id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 75 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
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42,200 | haaksmash/pyutils | utils/dicts/helpers.py | from_keyed_iterable | def from_keyed_iterable(iterable, key, filter_func=None):
"""Construct a dictionary out of an iterable, using an attribute name as
the key. Optionally provide a filter function, to determine what should be
kept in the dictionary."""
generated = {}
for element in iterable:
try:
... | python | def from_keyed_iterable(iterable, key, filter_func=None):
"""Construct a dictionary out of an iterable, using an attribute name as
the key. Optionally provide a filter function, to determine what should be
kept in the dictionary."""
generated = {}
for element in iterable:
try:
... | [
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42,201 | haaksmash/pyutils | utils/dicts/helpers.py | subtract_by_key | def subtract_by_key(dict_a, dict_b):
"""given two dicts, a and b, this function returns c = a - b, where
a - b is defined as the key difference between a and b.
e.g.,
{1:None, 2:3, 3:"yellow", 4:True} - {2:4, 1:"green"} =
{3:"yellow", 4:True}
"""
difference_dict = {}
for key in dic... | python | def subtract_by_key(dict_a, dict_b):
"""given two dicts, a and b, this function returns c = a - b, where
a - b is defined as the key difference between a and b.
e.g.,
{1:None, 2:3, 3:"yellow", 4:True} - {2:4, 1:"green"} =
{3:"yellow", 4:True}
"""
difference_dict = {}
for key in dic... | [
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42,202 | haaksmash/pyutils | utils/dicts/helpers.py | winnow_by_keys | def winnow_by_keys(dct, keys=None, filter_func=None):
"""separates a dict into has-keys and not-has-keys pairs, using either
a list of keys or a filtering function."""
has = {}
has_not = {}
for key in dct:
key_passes_check = False
if keys is not None:
key_passes_check = ... | python | def winnow_by_keys(dct, keys=None, filter_func=None):
"""separates a dict into has-keys and not-has-keys pairs, using either
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has = {}
has_not = {}
for key in dct:
key_passes_check = False
if keys is not None:
key_passes_check = ... | [
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42,203 | haaksmash/pyutils | utils/lists.py | flat_map | def flat_map(iterable, func):
"""func must take an item and return an interable that contains that
item. this is flatmap in the classic mode"""
results = []
for element in iterable:
result = func(element)
if len(result) > 0:
results.extend(result)
return results | python | def flat_map(iterable, func):
"""func must take an item and return an interable that contains that
item. this is flatmap in the classic mode"""
results = []
for element in iterable:
result = func(element)
if len(result) > 0:
results.extend(result)
return results | [
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42,204 | haaksmash/pyutils | utils/math.py | product | def product(sequence, initial=1):
"""like the built-in sum, but for multiplication."""
if not isinstance(sequence, collections.Iterable):
raise TypeError("'{}' object is not iterable".format(type(sequence).__name__))
return reduce(operator.mul, sequence, initial) | python | def product(sequence, initial=1):
"""like the built-in sum, but for multiplication."""
if not isinstance(sequence, collections.Iterable):
raise TypeError("'{}' object is not iterable".format(type(sequence).__name__))
return reduce(operator.mul, sequence, initial) | [
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42,205 | haaksmash/pyutils | utils/dates.py | date_from_string | def date_from_string(string, format_string=None):
"""Runs through a few common string formats for datetimes,
and attempts to coerce them into a datetime. Alternatively,
format_string can provide either a single string to attempt
or an iterable of strings to attempt."""
if isinstance(format_string, ... | python | def date_from_string(string, format_string=None):
"""Runs through a few common string formats for datetimes,
and attempts to coerce them into a datetime. Alternatively,
format_string can provide either a single string to attempt
or an iterable of strings to attempt."""
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42,206 | haaksmash/pyutils | utils/dates.py | to_datetime | def to_datetime(plain_date, hours=0, minutes=0, seconds=0, ms=0):
"""given a datetime.date, gives back a datetime.datetime"""
# don't mess with datetimes
if isinstance(plain_date, datetime.datetime):
return plain_date
return datetime.datetime(
plain_date.year,
plain_date.month,
... | python | def to_datetime(plain_date, hours=0, minutes=0, seconds=0, ms=0):
"""given a datetime.date, gives back a datetime.datetime"""
# don't mess with datetimes
if isinstance(plain_date, datetime.datetime):
return plain_date
return datetime.datetime(
plain_date.year,
plain_date.month,
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42,207 | haaksmash/pyutils | utils/dates.py | TimePeriod.get_containing_period | def get_containing_period(cls, *periods):
"""Given a bunch of TimePeriods, return a TimePeriod that most closely
contains them."""
if any(not isinstance(period, TimePeriod) for period in periods):
raise TypeError("periods must all be TimePeriods: {}".format(periods))
latest... | python | def get_containing_period(cls, *periods):
"""Given a bunch of TimePeriods, return a TimePeriod that most closely
contains them."""
if any(not isinstance(period, TimePeriod) for period in periods):
raise TypeError("periods must all be TimePeriods: {}".format(periods))
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42,208 | major/supernova | supernova/credentials.py | get_user_password | def get_user_password(env, param, force=False):
"""
Allows the user to print the credential for a particular keyring entry
to the screen
"""
username = utils.assemble_username(env, param)
if not utils.confirm_credential_display(force):
return
# Retrieve the credential from the keyc... | python | def get_user_password(env, param, force=False):
"""
Allows the user to print the credential for a particular keyring entry
to the screen
"""
username = utils.assemble_username(env, param)
if not utils.confirm_credential_display(force):
return
# Retrieve the credential from the keyc... | [
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42,209 | major/supernova | supernova/credentials.py | password_get | def password_get(username=None):
"""
Retrieves a password from the keychain based on the environment and
configuration parameter pair.
If this fails, None is returned.
"""
password = keyring.get_password('supernova', username)
if password is None:
split_username = tuple(username.spl... | python | def password_get(username=None):
"""
Retrieves a password from the keychain based on the environment and
configuration parameter pair.
If this fails, None is returned.
"""
password = keyring.get_password('supernova', username)
if password is None:
split_username = tuple(username.spl... | [
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42,210 | major/supernova | supernova/credentials.py | set_user_password | def set_user_password(environment, parameter, password):
"""
Sets a user's password in the keyring storage
"""
username = '%s:%s' % (environment, parameter)
return password_set(username, password) | python | def set_user_password(environment, parameter, password):
"""
Sets a user's password in the keyring storage
"""
username = '%s:%s' % (environment, parameter)
return password_set(username, password) | [
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42,211 | major/supernova | supernova/credentials.py | password_set | def password_set(username=None, password=None):
"""
Stores a password in a keychain for a particular environment and
configuration parameter pair.
"""
result = keyring.set_password('supernova', username, password)
# NOTE: keyring returns None when the storage is successful. That's weird.
i... | python | def password_set(username=None, password=None):
"""
Stores a password in a keychain for a particular environment and
configuration parameter pair.
