partition stringclasses 3
values | func_name stringlengths 1 134 | docstring stringlengths 1 46.9k | path stringlengths 4 223 | original_string stringlengths 75 104k | code stringlengths 75 104k | docstring_tokens listlengths 1 1.97k | repo stringlengths 7 55 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
|---|---|---|---|---|---|---|---|---|---|---|---|
valid | execute_reliabledictionary | Execute create, update, delete operations on existing reliable dictionaries.
carry out create, update and delete operations on existing reliable dictionaries for given application and service.
:param application_name: Name of the application.
:type application_name: str
:param service_name: Name of th... | rcctl/rcctl/custom_reliablecollections.py | def execute_reliabledictionary(client, application_name, service_name, input_file):
"""Execute create, update, delete operations on existing reliable dictionaries.
carry out create, update and delete operations on existing reliable dictionaries for given application and service.
:param application_name: N... | def execute_reliabledictionary(client, application_name, service_name, input_file):
"""Execute create, update, delete operations on existing reliable dictionaries.
carry out create, update and delete operations on existing reliable dictionaries for given application and service.
:param application_name: N... | [
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] | shalabhms/reliable-collections-cli | python | https://github.com/shalabhms/reliable-collections-cli/blob/195d69816fb5a6e1e9ab0ab66b606b1248b4780d/rcctl/rcctl/custom_reliablecollections.py#L126-L145 | [
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valid | select_arg_verify | Verify arguments for select command | rcctl/rcctl/custom_cluster.py | def select_arg_verify(endpoint, cert, key, pem, ca, aad, no_verify): #pylint: disable=invalid-name,too-many-arguments
"""Verify arguments for select command"""
if not (endpoint.lower().startswith('http')
or endpoint.lower().startswith('https')):
raise CLIError('Endpoint must be HTTP or HTTP... | def select_arg_verify(endpoint, cert, key, pem, ca, aad, no_verify): #pylint: disable=invalid-name,too-many-arguments
"""Verify arguments for select command"""
if not (endpoint.lower().startswith('http')
or endpoint.lower().startswith('https')):
raise CLIError('Endpoint must be HTTP or HTTP... | [
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valid | select | Connects to a Service Fabric cluster endpoint.
If connecting to secure cluster specify an absolute path to a cert (.crt)
and key file (.key) or a single file with both (.pem). Do not specify both.
Optionally, if connecting to a secure cluster, specify also an absolute
path to a CA bundle file or directo... | rcctl/rcctl/custom_cluster.py | def select(endpoint, cert=None, key=None, pem=None, ca=None, #pylint: disable=invalid-name, too-many-arguments
aad=False, no_verify=False):
#pylint: disable-msg=too-many-locals
"""
Connects to a Service Fabric cluster endpoint.
If connecting to secure cluster specify an absolute path to a cer... | def select(endpoint, cert=None, key=None, pem=None, ca=None, #pylint: disable=invalid-name, too-many-arguments
aad=False, no_verify=False):
#pylint: disable-msg=too-many-locals
"""
Connects to a Service Fabric cluster endpoint.
If connecting to secure cluster specify an absolute path to a cer... | [
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valid | get_aad_token | Get AAD token | rcctl/rcctl/custom_cluster.py | def get_aad_token(endpoint, no_verify):
#pylint: disable-msg=too-many-locals
"""Get AAD token"""
from azure.servicefabric.service_fabric_client_ap_is import (
ServiceFabricClientAPIs
)
from sfctl.auth import ClientCertAuthentication
from sfctl.config import set_aad_metadata
auth = C... | def get_aad_token(endpoint, no_verify):
#pylint: disable-msg=too-many-locals
"""Get AAD token"""
from azure.servicefabric.service_fabric_client_ap_is import (
ServiceFabricClientAPIs
)
from sfctl.auth import ClientCertAuthentication
from sfctl.config import set_aad_metadata
auth = C... | [
"Get",
"AAD",
"token"
] | shalabhms/reliable-collections-cli | python | https://github.com/shalabhms/reliable-collections-cli/blob/195d69816fb5a6e1e9ab0ab66b606b1248b4780d/rcctl/rcctl/custom_cluster.py#L101-L134 | [
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valid | _openpyxl_read_xl | Use openpyxl to read an Excel file. | boyle/excel_utils.py | def _openpyxl_read_xl(xl_path: str):
""" Use openpyxl to read an Excel file. """
try:
wb = load_workbook(filename=xl_path, read_only=True)
except:
raise
else:
return wb | def _openpyxl_read_xl(xl_path: str):
""" Use openpyxl to read an Excel file. """
try:
wb = load_workbook(filename=xl_path, read_only=True)
except:
raise
else:
return wb | [
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valid | _check_xl_path | Return the expanded absolute path of `xl_path` if
if exists and 'xlrd' or 'openpyxl' depending on
which module should be used for the Excel file in `xl_path`.
Parameters
----------
xl_path: str
Path to an Excel file
Returns
-------
xl_path: str
User expanded and absolut... | boyle/excel_utils.py | def _check_xl_path(xl_path: str):
""" Return the expanded absolute path of `xl_path` if
if exists and 'xlrd' or 'openpyxl' depending on
which module should be used for the Excel file in `xl_path`.
Parameters
----------
xl_path: str
Path to an Excel file
Returns
-------
xl_p... | def _check_xl_path(xl_path: str):
""" Return the expanded absolute path of `xl_path` if
if exists and 'xlrd' or 'openpyxl' depending on
which module should be used for the Excel file in `xl_path`.
Parameters
----------
xl_path: str
Path to an Excel file
Returns
-------
xl_p... | [
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valid | read_xl | Return the workbook from the Excel file in `xl_path`. | boyle/excel_utils.py | def read_xl(xl_path: str):
""" Return the workbook from the Excel file in `xl_path`."""
xl_path, choice = _check_xl_path(xl_path)
reader = XL_READERS[choice]
return reader(xl_path) | def read_xl(xl_path: str):
""" Return the workbook from the Excel file in `xl_path`."""
xl_path, choice = _check_xl_path(xl_path)
reader = XL_READERS[choice]
return reader(xl_path) | [
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valid | get_sheet_list | Return a list with the name of the sheets in
the Excel file in `xl_path`. | boyle/excel_utils.py | def get_sheet_list(xl_path: str) -> List:
"""Return a list with the name of the sheets in
the Excel file in `xl_path`.
"""
wb = read_xl(xl_path)
if hasattr(wb, 'sheetnames'):
return wb.sheetnames
else:
return wb.sheet_names() | def get_sheet_list(xl_path: str) -> List:
"""Return a list with the name of the sheets in
the Excel file in `xl_path`.
"""
wb = read_xl(xl_path)
if hasattr(wb, 'sheetnames'):
return wb.sheetnames
else:
return wb.sheet_names() | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/excel_utils.py#L101-L110 | [
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valid | concat_sheets | Return a pandas DataFrame with the concat'ed
content of the `sheetnames` from the Excel file in
`xl_path`.
Parameters
----------
xl_path: str
Path to the Excel file
sheetnames: list of str
List of existing sheet names of `xl_path`.
If None, will use all sheets from `xl_... | boyle/excel_utils.py | def concat_sheets(xl_path: str, sheetnames=None, add_tab_names=False):
""" Return a pandas DataFrame with the concat'ed
content of the `sheetnames` from the Excel file in
`xl_path`.
Parameters
----------
xl_path: str
Path to the Excel file
sheetnames: list of str
List of ex... | def concat_sheets(xl_path: str, sheetnames=None, add_tab_names=False):
""" Return a pandas DataFrame with the concat'ed
content of the `sheetnames` from the Excel file in
`xl_path`.
Parameters
----------
xl_path: str
Path to the Excel file
sheetnames: list of str
List of ex... | [
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valid | _check_cols | Raise an AttributeError if `df` does not have a column named as an item of
the list of strings `col_names`. | boyle/excel_utils.py | def _check_cols(df, col_names):
""" Raise an AttributeError if `df` does not have a column named as an item of
the list of strings `col_names`.
"""
for col in col_names:
if not hasattr(df, col):
raise AttributeError("DataFrame does not have a '{}' column, got {}.".format(col,
... | def _check_cols(df, col_names):
""" Raise an AttributeError if `df` does not have a column named as an item of
the list of strings `col_names`.
"""
for col in col_names:
if not hasattr(df, col):
raise AttributeError("DataFrame does not have a '{}' column, got {}.".format(col,
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valid | col_values | Return a list of not null values from the `col_name` column of `df`. | boyle/excel_utils.py | def col_values(df, col_name):
""" Return a list of not null values from the `col_name` column of `df`."""
_check_cols(df, [col_name])
if 'O' in df[col_name] or pd.np.issubdtype(df[col_name].dtype, str): # if the column is of strings
return [nom.lower() for nom in df[pd.notnull(df)][col_name] if not... | def col_values(df, col_name):
""" Return a list of not null values from the `col_name` column of `df`."""
_check_cols(df, [col_name])
if 'O' in df[col_name] or pd.np.issubdtype(df[col_name].dtype, str): # if the column is of strings
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valid | duplicated_rows | Return a DataFrame with the duplicated values of the column `col_name`
in `df`. | boyle/excel_utils.py | def duplicated_rows(df, col_name):
""" Return a DataFrame with the duplicated values of the column `col_name`
in `df`."""
_check_cols(df, [col_name])
dups = df[pd.notnull(df[col_name]) & df.duplicated(subset=[col_name])]
return dups | def duplicated_rows(df, col_name):
""" Return a DataFrame with the duplicated values of the column `col_name`
in `df`."""
