GUI and Desktop Applications int64 0 1 | A_Id int64 5.3k 72.5M | Networking and APIs int64 0 1 | Python Basics and Environment int64 0 1 | Other int64 0 1 | Database and SQL int64 0 1 | Available Count int64 1 13 | is_accepted bool 2
classes | Q_Score int64 0 1.72k | CreationDate stringlengths 23 23 | Users Score int64 -11 327 | AnswerCount int64 1 31 | System Administration and DevOps int64 0 1 | Title stringlengths 15 149 | Q_Id int64 5.14k 60M | Score float64 -1 1.2 | Tags stringlengths 6 90 | Answer stringlengths 18 5.54k | Question stringlengths 49 9.42k | Web Development int64 0 1 | Data Science and Machine Learning int64 1 1 | ViewCount int64 7 3.27M |
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0 | 7,746,882 | 0 | 1 | 0 | 0 | 1 | false | 0 | 2011-10-12T20:57:00.000 | 0 | 2 | 0 | in Python using the multiprocessing module, how can I determine which object caused a PicklingError? | 7,746,484 | 0 | python,multiprocessing | The error you're seeing could be caused by passing the wrong kind of function to the multiprocessing.Pool methods. The passed function must be directly importable from its parent module. It cannot be a method of a class, for instance. | I have a complex Python program. I'm trying to use the multiprocess Pool to parallelize it. I get the error message
PicklingError: Can't pickle <type 'function'>: attribute lookup __builtin__.function failed.
The traceback shows the statemen return send(obj)
My hypothesis is that its the "obj" that is causing the probl... | 0 | 1 | 82 |
0 | 37,692,584 | 0 | 1 | 0 | 0 | 1 | false | 2 | 2011-10-13T18:44:00.000 | 0 | 2 | 0 | Graph colouring in python using adjacency matrix | 7,758,913 | 0 | python,graph-algorithm | Implementing using adjacency is somewhat easier than using lists, as lists take a longer time and space. igraph has a quick method neighbors which can be used. However, with adjacency matrix alone, we can come up with our own graph coloring version which may not result in using minimum chromatic number. A quick strateg... | How can I implement graph colouring in python using adjacency matrix? Is it possible? I implemented it using list. But it has some problems. I want to implement it using matrix. Can anybody give me the answer or suggestions to this? | 0 | 1 | 1,943 |
0 | 7,761,877 | 0 | 1 | 0 | 0 | 2 | false | 5 | 2011-10-14T00:13:00.000 | 2 | 2 | 0 | Is it worth using a multithreaded blas implementation along with multiprocessing in Python? | 7,761,859 | 0.197375 | python,multithreading,numpy,multiprocessing,blas | If you are already using multiprocessing, and all cores are at max load, then there will be very little, if any, benefit to adding threads that will be waiting around for a processor.
Depending on your algorithm and what you're doing, it may be more beneficial to use one type over the other, but that's very dependent. | Suppose I have a 16 core machine, and an embarrassingly parallel program. I use lots of numpy dot products and addition of numpy arrays, and if I did not use multiprocessing it would be a no-brainer: Make sure numpy is built against a version of blas that uses multithreading. However, I am using multiprocessing, and... | 0 | 1 | 2,321 |
0 | 7,765,829 | 0 | 1 | 0 | 0 | 2 | false | 5 | 2011-10-14T00:13:00.000 | 6 | 2 | 0 | Is it worth using a multithreaded blas implementation along with multiprocessing in Python? | 7,761,859 | 1 | python,multithreading,numpy,multiprocessing,blas | You might need to be a little careful about the assumption that your code is actually used multithreaded BLAS calls. Relatively few numpy operators actually use the underlying BLAS, and relatively few BLAS calls are actually multithreaded. numpy.dot uses either BLAS dot, gemv or gemm, depending on the operation, but of... | Suppose I have a 16 core machine, and an embarrassingly parallel program. I use lots of numpy dot products and addition of numpy arrays, and if I did not use multiprocessing it would be a no-brainer: Make sure numpy is built against a version of blas that uses multithreading. However, I am using multiprocessing, and... | 0 | 1 | 2,321 |
0 | 7,779,373 | 0 | 0 | 0 | 0 | 2 | false | 22 | 2011-10-15T00:42:00.000 | 8 | 5 | 0 | Equivalent of "whos" command in NumPy | 7,774,964 | 1 | python,matlab,numpy,octave | Python has a builtin function dir() which returns the list of names in the current local scope. | I am new to Numpy and trying to search for a function to list out the variables along with their sizes (both the matrix dimensions as well as memory usage).
I am essentially looking for an equivalent of the "whos" command in MATLAB and Octave. Does there exist any such command in NumPy? | 0 | 1 | 21,664 |
0 | 60,568,982 | 0 | 0 | 0 | 0 | 2 | false | 22 | 2011-10-15T00:42:00.000 | 0 | 5 | 0 | Equivalent of "whos" command in NumPy | 7,774,964 | 0 | python,matlab,numpy,octave | try using: type(VAR_NAME)
this will output the class type for that particular variable, VAR_NAME | I am new to Numpy and trying to search for a function to list out the variables along with their sizes (both the matrix dimensions as well as memory usage).
I am essentially looking for an equivalent of the "whos" command in MATLAB and Octave. Does there exist any such command in NumPy? | 0 | 1 | 21,664 |
0 | 7,786,451 | 0 | 0 | 0 | 0 | 1 | true | 1 | 2011-10-16T18:07:00.000 | 1 | 1 | 0 | does Enthought Python distribution includes pyhdf and HDF 4 | 7,786,232 | 1.2 | python,image-processing | For the versions of EPD that include pyhdf, you don't need to install HDF 4 separately. However, note that pyhdf is not included in all versions of EPD---in particular, it's not included in the 64-bit Windows EPD or the 64-bit OS X EPD, though it is in the 32-bit versions. | In Enthought Python Distribution, I saw it includes pyhdf and numpy. Since it includes pyhdf, does it also include HDF 4?
I am using pylab to code at this moment.
Because I want to use a module of the pyhdf package called pyhdf.SD. And it Prerequisites HDF 4 library. So do I still need to install HDF 4 if I want to use... | 0 | 1 | 258 |
0 | 7,787,997 | 0 | 0 | 0 | 0 | 1 | false | 1 | 2011-10-16T22:18:00.000 | 1 | 3 | 0 | How do I do matrix computations in python without rounding? | 7,787,732 | 0.066568 | python,numpy | Note that if you're serious about your comment that you require your solution vector to be integer, then you're looking for something called the "integer least squares problem". Which is believed to be NP-hard. There are some heuristic solvers, but it all gets very complicated. | I have some integer matrices of moderate size (a few hundred rows). I need to solve equations of the form Ax = b where b is a standard basis vector and A is one of my matrices. I have been using numpy.linalg.lstsq for this purpose, but the rounding errors end up being too significant.
How can I carry out an exact symb... | 0 | 1 | 403 |
1 | 7,847,894 | 0 | 1 | 0 | 0 | 1 | false | 2 | 2011-10-21T07:41:00.000 | 0 | 3 | 0 | python: container to memorize a large number of images | 7,846,413 | 0 | python,database | You could pickle a dict that associates filenames to byte strings of RGBA data.
Assuming you have loaded the image with PIL, make sure they have all the same size and color format. Build a dict with images[filename] = im.tostring() and dump() it with pickle. Use Image.fromstring with the right size and mode parameters ... | I have to store/retrieve a large number of images to use in my program.
Each image is small: an icon 50x50, and each one has associated a string which is the path the icon is related to.
Since they are so small I was thinking if there is some library which allows to store all of them in a single file.
I would need to ... | 0 | 1 | 165 |
0 | 7,855,863 | 0 | 0 | 0 | 0 | 1 | false | 5 | 2011-10-21T22:09:00.000 | 5 | 4 | 0 | Python's random module made inaccessible by Numpy's random module | 7,855,845 | 0.244919 | python,numpy,random-sample | This shouldn't happen. Check your code for bad imports like from numpy import *. | When I call random.sample(arr,length)
an error returns random_sample() takes at most 1 positional argument (2 given). After some Googling I found out I'm calling Numpy's random sample function when I want to call the sample function of the random module. I've tried importing numpy under a different name, which doesn'... | 0 | 1 | 4,375 |
0 | 11,026,071 | 0 | 0 | 0 | 0 | 2 | false | 2 | 2011-10-22T00:57:00.000 | 0 | 2 | 0 | Anyone familiar with data format of Comfirmit? | 7,856,725 | 0 | python,spss | I was recently given a data set from confirmit. There are almost 4000 columns in the excel file. I want to enter it into a mysql db. There is not way they are just doing that output from one table. Do you know how the table schema works for confirmit? | I recently asked about accessing data from SPSS and got some absolutely wonderful help here. I now have an almost identical need to read data from a Confirmit data file. Not finding a ton of confirmit data file format on the web. It appears that Confirmit can export to SPSS *.sav files. This might be one avenue for me.... | 0 | 1 | 768 |
0 | 10,631,838 | 0 | 0 | 0 | 0 | 2 | true | 2 | 2011-10-22T00:57:00.000 | 0 | 2 | 0 | Anyone familiar with data format of Comfirmit? | 7,856,725 | 1.2 | python,spss | You can get the data schema from Excel definition export from Confirmit
You can export from Confirmit txt file with the same template | I recently asked about accessing data from SPSS and got some absolutely wonderful help here. I now have an almost identical need to read data from a Confirmit data file. Not finding a ton of confirmit data file format on the web. It appears that Confirmit can export to SPSS *.sav files. This might be one avenue for me.... | 0 | 1 | 768 |
0 | 7,878,155 | 0 | 0 | 0 | 0 | 1 | false | 38 | 2011-10-24T12:34:00.000 | 9 | 4 | 0 | How can I create a standard colorbar for a series of plots in python | 7,875,688 | 1 | python,matplotlib,colorbar | Easiest solution is to call clim(lower_limit, upper_limit) with the same arguments for each plot. | I using matplotlib to plot some data in python and the plots require a standard colour bar. The data consists of a series of NxM matrices containing frequency information so that a simple imshow() plot gives a 2D histogram with colour describing frequency. Each matrix contains data in different, but overlapping ranges.... | 0 | 1 | 46,914 |
0 | 7,891,137 | 0 | 0 | 0 | 1 | 1 | true | 12 | 2011-10-25T01:06:00.000 | 23 | 1 | 0 | exporting from/importing to numpy, scipy in SQLite and HDF5 formats | 7,883,646 | 1.2 | python,sqlite,numpy,scipy,hdf5 | Most of it depends on your use case.
