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MartinThoma/hwrt | hwrt/create_ffiles.py | training_set_multiplication | def training_set_multiplication(training_set, mult_queue):
"""
Multiply the training set by all methods listed in mult_queue.
Parameters
----------
training_set :
set of all recordings that will be used for training
mult_queue :
list of all algorithms that will take one recordin... | python | def training_set_multiplication(training_set, mult_queue):
"""
Multiply the training set by all methods listed in mult_queue.
Parameters
----------
training_set :
set of all recordings that will be used for training
mult_queue :
list of all algorithms that will take one recordin... | [
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MartinThoma/hwrt | hwrt/create_ffiles.py | _calculate_feature_stats | def _calculate_feature_stats(feature_list, prepared, serialization_file): # pylint: disable=R0914
"""Calculate min, max and mean for each feature. Store it in object."""
# Create feature only list
feats = [x for x, _ in prepared] # Label is not necessary
# Calculate all means / mins / maxs
means ... | python | def _calculate_feature_stats(feature_list, prepared, serialization_file): # pylint: disable=R0914
"""Calculate min, max and mean for each feature. Store it in object."""
# Create feature only list
feats = [x for x, _ in prepared] # Label is not necessary
# Calculate all means / mins / maxs
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MartinThoma/hwrt | hwrt/create_ffiles.py | make_hdf5 | def make_hdf5(dataset_name, feature_count, data,
output_filename, create_learning_curve):
"""
Create the hdf5 file.
Parameters
----------
filename :
name of the file that hdf5_create will use to create the hdf5 file.
feature_count : integer
number of features
d... | python | def make_hdf5(dataset_name, feature_count, data,
output_filename, create_learning_curve):
"""
Create the hdf5 file.
Parameters
----------
filename :
name of the file that hdf5_create will use to create the hdf5 file.
feature_count : integer
number of features
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MartinThoma/hwrt | hwrt/segmentation/segmentation.py | get_dataset | def get_dataset():
"""Create a dataset for machine learning of segmentations.
Returns
-------
tuple :
(X, y) where X is a list of tuples. Each tuple is a feature. y
is a list of labels (0 for 'not in one symbol' and 1 for 'in symbol')
"""
seg_data = "segmentation-X.npy"
seg_... | python | def get_dataset():
"""Create a dataset for machine learning of segmentations.
Returns
-------
tuple :
(X, y) where X is a list of tuples. Each tuple is a feature. y
is a list of labels (0 for 'not in one symbol' and 1 for 'in symbol')
"""
seg_data = "segmentation-X.npy"
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MartinThoma/hwrt | hwrt/segmentation/segmentation.py | get_segmented_raw_data | def get_segmented_raw_data(top_n=10000):
"""Fetch data from the server.
Parameters
----------
top_n : int
Number of data sets which get fetched from the server.
"""
cfg = utils.get_database_configuration()
mysql = cfg['mysql_online']
connection = pymysql.connect(host=mysql['host... | python | def get_segmented_raw_data(top_n=10000):
"""Fetch data from the server.
Parameters
----------
top_n : int
Number of data sets which get fetched from the server.
"""
cfg = utils.get_database_configuration()
mysql = cfg['mysql_online']
connection = pymysql.connect(host=mysql['host... | [
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MartinThoma/hwrt | hwrt/segmentation/segmentation.py | get_stroke_features | def get_stroke_features(recording, strokeid1, strokeid2):
"""Get the features used to decide if two strokes belong to the same symbol
or not.
Parameters
----------
recording : list
A list of strokes
strokeid1 : int
strokeid2 : int
Returns
-------
list :
A list o... | python | def get_stroke_features(recording, strokeid1, strokeid2):
"""Get the features used to decide if two strokes belong to the same symbol
or not.
Parameters
----------
recording : list
A list of strokes
strokeid1 : int
strokeid2 : int
Returns
-------
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MartinThoma/hwrt | hwrt/segmentation/segmentation.py | get_segmentation | def get_segmentation(recording,
single_clf,
single_stroke_clf,
stroke_segmented_classifier):
"""
Get a list of segmentations of recording with the probability of the
segmentation being correct.
Parameters
----------
recording : A li... | python | def get_segmentation(recording,
single_clf,
single_stroke_clf,
stroke_segmented_classifier):
"""
Get a list of segmentations of recording with the probability of the
segmentation being correct.
Parameters
----------
recording : A li... | [
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MartinThoma/hwrt | hwrt/segmentation/segmentation.py | break_mst | def break_mst(mst, i):
"""
Break mst into multiple MSTs by removing one node i.
Parameters
----------
mst : symmetrical square matrix
i : index of the mst where to break
Returns
-------
list of dictionarys ('mst' and 'strokes' are the keys)
"""
for j in range(len(mst['mst']... | python | def break_mst(mst, i):
"""
Break mst into multiple MSTs by removing one node i.
Parameters
----------
mst : symmetrical square matrix
i : index of the mst where to break
Returns
-------
list of dictionarys ('mst' and 'strokes' are the keys)
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MartinThoma/hwrt | hwrt/segmentation/segmentation.py | _is_out_of_order | def _is_out_of_order(segmentation):
"""
Check if a given segmentation is out of order.
Examples
--------
>>> _is_out_of_order([[0, 1, 2, 3]])
False
>>> _is_out_of_order([[0, 1], [2, 3]])
False
>>> _is_out_of_order([[0, 1, 3], [2]])
True
"""
last_stroke = -1
for symbo... | python | def _is_out_of_order(segmentation):
"""
Check if a given segmentation is out of order.
Examples
--------
>>> _is_out_of_order([[0, 1, 2, 3]])
False
>>> _is_out_of_order([[0, 1], [2, 3]])
False
>>> _is_out_of_order([[0, 1, 3], [2]])
True
"""
last_stroke = -1
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MartinThoma/hwrt | hwrt/segmentation/segmentation.py | get_bb_intersections | def get_bb_intersections(recording):
"""
Get all intersections of the bounding boxes of strokes.
Parameters
----------
recording : list of lists of integers
Returns
-------
A symmetrical matrix which indicates if two bounding boxes intersect.
"""
intersections = numpy.zeros((le... | python | def get_bb_intersections(recording):
"""
Get all intersections of the bounding boxes of strokes.
Parameters
----------
recording : list of lists of integers
Returns
-------
A symmetrical matrix which indicates if two bounding boxes intersect.
"""
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MartinThoma/hwrt | hwrt/segmentation/beam.py | p_strokes | def p_strokes(symbol, count):
"""
Get the probability of a written `symbol` having `count` strokes.
Parameters
----------
symbol : str
LaTeX command
count : int, >= 1
Returns
-------
float
In [0.0, 1.0]
"""
global stroke_prob
assert count >= 1
epsilo... | python | def p_strokes(symbol, count):
"""
Get the probability of a written `symbol` having `count` strokes.
