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jazzband/django-model-utils | model_utils/managers.py | SoftDeletableManagerMixin.get_queryset | def get_queryset(self):
"""
Return queryset limited to not removed entries.
"""
kwargs = {'model': self.model, 'using': self._db}
if hasattr(self, '_hints'):
kwargs['hints'] = self._hints
return self._queryset_class(**kwargs).filter(is_removed=False) | python | def get_queryset(self):
"""
Return queryset limited to not removed entries.
"""
kwargs = {'model': self.model, 'using': self._db}
if hasattr(self, '_hints'):
kwargs['hints'] = self._hints
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jazzband/django-model-utils | model_utils/tracker.py | FieldInstanceTracker.previous | def previous(self, field):
"""Returns currently saved value of given field"""
# handle deferred fields that have not yet been loaded from the database
if self.instance.pk and field in self.deferred_fields and field not in self.saved_data:
# if the field has not been assigned locall... | python | def previous(self, field):
"""Returns currently saved value of given field"""
# handle deferred fields that have not yet been loaded from the database
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jazzband/django-model-utils | model_utils/tracker.py | FieldTracker.get_field_map | def get_field_map(self, cls):
"""Returns dict mapping fields names to model attribute names"""
field_map = dict((field, field) for field in self.fields)
all_fields = dict((f.name, f.attname) for f in cls._meta.fields)
field_map.update(**dict((k, v) for (k, v) in all_fields.items()
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"""Returns dict mapping fields names to model attribute names"""
field_map = dict((field, field) for field in self.fields)
all_fields = dict((f.name, f.attname) for f in cls._meta.fields)
field_map.update(**dict((k, v) for (k, v) in all_fields.items()
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jazzband/django-model-utils | model_utils/models.py | add_status_query_managers | def add_status_query_managers(sender, **kwargs):
"""
Add a Querymanager for each status item dynamically.
"""
if not issubclass(sender, StatusModel):
return
if django.VERSION >= (1, 10):
# First, get current manager name...
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"""
Add a Querymanager for each status item dynamically.
"""
if not issubclass(sender, StatusModel):
return
if django.VERSION >= (1, 10):
# First, get current manager name...
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jazzband/django-model-utils | model_utils/models.py | add_timeframed_query_manager | def add_timeframed_query_manager(sender, **kwargs):
"""
Add a QueryManager for a specific timeframe.
"""
if not issubclass(sender, TimeFramedModel):
return
if _field_exists(sender, 'timeframed'):
raise ImproperlyConfigured(
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... | python | def add_timeframed_query_manager(sender, **kwargs):
"""
Add a QueryManager for a specific timeframe.
"""
if not issubclass(sender, TimeFramedModel):
return
if _field_exists(sender, 'timeframed'):
raise ImproperlyConfigured(
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invoice-x/invoice2data | src/invoice2data/input/tesseract4.py | to_text | def to_text(path, language='fra'):
"""Wraps Tesseract 4 OCR with custom language model.
Parameters
----------
path : str
path of electronic invoice in JPG or PNG format
Returns
-------
extracted_str : str
returns extracted text from image in JPG or PNG format
"""
i... | python | def to_text(path, language='fra'):
"""Wraps Tesseract 4 OCR with custom language model.
Parameters
----------
path : str
path of electronic invoice in JPG or PNG format
Returns
-------
extracted_str : str
returns extracted text from image in JPG or PNG format
"""
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invoice-x/invoice2data | src/invoice2data/input/gvision.py | to_text | def to_text(path, bucket_name='cloud-vision-84893', language='fr'):
"""Sends PDF files to Google Cloud Vision for OCR.
Before using invoice2data, make sure you have the auth json path set as
env var GOOGLE_APPLICATION_CREDENTIALS
Parameters
----------
path : str
path of electronic invo... | python | def to_text(path, bucket_name='cloud-vision-84893', language='fr'):
"""Sends PDF files to Google Cloud Vision for OCR.