"""
result = keyring.set_password('supernova', username, password)
# NOTE: keyring returns None when the storage is successful. That's weird.
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42,212 | major/supernova | supernova/credentials.py | prep_shell_environment | def prep_shell_environment(nova_env, nova_creds):
"""
Appends new variables to the current shell environment temporarily.
"""
new_env = {}
for key, value in prep_nova_creds(nova_env, nova_creds):
if type(value) == six.binary_type:
value = value.decode()
new_env[key] = va... | python | def prep_shell_environment(nova_env, nova_creds):
"""
Appends new variables to the current shell environment temporarily.
"""
new_env = {}
for key, value in prep_nova_creds(nova_env, nova_creds):
if type(value) == six.binary_type:
value = value.decode()
new_env[key] = va... | [
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42,213 | major/supernova | supernova/credentials.py | prep_nova_creds | def prep_nova_creds(nova_env, nova_creds):
"""
Finds relevant config options in the supernova config and cleans them
up for novaclient.
"""
try:
raw_creds = dict(nova_creds.get('DEFAULT', {}), **nova_creds[nova_env])
except KeyError:
msg = "{0} was not found in your supernova con... | python | def prep_nova_creds(nova_env, nova_creds):
"""
Finds relevant config options in the supernova config and cleans them
up for novaclient.
"""
try:
raw_creds = dict(nova_creds.get('DEFAULT', {}), **nova_creds[nova_env])
except KeyError:
msg = "{0} was not found in your supernova con... | [
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42,214 | major/supernova | supernova/config.py | load_config | def load_config(config_file_override=False):
"""
Pulls the supernova configuration file and reads it
"""
supernova_config = get_config_file(config_file_override)
supernova_config_dir = get_config_directory(config_file_override)
if not supernova_config and not supernova_config_dir:
raise... | python | def load_config(config_file_override=False):
"""
Pulls the supernova configuration file and reads it
"""
supernova_config = get_config_file(config_file_override)
supernova_config_dir = get_config_directory(config_file_override)
if not supernova_config and not supernova_config_dir:
raise... | [
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42,215 | major/supernova | supernova/config.py | get_config_file | def get_config_file(override_files=False):
"""
Looks for the most specific configuration file available. An override
can be provided as a string if needed.
"""
if override_files:
if isinstance(override_files, six.string_types):
possible_configs = [override_files]
else:
... | python | def get_config_file(override_files=False):
"""
Looks for the most specific configuration file available. An override
can be provided as a string if needed.
"""
if override_files:
if isinstance(override_files, six.string_types):
possible_configs = [override_files]
else:
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42,216 | major/supernova | supernova/config.py | get_config_directory | def get_config_directory(override_files=False):
"""
Looks for the most specific configuration directory possible, in order to
load individual configuration files.
"""
if override_files:
possible_dirs = [override_files]
else:
xdg_config_home = os.environ.get('XDG_CONFIG_HOME') or... | python | def get_config_directory(override_files=False):
"""
Looks for the most specific configuration directory possible, in order to
load individual configuration files.
"""
if override_files:
possible_dirs = [override_files]
else:
xdg_config_home = os.environ.get('XDG_CONFIG_HOME') or... | [
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42,217 | major/supernova | supernova/supernova.py | execute_executable | def execute_executable(nova_args, env_vars):
"""
Executes the executable given by the user.
Hey, I know this method has a silly name, but I write the code here and
I'm silly.
"""
process = subprocess.Popen(nova_args,
stdout=sys.stdout,
... | python | def execute_executable(nova_args, env_vars):
"""
Executes the executable given by the user.
Hey, I know this method has a silly name, but I write the code here and
I'm silly.
"""
process = subprocess.Popen(nova_args,
stdout=sys.stdout,
... | [
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42,218 | major/supernova | supernova/supernova.py | check_for_debug | def check_for_debug(supernova_args, nova_args):
"""
If the user wanted to run the executable with debugging enabled, we need
to apply the correct arguments to the executable.
Heat is a corner case since it uses -d instead of --debug.
"""
# Heat requires special handling for debug arguments
... | python | def check_for_debug(supernova_args, nova_args):
"""
If the user wanted to run the executable with debugging enabled, we need
to apply the correct arguments to the executable.
Heat is a corner case since it uses -d instead of --debug.
"""
# Heat requires special handling for debug arguments
... | [
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42,219 | major/supernova | supernova/supernova.py | check_for_executable | def check_for_executable(supernova_args, env_vars):
"""
It's possible that a user might set their custom executable via an
environment variable. If we detect one, we should add it to supernova's
arguments ONLY IF an executable wasn't set on the command line. The
command line executable must take p... | python | def check_for_executable(supernova_args, env_vars):
"""
It's possible that a user might set their custom executable via an
environment variable. If we detect one, we should add it to supernova's
arguments ONLY IF an executable wasn't set on the command line. The
command line executable must take p... | [
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42,220 | major/supernova | supernova/supernova.py | check_for_bypass_url | def check_for_bypass_url(raw_creds, nova_args):
"""
Return a list of extra args that need to be passed on cmdline to nova.
"""
if 'BYPASS_URL' in raw_creds.keys():
bypass_args = ['--bypass-url', raw_creds['BYPASS_URL']]
nova_args = bypass_args + nova_args
return nova_args | python | def check_for_bypass_url(raw_creds, nova_args):
"""
Return a list of extra args that need to be passed on cmdline to nova.
"""
if 'BYPASS_URL' in raw_creds.keys():
bypass_args = ['--bypass-url', raw_creds['BYPASS_URL']]
nova_args = bypass_args + nova_args
return nova_args | [
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42,221 | major/supernova | supernova/supernova.py | run_command | def run_command(nova_creds, nova_args, supernova_args):
"""
Sets the environment variables for the executable, runs the executable,
and handles the output.
"""
nova_env = supernova_args['nova_env']
# (gtmanfred) make a copy of this object. If we don't copy it, the insert
# to 0 happens mult... | python | def run_command(nova_creds, nova_args, supernova_args):
"""
Sets the environment variables for the executable, runs the executable,
and handles the output.
"""
nova_env = supernova_args['nova_env']
# (gtmanfred) make a copy of this object. If we don't copy it, the insert
# to 0 happens mult... | [
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42,222 | major/supernova | supernova/utils.py | check_environment_presets | def check_environment_presets():
"""
Checks for environment variables that can cause problems with supernova
"""
presets = [x for x in os.environ.copy().keys() if x.startswith('NOVA_') or
x.startswith('OS_')]
if len(presets) < 1:
return True
else:
click.echo("_" * ... | python | def check_environment_presets():
"""
Checks for environment variables that can cause problems with supernova
"""
presets = [x for x in os.environ.copy().keys() if x.startswith('NOVA_') or
x.startswith('OS_')]
if len(presets) < 1:
return True
else:
click.echo("_" * ... | [
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42,223 | major/supernova | supernova/utils.py | get_envs_in_group | def get_envs_in_group(group_name, nova_creds):
"""
Takes a group_name and finds any environments that have a SUPERNOVA_GROUP
configuration line that matches the group_name.