I have a lot more experience dealing with the various HDF5-based methods than traditional relational databases, so I can't comment too much on SQLite libraries for python...
At least as far as h5py vs pyTables, they both offer very seamless access via numpy arrays, but they're orie... | There seems to be many choices for Python to interface with SQLite (sqlite3, atpy) and HDF5 (h5py, pyTables) -- I wonder if anyone has experience using these together with numpy arrays or data tables (structured/record arrays), and which of these most seamlessly integrate with "scientific" modules (numpy, scipy) for ea... | 0 | 1 | 3,647 |
0 | 7,892,106 | 0 | 0 | 0 | 0 | 1 | true | 1 | 2011-10-25T15:19:00.000 | 3 | 3 | 0 | Run python script (with numpy dependency) from java | 7,891,586 | 1.2 | java,python,numpy,jython | If you're using Numpy you probably have to just use C Python, as it's a compiled extension. I'd recommend saving the image to disk, perhaps as a temporary file, and then calling the Python as a subprocess. If you're dealing with binary data you could even try memory mapping the data in Java and passing in in the path t... | In a java application I need to use a specific image processing algorithm that is currently implemented in python.
What would be the best approach, knowing that this script uses the Numpy library ?
I alreayd tried to compile the script to java using the jythonc compiler but it seems that it doesn't support dependencies... | 1 | 1 | 2,255 |
0 | 12,100,118 | 0 | 0 | 0 | 1 | 1 | false | 6 | 2011-10-26T11:15:00.000 | 1 | 4 | 0 | NumPy arrays with SQLite | 7,901,853 | 0.049958 | python,arrays,sqlite,numpy,scipy | This looks a bit older but is there any reason you cannot just do a fetchall() instead of iterating and then just initializing numpy on declaration? | The most common SQLite interface I've seen in Python is sqlite3, but is there anything that works well with NumPy arrays or recarrays? By that I mean one that recognizes data types and does not require inserting row by row, and extracts into a NumPy (rec)array...? Kind of like R's SQL functions in the RDB or sqldf lib... | 0 | 1 | 7,905 |
0 | 9,572,786 | 0 | 0 | 0 | 0 | 1 | false | 1 | 2011-10-26T14:21:00.000 | 1 | 1 | 0 | Detect Hand using OpenCV | 7,904,055 | 0.197375 | python,opencv,computer-vision,motion-detection | You can try the very basic but so effective and fast solution:
on the upper half of the image:
canny edge detection
morphologyEx with adequate Structuring element(also simple combination of erode/dilate may be enough)
convert to BW using adaptive threshold
Xor the result with a mask representing the expected covered a... | I want to use openCV to detect when a person raises or lowers a hand or both hands. I have looked through the tutorials provided by python opencv and none of them seem to do the job. There is a camera that sits in front of the 2 persons, about 50cm away from them(so you see them from the waist up). The person is able t... | 0 | 1 | 3,058 |
0 | 7,917,373 | 0 | 0 | 0 | 0 | 3 | false | 12 | 2011-10-26T20:52:00.000 | 1 | 6 | 0 | Generating random numbers under very specific constraints | 7,908,800 | 0.033321 | python,algorithm,random | Blocked Gibbs sampling is pretty simple and converges to the right distribution (this is along the lines of what Alexandre is proposing).
For all i, initialize ai = A / n and bi = B / n.
Select i ≠ j uniformly at random. With probability 1/2, update ai and aj with uniform random values satisfying the constraints. The ... | I am faced with the following programming problem. I need to generate n (a, b) tuples for which the sum of all a's is a given A and sum of all b's is a given B and for each tuple the ratio of a / b is in the range (c_min, c_max). A / B is within the same range, too. I am also trying to make sure there is no bias in the... | 0 | 1 | 2,895 |
0 | 7,908,987 | 0 | 0 | 0 | 0 | 3 | true | 12 | 2011-10-26T20:52:00.000 | 2 | 6 | 0 | Generating random numbers under very specific constraints | 7,908,800 | 1.2 | python,algorithm,random | Start by generating as many identical tuples, n, as you need:
(A/n, B/n)
Now pick two tuples at random. Make a random change to the a value of one, and a compensating change to the a value of the other, keeping everything within the given constraints. Put the two tuples back.
Now pick another random pair. This times... | I am faced with the following programming problem. I need to generate n (a, b) tuples for which the sum of all a's is a given A and sum of all b's is a given B and for each tuple the ratio of a / b is in the range (c_min, c_max). A / B is within the same range, too. I am also trying to make sure there is no bias in the... | 0 | 1 | 2,895 |
0 | 7,908,989 | 0 | 0 | 0 | 0 | 3 | false | 12 | 2011-10-26T20:52:00.000 | 2 | 6 | 0 | Generating random numbers under very specific constraints | 7,908,800 | 0.066568 | python,algorithm,random | I think the simplest thing is to
Use your favorite method to throw n-1 values such that \sum_i=0,n-1 a_i < A, and set a_n to get the right total. There are several SO question about doing that, though I've never seen a answer I'm really happy with yet. Maybe I'll write a paper or something.
Get the n-1 b's by throwing... | I am faced with the following programming problem. I need to generate n (a, b) tuples for which the sum of all a's is a given A and sum of all b's is a given B and for each tuple the ratio of a / b is in the range (c_min, c_max). A / B is within the same range, too. I am also trying to make sure there is no bias in the... | 0 | 1 | 2,895 |
0 | 7,909,874 | 0 | 1 | 0 | 0 | 3 | true | 3 | 2011-10-26T22:36:00.000 | 4 | 3 | 0 | Python - Run numpy without the python interpreter | 7,909,761 | 1.2 | python,numpy | find where numpy is installed on your system. For me, it's here:
/usr/lib/pymodules/python2.7
import it explicitly before importing numpy
import sys
sys.path.append('/usr/lib/pymodules/python2.7')
... if you need help finding the correct path, check the contents of sys.path while using your python interpreter
import s... | I have an .x3d code which references a python script. I am trying to implement certain functions which make use of the numpy module. However, I am only able to import the builtin modules from Python.
I am looking for a way to import the numpy module into the script without having to call the interpreter (i.e. "test.py"... | 0 | 1 | 1,209 |
0 | 7,909,895 | 0 | 1 | 0 | 0 | 3 | false | 3 | 2011-10-26T22:36:00.000 | 3 | 3 | 0 | Python - Run numpy without the python interpreter | 7,909,761 | 0.197375 | python,numpy | I'm going to guess that your #! line is pointing to a different python interpreter then the one you use normally. Make sure they point to the same one. | I have an .x3d code which references a python script. I am trying to implement certain functions which make use of the numpy module. However, I am only able to import the builtin modules from Python.
I am looking for a way to import the numpy module into the script without having to call the interpreter (i.e. "test.py"... | 0 | 1 | 1,209 |
0 | 7,909,774 | 0 | 1 | 0 | 0 | 3 | false | 3 | 2011-10-26T22:36:00.000 | 1 | 3 | 0 | Python - Run numpy without the python interpreter | 7,909,761 | 0.066568 | python,numpy | Add the num.py libraries to sys.path before you call import | I have an .x3d code which references a python script. I am trying to implement certain functions which make use of the numpy module. However, I am only able to import the builtin modules from Python.
I am looking for a way to import the numpy module into the script without having to call the interpreter (i.e. "test.py"... | 0 | 1 | 1,209 |
0 | 7,918,549 | 0 | 1 | 0 | 0 | 1 | true | 26 | 2011-10-27T14:07:00.000 | 17 | 2 | 0 | Add footnote under the x-axis using matplotlib | 7,917,107 | 1.2 | python,matplotlib | One way would be just use plt.text(x,y,'text') | I couldn't find the right function to add a footnote in my plot.
