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1a9aa6f116020180ebd30617e5a5310750c6ffd8 | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/config.py | [
"MIT"
] | Python | initialize_lr_config | null | def initialize_lr_config(self, warm_steps, n_epochs):
"""This function sets the configuration to initialize learning rate
Args:
warm_steps (int): Number of steps The learning rate is increased
n_epochs (int): Number of epochs
"""
self.lr_config = dict(
... | This function sets the configuration to initialize learning rate
Args:
warm_steps (int): Number of steps The learning rate is increased
n_epochs (int): Number of epochs
| This function sets the configuration to initialize learning rate | [
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self.lr_config = dict(
warm_steps=warm_steps,
n_epochs=n_epochs,
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1a9aa6f116020180ebd30617e5a5310750c6ffd8 | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/config.py | [
"MIT"
] | Python | prepare_models | <not_specific> | def prepare_models(encoder_config, transformer_config, replica_batch_size, verbose=0):
"""This function is used to initiate the Encoder and the Transformer with appropriate
configs set by the user. After initiating the models this function returns the Encoder,Transformer
and the optimizer.
Args:
... | This function is used to initiate the Encoder and the Transformer with appropriate
configs set by the user. After initiating the models this function returns the Encoder,Transformer
and the optimizer.
Args:
encoder_config ([type]): Encoder configuration set by user in the config class.
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optimizer = tf.keras.optimizers.Adam(learning_rate=0.00051)
encoder = Efficient_Net_encoder.Encoder(**encoder_config)
initialization_batch = encoder(
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1a9aa6f116020180ebd30617e5a5310750c6ffd8 | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/config.py | [
"MIT"
] | Python | download_trained_weights | null | def download_trained_weights(model_url: str, model_path: str, verbose=1):
"""This function downloads the trained models and tokenizers to a default location.
After downloading the zipped file the function unzips the file automatically.
If the model exists on the default location this function will not work.... | This function downloads the trained models and tokenizers to a default location.
After downloading the zipped file the function unzips the file automatically.
If the model exists on the default location this function will not work.
Args:
model_url (str): trained model url for downloading.
mo... | This function downloads the trained models and tokenizers to a default location.
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if verbose > 0:
print("Downloading trained model to " + str(model_path))
model_path = pystow.ensure("DECIMER-V2", url=model_url)
print(model_path)
if verbose > 0:
print("... done downloading trained model!"... | [
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07321e62900cba09798c29a6d30e4273fcaab38a | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/decimer.py | [
"MIT"
] | Python | main | null | def main():
"""
This function take the path of the image as user input
and returns the predicted SMILES as output in CLI.
Agrs:
str: image_path
Returns:
str: predicted SMILES
"""
if len(sys.argv) != 2:
print("Usage: {} $image_path".format(sys.argv[0]))
else:
... |
This function take the path of the image as user input
and returns the predicted SMILES as output in CLI.
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str: image_path
Returns:
str: predicted SMILES
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if len(sys.argv) != 2:
print("Usage: {} $image_path".format(sys.argv[0]))
else:
SMILES = predict_SMILES(sys.argv[1])
print(SMILES) | [
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07321e62900cba09798c29a6d30e4273fcaab38a | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/decimer.py | [
"MIT"
] | Python | detokenize_output | str | def detokenize_output(predicted_array: int) -> str:
"""
This function takes the predited tokens from the DECIMER model
and returns the decoded SMILES string.
Args:
predicted_array (int): Predicted tokens from DECIMER
Returns:
(str): SMILES representation of the molecule
"""
... |
This function takes the predited tokens from the DECIMER model
and returns the decoded SMILES string.
Args:
predicted_array (int): Predicted tokens from DECIMER
Returns:
(str): SMILES representation of the molecule
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] | def detokenize_output(predicted_array: int) -> str:
outputs = [tokenizer.index_word[i] for i in predicted_array[0].numpy()]
prediction = (
"".join([str(elem) for elem in outputs])
.replace("<start>", "")
.replace("<end>", "")
)
return prediction | [
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07321e62900cba09798c29a6d30e4273fcaab38a | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/decimer.py | [
"MIT"
] | Python | predict_SMILES | str | def predict_SMILES(image_path: str) -> str:
"""
This function takes an image path (str) and returns the SMILES
representation of the depicted molecule (str).
Args:
image_path (str): Path of chemical structure depiction image
Returns:
(str): SMILES representation of the molecule in ... |
This function takes an image path (str) and returns the SMILES
representation of the depicted molecule (str).
Args:
image_path (str): Path of chemical structure depiction image
Returns:
(str): SMILES representation of the molecule in the input image
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chemical_structure = config.decode_image(image_path)
predicted_tokens = DECIMER_V2(chemical_structure)
predicted_SMILES = detokenize_output(predicted_tokens)
return predicted_SMILES | [
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a1f149b967c2af55e0d8d72eace6a8c181a2e223 | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/DECIMER_EfficinetNetV2_Transfomer_Trainer.py | [
"MIT"
] | Python | decode_image | <not_specific> | def decode_image(image_data):
"""Preprocess the input image for Efficient-Net and
returned the preprocessed image
Args:
image_data (int array): Decoded image in 2D array
Returns:
image (array): Preprocessed image in 2D array
"""
try:
img = tf.image.decode_png(image_data... | Preprocess the input image for Efficient-Net and
returned the preprocessed image
Args:
image_data (int array): Decoded image in 2D array
Returns:
image (array): Preprocessed image in 2D array
| Preprocess the input image for Efficient-Net and
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try:
img = tf.image.decode_png(image_data, channels=3)
except InvalidArgumentError as e:
print(e)
pass
img = tf.image.resize(img, (299, 299))
img = efn.preprocess_input(img)
return img | [
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a1f149b967c2af55e0d8d72eace6a8c181a2e223 | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/DECIMER_EfficinetNetV2_Transfomer_Trainer.py | [
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] | Python | read_tfrecord | <not_specific> | def read_tfrecord(example):
"""Read a tf record file and decodes the image and text data
back into original form.