"""
envs = []
for key, value in nova_creds.items():
supernova_groups = value.get('SUPERNOVA_GROUP', [])
if ... | python | def get_envs_in_group(group_name, nova_creds):
"""
Takes a group_name and finds any environments that have a SUPERNOVA_GROUP
configuration line that matches the group_name.
"""
envs = []
for key, value in nova_creds.items():
supernova_groups = value.get('SUPERNOVA_GROUP', [])
if ... | [
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42,224 | major/supernova | supernova/utils.py | is_valid_group | def is_valid_group(group_name, nova_creds):
"""
Checks to see if the configuration file contains a SUPERNOVA_GROUP
configuration option.
"""
valid_groups = []
for key, value in nova_creds.items():
supernova_groups = value.get('SUPERNOVA_GROUP', [])
if hasattr(supernova_groups, 's... | python | def is_valid_group(group_name, nova_creds):
"""
Checks to see if the configuration file contains a SUPERNOVA_GROUP
configuration option.
"""
valid_groups = []
for key, value in nova_creds.items():
supernova_groups = value.get('SUPERNOVA_GROUP', [])
if hasattr(supernova_groups, 's... | [
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42,225 | major/supernova | supernova/utils.py | rm_prefix | def rm_prefix(name):
"""
Removes nova_ os_ novaclient_ prefix from string.
"""
if name.startswith('nova_'):
return name[5:]
elif name.startswith('novaclient_'):
return name[11:]
elif name.startswith('os_'):
return name[3:]
else:
return name | python | def rm_prefix(name):
"""
Removes nova_ os_ novaclient_ prefix from string.
"""
if name.startswith('nova_'):
return name[5:]
elif name.startswith('novaclient_'):
return name[11:]
elif name.startswith('os_'):
return name[3:]
else:
return name | [
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42,226 | corydolphin/flask-jsonpify | flask_jsonpify.py | __pad | def __pad(strdata):
""" Pads `strdata` with a Request's callback argument, if specified, or does
nothing.
"""
if request.args.get('callback'):
return "%s(%s);" % (request.args.get('callback'), strdata)
else:
return strdata | python | def __pad(strdata):
""" Pads `strdata` with a Request's callback argument, if specified, or does
nothing.
"""
if request.args.get('callback'):
return "%s(%s);" % (request.args.get('callback'), strdata)
else:
return strdata | [
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42,227 | corydolphin/flask-jsonpify | flask_jsonpify.py | __dumps | def __dumps(*args, **kwargs):
""" Serializes `args` and `kwargs` as JSON. Supports serializing an array
as the top-level object, if it is the only argument.
"""
indent = None
if (current_app.config.get('JSONIFY_PRETTYPRINT_REGULAR', False) and
not request.is_xhr):
indent =... | python | def __dumps(*args, **kwargs):
""" Serializes `args` and `kwargs` as JSON. Supports serializing an array
as the top-level object, if it is the only argument.
"""
indent = None
if (current_app.config.get('JSONIFY_PRETTYPRINT_REGULAR', False) and
not request.is_xhr):
indent =... | [
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42,228 | frejanordsiek/hdf5storage | hdf5storage/Marshallers.py | TypeMarshaller.update_type_lookups | def update_type_lookups(self):
""" Update type and typestring lookup dicts.
Must be called once the ``types`` and ``python_type_strings``
attributes are set so that ``type_to_typestring`` and
``typestring_to_type`` are constructed.
.. versionadded:: 0.2
Notes
-... | python | def update_type_lookups(self):
""" Update type and typestring lookup dicts.
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42,229 | frejanordsiek/hdf5storage | hdf5storage/Marshallers.py | TypeMarshaller.get_type_string | def get_type_string(self, data, type_string):
""" Gets type string.
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42,230 | frejanordsiek/hdf5storage | hdf5storage/Marshallers.py | TypeMarshaller.write | def write(self, f, grp, name, data, type_string, options):
""" Writes an object's metadata to file.
Writes the Python object 'data' to 'name' in h5py.Group 'grp'.
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Arguements changed.
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42,231 | frejanordsiek/hdf5storage | hdf5storage/Marshallers.py | TypeMarshaller.write_metadata | def write_metadata(self, f, dsetgrp, data, type_string, options,
attributes=None):
""" Writes an object to file.
Writes the metadata for a Python object `data` to file at `name`
in h5py.Group `grp`. Metadata is written to HDF5
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attributes=None):
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42,232 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | process_path | def process_path(pth):
""" Processes paths.
Processes the provided path and breaks it into it Group part
(`groupname`) and target part (`targetname`). ``bytes`` paths are
converted to ``str``. Separated paths are given as an iterable of
``str`` and ``bytes``. Each part of a separated path is escape... | python | def process_path(pth):
""" Processes paths.
Processes the provided path and breaks it into it Group part
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42,233 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | write_object_array | def write_object_array(f, data, options):
""" Writes an array of objects recursively.
Writes the elements of the given object array recursively in the
HDF5 Group ``options.group_for_references`` and returns an
``h5py.Reference`` array to all the elements.
Parameters
----------
f : h5py.Fil... | python | def write_object_array(f, data, options):
""" Writes an array of objects recursively.
Writes the elements of the given object array recursively in the
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42,234 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | read_object_array | def read_object_array(f, data, options):
""" Reads an array of objects recursively.
Read the elements of the given HDF5 Reference array recursively
in the and constructs a ``numpy.object_`` array from its elements,
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f : h5py.File
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""" Reads an array of objects recursively.
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42,235 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | next_unused_name_in_group | def next_unused_name_in_group(grp, length):
""" Gives a name that isn't used in a Group.
Generates a name of the desired length that is not a Dataset or
Group in the given group. Note, if length is not large enough and
`grp` is full enough, there may be no available names meaning that
this function... | python | def next_unused_name_in_group(grp, length):
""" Gives a name that isn't used in a Group.
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42,236 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | convert_numpy_str_to_uint16 | def convert_numpy_str_to_uint16(data):
""" Converts a numpy.unicode\_ to UTF-16 in numpy.uint16 form.
Convert a ``numpy.unicode_`` or an array of them (they are UTF-32
strings) to UTF-16 in the equivalent array of ``numpy.uint16``. The
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... | python | def convert_numpy_str_to_uint16(data):
""" Converts a numpy.unicode\_ to UTF-16 in numpy.uint16 form.
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42,237 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | convert_numpy_str_to_uint32 | def convert_numpy_str_to_uint32(data):
""" Converts a numpy.unicode\_ to its numpy.uint32 representation.
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42,238 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | decode_complex | def decode_complex(data, complex_names=(None, None)):
""" Decodes possibly complex data read from an HDF5 file.