The footnote I want to have is something like an explanation of one item in the legend, but it is too long to put in the legend box. So, I'd like to add a ref number, e.g. [1], to the legend item, and add the footnote in the bottom of the plot, under the ... | 0 | 1 | 42,816 |
0 | 33,510,117 | 0 | 0 | 0 | 0 | 1 | false | 102 | 2011-10-27T21:14:00.000 | 0 | 4 | 0 | How to transform numpy.matrix or array to scipy sparse matrix | 7,922,487 | 0 | python,numpy,scipy,sparse-matrix | As for the inverse, the function is inv(A), but I won't recommend using it, since for huge matrices it is very computationally costly and unstable. Instead, you should use an approximation to the inverse, or if you want to solve Ax = b you don't really need A-1. | For SciPy sparse matrix, one can use todense() or toarray() to transform to NumPy matrix or array. What are the functions to do the inverse?
I searched, but got no idea what keywords should be the right hit. | 0 | 1 | 141,998 |
1 | 7,940,923 | 0 | 0 | 0 | 0 | 1 | false | 2 | 2011-10-29T18:33:00.000 | 0 | 1 | 0 | Error when importing OpenCV python module (when built with Qt and QtOpenGL) | 7,940,848 | 0 | python,qt,opencv,import | Probably need the qt dll's in the same place as the opencv dlls - and they have to be the version built with the same compiler as opencv (and possibly python) | I recently downloaded OpenCV 2.3.1, compiled with the CMake flags withQt and withQtOpenGL turned on. My Qt version is 4.7.4 and is configured with OpenGL enabled. Supposedly I only need to copy cv2.pyd to Python's site-package path:
C:\Python27\Lib\site-packages
And in the mean time make sure the OpenCV dlls are some... | 0 | 1 | 488 |
0 | 36,474,703 | 0 | 1 | 1 | 0 | 1 | false | 14 | 2011-11-02T23:14:00.000 | 2 | 5 | 0 | Efficient way to generate and use millions of random numbers in Python | 7,988,494 | 0.07983 | python,random | Code to generate 10M random numbers efficiently and faster:
import random
l=10000000
listrandom=[]
for i in range (l):
value=random.randint(0,l)
listrandom.append(value)
print listrandom
Time taken included the I/O time lagged in printing on screen:
real 0m27.116s
user 0m24.391s
sys 0m0.819s | I'm in the process of working on programming project that involves some pretty extensive Monte Carlo simulation in Python, and as such the generation of a tremendous number of random numbers. Very nearly all of them, if not all of them, will be able to be generated by Python's built in random module.
I'm something of a... | 0 | 1 | 12,900 |
0 | 8,002,777 | 0 | 0 | 0 | 0 | 1 | true | 14 | 2011-11-03T22:13:00.000 | 17 | 1 | 0 | Difference between HDF5 file and PyTables file | 8,002,569 | 1.2 | python,numpy,hdf5,pytables | PyTables files are HDF5 files.
However, as I understand it, PyTables adds some extra metadata to the attributes of each entry in the HDF file.
If you're looking for a more "vanilla" hdf5 solution for python/numpy, have a look a h5py.
It's less database-like (i.e. less "table-like") than PyTables, and doesn't have as ma... | Is there a difference between HDF5 files and files created by PyTables?
PyTables has two functions .isHDFfile() and .isPyTablesFile() suggesting that there
is a difference between the two formats.
I've done some looking around on Google and have gathered that PyTables is built on top of HDF, but I wasn't able to find ... | 0 | 1 | 2,253 |
0 | 8,019,217 | 0 | 0 | 1 | 0 | 2 | false | 1 | 2011-11-05T08:59:00.000 | 3 | 3 | 0 | Coalition Search Algorithm | 8,019,172 | 0.197375 | java,c++,python,c,algorithm | In other words, you have an array X[1..n], and want to have all the subsets of it for which sum(subset) >= 1/2 * sum(X), right?
That probably means the whole set qualifies.
After that, you can drop any element k having X[k] < 1/2 * sum(X), and every such a coalition will be fine as an answer, too.
After that, you can ... | I am looking for an algorithm that is implemented in C, C++, Python or Java that calculates the set of winning coalitions for n agents where each agent has a different amount of votes. I would appreciate any hints. Thanks! | 0 | 1 | 373 |
0 | 8,019,235 | 0 | 0 | 1 | 0 | 2 | false | 1 | 2011-11-05T08:59:00.000 | 0 | 3 | 0 | Coalition Search Algorithm | 8,019,172 | 0 | java,c++,python,c,algorithm | Arrange the number of votes for each of the agents into an array, and compute the partial sums from the right, so that you can find out SUM_i = k to n Votes[i] just by looking up the partial sum.
Then do a backtrack search over all possible subsets of {1, 2, ...n}. At any point in the backtrack you have accepted some s... | I am looking for an algorithm that is implemented in C, C++, Python or Java that calculates the set of winning coalitions for n agents where each agent has a different amount of votes. I would appreciate any hints. Thanks! | 0 | 1 | 373 |
0 | 15,979,342 | 0 | 0 | 0 | 0 | 1 | false | 3 | 2011-11-08T03:24:00.000 | 4 | 2 | 0 | How to force the functions of the optimize module of scipy to take a function and its gradient simultaneously | 8,045,576 | 0.379949 | python,optimization,scipy | The scipy.optimize.minimize methods has a parameter called "jac". If set to True, minimize will expect the callable f(x) to both return the function value and it's derivatives. | I have a fairly complex function f(x) that I want to optimize and I am using the fmin_bfgs function from the scipy.optimize module from Scipy. It forces me to give the function to minimize and the function of the gradient f'(x) separately, which is a pity because some of the computations for the gradient can be done w... | 0 | 1 | 557 |
0 | 8,052,660 | 0 | 0 | 0 | 0 | 1 | false | 5 | 2011-11-08T15:10:00.000 | 0 | 2 | 0 | exponential moving sum in numpy / scipy? | 8,052,582 | 0 | python,numpy,scipy,vectorization | You can try to improve python loops by doing good "practices" (like avoiding dots).
Maybe you can code you function in C (into a "numpy library") and call it from python. | I am looking for a function to calculate exponential moving sum in numpy or scipy. I want to avoid using python loops because they are really slow.
to be specific, I have two series A[] and T[]. T[i] is the timestamp of value A[i]. I define a half-decay period tau. For a given time t, the exponential moving sum is the... | 0 | 1 | 2,259 |
0 | 11,141,963 | 0 | 0 | 0 | 0 | 1 | true | 2 | 2011-11-10T16:54:00.000 | 0 | 1 | 0 | Using OpenCV and Python to stitch puzzle images together | 8,083,263 | 1.2 | python,image-processing,opencv,image-stitching | If this is a small fun project that you are trying to do, you can compare image histograms or use SIFT/SURF. I don't think there is implementation of SIFT, SURF in Python API. If you can find compatible equivalent, you can do it.
Comparing images are very much dependent on the data-set that you have. Some techniques wo... | I am trying to use OpenCV and Python to stitch together several hundred puzzle piece images into one large, complete image. All of the images are digitized and are in a PNG format. The pieces were originally from a scan and extracted into individual pieces, so they have transparent backgrounds and are each a single p... | 0 | 1 | 1,769 |
0 | 8,091,830 | 0 | 0 | 0 | 0 | 3 | false | 6 | 2011-11-11T08:08:00.000 | 0 | 7 | 0 | better algorithm for checking 5 in a row/col in a matrix | 8,091,248 | 0 | python,algorithm,matrix | I don't think you can avoid iteration, but you can at least do an XOR of all elements and if the result of that is 0 => they are all equal, then you don't need to do any comparisons. | is there a good algorithm for checking whether there are 5 same elements in a row or a column or diagonally given a square matrix, say 6x6?
there is ofcourse the naive algorithm of iterating through every spot and then for each point in the matrix, iterate through that row, col and then the diagonal. I am wondering if ... | 0 | 1 | 3,808 |
0 | 8,098,697 | 0 | 0 | 0 | 0 | 3 | false | 6 | 2011-11-11T08:08:00.000 | 0 | 7 | 0 | better algorithm for checking 5 in a row/col in a matrix | 8,091,248 | 0 | python,algorithm,matrix | You can try improve your method with some heuristics: use the knowledge of the matrix size to exclude element sequences that do not fit and suspend unnecessary calculation. In case the given vector size is 6, you want to find 5 equal elements, and the first 3 elements are different, further calculation do not have any ... | is there a good algorithm for checking whether there are 5 same elements in a row or a column or diagonally given a square matrix, say 6x6?
there is ofcourse the naive algorithm of iterating through every spot and then for each point in the matrix, iterate through that row, col and then the diagonal. I am wondering if ... | 0 | 1 | 3,808 |
0 | 8,091,403 | 0 | 0 | 0 | 0 | 3 | false | 6 | 2011-11-11T08:08:00.000 | 0 | 7 | 0 | better algorithm for checking 5 in a row/col in a matrix | 8,091,248 | 0 | python,algorithm,matrix | Your best approach may depend on whether you control the placement of elements.
For example, if you were building a game and just placed the most recent element on the grid, you could capture into four strings the vertical, horizontal, and diagonal strips that intersected that point, and use the same algorithm on each ... | is there a good algorithm for checking whether there are 5 same elements in a row or a column or diagonally given a square matrix, say 6x6?
there is ofcourse the naive algorithm of iterating through every spot and then for each point in the matrix, iterate through that row, col and then the diagonal. I am wondering if ... | 0 | 1 | 3,808 |
0 | 8,288,377 | 0 | 0 | 0 | 0 | 1 | true | 7 | 2011-11-11T16:02:00.000 | 2 | 1 | 0 | HDF5 for Python: high level vs low level interfaces. h5py | 8,096,668 | 1.2 | python,performance,hdf5,h5py | High-level interfaces are generally going with a performance loss of some sort. After that, whether it is noticeable (worth being investigated) will depend on what you are doing exactly with your code.
