, wfMplsAtmSessNegotiatedVcRangeVpi=wfMplsAtmSessNegotiatedVcRangeVpi, wfMplsAtmSessStatusEntry=wfMplsAtmSessStatusEntry, wfMplsAtmIfTotalSess=wfMplsAtmIfTotalSess, wfMplsAtmSessConfEntry=wfMplsAtmSessConfEntry, wfMplsAtmSessConfVcRangeVpi=wfMplsAtmSessConfVcRangeVpi, wfMplsAtmVclAalCpcsReceiveSduSize=wfMplsAtmVclAalCpcsReceiveSduSize, wfMplsAtmSessOutboundInuseVcs=wfMplsAtmSessOutboundInuseVcs, wfMplsAtmIfTotalVcs=wfMplsAtmIfTotalVcs, wfMplsAtmIfCircuit=wfMplsAtmIfCircuit, wfMplsAtmVclVpi=wfMplsAtmVclVpi, wfMplsAtmSessConfDefVclVpi=wfMplsAtmSessConfDefVclVpi, wfMplsAtmSessStatusLineNumber=wfMplsAtmSessStatusLineNumber, wfMplsAtmSessStatusTable=wfMplsAtmSessStatusTable, wfMplsAtmVclEntry=wfMplsAtmVclEntry, wfMplsAtmIfStatusTable=wfMplsAtmIfStatusTable, wfMplsAtmVclCongestionIndication=wfMplsAtmVclCongestionIndication, wfMplsAtmSessDefVclRcvBurstSize=wfMplsAtmSessDefVclRcvBurstSize, wfMplsAtmVclRcvSustainableCellRate=wfMplsAtmVclRcvSustainableCellRate, wfMplsAtmSessDefVclXmtQosClass=wfMplsAtmSessDefVclXmtQosClass, wfMplsAtmSessDefVclRcvTagging=wfMplsAtmSessDefVclRcvTagging, wfMplsAtmVclRcvQosClass=wfMplsAtmVclRcvQosClass, wfMplsAtmIfCreate=wfMplsAtmIfCreate, wfMplsAtmVclVci=wfMplsAtmVclVci, wfMplsAtmSessInboundInuseVcs=wfMplsAtmSessInboundInuseVcs, wfMplsAtmVclRcvBurstSize=wfMplsAtmVclRcvBurstSize, wfMplsAtmSessDefVclCellLossPriority=wfMplsAtmSessDefVclCellLossPriority, wfMplsAtmSessDefVclXmtSustainableCellRate=wfMplsAtmSessDefVclXmtSustainableCellRate, wfMplsAtmVclXmtQosClass=wfMplsAtmVclXmtQosClass)

[ "dcwangmit01@gmail.com" ]

dcwangmit01@gmail.com

cefeca51da9d665c2fa87a15a7a909aa2b76ceb4

71596c8aec5ea7eb44b0f86736bc5acdccd55ac1

/Graphs/dfs_adv.py

95d92150b5ca2fd58e2045eea1bb44e2b2db9ca6

[]

no_license

karthikeyansa/Data_Structures_python

dbab61f67d1bc33995dd7ff86989aa56b6f11a5c

b64618a4cff2b1d29ce8c129cb1f8ec35dcddf6f

refs/heads/master

2023-01-16T05:21:10.308318

2020-11-22T06:28:08

264,231,273

0

null

UTF-8

Python

false

360

py

#undirected_cyclic_graph def dfs(g,s): vis,stack = {s},[] stack.append(s) while stack: u = stack.pop() for u in g[u]: if u not in vis: vis.add(u) stack.append(u) return vis n,m = map(int,input().split()) g = {} for i in range(n): g[i+1] = [] for _ in range(m): x,y = map(int,input().split()) g[x].append(y) g[y].append(x) print(dfs(g,1))

[ "karthikeyansa39@gmail.com" ]

karthikeyansa39@gmail.com

8a0cae9036743c46a8fba91fa5ef68a7cc72396c

17c371020e9d5f163246092dc2ba405a4ec19900

/posts/migrations/0001_initial.py

ab0b028560dcd5c70b2611f8b510221a5776e1d9

[]

no_license

avs8/My-Blog

2820386c8af8ceba448e45566c0cad01b832a2a6

636a48cf91d55c5688707295b0c0d78b47a17f7d

refs/heads/master

2021-01-10T23:19:32.467922

2016-10-12T18:39:00

70,621,951

0

null

UTF-8

Python

false

734

py

# -*- coding: utf-8 -*- # Generated by Django 1.9 on 2016-10-10 18:40 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='Post', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('title', models.CharField(max_length=256)), ('content', models.TextField()), ('updated', models.DateTimeField(auto_now=True)), ('timestamp', models.DateTimeField(auto_now_add=True)), ], ), ]