Decodes possibly complex datasets read from an HDF5 file. HDF5
doesn't have a native complex type, so they are stored as
H5T_COMPOUND types with fields such as 'r' and 'i' for the real and
... | python | def decode_complex(data, complex_names=(None, None)):
""" Decodes possibly complex data read from an HDF5 file.
Decodes possibly complex datasets read from an HDF5 file. HDF5
doesn't have a native complex type, so they are stored as
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42,239 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | encode_complex | def encode_complex(data, complex_names):
""" Encodes complex data to having arbitrary complex field names.
Encodes complex `data` to have the real and imaginary field names
given in `complex_numbers`. This is needed because the field names
have to be set so that it can be written to an HDF5 file with t... | python | def encode_complex(data, complex_names):
""" Encodes complex data to having arbitrary complex field names.
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42,240 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | convert_attribute_to_string | def convert_attribute_to_string(value):
""" Convert an attribute value to a string.
Converts the attribute value to a string if possible (get ``None``
if isn't a string type).
.. versionadded:: 0.2
Parameters
----------
value :
The Attribute value.
Returns
-------
s :... | python | def convert_attribute_to_string(value):
""" Convert an attribute value to a string.
Converts the attribute value to a string if possible (get ``None``
if isn't a string type).
.. versionadded:: 0.2
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42,241 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | set_attribute | def set_attribute(target, name, value):
""" Sets an attribute on a Dataset or Group.
If the attribute `name` doesn't exist yet, it is created. If it
already exists, it is overwritten if it differs from `value`.
Notes
-----
``set_attributes_all`` is the fastest way to set and delete
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""" Sets an attribute on a Dataset or Group.
If the attribute `name` doesn't exist yet, it is created. If it
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42,242 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | set_attribute_string | def set_attribute_string(target, name, value):
""" Sets an attribute to a string on a Dataset or Group.
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already exists, it is overwritten if it differs from `value`.
Notes
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42,243 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | set_attribute_string_array | def set_attribute_string_array(target, name, string_list):
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42,244 | frejanordsiek/hdf5storage | hdf5storage/utilities.py | set_attributes_all | def set_attributes_all(target, attributes, discard_others=True):
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42,245 | frejanordsiek/hdf5storage | hdf5storage/__init__.py | find_thirdparty_marshaller_plugins | def find_thirdparty_marshaller_plugins():
""" Find, but don't load, all third party marshaller plugins.
Third party marshaller plugins declare the entry point
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""" Find, but don't load, all third party marshaller plugins.
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42,246 | frejanordsiek/hdf5storage | hdf5storage/__init__.py | savemat | def savemat(file_name, mdict, appendmat=True, format='7.3',
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action_for_matlab_incompatible='error',
marshaller_collection=None, truncate_existing=False,
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""" Save a dictionary of pyt... | python | def savemat(file_name, mdict, appendmat=True, format='7.3',
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42,247 | frejanordsiek/hdf5storage | hdf5storage/__init__.py | loadmat | def loadmat(file_name, mdict=None, appendmat=True,
variable_names=None,
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""" Loads data to a MATLAB MAT file.
Reads data from the specified variables (or all) in a MATLAB MAT
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42,248 | frejanordsiek/hdf5storage | hdf5storage/__init__.py | MarshallerCollection._update_marshallers | def _update_marshallers(self):
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42,249 | frejanordsiek/hdf5storage | hdf5storage/__init__.py | MarshallerCollection._import_marshaller_modules | def _import_marshaller_modules(self, m):
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42,250 | frejanordsiek/hdf5storage | hdf5storage/__init__.py | MarshallerCollection.get_marshaller_for_type | def get_marshaller_for_type(self, tp):
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42,251 | frejanordsiek/hdf5storage | hdf5storage/__init__.py | MarshallerCollection.get_marshaller_for_type_string | def get_marshaller_for_type_string(self, type_string):
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42,252 | frejanordsiek/hdf5storage | hdf5storage/__init__.py | MarshallerCollection.get_marshaller_for_matlab_class | def get_marshaller_for_matlab_class(self, matlab_class):
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""" Gets the appropriate marshaller for a MATLAB class string.
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42,253 | jciskey/pygraph | pygraph/classes/directed_graph.py | DirectedGraph.new_node | def new_node(self):
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"""Adds a new, blank node to the graph.
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node = {'id': node_id,
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42,255 | jciskey/pygraph | pygraph/classes/directed_graph.py | DirectedGraph.adjacent | def adjacent(self, node_a, node_b):
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42,256 | jciskey/pygraph | pygraph/classes/directed_graph.py | DirectedGraph.edge_cost | def edge_cost(self, node_a, node_b):
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"""Returns the cost of moving between the edge that connects node_a to node_b.
Returns +inf if no such edge exists."""
cost = float('inf')
node_object_a = self.get_node(node_a)
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42,257 | jciskey/pygraph | pygraph/classes/directed_graph.py | DirectedGraph.get_node | def get_node(self, node_id):
"""Returns the node object identified by "node_id"."""
try:
node_object = self.nodes[node_id]
except KeyError:
raise NonexistentNodeError(node_id)
return node_object | python | def get_node(self, node_id):
"""Returns the node object identified by "node_id"."""
try:
node_object = self.nodes[node_id]
except KeyError:
raise NonexistentNodeError(node_id)
return node_object | [
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42,258 | jciskey/pygraph | pygraph/classes/directed_graph.py | DirectedGraph.get_edge | def get_edge(self, edge_id):
"""Returns the edge object identified by "edge_id"."""
try:
edge_object = self.edges[edge_id]
except KeyError:
raise NonexistentEdgeError(edge_id)
return edge_object | python | def get_edge(self, edge_id):
"""Returns the edge object identified by "edge_id"."""
try:
edge_object = self.edges[edge_id]
except KeyError:
raise NonexistentEdgeError(edge_id)
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42,259 | jciskey/pygraph | pygraph/classes/directed_graph.py | DirectedGraph.delete_edge_by_nodes | def delete_edge_by_nodes(self, node_a, node_b):
"""Removes all the edges from node_a to node_b from the graph."""
node = self.get_node(node_a)
# Determine the edge ids
edge_ids = []
for e_id in node['edges']:
edge = self.get_edge(e_id)
if edge['vertices']... | python | def delete_edge_by_nodes(self, node_a, node_b):
"""Removes all the edges from node_a to node_b from the graph."""
node = self.get_node(node_a)
# Determine the edge ids
edge_ids = []
for e_id in node['edges']:
edge = self.get_edge(e_id)
if edge['vertices']... | [
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42,260 | jciskey/pygraph | pygraph/classes/directed_graph.py | DirectedGraph.delete_node | def delete_node(self, node_id):
"""Removes the node identified by node_id from the graph."""
node = self.get_node(node_id)
# Remove all edges from the node
for e in node['edges']:
self.delete_edge_by_id(e)
# Remove all edges to the node
edges = [edge_id for ... | python | def delete_node(self, node_id):
"""Removes the node identified by node_id from the graph."""
node = self.get_node(node_id)
# Remove all edges from the node
for e in node['edges']:
self.delete_edge_by_id(e)
# Remove all edges to the node
edges = [edge_id for ... | [
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42,261 | jciskey/pygraph | pygraph/classes/directed_graph.py | DirectedGraph.move_edge_source | def move_edge_source(self, edge_id, node_a, node_b):
"""Moves an edge originating from node_a so that it originates from node_b."""