Just start with the high-level interface. If the code is overall too slow, start profiling and move the bottlenecks do... | I've been working with HDF5 files with C and Matlab, both using the same way for reading from and writing to datasets:
open file with h5f
open dataset with h5d
select space with h5s
and so on...
But now I'm working with Python, and with its h5py library I see that it has two ways to manage HDF5: high-level and low-le... | 0 | 1 | 932 |
0 | 8,121,141 | 0 | 0 | 1 | 0 | 1 | true | 5 | 2011-11-14T10:01:00.000 | 1 | 2 | 0 | Get the complete structure of a program? | 8,119,900 | 1.2 | python,coding-style | UML generation is provided by pyreverse - it's part of pylint package
It generates UML in dot format - or png, etc.
It creates UML diagram, so you can easily see basic structure of your code
I'm not sure if it satisfy all your needs, but it might be helpful | I would have a quite simple question, but can't find any suitable automated solution for now.
I have developed an algorithm that performs a lot of stuff (image processing in fact) in Python.
What I want to do now is to optimize it. And for that, I would love to create a graph of my algorithm.
Kind of an UML chart or ... | 0 | 1 | 435 |
0 | 8,147,354 | 0 | 0 | 0 | 0 | 1 | false | 4 | 2011-11-15T21:34:00.000 | 0 | 3 | 0 | How do get matplotlib pyplot to generate a chart for viewing / output to .png at a specific resolution? | 8,143,439 | 0 | python,matplotlib | For resolution, you can use the dpi (dots per inch) argument when creating a figure, or in the savefig() function. For high quality prints of graphics dpi=600 or more is recommended. | I'm fed up with manually creating graphs in excel and consequently, I'm trying to automate the process using Python to massage the .csv data into a workable form and matplotlib to plot the result.
Using matplotlib and generating them is no problem but I can't work out is how to set the aspect ration / resolution of the... | 0 | 1 | 1,578 |
0 | 16,157,331 | 0 | 0 | 0 | 0 | 1 | false | 6 | 2011-11-15T22:17:00.000 | 4 | 5 | 0 | Modeling a linear system with Python | 8,144,910 | 0.158649 | simulation,python,modeling | As @Matt said, I know this is old. But this came up as my first google hit, so I wanted to edit it.
You can use scipy.signal.lti to model linear, time invariant systems. That gives you lti.bode.
For an impulse response in the form of H(s) = (As^2 + Bs + C)/(Ds^2 + Es + F), you would enter h = scipy.signal.lti([A,B,C],[... | I would like to simulate/model a closed-loop, linear, time-invariant system (specifically a locked PLL approximation) with python.
Each sub-block within the model has a known transfer function which is given in terms of complex frequency H(s) = K / ( s * tau + 1 ). Using the model, I would like to see how the system ... | 0 | 1 | 14,035 |
0 | 9,634,189 | 0 | 0 | 0 | 0 | 1 | false | 0 | 2011-11-16T13:34:00.000 | 0 | 2 | 0 | Tracking two different colors using OpenCV 2.3 and Python | 8,152,504 | 0 | python,opencv | I don't really understand your concern.
With the camera, you would get an image object.
With this image object, you can calculate as much different histograms as you want.
Each histogram would be a different output object :).
Basicaly, you could track hundreds of colors at the same time! | I'm looking for a way to track two different colors at the same time using a single camera with OpenCV 2.3 (python bindings).
I've read through a number of papers regarding OpenCV but can't find any mention as to whether or not it's capable of analyzing multiple histograms at once.
Is this is even technically possibl... | 0 | 1 | 4,911 |
0 | 8,194,069 | 0 | 0 | 0 | 0 | 1 | false | 9 | 2011-11-19T10:58:00.000 | 1 | 4 | 0 | Predicting Values with k-Means Clustering Algorithm | 8,193,563 | 0.049958 | python,machine-learning,data-mining,k-means,prediction | If you are considering assigning a value based on the average value within the nearest cluster, you are talking about some form of "soft decoder", which estimates not only the correct value of the coordinate but your level of confidence in the estimate. The alternative would be a "hard decoder" where only values of 0 ... | I'm messing around with machine learning, and I've written a K Means algorithm implementation in Python. It takes a two dimensional data and organises them into clusters. Each data point also has a class value of either a 0 or a 1.
What confuses me about the algorithm is how I can then use it to predict some values for... | 0 | 1 | 14,656 |
0 | 8,232,587 | 0 | 0 | 0 | 0 | 1 | false | 6 | 2011-11-22T10:41:00.000 | 0 | 2 | 0 | Getting matplotlib plots to refresh on mouse focus | 8,225,460 | 0 | python,matplotlib | Have you tried to call plt.figure(fig.number) before plotting on figure fig and plt.show() after plotting a figure? It should update all the figures. | I am using matplotlib with interactive mode on and am performing a computation, say an optimization with many steps where I plot the intermediate results at each step for debugging purposes. These plots often fill the screen and overlap to a large extent.
My problem is that during the calculation, figures that are part... | 0 | 1 | 2,049 |
0 | 8,236,857 | 0 | 1 | 0 | 0 | 1 | false | 0 | 2011-11-23T03:02:00.000 | 1 | 5 | 0 | Python Sorting Lists in Lists | 8,236,823 | 0.039979 | python,list | What's wrong with itemgetter?
lst.sort(key=lambda l: list(reversed(l)) should do the trick | Given: lst = [['John',3],['Blake',4],['Ted',3]]
Result: lst = [['John',3],['Ted',3],['Blake',4]]
I'm looking for a way to sort lists in lists first numerically then alphabetically without the use of the "itemgetter" syntax. | 0 | 1 | 1,274 |
0 | 8,289,322 | 0 | 0 | 0 | 0 | 1 | false | 11 | 2011-11-27T21:21:00.000 | 0 | 7 | 0 | Alternative to scipy and numpy for linear algebra? | 8,289,157 | 0 | python | I sometimes have this problem..not sure if this works but I often install it using my own account then try to run it in an IDE(komodo in my case) and it doesn't work. Like your issue it says it cannot find it. The way I solve this is to use sudo -i to get into root and then install it from there.
If that does not work ... | Is there a good (small and light) alternative to numpy for python, to do linear algebra?
I only need matrices (multiplication, addition), inverses, transposes and such.
Why?
I am tired of trying to install numpy/scipy - it is such a pita to get
it to work - it never seems to install correctly (esp. since I have
tw... | 0 | 1 | 10,052 |
0 | 8,314,002 | 0 | 0 | 0 | 0 | 1 | false | 1 | 2011-11-29T14:43:00.000 | 0 | 3 | 0 | python - audio classification of equal length samples / 'vocoder' thingy | 8,312,672 | 0 | python,audio,classification,fft,pyaudioanalysis | Try searching for algorithms on "music fingerprinting". | Anybody able to supply links, advice, or other forms of help to the following?
Objective - use python to classify 10-second audio samples so that I afterwards can speak into a microphone and have python pick out and play snippets (faded together) of closest matches from db.
My objective is not to have the closest matc... | 0 | 1 | 1,085 |
0 | 8,341,353 | 0 | 1 | 0 | 0 | 1 | true | 11 | 2011-12-01T11:23:00.000 | 6 | 2 | 0 | Python ast to dot graph | 8,340,567 | 1.2 | python,grammar,abstract-syntax-tree | If you look at ast.NodeVisitor, it's a fairly trivial class. You can either subclass it or just reimplement its walking strategy to whatever you need. For instance, keeping references to the parent when nodes are visited is very simple to implement this way, just add a visit method that also accepts the parent as an ar... | I'm analyzing the AST generated by python code for "fun and profit", and I would like to have something more graphical than "ast.dump" to actually see the AST generated.
In theory is already a tree, so it shouldn't be too hard to create a graph, but I don't understand how I could do it.
ast.walk seems to walk with a BF... | 0 | 1 | 3,299 |
0 | 8,385,718 | 0 | 1 | 0 | 0 | 1 | false | 84 | 2011-12-05T12:53:00.000 | 0 | 6 | 0 | Why are NumPy arrays so fast? | 8,385,602 | 0 | python,arrays,numpy | Numpy arrays are extremily similar to 'normal' arrays such as those in c. Notice that every element has to be of the same type. The speedup is great because you can take advantage of prefetching and you can instantly access any element in array by it's index. | I just changed a program I am writing to hold my data as numpy arrays as I was having performance issues, and the difference was incredible. It originally took 30 minutes to run and now takes 2.5 seconds!
I was wondering how it does it. I assume it is that the because it removes the need for for loops but beyond that I... | 0 | 1 | 47,312 |
1 | 8,539,266 | 0 | 0 | 0 | 0 | 1 | true | 0 | 2011-12-05T16:41:00.000 | 0 | 1 | 0 | How can I keep row selections in QItemSelectionModel when columns are sorted? | 8,388,659 | 1.2 | python,pyqt | Here is the way I ended up solving this problem:
When row selections are made, put the unique IDs of each hidden row into a list, then hide all hidden rows
Use self.connect(self.myHorizontalHeader, SIGNAL("sectionClicked(int)"), self.keepSelectionValues) to catch the
event when a user clicks on a column header to sort... | I'm using QItemSelectionModel with QTableView to allow the users to select rows. The problem is that when the user then clicks on a column header to sort the rows, the selection disappears and all the sorted data is displayed. How can I keep the selection, and just sort that, rather than having all the rows appear?