Parameters
----------
symbol : str
LaTeX command
count : int, >= 1
Returns
-------
float
In [0.0, 1.0]
"""
global stroke_prob
assert count >= 1
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MartinThoma/hwrt | hwrt/segmentation/beam.py | Beam._add_hypotheses_assuming_new_stroke | def _add_hypotheses_assuming_new_stroke(self,
new_stroke,
stroke_nr,
new_beam):
"""
Get new guesses by assuming new_stroke is a new symbol.
Parameters
----... | python | def _add_hypotheses_assuming_new_stroke(self,
new_stroke,
stroke_nr,
new_beam):
"""
Get new guesses by assuming new_stroke is a new symbol.
Parameters
----... | [
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MartinThoma/hwrt | hwrt/segmentation/beam.py | Beam.add_stroke | def add_stroke(self, new_stroke):
"""
Update the beam so that it considers `new_stroke`.
When a `new_stroke` comes, it can either belong to a symbol for which
at least one other stroke was already made or belong to a symbol for
which `new_stroke` is the first stroke.
Th... | python | def add_stroke(self, new_stroke):
"""
Update the beam so that it considers `new_stroke`.
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MartinThoma/hwrt | hwrt/segmentation/beam.py | Beam._prune | def _prune(self):
"""Shorten hypotheses to the best k ones."""
self.hypotheses = sorted(self.hypotheses,
key=lambda e: e['probability'],
reverse=True)[:self.k] | python | def _prune(self):
"""Shorten hypotheses to the best k ones."""
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MartinThoma/hwrt | bin/convert_cuda2numpy.py | get_matrices | def get_matrices():
"""
Get the matrices from a pickled files.
Returns
-------
list
List of all matrices.
"""
with open('hwrt/misc/is_one_symbol_classifier.pickle', 'rb') as f:
a = pickle.load(f)
arrays = []
for el1 in a.input_storage:
for el2 in el1.__dict_... | python | def get_matrices():
"""
Get the matrices from a pickled files.
Returns
-------
list
List of all matrices.
"""
with open('hwrt/misc/is_one_symbol_classifier.pickle', 'rb') as f:
a = pickle.load(f)
arrays = []
for el1 in a.input_storage:
for el2 in el1.__dict_... | [
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MartinThoma/hwrt | bin/convert_cuda2numpy.py | create_model_tar | def create_model_tar(matrices, tarname="model-cuda-converted.tar"):
"""
Create a tar file which contains the model.
Parameters
----------
matrices : list
tarname : str
Target file which will be created.
"""
# Write layers
filenames = []
for layer in range(len(matrices)):... | python | def create_model_tar(matrices, tarname="model-cuda-converted.tar"):
"""
Create a tar file which contains the model.
Parameters
----------
matrices : list
tarname : str
Target file which will be created.
"""
# Write layers
filenames = []
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MartinThoma/hwrt | hwrt/selfcheck.py | check_python_version | def check_python_version():
"""Check if the currently running Python version is new enough."""
# Required due to multiple with statements on one line
req_version = (2, 7)
cur_version = sys.version_info
if cur_version >= req_version:
print("Python version... %sOK%s (found %s, requires %s)" %
... | python | def check_python_version():
"""Check if the currently running Python version is new enough."""
# Required due to multiple with statements on one line
req_version = (2, 7)
cur_version = sys.version_info
if cur_version >= req_version:
print("Python version... %sOK%s (found %s, requires %s)" %
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MartinThoma/hwrt | hwrt/selfcheck.py | main | def main():
"""Execute all checks."""
check_python_version()
check_python_modules()
check_executables()
home = os.path.expanduser("~")
print("\033[1mCheck files\033[0m")
rcfile = os.path.join(home, ".hwrtrc")
if os.path.isfile(rcfile):
print("~/.hwrtrc... %sFOUND%s" %
... | python | def main():
"""Execute all checks."""
check_python_version()
check_python_modules()
check_executables()
home = os.path.expanduser("~")
print("\033[1mCheck files\033[0m")
rcfile = os.path.join(home, ".hwrtrc")
if os.path.isfile(rcfile):
print("~/.hwrtrc... %sFOUND%s" %
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MartinThoma/hwrt | bin/merge.py | merge | def merge(d1, d2):
"""Merge two raw datasets into one.
Parameters
----------
d1 : dict
d2 : dict
Returns
-------
dict
"""
if d1['formula_id2latex'] is None:
formula_id2latex = {}
else:
formula_id2latex = d1['formula_id2latex'].copy()
formula_id2latex.upd... | python | def merge(d1, d2):
"""Merge two raw datasets into one.
Parameters
----------
d1 : dict
d2 : dict
Returns
-------
dict
"""
if d1['formula_id2latex'] is None:
formula_id2latex = {}
else:
formula_id2latex = d1['formula_id2latex'].copy()
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MartinThoma/hwrt | hwrt/download.py | is_file_consistent | def is_file_consistent(local_path_file, md5_hash):
"""Check if file is there and if the md5_hash is correct."""
return os.path.isfile(local_path_file) and \
hashlib.md5(open(local_path_file, 'rb').read()).hexdigest() == md5_hash | python | def is_file_consistent(local_path_file, md5_hash):
"""Check if file is there and if the md5_hash is correct."""
return os.path.isfile(local_path_file) and \
hashlib.md5(open(local_path_file, 'rb').read()).hexdigest() == md5_hash | [
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MartinThoma/hwrt | hwrt/download.py | main | def main():
"""Main part of the download script."""
# Read config file. This has to get updated via git
project_root = utils.get_project_root()
infofile = os.path.join(project_root, "raw-datasets/info.yml")
logging.info("Read '%s'...", infofile)
with open(infofile, 'r') as ymlfile:
datas... | python | def main():
"""Main part of the download script."""
# Read config file. This has to get updated via git
project_root = utils.get_project_root()
infofile = os.path.join(project_root, "raw-datasets/info.yml")
logging.info("Read '%s'...", infofile)
with open(infofile, 'r') as ymlfile:
datas... | [
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MartinThoma/hwrt | hwrt/language_model/language_model.py | load_model | def load_model():
"""
Load a n-gram language model for mathematics in ARPA format which gets
shipped with hwrt.
Returns
-------
A NgramLanguageModel object
"""
logging.info("Load language model...")
ngram_arpa_t = pkg_resources.resource_filename('hwrt',
... | python | def load_model():
"""
Load a n-gram language model for mathematics in ARPA format which gets
shipped with hwrt.
Returns
-------
A NgramLanguageModel object
"""
logging.info("Load language model...")
ngram_arpa_t = pkg_resources.resource_filename('hwrt',
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MartinThoma/hwrt | hwrt/language_model/language_model.py | NgramLanguageModel.load_from_arpa_str | def load_from_arpa_str(self, arpa_str):
"""
Initialize N-gram model by reading an ARPA language model string.
Parameters
----------
arpa_str : str
A string in ARPA language model file format
"""
data_found = False
end_found = False
in_... | python | def load_from_arpa_str(self, arpa_str):
"""
Initialize N-gram model by reading an ARPA language model string.
Parameters
----------
arpa_str : str
A string in ARPA language model file format
"""
data_found = False
end_found = False
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MartinThoma/hwrt | hwrt/language_model/language_model.py | NgramLanguageModel.get_probability | def get_probability(self, sentence):
"""
Calculate the probability of a sentence, given this language model.