_check_cols(df, [col_name])
dups = df[pd.notnull(df[col_name]) & df.duplicated(subset=[col_name])]
return dups | [
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valid | duplicated | Return the duplicated items in `values` | boyle/excel_utils.py | def duplicated(values: Sequence):
""" Return the duplicated items in `values`"""
vals = pd.Series(values)
return vals[vals.duplicated()] | def duplicated(values: Sequence):
""" Return the duplicated items in `values`"""
vals = pd.Series(values)
return vals[vals.duplicated()] | [
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valid | timestamp_with_tzinfo | Serialize a date/time value into an ISO8601 text representation
adjusted (if needed) to UTC timezone.
For instance:
>>> serialize_date(datetime(2012, 4, 10, 22, 38, 20, 604391))
'2012-04-10T22:38:20.604391Z' | boyle/petitdb.py | def timestamp_with_tzinfo(dt):
"""
Serialize a date/time value into an ISO8601 text representation
adjusted (if needed) to UTC timezone.
For instance:
>>> serialize_date(datetime(2012, 4, 10, 22, 38, 20, 604391))
'2012-04-10T22:38:20.604391Z'
"""
utc = tzutc()
if dt.tzinfo:
... | def timestamp_with_tzinfo(dt):
"""
Serialize a date/time value into an ISO8601 text representation
adjusted (if needed) to UTC timezone.
For instance:
>>> serialize_date(datetime(2012, 4, 10, 22, 38, 20, 604391))
'2012-04-10T22:38:20.604391Z'
"""
utc = tzutc()
if dt.tzinfo:
... | [
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valid | _to_string | Convert to string all values in `data`.
Parameters
----------
data: dict[str]->object
Returns
-------
string_data: dict[str]->str | boyle/petitdb.py | def _to_string(data):
""" Convert to string all values in `data`.
Parameters
----------
data: dict[str]->object
Returns
-------
string_data: dict[str]->str
"""
sdata = data.copy()
for k, v in data.items():
if isinstance(v, datetime):
sdata[k] = timestamp_to_... | def _to_string(data):
""" Convert to string all values in `data`.
Parameters
----------
data: dict[str]->object
Returns
-------
string_data: dict[str]->str
"""
sdata = data.copy()
for k, v in data.items():
if isinstance(v, datetime):
sdata[k] = timestamp_to_... | [
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valid | insert_unique | Insert `data` into `table` ensuring that data has unique values
in `table` for the fields listed in `unique_fields`.
If `raise_if_found` is True, will raise an NotUniqueItemError if
another item with the same `unique_fields` values are found
previously in `table`.
If False, will return the `eid` fr... | boyle/petitdb.py | def insert_unique(table, data, unique_fields=None, *, raise_if_found=False):
"""Insert `data` into `table` ensuring that data has unique values
in `table` for the fields listed in `unique_fields`.
If `raise_if_found` is True, will raise an NotUniqueItemError if
another item with the same `unique_fields... | def insert_unique(table, data, unique_fields=None, *, raise_if_found=False):
"""Insert `data` into `table` ensuring that data has unique values
in `table` for the fields listed in `unique_fields`.
If `raise_if_found` is True, will raise an NotUniqueItemError if
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valid | search_sample | Search for items in `table` that have the same field sub-set values as in `sample`.
Parameters
----------
table: tinydb.table
sample: dict
Sample data
Returns
-------
search_result: list of dict
List of the items found. The list is empty if no item is found. | boyle/petitdb.py | def search_sample(table, sample):
"""Search for items in `table` that have the same field sub-set values as in `sample`.
Parameters
----------
table: tinydb.table
sample: dict
Sample data
Returns
-------
search_result: list of dict
List of the items found. The list is ... | def search_sample(table, sample):
"""Search for items in `table` that have the same field sub-set values as in `sample`.
Parameters
----------
table: tinydb.table
sample: dict
Sample data
Returns
-------
search_result: list of dict
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valid | search_unique | Search for items in `table` that have the same field sub-set values as in `sample`.
Expecting it to be unique, otherwise will raise an exception.
Parameters
----------
table: tinydb.table
sample: dict
Sample data
Returns
-------
search_result: tinydb.database.Element
Un... | boyle/petitdb.py | def search_unique(table, sample, unique_fields=None):
""" Search for items in `table` that have the same field sub-set values as in `sample`.
Expecting it to be unique, otherwise will raise an exception.
Parameters
----------
table: tinydb.table
sample: dict
Sample data
Returns
... | def search_unique(table, sample, unique_fields=None):
""" Search for items in `table` that have the same field sub-set values as in `sample`.
Expecting it to be unique, otherwise will raise an exception.
Parameters
----------
table: tinydb.table
sample: dict
Sample data
Returns
... | [
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valid | find_unique | Search in `table` an item with the value of the `unique_fields` in the `sample` sample.
Check if the the obtained result is unique. If nothing is found will return an empty list,
if there is more than one item found, will raise an IndexError.
Parameters
----------
table: tinydb.table
sample: d... | boyle/petitdb.py | def find_unique(table, sample, unique_fields=None):
"""Search in `table` an item with the value of the `unique_fields` in the `sample` sample.
Check if the the obtained result is unique. If nothing is found will return an empty list,
if there is more than one item found, will raise an IndexError.
Param... | def find_unique(table, sample, unique_fields=None):
"""Search in `table` an item with the value of the `unique_fields` in the `sample` sample.
Check if the the obtained result is unique. If nothing is found will return an empty list,
if there is more than one item found, will raise an IndexError.
Param... | [
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valid | _query_sample | Create a TinyDB query that looks for items that have each field in `sample` with a value
compared with the correspondent operation in `operators`.
Parameters
----------
sample: dict
The sample data
operators: str or list of str
A list of comparison operations for each field value i... | boyle/petitdb.py | def _query_sample(sample, operators='__eq__'):
"""Create a TinyDB query that looks for items that have each field in `sample` with a value
compared with the correspondent operation in `operators`.
Parameters
----------
sample: dict
The sample data
operators: str or list of str
... | def _query_sample(sample, operators='__eq__'):
"""Create a TinyDB query that looks for items that have each field in `sample` with a value
compared with the correspondent operation in `operators`.
Parameters
----------
sample: dict
The sample data
operators: str or list of str
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valid | _query_data | Create a tinyDB Query object that looks for items that confirms the correspondent operator
from `operators` for each `field_names` field values from `data`.
Parameters
----------
data: dict
The data sample
field_names: str or list of str
The name of the fields in `data` that will b... | boyle/petitdb.py | def _query_data(data, field_names=None, operators='__eq__'):
"""Create a tinyDB Query object that looks for items that confirms the correspondent operator
from `operators` for each `field_names` field values from `data`.
Parameters
----------
data: dict
The data sample
field_names: str... | def _query_data(data, field_names=None, operators='__eq__'):
"""Create a tinyDB Query object that looks for items that confirms the correspondent operator
from `operators` for each `field_names` field values from `data`.
Parameters
----------
data: dict
The data sample
field_names: str... | [
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valid | _concat_queries | Create a tinyDB Query object that is the concatenation of each query in `queries`.
The concatenation operator is taken from `operators`.
Parameters
----------
queries: list of tinydb.Query
The list of tinydb.Query to be joined.
operators: str or list of str
List of binary operators... | boyle/petitdb.py | def _concat_queries(queries, operators='__and__'):
"""Create a tinyDB Query object that is the concatenation of each query in `queries`.
The concatenation operator is taken from `operators`.
Parameters
----------
queries: list of tinydb.Query
The list of tinydb.Query to be joined.
oper... | def _concat_queries(queries, operators='__and__'):
"""Create a tinyDB Query object that is the concatenation of each query in `queries`.
The concatenation operator is taken from `operators`.
Parameters
----------
queries: list of tinydb.Query
The list of tinydb.Query to be joined.
oper... | [
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valid | _build_query | Create a tinyDB Query object with the format:
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Parameters
----------
field_name: str
The name of the field to be queried.
field_value:
The value of the field
operator: str
The comparison operator.
Check TinyDB.Query... | boyle/petitdb.py | def _build_query(field_name, field_value, operator='__eq__'):
"""Create a tinyDB Query object with the format:
(where(`field_name`) `operator` `field_value`)
Parameters
----------
field_name: str
The name of the field to be queried.
field_value:
The value of the field
oper... | def _build_query(field_name, field_value, operator='__eq__'):
"""Create a tinyDB Query object with the format:
(where(`field_name`) `operator` `field_value`)
Parameters
----------
field_name: str
The name of the field to be queried.
field_value:
The value of the field
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valid | PetitDB.search_by_eid | Return the element in `table_name` with Object ID `eid`.
If None is found will raise a KeyError exception.
Parameters
----------
table_name: str
The name of the table to look in.
eid: int
The Object ID of the element to look for.
Returns
... | boyle/petitdb.py | def search_by_eid(self, table_name, eid):
"""Return the element in `table_name` with Object ID `eid`.
If None is found will raise a KeyError exception.
Parameters
----------
table_name: str
The name of the table to look in.
eid: int
The Object ID... | def search_by_eid(self, table_name, eid):
"""Return the element in `table_name` with Object ID `eid`.
If None is found will raise a KeyError exception.
Parameters
----------
table_name: str
The name of the table to look in.
eid: int
The Object ID... | [
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valid | PetitDB.insert_unique | Insert `data` into `table` ensuring that data has unique values
in `table` for the fields listed in `unique_fields`.
If `raise_if_found` is True, will raise an NotUniqueItemError if
another item with the same `unique_fields` values are found
previously in `table`.
If False, will... | boyle/petitdb.py | def insert_unique(self, table_name, data, unique_fields=None, *, raise_if_found=False):
"""Insert `data` into `table` ensuring that data has unique values
in `table` for the fields listed in `unique_fields`.