Tha... | 0 | 1 | 623 |
0 | 8,396,124 | 0 | 0 | 0 | 0 | 3 | true | 115 | 2011-12-06T06:20:00.000 | 221 | 4 | 0 | Invert image displayed by imshow in matplotlib | 8,396,101 | 1.2 | python,image,matplotlib | Specify the keyword argument origin='lower' or origin='upper' in your call to imshow. | I wanted the imshow() function in matplotlib.pyplot to display images the opposite way, i.e upside down. Is there a simple way to do this? | 0 | 1 | 82,762 |
0 | 67,577,958 | 0 | 0 | 0 | 0 | 3 | false | 115 | 2011-12-06T06:20:00.000 | 1 | 4 | 0 | Invert image displayed by imshow in matplotlib | 8,396,101 | 0.049958 | python,image,matplotlib | You can use the extent argument. For example, if X values range from -10 and 10 and Y values range from -5 to 5, you should pass extent=(-10,10,-5,5) to imshow(). | I wanted the imshow() function in matplotlib.pyplot to display images the opposite way, i.e upside down. Is there a simple way to do this? | 0 | 1 | 82,762 |
0 | 68,682,366 | 0 | 0 | 0 | 0 | 3 | false | 115 | 2011-12-06T06:20:00.000 | 0 | 4 | 0 | Invert image displayed by imshow in matplotlib | 8,396,101 | 0 | python,image,matplotlib | Use ax.invert_yaxis() to invert the y-axis, or ax.invert_xaxis() to invert the x-axis. | I wanted the imshow() function in matplotlib.pyplot to display images the opposite way, i.e upside down. Is there a simple way to do this? | 0 | 1 | 82,762 |
0 | 8,410,307 | 0 | 0 | 0 | 0 | 1 | true | 2 | 2011-12-07T04:06:00.000 | 4 | 1 | 0 | randomly select a 200x200 square inside an image in python | 8,410,260 | 1.2 | python,image-processing,matplotlib,python-imaging-library | If you convert to binary PPM format, then there should be an easy way to seek to the appropriate offsets - it's not compressed, so there should be simple relationships.
So pick two random numbers between 0 and 100000-200-1, and go to town.
(I'm assuming you don't have a system with 10's of gigabytes of RAM) | I am using python to work on my project in image processing. Suppose I got a very large image ( 100000 x 100000), and I need to randomly select a 200 x 200 square from this large image. Are there any easy way to do this job? Please share some light with me. Thank you
----------------------------- EDIT -----------------... | 0 | 1 | 465 |
0 | 8,414,694 | 0 | 1 | 0 | 0 | 2 | false | 1 | 2011-12-07T06:51:00.000 | 0 | 5 | 0 | Python: large number of dict like objects memory use | 8,411,476 | 0 | python,memory,dictionary | Possibilities:
(1) Benchmark the csv.DictReader approach and see if it causes a problem. Note that the dicts contain POINTERS to the keys and values; the actual key strings are not copied into each dict.
(2) For each file, use csv.Reader, after the first row, build a class dynamically, instantiate it once per remaining... | I am using csv.DictReader to read some large files into memory to then do some analysis, so all objects from multiple CSV files need to be kept in memory. I need to read them as Dictionary to make analysis easier, and because the CSV files may be altered by adding new columns.
Yes SQL can be used, but I'd rather avoid... | 0 | 1 | 490 |
0 | 8,411,784 | 0 | 1 | 0 | 0 | 2 | false | 1 | 2011-12-07T06:51:00.000 | 0 | 5 | 0 | Python: large number of dict like objects memory use | 8,411,476 | 0 | python,memory,dictionary | If all the data in one column are the same type, you can use NumPy. NumPy's loadtxt and genfromtxt function can be used to read csv file. And because it returns an array, the memory usage is smaller then dict. | I am using csv.DictReader to read some large files into memory to then do some analysis, so all objects from multiple CSV files need to be kept in memory. I need to read them as Dictionary to make analysis easier, and because the CSV files may be altered by adding new columns.
Yes SQL can be used, but I'd rather avoid... | 0 | 1 | 490 |
0 | 8,450,596 | 0 | 0 | 0 | 0 | 1 | false | 0 | 2011-12-09T17:39:00.000 | 0 | 3 | 0 | matlab: randomly permuting rows and columns of a 2-D array | 8,449,501 | 0 | python,matlab,random,permutation | Both solutions above are great, and will work, but I believe both will involve making a completely new copy of the entire matrix in memory while doing the work. Since this is a huge matrix, that's pretty painful. In the case of the MATLAB solution, I think you'll be possibly creating two extra temporary copies, dependi... | I have a large matrix (approx. 80,000 X 60,000), and I basically want to scramble all the entries (that is, randomly permute both rows and columns independently).
I believe it'll work if I loop over the columns, and use randperm to randomly permute each column. (Or, I could equally well do rows.) Since this involves a... | 0 | 1 | 2,124 |
0 | 8,458,779 | 0 | 0 | 0 | 0 | 1 | false | 6 | 2011-12-10T14:15:00.000 | 1 | 3 | 0 | How to vectorize the evaluation of bilinear & quadratic forms? | 8,457,110 | 0.066568 | python,r,matlab,matrix,numpy | It's not entirely clear what you're trying to achieve, but in R, you use crossprod to form cross-products: given matrices X and Y with compatible dimensions, crossprod(X, Y) returns XTY. Similarly, matrix multiplication is achieved with the %*% operator: X %*% Y returns the product XY. So you can get XTAY as crossprod(... | Given any n x n matrix of real coefficients A, we can define a bilinear form bA : Rn x Rn → R by
bA(x, y) = xTAy ,
and a quadratic form qA : Rn → R by
qA(x) = bA(x, x) = xTAx .
(For most common applications of quadratic forms qA, the matrix A is symmetric, or even symmetric positive definite, so feel free to assume... | 0 | 1 | 3,364 |
0 | 8,523,192 | 0 | 1 | 0 | 0 | 1 | false | 3 | 2011-12-15T15:51:00.000 | 0 | 4 | 0 | Sorting a Python list by third element, then by first element, etc? | 8,522,800 | 0 | python,list,sorting | If you go further down the page Mr. White linked to, you'll see how you can specify an arbitrary function to compute your sort key (using the handy cmp_to_key function provided). | Say I have a list in the form [[x,y,z], [x,y,z] etc...] etc where each grouping represents a random point.
I want to order my points by the z coordinate, then within each grouping of z's, sort them by x coordinate. Is this possible? | 0 | 1 | 3,538 |
0 | 8,590,831 | 0 | 0 | 0 | 0 | 1 | false | 3 | 2011-12-20T21:57:00.000 | 1 | 1 | 0 | Retrain a pybrain neural network after adding to the dataset | 8,582,498 | 0.197375 | python,neural-network,pybrain | It dependes of what is your objective. If you need an updated NN-model you can perform an online training, i.e. performing a single step of back-propagation with the sample acquired at time $t$ starting from the network you had at time $t-1$. Or maybe you can discard the older samples in order to have a fixed amount of... | I have a pybrain NN up and running, and it seems to be working rather well. Ideally, I would like to train the network and obtain a prediction after each data point (the previous weeks figures, in this case) has been added to the dataset.
At the moment I'm doing this by rebuilding the network each time, but it takes an... | 0 | 1 | 985 |
0 | 8,592,302 | 0 | 0 | 0 | 0 | 1 | true | 5 | 2011-12-21T15:15:00.000 | 8 | 2 | 0 | Is random.expovariate equivalent to a Poisson Process | 8,592,048 | 1.2 | python,math,statistics,poisson | On a strict reading of your question, yes, that is what random.expovariate does.
expovariate gives you random floating point numbers, exponentially distributed. In a Poisson process the size of the interval between consecutive events is exponential.
However, there are two other ways I could imagine modelling poiss... | I read somewhere that the python library function random.expovariate produces intervals equivalent to Poisson Process events.
Is that really the case or should I impose some other function on the results? | 0 | 1 | 12,528 |
0 | 25,213,056 | 0 | 0 | 0 | 0 | 1 | false | 22 | 2011-12-21T16:30:00.000 | 0 | 6 | 0 | Robust Hand Detection via Computer Vision | 8,593,091 | 0 | python,image-processing,opencv,computer-vision,skin | Well my experience with the skin modeling are bad, because:
1) lightning can vary - skin segmentation is not robust
2) it will mark your face also (as other skin-like objects)
I would use machine learning techniques like Haar training, which, in my opinion, if far more better approach than modeling and fixing some cons... | I am currently working on a system for robust hand detection.
The first step is to take a photo of the hand (in HSV color space) with the hand placed in a small rectangle to determine the skin color. I then apply a thresholding filter to set all non-skin pixels to black and all skin pixels white.