Get P(sentence) = P(w1, w2, w3, ..., wn)
= P(w1, w2, w3) * P(w2, w3, w4) *...* P(wn-2, wn-1, wn)
Parameters
----------
sentence : list
... | python | def get_probability(self, sentence):
"""
Calculate the probability of a sentence, given this language model.
Get P(sentence) = P(w1, w2, w3, ..., wn)
= P(w1, w2, w3) * P(w2, w3, w4) *...* P(wn-2, wn-1, wn)
Parameters
----------
sentence : list
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MartinThoma/hwrt | hwrt/datasets/crohme_eval.py | evaluate_dir | def evaluate_dir(sample_dir):
"""Evaluate all recordings in `sample_dir`.
Parameters
----------
sample_dir : string
The path to a directory with *.inkml files.
Returns
-------
list of dictionaries
Each dictionary contains the keys 'filename' and 'results', where
're... | python | def evaluate_dir(sample_dir):
"""Evaluate all recordings in `sample_dir`.
Parameters
----------
sample_dir : string
The path to a directory with *.inkml files.
Returns
-------
list of dictionaries
Each dictionary contains the keys 'filename' and 'results', where
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MartinThoma/hwrt | hwrt/datasets/crohme_eval.py | evaluate_inkml | def evaluate_inkml(inkml_file_path):
"""Evaluate an InkML file.
Parameters
----------
inkml_file_path : string
path to an InkML file
Returns
-------
dictionary
The dictionary contains the keys 'filename' and 'results', where
'results' itself is a list of dictionarie... | python | def evaluate_inkml(inkml_file_path):
"""Evaluate an InkML file.
Parameters
----------
inkml_file_path : string
path to an InkML file
Returns
-------
dictionary
The dictionary contains the keys 'filename' and 'results', where
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MartinThoma/hwrt | hwrt/datasets/crohme_eval.py | generate_output_csv | def generate_output_csv(evaluation_results, filename='results.csv'):
"""Generate the evaluation results in the format
Parameters
----------
evaluation_results : list of dictionaries
Each dictionary contains the keys 'filename' and 'results', where
'results' itself is a list of dictionar... | python | def generate_output_csv(evaluation_results, filename='results.csv'):
"""Generate the evaluation results in the format
Parameters
----------
evaluation_results : list of dictionaries
Each dictionary contains the keys 'filename' and 'results', where
'results' itself is a list of dictionar... | [
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MartinThoma/hwrt | hwrt/utils.py | get_project_configuration | def get_project_configuration():
"""Get project configuration as dictionary."""
home = os.path.expanduser("~")
rcfile = os.path.join(home, ".hwrtrc")
if not os.path.isfile(rcfile):
create_project_configuration(rcfile)
with open(rcfile, 'r') as ymlfile:
cfg = yaml.load(ymlfile)
re... | python | def get_project_configuration():
"""Get project configuration as dictionary."""
home = os.path.expanduser("~")
rcfile = os.path.join(home, ".hwrtrc")
if not os.path.isfile(rcfile):
create_project_configuration(rcfile)
with open(rcfile, 'r') as ymlfile:
cfg = yaml.load(ymlfile)
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MartinThoma/hwrt | hwrt/utils.py | create_project_configuration | def create_project_configuration(filename):
"""Create a project configuration file which contains a configuration
that might make sense."""
home = os.path.expanduser("~")
project_root_folder = os.path.join(home, "hwr-experiments")
config = {'root': project_root_folder,
'nntoolkit': ... | python | def create_project_configuration(filename):
"""Create a project configuration file which contains a configuration
that might make sense."""
home = os.path.expanduser("~")
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MartinThoma/hwrt | hwrt/utils.py | get_project_root | def get_project_root():
"""Get the project root folder as a string."""
cfg = get_project_configuration()
# At this point it can be sure that the configuration file exists
# Now make sure the project structure exists
for dirname in ["raw-datasets",
"preprocessed",
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"""Get the project root folder as a string."""
cfg = get_project_configuration()
# At this point it can be sure that the configuration file exists
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MartinThoma/hwrt | hwrt/utils.py | get_template_folder | def get_template_folder():
"""Get path to the folder where th HTML templates are."""
cfg = get_project_configuration()
if 'templates' not in cfg:
home = os.path.expanduser("~")
rcfile = os.path.join(home, ".hwrtrc")
cfg['templates'] = pkg_resources.resource_filename('hwrt',
... | python | def get_template_folder():
"""Get path to the folder where th HTML templates are."""
cfg = get_project_configuration()
if 'templates' not in cfg:
home = os.path.expanduser("~")
rcfile = os.path.join(home, ".hwrtrc")
cfg['templates'] = pkg_resources.resource_filename('hwrt',
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MartinThoma/hwrt | hwrt/utils.py | get_database_config_file | def get_database_config_file():
"""Get the absolute path to the database configuration file."""
cfg = get_project_configuration()
if 'dbconfig' in cfg:
if os.path.isfile(cfg['dbconfig']):
return cfg['dbconfig']
else:
logging.info("File '%s' was not found. Adjust 'dbco... | python | def get_database_config_file():
"""Get the absolute path to the database configuration file."""
cfg = get_project_configuration()
if 'dbconfig' in cfg:
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MartinThoma/hwrt | hwrt/utils.py | get_database_configuration | def get_database_configuration():
"""Get database configuration as dictionary."""
db_config = get_database_config_file()
if db_config is None:
return None
with open(db_config, 'r') as ymlfile:
cfg = yaml.load(ymlfile)
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"""Get database configuration as dictionary."""
db_config = get_database_config_file()
if db_config is None:
return None
with open(db_config, 'r') as ymlfile:
cfg = yaml.load(ymlfile)
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"""A function that works for both, Python 2.x and Python 3.x.
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"""
answer = input_string(question)
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"""A function that works for both, Python 2.x and Python 3.x.
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"""
answer = input_string(question)
if answer == "" or answer == "yes":
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MartinThoma/hwrt | hwrt/utils.py | create_run_logfile | def create_run_logfile(folder):
"""Create a 'run.log' within folder. This file contains the time of the
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"""
with open(os.path.join(folder, "run.log"), "w") as f:
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f.write("timestamp: '%s'" % da... | python | def create_run_logfile(folder):
"""Create a 'run.log' within folder. This file contains the time of the
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"""
with open(os.path.join(folder, "run.log"), "w") as f:
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MartinThoma/hwrt | hwrt/utils.py | choose_raw_dataset | def choose_raw_dataset(currently=""):
"""Let the user choose a raw dataset. Return the absolute path."""
folder = os.path.join(get_project_root(), "raw-datasets")
files = [os.path.join(folder, name) for name in os.listdir(folder)
if name.endswith(".pickle")]
default = -1
for i, filename... | python | def choose_raw_dataset(currently=""):
"""Let the user choose a raw dataset. Return the absolute path."""
folder = os.path.join(get_project_root(), "raw-datasets")
files = [os.path.join(folder, name) for name in os.listdir(folder)
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MartinThoma/hwrt | hwrt/utils.py | get_readable_time | def get_readable_time(t):
"""
Format the time to a readable format.