If `raise_if_found` is True, will raise an NotUniqueItemError if
another item w... | def insert_unique(self, table_name, data, unique_fields=None, *, raise_if_found=False):
"""Insert `data` into `table` ensuring that data has unique values
in `table` for the fields listed in `unique_fields`.
If `raise_if_found` is True, will raise an NotUniqueItemError if
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valid | PetitDB.search_unique | Search in `table` an item with the value of the `unique_fields` in the `data` sample.
Check if the the obtained result is unique. If nothing is found will return an empty list,
if there is more than one item found, will raise an IndexError.
Parameters
----------
table_name: str
... | boyle/petitdb.py | def search_unique(self, table_name, sample, unique_fields=None):
""" Search in `table` an item with the value of the `unique_fields` in the `data` sample.
Check if the the obtained result is unique. If nothing is found will return an empty list,
if there is more than one item found, will raise a... | def search_unique(self, table_name, sample, unique_fields=None):
""" Search in `table` an item with the value of the `unique_fields` in the `data` sample.
Check if the the obtained result is unique. If nothing is found will return an empty list,
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valid | PetitDB.search_sample | Search for items in `table` that have the same field sub-set values as in `sample`.
Parameters
----------
table_name: str
sample: dict
Sample data
Returns
-------
search_result: list of dict
List of the items found. The list is empty if ... | boyle/petitdb.py | def search_sample(self, table_name, sample):
"""Search for items in `table` that have the same field sub-set values as in `sample`.
Parameters
----------
table_name: str
sample: dict
Sample data
Returns
-------
search_result: list of dict
... | def search_sample(self, table_name, sample):
"""Search for items in `table` that have the same field sub-set values as in `sample`.
Parameters
----------
table_name: str
sample: dict
Sample data
Returns
-------
search_result: list of dict
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valid | PetitDB.is_unique | Return True if an item with the value of `unique_fields`
from `data` is unique in the table with `table_name`.
False if no sample is found or more than one is found.
See function `find_unique` for more details.
Parameters
----------
table_name: str
sample: dict... | boyle/petitdb.py | def is_unique(self, table_name, sample, unique_fields=None):
"""Return True if an item with the value of `unique_fields`
from `data` is unique in the table with `table_name`.
False if no sample is found or more than one is found.
See function `find_unique` for more details.
Par... | def is_unique(self, table_name, sample, unique_fields=None):
"""Return True if an item with the value of `unique_fields`
from `data` is unique in the table with `table_name`.
False if no sample is found or more than one is found.
See function `find_unique` for more details.
Par... | [
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valid | PetitDB.update_unique | Update the unique matching element to have a given set of fields.
Parameters
----------
table_name: str
fields: dict or function[dict -> None]
new data/values to insert into the unique element
or a method that will update the elements.
data: dict
... | boyle/petitdb.py | def update_unique(self, table_name, fields, data, cond=None, unique_fields=None,
*, raise_if_not_found=False):
"""Update the unique matching element to have a given set of fields.
Parameters
----------
table_name: str
fields: dict or function[dict -> None]... | def update_unique(self, table_name, fields, data, cond=None, unique_fields=None,
*, raise_if_not_found=False):
"""Update the unique matching element to have a given set of fields.
Parameters
----------
table_name: str
fields: dict or function[dict -> None]... | [
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valid | PetitDB.count | Return the number of items that match the `sample` field values
in table `table_name`.
Check function search_sample for more details. | boyle/petitdb.py | def count(self, table_name, sample):
"""Return the number of items that match the `sample` field values
in table `table_name`.
Check function search_sample for more details.
"""
return len(list(search_sample(table=self.table(table_name),
samp... | def count(self, table_name, sample):
"""Return the number of items that match the `sample` field values
in table `table_name`.
Check function search_sample for more details.
"""
return len(list(search_sample(table=self.table(table_name),
samp... | [
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valid | is_img | Check for get_data and get_affine method in an object
Parameters
----------
obj: any object
Tested object
Returns
-------
is_img: boolean
True if get_data and get_affine methods are present and callable,
False otherwise. | boyle/nifti/check.py | def is_img(obj):
""" Check for get_data and get_affine method in an object
Parameters
----------
obj: any object
Tested object
Returns
-------
is_img: boolean
True if get_data and get_affine methods are present and callable,
False otherwise.
"""
try:
... | def is_img(obj):
""" Check for get_data and get_affine method in an object
Parameters
----------
obj: any object
Tested object
Returns
-------
is_img: boolean
True if get_data and get_affine methods are present and callable,
False otherwise.
"""
try:
... | [
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"object"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/check.py#L32-L53 | [
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valid | get_data | Get the data in the image without having a side effect on the Nifti1Image object
Parameters
----------
img: Nifti1Image
Returns
-------
np.ndarray | boyle/nifti/check.py | def get_data(img):
"""Get the data in the image without having a side effect on the Nifti1Image object
Parameters
----------
img: Nifti1Image
Returns
-------
np.ndarray
"""
if hasattr(img, '_data_cache') and img._data_cache is None:
# Copy locally the nifti_image to avoid t... | def get_data(img):
"""Get the data in the image without having a side effect on the Nifti1Image object
Parameters
----------
img: Nifti1Image
Returns
-------
np.ndarray
"""
if hasattr(img, '_data_cache') and img._data_cache is None:
# Copy locally the nifti_image to avoid t... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/check.py#L56-L73 | [
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valid | get_shape | Return the shape of img.
Paramerers
-----------
img:
Returns
-------
shape: tuple | boyle/nifti/check.py | def get_shape(img):
"""Return the shape of img.
Paramerers
-----------
img:
Returns
-------
shape: tuple
"""
if hasattr(img, 'shape'):
shape = img.shape
else:
shape = img.get_data().shape
return shape | def get_shape(img):
"""Return the shape of img.
Paramerers
-----------
img:
Returns
-------
shape: tuple
"""
if hasattr(img, 'shape'):
shape = img.shape
else:
shape = img.get_data().shape
return shape | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/check.py#L76-L91 | [
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] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | is_valid_coordinate | Return True if the given (i, j, k) voxel grid coordinate values are within the img boundaries.
Parameters
----------
@param img:
@param i:
@param j:
@param k:
Returns
-------
bool | boyle/nifti/check.py | def is_valid_coordinate(img, i, j, k):
"""Return True if the given (i, j, k) voxel grid coordinate values are within the img boundaries.
Parameters
----------
@param img:
@param i:
@param j:
@param k:
Returns
-------
bool
"""
imgx, imgy, imgz = get_shape(img)
return... | def is_valid_coordinate(img, i, j, k):
"""Return True if the given (i, j, k) voxel grid coordinate values are within the img boundaries.
Parameters
----------
@param img:
@param i:
@param j:
@param k:
Returns
-------
bool
"""
imgx, imgy, imgz = get_shape(img)
return... | [
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valid | check_img_compatibility | Return true if one_img and another_img have the same shape.
False otherwise.
If both are nibabel.Nifti1Image will also check for affine matrices.
Parameters
----------
one_img: nibabel.Nifti1Image or np.ndarray
another_img: nibabel.Nifti1Image or np.ndarray
only_check_3d: bool
If... | boyle/nifti/check.py | def check_img_compatibility(one_img, another_img, only_check_3d=False):
"""Return true if one_img and another_img have the same shape.
False otherwise.
If both are nibabel.Nifti1Image will also check for affine matrices.
Parameters
----------
one_img: nibabel.Nifti1Image or np.ndarray
anot... | def check_img_compatibility(one_img, another_img, only_check_3d=False):
"""Return true if one_img and another_img have the same shape.
False otherwise.
If both are nibabel.Nifti1Image will also check for affine matrices.
Parameters
----------
one_img: nibabel.Nifti1Image or np.ndarray
anot... | [
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valid | have_same_affine | Return True if the affine matrix of one_img is close to the affine matrix of another_img.
False otherwise.
Parameters
----------
one_img: nibabel.Nifti1Image
another_img: nibabel.Nifti1Image
only_check_3d: bool
If True will extract only the 3D part of the affine matrices when they hav... | boyle/nifti/check.py | def have_same_affine(one_img, another_img, only_check_3d=False):
"""Return True if the affine matrix of one_img is close to the affine matrix of another_img.
False otherwise.
Parameters
----------
one_img: nibabel.Nifti1Image
another_img: nibabel.Nifti1Image
only_check_3d: bool
If... | def have_same_affine(one_img, another_img, only_check_3d=False):
"""Return True if the affine matrix of one_img is close to the affine matrix of another_img.
False otherwise.
Parameters
----------
one_img: nibabel.Nifti1Image
another_img: nibabel.Nifti1Image
only_check_3d: bool
If... | [
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... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | _make_it_3d | Enforce that img is a 3D img-like object, if it is not, raise a TypeError.
i.e., remove dimensions of size 1.
Parameters
----------
img: img-like object
Returns
-------
3D img-like object | boyle/nifti/check.py | def _make_it_3d(img):
"""Enforce that img is a 3D img-like object, if it is not, raise a TypeError.
i.e., remove dimensions of size 1.
Parameters
----------
img: img-like object
Returns
-------
3D img-like object
"""
shape = get_shape(img)
if len(shape) == 3:
return... | def _make_it_3d(img):
"""Enforce that img is a 3D img-like object, if it is not, raise a TypeError.
i.e., remove dimensions of size 1.
Parameters
----------
img: img-like object
Returns
-------
3D img-like object
"""
shape = get_shape(img)
if len(shape) == 3:
return... | [
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valid | check_img | Check that image is a proper img. Turn filenames into objects.
Parameters
----------
image: img-like object or str
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affine() methods, e.g., nibabel.Nifti1Image.