Before using invoice2data, make sure you have the auth json path set as
env var GOOGLE_APPLICATION_CREDENTIALS
Parameters
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path : str
path of electronic invo... | [
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invoice-x/invoice2data | src/invoice2data/output/to_csv.py | write_to_file | def write_to_file(data, path):
"""Export extracted fields to csv
Appends .csv to path if missing and generates csv file in specified directory, if not then in root
Parameters
----------
data : dict
Dictionary of extracted fields
path : str
directory to save generated csv file
... | python | def write_to_file(data, path):
"""Export extracted fields to csv
Appends .csv to path if missing and generates csv file in specified directory, if not then in root
Parameters
----------
data : dict
Dictionary of extracted fields
path : str
directory to save generated csv file
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invoice-x/invoice2data | src/invoice2data/input/tesseract.py | to_text | def to_text(path):
"""Wraps Tesseract OCR.
Parameters
----------
path : str
path of electronic invoice in JPG or PNG format
Returns
-------
extracted_str : str
returns extracted text from image in JPG or PNG format
"""
import subprocess
from distutils import sp... | python | def to_text(path):
"""Wraps Tesseract OCR.
Parameters
----------
path : str
path of electronic invoice in JPG or PNG format
Returns
-------
extracted_str : str
returns extracted text from image in JPG or PNG format
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invoice-x/invoice2data | src/invoice2data/extract/plugins/tables.py | extract | def extract(self, content, output):
"""Try to extract tables from an invoice"""
for table in self['tables']:
# First apply default options.
plugin_settings = DEFAULT_OPTIONS.copy()
plugin_settings.update(table)
table = plugin_settings
# Validate settings
assert... | python | def extract(self, content, output):
"""Try to extract tables from an invoice"""
for table in self['tables']:
# First apply default options.
plugin_settings = DEFAULT_OPTIONS.copy()
plugin_settings.update(table)
table = plugin_settings
# Validate settings
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invoice-x/invoice2data | src/invoice2data/input/pdftotext.py | to_text | def to_text(path):
"""Wrapper around Poppler pdftotext.
Parameters
----------
path : str
path of electronic invoice in PDF
Returns
-------
out : str
returns extracted text from pdf
Raises
------
EnvironmentError:
If pdftotext library is not found
""... | python | def to_text(path):
"""Wrapper around Poppler pdftotext.
Parameters
----------
path : str
path of electronic invoice in PDF
Returns
-------
out : str
returns extracted text from pdf
Raises
------
EnvironmentError:
If pdftotext library is not found
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invoice-x/invoice2data | src/invoice2data/extract/invoice_template.py | InvoiceTemplate.prepare_input | def prepare_input(self, extracted_str):
"""
Input raw string and do transformations, as set in template file.
"""
# Remove withspace
if self.options['remove_whitespace']:
optimized_str = re.sub(' +', '', extracted_str)
else:
optimized_str = extrac... | python | def prepare_input(self, extracted_str):
"""
Input raw string and do transformations, as set in template file.
"""
# Remove withspace
if self.options['remove_whitespace']:
optimized_str = re.sub(' +', '', extracted_str)
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invoice-x/invoice2data | src/invoice2data/extract/invoice_template.py | InvoiceTemplate.matches_input | def matches_input(self, optimized_str):
"""See if string matches keywords set in template file"""
if all([keyword in optimized_str for keyword in self['keywords']]):
logger.debug('Matched template %s', self['template_name'])
return True | python | def matches_input(self, optimized_str):
"""See if string matches keywords set in template file"""
if all([keyword in optimized_str for keyword in self['keywords']]):
logger.debug('Matched template %s', self['template_name'])
return True | [
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invoice-x/invoice2data | src/invoice2data/extract/invoice_template.py | InvoiceTemplate.parse_date | def parse_date(self, value):
"""Parses date and returns date after parsing"""
res = dateparser.parse(
value, date_formats=self.options['date_formats'], languages=self.options['languages']
)
logger.debug("result of date parsing=%s", res)
return res | python | def parse_date(self, value):
"""Parses date and returns date after parsing"""
res = dateparser.parse(
value, date_formats=self.options['date_formats'], languages=self.options['languages']
)
logger.debug("result of date parsing=%s", res)
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invoice-x/invoice2data | src/invoice2data/output/to_json.py | write_to_file | def write_to_file(data, path):
"""Export extracted fields to json
Appends .json to path if missing and generates json file in specified directory, if not then in root
Parameters
----------
data : dict
Dictionary of extracted fields
path : str
directory to save generated json fi... | python | def write_to_file(data, path):
"""Export extracted fields to json
Appends .json to path if missing and generates json file in specified directory, if not then in root
Parameters
----------
data : dict
Dictionary of extracted fields
path : str
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invoice-x/invoice2data | src/invoice2data/main.py | create_parser | def create_parser():
"""Returns argument parser """
parser = argparse.ArgumentParser(
description='Extract structured data from PDF files and save to CSV or JSON.'
