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 | NiftiSubjectsSet._load_image | Parameters
----------
file_path: str
Path to the nifti file
Returns
-------
nipy.Image with a file_path member | boyle/nifti/sets.py | def _load_image(file_path):
"""
Parameters
----------
file_path: str
Path to the nifti file
Returns
-------
nipy.Image with a file_path member
"""
if not os.path.exists(file_path):
raise FileNotFound(file_path)
try... | def _load_image(file_path):
"""
Parameters
----------
file_path: str
Path to the nifti file
Returns
-------
nipy.Image with a file_path member
"""
if not os.path.exists(file_path):
raise FileNotFound(file_path)
try... | [
"Parameters",
"----------",
"file_path",
":",
"str",
"Path",
"to",
"the",
"nifti",
"file"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/sets.py#L381-L400 | [
"def",
"_load_image",
"(",
"file_path",
")",
":",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"file_path",
")",
":",
"raise",
"FileNotFound",
"(",
"file_path",
")",
"try",
":",
"nii_img",
"=",
"load_nipy_img",
"(",
"file_path",
")",
"nii_img",
".... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NiftiSubjectsSet._smooth_img | Parameters
----------
nii_img: nipy.Image
smooth_fwhm: float
Returns
-------
smoothed nipy.Image | boyle/nifti/sets.py | def _smooth_img(nii_img, smooth_fwhm):
"""
Parameters
----------
nii_img: nipy.Image
smooth_fwhm: float
Returns
-------
smoothed nipy.Image
"""
# delayed import because could not install nipy on Python 3 on OSX
from nipy.algorit... | def _smooth_img(nii_img, smooth_fwhm):
"""
Parameters
----------
nii_img: nipy.Image
smooth_fwhm: float
Returns
-------
smoothed nipy.Image
"""
# delayed import because could not install nipy on Python 3 on OSX
from nipy.algorit... | [
"Parameters",
"----------",
"nii_img",
":",
"nipy",
".",
"Image"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/sets.py#L403-L422 | [
"def",
"_smooth_img",
"(",
"nii_img",
",",
"smooth_fwhm",
")",
":",
"# delayed import because could not install nipy on Python 3 on OSX",
"from",
"nipy",
".",
"algorithms",
".",
"kernel_smooth",
"import",
"LinearFilter",
"if",
"smooth_fwhm",
"<=",
"0",
":",
"return",
"n... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NiftiSubjectsSet.from_dict | Parameters
----------
subj_files: dict of str
file_path -> int/str | boyle/nifti/sets.py | def from_dict(self, subj_files):
"""
Parameters
----------
subj_files: dict of str
file_path -> int/str
"""
for group_label in subj_files:
try:
group_files = subj_files[group_label]
self.items.extend([self._load_imag... | def from_dict(self, subj_files):
"""
Parameters
----------
subj_files: dict of str
file_path -> int/str
"""
for group_label in subj_files:
try:
group_files = subj_files[group_label]
self.items.extend([self._load_imag... | [
"Parameters",
"----------",
"subj_files",
":",
"dict",
"of",
"str",
"file_path",
"-",
">",
"int",
"/",
"str"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/sets.py#L424-L440 | [
"def",
"from_dict",
"(",
"self",
",",
"subj_files",
")",
":",
"for",
"group_label",
"in",
"subj_files",
":",
"try",
":",
"group_files",
"=",
"subj_files",
"[",
"group_label",
"]",
"self",
".",
"items",
".",
"extend",
"(",
"[",
"self",
".",
"_load_image",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NiftiSubjectsSet.from_list | Parameters
----------
subj_files: list of str
file_paths | boyle/nifti/sets.py | def from_list(self, subj_files):
"""
Parameters
----------
subj_files: list of str
file_paths
"""
for sf in subj_files:
try:
nii_img = self._load_image(get_abspath(sf))
self.items.append(nii_img)
except E... | def from_list(self, subj_files):
"""
Parameters
----------
subj_files: list of str
file_paths
"""
for sf in subj_files:
try:
nii_img = self._load_image(get_abspath(sf))
self.items.append(nii_img)
except E... | [
"Parameters",
"----------",
"subj_files",
":",
"list",
"of",
"str",
"file_paths"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/sets.py#L442-L454 | [
"def",
"from_list",
"(",
"self",
",",
"subj_files",
")",
":",
"for",
"sf",
"in",
"subj_files",
":",
"try",
":",
"nii_img",
"=",
"self",
".",
"_load_image",
"(",
"get_abspath",
"(",
"sf",
")",
")",
"self",
".",
"items",
".",
"append",
"(",
"nii_img",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NiftiSubjectsSet.set_labels | Parameters
----------
subj_labels: list of int or str
This list will be checked to have the same size as files list
(self.items) | boyle/nifti/sets.py | def set_labels(self, subj_labels):
"""
Parameters
----------
subj_labels: list of int or str
This list will be checked to have the same size as files list
(self.items)
"""
if len(subj_labels) != self.n_subjs:
raise ValueError('The numbe... | def set_labels(self, subj_labels):
"""
Parameters
----------
subj_labels: list of int or str
This list will be checked to have the same size as files list
(self.items)
"""
if len(subj_labels) != self.n_subjs:
raise ValueError('The numbe... | [
"Parameters",
"----------",
"subj_labels",
":",
"list",
"of",
"int",
"or",
"str",
"This",
"list",
"will",
"be",
"checked",
"to",
"have",
"the",
"same",
"size",
"as",
"files",
"list",
"(",
"self",
".",
"items",
")"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/sets.py#L469-L480 | [
"def",
"set_labels",
"(",
"self",
",",
"subj_labels",
")",
":",
"if",
"len",
"(",
"subj_labels",
")",
"!=",
"self",
".",
"n_subjs",
":",
"raise",
"ValueError",
"(",
"'The number of given labels is not the same as the number of subjects.'",
")",
"self",
".",
"labels"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NiftiSubjectsSet.to_matrix | Create a Numpy array with the data and return the relevant information (mask indices and volume shape).
Parameters
----------
smooth_fwhm: int
Integer indicating the size of the FWHM Gaussian smoothing kernel
to smooth the subject volumes before creating the data matrix
... | boyle/nifti/sets.py | def to_matrix(self, smooth_fwhm=0, outdtype=None):
"""Create a Numpy array with the data and return the relevant information (mask indices and volume shape).
Parameters
----------
smooth_fwhm: int
Integer indicating the size of the FWHM Gaussian smoothing kernel
... | def to_matrix(self, smooth_fwhm=0, outdtype=None):
"""Create a Numpy array with the data and return the relevant information (mask indices and volume shape).
Parameters
----------
smooth_fwhm: int
Integer indicating the size of the FWHM Gaussian smoothing kernel
... | [
"Create",
"a",
"Numpy",
"array",
"with",
"the",
"data",
"and",
"return",
"the",
"relevant",
"information",
"(",
"mask",
"indices",
"and",
"volume",
"shape",
")",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/sets.py#L482-L536 | [
"def",
"to_matrix",
"(",
"self",
",",
"smooth_fwhm",
"=",
"0",
",",
"outdtype",
"=",
"None",
")",
":",
"vol",
"=",
"self",
".",
"items",
"[",
"0",
"]",
".",
"get_data",
"(",
")",
"if",
"not",
"outdtype",
":",
"outdtype",
"=",
"vol",
".",
"dtype",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | die | Writes msg to stderr and exits with return code | boyle/commands.py | def die(msg, code=-1):
"""Writes msg to stderr and exits with return code"""
sys.stderr.write(msg + "\n")
sys.exit(code) | def die(msg, code=-1):
"""Writes msg to stderr and exits with return code"""
sys.stderr.write(msg + "\n")
sys.exit(code) | [
"Writes",
"msg",
"to",
"stderr",
"and",
"exits",
"with",
"return",
"code"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/commands.py#L68-L71 | [
"def",
"die",
"(",
"msg",
",",
"code",
"=",
"-",
"1",
")",
":",
"sys",
".",
"stderr",
".",
"write",
"(",
"msg",
"+",
"\"\\n\"",
")",
"sys",
".",
"exit",
"(",
"code",
")"
] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | check_call | Calls the command
Parameters
----------
cmd_args: list of str
Command name to call and its arguments in a list.