If niimg is a string, consider i... | boyle/nifti/check.py | def check_img(image, make_it_3d=False):
"""Check that image is a proper img. Turn filenames into objects.
Parameters
----------
image: img-like object or str
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affine() methods, e.g., nibabel.Nifti1... | def check_img(image, make_it_3d=False):
"""Check that image is a proper img. Turn filenames into objects.
Parameters
----------
image: img-like object or str
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affine() methods, e.g., nibabel.Nifti1... | [
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valid | repr_imgs | Printing of img or imgs | boyle/nifti/check.py | def repr_imgs(imgs):
"""Printing of img or imgs"""
if isinstance(imgs, string_types):
return imgs
if isinstance(imgs, collections.Iterable):
return '[{}]'.format(', '.join(repr_imgs(img) for img in imgs))
# try get_filename
try:
filename = imgs.get_filename()
if fil... | def repr_imgs(imgs):
"""Printing of img or imgs"""
if isinstance(imgs, string_types):
return imgs
if isinstance(imgs, collections.Iterable):
return '[{}]'.format(', '.join(repr_imgs(img) for img in imgs))
# try get_filename
try:
filename = imgs.get_filename()
if fil... | [
"Printing",
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"img",
"or",
"imgs"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/check.py#L295-L316 | [
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valid | have_same_shape | Returns true if array1 and array2 have the same shapes, false
otherwise.
Parameters
----------
array1: numpy.ndarray
array2: numpy.ndarray
nd_to_check: int
Number of the dimensions to check, i.e., if == 3 then will check only the 3 first numbers of array.shape.
Returns
-------... | boyle/nifti/check.py | def have_same_shape(array1, array2, nd_to_check=None):
"""
Returns true if array1 and array2 have the same shapes, false
otherwise.
Parameters
----------
array1: numpy.ndarray
array2: numpy.ndarray
nd_to_check: int
Number of the dimensions to check, i.e., if == 3 then will che... | def have_same_shape(array1, array2, nd_to_check=None):
"""
Returns true if array1 and array2 have the same shapes, false
otherwise.
Parameters
----------
array1: numpy.ndarray
array2: numpy.ndarray
nd_to_check: int
Number of the dimensions to check, i.e., if == 3 then will che... | [
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valid | have_same_geometry | @param fname1: string
File path of an image
@param fname2: string
File path of an image
@return: bool
True if both have the same geometry | boyle/nifti/check.py | def have_same_geometry(fname1, fname2):
"""
@param fname1: string
File path of an image
@param fname2: string
File path of an image
@return: bool
True if both have the same geometry
"""
img1shape = nib.load(fname1).get_shape()
img2shape = nib.load(fname2).get_shape()
return... | def have_same_geometry(fname1, fname2):
"""
@param fname1: string
File path of an image
@param fname2: string
File path of an image
@return: bool
True if both have the same geometry
"""
img1shape = nib.load(fname1).get_shape()
img2shape = nib.load(fname2).get_shape()
return... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/check.py#L357-L370 | [
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valid | have_same_spatial_geometry | @param fname1: string
File path of an image
@param fname2: string
File path of an image
@return: bool
True if both have the same geometry | boyle/nifti/check.py | def have_same_spatial_geometry(fname1, fname2):
"""
@param fname1: string
File path of an image
@param fname2: string
File path of an image
@return: bool
True if both have the same geometry
"""
img1shape = nib.load(fname1).get_shape()
img2shape = nib.load(fname2).get_shape()
... | def have_same_spatial_geometry(fname1, fname2):
"""
@param fname1: string
File path of an image
@param fname2: string
File path of an image
@return: bool
True if both have the same geometry
"""
img1shape = nib.load(fname1).get_shape()
img2shape = nib.load(fname2).get_shape()
... | [
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valid | dir_match | Create a list of regex matches that result from the match_regex
of all file names within wd.
The list of files will have wd as path prefix.
@param regex: string
@param wd: string
working directory
@return: | boyle/files/search.py | def dir_match(regex, wd=os.curdir):
"""Create a list of regex matches that result from the match_regex
of all file names within wd.
The list of files will have wd as path prefix.
@param regex: string
@param wd: string
working directory
@return:
"""
ls = os.listdir(wd)
filt = re... | def dir_match(regex, wd=os.curdir):
"""Create a list of regex matches that result from the match_regex
of all file names within wd.
The list of files will have wd as path prefix.
@param regex: string
@param wd: string
working directory
@return:
"""
ls = os.listdir(wd)
filt = re... | [
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valid | recursive_dir_match | Returns absolute paths of folders that match the regex within folder_path and
all its children folders.
Note: The regex matching is done using the match function
of the re module.
Parameters
----------
folder_path: string
regex: string
Returns
-------
A list of strings. | boyle/files/search.py | def recursive_dir_match(folder_path, regex=''):
"""
Returns absolute paths of folders that match the regex within folder_path and
all its children folders.
Note: The regex matching is done using the match function
of the re module.
Parameters
----------
folder_path: string
regex: ... | def recursive_dir_match(folder_path, regex=''):
"""
Returns absolute paths of folders that match the regex within folder_path and
all its children folders.
Note: The regex matching is done using the match function
of the re module.
Parameters
----------
folder_path: string
regex: ... | [
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valid | get_file_list | Creates a list of files that match the search_regex within file_dir.
The list of files will have file_dir as path prefix.
Parameters
----------
@param file_dir:
@param search_regex:
Returns:
--------
List of paths to files that match the search_regex | boyle/files/search.py | def get_file_list(file_dir, regex=''):
"""
Creates a list of files that match the search_regex within file_dir.
The list of files will have file_dir as path prefix.
Parameters
----------
@param file_dir:
@param search_regex:
Returns:
--------
List of paths to files that match ... | def get_file_list(file_dir, regex=''):
"""
Creates a list of files that match the search_regex within file_dir.
The list of files will have file_dir as path prefix.
Parameters
----------
@param file_dir:
@param search_regex:
Returns:
--------
List of paths to files that match ... | [
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valid | recursive_find_search | Returns absolute paths of files that match the regex within file_dir and
all its children folders.
Note: The regex matching is done using the search function
of the re module.
Parameters
----------
folder_path: string
regex: string
Returns
-------
A list of strings. | boyle/files/search.py | def recursive_find_search(folder_path, regex=''):
"""
Returns absolute paths of files that match the regex within file_dir and
all its children folders.
Note: The regex matching is done using the search function
of the re module.
Parameters
----------
folder_path: string
regex: st... | def recursive_find_search(folder_path, regex=''):
"""
Returns absolute paths of files that match the regex within file_dir and
all its children folders.
Note: The regex matching is done using the search function
of the re module.
Parameters
----------
folder_path: string
regex: st... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/files/search.py#L159-L183 | [
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valid | iter_recursive_find | Returns absolute paths of files that match the regexs within folder_path and
all its children folders.
This is an iterator function that will use yield to return each set of
file_paths in one iteration.
Will only return value if all the strings in regex match a file name.
Note: The regex matching... | boyle/files/search.py | def iter_recursive_find(folder_path, *regex):
"""
Returns absolute paths of files that match the regexs within folder_path and
all its children folders.
This is an iterator function that will use yield to return each set of
file_paths in one iteration.
Will only return value if all the strings... | def iter_recursive_find(folder_path, *regex):
"""
Returns absolute paths of files that match the regexs within folder_path and
all its children folders.
This is an iterator function that will use yield to return each set of
file_paths in one iteration.
Will only return value if all the strings... | [
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valid | get_all_files | Generator that loops through all absolute paths of the files within folder
Parameters
----------
folder: str
Root folder start point for recursive search.
Yields
------
fpath: str
Absolute path of one file in the folders | boyle/files/search.py | def get_all_files(folder):
"""
Generator that loops through all absolute paths of the files within folder
Parameters
----------
folder: str
Root folder start point for recursive search.
Yields
------
fpath: str
Absolute path of one file in the folders
"""
for path, dirl... | def get_all_files(folder):
"""
Generator that loops through all absolute paths of the files within folder
Parameters
----------
folder: str
Root folder start point for recursive search.
Yields
------
fpath: str
Absolute path of one file in the folders
"""
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/files/search.py#L220-L236 | [
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] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | recursive_glob | Uses glob to find all files or folders that match the regex
starting from the base_directory.
Parameters
----------
base_directory: str
regex: str
Returns
-------
files: list | boyle/files/search.py | def recursive_glob(base_directory, regex=''):
"""
Uses glob to find all files or folders that match the regex
starting from the base_directory.
Parameters
----------
base_directory: str
regex: str
Returns
-------
files: list
"""
files = glob(op.join(base_directory, re... | def recursive_glob(base_directory, regex=''):
"""
Uses glob to find all files or folders that match the regex
starting from the base_directory.
Parameters
----------
base_directory: str
regex: str
Returns
-------
files: list
"""
files = glob(op.join(base_directory, re... | [
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valid | get_last_file | Return the path to the latest file in `input_dir`.
The `key` argument defines which information to use for sorting
the list of files, could be:
- creation date: os.path.getctime,
- modification date: os.path.getmtime,
etc.
Parameters
----------
input_dir: str
Path ... | boyle/files/search.py | def get_last_file(input_dir, glob_pattern='*', key=op.getctime, reverse=True):
""" Return the path to the latest file in `input_dir`.
The `key` argument defines which information to use for sorting
the list of files, could be:
- creation date: os.path.getctime,
- modification date: os.path... | def get_last_file(input_dir, glob_pattern='*', key=op.getctime, reverse=True):
""" Return the path to the latest file in `input_dir`.
The `key` argument defines which information to use for sorting
the list of files, could be:
- creation date: os.path.getctime,
- modification date: os.path... | [
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valid | compose_err_msg | Append key-value pairs to msg, for display.