# Grab the edge
edge = self.get_edge(edge_id)
# Alter the vertices
edge['vertices'] = (node_b, edge['vertices'][1])
# Remove the edge from... | python | def move_edge_source(self, edge_id, node_a, node_b):
"""Moves an edge originating from node_a so that it originates from node_b."""
# Grab the edge
edge = self.get_edge(edge_id)
# Alter the vertices
edge['vertices'] = (node_b, edge['vertices'][1])
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42,262 | jciskey/pygraph | pygraph/classes/directed_graph.py | DirectedGraph.get_edge_ids_by_node_ids | def get_edge_ids_by_node_ids(self, node_a, node_b):
"""Returns a list of edge ids connecting node_a to node_b."""
# Check if the nodes are adjacent
if not self.adjacent(node_a, node_b):
return []
# They're adjacent, so pull the list of edges from node_a and determine which o... | python | def get_edge_ids_by_node_ids(self, node_a, node_b):
"""Returns a list of edge ids connecting node_a to node_b."""
# Check if the nodes are adjacent
if not self.adjacent(node_a, node_b):
return []
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42,263 | jciskey/pygraph | pygraph/functions/biconnected_components.py | find_biconnected_components | def find_biconnected_components(graph):
"""Finds all the biconnected components in a graph.
Returns a list of lists, each containing the edges that form a biconnected component.
Returns an empty list for an empty graph.
"""
list_of_components = []
# Run the algorithm on each of the connected c... | python | def find_biconnected_components(graph):
"""Finds all the biconnected components in a graph.
Returns a list of lists, each containing the edges that form a biconnected component.
Returns an empty list for an empty graph.
"""
list_of_components = []
# Run the algorithm on each of the connected c... | [
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42,264 | jciskey/pygraph | pygraph/functions/biconnected_components.py | find_biconnected_components_as_subgraphs | def find_biconnected_components_as_subgraphs(graph):
"""Finds the biconnected components and returns them as subgraphs."""
list_of_graphs = []
list_of_components = find_biconnected_components(graph)
for edge_list in list_of_components:
subgraph = get_subgraph_from_edge_list(graph, edge_list)
... | python | def find_biconnected_components_as_subgraphs(graph):
"""Finds the biconnected components and returns them as subgraphs."""
list_of_graphs = []
list_of_components = find_biconnected_components(graph)
for edge_list in list_of_components:
subgraph = get_subgraph_from_edge_list(graph, edge_list)
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42,265 | jciskey/pygraph | pygraph/functions/biconnected_components.py | find_articulation_vertices | def find_articulation_vertices(graph):
"""Finds all of the articulation vertices within a graph.
Returns a list of all articulation vertices within the graph.
Returns an empty list for an empty graph.
"""
articulation_vertices = []
all_nodes = graph.get_all_node_ids()
if len(all_nodes) == ... | python | def find_articulation_vertices(graph):
"""Finds all of the articulation vertices within a graph.
Returns a list of all articulation vertices within the graph.
Returns an empty list for an empty graph.
"""
articulation_vertices = []
all_nodes = graph.get_all_node_ids()
if len(all_nodes) == ... | [
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42,266 | jciskey/pygraph | pygraph/functions/biconnected_components.py | output_component | def output_component(graph, edge_stack, u, v):
"""Helper function to pop edges off the stack and produce a list of them."""
edge_list = []
while len(edge_stack) > 0:
edge_id = edge_stack.popleft()
edge_list.append(edge_id)
edge = graph.get_edge(edge_id)
tpl_a = (u, v)
... | python | def output_component(graph, edge_stack, u, v):
"""Helper function to pop edges off the stack and produce a list of them."""
edge_list = []
while len(edge_stack) > 0:
edge_id = edge_stack.popleft()
edge_list.append(edge_id)
edge = graph.get_edge(edge_id)
tpl_a = (u, v)
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42,267 | jciskey/pygraph | pygraph/functions/searching/depth_first_search.py | depth_first_search_with_parent_data | def depth_first_search_with_parent_data(graph, root_node = None, adjacency_lists = None):
"""Performs a depth-first search with visiting order of nodes determined by provided adjacency lists,
and also returns a parent lookup dict and a children lookup dict."""
ordering = []
parent_lookup = {}
child... | python | def depth_first_search_with_parent_data(graph, root_node = None, adjacency_lists = None):
"""Performs a depth-first search with visiting order of nodes determined by provided adjacency lists,
and also returns a parent lookup dict and a children lookup dict."""
ordering = []
parent_lookup = {}
child... | [
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42,268 | jciskey/pygraph | pygraph/render.py | graph_to_dot | def graph_to_dot(graph, node_renderer=None, edge_renderer=None):
"""Produces a DOT specification string from the provided graph."""
node_pairs = list(graph.nodes.items())
edge_pairs = list(graph.edges.items())
if node_renderer is None:
node_renderer_wrapper = lambda nid: ''
else:
no... | python | def graph_to_dot(graph, node_renderer=None, edge_renderer=None):
"""Produces a DOT specification string from the provided graph."""
node_pairs = list(graph.nodes.items())
edge_pairs = list(graph.edges.items())
if node_renderer is None:
node_renderer_wrapper = lambda nid: ''
else:
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42,269 | jciskey/pygraph | pygraph/functions/connected_components.py | get_connected_components | def get_connected_components(graph):
"""Finds all connected components of the graph.
Returns a list of lists, each containing the nodes that form a connected component.
Returns an empty list for an empty graph.
"""
list_of_components = []
component = [] # Not strictly necessary due to the whil... | python | def get_connected_components(graph):
"""Finds all connected components of the graph.
Returns a list of lists, each containing the nodes that form a connected component.
Returns an empty list for an empty graph.
"""
list_of_components = []
component = [] # Not strictly necessary due to the whil... | [
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42,270 | jciskey/pygraph | pygraph/functions/connected_components.py | get_connected_components_as_subgraphs | def get_connected_components_as_subgraphs(graph):
"""Finds all connected components of the graph.
Returns a list of graph objects, each representing a connected component.
Returns an empty list for an empty graph.
"""
components = get_connected_components(graph)
list_of_graphs = []
for c i... | python | def get_connected_components_as_subgraphs(graph):
"""Finds all connected components of the graph.
Returns a list of graph objects, each representing a connected component.
Returns an empty list for an empty graph.
"""
components = get_connected_components(graph)
list_of_graphs = []
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Returns a list of graph objects, each representing a connected component.