Args:
example (tf.record): single entry from tf record file
Returns:
img (float array): 2D float array
caption: tokenized SMILES string
"""
feature = {
... | Read a tf record file and decodes the image and text data
back into original form.
Args:
example (tf.record): single entry from tf record file
Returns:
img (float array): 2D float array
caption: tokenized SMILES string
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feature = {
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example = tf.io.parse_single_example(example, feature)
img = decode_image(example["image_raw"])
caption = tf.io.decode_raw(example["caption"],... | [
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a1f149b967c2af55e0d8d72eace6a8c181a2e223 | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/DECIMER_EfficinetNetV2_Transfomer_Trainer.py | [
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] | Python | prepare_for_training | <not_specific> | def prepare_for_training(lr_config, encoder_config, transformer_config, verbose=0):
"""Preparte the model for training. initiate the learning rate, loss object, metrics
and optimizer
Args:
lr_config (int): values for learning rate configuration
encoder_config (_type_): encoder configuration... | Preparte the model for training. initiate the learning rate, loss object, metrics
and optimizer
Args:
lr_config (int): values for learning rate configuration
encoder_config (_type_): encoder configuration values
transformer_config (_type_): transformer configuration values
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with strategy.scope():
loss_object = tf.keras.losses.SparseCategoricalCrossentropy(
from_logits=True, reduction=tf.keras.losses.Reduction.NONE
)
def loss_fn(real, pred):
mask = tf.math... | [
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6fed6e222c90c198530df949727632923645d36a | Steinbeck-Lab/DECIMER-Image_Transformer | Benchmark/run_decimer_save_results.py | [
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] | Python | main | null | def main():
"""
This script runs Decimer on every image in a given directory (first argument) and saves the
results in a text file with a given ID (second argument).
"""
im_path = sys.argv[1]
save_ID = sys.argv[2]
# Don't start from beginning if a benchmark run aborted for some reason
w... |
This script runs Decimer on every image in a given directory (first argument) and saves the
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7e24b86d8b36f2271ae93a4331f8b34429f402d9 | Steinbeck-Lab/DECIMER-Image_Transformer | Benchmark/evaluate_benchmarks.py | [
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] | Python | compare_molecules_inchi_match | None | def compare_molecules_inchi_match(
input_file_path: str, reference_directory: str
) -> None:
"""
This function checks if the molecules in the DECIMER results to a set of reference
mol-files using Standard InChI.
Args:
input_file (str): Path of file that contains image names and SMILES a... |
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input_file (str): Path of file that contains image names and SMILES as created by run_decimer_save_results.py
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6265c6c673a75fadbf0413b13d2fee186bbc4f7f | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/Predictor_EfficientNet2.py | [
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"""
This function takes an image path (str) and returns the SELFIES
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Args:
image_path (str): Path of chemical structure depiction image
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(str): SELFIES representation of the molecule in the input i... |
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image_path (str): Path of chemical structure depiction image
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6265c6c673a75fadbf0413b13d2fee186bbc4f7f | Steinbeck-Lab/DECIMER-Image_Transformer | DECIMER/Predictor_EfficientNet2.py | [
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"""
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image_path (str): Path of chemical structure depiction image
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a93cbdaaf899703eb431a6a6998985d1464c6558 | HyperGH/Starr | starr/db.py | [
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a93cbdaaf899703eb431a6a6998985d1464c6558 | HyperGH/Starr | starr/db.py | [
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6d94c448f26e5fb8b8f9fc513a7b5b6e64921669 | InbarRose/kitir | kitir/_libs/byte_utils.py | [
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6d94c448f26e5fb8b8f9fc513a7b5b6e64921669 | InbarRose/kitir | kitir/_libs/byte_utils.py | [
"MIT"
] | Python | bytes2human | <not_specific> | def bytes2human(n, frmt='%(value).1f%(symbol)s', symbols='customary'):
"""
Convert n bytes into a human readable string based on format.
symbols can be either "customary", "customary_ext", "iec" or "iec_ext",
see: http://goo.gl/kTQMs
"""