)
parser.add_argument(
'--input-reader',
choices=input_mapping.keys(),
default='pdftotext',
help='... | python | def create_parser():
"""Returns argument parser """
parser = argparse.ArgumentParser(
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invoice-x/invoice2data | src/invoice2data/main.py | main | def main(args=None):
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invoice-x/invoice2data | src/invoice2data/output/to_xml.py | write_to_file | def write_to_file(data, path):
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Appends .xml to path if missing and generates xml file in specified directory, if not then in root
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----------
data : dict
Dictionary of extracted fields
path : str
directory to save generated xml file
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data : dict
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path : str
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invoice-x/invoice2data | src/invoice2data/extract/loader.py | read_templates | def read_templates(folder=None):
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invoice-x/invoice2data | src/invoice2data/input/pdfminer_wrapper.py | to_text | def to_text(path):
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Parameters
----------
path : str
path of electronic invoice in PDF
Returns
-------
str : str
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"""
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import sys
... | python | def to_text(path):
"""Wrapper around `pdfminer`.
Parameters
----------
path : str
path of electronic invoice in PDF
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-------
str : str
returns extracted text from pdf
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A tuple of DataFrames for main effects and interaction effects.
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SALib/SALib | src/SALib/util/__init__.py | avail_approaches | def avail_approaches(pkg):
'''Create list of available modules.
Arguments
---------
pkg : module
module to inspect
Returns
---------
method : list
A list of available submodules
'''
methods = [modname for importer, modname, ispkg in
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'''Create list of available modules.
Arguments
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pkg : module
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method : list
A list of available submodules
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SALib/SALib | src/SALib/util/__init__.py | scale_samples | def scale_samples(params, bounds):
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list of lists of dimensions `num_params`-by-2
params : numpy.ndarray
numpy array of dimensions `num_params`-by-:math:`N`,
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SALib/SALib | src/SALib/util/__init__.py | nonuniform_scale_samples | def nonuniform_scale_samples(params, bounds, dists):
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numpy array of dimensions num_params-by-N,
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SALib/SALib | src/SALib/util/__init__.py | read_param_file | def read_param_file(filename, delimiter=None):
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Param2,0,1,Group2,dist2
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... | python | def read_param_file(filename, delimiter=None):
"""Unpacks a parameter file into a dictionary
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SALib/SALib | src/SALib/util/__init__.py | compute_groups_matrix | def compute_groups_matrix(groups):
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SALib/SALib | src/SALib/util/__init__.py | requires_gurobipy | def requires_gurobipy(_has_gurobi):
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Raises an import error at runtime if gurobi is not present.
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using brut... | python | def requires_gurobipy(_has_gurobi):
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Decorator function which takes a boolean _has_gurobi as an argument.
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Raises an import error at runtime if gurobi is not present.