Parameters
----------
t : int
Time in ms
Returns
-------
string
The time splitted to highest used time (minutes, hours, ...)
"""
ms = t % 1000
t -= ms
t /= 1000
s = t % 60
t -= ... | python | def get_readable_time(t):
"""
Format the time to a readable format.
Parameters
----------
t : int
Time in ms
Returns
-------
string
The time splitted to highest used time (minutes, hours, ...)
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MartinThoma/hwrt | hwrt/utils.py | default_model | def default_model():
"""Get a path for a default value for the model. Start searching in the
current directory."""
project_root = get_project_root()
models_dir = os.path.join(project_root, "models")
curr_dir = os.getcwd()
if os.path.commonprefix([models_dir, curr_dir]) == models_dir and \
... | python | def default_model():
"""Get a path for a default value for the model. Start searching in the
current directory."""
project_root = get_project_root()
models_dir = os.path.join(project_root, "models")
curr_dir = os.getcwd()
if os.path.commonprefix([models_dir, curr_dir]) == models_dir and \
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MartinThoma/hwrt | hwrt/utils.py | create_adjusted_model_for_percentages | def create_adjusted_model_for_percentages(model_src, model_use):
"""Replace logreg layer by sigmoid to get probabilities."""
# Copy model file
shutil.copyfile(model_src, model_use)
# Adjust model file
with open(model_src) as f:
content = f.read()
content = content.replace("logreg", "sigm... | python | def create_adjusted_model_for_percentages(model_src, model_use):
"""Replace logreg layer by sigmoid to get probabilities."""
# Copy model file
shutil.copyfile(model_src, model_use)
# Adjust model file
with open(model_src) as f:
content = f.read()
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MartinThoma/hwrt | hwrt/utils.py | create_hdf5 | def create_hdf5(output_filename, feature_count, data):
"""
Create a HDF5 feature files.
Parameters
----------
output_filename : string
name of the HDF5 file that will be created
feature_count : int
dimension of all features combined
data : list of tuples
list of (x, ... | python | def create_hdf5(output_filename, feature_count, data):
"""
Create a HDF5 feature files.
Parameters
----------
output_filename : string
name of the HDF5 file that will be created
feature_count : int
dimension of all features combined
data : list of tuples
list of (x, ... | [
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MartinThoma/hwrt | hwrt/utils.py | load_model | def load_model(model_file):
"""Load a model by its file. This includes the model itself, but also
the preprocessing queue, the feature list and the output semantics.
"""
# Extract tar
with tarfile.open(model_file) as tar:
tarfolder = tempfile.mkdtemp()
tar.extractall(path=tarfolde... | python | def load_model(model_file):
"""Load a model by its file. This includes the model itself, but also
the preprocessing queue, the feature list and the output semantics.
"""
# Extract tar
with tarfile.open(model_file) as tar:
tarfolder = tempfile.mkdtemp()
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MartinThoma/hwrt | hwrt/utils.py | evaluate_model_single_recording_preloaded | def evaluate_model_single_recording_preloaded(preprocessing_queue,
feature_list,
model,
output_semantics,
recording,
... | python | def evaluate_model_single_recording_preloaded(preprocessing_queue,
feature_list,
model,
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MartinThoma/hwrt | hwrt/utils.py | evaluate_model_single_recording_preloaded_multisymbol | def evaluate_model_single_recording_preloaded_multisymbol(preprocessing_queue,
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output_semantics,
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MartinThoma/hwrt | hwrt/utils.py | evaluate_model_single_recording_multisymbol | def evaluate_model_single_recording_multisymbol(model_file, recording):
"""
Evaluate a model for a single recording where possibly multiple symbols
are.
Parameters
----------
model_file : string
Model file (.tar)
recording :
The handwritten recording.
"""
(preprocess... | python | def evaluate_model_single_recording_multisymbol(model_file, recording):
"""
Evaluate a model for a single recording where possibly multiple symbols
are.
Parameters
----------
model_file : string
Model file (.tar)
recording :
The handwritten recording.
"""
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MartinThoma/hwrt | hwrt/utils.py | evaluate_model | def evaluate_model(recording, model_folder, verbose=False):
"""Evaluate model for a single recording."""
from . import preprocess_dataset
from . import features
for target_folder in get_recognizer_folders(model_folder):
# The source is later than the target. That means we need to
# refr... | python | def evaluate_model(recording, model_folder, verbose=False):
"""Evaluate model for a single recording."""
from . import preprocess_dataset
from . import features
for target_folder in get_recognizer_folders(model_folder):
# The source is later than the target. That means we need to
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MartinThoma/hwrt | hwrt/utils.py | get_index2latex | def get_index2latex(model_description):
"""
Get a dictionary that maps indices to LaTeX commands.
Parameters
----------
model_description : string
A model description file that points to a feature folder where an
`index2formula_id.csv` has to be.
Returns
-------
diction... | python | def get_index2latex(model_description):
"""
Get a dictionary that maps indices to LaTeX commands.
Parameters
----------
model_description : string
A model description file that points to a feature folder where an
`index2formula_id.csv` has to be.
Returns
-------
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MartinThoma/hwrt | hwrt/utils.py | get_online_symbol_data | def get_online_symbol_data(database_id):
"""Get from the server."""
import pymysql
import pymysql.cursors
cfg = get_database_configuration()
mysql = cfg['mysql_online']
connection = pymysql.connect(host=mysql['host'],
user=mysql['user'],
... | python | def get_online_symbol_data(database_id):
"""Get from the server."""
import pymysql
import pymysql.cursors
cfg = get_database_configuration()
mysql = cfg['mysql_online']
connection = pymysql.connect(host=mysql['host'],
user=mysql['user'],
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MartinThoma/hwrt | hwrt/utils.py | classify_single_recording | def classify_single_recording(raw_data_json, model_folder, verbose=False):
"""
Get the classification as a list of tuples. The first value is the LaTeX
code, the second value is the probability.
"""
evaluation_file = evaluate_model(raw_data_json, model_folder, verbose)
with open(os.path.join(mod... | python | def classify_single_recording(raw_data_json, model_folder, verbose=False):
"""
Get the classification as a list of tuples. The first value is the LaTeX
code, the second value is the probability.
"""
evaluation_file = evaluate_model(raw_data_json, model_folder, verbose)
with open(os.path.join(mod... | [
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MartinThoma/hwrt | hwrt/utils.py | get_objectlist | def get_objectlist(description, config_key, module):
"""
Take a description and return a list of classes.
Parameters
----------
description : list of dictionaries
Each dictionary has only one entry. The key is the name of a class. The
value of that entry is a list of dictionaries ag... | python | def get_objectlist(description, config_key, module):
"""
Take a description and return a list of classes.