[ "ajitavsingh_8@yahoo.com" ]

ajitavsingh_8@yahoo.com

b5d2e8ce15ead6d7ef987071845d4c21c1689de8

7a4ed01a40e8d79126b26f5e8fca43c8e61e78fd

/Geeky Shows/Advance Pyhton/203.Passing_Member_Of_One_Class_To_Another_Class[17].py

503cf407b9664e539e7ad2bd8bdf02bdd184c17a

[]

no_license

satyam-seth-learnings/python_learning

5a7f75bb613dcd7fedc31a1567a434039b9417f8

7e76c03e94f5c314dcf1bfae6f26b4a8a6e658da

refs/heads/main

2023-08-25T14:08:11.423875

2021-10-09T13:00:49

333,840,032

1

0

null

UTF-8

Python

false

502

py

# Passing Members Of One Class To Another Class class Student: # Constructor def __init__(self,n,r): self.name=n self.roll=r # Instance Method def disp(self): print('Student Name:',self.name) print('Student Roll:',self.roll) class User: # Static Method @staticmethod def show(s): print('User Name:',s.name) print('User Roll:',s.roll) s.disp() # Creating Object Of Student Class stu=Student('Satyam',101) User.show(stu)

[ "satyam1998.1998@gmail.com" ]

satyam1998.1998@gmail.com

2cad8786efb1b0659b1f3bf2c217c5e0e997bd99

70c532c46847329d09757455721f4dc15bc16a77

/morsite/settings.py

982da5827335efc59b68cc8dd085fa929c876566

[]