Returns an empty list for an empty graph. | [
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42,271 | jciskey/pygraph | pygraph/classes/undirected_graph.py | UndirectedGraph.new_edge | def new_edge(self, node_a, node_b, cost=1):
"""Adds a new, undirected edge between node_a and node_b with a cost.
Returns the edge id of the new edge."""
edge_id = super(UndirectedGraph, self).new_edge(node_a, node_b, cost)
self.nodes[node_b]['edges'].append(edge_id)
return edge_... | python | def new_edge(self, node_a, node_b, cost=1):
"""Adds a new, undirected edge between node_a and node_b with a cost.
Returns the edge id of the new edge."""
edge_id = super(UndirectedGraph, self).new_edge(node_a, node_b, cost)
self.nodes[node_b]['edges'].append(edge_id)
return edge_... | [
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42,272 | jciskey/pygraph | pygraph/classes/undirected_graph.py | UndirectedGraph.delete_edge_by_id | def delete_edge_by_id(self, edge_id):
"""Removes the edge identified by "edge_id" from the graph."""
edge = self.get_edge(edge_id)
# Remove the edge from the "from node"
# --Determine the from node
from_node_id = edge['vertices'][0]
from_node = self.get_node(from_node_id... | python | def delete_edge_by_id(self, edge_id):
"""Removes the edge identified by "edge_id" from the graph."""
edge = self.get_edge(edge_id)
# Remove the edge from the "from node"
# --Determine the from node
from_node_id = edge['vertices'][0]
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42,273 | jciskey/pygraph | pygraph/functions/spanning_tree.py | find_minimum_spanning_tree | def find_minimum_spanning_tree(graph):
"""Calculates a minimum spanning tree for a graph.
Returns a list of edges that define the tree.
Returns an empty list for an empty graph.
"""
mst = []
if graph.num_nodes() == 0:
return mst
if graph.num_edges() == 0:
return mst
con... | python | def find_minimum_spanning_tree(graph):
"""Calculates a minimum spanning tree for a graph.
Returns a list of edges that define the tree.
Returns an empty list for an empty graph.
"""
mst = []
if graph.num_nodes() == 0:
return mst
if graph.num_edges() == 0:
return mst
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42,274 | jciskey/pygraph | pygraph/functions/spanning_tree.py | find_minimum_spanning_tree_as_subgraph | def find_minimum_spanning_tree_as_subgraph(graph):
"""Calculates a minimum spanning tree and returns a graph representation."""
edge_list = find_minimum_spanning_tree(graph)
subgraph = get_subgraph_from_edge_list(graph, edge_list)
return subgraph | python | def find_minimum_spanning_tree_as_subgraph(graph):
"""Calculates a minimum spanning tree and returns a graph representation."""
edge_list = find_minimum_spanning_tree(graph)
subgraph = get_subgraph_from_edge_list(graph, edge_list)
return subgraph | [
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42,275 | jciskey/pygraph | pygraph/functions/spanning_tree.py | find_minimum_spanning_forest | def find_minimum_spanning_forest(graph):
"""Calculates the minimum spanning forest of a disconnected graph.
Returns a list of lists, each containing the edges that define that tree.
Returns an empty list for an empty graph.
"""
msf = []
if graph.num_nodes() == 0:
return msf
if graph... | python | def find_minimum_spanning_forest(graph):
"""Calculates the minimum spanning forest of a disconnected graph.
Returns a list of lists, each containing the edges that define that tree.
Returns an empty list for an empty graph.
"""
msf = []
if graph.num_nodes() == 0:
return msf
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42,276 | jciskey/pygraph | pygraph/functions/spanning_tree.py | find_minimum_spanning_forest_as_subgraphs | def find_minimum_spanning_forest_as_subgraphs(graph):
"""Calculates the minimum spanning forest and returns a list of trees as subgraphs."""
forest = find_minimum_spanning_forest(graph)
list_of_subgraphs = [get_subgraph_from_edge_list(graph, edge_list) for edge_list in forest]
return list_of_subgraphs | python | def find_minimum_spanning_forest_as_subgraphs(graph):
"""Calculates the minimum spanning forest and returns a list of trees as subgraphs."""
forest = find_minimum_spanning_forest(graph)
list_of_subgraphs = [get_subgraph_from_edge_list(graph, edge_list) for edge_list in forest]
return list_of_subgraphs | [
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42,277 | jciskey/pygraph | pygraph/functions/spanning_tree.py | kruskal_mst | def kruskal_mst(graph):
"""Implements Kruskal's Algorithm for finding minimum spanning trees.
Assumes a non-empty, connected graph.
"""
edges_accepted = 0
ds = DisjointSet()
pq = PriorityQueue()
accepted_edges = []
label_lookup = {}
nodes = graph.get_all_node_ids()
num_vertices ... | python | def kruskal_mst(graph):
"""Implements Kruskal's Algorithm for finding minimum spanning trees.
Assumes a non-empty, connected graph.
"""
edges_accepted = 0
ds = DisjointSet()
pq = PriorityQueue()
accepted_edges = []
label_lookup = {}
nodes = graph.get_all_node_ids()
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42,278 | jciskey/pygraph | pygraph/functions/planarity/lipton-tarjan_algorithm.py | __get_cycle | def __get_cycle(graph, ordering, parent_lookup):
"""Gets the main cycle of the dfs tree."""
root_node = ordering[0]
for i in range(2, len(ordering)):
current_node = ordering[i]
if graph.adjacent(current_node, root_node):
path = []
while current_node != root_node:
... | python | def __get_cycle(graph, ordering, parent_lookup):
"""Gets the main cycle of the dfs tree."""
root_node = ordering[0]
for i in range(2, len(ordering)):
current_node = ordering[i]
if graph.adjacent(current_node, root_node):
path = []
while current_node != root_node:
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42,279 | jciskey/pygraph | pygraph/functions/planarity/lipton-tarjan_algorithm.py | __get_segments_from_node | def __get_segments_from_node(node, graph):
"""Calculates the segments that can emanate from a particular node on the main cycle."""
list_of_segments = []
node_object = graph.get_node(node)
for e in node_object['edges']:
list_of_segments.append(e)
return list_of_segments | python | def __get_segments_from_node(node, graph):
"""Calculates the segments that can emanate from a particular node on the main cycle."""
list_of_segments = []
node_object = graph.get_node(node)
for e in node_object['edges']:
list_of_segments.append(e)
return list_of_segments | [
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42,280 | jciskey/pygraph | pygraph/functions/planarity/lipton-tarjan_algorithm.py | __get_segments_from_cycle | def __get_segments_from_cycle(graph, cycle_path):
"""Calculates the segments that emanate from the main cycle."""
list_of_segments = []
# We work through the cycle in a bottom-up fashion
for n in cycle_path[::-1]:
segments = __get_segments_from_node(n, graph)
if segments:
lis... | python | def __get_segments_from_cycle(graph, cycle_path):
"""Calculates the segments that emanate from the main cycle."""
list_of_segments = []
# We work through the cycle in a bottom-up fashion
for n in cycle_path[::-1]:
segments = __get_segments_from_node(n, graph)
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42,281 | jciskey/pygraph | pygraph/helpers/functions.py | make_subgraph | def make_subgraph(graph, vertices, edges):
"""Converts a subgraph given by a list of vertices and edges into a graph object."""