Parameters
----------
msg: string
arbitrary message
kwargs: dict
arbitrary dictionary
Returns
-------
updated_msg: string
msg, with "key: value" appended. Only string values are appended.
Example
-------
>>> c... | boyle/exceptions.py | def compose_err_msg(msg, **kwargs):
"""Append key-value pairs to msg, for display.
Parameters
----------
msg: string
arbitrary message
kwargs: dict
arbitrary dictionary
Returns
-------
updated_msg: string
msg, with "key: value" appended. Only string values are a... | def compose_err_msg(msg, **kwargs):
"""Append key-value pairs to msg, for display.
Parameters
----------
msg: string
arbitrary message
kwargs: dict
arbitrary dictionary
Returns
-------
updated_msg: string
msg, with "key: value" appended. Only string values are a... | [
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... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | group_dicom_files | Gets a list of DICOM file absolute paths and returns a list of lists of
DICOM file paths. Each group contains a set of DICOM files that have
exactly the same headers.
Parameters
----------
dicom_file_paths: list of str
List or set of DICOM file paths
header_fields: list of str
... | boyle/dicom/comparison.py | def group_dicom_files(dicom_file_paths, header_fields):
"""
Gets a list of DICOM file absolute paths and returns a list of lists of
DICOM file paths. Each group contains a set of DICOM files that have
exactly the same headers.
Parameters
----------
dicom_file_paths: list of str
List... | def group_dicom_files(dicom_file_paths, header_fields):
"""
Gets a list of DICOM file absolute paths and returns a list of lists of
DICOM file paths. Each group contains a set of DICOM files that have
exactly the same headers.
Parameters
----------
dicom_file_paths: list of str
List... | [
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valid | copy_groups_to_folder | Copy the DICOM file groups to folder_path. Each group will be copied into
a subfolder with named given by groupby_field.
Parameters
----------
dicom_groups: boyle.dicom.sets.DicomFileSet
folder_path: str
Path to where copy the DICOM files.
groupby_field_name: str
DICOM field name. W... | boyle/dicom/comparison.py | def copy_groups_to_folder(dicom_groups, folder_path, groupby_field_name):
"""Copy the DICOM file groups to folder_path. Each group will be copied into
a subfolder with named given by groupby_field.
Parameters
----------
dicom_groups: boyle.dicom.sets.DicomFileSet
folder_path: str
Path to ... | def copy_groups_to_folder(dicom_groups, folder_path, groupby_field_name):
"""Copy the DICOM file groups to folder_path. Each group will be copied into
a subfolder with named given by groupby_field.
Parameters
----------
dicom_groups: boyle.dicom.sets.DicomFileSet
folder_path: str
Path to ... | [
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valid | calculate_file_distances | Calculates the DicomFileDistance between all files in dicom_files, using an
weighted Levenshtein measure between all field names in field_weights and
their corresponding weights.
Parameters
----------
dicom_files: iterable of str
Dicom file paths
field_weights: dict of str to float
... | boyle/dicom/comparison.py | def calculate_file_distances(dicom_files, field_weights=None,
dist_method_cls=None, **kwargs):
"""
Calculates the DicomFileDistance between all files in dicom_files, using an
weighted Levenshtein measure between all field names in field_weights and
their corresponding weight... | def calculate_file_distances(dicom_files, field_weights=None,
dist_method_cls=None, **kwargs):
"""
Calculates the DicomFileDistance between all files in dicom_files, using an
weighted Levenshtein measure between all field names in field_weights and
their corresponding weight... | [
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valid | SimpleDicomFileDistance.fit | Parameters
----------
dcm_file1: str (path to file) or DicomFile or namedtuple
dcm_file2: str (path to file) or DicomFile or namedtuple | boyle/dicom/comparison.py | def fit(self, dcm_file1, dcm_file2):
"""
Parameters
----------
dcm_file1: str (path to file) or DicomFile or namedtuple
dcm_file2: str (path to file) or DicomFile or namedtuple
"""
self.set_dicom_file1(dcm_file1)
self.set_dicom_file2(dcm_file2) | def fit(self, dcm_file1, dcm_file2):
"""
Parameters
----------
dcm_file1: str (path to file) or DicomFile or namedtuple
dcm_file2: str (path to file) or DicomFile or namedtuple
"""
self.set_dicom_file1(dcm_file1)
self.set_dicom_file2(dcm_file2) | [
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valid | SimpleDicomFileDistance.transform | Check the field values in self.dcmf1 and self.dcmf2 and returns True
if all the field values are the same, False otherwise.
Returns
-------
bool | boyle/dicom/comparison.py | def transform(self):
"""Check the field values in self.dcmf1 and self.dcmf2 and returns True
if all the field values are the same, False otherwise.
Returns
-------
bool
"""
if self.dcmf1 is None or self.dcmf2 is None:
return np.inf
for field_... | def transform(self):
"""Check the field values in self.dcmf1 and self.dcmf2 and returns True
if all the field values are the same, False otherwise.
Returns
-------
bool
"""
if self.dcmf1 is None or self.dcmf2 is None:
return np.inf
for field_... | [
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valid | DicomFilesClustering.levenshtein_analysis | Updates the status of the file clusters comparing the cluster
key files with a levenshtein weighted measure using either the
header_fields or self.header_fields.
Parameters
----------
field_weights: dict of strings with floats
A dict with header field names to float ... | boyle/dicom/comparison.py | def levenshtein_analysis(self, field_weights=None):
"""
Updates the status of the file clusters comparing the cluster
key files with a levenshtein weighted measure using either the
header_fields or self.header_fields.
Parameters
----------
field_weights: dict of ... | def levenshtein_analysis(self, field_weights=None):
"""
Updates the status of the file clusters comparing the cluster
key files with a levenshtein weighted measure using either the
header_fields or self.header_fields.
Parameters
----------
field_weights: dict of ... | [
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valid | DicomFilesClustering.dist_percentile_threshold | Thresholds a distance matrix and returns the result.
Parameters
----------
dist_matrix: array_like
Input array or object that can be converted to an array.
perc_thr: float in range of [0,100]
Percentile to compute which must be between 0 and 100 inclusive.
k: ... | boyle/dicom/comparison.py | def dist_percentile_threshold(dist_matrix, perc_thr=0.05, k=1):
"""Thresholds a distance matrix and returns the result.
Parameters
----------
dist_matrix: array_like
Input array or object that can be converted to an array.
perc_thr: float in range of [0,100]
Pe... | def dist_percentile_threshold(dist_matrix, perc_thr=0.05, k=1):
"""Thresholds a distance matrix and returns the result.
Parameters
----------
dist_matrix: array_like
Input array or object that can be converted to an array.
perc_thr: float in range of [0,100]
Pe... | [
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valid | DicomFilesClustering.get_groups_in_same_folder | Returns a list of 2-tuples with pairs of dicom groups that
are in the same folder within given depth.
Parameters
----------
folder_depth: int
Path depth to check for folder equality.
Returns
-------
list of tuples of str | boyle/dicom/comparison.py | def get_groups_in_same_folder(self, folder_depth=3):
"""
Returns a list of 2-tuples with pairs of dicom groups that
are in the same folder within given depth.
Parameters
----------
folder_depth: int
Path depth to check for folder equality.
Returns
... | def get_groups_in_same_folder(self, folder_depth=3):
"""
Returns a list of 2-tuples with pairs of dicom groups that
are in the same folder within given depth.
Parameters
----------
folder_depth: int
Path depth to check for folder equality.
Returns
... | [
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... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | DicomFilesClustering.plot_file_distances | Plots dist_matrix
Parameters
----------
dist_matrix: np.ndarray | boyle/dicom/comparison.py | def plot_file_distances(dist_matrix):
"""
Plots dist_matrix
Parameters
----------
dist_matrix: np.ndarray
"""
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.matshow(dist_matrix, interpolation='nearest',
... | def plot_file_distances(dist_matrix):
"""
Plots dist_matrix
Parameters
----------
dist_matrix: np.ndarray
"""
import matplotlib.pyplot as plt
fig = plt.figure()
ax = fig.add_subplot(111)
ax.matshow(dist_matrix, interpolation='nearest',
... | [
"Plots",
"dist_matrix"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/comparison.py#L492-L505 | [
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valid | DicomFilesClustering.merge_groups | Extend the lists within the DICOM groups dictionary.
The indices will indicate which list have to be extended by which
other list.
Parameters
----------
indices: list or tuple of 2 iterables of int, bot having the same len
The indices of the lists that have to be me... | boyle/dicom/comparison.py | def merge_groups(self, indices):
"""Extend the lists within the DICOM groups dictionary.
The indices will indicate which list have to be extended by which
other list.
Parameters
----------
indices: list or tuple of 2 iterables of int, bot having the same len
... | def merge_groups(self, indices):
"""Extend the lists within the DICOM groups dictionary.
The indices will indicate which list have to be extended by which
other list.
Parameters
----------
indices: list or tuple of 2 iterables of int, bot having the same len
... | [
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valid | DicomFilesClustering.move_to_folder | Copy the file groups to folder_path. Each group will be copied into
a subfolder with named given by groupby_field.
Parameters
----------
folder_path: str
Path to where copy the DICOM files.
groupby_field_name: str
DICOM field name. Will get the value of this f... | boyle/dicom/comparison.py | def move_to_folder(self, folder_path, groupby_field_name=None):
"""Copy the file groups to folder_path. Each group will be copied into
a subfolder with named given by groupby_field.
Parameters
----------
folder_path: str
Path to where copy the DICOM files.
grou... | def move_to_folder(self, folder_path, groupby_field_name=None):
"""Copy the file groups to folder_path. Each group will be copied into
a subfolder with named given by groupby_field.