# Bytes-to-human / human-to-bytes converter.
# Based o... |
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Author: Giampaolo Rodola' <g.rodola [AT] gmail [DOT] com>
License: MIT
copied from: http://code.activestate.com/recipes/578019-bytes-to-human-human-to-bytes-converter/?in=user-4178764
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6d94c448f26e5fb8b8f9fc513a7b5b6e64921669 | InbarRose/kitir | kitir/_libs/byte_utils.py | [
"MIT"
] | Python | human2bytes | <not_specific> | def human2bytes(s):
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Attempts to guess the string format based on default symbols
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
"MIT"
] | Python | _log_transaction | <not_specific> | def _log_transaction(cls, response, **kwargs):
"""
logs the request transaction, both request and response with optional kwargs
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:param kwargs:
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"""
only_not_ok = kwargs.pop('only_not_ok', False)
transact_name = kwargs.pop('transact... |
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transact_parts = [transact_name, response.request.method]
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
"MIT"
] | Python | _log_request_full | null | def _log_request_full(cls, response, request_file_path):
"""log the full request side of a transaction"""
assert isinstance(response, requests.Response)
req = response.request
assert isinstance(req, requests.PreparedRequest)
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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"""log the full response side of a transaction"""
assert isinstance(response, requests.Response)
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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] | Python | _log_request | null | def _log_request(cls, response, request_file_path):
"""log the request side of a transaction"""
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content = response.request.url
data_file = utils.write_file(request_file_path, content)
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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] | Python | _get_body_from_req | <not_specific> | def _get_body_from_req(cls, req):
"""attempts to extract body from req as json, if fails, gets raw body (as string)"""
assert isinstance(req, requests.PreparedRequest)
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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a4f7b19d36f0dff5b59f552fbb1a50e67c89c4cf | InbarRose/kitir | kitir/kits/restful_api.py | [
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665e23901c38f0189a15ce2fba1e6ff5459defad | InbarRose/kitir | kitir/utils.py | [
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665e23901c38f0189a15ce2fba1e6ff5459defad | InbarRose/kitir | kitir/utils.py | [
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665e23901c38f0189a15ce2fba1e6ff5459defad | InbarRose/kitir | kitir/utils.py | [
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return functools.reduce(dict.get, key, col)
except KeyError:
if raise_if_missing:
raise
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665e23901c38f0189a15ce2fba1e6ff5459defad | InbarRose/kitir | kitir/utils.py | [
"MIT"
] | Python | is_same_class_or_subclass | <not_specific> | def is_same_class_or_subclass(target, main_class):
"""
checks if target is the same class or a subclass of main_class
:param target:
:param main_class:
:return:
"""
return isinstance(target, main_class) or issubclass(target.__class__, main_class) |
checks if target is the same class or a subclass of main_class
:param target:
:param main_class:
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return isinstance(target, main_class) or issubclass(target.__class__, main_class) | [
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0a16368509b08037c47429e027e58570fb2b2faf | InbarRose/kitir | kitir/_libs/package_utils.py | [
"MIT"
] | Python | verify_pip | <not_specific> | def verify_pip(get_if_needed=True, raise_on_failure=True, **kwargs):
"""
verify that pip exists on machine
:param get_if_needed: get pip if missing
:param raise_on_failure: raise exception if no pip at the end
:return: returns the pip base if all is okay, or false otherwise (or raises exception)
... |
verify that pip exists on machine
:param get_if_needed: get pip if missing
:param raise_on_failure: raise exception if no pip at the end
:return: returns the pip base if all is okay, or false otherwise (or raises exception)
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] | def verify_pip(get_if_needed=True, raise_on_failure=True, **kwargs):
log.trace('verifying pip exists: get_if_needed={}'.format(get_if_needed))
kwargs.setdefault('to_console', False)
kwargs.setdefault('trace_file', ir_artifact_dir + '/packages/pip/verify_pip.trace.out')
def _check_for_pip():
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0a16368509b08037c47429e027e58570fb2b2faf | InbarRose/kitir | kitir/_libs/package_utils.py | [
"MIT"
] | Python | pip_cmd | <not_specific> | def pip_cmd(*packages, **kwargs):
"""
executes pip on current machine. Using the supplied mode and packages
:param packages: a list of packages,
:param kwargs: kwargs for iexec and flags
:return:
"""
# delete pip cache dir
shutil.rmtree('/root/.cache/pip', ignore_errors=True)
# tes... |
executes pip on current machine. Using the supplied mode and packages
:param packages: a list of packages,
:param kwargs: kwargs for iexec and flags
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shutil.rmtree('/root/.cache/pip', ignore_errors=True)
if running_on_windows:
pip_base = 'python -m pip'
else:
pip_base = verify_pip(**kwargs)
mode = kwargs.pop('mode', 'install')
assert mode in ['install', 'uninstall']
kwargs.setdefault('trace_... | [
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... |
d3398089555244f019fe44321a09f12792ac8080 | InbarRose/kitir | kitir/_libs/csv_utils.py | [
"MIT"
] | Python | read_csv_from_string | <not_specific> | def read_csv_from_string(text, return_headers=False):
"""
reads a csv (comma separated values) string using DictReader and returns a rowdicts list
:param text: string to parse CSV from
:param return_headers: return value becomes (rows, headers)
:return: rows read from csv
"""
log.trace('read... |
reads a csv (comma separated values) string using DictReader and returns a rowdicts list
:param text: string to parse CSV from
:param return_headers: return value becomes (rows, headers)
:return: rows read from csv
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] | def read_csv_from_string(text, return_headers=False):
log.trace('reading csv string: content[:20]={} len={}'.format(repr(text[:20]), len(text)))
reader = csv.DictReader(text.splitlines())
rows = [row for row in reader]
if return_headers:
return rows, reader.fieldnames
return rows | [
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d3398089555244f019fe44321a09f12792ac8080 | InbarRose/kitir | kitir/_libs/csv_utils.py | [
"MIT"
] | Python | read_tsv_from_string | <not_specific> | def read_tsv_from_string(text, return_headers=False):