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SALib/SALib | src/SALib/analyze/morris.py | compute_grouped_sigma | def compute_grouped_sigma(ungrouped_sigma, group_matrix):
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group_matrix = np.array(group_matrix, dtype=np.bool)
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SALib/SALib | src/SALib/analyze/morris.py | compute_grouped_metric | def compute_grouped_metric(ungrouped_metric, group_matrix):
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... | python | def compute_grouped_metric(ungrouped_metric, group_matrix):
'''
Computes the mean value for the groups of parameter values in the
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SALib/SALib | src/SALib/analyze/morris.py | compute_mu_star_confidence | def compute_mu_star_confidence(ee, num_trajectories, num_resamples,
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'''
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SALib/SALib | src/SALib/sample/morris/gurobi.py | timestamp | def timestamp(num_params, p_levels, k_choices, N):
"""
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"""
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... | python | def timestamp(num_params, p_levels, k_choices, N):
"""
Returns a uniform timestamp with parameter values for file identification
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SALib/SALib | src/SALib/sample/morris/brute.py | BruteForce.brute_force_most_distant | def brute_force_most_distant(self, input_sample, num_samples,
num_params, k_choices,
num_groups=None):
"""Use brute force method to find most distant trajectories
Arguments
---------
input_sample : numpy.ndarray
n... | python | def brute_force_most_distant(self, input_sample, num_samples,
num_params, k_choices,
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input_sample : numpy.ndarray
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SALib/SALib | src/SALib/sample/morris/brute.py | BruteForce.find_most_distant | def find_most_distant(self, input_sample, num_samples,
num_params, k_choices, num_groups=None):
"""
Finds the 'k_choices' most distant choices from the
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Arguments
---------
input_sample : num... | python | def find_most_distant(self, input_sample, num_samples,
num_params, k_choices, num_groups=None):
"""
Finds the 'k_choices' most distant choices from the
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SALib/SALib | src/SALib/sample/morris/brute.py | BruteForce.mappable | def mappable(combos, pairwise, distance_matrix):
'''
Obtains scores from the distance_matrix for each pairwise combination
held in the combos array
Arguments
----------
combos : numpy.ndarray
pairwise : numpy.ndarray
distance_matrix : numpy.ndarray
... | python | def mappable(combos, pairwise, distance_matrix):
'''
Obtains scores from the distance_matrix for each pairwise combination
held in the combos array
Arguments
----------
combos : numpy.ndarray
pairwise : numpy.ndarray
distance_matrix : numpy.ndarray
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SALib/SALib | src/SALib/sample/morris/brute.py | BruteForce.find_maximum | def find_maximum(self, scores, N, k_choices):
"""Finds the `k_choices` maximum scores from `scores`
Arguments
---------
scores : numpy.ndarray
N : int
k_choices : int
Returns
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list
"""
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"""Finds the `k_choices` maximum scores from `scores`
Arguments
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scores : numpy.ndarray
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k_choices : int
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SALib/SALib | src/SALib/sample/morris/brute.py | BruteForce.nth | def nth(iterable, n, default=None):
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Arguments
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iterable : iterable
n : int
default : default=None
The default value to return
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The default value to return
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SALib/SALib | src/SALib/sample/morris/__init__.py | sample | def sample(problem, N, num_levels=4, optimal_trajectories=None,
local_optimization=True):
"""Generate model inputs using the Method of Morris
Returns a NumPy matrix containing the model inputs required for Method of
Morris. The resulting matrix has :math:`(G+1)*T` rows and :math:`D`
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SALib/SALib | src/SALib/sample/morris/__init__.py | _sample_oat | def _sample_oat(problem, N, num_levels=4):
"""Generate trajectories without groups
Arguments
---------
problem : dict
The problem definition
N : int
The number of samples to generate
num_levels : int, default=4
The number of grid levels
"""
group_membership = np.... | python | def _sample_oat(problem, N, num_levels=4):
"""Generate trajectories without groups
Arguments
---------
problem : dict
The problem definition
N : int
The number of samples to generate
num_levels : int, default=4
The number of grid levels
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SALib/SALib | src/SALib/sample/morris/__init__.py | _sample_groups | def _sample_groups(problem, N, num_levels=4):
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---------
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SALib/SALib | src/SALib/sample/morris/__init__.py | generate_trajectory | def generate_trajectory(group_membership, num_levels=4):
"""Return a single trajectory
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where :math:`g` is the number of groups,
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... | python | def generate_trajectory(group_membership, num_levels=4):
"""Return a single trajectory
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SALib/SALib | src/SALib/sample/morris/__init__.py | generate_p_star | def generate_p_star(num_groups):
"""Describe the order in which groups move
Arguments
---------
num_groups : int
Returns
-------
np.ndarray
Matrix P* - size (g-by-g)
"""
p_star = np.eye(num_groups, num_groups)
rd.shuffle(p_star)
return p_star | python | def generate_p_star(num_groups):
"""Describe the order in which groups move
Arguments
---------
num_groups : int
Returns
-------
np.ndarray
Matrix P* - size (g-by-g)
"""
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SALib/SALib | src/SALib/scripts/salib.py | parse_subargs | def parse_subargs(module, parser, method, opts):
'''Attach argument parser for action specific options.