Parameters
----------
folder_path: str
Path to where copy the DICOM files.
grou... | [
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valid | DicomFilesClustering.get_unique_field_values_per_group | Return a dictionary where the key is the group key file path and
the values are sets of unique values of the field name of all DICOM
files in the group.
Parameters
----------
field_name: str
Name of the field to read from all files
field_to_use_as_key: str
... | boyle/dicom/comparison.py | def get_unique_field_values_per_group(self, field_name,
field_to_use_as_key=None):
"""Return a dictionary where the key is the group key file path and
the values are sets of unique values of the field name of all DICOM
files in the group.
Parame... | def get_unique_field_values_per_group(self, field_name,
field_to_use_as_key=None):
"""Return a dictionary where the key is the group key file path and
the values are sets of unique values of the field name of all DICOM
files in the group.
Parame... | [
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valid | get_config_value | Gets a config by name.
In the case where the config name is not found, will use fallback value. | rcctl/rcctl/config.py | def get_config_value(name, fallback=None):
"""Gets a config by name.
In the case where the config name is not found, will use fallback value."""
cli_config = CLIConfig(SF_CLI_CONFIG_DIR, SF_CLI_ENV_VAR_PREFIX)
return cli_config.get('servicefabric', name, fallback) | def get_config_value(name, fallback=None):
"""Gets a config by name.
In the case where the config name is not found, will use fallback value."""
cli_config = CLIConfig(SF_CLI_CONFIG_DIR, SF_CLI_ENV_VAR_PREFIX)
return cli_config.get('servicefabric', name, fallback) | [
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valid | get_config_bool | Checks if a config value is set to a valid bool value. | rcctl/rcctl/config.py | def get_config_bool(name):
"""Checks if a config value is set to a valid bool value."""
cli_config = CLIConfig(SF_CLI_CONFIG_DIR, SF_CLI_ENV_VAR_PREFIX)
return cli_config.getboolean('servicefabric', name, False) | def get_config_bool(name):
"""Checks if a config value is set to a valid bool value."""
cli_config = CLIConfig(SF_CLI_CONFIG_DIR, SF_CLI_ENV_VAR_PREFIX)
return cli_config.getboolean('servicefabric', name, False) | [
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valid | set_config_value | Set a config by name to a value. | rcctl/rcctl/config.py | def set_config_value(name, value):
"""Set a config by name to a value."""
cli_config = CLIConfig(SF_CLI_CONFIG_DIR, SF_CLI_ENV_VAR_PREFIX)
cli_config.set_value('servicefabric', name, value) | def set_config_value(name, value):
"""Set a config by name to a value."""
cli_config = CLIConfig(SF_CLI_CONFIG_DIR, SF_CLI_ENV_VAR_PREFIX)
cli_config.set_value('servicefabric', name, value) | [
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valid | cert_info | Path to certificate related files, either a single file path or a
tuple. In the case of no security, returns None. | rcctl/rcctl/config.py | def cert_info():
"""Path to certificate related files, either a single file path or a
tuple. In the case of no security, returns None."""
sec_type = security_type()
if sec_type == 'pem':
return get_config_value('pem_path', fallback=None)
if sec_type == 'cert':
cert_path = get_config... | def cert_info():
"""Path to certificate related files, either a single file path or a
tuple. In the case of no security, returns None."""
sec_type = security_type()
if sec_type == 'pem':
return get_config_value('pem_path', fallback=None)
if sec_type == 'cert':
cert_path = get_config... | [
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] | shalabhms/reliable-collections-cli | python | https://github.com/shalabhms/reliable-collections-cli/blob/195d69816fb5a6e1e9ab0ab66b606b1248b4780d/rcctl/rcctl/config.py#L80-L92 | [
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valid | set_aad_cache | Set AAD token cache. | rcctl/rcctl/config.py | def set_aad_cache(token, cache):
"""Set AAD token cache."""
set_config_value('aad_token', jsonpickle.encode(token))
set_config_value('aad_cache', jsonpickle.encode(cache)) | def set_aad_cache(token, cache):
"""Set AAD token cache."""
set_config_value('aad_token', jsonpickle.encode(token))
set_config_value('aad_cache', jsonpickle.encode(cache)) | [
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valid | set_aad_metadata | Set AAD metadata. | rcctl/rcctl/config.py | def set_aad_metadata(uri, resource, client):
"""Set AAD metadata."""
set_config_value('authority_uri', uri)
set_config_value('aad_resource', resource)
set_config_value('aad_client', client) | def set_aad_metadata(uri, resource, client):
"""Set AAD metadata."""
set_config_value('authority_uri', uri)
set_config_value('aad_resource', resource)
set_config_value('aad_client', client) | [
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valid | set_auth | Set certificate usage paths | rcctl/rcctl/config.py | def set_auth(pem=None, cert=None, key=None, aad=False):
"""Set certificate usage paths"""
if any([cert, key]) and pem:
raise ValueError('Cannot specify both pem and cert or key')
if any([cert, key]) and not all([cert, key]):
raise ValueError('Must specify both cert and key')
if pem:
... | def set_auth(pem=None, cert=None, key=None, aad=False):
"""Set certificate usage paths"""
if any([cert, key]) and pem:
raise ValueError('Cannot specify both pem and cert or key')
if any([cert, key]) and not all([cert, key]):
raise ValueError('Must specify both cert and key')
if pem:
... | [
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valid | filter_objlist | Returns a list with of the objects in olist that have a fieldname valued as fieldval
Parameters
----------
olist: list of objects
fieldname: string
fieldval: anything
Returns
-------
list of objets | boyle/utils/strings.py | def filter_objlist(olist, fieldname, fieldval):
"""
Returns a list with of the objects in olist that have a fieldname valued as fieldval
Parameters
----------
olist: list of objects
fieldname: string
fieldval: anything
Returns
-------
list of objets
"""
return [x for ... | def filter_objlist(olist, fieldname, fieldval):
"""
Returns a list with of the objects in olist that have a fieldname valued as fieldval
Parameters
----------
olist: list of objects
fieldname: string
fieldval: anything
Returns
-------
list of objets
"""
return [x for ... | [
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valid | filter_list | Parameters
----------
lst: list
filter: function
Unary string filter function
Returns
-------
list
List of items that passed the filter
Example
-------
>>> l = ['12123123', 'N123213']
>>> filt = re.compile('\d*').match
>>> nu_l = list_filter(l, filt) | boyle/utils/strings.py | def filter_list(lst, filt):
"""
Parameters
----------
lst: list
filter: function
Unary string filter function
Returns
-------
list
List of items that passed the filter
Example
-------
>>> l = ['12123123', 'N123213']
>>> filt = re.compile('\d*').match... | def filter_list(lst, filt):
"""
Parameters
----------
lst: list
filter: function
Unary string filter function
Returns
-------
list
List of items that passed the filter
Example
-------
>>> l = ['12123123', 'N123213']
>>> filt = re.compile('\d*').match... | [
"Parameters",
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/utils/strings.py#L34-L54 | [
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valid | match_list | Parameters
----------
lst: list of str
regex: string
group_names: list of strings
See re.MatchObject group docstring
Returns
-------
list of strings
Filtered list, with the strings that match the pattern | boyle/utils/strings.py | def match_list(lst, pattern, group_names=[]):
"""
Parameters
----------
lst: list of str
regex: string
group_names: list of strings
See re.MatchObject group docstring
Returns
-------
list of strings
Filtered list, with the strings that match the pattern
"""
... | def match_list(lst, pattern, group_names=[]):
"""
Parameters
----------
lst: list of str
regex: string
group_names: list of strings
See re.MatchObject group docstring
Returns
-------
list of strings
Filtered list, with the strings that match the pattern
"""
... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/utils/strings.py#L57-L78 | [
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valid | append_to_keys | Parameters
----------
adict:
preffix:
Returns
------- | boyle/utils/strings.py | def append_to_keys(adict, preffix):
"""
Parameters
----------
adict:
preffix:
Returns
-------
"""
return {preffix + str(key): (value if isinstance(value, dict) else value)
for key, value in list(adict.items())} | def append_to_keys(adict, preffix):
"""
Parameters
----------
adict:
preffix:
Returns
-------
"""
return {preffix + str(key): (value if isinstance(value, dict) else value)
for key, value in list(adict.items())} | [
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valid | is_valid_regex | Checks whether the re module can compile the given regular expression.
Parameters
----------
string: str
Returns
-------
boolean | boyle/utils/strings.py | def is_valid_regex(string):
"""
Checks whether the re module can compile the given regular expression.
Parameters
----------
string: str
Returns
-------
boolean
"""
try:
re.compile(string)
is_valid = True
except re.error:
is_valid = False
return ... | def is_valid_regex(string):
"""
Checks whether the re module can compile the given regular expression.
Parameters
----------
string: str
Returns
-------
boolean
"""
try:
re.compile(string)
is_valid = True
except re.error:
is_valid = False
return ... | [
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valid | is_regex | TODO: improve this!
Returns True if the given string is considered a regular expression,
False otherwise.
It will be considered a regex if starts with a non alphabetic character
and then correctly compiled by re.compile
:param string: str | boyle/utils/strings.py | def is_regex(string):
"""
TODO: improve this!
Returns True if the given string is considered a regular expression,
False otherwise.
It will be considered a regex if starts with a non alphabetic character
and then correctly compiled by re.compile
:param string: str
"""
is_regex = F... | def is_regex(string):
"""
TODO: improve this!
Returns True if the given string is considered a regular expression,
False otherwise.