Parameters
----------
description : list of dictionaries
Each dictionary has only one entry. The key is the name of a class. The
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MartinThoma/hwrt | hwrt/utils.py | get_class | def get_class(name, config_key, module):
"""Get the class by its name as a string."""
clsmembers = inspect.getmembers(module, inspect.isclass)
for string_name, act_class in clsmembers:
if string_name == name:
return act_class
# Check if the user has specified a plugin and if the cla... | python | def get_class(name, config_key, module):
"""Get the class by its name as a string."""
clsmembers = inspect.getmembers(module, inspect.isclass)
for string_name, act_class in clsmembers:
if string_name == name:
return act_class
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MartinThoma/hwrt | hwrt/utils.py | get_mysql_cfg | def get_mysql_cfg():
"""
Get the appropriate MySQL configuration
"""
environment = get_project_configuration()['environment']
cfg = get_database_configuration()
if environment == 'production':
mysql = cfg['mysql_online']
else:
mysql = cfg['mysql_dev']
return mysql | python | def get_mysql_cfg():
"""
Get the appropriate MySQL configuration
"""
environment = get_project_configuration()['environment']
cfg = get_database_configuration()
if environment == 'production':
mysql = cfg['mysql_online']
else:
mysql = cfg['mysql_dev']
return mysql | [
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MartinThoma/hwrt | hwrt/utils.py | softmax | def softmax(w, t=1.0):
"""Calculate the softmax of a list of numbers w.
Parameters
----------
w : list of numbers
Returns
-------
a list of the same length as w of non-negative numbers
Examples
--------
>>> softmax([0.1, 0.2])
array([ 0.47502081, 0.52497919])
>>> soft... | python | def softmax(w, t=1.0):
"""Calculate the softmax of a list of numbers w.
Parameters
----------
w : list of numbers
Returns
-------
a list of the same length as w of non-negative numbers
Examples
--------
>>> softmax([0.1, 0.2])
array([ 0.47502081, 0.52497919])
>>> soft... | [
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>>> softmax([0.1, 0.2])
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>>> softmax([-0.1, 0.2])
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MartinThoma/hwrt | hwrt/utils.py | get_beam_cache_directory | def get_beam_cache_directory():
"""
Get a directory where pickled Beam Data can be stored.
Create that directory, if it doesn't exist.
Returns
-------
str
Path to the directory
"""
home = os.path.expanduser("~")
cache_dir = os.path.join(home, '.hwrt-beam-cache')
if not ... | python | def get_beam_cache_directory():
"""
Get a directory where pickled Beam Data can be stored.
Create that directory, if it doesn't exist.
Returns
-------
str
Path to the directory
"""
home = os.path.expanduser("~")
cache_dir = os.path.join(home, '.hwrt-beam-cache')
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MartinThoma/hwrt | hwrt/utils.py | get_beam | def get_beam(secret_uuid):
"""
Get a beam from the session with `secret_uuid`.
Parameters
----------
secret_uuid : str
Returns
-------
The beam object if it exists, otherwise `None`.
"""
beam_dir = get_beam_cache_directory()
beam_filename = os.path.join(beam_dir, secret_uui... | python | def get_beam(secret_uuid):
"""
Get a beam from the session with `secret_uuid`.
Parameters
----------
secret_uuid : str
Returns
-------
The beam object if it exists, otherwise `None`.
"""
beam_dir = get_beam_cache_directory()
beam_filename = os.path.join(beam_dir, secret_uui... | [
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MartinThoma/hwrt | hwrt/utils.py | is_valid_uuid | def is_valid_uuid(uuid_to_test, version=4):
"""
Check if uuid_to_test is a valid UUID.
Parameters
----------
uuid_to_test : str
version : {1, 2, 3, 4}
Returns
-------
`True` if uuid_to_test is a valid UUID, otherwise `False`.
Examples
--------
>>> is_valid_uuid('c9bf9e... | python | def is_valid_uuid(uuid_to_test, version=4):
"""
Check if uuid_to_test is a valid UUID.
Parameters
----------
uuid_to_test : str
version : {1, 2, 3, 4}
Returns
-------
`True` if uuid_to_test is a valid UUID, otherwise `False`.
Examples
--------
>>> is_valid_uuid('c9bf9e... | [
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MartinThoma/hwrt | hwrt/partitions.py | prepare_table | def prepare_table(table):
"""Make the table 'symmetric' where the lower left part of the matrix is
the reverse probability
"""
n = len(table)
for i, row in enumerate(table):
assert len(row) == n
for j, el in enumerate(row):
if i == j:
table[i][i] = 0.0
... | python | def prepare_table(table):
"""Make the table 'symmetric' where the lower left part of the matrix is
the reverse probability
"""
n = len(table)
for i, row in enumerate(table):
assert len(row) == n
for j, el in enumerate(row):
if i == j:
table[i][i] = 0.0
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MartinThoma/hwrt | hwrt/partitions.py | neclusters | def neclusters(l, K):
"""Partition list ``l`` in ``K`` partitions, without empty parts.
>>> l = [0, 1, 2]
>>> list(neclusters(l, 2))
[[[0, 1], [2]], [[1], [0, 2]], [[0], [1, 2]]]
>>> list(neclusters(l, 1))
[[[0, 1, 2]]]
"""
for c in clusters(l, K):
if all(x for x in c):
... | python | def neclusters(l, K):
"""Partition list ``l`` in ``K`` partitions, without empty parts.
>>> l = [0, 1, 2]
>>> list(neclusters(l, 2))
[[[0, 1], [2]], [[1], [0, 2]], [[0], [1, 2]]]
>>> list(neclusters(l, 1))
[[[0, 1, 2]]]
"""
for c in clusters(l, K):
if all(x for x in c):
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MartinThoma/hwrt | hwrt/partitions.py | all_segmentations | def all_segmentations(l):
"""Get all segmentations of a list ``l``.
This gets bigger fast. See https://oeis.org/A000110
For len(l) = 14 it is 190,899,322
>>> list(all_segmentations([0, 1, 2]))
[[[0, 1, 2]], [[0, 1], [2]], [[1], [0, 2]], [[0], [1, 2]], [[0], [1], [2]]]
"""
for K in range(1... | python | def all_segmentations(l):
"""Get all segmentations of a list ``l``.
This gets bigger fast. See https://oeis.org/A000110
For len(l) = 14 it is 190,899,322
>>> list(all_segmentations([0, 1, 2]))
[[[0, 1, 2]], [[0, 1], [2]], [[1], [0, 2]], [[0], [1, 2]], [[0], [1], [2]]]
"""
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MartinThoma/hwrt | hwrt/partitions.py | q | def q(segmentation, s1, s2):
"""Test if ``s1`` and ``s2`` are in the same symbol, given the
``segmentation``.
"""
index1 = find_index(segmentation, s1)
index2 = find_index(segmentation, s2)
return index1 == index2 | python | def q(segmentation, s1, s2):
"""Test if ``s1`` and ``s2`` are in the same symbol, given the
``segmentation``.