"""
reads a tsv (tab separated values) string using DictReader and returns a rowdicts list
:param text: string to parse TSV from
:param return_headers: return value becomes (rows, headers)
:return: rows read from csv
"""
log.trace('readin... |
reads a tsv (tab separated values) string using DictReader and returns a rowdicts list
:param text: string to parse TSV from
:param return_headers: return value becomes (rows, headers)
:return: rows read from csv
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log.trace('reading tsv string: content[:20]={} len={}'.format(repr(text[:20]), len(text)))
reader = csv.DictReader(text.splitlines(), dialect='excel-tab')
rows = [row for row in reader]
if return_headers:
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d3398089555244f019fe44321a09f12792ac8080 | InbarRose/kitir | kitir/_libs/csv_utils.py | [
"MIT"
] | Python | read_ssv_from_string | <not_specific> | def read_ssv_from_string(text, return_headers=False):
"""
reads a ssv (space separated values) string using DictReader and returns a rowdicts list
:param text: string to parse SSV from
:param return_headers: return value becomes (rows, headers)
:return: rows read from csv
"""
log.trace('read... |
reads a ssv (space separated values) string using DictReader and returns a rowdicts list
:param text: string to parse SSV from
:param return_headers: return value becomes (rows, headers)
:return: rows read from csv
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reader = csv.DictReader(text.splitlines(), dialect='excel-space')
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cb53f210f08995c121062a27282bb1063402787e | InbarRose/kitir | kitir/_libs/file_utils.py | [
"MIT"
] | Python | write_to_tmp_file | <not_specific> | def write_to_tmp_file(content, **kwargs):
"""
writes the content to a temporary file
:param content: the content to write (string)
:return: returns the file_path
"""
kwargs.setdefault('mode', 'w+')
with tempfile.NamedTemporaryFile(delete=False, **kwargs) as f:
f.write(content)
re... |
writes the content to a temporary file
:param content: the content to write (string)
:return: returns the file_path
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kwargs.setdefault('mode', 'w+')
with tempfile.NamedTemporaryFile(delete=False, **kwargs) as f:
f.write(content)
return f.name | [
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cb53f210f08995c121062a27282bb1063402787e | InbarRose/kitir | kitir/_libs/file_utils.py | [
"MIT"
] | Python | write_file | <not_specific> | def write_file(file_name, contents=None, filemode='w', rotate=False, **kwargs):
"""
create, or append to a file, optionally with content, return file_name
:param file_name:
:param contents:
:param filemode:
:param rotate:
:return: the filename that was written
"""
check_makedir(os.pa... |
create, or append to a file, optionally with content, return file_name
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:param contents:
:param filemode:
:param rotate:
:return: the filename that was written
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check_makedir(os.path.dirname(file_name))
if rotate:
file_name = file_rotation(file_name, rotate_rx=kwargs.get('rotate_rx', '_rx_'))
with open(file_name, filemode) as f:
if contents:
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cb53f210f08995c121062a27282bb1063402787e | InbarRose/kitir | kitir/_libs/file_utils.py | [
"MIT"
] | Python | write_csv | <not_specific> | def write_csv(file_name, contents, headers=None, **kwargs):
"""
writes a csv file using DictWriter and returns the filename
if contents is a rowdicts uses the keys of the first dict in contents as the headers
if contents is a dictionary, you must supply the headers, for 2 columns [key, value]
:param... |
writes a csv file using DictWriter and returns the filename
if contents is a rowdicts uses the keys of the first dict in contents as the headers
if contents is a dictionary, you must supply the headers, for 2 columns [key, value]
:param file_name: path of the file
:param contents: rowdicts list (or... | writes a csv file using DictWriter and returns the filename
if contents is a rowdicts uses the keys of the first dict in contents as the headers
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filemode = kwargs.pop('filemode', 'w')
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assert headers and len(headers) == 2
contents = [{headers[0]: key, headers[1]: value} for key, value in contents.items()]
headers = headers or contents[0].keys()
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cb53f210f08995c121062a27282bb1063402787e | InbarRose/kitir | kitir/_libs/file_utils.py | [
"MIT"
] | Python | read_csv | <not_specific> | def read_csv(file_name, return_headers=False, **kwargs):
"""
reads a csv file using DictReader and returns a rowdicts list
:param file_name: path of the file
:param return_headers: return value becomes (rows, headers)
:return: rows read from csv
"""
filemode = kwargs.pop('filemode', 'r')
... |
reads a csv file using DictReader and returns a rowdicts list
:param file_name: path of the file
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filemode = kwargs.pop('filemode', 'r')
log.trace('reading csv file: path={}'.format(file_name))
with open(file_name, filemode) as f:
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cb53f210f08995c121062a27282bb1063402787e | InbarRose/kitir | kitir/_libs/file_utils.py | [
"MIT"
] | Python | iread_csv | null | def iread_csv(file_name, return_headers=False, **kwargs):
"""
iter-reads a csv file using DictReader and returns a rowdicts generator
:param file_name: path of the file
:param return_headers: first yield is the headers
:return: rows read from csv as generator
"""
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iter-reads a csv file using DictReader and returns a rowdicts generator
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cb53f210f08995c121062a27282bb1063402787e | InbarRose/kitir | kitir/_libs/file_utils.py | [
"MIT"
] | Python | file_diff | <not_specific> | def file_diff(file_a, file_b, output=None, **kwargs):
"""
performance a diff between two files
:param file_a: first file
:param file_b: second file
:param output: output file for diff
:param kwargs: any kwargs
:return:
"""
filemode = kwargs.pop('filemode', 'Ur')
if kwargs.pop('sh... |
performance a diff between two files
:param file_a: first file
:param file_b: second file
:param output: output file for diff
:param kwargs: any kwargs
:return:
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filemode = kwargs.pop('filemode', 'Ur')
if kwargs.pop('show_log', True):
log.trace('performing file diff between two files: a={} b={}'.format(file_a, file_b))
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cb53f210f08995c121062a27282bb1063402787e | InbarRose/kitir | kitir/_libs/file_utils.py | [
"MIT"
] | Python | bulk_rename | <not_specific> | def bulk_rename(src_dir, before, after, dst_dir=None, raise_on_error=True):
"""
Perform bulk-rename operation on files in a directory. optionally move them to another directory.