Returns
-------
Command output | boyle/commands.py | def check_call(cmd_args):
"""
Calls the command
Parameters
----------
cmd_args: list of str
Command name to call and its arguments in a list.
Returns
-------
Command output
"""
p = subprocess.Popen(cmd_args, stdout=subprocess.PIPE)
(output, err) = p.communicate()
... | def check_call(cmd_args):
"""
Calls the command
Parameters
----------
cmd_args: list of str
Command name to call and its arguments in a list.
Returns
-------
Command output
"""
p = subprocess.Popen(cmd_args, stdout=subprocess.PIPE)
(output, err) = p.communicate()
... | [
"Calls",
"the",
"command"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/commands.py#L74-L89 | [
"def",
"check_call",
"(",
"cmd_args",
")",
":",
"p",
"=",
"subprocess",
".",
"Popen",
"(",
"cmd_args",
",",
"stdout",
"=",
"subprocess",
".",
"PIPE",
")",
"(",
"output",
",",
"err",
")",
"=",
"p",
".",
"communicate",
"(",
")",
"return",
"output"
] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | call_command | Call CLI command with arguments and returns its return value.
Parameters
----------
cmd_name: str
Command name or full path to the binary file.
arg_strings: list of str
Argument strings list.
Returns
-------
return_value
Command return value. | boyle/commands.py | def call_command(cmd_name, args_strings):
"""Call CLI command with arguments and returns its return value.
Parameters
----------
cmd_name: str
Command name or full path to the binary file.
arg_strings: list of str
Argument strings list.
Returns
-------
return_value
... | def call_command(cmd_name, args_strings):
"""Call CLI command with arguments and returns its return value.
Parameters
----------
cmd_name: str
Command name or full path to the binary file.
arg_strings: list of str
Argument strings list.
Returns
-------
return_value
... | [
"Call",
"CLI",
"command",
"with",
"arguments",
"and",
"returns",
"its",
"return",
"value",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/commands.py#L92-L124 | [
"def",
"call_command",
"(",
"cmd_name",
",",
"args_strings",
")",
":",
"if",
"not",
"op",
".",
"isabs",
"(",
"cmd_name",
")",
":",
"cmd_fullpath",
"=",
"which",
"(",
"cmd_name",
")",
"else",
":",
"cmd_fullpath",
"=",
"cmd_name",
"try",
":",
"cmd_line",
"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | condor_call | Tries to submit cmd to HTCondor, if it does not succeed, it will
be called with subprocess.call.
Parameters
----------
cmd: string
Command to be submitted
Returns
------- | boyle/commands.py | def condor_call(cmd, shell=True):
"""
Tries to submit cmd to HTCondor, if it does not succeed, it will
be called with subprocess.call.
Parameters
----------
cmd: string
Command to be submitted
Returns
-------
"""
log.info(cmd)
ret = condor_submit(cmd)
if ret != ... | def condor_call(cmd, shell=True):
"""
Tries to submit cmd to HTCondor, if it does not succeed, it will
be called with subprocess.call.
Parameters
----------
cmd: string
Command to be submitted
Returns
-------
"""
log.info(cmd)
ret = condor_submit(cmd)
if ret != ... | [
"Tries",
"to",
"submit",
"cmd",
"to",
"HTCondor",
"if",
"it",
"does",
"not",
"succeed",
"it",
"will",
"be",
"called",
"with",
"subprocess",
".",
"call",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/commands.py#L127-L143 | [
"def",
"condor_call",
"(",
"cmd",
",",
"shell",
"=",
"True",
")",
":",
"log",
".",
"info",
"(",
"cmd",
")",
"ret",
"=",
"condor_submit",
"(",
"cmd",
")",
"if",
"ret",
"!=",
"0",
":",
"subprocess",
".",
"call",
"(",
"cmd",
",",
"shell",
"=",
"shel... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | condor_submit | Submits cmd to HTCondor queue
Parameters
----------
cmd: string
Command to be submitted
Returns
-------
int
returncode value from calling the submission command. | boyle/commands.py | def condor_submit(cmd):
"""
Submits cmd to HTCondor queue
Parameters
----------
cmd: string
Command to be submitted
Returns
-------
int
returncode value from calling the submission command.
"""
is_running = subprocess.call('condor_status', shell=True) == 0
i... | def condor_submit(cmd):
"""
Submits cmd to HTCondor queue
Parameters
----------
cmd: string
Command to be submitted
Returns
-------
int
returncode value from calling the submission command.
"""
is_running = subprocess.call('condor_status', shell=True) == 0
i... | [
"Submits",
"cmd",
"to",
"HTCondor",
"queue"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/commands.py#L146-L169 | [
"def",
"condor_submit",
"(",
"cmd",
")",
":",
"is_running",
"=",
"subprocess",
".",
"call",
"(",
"'condor_status'",
",",
"shell",
"=",
"True",
")",
"==",
"0",
"if",
"not",
"is_running",
":",
"raise",
"CalledProcessError",
"(",
"'HTCondor is not running.'",
")"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | clean | Clean previously built package artifacts. | tasks.py | def clean(ctx):
"""Clean previously built package artifacts.
"""
ctx.run(f'python setup.py clean')
dist = ROOT.joinpath('dist')
print(f'removing {dist}')
shutil.rmtree(str(dist)) | def clean(ctx):
"""Clean previously built package artifacts.
"""
ctx.run(f'python setup.py clean')
dist = ROOT.joinpath('dist')
print(f'removing {dist}')
shutil.rmtree(str(dist)) | [
"Clean",
"previously",
"built",
"package",
"artifacts",
"."
] | sarugaku/pipfile-cli | python | https://github.com/sarugaku/pipfile-cli/blob/ee9f8d1137e7423d2adc7e5748e8287b4402903d/tasks.py#L21-L27 | [
"def",
"clean",
"(",
"ctx",
")",
":",
"ctx",
".",
"run",
"(",
"f'python setup.py clean'",
")",
"dist",
"=",
"ROOT",
".",
"joinpath",
"(",
"'dist'",
")",
"print",
"(",
"f'removing {dist}'",
")",
"shutil",
".",
"rmtree",
"(",
"str",
"(",
"dist",
")",
")"... | ee9f8d1137e7423d2adc7e5748e8287b4402903d |
valid | upload | Upload the package to an index server.
This implies cleaning and re-building the package.
:param repo: Required. Name of the index server to upload to, as specifies
in your .pypirc configuration file. | tasks.py | def upload(ctx, repo):
"""Upload the package to an index server.
This implies cleaning and re-building the package.
:param repo: Required. Name of the index server to upload to, as specifies
in your .pypirc configuration file.
"""
artifacts = ' '.join(
shlex.quote(str(n))
f... | def upload(ctx, repo):
"""Upload the package to an index server.
This implies cleaning and re-building the package.
:param repo: Required. Name of the index server to upload to, as specifies
in your .pypirc configuration file.
"""
artifacts = ' '.join(
shlex.quote(str(n))
f... | [
"Upload",
"the",
"package",
"to",
"an",
"index",
"server",
"."