"""
index1 = find_index(segmentation, s1)
index2 = find_index(segmentation, s2)
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MartinThoma/hwrt | hwrt/partitions.py | score_segmentation | def score_segmentation(segmentation, table):
"""Get the score of a segmentation."""
stroke_nr = sum(1 for symbol in segmentation for stroke in symbol)
score = 1
for i in range(stroke_nr):
for j in range(i+1, stroke_nr):
qval = q(segmentation, i, j)
if qval:
... | python | def score_segmentation(segmentation, table):
"""Get the score of a segmentation."""
stroke_nr = sum(1 for symbol in segmentation for stroke in symbol)
score = 1
for i in range(stroke_nr):
for j in range(i+1, stroke_nr):
qval = q(segmentation, i, j)
if qval:
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MartinThoma/hwrt | hwrt/partitions.py | TopFinder.push | def push(self, element, value):
"""Push an ``element`` into the datastrucutre together with its value
and only save it if it currently is one of the top n elements.
Drop elements if necessary.
"""
insert_pos = 0
for index, el in enumerate(self.tops):
if... | python | def push(self, element, value):
"""Push an ``element`` into the datastrucutre together with its value
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MartinThoma/hwrt | bin/convert.py | _array2cstr | def _array2cstr(arr):
""" Serializes a numpy array to a compressed base64 string """
out = StringIO()
np.save(out, arr)
return b64encode(out.getvalue()) | python | def _array2cstr(arr):
""" Serializes a numpy array to a compressed base64 string """
out = StringIO()
np.save(out, arr)
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MartinThoma/hwrt | bin/convert.py | _str2array | def _str2array(d):
""" Reconstructs a numpy array from a plain-text string """
if type(d) == list:
return np.asarray([_str2array(s) for s in d])
ins = StringIO(d)
return np.loadtxt(ins) | python | def _str2array(d):
""" Reconstructs a numpy array from a plain-text string """
if type(d) == list:
return np.asarray([_str2array(s) for s in d])
ins = StringIO(d)
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MartinThoma/hwrt | bin/convert.py | create_output_semantics | def create_output_semantics(model_folder, outputs):
"""
Create a 'output_semantics.csv' file which contains information what the
output of the single output neurons mean.
Parameters
----------
model_folder : str
folder where the model description file is
outputs : int
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"""
Create a 'output_semantics.csv' file which contains information what the
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Parameters
----------
model_folder : str
folder where the model description file is
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MartinThoma/hwrt | hwrt/datasets/mfrdb.py | elementtree_to_dict | def elementtree_to_dict(element):
"""Convert an xml ElementTree to a dictionary."""
d = dict()
if hasattr(element, 'text') and element.text is not None:
d['text'] = element.text
d.update(element.items()) # element's attributes
for c in list(element): # element's children
if c.tag... | python | def elementtree_to_dict(element):
"""Convert an xml ElementTree to a dictionary."""
d = dict()
if hasattr(element, 'text') and element.text is not None:
d['text'] = element.text
d.update(element.items()) # element's attributes
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MartinThoma/hwrt | hwrt/datasets/mfrdb.py | strip_end | def strip_end(text, suffix):
"""Strip `suffix` from the end of `text` if `text` has that suffix."""
if not text.endswith(suffix):
return text
return text[:len(text)-len(suffix)] | python | def strip_end(text, suffix):
"""Strip `suffix` from the end of `text` if `text` has that suffix."""
if not text.endswith(suffix):
return text
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MartinThoma/hwrt | hwrt/datasets/__init__.py | formula_to_dbid | def formula_to_dbid(formula_str, backslash_fix=False):
"""
Convert a LaTeX formula to the database index.
Parameters
----------
formula_str : string
The formula as LaTeX code.
backslash_fix : boolean
If this is set to true, then it will be checked if the same formula
exi... | python | def formula_to_dbid(formula_str, backslash_fix=False):
"""
Convert a LaTeX formula to the database index.
Parameters
----------
formula_str : string
The formula as LaTeX code.
backslash_fix : boolean
If this is set to true, then it will be checked if the same formula
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MartinThoma/hwrt | hwrt/datasets/__init__.py | insert_recording | def insert_recording(hw):
"""Insert recording `hw` into database."""
mysql = utils.get_mysql_cfg()
connection = pymysql.connect(host=mysql['host'],
user=mysql['user'],
passwd=mysql['passwd'],
db=mysql['db'],
... | python | def insert_recording(hw):
"""Insert recording `hw` into database."""
mysql = utils.get_mysql_cfg()
connection = pymysql.connect(host=mysql['host'],
user=mysql['user'],
passwd=mysql['passwd'],
db=mysql['db'],
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MartinThoma/hwrt | hwrt/datasets/__init__.py | insert_symbol_mapping | def insert_symbol_mapping(raw_data_id, symbol_id, user_id, strokes):
"""
Insert data into `wm_strokes_to_symbol`.
Parameters
----------
raw_data_id : int
user_id : int
strokes: list of int
"""
mysql = utils.get_mysql_cfg()
connection = pymysql.connect(host=mysql['host'],
... | python | def insert_symbol_mapping(raw_data_id, symbol_id, user_id, strokes):
"""
Insert data into `wm_strokes_to_symbol`.
Parameters
----------
raw_data_id : int
user_id : int
strokes: list of int
"""
mysql = utils.get_mysql_cfg()
connection = pymysql.connect(host=mysql['host'],
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MartinThoma/hwrt | hwrt/analyze_data.py | filter_label | def filter_label(label, replace_by_similar=True):
"""Some labels currently don't work together because of LaTeX naming
clashes. Those will be replaced by simple strings. """
bad_names = ['celsius', 'degree', 'ohm', 'venus', 'mars', 'astrosun',
'fullmoon', 'leftmoon', 'female', 'male', 'c... | python | def filter_label(label, replace_by_similar=True):
"""Some labels currently don't work together because of LaTeX naming
clashes. Those will be replaced by simple strings. """
bad_names = ['celsius', 'degree', 'ohm', 'venus', 'mars', 'astrosun',
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MartinThoma/hwrt | hwrt/analyze_data.py | analyze_feature | def analyze_feature(raw_datasets, feature, basename="aspect_ratios"):
"""
Apply ``feature`` to all recordings in ``raw_datasets``. Store the results
in two files. One file stores the raw result, the other one groups the
results by symbols and stores the mean, standard deviation and the name of
the s... | python | def analyze_feature(raw_datasets, feature, basename="aspect_ratios"):
"""
Apply ``feature`` to all recordings in ``raw_datasets``. Store the results
in two files. One file stores the raw result, the other one groups the
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MartinThoma/hwrt | hwrt/analyze_data.py | main | def main(handwriting_datasets_file, analyze_features):
"""Start the creation of the wanted metric."""
# Load from pickled file
logging.info("Start loading data '%s' ...", handwriting_datasets_file)
loaded = pickle.load(open(handwriting_datasets_file))
raw_datasets = loaded['handwriting_datasets']
... | python | def main(handwriting_datasets_file, analyze_features):
"""Start the creation of the wanted metric."""
# Load from pickled file
logging.info("Start loading data '%s' ...", handwriting_datasets_file)
loaded = pickle.load(open(handwriting_datasets_file))
raw_datasets = loaded['handwriting_datasets']
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MartinThoma/hwrt | hwrt/datasets/mathbrush.py | remove_matching_braces | def remove_matching_braces(latex):
"""
If `latex` is surrounded by matching braces, remove them. They are not
necessary.