:param src_dir:
:param before:
:param after:
:param dst_dir:
:param raise_on_error:
:return:
"""
asser... |
Perform bulk-rename operation on files in a directory. optionally move them to another directory.
:param src_dir:
:param before:
:param after:
:param dst_dir:
:param raise_on_error:
:return:
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log.debug('bulk-renaming: src={} dst={} before={} after={}'.format(src_dir, dst_dir, before, after))
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cb53f210f08995c121062a27282bb1063402787e | InbarRose/kitir | kitir/_libs/file_utils.py | [
"MIT"
] | Python | format_file | <not_specific> | def format_file(filepath, raise_on_fail=True, **kwargs):
"""
format a files contents with given kwargs using pythons string.format()
:param filepath: filepath to format
:param raise_on_fail: raise exceptions
:param kwargs:
:return: returns True if success else False
"""
filemode_read = k... |
format a files contents with given kwargs using pythons string.format()
:param filepath: filepath to format
:param raise_on_fail: raise exceptions
:param kwargs:
:return: returns True if success else False
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filemode_read = kwargs.pop('filemode_read', 'r')
filemode_write = kwargs.pop('filemode_write', 'w')
try:
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content_before = fr.readlines()
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cb53f210f08995c121062a27282bb1063402787e | InbarRose/kitir | kitir/_libs/file_utils.py | [
"MIT"
] | Python | replace_content_in_file | <not_specific> | def replace_content_in_file(filepath, replacements, raise_on_fail=True, **kwargs):
"""
replaces content in a file,
:param filepath: the path to the file for replacements
:param replacements: replacements should be a dictionary of {target: replacement}
:param raise_on_fail:
:param kwargs:
:re... |
replaces content in a file,
:param filepath: the path to the file for replacements
:param replacements: replacements should be a dictionary of {target: replacement}
:param raise_on_fail:
:param kwargs:
:return:
| replaces content in a file. | [
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filemode_read = kwargs.pop('filemode_read', 'r')
filemode_write = kwargs.pop('filemode_write', 'w')
log.debug('Modifying file in-place: filepath={}'.format(filepath))
backup_file = kwargs.pop('backup_file', None)
retu... | [
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bd3b341c6bc3c84125c3ab07b8794677f3e4808f | autotraderuk/fastapi-mlflow | fastapi_mlflow/applications.py | [
"Apache-2.0"
] | Python | build_app | FastAPI | def build_app(pyfunc_model: PyFuncModel) -> FastAPI:
"""Build and return a FastAPI app for the mlflow model."""
app = FastAPI()
predictor = build_predictor(pyfunc_model)
response_model = signature(predictor).return_annotation
app.add_api_route(
"/predictions",
predictor,
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] | def build_app(pyfunc_model: PyFuncModel) -> FastAPI:
app = FastAPI()
predictor = build_predictor(pyfunc_model)
response_model = signature(predictor).return_annotation
app.add_api_route(
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predictor,
response_model=response_model,
methods=["POST"],
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431de92a08ae414e9324d7577cb4a2a746439c64 | autotraderuk/fastapi-mlflow | fastapi_mlflow/predictors.py | [
"Apache-2.0"
] | Python | build_predictor | Callable[[List[BaseModel]], Any] | def build_predictor(model: PyFuncModel) -> Callable[[List[BaseModel]], Any]:
"""Build and return a function that wraps the mlflow model.
Currently supports only the `pyfunc`_ flavour of mlflow.
:param model: PyFuncModel
:return: Function suitable for mounting as a FastAPI endpoint or route.
Examp... | Build and return a function that wraps the mlflow model.
Currently supports only the `pyfunc`_ flavour of mlflow.
:param model: PyFuncModel
:return: Function suitable for mounting as a FastAPI endpoint or route.
Example::
model = load_model("/Users/me/path/to/local/model")
predictor ... | Build and return a function that wraps the mlflow model.
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return_type: Any = _mlflow_types.build_output_model(
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3b8976a93318f45e933c0d30b646460662e27f1b | TharinduDR/STS-Transformers | examples/arabic_sts/arabic_preprocess.py | [
"Apache-2.0"
] | Python | preprocess | <not_specific> | def preprocess(text, do_farasa_tokenization=True, farasa=None, use_farasapy=False):
"""
Preprocess takes an input text line an applies the same preprocessing used in araBERT
pretraining
Note: a farasapy segmenter is ~6x faster than the py4j.java_gateway, consider setting use_farasapy=True
Farsa Segmentation... |
Preprocess takes an input text line an applies the same preprocessing used in araBERT
pretraining
Note: a farasapy segmenter is ~6x faster than the py4j.java_gateway, consider setting use_farasapy=True
Farsa Segmentation will soon be fully migrated to farasapy, and support for the py4j.java_gateway.JavaObject ... | Preprocess takes an input text line an applies the same preprocessing used in araBERT
pretraining
a farasapy segmenter is ~6x faster than the py4j.java_gateway, consider setting use_farasapy=True
Farsa Segmentation will soon be fully migrated to farasapy, and support for the py4j.java_gateway.JavaObject will be remove... | [
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4a9e0e607f54d99d430b0fec78a1dd55835c0210 | noosenergy/terraform-client | src/noos_tf/cli.py | [
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] | Python | update | null | def update(ctx, variable="", value="", workspace="", organisation=None, token=None):
"""Update variable in Terraform cloud."""
organisation = organisation or os.getenv("TERRAFORM_USER")
token = token or os.getenv("TERRAFORM_TOKEN")
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4a9e0e607f54d99d430b0fec78a1dd55835c0210 | noosenergy/terraform-client | src/noos_tf/cli.py | [
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] | Python | run | null | def run(ctx, message="", workspace="", organisation=None, token=None):
"""Run a plan in Terraform cloud."""
organisation = organisation or os.getenv("TERRAFORM_USER")
token = token or os.getenv("TERRAFORM_TOKEN")
assert organisation is not None, "Missing Terraform Cloud organisation."