Arguments
---------
module : module
name of module to extract action from
parser : argparser
argparser object to attach additional arguments to
method : str
name of me... | python | def parse_subargs(module, parser, method, opts):
'''Attach argument parser for action specific options.
Arguments
---------
module : module
name of module to extract action from
parser : argparser
argparser object to attach additional arguments to
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SALib/SALib | src/SALib/sample/morris/local.py | LocalOptimisation.find_local_maximum | def find_local_maximum(self, input_sample, N, num_params,
k_choices, num_groups=None):
"""Find the most different trajectories in the input sample using a
local approach
An alternative by Ruano et al. (2012) for the brute force approach as
originally proposed ... | python | def find_local_maximum(self, input_sample, N, num_params,
k_choices, num_groups=None):
"""Find the most different trajectories in the input sample using a
local approach
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SALib/SALib | src/SALib/sample/morris/local.py | LocalOptimisation.sum_distances | def sum_distances(self, indices, distance_matrix):
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SALib/SALib | src/SALib/sample/morris/local.py | LocalOptimisation.get_max_sum_ind | def get_max_sum_ind(self, indices_list, distances, i, m):
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SALib/SALib | src/SALib/sample/morris/local.py | LocalOptimisation.add_indices | def add_indices(self, indices, distance_matrix):
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Arguments
---------
indices : tuple
distance_matrix : numpy.ndarray (M,M)
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[(1, 2, 3),... | python | def add_indices(self, indices, distance_matrix):
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SALib/SALib | src/SALib/util/results.py | ResultDict.to_df | def to_df(self):
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SALib/SALib | src/SALib/plotting/morris.py | horizontal_bar_plot | def horizontal_bar_plot(ax, Si, param_dict, sortby='mu_star', unit=''):
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'''
assert sortby in ['mu_star', 'mu_star_conf', 'sigma', 'mu']
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SALib/SALib | src/SALib/plotting/morris.py | sample_histograms | def sample_histograms(fig, input_sample, problem, param_dict):
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'''
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ou... | python | def sample_histograms(fig, input_sample, problem, param_dict):
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SALib/SALib | src/SALib/sample/ff.py | extend_bounds | def extend_bounds(problem):
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problem : dict
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SALib/SALib | src/SALib/sample/ff.py | generate_contrast | def generate_contrast(problem):
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problem : dict
The problem definition
"""
num_vars = problem['num_vars']
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k_chosen = 2 ** find... | python | def generate_contrast(problem):
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problem : dict
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SALib/SALib | src/SALib/sample/ff.py | sample | def sample(problem, seed=None):
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The resulting matrix has D columns, where D is smallest power of 2 that is
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SALib/SALib | src/SALib/sample/ff.py | cli_action | def cli_action(args):
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Parameters
----------
args : argparse namespace
"""
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param_values = sample(problem, seed=args.seed)
np.savetxt(args.output, param_values, delimiter=args.delimiter,
fmt='%.' + str(args.pr... | python | def cli_action(args):
"""Run sampling method
Parameters
----------
args : argparse namespace
"""
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SALib/SALib | src/SALib/sample/common_args.py | setup | def setup(parser):
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Parameters
----------
parser : argparse object
Returns
----------
Updated argparse object
"""
parser.add_argument(
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help='Parameter Range File')
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Parameters
----------
parser : argparse object
Returns
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Updated argparse object
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SALib/SALib | src/SALib/sample/common_args.py | run_cli | def run_cli(cli_parser, run_sample, known_args=None):
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cli_parser : function
Function to add method specific arguments to parser