] | sarugaku/pipfile-cli | python | https://github.com/sarugaku/pipfile-cli/blob/ee9f8d1137e7423d2adc7e5748e8287b4402903d/tasks.py#L31-L43 | [
"def",
"upload",
"(",
"ctx",
",",
"repo",
")",
":",
"artifacts",
"=",
"' '",
".",
"join",
"(",
"shlex",
".",
"quote",
"(",
"str",
"(",
"n",
")",
")",
"for",
"n",
"in",
"ROOT",
".",
"joinpath",
"(",
"'dist'",
")",
".",
"glob",
"(",
"'pipfile[-_]cl... | ee9f8d1137e7423d2adc7e5748e8287b4402903d |
valid | SFCommandLoader.load_command_table | Load all Service Fabric commands | rcctl/rcctl/commands.py | def load_command_table(self, args): #pylint: disable=too-many-statements
"""Load all Service Fabric commands"""
# Need an empty client for the select and upload operations
with CommandSuperGroup(__name__, self,
'rcctl.custom_cluster#{}') as super_group:
... | def load_command_table(self, args): #pylint: disable=too-many-statements
"""Load all Service Fabric commands"""
# Need an empty client for the select and upload operations
with CommandSuperGroup(__name__, self,
'rcctl.custom_cluster#{}') as super_group:
... | [
"Load",
"all",
"Service",
"Fabric",
"commands"
] | shalabhms/reliable-collections-cli | python | https://github.com/shalabhms/reliable-collections-cli/blob/195d69816fb5a6e1e9ab0ab66b606b1248b4780d/rcctl/rcctl/commands.py#L33-L60 | [
"def",
"load_command_table",
"(",
"self",
",",
"args",
")",
":",
"#pylint: disable=too-many-statements",
"# Need an empty client for the select and upload operations",
"with",
"CommandSuperGroup",
"(",
"__name__",
",",
"self",
",",
"'rcctl.custom_cluster#{}'",
")",
"as",
"sup... | 195d69816fb5a6e1e9ab0ab66b606b1248b4780d |
valid | open_volume_file | Open a volumetric file using the tools following the file extension.
Parameters
----------
filepath: str
Path to a volume file
Returns
-------
volume_data: np.ndarray
Volume data
pixdim: 1xN np.ndarray
Vector with the description of the voxels physical size (usuall... | boyle/image/utils.py | def open_volume_file(filepath):
"""Open a volumetric file using the tools following the file extension.
Parameters
----------
filepath: str
Path to a volume file
Returns
-------
volume_data: np.ndarray
Volume data
pixdim: 1xN np.ndarray
Vector with the descript... | def open_volume_file(filepath):
"""Open a volumetric file using the tools following the file extension.
Parameters
----------
filepath: str
Path to a volume file
Returns
-------
volume_data: np.ndarray
Volume data
pixdim: 1xN np.ndarray
Vector with the descript... | [
"Open",
"a",
"volumetric",
"file",
"using",
"the",
"tools",
"following",
"the",
"file",
"extension",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/utils.py#L32-L93 | [
"def",
"open_volume_file",
"(",
"filepath",
")",
":",
"# check if the file exists",
"if",
"not",
"op",
".",
"exists",
"(",
"filepath",
")",
":",
"raise",
"IOError",
"(",
"'Could not find file {}.'",
".",
"format",
"(",
"filepath",
")",
")",
"# define helper functi... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | _check_medimg | 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 medical image file, e.g. NifTI, .mhd/raw, .mha
- any object with get_data() method and affine & header attributes, e.g., nibabel.Nifti... | boyle/image/utils.py | def _check_medimg(image, make_it_3d=True):
"""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 medical image file, e.g. NifTI, .mhd/raw, .mha
- any object with get_data() method a... | def _check_medimg(image, make_it_3d=True):
"""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 medical image file, e.g. NifTI, .mhd/raw, .mha
- any object with get_data() method a... | [
"Check",
"that",
"image",
"is",
"a",
"proper",
"img",
".",
"Turn",
"filenames",
"into",
"objects",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/utils.py#L96-L137 | [
"def",
"_check_medimg",
"(",
"image",
",",
"make_it_3d",
"=",
"True",
")",
":",
"if",
"isinstance",
"(",
"image",
",",
"string_types",
")",
":",
"# a filename, load it",
"img",
"=",
"open_volume_file",
"(",
"image",
")",
"if",
"make_it_3d",
":",
"img",
"=",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | rename_file_group_to_serial_nums | Will rename all files in file_lst to a padded serial
number plus its extension
:param file_lst: list of path.py paths | boyle/dicom/sets.py | def rename_file_group_to_serial_nums(file_lst):
"""Will rename all files in file_lst to a padded serial
number plus its extension
:param file_lst: list of path.py paths
"""
file_lst.sort()
c = 1
for f in file_lst:
dirname = get_abspath(f.dirname())
fdest = f.joinpath(dirname... | def rename_file_group_to_serial_nums(file_lst):
"""Will rename all files in file_lst to a padded serial
number plus its extension
:param file_lst: list of path.py paths
"""
file_lst.sort()
c = 1
for f in file_lst:
dirname = get_abspath(f.dirname())
fdest = f.joinpath(dirname... | [
"Will",
"rename",
"all",
"files",
"in",
"file_lst",
"to",
"a",
"padded",
"serial",
"number",
"plus",
"its",
"extension"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/sets.py#L291-L305 | [
"def",
"rename_file_group_to_serial_nums",
"(",
"file_lst",
")",
":",
"file_lst",
".",
"sort",
"(",
")",
"c",
"=",
"1",
"for",
"f",
"in",
"file_lst",
":",
"dirname",
"=",
"get_abspath",
"(",
"f",
".",
"dirname",
"(",
")",
")",
"fdest",
"=",
"f",
".",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | DicomFileSet._store_dicom_paths | Search for dicoms in folders and save file paths into
self.dicom_paths set.
:param folders: str or list of str | boyle/dicom/sets.py | def _store_dicom_paths(self, folders):
"""Search for dicoms in folders and save file paths into
self.dicom_paths set.
:param folders: str or list of str
"""
if isinstance(folders, str):
folders = [folders]
for folder in folders:
if not os.path.e... | def _store_dicom_paths(self, folders):
"""Search for dicoms in folders and save file paths into
self.dicom_paths set.
:param folders: str or list of str
"""
if isinstance(folders, str):
folders = [folders]
for folder in folders:
if not os.path.e... | [
"Search",
"for",
"dicoms",
"in",
"folders",
"and",
"save",
"file",
"paths",
"into",
"self",
".",
"dicom_paths",
"set",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/sets.py#L29-L43 | [
"def",
"_store_dicom_paths",
"(",
"self",
",",
"folders",
")",
":",
"if",
"isinstance",
"(",
"folders",
",",
"str",
")",
":",
"folders",
"=",
"[",
"folders",
"]",
"for",
"folder",
"in",
"folders",
":",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | DicomFileSet.from_set | Overwrites self.items with the given set of files.
Will filter the fileset and keep only Dicom files.
Parameters
----------
fileset: iterable of str
Paths to files
check_if_dicoms: bool
Whether to check if the items in fileset are dicom file paths | boyle/dicom/sets.py | def from_set(self, fileset, check_if_dicoms=True):
"""Overwrites self.items with the given set of files.
Will filter the fileset and keep only Dicom files.
Parameters
----------
fileset: iterable of str
Paths to files
check_if_dicoms: bool
Whether to che... | def from_set(self, fileset, check_if_dicoms=True):
"""Overwrites self.items with the given set of files.
Will filter the fileset and keep only Dicom files.
Parameters
----------
fileset: iterable of str
Paths to files
check_if_dicoms: bool
Whether to che... | [
"Overwrites",
"self",
".",
"items",
"with",
"the",
"given",
"set",
"of",
"files",
".",
"Will",
"filter",
"the",
"fileset",
"and",
"keep",
"only",
"Dicom",
"files",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/sets.py#L57-L75 | [
"def",
"from_set",
"(",
"self",
",",
"fileset",
",",
"check_if_dicoms",
"=",
"True",
")",
":",
"if",
"check_if_dicoms",
":",
"self",
".",
"items",
"=",
"[",
"]",
"for",
"f",
"in",
"fileset",
":",
"if",
"is_dicom_file",
"(",
"f",
")",
":",
"self",
"."... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | DicomFileSet.update | Update this set with the union of itself and dicomset.