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8327657998506dc264c587a0f7559b3d0b86f5cc | noosenergy/terraform-client | src/noos_tf/client.py | [
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] | Python | update_variable | None | def update_variable(self, variable_id: str, value: str) -> None:
"""Update the value of a variable stored onto a given workspace for a organization."""
data = {
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"type": "vars",
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8327657998506dc264c587a0f7559b3d0b86f5cc | noosenergy/terraform-client | src/noos_tf/client.py | [
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] | Python | run_plan | str | def run_plan(self, workspace_id: str, message: str) -> str:
"""Run a plan onto a given workspace for a organization."""
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79733b32e2762ac9233295cf4fe7f7ce00d21e49 | noosenergy/terraform-client | src/noos_tf/api.py | [
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organization: str,
workspace: str,
token: str,
variable: str,
value: str,
) -> None:
"""Update variable in Terraform cloud."""
# Authenticate client
tf_client = client.TerraformClient()
tf_client.set_auth_header(token)
# Retrieve variables IDs
... | Update variable in Terraform cloud. | Update variable in Terraform cloud. | [
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tf_client = client.TerraformClient()
tf_client.set_auth_header(token)
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79733b32e2762ac9233295cf4fe7f7ce00d21e49 | noosenergy/terraform-client | src/noos_tf/api.py | [
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tf_client = client.TerraformClient()
tf_client.set_auth_header(token)
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tf_client = client.TerraformClient()
tf_client.set_auth_header(token)
workspace_id = tf_client.get_workspace_id(organization, workspace)
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _have_adequate_put_responses | null | def _have_adequate_put_responses(self, statuses, num_nodes, min_responses):
"""
Test for sufficient PUT responses from backend nodes to proceed with
PUT handling.
:param statuses: a list of response statuses.
:param num_nodes: number of backend nodes to which PUT requests may be... |
Test for sufficient PUT responses from backend nodes to proceed with
PUT handling.
:param statuses: a list of response statuses.
:param num_nodes: number of backend nodes to which PUT requests may be
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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] | Python | _get_put_responses | <not_specific> | def _get_put_responses(self, req, putters, num_nodes, final_phase=True,
min_responses=None):
"""
Collect object responses to a PUT request and determine if a
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lists of accumulated status codes, reasons... |
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:param req: the request
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _check_failure_put_connections | null | def _check_failure_put_connections(self, putters, req, min_conns):
"""
Identify any failed connections and check minimum connection count.
:param putters: a list of Putter instances
:param req: request
:param min_conns: minimum number of putter connections required
"""
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Identify any failed connections and check minimum connection count.
:param putters: a list of Putter instances
:param req: request
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statuses = [
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
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"""
Returns a putter object for handling streaming of object to object
servers.
Subclasses must implement this method.
:param node: a storage node
:param part: ring partition number
:param req: a swob Request
... |
Returns a putter object for handling streaming of object to object
servers.
Subclasses must implement this method.
:param node: a storage node
:param part: ring partition number
:param req: a swob Request
:param headers: request headers
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _connect_put_node | <not_specific> | def _connect_put_node(self, nodes, part, req, headers,
logger_thread_locals):
"""
Make connection to storage nodes
Connects to the first working node that it finds in nodes iter and
sends over the request headers. Returns a Putter to handle the rest of
... |
Make connection to storage nodes
Connects to the first working node that it finds in nodes iter and
sends over the request headers. Returns a Putter to handle the rest of
the streaming, or None if no working nodes were found.
:param nodes: an iterator of the target storage nod... | Make connection to storage nodes
Connects to the first working node that it finds in nodes iter and
sends over the request headers. Returns a Putter to handle the rest of
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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] | Python | _get_put_connections | <not_specific> | def _get_put_connections(self, req, nodes, partition, outgoing_headers,
policy):
"""
Establish connections to storage nodes for PUT request
"""
obj_ring = policy.object_ring
node_iter = GreenthreadSafeIterator(
self.iter_nodes_local_first(... |
Establish connections to storage nodes for PUT request
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obj_ring = policy.object_ring
node_iter = GreenthreadSafeIterator(
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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outgoing_headers):
"""
This method is responsible for establishing connection
with storage nodes and sending the data to each one of those
nodes. The process of transferring data is specific to each
... |
This method is responsible for establishing connection
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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"""Delete object considering write-affinity.
When deleting object in write affinity deployment, also take configured
handoff nodes number into consideration, instead of just sending
requests to primary nodes. Otherwise (write-... | Delete object considering write-affinity.
When deleting object in write affinity deployment, also take configured
handoff nodes number into consideration, instead of just sending
requests to primary nodes. Otherwise (write-affinity is disabled),
go with the same way as before.
... | Delete object considering write-affinity.