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Method specific function that runs the sampling
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SALib/SALib | src/SALib/sample/morris/strategy.py | Strategy.run_checks | def run_checks(number_samples, k_choices):
"""Runs checks on `k_choices`
"""
assert isinstance(k_choices, int), \
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if k_choices < 2:
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SALib/SALib | src/SALib/sample/morris/strategy.py | Strategy._make_index_list | def _make_index_list(num_samples, num_params, num_groups=None):
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... | python | def _make_index_list(num_samples, num_params, num_groups=None):
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SALib/SALib | src/SALib/sample/morris/strategy.py | Strategy.compile_output | def compile_output(self, input_sample, num_samples, num_params,
maximum_combo, num_groups=None):
"""Picks the trajectories from the input
Arguments
---------
input_sample : numpy.ndarray
num_samples : int
num_params : int
maximum_combo : li... | python | def compile_output(self, input_sample, num_samples, num_params,
maximum_combo, num_groups=None):
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num_samples : int
num_params : int
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Checks input sample is:
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input_sample : numpy.ndarray
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SALib/SALib | src/SALib/sample/morris/strategy.py | Strategy.compute_distance | def compute_distance(m, l):
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'''
if np.shape(m) != np.shape(l):
raise ValueError("Input matrices are different sizes")
if np.array_equal(m, l):
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nicodv/kmodes | kmodes/kmodes.py | move_point_cat | def move_point_cat(point, ipoint, to_clust, from_clust, cl_attr_freq,
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"""Move point between clusters, categorical attributes."""
membship[to_clust, ipoint] = 1
membship[from_clust, ipoint] = 0
# Update frequencies of attributes in cluster.
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nicodv/kmodes | kmodes/kmodes.py | _labels_cost | def _labels_cost(X, centroids, dissim, membship=None):
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nicodv/kmodes | kmodes/kmodes.py | _k_modes_iter | def _k_modes_iter(X, centroids, cl_attr_freq, membship, dissim, random_state):
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... | python | def _k_modes_iter(X, centroids, cl_attr_freq, membship, dissim, random_state):
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moves = 0
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nicodv/kmodes | kmodes/kmodes.py | k_modes | def k_modes(X, n_clusters, max_iter, dissim, init, n_init, verbose, random_state, n_jobs):
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nicodv/kmodes | kmodes/kmodes.py | KModes.fit | def fit(self, X, y=None, **kwargs):
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X : array-like, shape=[n_samples, n_features]
"""
X = pandas_to_numpy(X)
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X : array-like, shape=[n_samples, n_features]
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nicodv/kmodes | kmodes/kmodes.py | KModes.fit_predict | def fit_predict(self, X, y=None, **kwargs):
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nicodv/kmodes | kmodes/util/__init__.py | get_max_value_key | def get_max_value_key(dic):
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nicodv/kmodes | kmodes/util/__init__.py | decode_centroids | def decode_centroids(encoded, mapping):
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nicodv/kmodes | kmodes/kprototypes.py | move_point_num | def move_point_num(point, to_clust, from_clust, cl_attr_sum, cl_memb_sum):
"""Move point between clusters, numerical attributes."""
# Update sum of attributes in cluster.
for iattr, curattr in enumerate(point):
cl_attr_sum[to_clust][iattr] += curattr
cl_attr_sum[from_clust][iattr] -= curattr... | python | def move_point_num(point, to_clust, from_clust, cl_attr_sum, cl_memb_sum):
"""Move point between clusters, numerical attributes."""
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nicodv/kmodes | kmodes/kprototypes.py | _split_num_cat | def _split_num_cat(X, categorical):
"""Extract numerical and categorical columns.
Convert to numpy arrays, if needed.
:param X: Feature matrix
:param categorical: Indices of categorical columns
"""
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"""Extract numerical and categorical columns.
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nicodv/kmodes | kmodes/kprototypes.py | _labels_cost | def _labels_cost(Xnum, Xcat, centroids, num_dissim, cat_dissim, gamma, membship=None):
"""Calculate labels and cost function given a matrix of points and
a list of centroids for the k-prototypes algorithm.