# Copy the entire graph
local_graph = copy.deepcopy(graph)
# Remove all the edges that aren't in the list
edges_to_delete = [x for x in local_graph.get_all_edge_ids() if x... | python | def make_subgraph(graph, vertices, edges):
"""Converts a subgraph given by a list of vertices and edges into a graph object."""
# Copy the entire graph
local_graph = copy.deepcopy(graph)
# Remove all the edges that aren't in the list
edges_to_delete = [x for x in local_graph.get_all_edge_ids() if x... | [
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42,282 | jciskey/pygraph | pygraph/helpers/functions.py | convert_graph_directed_to_undirected | def convert_graph_directed_to_undirected(dg):
"""Converts a directed graph into an undirected graph. Directed edges are made undirected."""
udg = UndirectedGraph()
# Copy the graph
# --Copy nodes
# --Copy edges
udg.nodes = copy.deepcopy(dg.nodes)
udg.edges = copy.deepcopy(dg.edges)
udg... | python | def convert_graph_directed_to_undirected(dg):
"""Converts a directed graph into an undirected graph. Directed edges are made undirected."""
udg = UndirectedGraph()
# Copy the graph
# --Copy nodes
# --Copy edges
udg.nodes = copy.deepcopy(dg.nodes)
udg.edges = copy.deepcopy(dg.edges)
udg... | [
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42,283 | jciskey/pygraph | pygraph/helpers/functions.py | remove_duplicate_edges_directed | def remove_duplicate_edges_directed(dg):
"""Removes duplicate edges from a directed graph."""
# With directed edges, we can just hash the to and from node id tuples and if
# a node happens to conflict with one that already exists, we delete it
# --For aesthetic, we sort the edge ids so that lower edge ... | python | def remove_duplicate_edges_directed(dg):
"""Removes duplicate edges from a directed graph."""
# With directed edges, we can just hash the to and from node id tuples and if
# a node happens to conflict with one that already exists, we delete it
# --For aesthetic, we sort the edge ids so that lower edge ... | [
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42,284 | jciskey/pygraph | pygraph/helpers/functions.py | remove_duplicate_edges_undirected | def remove_duplicate_edges_undirected(udg):
"""Removes duplicate edges from an undirected graph."""
# With undirected edges, we need to hash both combinations of the to-from node ids, since a-b and b-a are equivalent
# --For aesthetic, we sort the edge ids so that lower edges ids are kept
lookup = {}
... | python | def remove_duplicate_edges_undirected(udg):
"""Removes duplicate edges from an undirected graph."""
# With undirected edges, we need to hash both combinations of the to-from node ids, since a-b and b-a are equivalent
# --For aesthetic, we sort the edge ids so that lower edges ids are kept
lookup = {}
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42,285 | jciskey/pygraph | pygraph/helpers/functions.py | get_vertices_from_edge_list | def get_vertices_from_edge_list(graph, edge_list):
"""Transforms a list of edges into a list of the nodes those edges connect.
Returns a list of nodes, or an empty list if given an empty list.
"""
node_set = set()
for edge_id in edge_list:
edge = graph.get_edge(edge_id)
a, b = edge['... | python | def get_vertices_from_edge_list(graph, edge_list):
"""Transforms a list of edges into a list of the nodes those edges connect.
Returns a list of nodes, or an empty list if given an empty list.
"""
node_set = set()
for edge_id in edge_list:
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42,286 | jciskey/pygraph | pygraph/helpers/functions.py | get_subgraph_from_edge_list | def get_subgraph_from_edge_list(graph, edge_list):
"""Transforms a list of edges into a subgraph."""
node_list = get_vertices_from_edge_list(graph, edge_list)
subgraph = make_subgraph(graph, node_list, edge_list)
return subgraph | python | def get_subgraph_from_edge_list(graph, edge_list):
"""Transforms a list of edges into a subgraph."""
node_list = get_vertices_from_edge_list(graph, edge_list)
subgraph = make_subgraph(graph, node_list, edge_list)
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42,287 | jciskey/pygraph | pygraph/helpers/functions.py | merge_graphs | def merge_graphs(main_graph, addition_graph):
"""Merges an ''addition_graph'' into the ''main_graph''.
Returns a tuple of dictionaries, mapping old node ids and edge ids to new ids.
"""
node_mapping = {}
edge_mapping = {}
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node_id = nod... | python | def merge_graphs(main_graph, addition_graph):
"""Merges an ''addition_graph'' into the ''main_graph''.
Returns a tuple of dictionaries, mapping old node ids and edge ids to new ids.
"""
node_mapping = {}
edge_mapping = {}
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42,288 | jciskey/pygraph | pygraph/helpers/functions.py | create_graph_from_adjacency_matrix | def create_graph_from_adjacency_matrix(adjacency_matrix):
"""Generates a graph from an adjacency matrix specification.
Returns a tuple containing the graph and a list-mapping of node ids to matrix column indices.
The graph will be an UndirectedGraph if the provided adjacency matrix is symmetric.
... | python | def create_graph_from_adjacency_matrix(adjacency_matrix):
"""Generates a graph from an adjacency matrix specification.
Returns a tuple containing the graph and a list-mapping of node ids to matrix column indices.
The graph will be an UndirectedGraph if the provided adjacency matrix is symmetric.
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42,289 | jciskey/pygraph | pygraph/helpers/classes/disjoint_set.py | DisjointSet.add_set | def add_set(self):
"""Adds a new set to the forest.
Returns a label by which the new set can be referenced
"""
self.__label_counter += 1
new_label = self.__label_counter
self.__forest[new_label] = -1 # All new sets have their parent set to themselves
self.__set_c... | python | def add_set(self):
"""Adds a new set to the forest.
Returns a label by which the new set can be referenced
"""
self.__label_counter += 1
new_label = self.__label_counter
self.__forest[new_label] = -1 # All new sets have their parent set to themselves
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42,290 | jciskey/pygraph | pygraph/helpers/classes/disjoint_set.py | DisjointSet.find | def find(self, node_label):
"""Finds the set containing the node_label.
Returns the set label.
"""
queue = []
current_node = node_label
while self.__forest[current_node] >= 0:
queue.append(current_node)
current_node = self.__forest[current_node]
... | python | def find(self, node_label):
"""Finds the set containing the node_label.
Returns the set label.