Parameters
----------
dicomset: DicomFileSet | boyle/dicom/sets.py | def update(self, dicomset):
"""Update this set with the union of itself and dicomset.
Parameters
----------
dicomset: DicomFileSet
"""
if not isinstance(dicomset, DicomFileSet):
raise ValueError('Given dicomset is not a DicomFileSet.')
self.items = l... | def update(self, dicomset):
"""Update this set with the union of itself and dicomset.
Parameters
----------
dicomset: DicomFileSet
"""
if not isinstance(dicomset, DicomFileSet):
raise ValueError('Given dicomset is not a DicomFileSet.')
self.items = l... | [
"Update",
"this",
"set",
"with",
"the",
"union",
"of",
"itself",
"and",
"dicomset",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/sets.py#L77-L87 | [
"def",
"update",
"(",
"self",
",",
"dicomset",
")",
":",
"if",
"not",
"isinstance",
"(",
"dicomset",
",",
"DicomFileSet",
")",
":",
"raise",
"ValueError",
"(",
"'Given dicomset is not a DicomFileSet.'",
")",
"self",
".",
"items",
"=",
"list",
"(",
"set",
"("... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | DicomFileSet.copy_files_to_other_folder | Copies all files within this set to the output_folder
Parameters
----------
output_folder: str
Path of the destination folder of the files
rename_files: bool
Whether or not rename the files to a sequential format
mkdir: bool
Whether to make the folder i... | boyle/dicom/sets.py | def copy_files_to_other_folder(self, output_folder, rename_files=True,
mkdir=True, verbose=False):
"""
Copies all files within this set to the output_folder
Parameters
----------
output_folder: str
Path of the destination folder of the ... | def copy_files_to_other_folder(self, output_folder, rename_files=True,
mkdir=True, verbose=False):
"""
Copies all files within this set to the output_folder
Parameters
----------
output_folder: str
Path of the destination folder of the ... | [
"Copies",
"all",
"files",
"within",
"this",
"set",
"to",
"the",
"output_folder"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/sets.py#L89-L126 | [
"def",
"copy_files_to_other_folder",
"(",
"self",
",",
"output_folder",
",",
"rename_files",
"=",
"True",
",",
"mkdir",
"=",
"True",
",",
"verbose",
"=",
"False",
")",
":",
"import",
"shutil",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"output_fol... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | DicomGenericSet.get_dcm_reader | Creates a lambda function to read DICOM files.
If store_store_metadata is False, will only return the file path.
Else if you give header_fields, will return only the set of of
header_fields within a DicomFile object or the whole DICOM file if
None.
:return: function
This... | boyle/dicom/sets.py | def get_dcm_reader(store_metadata=True, header_fields=None):
"""
Creates a lambda function to read DICOM files.
If store_store_metadata is False, will only return the file path.
Else if you give header_fields, will return only the set of of
header_fields within a DicomFile object... | def get_dcm_reader(store_metadata=True, header_fields=None):
"""
Creates a lambda function to read DICOM files.
If store_store_metadata is False, will only return the file path.
Else if you give header_fields, will return only the set of of
header_fields within a DicomFile object... | [
"Creates",
"a",
"lambda",
"function",
"to",
"read",
"DICOM",
"files",
".",
"If",
"store_store_metadata",
"is",
"False",
"will",
"only",
"return",
"the",
"file",
"path",
".",
"Else",
"if",
"you",
"give",
"header_fields",
"will",
"return",
"only",
"the",
"set"... | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/sets.py#L151-L171 | [
"def",
"get_dcm_reader",
"(",
"store_metadata",
"=",
"True",
",",
"header_fields",
"=",
"None",
")",
":",
"if",
"not",
"store_metadata",
":",
"return",
"lambda",
"fpath",
":",
"fpath",
"if",
"header_fields",
"is",
"None",
":",
"build_dcm",
"=",
"lambda",
"fp... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | DicomGenericSet.scrape_all_files | Generator that yields one by one the return value for self.read_dcm
for each file within this set | boyle/dicom/sets.py | def scrape_all_files(self):
"""
Generator that yields one by one the return value for self.read_dcm
for each file within this set
"""
try:
for dcmf in self.items:
yield self.read_dcm(dcmf)
except IOError as ioe:
raise IOError('Error... | def scrape_all_files(self):
"""
Generator that yields one by one the return value for self.read_dcm
for each file within this set
"""
try:
for dcmf in self.items:
yield self.read_dcm(dcmf)
except IOError as ioe:
raise IOError('Error... | [
"Generator",
"that",
"yields",
"one",
"by",
"one",
"the",
"return",
"value",
"for",
"self",
".",
"read_dcm",
"for",
"each",
"file",
"within",
"this",
"set"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/sets.py#L173-L182 | [
"def",
"scrape_all_files",
"(",
"self",
")",
":",
"try",
":",
"for",
"dcmf",
"in",
"self",
".",
"items",
":",
"yield",
"self",
".",
"read_dcm",
"(",
"dcmf",
")",
"except",
"IOError",
"as",
"ioe",
":",
"raise",
"IOError",
"(",
"'Error reading DICOM file: {}... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | get_unique_field_values | Return a set of unique field values from a list of DICOM files
Parameters
----------
dcm_file_list: iterable of DICOM file paths
field_name: str
Name of the field from where to get each value
Returns
-------
Set of field values | boyle/dicom/utils.py | def get_unique_field_values(dcm_file_list, field_name):
"""Return a set of unique field values from a list of DICOM files
Parameters
----------
dcm_file_list: iterable of DICOM file paths
field_name: str
Name of the field from where to get each value
Returns
-------
Set of field ... | def get_unique_field_values(dcm_file_list, field_name):
"""Return a set of unique field values from a list of DICOM files
Parameters
----------
dcm_file_list: iterable of DICOM file paths
field_name: str
Name of the field from where to get each value
Returns
-------
Set of field ... | [
"Return",
"a",
"set",
"of",
"unique",
"field",
"values",
"from",
"a",
"list",
"of",
"DICOM",
"files"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/utils.py#L95-L114 | [
"def",
"get_unique_field_values",
"(",
"dcm_file_list",
",",
"field_name",
")",
":",
"field_values",
"=",
"set",
"(",
")",
"for",
"dcm",
"in",
"dcm_file_list",
":",
"field_values",
".",
"add",
"(",
"str",
"(",
"DicomFile",
"(",
"dcm",
")",
".",
"get_attribut... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | find_all_dicom_files | Returns a list of the dicom files within root_path
Parameters
----------
root_path: str
Path to the directory to be recursively searched for DICOM files.
Returns
-------
dicoms: set
Set of DICOM absolute file paths | boyle/dicom/utils.py | def find_all_dicom_files(root_path):
"""
Returns a list of the dicom files within root_path
Parameters
----------
root_path: str
Path to the directory to be recursively searched for DICOM files.
Returns
-------
dicoms: set
Set of DICOM absolute file paths
"""
dicoms = s... | def find_all_dicom_files(root_path):
"""
Returns a list of the dicom files within root_path
Parameters
----------
root_path: str
Path to the directory to be recursively searched for DICOM files.
Returns
-------
dicoms: set
Set of DICOM absolute file paths
"""
dicoms = s... | [
"Returns",
"a",
"list",
"of",
"the",
"dicom",
"files",
"within",
"root_path"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/utils.py#L117-L140 | [
"def",
"find_all_dicom_files",
"(",
"root_path",
")",
":",
"dicoms",
"=",
"set",
"(",
")",
"try",
":",
"for",
"fpath",
"in",
"get_all_files",
"(",
"root_path",
")",
":",
"if",
"is_dicom_file",
"(",
"fpath",
")",
":",
"dicoms",
".",
"add",
"(",
"fpath",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | is_dicom_file | Tries to read the file using dicom.read_file,
if the file exists and dicom.read_file does not raise
and Exception returns True. False otherwise.