"""
n_points = Xnum.shape[0]
Xnum = check_array(Xnum)
cost = 0.
labels = np.empty(n_... | python | def _labels_cost(Xnum, Xcat, centroids, num_dissim, cat_dissim, gamma, membship=None):
"""Calculate labels and cost function given a matrix of points and
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nicodv/kmodes | kmodes/kprototypes.py | _k_prototypes_iter | def _k_prototypes_iter(Xnum, Xcat, centroids, cl_attr_sum, cl_memb_sum, cl_attr_freq,
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nicodv/kmodes | kmodes/kprototypes.py | k_prototypes | def k_prototypes(X, categorical, n_clusters, max_iter, num_dissim, cat_dissim,
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categorical : Index of columns that contain categorical data
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nicodv/kmodes | kmodes/util/dissim.py | euclidean_dissim | def euclidean_dissim(a, b, **_):
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nicodv/kmodes | kmodes/util/dissim.py | ng_dissim | def ng_dissim(a, b, X=None, membship=None):
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Bogdanp/dramatiq | dramatiq/message.py | Message.copy | def copy(self, **attributes):
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Bogdanp/dramatiq | dramatiq/common.py | compute_backoff | def compute_backoff(attempts, *, factor=5, jitter=True, max_backoff=2000, max_exponent=32):
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Parameters:
attempts(int): The number of attempts there have been so far.
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Bogdanp/dramatiq | dramatiq/common.py | join_all | def join_all(joinables, timeout):
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Parameters:
joinables(object): Objects with a join method.
timeout(int): The total timeout in milliseconds.
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Bogdanp/dramatiq | dramatiq/common.py | dq_name | def dq_name(queue_name):
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Bogdanp/dramatiq | dramatiq/common.py | xq_name | def xq_name(queue_name):
"""Returns the dead letter queue name for a given queue. If the
given queue name belongs to a delayed queue, the dead letter queue
name for the original queue is generated.
"""
if queue_name.endswith(".XQ"):
return queue_name
if queue_name.endswith(".DQ"):
... | python | def xq_name(queue_name):
"""Returns the dead letter queue name for a given queue. If the
given queue name belongs to a delayed queue, the dead letter queue
name for the original queue is generated.
"""
if queue_name.endswith(".XQ"):
return queue_name
if queue_name.endswith(".DQ"):
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Bogdanp/dramatiq | dramatiq/broker.py | get_broker | def get_broker() -> "Broker":
"""Get the global broker instance. If no global broker is set,
this initializes a RabbitmqBroker and returns it.
Returns:
Broker: The default Broker.
"""
global global_broker
if global_broker is None:
from .brokers.rabbitmq import RabbitmqBroker
... | python | def get_broker() -> "Broker":
"""Get the global broker instance. If no global broker is set,
this initializes a RabbitmqBroker and returns it.
Returns:
Broker: The default Broker.
"""
global global_broker
if global_broker is None:
from .brokers.rabbitmq import RabbitmqBroker
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Bogdanp/dramatiq | dramatiq/broker.py | Broker.add_middleware | def add_middleware(self, middleware, *, before=None, after=None):
"""Add a middleware object to this broker. The middleware is
appended to the end of the middleware list by default.
You can specify another middleware (by class) as a reference
point for where the new middleware should b... | python | def add_middleware(self, middleware, *, before=None, after=None):
"""Add a middleware object to this broker. The middleware is
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Bogdanp/dramatiq | dramatiq/broker.py | Broker.declare_actor | def declare_actor(self, actor): # pragma: no cover
"""Declare a new actor on this broker. Declaring an Actor
twice replaces the first actor with the second by name.
Parameters:
actor(Actor): The actor being declared.
"""
self.emit_before("declare_actor", actor)
... | python | def declare_actor(self, actor): # pragma: no cover
"""Declare a new actor on this broker. Declaring an Actor
twice replaces the first actor with the second by name.
Parameters:
actor(Actor): The actor being declared.