When deleting object in write affinity deployment, also take configured
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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"""
send object POST request to storage nodes.
:param req: the POST Request
:param obj_ring: the object ring
:param partition: ring partition number
:param headers: system headers to storage nodes
:return... |
send object POST request to storage nodes.
:param req: the POST Request
:param obj_ring: the object ring
:param partition: ring partition number
:param headers: system headers to storage nodes
:return: Response object
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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"""
Transfer data for a replicated object.
This method was added in the PUT method extraction change
"""
bytes_transferred = 0
def send_chunk(chunk):
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Transfer data for a replicated object.
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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"""
Store a replicated object.
This method is responsible for establishing connection
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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"""
Start pulling data from the backends so that we can learn things like
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Also, this is the first point at which we can learn the MI... |
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the real Content-Type that might only be in the multipart/byteranges
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the real Content-Type that might only be in the multipart/byteranges
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
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"""
Get 100-continue response indicating the end of 1st phase of a 2-phase
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Might or might not actually wait for anything. If we said Expect:
100-continue but go... |
Get 100-continue response indicating the end of 1st phase of a 2-phase
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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"""
Call when there is no more data to send.
"""
if self.state == DATA_SENT:
raise ValueError("called end_of_object_data twice")
self.queue.put('')
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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Method for a file PUT coroutine. Takes chunks from a queue and sends
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If something goes wrong, the "failed" attribute will be set to true
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"""
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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Connect to a backend node and send the headers.
:returns: Putter instance
:raises ConnectionTimeout: if initial connection timed out
:raises Respon... |
Connect to a backend node and send the headers.
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:raises ConnectionTimeout: if initial connection timed out
:raises ResponseTimeout: if header retrieval timed out
:raises InsufficientStorage: on 507 response from node
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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"""
Call when there is no more data to send.
Overrides superclass implementation to send any footer metadata
after object data.
:param footer_metadata: dictionary of metadata items
to be sent as... |
Call when there is no more data to send.
Overrides superclass implementation to send any footer metadata
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:param footer_metadata: dictionary of metadata items
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| Call when there is no more data to send.
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | send_commit_confirmation | null | def send_commit_confirmation(self):
"""
Call when there are > quorum 2XX responses received. Send commit
confirmations to all object nodes to finalize the PUT.
"""
if not self.multiphase:
raise ValueError(
"called send_commit_confirmation but multipha... |
Call when there are > quorum 2XX responses received. Send commit
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
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logger=None, need_multiphase=True, **kwargs):
"""
Connect to a backend node and send the headers.
Override superclass method to notify object of need for support for
multipart body with footers and op... |
Connect to a backend node and send the headers.
Override superclass method to notify object of need for support for
multipart body with footers and optionally multiphase commit, and
verify object server's capabilities.
:param need_multiphase: if True then multiphase support is... | Connect to a backend node and send the headers.
Override superclass method to notify object of need for support for
multipart body with footers and optionally multiphase commit, and
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | chunk_transformer | null | def chunk_transformer(policy):
"""
A generator to transform a source chunk to erasure coded chunks for each
`send` call. The number of erasure coded chunks is as
policy.ec_n_unique_fragments.
"""
segment_size = policy.ec_segment_size
buf = collections.deque() # deque()定义了双端队列，可以从头/尾两端添加或删除... |
A generator to transform a source chunk to erasure coded chunks for each
`send` call. The number of erasure coded chunks is as
policy.ec_n_unique_fragments.
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | add_response | null | def add_response(self, get, parts_iter):
"""
Add a response to the collection.
:param get: An instance of
:class:`~swift.proxy.controllers.base.ResumingGetter`
:param parts_iter: An iterator over response body parts
:raises ValueError: if the response etag or... |
Add a response to the collection.
:param get: An instance of
:class:`~swift.proxy.controllers.base.ResumingGetter`
:param parts_iter: An iterator over response body parts
:raises ValueError: if the response etag or status code values do not
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headers = get.last_headers
t_data_file = headers.get('X-Backend-Data-Timestamp')
t_obj = headers.get('X-Backend-Timestamp', headers.get('X-Timestamp'))
self._get_bucket(t_data_file or t_obj).add_response(get, parts_iter)
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | best_bucket | <not_specific> | def best_bucket(self):
"""
Return the best bucket in the collection.
The "best" bucket is the newest timestamp with sufficient getters, or
the closest to having sufficient getters, unless it is bettered by a
bucket with potential alternate nodes.
:return: An instance of... |
Return the best bucket in the collection.
The "best" bucket is the newest timestamp with sufficient getters, or
the closest to having sufficient getters, unless it is bettered by a
bucket with potential alternate nodes.
:return: An instance of :class:`~ECGetResponseBucket` or ... | Return the best bucket in the collection.
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | provide_alternate_node | <not_specific> | def provide_alternate_node(self):
"""
Callback function that is installed in a NodeIter. Called on every call
to NodeIter.next(), which means we can track the number of nodes to
which GET requests have been made and selectively inject an alternate
node, if we have one.
:... |
Callback function that is installed in a NodeIter. Called on every call
to NodeIter.next(), which means we can track the number of nodes to
which GET requests have been made and selectively inject an alternate
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:return: A dict describing a node to which the... | Callback function that is installed in a NodeIter. Called on every call
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _fragment_GET_request | <not_specific> | def _fragment_GET_request(self, req, node_iter, partition, policy,
header_provider=None):
"""
Makes a GET request for a fragment.