:param filepath: str
Path to DICOM file
:return: bool | boyle/dicom/utils.py | def is_dicom_file(filepath):
"""
Tries to read the file using dicom.read_file,
if the file exists and dicom.read_file does not raise
and Exception returns True. False otherwise.
:param filepath: str
Path to DICOM file
:return: bool
"""
if not os.path.exists(filepath):
rais... | def is_dicom_file(filepath):
"""
Tries to read the file using dicom.read_file,
if the file exists and dicom.read_file does not raise
and Exception returns True. False otherwise.
:param filepath: str
Path to DICOM file
:return: bool
"""
if not os.path.exists(filepath):
rais... | [
"Tries",
"to",
"read",
"the",
"file",
"using",
"dicom",
".",
"read_file",
"if",
"the",
"file",
"exists",
"and",
"dicom",
".",
"read_file",
"does",
"not",
"raise",
"and",
"Exception",
"returns",
"True",
".",
"False",
"otherwise",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/utils.py#L143-L168 | [
"def",
"is_dicom_file",
"(",
"filepath",
")",
":",
"if",
"not",
"os",
".",
"path",
".",
"exists",
"(",
"filepath",
")",
":",
"raise",
"IOError",
"(",
"'File {} not found.'",
".",
"format",
"(",
"filepath",
")",
")",
"filename",
"=",
"os",
".",
"path",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | group_dicom_files | Group in a dictionary all the DICOM files in dicom_paths
separated by the given `hdr_field` tag value.
Parameters
----------
dicom_paths: str
Iterable of DICOM file paths.
hdr_field: str
Name of the DICOM tag whose values will be used as key for the group.
Returns
-------
... | boyle/dicom/utils.py | def group_dicom_files(dicom_paths, hdr_field='PatientID'):
"""Group in a dictionary all the DICOM files in dicom_paths
separated by the given `hdr_field` tag value.
Parameters
----------
dicom_paths: str
Iterable of DICOM file paths.
hdr_field: str
Name of the DICOM tag whose v... | def group_dicom_files(dicom_paths, hdr_field='PatientID'):
"""Group in a dictionary all the DICOM files in dicom_paths
separated by the given `hdr_field` tag value.
Parameters
----------
dicom_paths: str
Iterable of DICOM file paths.
hdr_field: str
Name of the DICOM tag whose v... | [
"Group",
"in",
"a",
"dictionary",
"all",
"the",
"DICOM",
"files",
"in",
"dicom_paths",
"separated",
"by",
"the",
"given",
"hdr_field",
"tag",
"value",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/utils.py#L171-L196 | [
"def",
"group_dicom_files",
"(",
"dicom_paths",
",",
"hdr_field",
"=",
"'PatientID'",
")",
":",
"dicom_groups",
"=",
"defaultdict",
"(",
"list",
")",
"try",
":",
"for",
"dcm",
"in",
"dicom_paths",
":",
"hdr",
"=",
"dicom",
".",
"read_file",
"(",
"dcm",
")"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | decompress | Decompress all *.dcm files recursively found in DICOM_DIR.
This uses 'gdcmconv --raw'.
It works when 'dcm2nii' shows the `Unsupported Transfer Syntax` error. This error is
usually caused by lack of JPEG2000 support in dcm2nii compilation.
Read more:
http://www.nitrc.org/plugins/mwiki/index.php/dcm2... | boyle/dicom/utils.py | def decompress(input_dir, dcm_pattern='*.dcm'):
""" Decompress all *.dcm files recursively found in DICOM_DIR.
This uses 'gdcmconv --raw'.
It works when 'dcm2nii' shows the `Unsupported Transfer Syntax` error. This error is
usually caused by lack of JPEG2000 support in dcm2nii compilation.
Read mor... | def decompress(input_dir, dcm_pattern='*.dcm'):
""" Decompress all *.dcm files recursively found in DICOM_DIR.
This uses 'gdcmconv --raw'.
It works when 'dcm2nii' shows the `Unsupported Transfer Syntax` error. This error is
usually caused by lack of JPEG2000 support in dcm2nii compilation.
Read mor... | [
"Decompress",
"all",
"*",
".",
"dcm",
"files",
"recursively",
"found",
"in",
"DICOM_DIR",
".",
"This",
"uses",
"gdcmconv",
"--",
"raw",
".",
"It",
"works",
"when",
"dcm2nii",
"shows",
"the",
"Unsupported",
"Transfer",
"Syntax",
"error",
".",
"This",
"error",... | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/utils.py#L199-L224 | [
"def",
"decompress",
"(",
"input_dir",
",",
"dcm_pattern",
"=",
"'*.dcm'",
")",
":",
"dcmfiles",
"=",
"sorted",
"(",
"recursive_glob",
"(",
"input_dir",
",",
"dcm_pattern",
")",
")",
"for",
"dcm",
"in",
"dcmfiles",
":",
"cmd",
"=",
"'gdcmconv --raw -i \"{0}\" ... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | DicomFile.get_attributes | Return the attributes values from this DicomFile
Parameters
----------
attributes: str or list of str
DICOM field names
default: str
Default value if the attribute does not exist.
Returns
-------
Value of the field or list of values. | boyle/dicom/utils.py | def get_attributes(self, attributes, default=''):
"""Return the attributes values from this DicomFile
Parameters
----------
attributes: str or list of str
DICOM field names
default: str
Default value if the attribute does not exist.
Returns
--... | def get_attributes(self, attributes, default=''):
"""Return the attributes values from this DicomFile
Parameters
----------
attributes: str or list of str
DICOM field names
default: str
Default value if the attribute does not exist.
Returns
--... | [
"Return",
"the",
"attributes",
"values",
"from",
"this",
"DicomFile"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/utils.py#L63-L86 | [
"def",
"get_attributes",
"(",
"self",
",",
"attributes",
",",
"default",
"=",
"''",
")",
":",
"if",
"isinstance",
"(",
"attributes",
",",
"str",
")",
":",
"attributes",
"=",
"[",
"attributes",
"]",
"attrs",
"=",
"[",
"getattr",
"(",
"self",
",",
"attr"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | merge_images | Concatenate `images` in the direction determined in `axis`.
Parameters
----------
images: list of str or img-like object.
See NeuroImage constructor docstring.
axis: str
't' : concatenate images in time
'x' : concatenate images in the x direction
'y' : concatenate images in t... | boyle/nifti/utils.py | def merge_images(images, axis='t'):
""" Concatenate `images` in the direction determined in `axis`.
Parameters
----------
images: list of str or img-like object.
See NeuroImage constructor docstring.
axis: str
't' : concatenate images in time
'x' : concatenate images in the x d... | def merge_images(images, axis='t'):
""" Concatenate `images` in the direction determined in `axis`.
Parameters
----------
images: list of str or img-like object.
See NeuroImage constructor docstring.
axis: str
't' : concatenate images in time
'x' : concatenate images in the x d... | [
"Concatenate",
"images",
"in",
"the",
"direction",
"determined",
"in",
"axis",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/utils.py#L25-L77 | [
"def",
"merge_images",
"(",
"images",
",",
"axis",
"=",
"'t'",
")",
":",
"# check if images is not empty",
"if",
"not",
"images",
":",
"return",
"None",
"# the given axis name to axis idx",
"axis_dim",
"=",
"{",
"'x'",
":",
"0",
",",
"'y'",
":",
"1",
",",
"'... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | nifti_out | Picks a function whose first argument is an `img`, processes its
data and returns a numpy array. This decorator wraps this numpy array
into a nibabel.Nifti1Image. | boyle/nifti/utils.py | def nifti_out(f):
""" Picks a function whose first argument is an `img`, processes its
data and returns a numpy array. This decorator wraps this numpy array
into a nibabel.Nifti1Image."""
@wraps(f)
def wrapped(*args, **kwargs):
r = f(*args, **kwargs)
img = read_img(args[0])
... | def nifti_out(f):
""" Picks a function whose first argument is an `img`, processes its
data and returns a numpy array. This decorator wraps this numpy array
into a nibabel.Nifti1Image."""
