INSTRUCTION stringlengths 1 8.43k | RESPONSE stringlengths 75 104k |
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Execute create update delete operations on existing reliable dictionaries. | 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... |
Verify arguments for select command | 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... |
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 directory of truste... | 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... |
Get AAD token | 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... |
Use openpyxl to read an Excel file. | 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 |
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. | 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... |
Return the workbook from the Excel file in 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) |
Return a list with the name of the sheets in the Excel file in xl_path. | 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() |
Return a pandas DataFrame with the concat ed content of the sheetnames from the Excel file in xl_path. | 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... |
Raise an AttributeError if df does not have a column named as an item of the list of strings col_names. | 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,
... |
Return a list of not null values from the col_name column of df. | 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... |
Return a DataFrame with the duplicated values of the column col_name in df. | 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 |
Return the duplicated items in values | def duplicated(values: Sequence):
""" Return the duplicated items in `values`"""
vals = pd.Series(values)
return vals[vals.duplicated()] |
Serialize a date/ time value into an ISO8601 text representation adjusted ( if needed ) to UTC timezone. | 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:
... |
Convert to string all values in data. | 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_... |
Insert data into table ensuring that data has unique values in table for the fields listed in 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
another item with the same `unique_fields... |
Search for items in table that have the same field sub - set values as in sample. | 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 ... |
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. | 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
... |
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. | 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... |
Create a TinyDB query that looks for items that have each field in sample with a value compared with the correspondent operation in operators. | 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
... |
Create a tinyDB Query object that looks for items that confirms the correspondent operator from operators for each field_names field values from data. | 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... |
Create a tinyDB Query object that is the concatenation of each query in queries. The concatenation operator is taken from operators. | 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... |
Create a tinyDB Query object with the format: ( where ( field_name ) operator field_value ) | 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... |
Return the element in table_name with Object ID eid. If None is found will raise a KeyError exception. | 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... |
Insert data into table ensuring that data has unique values in table for the fields listed in unique_fields. | 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... |
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. | 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... |
Search for items in table that have the same field sub - set values as in sample. | 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
... |
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. | 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... |
Update the unique matching element to have a given set of fields. | 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]... |
Return the number of items that match the sample field values in table table_name. Check function search_sample for more details. | 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... |
Check for get_data and get_affine method in an object | 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:
... |
Get the data in the image without having a side effect on the Nifti1Image object | 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... |
Return the shape of img. | 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 |
Return True if the given ( i j k ) voxel grid coordinate values are within the img boundaries. | 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... |
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. | 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... |
Return True if the affine matrix of one_img is close to the affine matrix of another_img. False otherwise. | 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... |
Enforce that img is a 3D img - like object if it is not raise a TypeError. i. e. remove dimensions of size 1. | 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... |
Check that image is a proper img. Turn filenames into objects. | 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... |
Printing of img or imgs | 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... |
Returns true if array1 and array2 have the same shapes false otherwise. | 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... |
@param fname1: string File path of an image | 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... |
@param fname1: string File path of an image | 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()
... |
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. | 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... |
Returns absolute paths of folders that match the regex within folder_path and all its children folders. | 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: ... |
Creates a list of files that match the search_regex within file_dir. The list of files will have file_dir as path prefix. | 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 ... |
Returns absolute paths of files that match the regex within file_dir and all its children folders. | 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... |
Returns absolute paths of files that match the regexs within folder_path and all its children folders. | 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... |
Generator that loops through all absolute paths of the files within folder | 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... |
Uses glob to find all files or folders that match the regex starting from the base_directory. | 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... |
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. | 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... |
Append key - value pairs to msg for display. | 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... |
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. | 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... |
Copy the DICOM file groups to folder_path. Each group will be copied into a subfolder with named given by groupby_field. | 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 ... |
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. | 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... |
Parameters ---------- dcm_file1: str ( path to file ) or DicomFile or namedtuple | 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) |
Check the field values in self. dcmf1 and self. dcmf2 and returns True if all the field values are the same False otherwise. | 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_... |
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. | 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 ... |
Thresholds a distance matrix and returns the result. | 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... |
Returns a list of 2 - tuples with pairs of dicom groups that are in the same folder within given depth. | 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
... |
Plots dist_matrix | 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',
... |
Extend the lists within the DICOM groups dictionary. The indices will indicate which list have to be extended by which other list. | 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
... |
Copy the file groups to folder_path. Each group will be copied into a subfolder with named given by groupby_field. | 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... |
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. | 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... |
Gets a config by name. | 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) |
Checks if a config value is set to a valid bool value. | 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) |
Set a config by name to a 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) |
Path to certificate related files either a single file path or a tuple. In the case of no security returns None. | 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... |
Set AAD token 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)) |
Set AAD metadata. | 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) |
Set certificate usage paths | 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:
... |
Returns a list with of the objects in olist that have a fieldname valued as fieldval | 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 ... |
Parameters ---------- lst: list | 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 ---------- lst: list of str | 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
"""
... |
Parameters ---------- adict: preffix: | 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())} |
Checks whether the re module can compile the given regular expression. | 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 ... |
TODO: improve this! | 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... |
Returns True if the given string is considered a fnmatch regular expression False otherwise. It will look for | 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... |
Return index of the nth match found of pattern in strings | 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... |
Generate a dcm2nii configuration file that disable the interactive mode. | 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... |
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 header field. Not... | 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`.
... |
Converts all DICOM files within work_dir into one or more NifTi files by calling dcm2nii on this folder. | 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... |
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. | 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
... |
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... |
Transform a named tuple into a dictionary | 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) |
Extend the within a dict of lists. The indices will indicate which list have to be extended by which other list. | 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... |
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. | 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... |
Imports the contents of filepath as a Python module. | 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... |
Copies the files in the built file tree map to despath. | 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 ... |
Returns ------- ndarray Array of references in self. reflst whose self id is None. | 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... |
: param idset1:: param idset2: | 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
... |
: param idset1:: param idset2: | 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
... |
idset1_name: string key of an idset_with_reference | 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... |
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 | 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... |
Load a Nifti mask volume. | 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.
... |
Load a Nifti mask volume and return its data matrix as boolean and affine. | 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... |
Creates a binarised mask with the union of the files in filelist. | 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... |
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. | 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... |
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. | 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 ... |
Transform a given vector to a volume. This is a reshape function for 3D flattened and maybe masked vectors. | 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.... |
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. | 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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