"""
queue = []
current_node = node_label
while self.__forest[current_node] >= 0:
queue.append(current_node)
current_node = self.__forest[current_node]
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42,291 | jciskey/pygraph | pygraph/helpers/classes/disjoint_set.py | DisjointSet.union | def union(self, label_a, label_b):
"""Joins two sets into a single new set.
label_a, label_b can be any nodes within the sets
"""
# Base case to avoid work
if label_a == label_b:
return
# Find the tree root of each node
root_a = self.find(label_a)
... | python | def union(self, label_a, label_b):
"""Joins two sets into a single new set.
label_a, label_b can be any nodes within the sets
"""
# Base case to avoid work
if label_a == label_b:
return
# Find the tree root of each node
root_a = self.find(label_a)
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42,292 | jciskey/pygraph | pygraph/helpers/classes/disjoint_set.py | DisjointSet.__internal_union | def __internal_union(self, root_a, root_b):
"""Internal function to join two set trees specified by root_a and root_b.
Assumes root_a and root_b are distinct.
"""
# Merge the trees, smaller to larger
update_rank = False
# --Determine the larger tree
rank_a = self.... | python | def __internal_union(self, root_a, root_b):
"""Internal function to join two set trees specified by root_a and root_b.
Assumes root_a and root_b are distinct.
"""
# Merge the trees, smaller to larger
update_rank = False
# --Determine the larger tree
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42,293 | jciskey/pygraph | pygraph/functions/planarity/functions.py | is_planar | def is_planar(graph):
"""Determines whether a graph is planar or not."""
# Determine connected components as subgraphs; their planarity is independent of each other
connected_components = get_connected_components_as_subgraphs(graph)
for component in connected_components:
# Biconnected components... | python | def is_planar(graph):
"""Determines whether a graph is planar or not."""
# Determine connected components as subgraphs; their planarity is independent of each other
connected_components = get_connected_components_as_subgraphs(graph)
for component in connected_components:
# Biconnected components... | [
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42,294 | jciskey/pygraph | pygraph/functions/planarity/functions.py | __is_subgraph_planar | def __is_subgraph_planar(graph):
"""Internal function to determine if a subgraph is planar."""
# --First pass: Determine edge and vertex counts validate Euler's Formula
num_nodes = graph.num_nodes()
num_edges = graph.num_edges()
# --We can guarantee that if there are 4 or less nodes, then the graph... | python | def __is_subgraph_planar(graph):
"""Internal function to determine if a subgraph is planar."""
# --First pass: Determine edge and vertex counts validate Euler's Formula
num_nodes = graph.num_nodes()
num_edges = graph.num_edges()
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42,295 | jciskey/pygraph | pygraph/functions/planarity/kocay_algorithm.py | __setup_dfs_data | def __setup_dfs_data(graph, adj):
"""Sets up the dfs_data object, for consistency."""
dfs_data = __get_dfs_data(graph, adj)
dfs_data['graph'] = graph
dfs_data['adj'] = adj
L1, L2 = __low_point_dfs(dfs_data)
dfs_data['lowpoint_1_lookup'] = L1
dfs_data['lowpoint_2_lookup'] = L2
edge_wei... | python | def __setup_dfs_data(graph, adj):
"""Sets up the dfs_data object, for consistency."""
dfs_data = __get_dfs_data(graph, adj)
dfs_data['graph'] = graph
dfs_data['adj'] = adj
L1, L2 = __low_point_dfs(dfs_data)
dfs_data['lowpoint_1_lookup'] = L1
dfs_data['lowpoint_2_lookup'] = L2
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42,296 | jciskey/pygraph | pygraph/functions/planarity/kocay_algorithm.py | __calculate_edge_weights | def __calculate_edge_weights(dfs_data):
"""Calculates the weight of each edge, for embedding-order sorting."""
graph = dfs_data['graph']
weights = {}
for edge_id in graph.get_all_edge_ids():
edge_weight = __edge_weight(edge_id, dfs_data)
weights[edge_id] = edge_weight
return weight... | python | def __calculate_edge_weights(dfs_data):
"""Calculates the weight of each edge, for embedding-order sorting."""
graph = dfs_data['graph']
weights = {}
for edge_id in graph.get_all_edge_ids():
edge_weight = __edge_weight(edge_id, dfs_data)
weights[edge_id] = edge_weight
return weight... | [
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42,297 | jciskey/pygraph | pygraph/functions/planarity/kocay_algorithm.py | __sort_adjacency_lists | def __sort_adjacency_lists(dfs_data):
"""Sorts the adjacency list representation by the edge weights."""
new_adjacency_lists = {}
adjacency_lists = dfs_data['adj']
edge_weights = dfs_data['edge_weights']
edge_lookup = dfs_data['edge_lookup']
for node_id, adj_list in list(adjacency_lists.items(... | python | def __sort_adjacency_lists(dfs_data):
"""Sorts the adjacency list representation by the edge weights."""
new_adjacency_lists = {}
adjacency_lists = dfs_data['adj']
edge_weights = dfs_data['edge_weights']
edge_lookup = dfs_data['edge_lookup']
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42,298 | jciskey/pygraph | pygraph/functions/planarity/kocay_algorithm.py | __branch_point_dfs_recursive | def __branch_point_dfs_recursive(u, large_n, b, stem, dfs_data):
"""A recursive implementation of the BranchPtDFS function, as defined on page 14 of the paper."""
first_vertex = dfs_data['adj'][u][0]
large_w = wt(u, first_vertex, dfs_data)
if large_w % 2 == 0:
large_w += 1
v_I = 0
v_II =... | python | def __branch_point_dfs_recursive(u, large_n, b, stem, dfs_data):
"""A recursive implementation of the BranchPtDFS function, as defined on page 14 of the paper."""
first_vertex = dfs_data['adj'][u][0]
large_w = wt(u, first_vertex, dfs_data)
if large_w % 2 == 0:
large_w += 1
v_I = 0
v_II =... | [
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] | 037bb2f32503fecb60d62921f9766d54109f15e2 | https://github.com/jciskey/pygraph/blob/037bb2f32503fecb60d62921f9766d54109f15e2/pygraph/functions/planarity/kocay_algorithm.py#L123-L180 |
42,299 | jciskey/pygraph | pygraph/functions/planarity/kocay_algorithm.py | __embed_branch | def __embed_branch(dfs_data):
"""Builds the combinatorial embedding of the graph. Returns whether the graph is planar."""
u = dfs_data['ordering'][0]
dfs_data['LF'] = []
dfs_data['RF'] = []
dfs_data['FG'] = {}
n = dfs_data['graph'].num_nodes()
f0 = (0, n)
g0 = (0, n)
L0 = {'u': 0, 'v... | python | def __embed_branch(dfs_data):
"""Builds the combinatorial embedding of the graph. Returns whether the graph is planar."""
u = dfs_data['ordering'][0]
dfs_data['LF'] = []
dfs_data['RF'] = []
dfs_data['FG'] = {}
n = dfs_data['graph'].num_nodes()
f0 = (0, n)
g0 = (0, n)
L0 = {'u': 0, 'v... | [
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] | 037bb2f32503fecb60d62921f9766d54109f15e2 | https://github.com/jciskey/pygraph/blob/037bb2f32503fecb60d62921f9766d54109f15e2/pygraph/functions/planarity/kocay_algorithm.py#L183-L209 |
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