@wraps(f)
def wrapped(*args, **kwargs):
r = f(*args, **kwargs)
img = read_img(args[0])
... | [
"Picks",
"a",
"function",
"whose",
"first",
"argument",
"is",
"an",
"img",
"processes",
"its",
"data",
"and",
"returns",
"a",
"numpy",
"array",
".",
"This",
"decorator",
"wraps",
"this",
"numpy",
"array",
"into",
"a",
"nibabel",
".",
"Nifti1Image",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/utils.py#L80-L91 | [
"def",
"nifti_out",
"(",
"f",
")",
":",
"@",
"wraps",
"(",
"f",
")",
"def",
"wrapped",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"r",
"=",
"f",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"img",
"=",
"read_img",
"(",
"args",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | thr_img | Use the given magic function name `func` to threshold with value `thr`
the data of `img` and return a new nibabel.Nifti1Image.
Parameters
----------
img: img-like
thr: float or int
The threshold value.
mode: str
Choices: '+' for positive threshold,
'+-' for pos... | boyle/nifti/utils.py | def thr_img(img, thr=2., mode='+'):
""" Use the given magic function name `func` to threshold with value `thr`
the data of `img` and return a new nibabel.Nifti1Image.
Parameters
----------
img: img-like
thr: float or int
The threshold value.
mode: str
Choices: '+' for posit... | def thr_img(img, thr=2., mode='+'):
""" Use the given magic function name `func` to threshold with value `thr`
the data of `img` and return a new nibabel.Nifti1Image.
Parameters
----------
img: img-like
thr: float or int
The threshold value.
mode: str
Choices: '+' for posit... | [
"Use",
"the",
"given",
"magic",
"function",
"name",
"func",
"to",
"threshold",
"with",
"value",
"thr",
"the",
"data",
"of",
"img",
"and",
"return",
"a",
"new",
"nibabel",
".",
"Nifti1Image",
".",
"Parameters",
"----------",
"img",
":",
"img",
"-",
"like"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/utils.py#L95-L127 | [
"def",
"thr_img",
"(",
"img",
",",
"thr",
"=",
"2.",
",",
"mode",
"=",
"'+'",
")",
":",
"vol",
"=",
"read_img",
"(",
"img",
")",
".",
"get_data",
"(",
")",
"if",
"mode",
"==",
"'+'",
":",
"mask",
"=",
"vol",
">",
"thr",
"elif",
"mode",
"==",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | div_img | Pixelwise division or divide by a number | boyle/nifti/utils.py | def div_img(img1, div2):
""" Pixelwise division or divide by a number """
if is_img(div2):
return img1.get_data()/div2.get_data()
elif isinstance(div2, (float, int)):
return img1.get_data()/div2
else:
raise NotImplementedError('Cannot divide {}({}) by '
... | def div_img(img1, div2):
""" Pixelwise division or divide by a number """
if is_img(div2):
return img1.get_data()/div2.get_data()
elif isinstance(div2, (float, int)):
return img1.get_data()/div2
else:
raise NotImplementedError('Cannot divide {}({}) by '
... | [
"Pixelwise",
"division",
"or",
"divide",
"by",
"a",
"number"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/utils.py#L161-L172 | [
"def",
"div_img",
"(",
"img1",
",",
"div2",
")",
":",
"if",
"is_img",
"(",
"div2",
")",
":",
"return",
"img1",
".",
"get_data",
"(",
")",
"/",
"div2",
".",
"get_data",
"(",
")",
"elif",
"isinstance",
"(",
"div2",
",",
"(",
"float",
",",
"int",
")... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | apply_mask | Return the image with the given `mask` applied. | boyle/nifti/utils.py | def apply_mask(img, mask):
"""Return the image with the given `mask` applied."""
from .mask import apply_mask
vol, _ = apply_mask(img, mask)
return vector_to_volume(vol, read_img(mask).get_data().astype(bool)) | def apply_mask(img, mask):
"""Return the image with the given `mask` applied."""
from .mask import apply_mask
vol, _ = apply_mask(img, mask)
return vector_to_volume(vol, read_img(mask).get_data().astype(bool)) | [
"Return",
"the",
"image",
"with",
"the",
"given",
"mask",
"applied",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/utils.py#L176-L181 | [
"def",
"apply_mask",
"(",
"img",
",",
"mask",
")",
":",
"from",
".",
"mask",
"import",
"apply_mask",
"vol",
",",
"_",
"=",
"apply_mask",
"(",
"img",
",",
"mask",
")",
"return",
"vector_to_volume",
"(",
"vol",
",",
"read_img",
"(",
"mask",
")",
".",
"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | abs_img | Return an image with the binarised version of the data of `img`. | boyle/nifti/utils.py | def abs_img(img):
""" Return an image with the binarised version of the data of `img`."""
bool_img = np.abs(read_img(img).get_data())
return bool_img.astype(int) | def abs_img(img):
""" Return an image with the binarised version of the data of `img`."""
bool_img = np.abs(read_img(img).get_data())
return bool_img.astype(int) | [
"Return",
"an",
"image",
"with",
"the",
"binarised",
"version",
"of",
"the",
"data",
"of",
"img",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/utils.py#L185-L188 | [
"def",
"abs_img",
"(",
"img",
")",
":",
"bool_img",
"=",
"np",
".",
"abs",
"(",
"read_img",
"(",
"img",
")",
".",
"get_data",
"(",
")",
")",
"return",
"bool_img",
".",
"astype",
"(",
"int",
")"
] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | icc_img_to_zscore | Return a z-scored version of `icc`.
This function is based on GIFT `icatb_convertImageToZScores` function. | boyle/nifti/utils.py | def icc_img_to_zscore(icc, center_image=False):
""" Return a z-scored version of `icc`.
This function is based on GIFT `icatb_convertImageToZScores` function.
"""
vol = read_img(icc).get_data()
v2 = vol[vol != 0]
if center_image:
v2 = detrend(v2, axis=0)
vstd = np.linalg.norm(v2, o... | def icc_img_to_zscore(icc, center_image=False):
""" Return a z-scored version of `icc`.
This function is based on GIFT `icatb_convertImageToZScores` function.
"""
vol = read_img(icc).get_data()
v2 = vol[vol != 0]
if center_image:
v2 = detrend(v2, axis=0)
vstd = np.linalg.norm(v2, o... | [
"Return",
"a",
"z",
"-",
"scored",
"version",
"of",
"icc",
".",
"This",
"function",
"is",
"based",
"on",
"GIFT",
"icatb_convertImageToZScores",
"function",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/utils.py#L192-L207 | [
"def",
"icc_img_to_zscore",
"(",
"icc",
",",
"center_image",
"=",
"False",
")",
":",
"vol",
"=",
"read_img",
"(",
"icc",
")",
".",
"get_data",
"(",
")",
"v2",
"=",
"vol",
"[",
"vol",
"!=",
"0",
"]",
"if",
"center_image",
":",
"v2",
"=",
"detrend",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | spatial_map | Return the thresholded z-scored `icc`. | boyle/nifti/utils.py | def spatial_map(icc, thr, mode='+'):
""" Return the thresholded z-scored `icc`. """
return thr_img(icc_img_to_zscore(icc), thr=thr, mode=mode).get_data() | def spatial_map(icc, thr, mode='+'):
""" Return the thresholded z-scored `icc`. """
return thr_img(icc_img_to_zscore(icc), thr=thr, mode=mode).get_data() | [
"Return",
"the",
"thresholded",
"z",
"-",
"scored",
"icc",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/utils.py#L211-L213 | [
"def",
"spatial_map",
"(",
"icc",
",",
"thr",
",",
"mode",
"=",
"'+'",
")",
":",
"return",
"thr_img",
"(",
"icc_img_to_zscore",
"(",
"icc",
")",
",",
"thr",
"=",
"thr",
",",
"mode",
"=",
"mode",
")",
".",
"get_data",
"(",
")"
] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | filter_icc | Threshold then mask an IC correlation map.