Parameters
----------
latex : string
Returns
-------
string
Examples
--------
>>> remove_matching_braces('{2+2}')
'2+2'
>>> remove_matching_... | python | def remove_matching_braces(latex):
"""
If `latex` is surrounded by matching braces, remove them. They are not
necessary.
Parameters
----------
latex : string
Returns
-------
string
Examples
--------
>>> remove_matching_braces('{2+2}')
'2+2'
>>> remove_matching_... | [
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MartinThoma/hwrt | hwrt/datasets/mathbrush.py | read_folder | def read_folder(folder):
"""Read all files of `folder` and return a list of HandwrittenData
objects.
Parameters
----------
folder : string
Path to a folder
Returns
-------
list :
A list of all .ink files in the given folder.
"""
recordings = []
for filename ... | python | def read_folder(folder):
"""Read all files of `folder` and return a list of HandwrittenData
objects.
Parameters
----------
folder : string
Path to a folder
Returns
-------
list :
A list of all .ink files in the given folder.
"""
recordings = []
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MartinThoma/hwrt | hwrt/handwritten_data.py | _get_colors | def _get_colors(segmentation):
"""Get a list of colors which is as long as the segmentation.
Parameters
----------
segmentation : list of lists
Returns
-------
list
A list of colors.
"""
symbol_count = len(segmentation)
num_colors = symbol_count
# See http://stacko... | python | def _get_colors(segmentation):
"""Get a list of colors which is as long as the segmentation.
Parameters
----------
segmentation : list of lists
Returns
-------
list
A list of colors.
"""
symbol_count = len(segmentation)
num_colors = symbol_count
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.fix_times | def fix_times(self):
"""
Some recordings have wrong times. Fix them so that nothing after
loading a handwritten recording breaks.
"""
pointlist = self.get_pointlist()
times = [point['time'] for stroke in pointlist for point in stroke]
times_min = max(min(times), 0... | python | def fix_times(self):
"""
Some recordings have wrong times. Fix them so that nothing after
loading a handwritten recording breaks.
"""
pointlist = self.get_pointlist()
times = [point['time'] for stroke in pointlist for point in stroke]
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.get_pointlist | def get_pointlist(self):
"""
Get a list of lists of tuples from JSON raw data string. Those lists
represent strokes with control points.
Returns
-------
list :
A list of strokes. Each stroke is a list of dictionaries
{'x': 123, 'y': 42, 'time': 13... | python | def get_pointlist(self):
"""
Get a list of lists of tuples from JSON raw data string. Those lists
represent strokes with control points.
Returns
-------
list :
A list of strokes. Each stroke is a list of dictionaries
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.get_sorted_pointlist | def get_sorted_pointlist(self):
"""
Make sure that the points and strokes are in order.
Returns
-------
list
A list of all strokes in the recording. Each stroke is represented
as a list of dicts {'time': 123, 'x': 45, 'y': 67}
"""
pointlis... | python | def get_sorted_pointlist(self):
"""
Make sure that the points and strokes are in order.
Returns
-------
list
A list of all strokes in the recording. Each stroke is represented
as a list of dicts {'time': 123, 'x': 45, 'y': 67}
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.set_pointlist | def set_pointlist(self, pointlist):
"""Overwrite pointlist.
Parameters
----------
pointlist : a list of strokes; each stroke is a list of points
The inner lists represent strokes. Every stroke consists of points.
Every point is a dictinary with 'x', 'y', 'time'.
... | python | def set_pointlist(self, pointlist):
"""Overwrite pointlist.
Parameters
----------
pointlist : a list of strokes; each stroke is a list of points
The inner lists represent strokes. Every stroke consists of points.
Every point is a dictinary with 'x', 'y', 'time'.
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.get_bounding_box | def get_bounding_box(self):
""" Get the bounding box of a pointlist. """
pointlist = self.get_pointlist()
# Initialize bounding box parameters to save values
minx, maxx = pointlist[0][0]["x"], pointlist[0][0]["x"]
miny, maxy = pointlist[0][0]["y"], pointlist[0][0]["y"]
m... | python | def get_bounding_box(self):
""" Get the bounding box of a pointlist. """
pointlist = self.get_pointlist()
# Initialize bounding box parameters to save values
minx, maxx = pointlist[0][0]["x"], pointlist[0][0]["x"]
miny, maxy = pointlist[0][0]["y"], pointlist[0][0]["y"]
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.get_bitmap | def get_bitmap(self, time=None, size=32, store_path=None):
"""
Get a bitmap of the object at a given instance of time. If time is
`None`,`then the bitmap is generated for the last point in time.
Parameters
----------
time : int or None
size : int
Size... | python | def get_bitmap(self, time=None, size=32, store_path=None):
"""
Get a bitmap of the object at a given instance of time. If time is
`None`,`then the bitmap is generated for the last point in time.
Parameters
----------
time : int or None
size : int
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.preprocessing | def preprocessing(self, algorithms):
"""Apply preprocessing algorithms.
Parameters
----------
algorithms : a list objects
Preprocessing allgorithms which get applied in order.
Examples
--------
>>> import preprocessing
>>> a = HandwrittenData... | python | def preprocessing(self, algorithms):
"""Apply preprocessing algorithms.
Parameters
----------
algorithms : a list objects
Preprocessing allgorithms which get applied in order.
Examples
--------
>>> import preprocessing
>>> a = HandwrittenData... | [
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>>> import preprocessing
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.feature_extraction | def feature_extraction(self, algorithms):
"""Get a list of features.
Every algorithm has to return the features as a list."""
assert type(algorithms) is list
features = []
for algorithm in algorithms:
new_features = algorithm(self)
assert len(new_features... | python | def feature_extraction(self, algorithms):
"""Get a list of features.
Every algorithm has to return the features as a list."""
assert type(algorithms) is list
features = []
for algorithm in algorithms:
new_features = algorithm(self)
assert len(new_features... | [
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.show | def show(self):
"""Show the data graphically in a new pop-up window."""
# prevent the following error:
# '_tkinter.TclError: no display name and no $DISPLAY environment
# variable'
# import matplotlib
# matplotlib.use('GTK3Agg', warn=False)
import matplotlib.... | python | def show(self):
"""Show the data graphically in a new pop-up window."""
# prevent the following error:
# '_tkinter.TclError: no display name and no $DISPLAY environment
# variable'
# import matplotlib
# matplotlib.use('GTK3Agg', warn=False)
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.count_single_dots | def count_single_dots(self):
"""Count all strokes of this recording that have only a single dot.
"""
pointlist = self.get_pointlist()
single_dots = 0
for stroke in pointlist:
if len(stroke) == 1:
single_dots += 1
return single_dots | python | def count_single_dots(self):
"""Count all strokes of this recording that have only a single dot.