It will be considered a regex if starts with a non alphabetic character
and then correctly compiled by re.compile
:param string: str
"""
is_regex = F... | [
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valid | is_fnmatch_regex | Returns True if the given string is considered a fnmatch
regular expression, False otherwise.
It will look for
:param string: str | boyle/utils/strings.py | def is_fnmatch_regex(string):
"""
Returns True if the given string is considered a fnmatch
regular expression, False otherwise.
It will look for
:param string: str
"""
is_regex = False
regex_chars = ['!', '*', '$']
for c in regex_chars:
if string.find(c) > -1:
r... | def is_fnmatch_regex(string):
"""
Returns True if the given string is considered a fnmatch
regular expression, False otherwise.
It will look for
:param string: str
"""
is_regex = False
regex_chars = ['!', '*', '$']
for c in regex_chars:
if string.find(c) > -1:
r... | [
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valid | where_is | Return index of the nth match found of pattern in strings
Parameters
----------
strings: list of str
List of strings
pattern: str
Pattern to be matched
nth: int
Number of times the match must happen to return the item index.
lookup_func: callable
Function to m... | boyle/utils/strings.py | def where_is(strings, pattern, n=1, lookup_func=re.match):
"""Return index of the nth match found of pattern in strings
Parameters
----------
strings: list of str
List of strings
pattern: str
Pattern to be matched
nth: int
Number of times the match must happen to retur... | def where_is(strings, pattern, n=1, lookup_func=re.match):
"""Return index of the nth match found of pattern in strings
Parameters
----------
strings: list of str
List of strings
pattern: str
Pattern to be matched
nth: int
Number of times the match must happen to retur... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/utils/strings.py#L209-L238 | [
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valid | generate_config | Generate a dcm2nii configuration file that disable the interactive
mode. | boyle/dicom/convert.py | def generate_config(output_directory):
""" Generate a dcm2nii configuration file that disable the interactive
mode.
"""
if not op.isdir(output_directory):
os.makedirs(output_directory)
config_file = op.join(output_directory, "config.ini")
open_file = open(config_file, "w")
open_file... | def generate_config(output_directory):
""" Generate a dcm2nii configuration file that disable the interactive
mode.
"""
if not op.isdir(output_directory):
os.makedirs(output_directory)
config_file = op.join(output_directory, "config.ini")
open_file = open(config_file, "w")
open_file... | [
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valid | add_meta_to_nii | Add slice duration and acquisition times to the headers of the nifit1 files in `nii_file`.
It will add the repetition time of the DICOM file (field: {0x0018, 0x0080, DS, Repetition Time})
to the NifTI file as well as any other tag in `dcm_tags`.
All selected DICOM tags values are set in the `descrip` nifti ... | boyle/dicom/convert.py | def add_meta_to_nii(nii_file, dicom_file, dcm_tags=''):
""" Add slice duration and acquisition times to the headers of the nifit1 files in `nii_file`.
It will add the repetition time of the DICOM file (field: {0x0018, 0x0080, DS, Repetition Time})
to the NifTI file as well as any other tag in `dcm_tags`.
... | def add_meta_to_nii(nii_file, dicom_file, dcm_tags=''):
""" Add slice duration and acquisition times to the headers of the nifit1 files in `nii_file`.
It will add the repetition time of the DICOM file (field: {0x0018, 0x0080, DS, Repetition Time})
to the NifTI file as well as any other tag in `dcm_tags`.
... | [
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valid | call_dcm2nii | Converts all DICOM files within `work_dir` into one or more
NifTi files by calling dcm2nii on this folder.
Parameters
----------
work_dir: str
Path to the folder that contain the DICOM files
arguments: str
String containing all the flag arguments for `dcm2nii` CLI.
Returns
... | boyle/dicom/convert.py | def call_dcm2nii(work_dir, arguments=''):
"""Converts all DICOM files within `work_dir` into one or more
NifTi files by calling dcm2nii on this folder.
Parameters
----------
work_dir: str
Path to the folder that contain the DICOM files
arguments: str
String containing all the f... | def call_dcm2nii(work_dir, arguments=''):
"""Converts all DICOM files within `work_dir` into one or more
NifTi files by calling dcm2nii on this folder.
Parameters
----------
work_dir: str
Path to the folder that contain the DICOM files
arguments: str
String containing all the f... | [
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valid | convert_dcm2nii | Call MRICron's `dcm2nii` to convert the DICOM files inside `input_dir`
to Nifti and save the Nifti file in `output_dir` with a `filename` prefix.
Parameters
----------
input_dir: str
Path to the folder that contains the DICOM files
output_dir: str
Path to the folder where to save t... | boyle/dicom/convert.py | def convert_dcm2nii(input_dir, output_dir, filename):
""" Call MRICron's `dcm2nii` to convert the DICOM files inside `input_dir`
to Nifti and save the Nifti file in `output_dir` with a `filename` prefix.
Parameters
----------
input_dir: str
Path to the folder that contains the DICOM files
... | def convert_dcm2nii(input_dir, output_dir, filename):
""" Call MRICron's `dcm2nii` to convert the DICOM files inside `input_dir`
to Nifti and save the Nifti file in `output_dir` with a `filename` prefix.
Parameters
----------
input_dir: str
Path to the folder that contains the DICOM files
... | [
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valid | remove_dcm2nii_underprocessed | Return a subset of `filepaths`. Keep only the files that have a basename longer than the
others with same suffix.
This works based on that dcm2nii appends a preffix character for each processing
step it does automatically in the DICOM to NifTI conversion.
Parameters
----------
filepaths: iterab... | boyle/dicom/convert.py | def remove_dcm2nii_underprocessed(filepaths):
""" Return a subset of `filepaths`. Keep only the files that have a basename longer than the
others with same suffix.
This works based on that dcm2nii appends a preffix character for each processing
step it does automatically in the DICOM to NifTI conversion... | def remove_dcm2nii_underprocessed(filepaths):
""" Return a subset of `filepaths`. Keep only the files that have a basename longer than the
others with same suffix.
This works based on that dcm2nii appends a preffix character for each processing
step it does automatically in the DICOM to NifTI conversion... | [
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valid | dictify | Transform a named tuple into a dictionary | boyle/more_collections.py | def dictify(a_named_tuple):
"""Transform a named tuple into a dictionary"""
return dict((s, getattr(a_named_tuple, s)) for s in a_named_tuple._fields) | def dictify(a_named_tuple):
"""Transform a named tuple into a dictionary"""
return dict((s, getattr(a_named_tuple, s)) for s in a_named_tuple._fields) | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/more_collections.py#L6-L8 | [
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] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | merge_dict_of_lists | Extend the within a dict of lists. The indices will indicate which
list have to be extended by which other list.
Parameters
----------
adict: OrderedDict
An ordered dictionary of lists
indices: list or tuple of 2 iterables of int, bot having the same length
The indices of the lists... | boyle/more_collections.py | def merge_dict_of_lists(adict, indices, pop_later=True, copy=True):
"""Extend the within a dict of lists. The indices will indicate which
list have to be extended by which other list.
Parameters
----------
adict: OrderedDict
An ordered dictionary of lists
indices: list or tuple of 2 it... | def merge_dict_of_lists(adict, indices, pop_later=True, copy=True):
"""Extend the within a dict of lists. The indices will indicate which
list have to be extended by which other list.
Parameters
----------
adict: OrderedDict
An ordered dictionary of lists
indices: list or tuple of 2 it... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/more_collections.py#L11-L61 | [
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valid | append_dict_values | Return a dict of lists from a list of dicts with the same keys.
For each dict in list_of_dicts with look for the values of the
given keys and append it to the output dict.
Parameters
----------
list_of_dicts: list of dicts
keys: list of str
List of keys to create in the output dict
... | boyle/more_collections.py | def append_dict_values(list_of_dicts, keys=None):
"""
Return a dict of lists from a list of dicts with the same keys.
For each dict in list_of_dicts with look for the values of the
given keys and append it to the output dict.
Parameters
----------
list_of_dicts: list of dicts
keys: lis... | def append_dict_values(list_of_dicts, keys=None):
"""
Return a dict of lists from a list of dicts with the same keys.
For each dict in list_of_dicts with look for the values of the
given keys and append it to the output dict.
Parameters
----------
list_of_dicts: list of dicts
keys: lis... | [
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valid | import_pyfile | Imports the contents of filepath as a Python module.
:param filepath: string
:param mod_name: string
Name of the module when imported
:return: module
Imported module | boyle/utils/imports.py | def import_pyfile(filepath, mod_name=None):
"""
Imports the contents of filepath as a Python module.
:param filepath: string
:param mod_name: string
Name of the module when imported
:return: module
Imported module
"""
import sys
if sys.version_info.major == 3:
import i... | def import_pyfile(filepath, mod_name=None):
"""
Imports the contents of filepath as a Python module.
:param filepath: string
:param mod_name: string
Name of the module when imported
:return: module
Imported module
"""
import sys
if sys.version_info.major == 3:
import i... | [
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"filepath",
"as",
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"Python",
"module",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/utils/imports.py#L6-L27 | [
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... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | copy | Copies the files in the built file tree map
to despath.
:param configfile: string
Path to the FileTreeMap config file
:param destpath: string
Path to the files destination
:param overwrite: bool
Overwrite files if they already exist.
:param sub_node: string
Tree map configura... | scripts/filetree.py | def copy(configfile='', destpath='', overwrite=False, sub_node=''):
"""Copies the files in the built file tree map
to despath.
:param configfile: string
Path to the FileTreeMap config file
:param destpath: string
Path to the files destination
:param overwrite: bool
Overwrite files ... | def copy(configfile='', destpath='', overwrite=False, sub_node=''):
"""Copies the files in the built file tree map
to despath.