Parameters
----------
icc: img-like
The 'raw' ICC map.
mask: img-like
If not None. Will apply this masks in the end of the process.
thr: float
The threshold value.
zscore: bool
If True will calculate the z-score of the... | boyle/nifti/utils.py | def filter_icc(icc, mask=None, thr=2, zscore=True, mode="+"):
""" Threshold then mask an IC correlation map.
Parameters
----------
icc: img-like
The 'raw' ICC map.
mask: img-like
If not None. Will apply this masks in the end of the process.
thr: float
The threshold valu... | def filter_icc(icc, mask=None, thr=2, zscore=True, mode="+"):
""" Threshold then mask an IC correlation map.
Parameters
----------
icc: img-like
The 'raw' ICC map.
mask: img-like
If not None. Will apply this masks in the end of the process.
thr: float
The threshold valu... | [
"Threshold",
"then",
"mask",
"an",
"IC",
"correlation",
"map",
".",
"Parameters",
"----------",
"icc",
":",
"img",
"-",
"like",
"The",
"raw",
"ICC",
"map",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/utils.py#L216-L250 | [
"def",
"filter_icc",
"(",
"icc",
",",
"mask",
"=",
"None",
",",
"thr",
"=",
"2",
",",
"zscore",
"=",
"True",
",",
"mode",
"=",
"\"+\"",
")",
":",
"if",
"zscore",
":",
"icc_filt",
"=",
"thr_img",
"(",
"icc_img_to_zscore",
"(",
"icc",
")",
",",
"thr"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | check_mhd_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 .mhd file. (if it is a .raw file, this won't work).
- any object with get_data() and get_affine() methods, e.g., nibabel.Nifti1Image.
... | boyle/mhd/check.py | def check_mhd_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 .mhd file. (if it is a .raw file, this won't work).
- any object with get_data() an... | def check_mhd_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 .mhd file. (if it is a .raw file, this won't work).
- any object with get_data() an... | [
"Check",
"that",
"image",
"is",
"a",
"proper",
"img",
".",
"Turn",
"filenames",
"into",
"objects",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/mhd/check.py#L23-L66 | [
"def",
"check_mhd_img",
"(",
"image",
",",
"make_it_3d",
"=",
"False",
")",
":",
"if",
"isinstance",
"(",
"image",
",",
"string_types",
")",
":",
"# a filename, load it",
"if",
"not",
"op",
".",
"exists",
"(",
"image",
")",
":",
"raise",
"FileNotFound",
"(... | 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: numpy.ndarray
Image data array
Returns
-------
3D numpy ndarray object | boyle/mhd/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: numpy.ndarray
Image data array
Returns
-------
3D numpy ndarray object
"""
shape = img.shape
if len(sha... | 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: numpy.ndarray
Image data array
Returns
-------
3D numpy ndarray object
"""
shape = img.shape
if len(sha... | [
"Enforce",
"that",
"img",
"is",
"a",
"3D",
"img",
"-",
"like",
"object",
"if",
"it",
"is",
"not",
"raise",
"a",
"TypeError",
".",
"i",
".",
"e",
".",
"remove",
"dimensions",
"of",
"size",
"1",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/mhd/check.py#L69-L92 | [
"def",
"_make_it_3d",
"(",
"img",
")",
":",
"shape",
"=",
"img",
".",
"shape",
"if",
"len",
"(",
"shape",
")",
"==",
"3",
":",
"return",
"img",
"elif",
"len",
"(",
"shape",
")",
"==",
"4",
"and",
"shape",
"[",
"3",
"]",
"==",
"1",
":",
"# \"squ... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | write_meta_header | Write the content of the `meta_dict` into `filename`.
Parameters
----------
filename: str
Path to the output file
meta_dict: dict
Dictionary with the fields of the metadata .mhd file | boyle/mhd/write.py | def write_meta_header(filename, meta_dict):
""" Write the content of the `meta_dict` into `filename`.
Parameters
----------
filename: str
Path to the output file
meta_dict: dict
Dictionary with the fields of the metadata .mhd file
"""
header = ''
# do not use tags = met... | def write_meta_header(filename, meta_dict):
""" Write the content of the `meta_dict` into `filename`.
Parameters
----------
filename: str
Path to the output file
meta_dict: dict
Dictionary with the fields of the metadata .mhd file
"""
header = ''
# do not use tags = met... | [
"Write",
"the",
"content",
"of",
"the",
"meta_dict",
"into",
"filename",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/mhd/write.py#L25-L43 | [
"def",
"write_meta_header",
"(",
"filename",
",",
"meta_dict",
")",
":",
"header",
"=",
"''",
"# do not use tags = meta_dict.keys() because the order of tags matters",
"for",
"tag",
"in",
"MHD_TAGS",
":",
"if",
"tag",
"in",
"meta_dict",
".",
"keys",
"(",
")",
":",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | dump_raw_data | Write the data into a raw format file. Big endian is always used.
Parameters
----------
filename: str
Path to the output file
data: numpy.ndarray
n-dimensional image data array. | boyle/mhd/write.py | def dump_raw_data(filename, data):
""" Write the data into a raw format file. Big endian is always used.
Parameters
----------
filename: str
Path to the output file
data: numpy.ndarray
n-dimensional image data array.
"""
if data.ndim == 3:
# Begin 3D fix
dat... | def dump_raw_data(filename, data):
""" Write the data into a raw format file. Big endian is always used.
Parameters
----------
filename: str
Path to the output file
data: numpy.ndarray
n-dimensional image data array.
"""
if data.ndim == 3:
# Begin 3D fix
dat... | [
"Write",
"the",
"data",
"into",
"a",
"raw",
"format",
"file",
".",
"Big",
"endian",
"is",
"always",
"used",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/mhd/write.py#L46-L70 | [
"def",
"dump_raw_data",
"(",
"filename",
",",
"data",
")",
":",
"if",
"data",
".",
"ndim",
"==",
"3",
":",
"# Begin 3D fix",
"data",
"=",
"data",
".",
"reshape",
"(",
"[",
"data",
".",
"shape",
"[",
"0",
"]",
",",
"data",
".",
"shape",
"[",
"1",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | write_mhd_file | Write the `data` and `meta_dict` in two files with names
that use `filename` as a prefix.
Parameters
----------
filename: str
Path to the output file.
This is going to be used as a preffix.
Two files will be created, one with a '.mhd' extension
and another with '.raw'. I... | boyle/mhd/write.py | def write_mhd_file(filename, data, shape=None, meta_dict=None):
""" Write the `data` and `meta_dict` in two files with names
that use `filename` as a prefix.
Parameters
----------
filename: str
Path to the output file.
This is going to be used as a preffix.
Two files will be... | def write_mhd_file(filename, data, shape=None, meta_dict=None):
""" Write the `data` and `meta_dict` in two files with names
that use `filename` as a prefix.
Parameters
----------
filename: str
Path to the output file.
This is going to be used as a preffix.
Two files will be... | [
"Write",
"the",
"data",
"and",
"meta_dict",
"in",
"two",
"files",
"with",
"names",
"that",
"use",
"filename",
"as",
"a",
"prefix",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/mhd/write.py#L73-L147 | [
"def",
"write_mhd_file",
"(",
"filename",
",",
"data",
",",
"shape",
"=",
"None",
",",
"meta_dict",
"=",
"None",
")",
":",
"# check its extension",
"ext",
"=",
"get_extension",
"(",
"filename",
")",
"fname",
"=",
"op",
".",
"basename",
"(",
"filename",
")"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | copy_mhd_and_raw | Copy .mhd and .raw files to dst.
If dst is a folder, won't change the file, but if dst is another filepath,
will modify the ElementDataFile field in the .mhd to point to the
new renamed .raw file.