"""
pointlist = self.get_pointlist()
single_dots = 0
for stroke in pointlist:
if len(stroke) == 1:
single_dots += 1
return single_dots | [
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MartinThoma/hwrt | hwrt/handwritten_data.py | HandwrittenData.to_single_symbol_list | def to_single_symbol_list(self):
"""
Convert this HandwrittenData object into a list of HandwrittenData
objects. Each element of the list is a single symbol.
Returns
-------
list of HandwrittenData objects
"""
symbol_stream = getattr(self,
... | python | def to_single_symbol_list(self):
"""
Convert this HandwrittenData object into a list of HandwrittenData
objects. Each element of the list is a single symbol.
Returns
-------
list of HandwrittenData objects
"""
symbol_stream = getattr(self,
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acsone/setuptools-odoo | setuptools_odoo/git_postversion.py | get_git_postversion | def get_git_postversion(addon_dir):
""" return the addon version number, with a developmental version increment
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""" return the addon version number, with a developmental version increment
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acsone/setuptools-odoo | setuptools_odoo/core.py | _get_odoo_version_info | def _get_odoo_version_info(addons_dir, odoo_version_override=None):
""" Detect Odoo version from an addons directory """
odoo_version_info = None
addons = os.listdir(addons_dir)
for addon in addons:
addon_dir = os.path.join(addons_dir, addon)
if is_installable_addon(addon_dir):
... | python | def _get_odoo_version_info(addons_dir, odoo_version_override=None):
""" Detect Odoo version from an addons directory """
odoo_version_info = None
addons = os.listdir(addons_dir)
for addon in addons:
addon_dir = os.path.join(addons_dir, addon)
if is_installable_addon(addon_dir):
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acsone/setuptools-odoo | setuptools_odoo/core.py | _get_version | def _get_version(addon_dir, manifest, odoo_version_override=None,
git_post_version=True):
""" Get addon version information from an addon directory """
version = manifest.get('version')
if not version:
warn("No version in manifest in %s" % addon_dir)
version = '0.0.0'
if... | python | def _get_version(addon_dir, manifest, odoo_version_override=None,
git_post_version=True):
""" Get addon version information from an addon directory """
version = manifest.get('version')
if not version:
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acsone/setuptools-odoo | setuptools_odoo/core.py | get_install_requires_odoo_addon | def get_install_requires_odoo_addon(addon_dir,
no_depends=[],
depends_override={},
external_dependencies_override={},
odoo_version_override=None):
""" Get the list of requi... | python | def get_install_requires_odoo_addon(addon_dir,
no_depends=[],
depends_override={},
external_dependencies_override={},
odoo_version_override=None):
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acsone/setuptools-odoo | setuptools_odoo/core.py | get_install_requires_odoo_addons | def get_install_requires_odoo_addons(addons_dir,
depends_override={},
external_dependencies_override={},
odoo_version_override=None):
""" Get the list of requirements for a directory containing addons """
... | python | def get_install_requires_odoo_addons(addons_dir,
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external_dependencies_override={},
odoo_version_override=None):
""" Get the list of requirements for a directory containing addons """
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dgilland/flask-alchy | flask_alchy.py | Alchy.make_declarative_base | def make_declarative_base(self, metadata=None):
"""Override parent function with alchy's"""
return make_declarative_base(self.session,
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metadata=metadata) | python | def make_declarative_base(self, metadata=None):
"""Override parent function with alchy's"""
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capless/kev | kev/backends/__init__.py | DocDB.prep_doc | def prep_doc(self, doc_obj):
"""
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Useful for save and backup functions.
@param doc_obj:
@return:
"""
doc = doc_obj._da... | python | def prep_doc(self, doc_obj):
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Useful for save and backup functions.
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Miserlou/flask-zappa | bin/client.py | apply_zappa_settings | def apply_zappa_settings(zappa_obj, zappa_settings, environment):
'''Load Zappa settings, set defaults if needed, and apply to the Zappa object'''
settings_all = json.load(zappa_settings)
settings = settings_all[environment]
# load defaults for missing options
for key,value in DEFAULT_SETTINGS.ite... | python | def apply_zappa_settings(zappa_obj, zappa_settings, environment):
'''Load Zappa settings, set defaults if needed, and apply to the Zappa object'''
settings_all = json.load(zappa_settings)
settings = settings_all[environment]
# load defaults for missing options
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Miserlou/flask-zappa | bin/client.py | deploy | def deploy(environment, zappa_settings):
""" Package, create and deploy to Lambda."""
print(("Deploying " + environment))
zappa, settings, lambda_name, zip_path = \
_package(environment, zappa_settings)
s3_bucket_name = settings['s3_bucket']
try:
# Load your AWS credentials from ~... | python | def deploy(environment, zappa_settings):
""" Package, create and deploy to Lambda."""
print(("Deploying " + environment))
zappa, settings, lambda_name, zip_path = \
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s3_bucket_name = settings['s3_bucket']
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Miserlou/flask-zappa | bin/client.py | update | def update(environment, zappa_settings):
""" Update an existing deployment."""
print(("Updating " + environment))
# Package dependencies, and the source code into a zip
zappa, settings, lambda_name, zip_path = \
_package(environment, zappa_settings)
s3_bucket_name = settings['s3_bucket']
... | python | def update(environment, zappa_settings):
""" Update an existing deployment."""
print(("Updating " + environment))
# Package dependencies, and the source code into a zip
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Miserlou/flask-zappa | flask_zappa/handler.py | lambda_handler | def lambda_handler(event, context, settings_name="zappa_settings"):
""" An AWS Lambda function which parses specific API Gateway input into a
WSGI request, feeds it to Flask, procceses the Flask response, and returns
that back to the API Gateway.
"""
# Loading settings from a python module
setti... | python | def lambda_handler(event, context, settings_name="zappa_settings"):
""" An AWS Lambda function which parses specific API Gateway input into a
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frankban/django-endless-pagination | endless_pagination/views.py | MultipleObjectMixin.get_context_data | def get_context_data(self, **kwargs):
"""Get the context for this view.
Also adds the *page_template* variable in the context.
If the *page_template* is not given as a kwarg of the *as_view*
method then it is generated using app label, model name
(obviously if the list is a que... | python | def get_context_data(self, **kwargs):
"""Get the context for this view.
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SpockBotMC/SpockBot | spockbot/mcdata/utils.py | clean_var | def clean_var(text):
"""Turn text into a valid python classname or variable"""
text = re_invalid_var.sub('', text)
text = re_invalid_start.sub('', text)
return text | python | def clean_var(text):
"""Turn text into a valid python classname or variable"""
text = re_invalid_var.sub('', text)
text = re_invalid_start.sub('', text)
return text | [
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SpockBotMC/SpockBot | spockbot/plugins/tools/task.py | TaskFailed.full_tasktrace | def full_tasktrace(self):
"""
List of all failed tasks caused by this and all previous errors.
Returns:
List[Task]
"""
if self.prev_error:
return self.prev_error.tasktrace + self.tasktrace
else:
return self.tasktrace | python | def full_tasktrace(self):
"""
List of all failed tasks caused by this and all previous errors.
Returns:
List[Task]
"""
if self.prev_error:
return self.prev_error.tasktrace + self.tasktrace
else:
return self.tasktrace | [
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