So far it works quite... | 0 | 1 | 11,923 |
0 | 8,633,193 | 0 | 0 | 0 | 0 | 2 | false | 0 | 2011-12-26T05:17:00.000 | 0 | 2 | 1 | Hadoop - Saving Log Data and Developing GUI | 8,633,112 | 0 | java,python,hadoop | I think you can use HIVE. Even I am new to Hadoop but read some where that HIVE is for hadoop analytics. Not sure whether it has GUI or not, but for sure it has SQL capability to query unstructed data. | I am doing research for my new project, Following is the details of my project, research and questions:
Project:
Save the Logs (ex. format is TimeStamp,LOG Entry,Location,Remarks etc ) from different sources. Here Different sources is like, gettting the LOG data from the different systems world wide (Just an Overview)... | 0 | 1 | 321 |
0 | 8,633,276 | 0 | 0 | 0 | 0 | 2 | false | 0 | 2011-12-26T05:17:00.000 | 1 | 2 | 1 | Hadoop - Saving Log Data and Developing GUI | 8,633,112 | 0.099668 | java,python,hadoop | Have you looked at Datameer ? It provides a GUI to import all these types of files, and create reports as well as dashboards. | I am doing research for my new project, Following is the details of my project, research and questions:
Project:
Save the Logs (ex. format is TimeStamp,LOG Entry,Location,Remarks etc ) from different sources. Here Different sources is like, gettting the LOG data from the different systems world wide (Just an Overview)... | 0 | 1 | 321 |
0 | 8,660,103 | 0 | 0 | 0 | 0 | 1 | false | 4 | 2011-12-28T18:53:00.000 | 1 | 2 | 0 | Markov chain on letter scale and random text | 8,660,015 | 0.099668 | python,markov-chains | If each character only depends on the previous character, you could just compute the probabilities for all 27^2 pairs of characters. | I would like to generate a random text using letter frequencies from a book in a .txt file, so that each new character (string.lowercase + ' ') depends on the previous one.
How do I use Markov chains to do so? Or is it simpler to use 27 arrays with conditional frequencies for each letter? | 0 | 1 | 1,880 |
0 | 8,724,586 | 0 | 0 | 0 | 0 | 1 | false | 1 | 2012-01-02T10:19:00.000 | 0 | 1 | 0 | Linking segments of edges | 8,699,665 | 0 | python,image-processing,edge-detection | You can use a method named dynamic programming. A very good intro on this can be found on chapter 6 of Sonka's digital image processing book | I have written a canny edge detection algorithm for a project. I want to know is there any method to link the broken segments of an edge, since i am getting a single edge as a conglomeration of a few segments. I am getting around 100 segments, which i am sure can be decreased with some intelligence. Please help. | 0 | 1 | 433 |
0 | 8,711,375 | 0 | 0 | 0 | 0 | 1 | true | 0 | 2012-01-03T10:52:00.000 | 3 | 2 | 1 | Formatting a single row as CSV | 8,711,147 | 1.2 | python,csv | The csv module wraps the _csv module, which is written in C. You could grab the source for it and modify it to not require the file-like object, but poking around in the module, I don't see any clear way to do it without recompiling. | I'm creating a script to convert a whole lot of data into CSV format. It runs on Google AppEngine using the mapreduce API, which is only relevant in that it means each row of data is formatted and output separately, in a callback function.
I want to take advantage of the logic that already exists in the csv module to c... | 0 | 1 | 464 |
0 | 8,717,213 | 0 | 1 | 0 | 0 | 1 | false | 18 | 2012-01-03T18:52:00.000 | 2 | 2 | 0 | Chunking data from a large file for multiprocessing? | 8,717,179 | 0.197375 | python,parallel-processing | I would keep it simple. Have a single program open the file and read it line by line. You can choose how many files to split it into, open that many output files, and every line write to the next file. This will split the file into n equal parts. You can then run a Python program against each of the files in parallel. | I'm trying to a parallelize an application using multiprocessing which takes in
a very large csv file (64MB to 500MB), does some work line by line, and then outputs a small, fixed size
file.
Currently I do a list(file_obj), which unfortunately is loaded entirely
into memory (I think) and I then I break that list up in... | 0 | 1 | 14,016 |
0 | 8,741,894 | 0 | 1 | 0 | 0 | 1 | false | 2 | 2012-01-05T01:13:00.000 | 0 | 4 | 0 | Parallel computing | 8,736,396 | 0 | python | Like the commentators have said, find someone to talk to in your university. The answer to your question will be specific to what software is installed on the grid. If you have access to a grid, it's highly likely you also have access to a person whose job it is to answer your questions (and they will be pleased to h... | I have a two dimensional table (Matrix)
I need to process each line in this matrix independently from the others.
The process of each line is time consuming.
I'd like to use parallel computing resources in our university (Canadian Grid something)
Can I have some advise on how to start ? I never used parallel computing ... | 0 | 1 | 1,155 |
0 | 21,651,546 | 0 | 1 | 0 | 0 | 1 | false | 82 | 2012-01-05T07:49:00.000 | 2 | 9 | 0 | How to solve a pair of nonlinear equations using Python? | 8,739,227 | 0.044415 | python,numpy,scipy,sympy | You can use openopt package and its NLP method. It has many dynamic programming algorithms to solve nonlinear algebraic equations consisting:
goldenSection, scipy_fminbound, scipy_bfgs, scipy_cg, scipy_ncg, amsg2p, scipy_lbfgsb, scipy_tnc, bobyqa, ralg, ipopt, scipy_slsqp, scipy_cobyla, lincher, algencan, which you c... | What's the (best) way to solve a pair of non linear equations using Python. (Numpy, Scipy or Sympy)
eg:
x+y^2 = 4
e^x+ xy = 3
A code snippet which solves the above pair will be great | 0 | 1 | 135,871 |
0 | 43,361,173 | 0 | 0 | 0 | 1 | 1 | false | 2 | 2012-01-05T23:13:00.000 | 0 | 3 | 0 | does cassandra cql support aggregation functions, like group by and order by | 8,751,293 | 0 | python,cassandra,cql | Latest versions of Cassandra support aggregations within single partition only. | For example in CQL,
SELECT * from abc_dimension ORDER BY key ASC;
seems to be not working.
Any help? | 0 | 1 | 3,328 |
0 | 8,775,931 | 0 | 0 | 0 | 0 | 1 | false | 6 | 2012-01-08T06:12:00.000 | 2 | 3 | 0 | Efficient ways to write a large NumPy array to a file | 8,775,786 | 0.132549 | python,numpy,scientific-computing | I would recommend looking at the pickle module. The pickle module allows you to serialize python objects as streams of bytes (e.g., strings). This allows you to write them to a file or send them over a network, and then reinstantiate the objects later. | I've currently got a project running on PiCloud that involves multiple iterations of an ODE Solver. Each iteration produces a NumPy array of about 30 rows and 1500 columns, with each iterations being appended to the bottom of the array of the previous results.
Normally, I'd just let these fairly big arrays be returned ... | 0 | 1 | 8,395 |
0 | 33,917,789 | 0 | 0 | 0 | 0 | 1 | false | 5 | 2012-01-12T18:15:00.000 | 0 | 2 | 0 | OpenCV Lip Segmentation | 8,840,127 | 0 | python,opencv,face-detection,simplecv | The color segementation involves "gradient of the difference between the pseudo-hue and luminance (obtaining hybrid contours)". Try googling for qouted string and you will find multiple research papers on this topic. | How do people usually extract the shape of the lips once the mouth region is found (in my case using haar cascade)? I tried color segmentation and edge/corner detection but they're very inaccurate for me. I need to find the two corners and the very upper and lower lip at the center. I've heard things about active appea... | 0 | 1 | 4,301 |
0 | 8,860,314 | 0 | 1 | 0 | 0 | 1 | true | 5 | 2012-01-12T20:08:00.000 | 2 | 4 | 0 | Find subject in incomplete sentence with NLTK | 8,841,569 | 1.2 | python,nlp,nltk | NLP techniques are relatively ill equipped to deal with this kind of text.
Phrased differently: it is quite possible to build a solution which includes NLP processes to implement the desired classifier but the added complexity doesn't necessarily pays off in term of speed of development nor classifier precision improve... | I have a list of products that I am trying to classify into categories. They will be described with incomplete sentences like:
"Solid State Drive Housing"
"Hard Drive Cable"
"1TB Hard Drive"
"500GB Hard Drive, Refurbished from Manufacturer"
How can I use python and NLP to get an output like "Housing, Cable, Drive, Dri... | 0 | 1 | 2,952 |
0 | 8,858,983 | 0 | 0 | 0 | 0 | 1 | false | 5 | 2012-01-14T00:11:00.000 | 0 | 4 | 0 | converting a space delimited file to a CSV | 8,858,946 | 0 | python | str.split() without any arguments will split by any length of whitespace. operator.itemgetter() takes multiple arguments, and will return a tuple. | I have a text file containing tabular data. What I need to do is automate the task of writing to a new text file that is comma delimited instead of space delimited, extract a few columns from existing data, reorder the columns.
This is a snippet of the first 4 lines of the original data:
Number of rows: 8542
Algor... | 0 | 1 | 18,146 |
0 | 9,473,690 | 0 | 0 | 0 | 0 | 1 | false | 6 | 2012-01-14T19:03:00.000 | 0 | 7 | 0 | Convert netcdf to image | 8,864,599 | 0 | python,netcdf | IDV is a good visualization tool for NetCDF, but, as far as I know, there is no command line interface.
I would recommend Matlab. It has read and write functions for NetCDF as well as an extensive plotting library...probably one of the best. You can then compile the matlab code and run it from the command line. | I have a netcdf file that I would like to convert to an image (joed, png, gif) using a command line tool.