"""
self.emit_before("declare_actor", actor)
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Bogdanp/dramatiq | dramatiq/brokers/rabbitmq.py | URLRabbitmqBroker | def URLRabbitmqBroker(url, *, middleware=None):
"""Alias for the RabbitMQ broker that takes a connection URL as a
positional argument.
Parameters:
url(str): A connection string.
middleware(list[Middleware]): The middleware to add to this
broker.
"""
warnings.warn(
"Use R... | python | def URLRabbitmqBroker(url, *, middleware=None):
"""Alias for the RabbitMQ broker that takes a connection URL as a
positional argument.
Parameters:
url(str): A connection string.
middleware(list[Middleware]): The middleware to add to this
broker.
"""
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Bogdanp/dramatiq | dramatiq/brokers/rabbitmq.py | RabbitmqBroker.close | def close(self):
"""Close all open RabbitMQ connections.
"""
# The main thread may keep connections open for a long time
# w/o publishing heartbeats, which means that they'll end up
# being closed by the time the broker is closed. When that
# happens, pika logs a bunch o... | python | def close(self):
"""Close all open RabbitMQ connections.
"""
# The main thread may keep connections open for a long time
# w/o publishing heartbeats, which means that they'll end up
# being closed by the time the broker is closed. When that
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Bogdanp/dramatiq | dramatiq/brokers/rabbitmq.py | RabbitmqBroker.declare_queue | def declare_queue(self, queue_name):
"""Declare a queue. Has no effect if a queue with the given
name already exists.
Parameters:
queue_name(str): The name of the new queue.
Raises:
ConnectionClosed: If the underlying channel or connection
has been clos... | python | def declare_queue(self, queue_name):
"""Declare a queue. Has no effect if a queue with the given
name already exists.
Parameters:
queue_name(str): The name of the new queue.
Raises:
ConnectionClosed: If the underlying channel or connection
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Bogdanp/dramatiq | dramatiq/brokers/rabbitmq.py | RabbitmqBroker.get_queue_message_counts | def get_queue_message_counts(self, queue_name):
"""Get the number of messages in a queue. This method is only
meant to be used in unit and integration tests.
Parameters:
queue_name(str): The queue whose message counts to get.
Returns:
tuple: A triple representing t... | python | def get_queue_message_counts(self, queue_name):
"""Get the number of messages in a queue. This method is only
meant to be used in unit and integration tests.
Parameters:
queue_name(str): The queue whose message counts to get.
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tuple: A triple representing t... | [
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Bogdanp/dramatiq | dramatiq/rate_limits/barrier.py | Barrier.create | def create(self, parties):
"""Create the barrier for the given number of parties.
Parameters:
parties(int): The number of parties to wait for.
Returns:
bool: Whether or not the new barrier was successfully created.
"""
assert parties > 0, "parties must be a ... | python | def create(self, parties):
"""Create the barrier for the given number of parties.
Parameters:
parties(int): The number of parties to wait for.
Returns:
bool: Whether or not the new barrier was successfully created.
"""
assert parties > 0, "parties must be a ... | [
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Bogdanp/dramatiq | dramatiq/rate_limits/barrier.py | Barrier.wait | def wait(self, *, block=True, timeout=None):
"""Signal that a party has reached the barrier.
Warning:
Barrier blocking is currently only supported by the stub and
Redis backends.
Warning:
Re-using keys between blocking calls may lead to undefined
behavio... | python | def wait(self, *, block=True, timeout=None):
"""Signal that a party has reached the barrier.
Warning:
Barrier blocking is currently only supported by the stub and
Redis backends.
Warning:
Re-using keys between blocking calls may lead to undefined
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Bogdanp/dramatiq | dramatiq/middleware/threading.py | raise_thread_exception | def raise_thread_exception(thread_id, exception):
"""Raise an exception in a thread.
Currently, this is only available on CPython.
Note:
This works by setting an async exception in the thread. This means
that the exception will only get called the next time that thread
acquires the GIL.... | python | def raise_thread_exception(thread_id, exception):
"""Raise an exception in a thread.
Currently, this is only available on CPython.
Note:
This works by setting an async exception in the thread. This means
that the exception will only get called the next time that thread
acquires the GIL.... | [
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