"""
backend_headers = self.generate_request_headers(
req, additional=req.headers)
getter = ResumingGetter(s... |
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backend_headers = self.generate_request_headers(
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getter = ResumingGetter(self.app, req, 'Object', node_iter,
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _convert_range | <not_specific> | def _convert_range(self, req, policy):
"""
Take the requested range(s) from the client and convert it to range(s)
to be sent to the object servers.
This includes widening requested ranges to full segments, then
converting those ranges to fragments so that we retrieve the minimum... |
Take the requested range(s) from the client and convert it to range(s)
to be sent to the object servers.
This includes widening requested ranges to full segments, then
converting those ranges to fragments so that we retrieve the minimum
number of fragments from the object serve... | Take the requested range(s) from the client and convert it to range(s)
to be sent to the object servers.
This includes widening requested ranges to full segments, then
converting those ranges to fragments so that we retrieve the minimum
number of fragments from the object server.
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new_ranges = []
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _determine_chunk_destinations | <not_specific> | def _determine_chunk_destinations(self, putters, policy):
"""
Given a list of putters, return a dict where the key is the putter
and the value is the frag index to use.
This is done so that we line up handoffs using the same frag index
(in the primary part list) as the primary t... |
Given a list of putters, return a dict where the key is the putter
and the value is the frag index to use.
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in for. This lets erasure-code f... | Given a list of putters, return a dict where the key is the putter
and the value is the frag index to use.
This is done so that we line up handoffs using the same frag index
(in the primary part list) as the primary that the handoff is standing
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handoff_conns = []
putter_to_frag_index = {}
fo... | [
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _transfer_data | <not_specific> | def _transfer_data(self, req, policy, data_source, putters, nodes,
min_conns, etag_hasher):
"""
Transfer data for an erasure coded object.
This method was added in the PUT method extraction change
"""
bytes_transferred = 0
# 生成一个迭代器 chunk_transform... |
Transfer data for an erasure coded object.
This method was added in the PUT method extraction change
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This method was added in the PUT method extraction change | [
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bytes_transferred = 0
chunk_transform = chunk_transformer(policy)
chunk_transform.send(None)
frag_hashers = collections.defaultdict(md5)
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _have_adequate_responses | <not_specific> | def _have_adequate_responses(
self, statuses, min_responses, conditional_func):
"""
Given a list of statuses from several requests, determine if a
satisfactory number of nodes have responded with 1xx or 2xx statuses to
deem the transaction for a successful response to the cli... |
Given a list of statuses from several requests, determine if a
satisfactory number of nodes have responded with 1xx or 2xx statuses to
deem the transaction for a successful response to the client.
:param statuses: list of statuses returned so far
:param min_responses: minimal p... | Given a list of statuses from several requests, determine if a
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if sum(1 for s in statuses if (conditional_func(s))) >= min_responses:
return True
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _have_adequate_successes | <not_specific> | def _have_adequate_successes(self, statuses, min_responses):
"""
Partial method of _have_adequate_responses for 2xx
"""
return self._have_adequate_responses(
statuses, min_responses, is_success) |
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _have_adequate_informational | <not_specific> | def _have_adequate_informational(self, statuses, min_responses):
"""
Partial method of _have_adequate_responses for 1xx
"""
return self._have_adequate_responses(
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Partial method of _have_adequate_responses for 1xx
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510d1ca6770f8d9fb11c5787f2ce60080b0a8740 | cighao/swift-with-comment | swift/proxy/controllers/obj.py | [
"Apache-2.0"
] | Python | _store_object | <not_specific> | def _store_object(self, req, data_source, nodes, partition,
outgoing_headers):
"""
Store an erasure coded object.
"""
policy_index = int(req.headers.get('X-Backend-Storage-Policy-Index'))
policy = POLICIES.get_by_index(policy_index)
expected_frag_si... |
Store an erasure coded object.
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] | def _store_object(self, req, data_source, nodes, partition,
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policy_index = int(req.headers.get('X-Backend-Storage-Policy-Index'))
policy = POLICIES.get_by_index(policy_index)
expected_frag_size = None
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3b9ee55e85a85f9b22651a40501ab84f4e95c1a6 | callumparr/TALON-paper-2020 | plotting_scripts/plot_gene_or_transcript_length_by_DE.py | [
"MIT"
] | Python | violin_plot | null | def violin_plot(data, colname, mode, ymax, fname):
""" Plot a violin plot with the length of each read by novelty category"""
sns.set_context("paper", font_scale=1.3)
#ax = sns.stripplot(x='transcript_novelty', y='read_length', data=data, color="grey", jitter = True)
ax = sns.boxplot(x='DE_type', y=co... | Plot a violin plot with the length of each read by novelty category | Plot a violin plot with the length of each read by novelty category | [
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ax = sns.boxplot(x='DE_type', y=colname, data=data, palette = "Blues")
nobs = list(data.groupby("DE_type").size())
nobs = [str(x) for x in nobs]
nobs = ["n=" + i for i in nobs]
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fa27bd78a3a1643ee8493c82bb94d5e94f1a7685 | callumparr/TALON-paper-2020 | ebv/talon_GTF_2_transcript_bed.py | [
"MIT"
] | Python | create_BED_entry | <not_specific> | def create_BED_entry(gtf_transcript):
""" Given a GTF transcript (in list form), create a BED entry. This entails:
1. Convert coordinates from 1-based to 0-based
2. Extract unique transcript identifier to use in name field
3. Extract other attributes (ie chromosome, strand) """
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2. Extract unique transcript identifier to use in name field
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strand = gtf_transcript[6]
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} |
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