Is someone could please help me with the library name and possibly a link to how it is done.
Regards
David | 0 | 1 | 8,951 |
0 | 8,959,115 | 0 | 1 | 0 | 0 | 1 | false | 2 | 2012-01-18T22:59:00.000 | 2 | 2 | 0 | 'Memory leak' when calling openopt SNLE in a loop | 8,918,773 | 0.197375 | python,memory-leaks,numpy,scipy | Yes, there is clearly a memory leak here. I ran the nlsp demo, that uses SNLE with interalg, using valgrind and found that 295k has been leaked from running the solver once. This should be reported to them. | Whenever I run the solver 'interalg' (in the SNLE function call from OpenOpt) in a loop my memory usage accumulates until the code stops running.
It happen both in my Mac Os X 10.6.8 and in Slackware Linux.
I would really appreciate some advice, considering that I am not extremely literate in python.
Thank you!
Daniel | 0 | 1 | 143 |
0 | 8,938,840 | 0 | 0 | 0 | 0 | 1 | false | 25 | 2012-01-20T08:15:00.000 | 2 | 5 | 0 | How to extract data from matplotlib plot | 8,938,449 | 0.07983 | python,matplotlib | Its Python, so you can modify the source script directly so the data is dumped before it is plotted | I have a wxPython program which reads from different datasets, performs various types of simple on-the-fly analysis on the data and plots various combinations of the datasets to matplotlib canvas. I would like to have the opportunity to dump currently plotted data to file for more sophisticated analysis later on.
The ... | 0 | 1 | 31,312 |
0 | 8,954,018 | 0 | 0 | 0 | 0 | 2 | true | 0 | 2012-01-21T15:03:00.000 | 2 | 3 | 0 | python: least-squares estimation? | 8,953,991 | 1.2 | python,matrix,numerical-methods | scipy and numpy is the obvious way to go here.
Note that numpy uses the famous (and well-optimized) BLAS libraries, so it is also very fast. Much faster than any "pure python" will ever be. | I know how to implement least-squares with elementary matrix decomposition and other operations, but how can I do it in Python? (I've never tried to use matrices in Python)
(clarification edit to satisfy the shoot-first-and-ask-questions-later -1'er)
I was looking for help to find out how to use numerical programming ... | 0 | 1 | 819 |
0 | 8,954,011 | 0 | 0 | 0 | 0 | 2 | false | 0 | 2012-01-21T15:03:00.000 | 1 | 3 | 0 | python: least-squares estimation? | 8,953,991 | 0.066568 | python,matrix,numerical-methods | Have a look at SciPy. It's got matrix operations. | I know how to implement least-squares with elementary matrix decomposition and other operations, but how can I do it in Python? (I've never tried to use matrices in Python)
(clarification edit to satisfy the shoot-first-and-ask-questions-later -1'er)
I was looking for help to find out how to use numerical programming ... | 0 | 1 | 819 |
0 | 9,020,306 | 0 | 0 | 0 | 0 | 1 | false | 2 | 2012-01-26T14:52:00.000 | 1 | 2 | 0 | Finding 'edge cases' in a dataset | 9,019,949 | 0.099668 | python,statistics,matplotlib | I think what you want is a variance plot. Create a dictionary for distinct x values. Put each distinct value of y in a list associated with each x. Find the stdev (np.std) of the list associated with each x say "s". Plot the s vs. x. | i apologize in advance for not being very precise, as a i dont know the mathematical expression for what i want.
i am using matplotlib to analyze a large dataset. What i have now is a distribution of x,y points. I want to find out the cases in which the x values of my function are the same, but y differs the greatest.... | 0 | 1 | 960 |
0 | 9,027,774 | 0 | 1 | 0 | 0 | 1 | false | 3 | 2012-01-27T00:07:00.000 | 3 | 3 | 0 | merging records in python or numpy | 9,027,355 | 0.197375 | python,merge,numpy | You can use a dictionary if the values are lists. defaultdict in the collections module is very useful for this. | I have a csv file in which the first column contains an identifier and the second column associated data. The identifier is replicated an arbitrary number of times so the file looks like this.
data1,123
data1,345
data1,432
data2,654
data2,431
data3,947
data3,673
I would like to merge the records to generate a single... | 0 | 1 | 267 |
0 | 9,144,538 | 0 | 0 | 0 | 0 | 2 | false | 0 | 2012-01-27T09:01:00.000 | 0 | 2 | 0 | How to create columns in a csv file and insert row under them in python scrapy | 9,030,953 | 0 | python,scrapy | 1)you can use custom Csv feed exporter each item key will be treated as a column heading and value as column value.
2) you can write a pipeline that can write data in csv file using python csv lib. | Please help me in creating columns and inserting rows under them in a csv file using python scrapy. I need to write scraped data into 3 columns. So first of all three columns are to be created and then data is to be entered in each row. | 1 | 1 | 506 |
0 | 9,032,800 | 0 | 0 | 0 | 0 | 2 | false | 0 | 2012-01-27T09:01:00.000 | 1 | 2 | 0 | How to create columns in a csv file and insert row under them in python scrapy | 9,030,953 | 0.099668 | python,scrapy | CSV is a Comma Saparated Values format. That basically means that it is a text file with some strings separated by commas and line-downs.
Each line down creates a row and each comma creates a column in that row.
I guess the simplest way to create a CSV file would be to create a Pythonic dict where each key is a column ... | Please help me in creating columns and inserting rows under them in a csv file using python scrapy. I need to write scraped data into 3 columns. So first of all three columns are to be created and then data is to be entered in each row. | 1 | 1 | 506 |
0 | 9,042,475 | 0 | 0 | 0 | 0 | 1 | false | 1 | 2012-01-27T23:03:00.000 | 1 | 2 | 0 | Load sparse scipy matrix into existing numpy dense matrix | 9,041,236 | 0.099668 | python,numpy,scipy,numerical-computing | It does seem like there should be a better way to do this (and I haven't scoured the documentation), but you could always loop over the elements of the sparse array and assign to the dense array (probably zeroing out the dense array first). If this ends up too slow, that seems like an easy C extension to write.... | Say I have a huge numpy matrix A taking up tens of gigabytes. It takes a non-negligible amount of time to allocate this memory.
Let's say I also have a collection of scipy sparse matrices with the same dimensions as the numpy matrix. Sometimes I want to convert one of these sparse matrices into a dense matrix to perf... | 0 | 1 | 995 |
0 | 9,046,880 | 0 | 0 | 0 | 0 | 1 | true | 0 | 2012-01-28T14:16:00.000 | 1 | 1 | 0 | Fitted curve on chart using ReportLab | 9,045,888 | 1.2 | python,charts,reportlab,curve-fitting | I would recommend using MatPlotLib. This is exactly the sort of thing it's designed to handle and it will be much easier than trying to piece together something in ReportLab alone, especially since you'll have to do all the calculation of the line on your own and figure out the details of how to draw it in just the ri... | I'm preparing a set of reports using open source ReportLab. The reports contain a number of charts. Everything works well so far.
I've been asked to take a (working) bar chart that shows two series of data and overlay a fitted curve for each series.
I can see how I could overlay a segmented line on the bar graph by c... | 0 | 1 | 447 |
0 | 66,779,646 | 0 | 0 | 0 | 0 | 3 | false | 14 | 2012-01-29T20:51:00.000 | 0 | 5 | 0 | Python OpenCV - Find black areas in a binary image | 9,056,646 | 0 | python,opencv,colors,detection,threshold | I know this is an old question, but for completeness I wanted to point out that cv2.moments() will not always work for small contours. In this case, you can use cv2.minEnclosingCircle() which will always return the center coordinates (and radius), even if you have only a single point. Slightly more resource-hungry tho... | There is any method/function in the python wrapper of Opencv that finds black areas in a binary image? (like regionprops in Matlab)
Up to now I load my source image, transform it into a binary image via threshold and then invert it to highlight the black areas (that now are white).
I can't use third party libraries suc... | 0 | 1 | 26,428 |
0 | 15,779,624 | 0 | 0 | 0 | 0 | 3 | false | 14 | 2012-01-29T20:51:00.000 | 0 | 5 | 0 | Python OpenCV - Find black areas in a binary image | 9,056,646 | 0 | python,opencv,colors,detection,threshold | Transform it to binary image using threshold with the CV_THRESH_BINARY_INV flag, you get threshold + inversion in one step. | There is any method/function in the python wrapper of Opencv that finds black areas in a binary image? (like regionprops in Matlab)
Up to now I load my source image, transform it into a binary image via threshold and then invert it to highlight the black areas (that now are white).
I can't use third party libraries suc... | 0 | 1 | 26,428 |
0 | 9,058,880 | 0 | 0 | 0 | 0 | 3 | false | 14 | 2012-01-29T20:51:00.000 | 2 | 5 | 0 | Python OpenCV - Find black areas in a binary image | 9,056,646 | 0.07983 | python,opencv,colors,detection,threshold | After inverting binary image to turn black to white areas, apply cv.FindContours function. It will give you boundaries of the region you need.
Later you can use cv.BoundingRect to get minimum bounding rectangle around region. Once you got the rectangle vertices, you can find its center etc.
Or to find centroid of regio... | There is any method/function in the python wrapper of Opencv that finds black areas in a binary image? (like regionprops in Matlab)
Up to now I load my source image, transform it into a binary image via threshold and then invert it to highlight the black areas (that now are white).