no_license

yaronsamuel-zz/morsite

31a8f8b25c76f33819bc4eb72ad23c1ca258b7f7

4a609bc8cfa49ab8798c1bb87c43cd224a635f1b

refs/heads/master

2023-01-29T13:26:08.915327

2014-04-17T14:20:01

null

0

null

UTF-8

Python

false

7,551

py

import os # Django settings for morsite project. LOCAL_DIR = r"c:\morsite" IS_LOCAL = os.path.isdir(LOCAL_DIR) if IS_LOCAL: PROJECT_DIR = LOCAL_DIR # BASE_URL = "http://127.0.0.1:8000/" else: PROJECT_DIR = r"/home/ordercak/public_html/sweetsamuel.co.il/" # BASE_URL = "http://www.morsite.ordercakeinhaifa.com/" def relToAbs(path): return os.path.join(PROJECT_DIR, path).replace('\\','/') def dec(st): ret = '' key = '\xab\x67\xa4\x5c\xbb' * 10 for i in xrange(len(st)): ret += chr( ord(st[i]) ^ ord(key[i]) ) return ret def assign(name , value): attr_name = dec(name) attr_value = dec(value) globals()[attr_name] = attr_value DEBUG = False TEMPLATE_DEBUG = DEBUG ADMINS = [ ('Mor' , 'SamuelCakes@gmail.com') , # ('Your Name', 'your_emai@example.com'), ] MANAGERS = ADMINS DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', # Add 'postgresql_psycopg2', 'mysql', 'sqlite3' or 'oracle'. 'NAME': 'morsite.db', # Or path to database file if using sqlite3. # The following settings are not used with sqlite3: 'USER': '', 'PASSWORD': '', 'HOST': '', # Empty for localhost through domain sockets or '127.0.0.1' for localhost through TCP. 'PORT': '', # Set to empty string for default. } } # Hosts/domain names that are valid for this site; required if DEBUG is False # See https://docs.djangoproject.com/en/1.5/ref/settings/#allowed-hosts ALLOWED_HOSTS = ['*'] # Local time zone for this installation. Choices can be found here: # http://en.wikipedia.org/wiki/List_of_tz_zones_by_name # although not all choices may be available on all operating systems. # In a Windows environment this must be set to your system time zone. TIME_ZONE = 'Asia/Tel_Aviv' # Language code for this installation. All choices can be found here: # http://www.i18nguy.com/unicode/language-identifiers.html LANGUAGE_CODE = 'he'#'en-us' SITE_ID = 1 # If you set this to False, Django will make some optimizations so as not # to load the internationalization machinery. USE_I18N = True # If you set this to False, Django will not format dates, numbers and # calendars according to the current locale. USE_L10N = True # If you set this to False, Django will not use timezone-aware datetimes. USE_TZ = True MEDIA_ROOT = relToAbs('media') MEDIA_URL = '/media/' STATIC_ROOT = relToAbs('static') STATIC_URL = '/static/' MY_STATIC_ROOT = relToAbs('static_files') # Additional locations of static files STATICFILES_DIRS = ( MY_STATIC_ROOT, # Put strings here, like "/home/html/static" or "C:/www/django/static". # Always use forward slashes, even on Windows. # Don't forget to use absolute paths, not relative paths. ) # List of finder classes that know how to find static files in # various locations. STATICFILES_FINDERS = ( 'django.contrib.staticfiles.finders.FileSystemFinder', 'django.contrib.staticfiles.finders.AppDirectoriesFinder', # 'django.contrib.staticfiles.finders.DefaultStorageFinder', ) # Make this unique, and don't share it with anybody. SECRET_KEY = 'f3oda#81rs%yu+*-bc%_5@*nmmf0!yiyw23d(!34awfexfc+j-' # List of callables that know how to import templates from various sources. if IS_LOCAL: TEMPLATE_LOADERS = ( 'django.template.loaders.filesystem.Loader', 'django.template.loaders.app_directories.Loader', # 'django.template.loaders.eggs.Loader', ) else: TEMPLATE_LOADERS = ( ('django.template.loaders.cached.Loader', ( 'django.template.loaders.filesystem.Loader', 'django.template.loaders.app_directories.Loader', )), # 'django.template.loaders.eggs.Loader', ) MIDDLEWARE_CLASSES = ( 'django.middleware.common.CommonMiddleware', 'django.contrib.sessions.middleware.SessionMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', # Uncomment the next line for simple clickjacking protection: # 'django.middleware.clickjacking.XFrameOptionsMiddleware', ) ROOT_URLCONF = 'morsite.urls' # Python dotted path to the WSGI application used by Django's runserver. WSGI_APPLICATION = 'morsite.wsgi.application' TEMPLATE_DIRS = ( relToAbs('templates') , # Put strings here, like "/home/html/django_templates" or "C:/www/django/templates". # Always use forward slashes, even on Windows. # Don't forget to use absolute paths, not relative paths. ) INSTALLED_APPS = ( 'grappelli', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.sites', 'django.contrib.messages', 'django.contrib.staticfiles', 'django.contrib.admin', # Uncomment the next line to enable admin documentation: # 'django.contrib.admindocs', 'Prices' , 'orderedmodel', 'django.contrib.comments', 'tagging', 'mptt', 'zinnia', 'menu' , 'Gallery', 'contact_form', 'my_comment_app', 'tinymce', ) COMMENTS_APP = 'my_comment_app' #Zinnia stuff TEMPLATE_CONTEXT_PROCESSORS = ( 'django.contrib.auth.context_processors.auth', 'django.core.context_processors.i18n', 'django.core.context_processors.request', 'django.core.context_processors.media', 'django.core.context_processors.static', 'zinnia.context_processors.version', "django.core.context_processors.debug", "django.contrib.messages.context_processors.messages", ) # Optional SESSION_SERIALIZER = 'django.contrib.sessions.serializers.JSONSerializer' # A sample logging configuration. The only tangible logging # performed by this configuration is to send an email to # the site admins on every HTTP 500 error when DEBUG=False. # See http://docs.djangoproject.com/en/dev/topics/logging for # more details on how to customize your logging configuration. LOGGING = { 'version': 1, 'disable_existing_loggers': False, 'filters': { 'require_debug_false': { '()': 'django.utils.log.RequireDebugFalse' } }, 'handlers': { 'mail_admins': { 'level': 'ERROR', 'filters': ['require_debug_false'], 'class': 'django.utils.log.AdminEmailHandler' } }, 'loggers': { 'django.request': { 'handlers': ['mail_admins'], 'level': 'ERROR', 'propagate': True, }, } } TINYMCE_DEFAULT_CONFIG = { 'theme_advanced_buttons1' : "save,newdocument,|,bold,italic,underline,strikethrough,|,justifyleft,justifycenter,justifyright,justifyfull,|,styleselect,formatselect,fontselect,fontsizeselect", } # assign('\xee*\xe5\x15\xf7\xf4/\xeb\x0f\xef\xf47\xe5\x0f\xe8\xfc(\xf6\x18' , '\x9aU\x97h\x8e\x9dP\xdd') EMAIL_HOST = 'smtp.gmail.com' EMAIL_HOST_USER = 'cakesnmore1010@gmail.com' assign('\xee*\xe5\x15\xf7\xf4/\xeb\x0f\xef\xf47\xe5\x0f\xe8\xfc(\xf6\x18' , '\xd1\x00\xce2\xd5\xc7\x08\xd1-\xcc\xde\x11\xd32\xcf\xc1') EMAIL_PORT = 587 EMAIL_USE_TLS = True # EMAIL_RECIPIAENTS_LIST = [EMAIL_HOST_USER ] EMAIL_RECIPIAENTS_LIST = ['cakesnmore1010@gmail.com' , 'SamuelCakes@gmail.com']

[ "samuel.yaron@gmail.com" ]

samuel.yaron@gmail.com