:param configfile: string
Path to the FileTreeMap config file
:param destpath: string
Path to the files destination
:param overwrite: bool
Overwrite files ... | [
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"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/scripts/filetree.py#L20-L72 | [
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"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | idset_with_reference.get_noneid_references | Returns
-------
ndarray
Array of references in self.reflst whose self id is None. | scripts/compare_id_sets.py | def get_noneid_references(self):
"""
Returns
-------
ndarray
Array of references in self.reflst whose self id is None.
"""
#return [self.reflst[idx] for idx, idval in enumerate(self) if idval is None]
try:
nun = np.array(None).astype(self.dtype... | def get_noneid_references(self):
"""
Returns
-------
ndarray
Array of references in self.reflst whose self id is None.
"""
#return [self.reflst[idx] for idx, idval in enumerate(self) if idval is None]
try:
nun = np.array(None).astype(self.dtype... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/scripts/compare_id_sets.py#L157-L170 | [
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valid | idset_comparator._print_general_vs_table | :param idset1:
:param idset2: | scripts/compare_id_sets.py | def _print_general_vs_table(self, idset1, idset2):
"""
:param idset1:
:param idset2:
"""
ref1name = ''
set1_hasref = isinstance(idset1, idset_with_reference)
if set1_hasref:
ref1arr = np.array(idset1.reflst)
ref1name = idset1.refname
... | def _print_general_vs_table(self, idset1, idset2):
"""
:param idset1:
:param idset2:
"""
ref1name = ''
set1_hasref = isinstance(idset1, idset_with_reference)
if set1_hasref:
ref1arr = np.array(idset1.reflst)
ref1name = idset1.refname
... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/scripts/compare_id_sets.py#L233-L278 | [
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valid | idset_comparator._print_foreign_repetition_table | :param idset1:
:param idset2: | scripts/compare_id_sets.py | def _print_foreign_repetition_table(self, idset1, idset2):
"""
:param idset1:
:param idset2:
"""
assert(isinstance(idset1, idset_with_reference))
assert(isinstance(idset2, idset))
reps = idset2.get_repetitions()
if len(reps) < 1:
return
... | def _print_foreign_repetition_table(self, idset1, idset2):
"""
:param idset1:
:param idset2:
"""
assert(isinstance(idset1, idset_with_reference))
assert(isinstance(idset2, idset))
reps = idset2.get_repetitions()
if len(reps) < 1:
return
... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/scripts/compare_id_sets.py#L280-L308 | [
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valid | idset_comparator.print_compare_idsets_one_ref | idset1_name: string
key of an idset_with_reference
idset2_name: string
key of an idset | scripts/compare_id_sets.py | def print_compare_idsets_one_ref(self, idset1_name, idset2_name):
"""
idset1_name: string
key of an idset_with_reference
idset2_name: string
key of an idset
"""
try:
idset1 = self[idset1_name]
idset2 = self[idset2_name]
except KeyE... | def print_compare_idsets_one_ref(self, idset1_name, idset2_name):
"""
idset1_name: string
key of an idset_with_reference
idset2_name: string
key of an idset
"""
try:
idset1 = self[idset1_name]
idset2 = self[idset2_name]
except KeyE... | [
"idset1_name",
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"idset_with_reference"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/scripts/compare_id_sets.py#L342-L364 | [
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... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | convert_sav | Transforms the input .sav SPSS file into other format.
If you don't specify an outputfile, it will use the
inputfile and change its extension to .csv | scripts/convert_sav.py | def convert_sav(inputfile, outputfile=None, method='rpy2', otype='csv'):
""" Transforms the input .sav SPSS file into other format.
If you don't specify an outputfile, it will use the
inputfile and change its extension to .csv
"""
assert(os.path.isfile(inputfile))
assert(method=='rpy2' or method... | def convert_sav(inputfile, outputfile=None, method='rpy2', otype='csv'):
""" Transforms the input .sav SPSS file into other format.
If you don't specify an outputfile, it will use the
inputfile and change its extension to .csv
"""
assert(os.path.isfile(inputfile))
assert(method=='rpy2' or method... | [
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valid | load_mask | Load a Nifti mask volume.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affine() methods, e.g., nibabel.Nifti1Image.
If niimg is a string, consider it as a path... | boyle/nifti/mask.py | def load_mask(image, allow_empty=True):
"""Load a Nifti mask volume.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affine() methods, e.g., nibabel.Nifti1Image.
... | def load_mask(image, allow_empty=True):
"""Load a Nifti mask volume.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affine() methods, e.g., nibabel.Nifti1Image.
... | [
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"mask",
"volume",
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/mask.py#L23-L62 | [
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valid | load_mask_data | Load a Nifti mask volume and return its data matrix as boolean and affine.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affine() methods, e.g., nibabel.Nifti1Image.
... | boyle/nifti/mask.py | def load_mask_data(image, allow_empty=True):
"""Load a Nifti mask volume and return its data matrix as boolean and affine.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a file path to a Nifti image
- any object with get_data() and... | def load_mask_data(image, allow_empty=True):
"""Load a Nifti mask volume and return its data matrix as boolean and affine.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a file path to a Nifti image
- any object with get_data() and... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/mask.py#L65-L86 | [
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] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | union_mask | Creates a binarised mask with the union of the files in filelist.
Parameters
----------
filelist: list of img-like object or boyle.nifti.NeuroImage or str
List of paths to the volume files containing the ROIs.
Can either be:
- a file path to a Nifti image
- any object with g... | boyle/nifti/mask.py | def union_mask(filelist):
"""
Creates a binarised mask with the union of the files in filelist.
Parameters
----------
filelist: list of img-like object or boyle.nifti.NeuroImage or str
List of paths to the volume files containing the ROIs.
Can either be:
- a file path to a N... | def union_mask(filelist):
"""
Creates a binarised mask with the union of the files in filelist.
Parameters
----------
filelist: list of img-like object or boyle.nifti.NeuroImage or str
List of paths to the volume files containing the ROIs.
Can either be:
- a file path to a N... | [
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"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/mask.py#L113-L149 | [
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"# create space for all features and read from subjects",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | apply_mask | Read a Nifti file nii_file and a mask Nifti file.
Returns the voxels in nii_file that are within the mask, the mask indices
and the mask shape.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a file path to a Nifti image
- any o... | boyle/nifti/mask.py | def apply_mask(image, mask_img):
"""Read a Nifti file nii_file and a mask Nifti file.
Returns the voxels in nii_file that are within the mask, the mask indices
and the mask shape.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a fi... | def apply_mask(image, mask_img):
"""Read a Nifti file nii_file and a mask Nifti file.
Returns the voxels in nii_file that are within the mask, the mask indices
and the mask shape.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a fi... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/mask.py#L152-L190 | [
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... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | apply_mask_4d | Read a Nifti file nii_file and a mask Nifti file.
Extract the signals in nii_file that are within the mask, the mask indices
and the mask shape.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage or str
Can either be:
- a file path to a Nifti image
- any ... | boyle/nifti/mask.py | def apply_mask_4d(image, mask_img): # , smooth_mm=None, remove_nans=True):
"""Read a Nifti file nii_file and a mask Nifti file.
Extract the signals in nii_file that are within the mask, the mask indices
and the mask shape.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage ... | def apply_mask_4d(image, mask_img): # , smooth_mm=None, remove_nans=True):
"""Read a Nifti file nii_file and a mask Nifti file.
Extract the signals in nii_file that are within the mask, the mask indices
and the mask shape.
Parameters
----------
image: img-like object or boyle.nifti.NeuroImage ... | [
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] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/mask.py#L193-L241 | [
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"(",
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",",
"mask",
",",
"only_... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | vector_to_volume | Transform a given vector to a volume. This is a reshape function for
3D flattened and maybe masked vectors.
Parameters
----------
arr: np.array
1-Dimensional array
mask: numpy.ndarray
Mask image. Must have 3 dimensions, bool dtype.
Returns
-------
np.ndarray | boyle/nifti/mask.py | def vector_to_volume(arr, mask, order='C'):
"""Transform a given vector to a volume. This is a reshape function for
3D flattened and maybe masked vectors.
Parameters
----------
arr: np.array
1-Dimensional array
mask: numpy.ndarray
Mask image. Must have 3 dimensions, bool dtype.... | def vector_to_volume(arr, mask, order='C'):
"""Transform a given vector to a volume. This is a reshape function for
3D flattened and maybe masked vectors.
Parameters
----------
arr: np.array
1-Dimensional array
mask: numpy.ndarray
Mask image. Must have 3 dimensions, bool dtype.... | [
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"for",
"3D",
"flattened",
"and",
"maybe",
"masked",
"vectors",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/mask.py#L267-L295 | [
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"!=",
"1",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | matrix_to_4dvolume | Transform a given vector to a volume. This is a reshape function for
4D flattened masked matrices where the second dimension of the matrix
corresponds to the original 4th dimension.
Parameters
----------
arr: numpy.array
2D numpy.array
mask: numpy.ndarray
Mask image. Must have ... | boyle/nifti/mask.py | def matrix_to_4dvolume(arr, mask, order='C'):
"""Transform a given vector to a volume. This is a reshape function for
4D flattened masked matrices where the second dimension of the matrix
corresponds to the original 4th dimension.
Parameters
----------
arr: numpy.array
2D numpy.array
... | def matrix_to_4dvolume(arr, mask, order='C'):
"""Transform a given vector to a volume. This is a reshape function for
4D flattened masked matrices where the second dimension of the matrix
corresponds to the original 4th dimension.
Parameters
----------
arr: numpy.array
2D numpy.array
... | [
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"corresponds",
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"original",
"4t... | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/mask.py#L298-L333 | [
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"ndim",
"!=",
"2",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
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