I can't use third party libraries suc... | 0 | 1 | 26,428 |
0 | 9,071,479 | 0 | 1 | 0 | 0 | 2 | true | 3 | 2012-01-30T21:29:00.000 | 1 | 2 | 0 | How to handle large memory footprint in Python? | 9,071,031 | 1.2 | python | Well, if you need the whole dataset in RAM, there's not much to do but get more RAM. Sounds like you aren't sure if you really need to, but keeping all the data resident requires the smallest amount of thinking :)
If your data comes in a stream over a long period of time, and all you are doing is creating a histogram,... | I have a scientific application that reads a potentially huge data file from disk and transforms it into various Python data structures such as a map of maps, list of lists etc. NumPy is called in for numerical analysis. The problem is, the memory usage can grow rapidly. As swap space is called in, the system slows dow... | 0 | 1 | 294 |
0 | 9,071,108 | 0 | 1 | 0 | 0 | 2 | false | 3 | 2012-01-30T21:29:00.000 | 3 | 2 | 0 | How to handle large memory footprint in Python? | 9,071,031 | 0.291313 | python | Have you considered divide and conquer? Maybe your problem lends itself to that. One framework you could use for that is Map/Reduce.
Does your problem have multiple phases such that Phase I requires some data as input and generates an output which can be fed to phase II? In that case you can have 1 process do phase I a... | I have a scientific application that reads a potentially huge data file from disk and transforms it into various Python data structures such as a map of maps, list of lists etc. NumPy is called in for numerical analysis. The problem is, the memory usage can grow rapidly. As swap space is called in, the system slows dow... | 0 | 1 | 294 |
0 | 9,079,959 | 0 | 1 | 0 | 0 | 1 | false | 1 | 2012-01-31T09:31:00.000 | 1 | 2 | 0 | For cycle in Python's way in Matlab | 9,077,225 | 0.099668 | python,matlab,for-loop | In addition to the given answer, be aware that MATLAB's forloop is very slow.
Maybe programming in a functional style using arrayfun, cellfun() and structfun() might be a handier solution, and quite close to Python's map(). | May seem stupid, but after using Matlab for a while (a couple of years), I've tried Python, and despite some Matlab's features that are really handy, I really like Python.
Now, for work, I'm using Matlab again, and sometimes I miss a structure like Python's 'for' loop. Instead of using the standard 'for' that Matlab pr... | 0 | 1 | 273 |
0 | 9,091,268 | 0 | 1 | 0 | 0 | 1 | false | 2 | 2012-02-01T05:31:00.000 | 0 | 4 | 0 | Data structures with Python | 9,091,252 | 0 | python,data-structures | Given that all data structures exist in memory, and memory is effectively just a list (array)... there is no data structure that couldn't be expressed in terms of the basic Python data structures (with appropriate code to interact with them). | Python has a lot of convenient data structures (lists, tuples, dicts, sets, etc) which can be used to make other 'conventional' data structures (Eg, I can use a Python list to create a stack and a collections.dequeue to make a queue, dicts to make trees and graphs, etc).
There are even third-party data structures that ... | 0 | 1 | 2,410 |
0 | 9,136,461 | 0 | 1 | 0 | 0 | 1 | false | 0 | 2012-02-03T19:59:00.000 | 1 | 1 | 0 | IronPython and setuptools/ez_install | 9,134,717 | 0.197375 | ironpython,setuptools | Distribute is a fork of setuptools that supports Python 3, among other things. ez_install is used to install setuptools/easy_install, and then easy_install can be used to install packages (although pip is better).
Three years ago IronPython was missing a lot of the pieces needed, like zlib (2.7.0) and zipimport (upcomi... | Our company has developed Python libraries to open and display data from files using our proprietary file format. The library only depends on numpy which has been ported to IronPython.
The setup.py for our internal distribution imports from setuptools but apparently this is not yet supported in IronPython. Searching th... | 0 | 1 | 919 |
0 | 9,215,067 | 0 | 0 | 0 | 0 | 1 | false | 8 | 2012-02-09T15:33:00.000 | 0 | 3 | 0 | Graphviz - Drawing maximal cliques | 9,213,797 | 0 | python,graphviz | I don't think you can do this. Clusters are done via subgraphs, which are expected to be separate graphs, not overlapping with other subgraphs.
You could change the visualisation though; if you imagine that the members of a clique are members of some set S, then you could simply add a node S and add directed or dashed ... | I want to use graphviz in order to draw for a given graph all the maximal cliques that it has.
Therefore I would like that nodes in the same maximal clique will be visually encapsulated together (meaning that I would like that a big circle will surround them). I know that the cluster option exists - but in all the exam... | 0 | 1 | 3,488 |
0 | 11,412,849 | 0 | 0 | 0 | 0 | 1 | false | 5 | 2012-02-09T23:43:00.000 | 2 | 2 | 0 | Image Conversion between cv2, cv, mahotas, and SimpleCV | 9,220,720 | 0.197375 | python,opencv,python-2.7,simplecv,mahotas | I have never used mahotas. But I'm currently working on SimpleCV. I have just sent a pull request for making SimpleCV numpy array compatible with cv2.
So, basically,
Image.getNumpy() -> numpy.ndarray for cv2
Image.getBitmap() -> cv2.cv.iplimage
Image.getMatrix() -> cv2.cv.cvmat
To convert cv2 numpy array to SimpleCV... | I am having to do a lot of vision related work in Python lately, and I am facing a lot of difficulties switching between formats. When I read an image using Mahotas, I cannot seem to get it to cv2, though they are both using numpy.ndarray. SimpleCV can take OpenCV images easily, but getting SimpleCV image out for legac... | 0 | 1 | 5,140 |
0 | 9,245,481 | 0 | 0 | 0 | 0 | 1 | false | 1 | 2012-02-12T00:51:00.000 | 0 | 3 | 0 | Efficient two dimensional numpy array statistics | 9,245,466 | 0 | python,numpy,statistics | How many grids are there?
One option would be to create a 3D array that is 100x100xnumGrids and compute the median across the 3rd dimension. | I have many 100x100 grids, is there an efficient way using numpy to calculate the median for every grid point and return just one 100x100 grid with the median values? Presently, I'm using a for loop to run through each grid point, calculating the median and then combining them into one grid at the end. I'm sure there's... | 0 | 1 | 1,689 |
0 | 9,248,907 | 0 | 0 | 0 | 0 | 1 | false | 3 | 2012-02-12T12:37:00.000 | 1 | 1 | 0 | Python Sparse matrix inverse and laplacian calculation | 9,248,821 | 0.197375 | python,linear-algebra,sparse-matrix,matrix-inverse | In general the inverse of a sparse matrix is not sparse which is why you won't find sparse matrix inverters in linear algebra libraries. Since D is diagonal, D^(-1/2) is trivial and the Laplacian matrix calculation is thus trivial to write down. L has the same sparsity pattern as A but each value A_{ij} is multiplied b... | I have two sparse matrix A (affinity matrix) and D (Diagonal matrix) with dimension 100000*100000. I have to compute the Laplacian matrix L = D^(-1/2)*A*D^(-1/2). I am using scipy CSR format for sparse matrix.
I didnt find any method to find inverse of sparse matrix. How to find L and inverse of sparse matrix? Also sug... | 0 | 1 | 1,503 |
0 | 9,254,885 | 0 | 0 | 0 | 0 | 1 | false | 2 | 2012-02-13T01:53:00.000 | 1 | 2 | 0 | Generate volume curve from mp3 | 9,254,671 | 0.099668 | python,waveform | An MP3 file is an encoded version of a waveform. Before you can work with the waveform, you must first decode the MP3 data into a PCM waveform. Once you have PCM data, each sample represents the waveform's amplitude at the point in time. If we assume an MP3 decoder outputs signed, 16-bit values, your amplitudes will ra... | I'm trying to build something in python that can analyze an uploaded mp3 and generate the necessary data to build a waveform graphic. Everything I've found is much more complex than I need. Ultimately, I'm trying to build something like you'd see on SoundCloud.
I've been looking into numpy and fft's, but it all seem mo... | 0 | 1 | 1,275 |
0 | 9,280,538 | 0 | 0 | 0 | 0 | 1 | false | 55 | 2012-02-14T16:06:00.000 | 52 | 5 | 0 | Matplotlib python show() returns immediately | 9,280,171 | 1 | python,matplotlib | I think that using show(block=True) should fix your problem. | I have a simple python script which plots some graphs in the same figure. All graphs are created by the draw() and in the end I call the show() function to block.
The script used to work with Python 2.6.6, Matplotlib 0.99.3, and Ubuntu 11.04. Tried to run it under Python 2.7.2, Matplotlib 1.0.1, and Ubuntu 11.10 but t... | 0 | 1 | 84,640 |
0 | 9,280,574 | 0 | 0 | 0 | 0 | 1 | false | 5 | 2012-02-14T16:27:00.000 | 1 | 4 | 0 | How to store numerical lookup table in Python (with labels) | 9,280,488 | 0.049958 | python,numpy | If you want to access the results by name, then you could use a python nested dictionary instead of ndarray, and serialize it in a .JSON text file using json module. | I have a scientific model which I am running in Python which produces a lookup table as output. That is, it produces a many-dimensional 'table' where each dimension is a parameter in the model and the value in each cell is the output of the model.
My question is how best to store this lookup table in Python. I am runni... | 0 | 1 | 1,600 |
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