Parameters
----------
src: str
Path to the .mhd file to be copied
dst: str
P... | boyle/mhd/write.py | def copy_mhd_and_raw(src, dst):
"""Copy .mhd and .raw files to dst.
If dst is a folder, won't change the file, but if dst is another filepath,
will modify the ElementDataFile field in the .mhd to point to the
new renamed .raw file.
Parameters
----------
src: str
Path to the .mhd fi... | def copy_mhd_and_raw(src, dst):
"""Copy .mhd and .raw files to dst.
If dst is a folder, won't change the file, but if dst is another filepath,
will modify the ElementDataFile field in the .mhd to point to the
new renamed .raw file.
Parameters
----------
src: str
Path to the .mhd fi... | [
"Copy",
".",
"mhd",
"and",
".",
"raw",
"files",
"to",
"dst",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/mhd/write.py#L150-L217 | [
"def",
"copy_mhd_and_raw",
"(",
"src",
",",
"dst",
")",
":",
"# check if src exists",
"if",
"not",
"op",
".",
"exists",
"(",
"src",
")",
":",
"raise",
"IOError",
"(",
"'Could not find file {}.'",
".",
"format",
"(",
"src",
")",
")",
"# check its extension",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | sav_to_pandas_rpy2 | SPSS .sav files to Pandas DataFrame through Rpy2
:param input_file: string
:return: | boyle/storage.py | def sav_to_pandas_rpy2(input_file):
"""
SPSS .sav files to Pandas DataFrame through Rpy2
:param input_file: string
:return:
"""
import pandas.rpy.common as com
w = com.robj.r('foreign::read.spss("%s", to.data.frame=TRUE)' % input_file)
return com.convert_robj(w) | def sav_to_pandas_rpy2(input_file):
"""
SPSS .sav files to Pandas DataFrame through Rpy2
:param input_file: string
:return:
"""
import pandas.rpy.common as com
w = com.robj.r('foreign::read.spss("%s", to.data.frame=TRUE)' % input_file)
return com.convert_robj(w) | [
"SPSS",
".",
"sav",
"files",
"to",
"Pandas",
"DataFrame",
"through",
"Rpy2"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/storage.py#L23-L34 | [
"def",
"sav_to_pandas_rpy2",
"(",
"input_file",
")",
":",
"import",
"pandas",
".",
"rpy",
".",
"common",
"as",
"com",
"w",
"=",
"com",
".",
"robj",
".",
"r",
"(",
"'foreign::read.spss(\"%s\", to.data.frame=TRUE)'",
"%",
"input_file",
")",
"return",
"com",
".",... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | sav_to_pandas_savreader | SPSS .sav files to Pandas DataFrame through savreader module
:param input_file: string
:return: | boyle/storage.py | def sav_to_pandas_savreader(input_file):
"""
SPSS .sav files to Pandas DataFrame through savreader module
:param input_file: string
:return:
"""
from savReaderWriter import SavReader
lines = []
with SavReader(input_file, returnHeader=True) as reader:
header = next(reader)
... | def sav_to_pandas_savreader(input_file):
"""
SPSS .sav files to Pandas DataFrame through savreader module
:param input_file: string
:return:
"""
from savReaderWriter import SavReader
lines = []
with SavReader(input_file, returnHeader=True) as reader:
header = next(reader)
... | [
"SPSS",
".",
"sav",
"files",
"to",
"Pandas",
"DataFrame",
"through",
"savreader",
"module"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/storage.py#L37-L52 | [
"def",
"sav_to_pandas_savreader",
"(",
"input_file",
")",
":",
"from",
"savReaderWriter",
"import",
"SavReader",
"lines",
"=",
"[",
"]",
"with",
"SavReader",
"(",
"input_file",
",",
"returnHeader",
"=",
"True",
")",
"as",
"reader",
":",
"header",
"=",
"next",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | ExportData.save_variables | Save given variables in a file.
Valid extensions: '.pyshelf' or '.shelf' (Python shelve)
'.mat' (Matlab archive),
'.hdf5' or '.h5' (HDF5 file)
Parameters
----------
filename: str
Output file path.
variables: dict
... | boyle/storage.py | def save_variables(filename, variables):
"""Save given variables in a file.
Valid extensions: '.pyshelf' or '.shelf' (Python shelve)
'.mat' (Matlab archive),
'.hdf5' or '.h5' (HDF5 file)
Parameters
----------
filename: str
... | def save_variables(filename, variables):
"""Save given variables in a file.
Valid extensions: '.pyshelf' or '.shelf' (Python shelve)
'.mat' (Matlab archive),
'.hdf5' or '.h5' (HDF5 file)
Parameters
----------
filename: str
... | [
"Save",
"given",
"variables",
"in",
"a",
"file",
".",
"Valid",
"extensions",
":",
".",
"pyshelf",
"or",
".",
"shelf",
"(",
"Python",
"shelve",
")",
".",
"mat",
"(",
"Matlab",
"archive",
")",
".",
"hdf5",
"or",
".",
"h5",
"(",
"HDF5",
"file",
")"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/storage.py#L118-L155 | [
"def",
"save_variables",
"(",
"filename",
",",
"variables",
")",
":",
"ext",
"=",
"get_extension",
"(",
"filename",
")",
".",
"lower",
"(",
")",
"out_exts",
"=",
"{",
"'.pyshelf'",
",",
"'.shelf'",
",",
"'.mat'",
",",
"'.hdf5'",
",",
"'.h5'",
"}",
"outpu... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | ExportData.save_varlist | Valid extensions '.pyshelf', '.mat', '.hdf5' or '.h5'
@param filename: string
@param varnames: list of strings
Names of the variables
@param varlist: list of objects
The objects to be saved | boyle/storage.py | def save_varlist(filename, varnames, varlist):
"""
Valid extensions '.pyshelf', '.mat', '.hdf5' or '.h5'
@param filename: string
@param varnames: list of strings
Names of the variables
@param varlist: list of objects
The objects to be saved
"""
... | def save_varlist(filename, varnames, varlist):
"""
Valid extensions '.pyshelf', '.mat', '.hdf5' or '.h5'
@param filename: string
@param varnames: list of strings
Names of the variables
@param varlist: list of objects
The objects to be saved
"""
... | [
"Valid",
"extensions",
".",
"pyshelf",
".",
"mat",
".",
"hdf5",
"or",
".",
"h5"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/storage.py#L158-L174 | [
"def",
"save_varlist",
"(",
"filename",
",",
"varnames",
",",
"varlist",
")",
":",
"variables",
"=",
"{",
"}",
"for",
"i",
",",
"vn",
"in",
"enumerate",
"(",
"varnames",
")",
":",
"variables",
"[",
"vn",
"]",
"=",
"varlist",
"[",
"i",
"]",
"ExportDat... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | cli | Create CLI environment | rcctl/rcctl/entry.py | def cli():
"""Create CLI environment"""
return VersionedCLI(cli_name=SF_CLI_NAME,
config_dir=SF_CLI_CONFIG_DIR,
config_env_var_prefix=SF_CLI_ENV_VAR_PREFIX,
commands_loader_cls=SFCommandLoader,
help_cls=SFCommandHelp... | def cli():
"""Create CLI environment"""
return VersionedCLI(cli_name=SF_CLI_NAME,
config_dir=SF_CLI_CONFIG_DIR,
config_env_var_prefix=SF_CLI_ENV_VAR_PREFIX,
commands_loader_cls=SFCommandLoader,
help_cls=SFCommandHelp... | [
"Create",
"CLI",
"environment"
] | shalabhms/reliable-collections-cli | python | https://github.com/shalabhms/reliable-collections-cli/blob/195d69816fb5a6e1e9ab0ab66b606b1248b4780d/rcctl/rcctl/entry.py#L10-L16 | [
"def",
"cli",
"(",
")",
":",
"return",
"VersionedCLI",
"(",
"cli_name",
"=",
"SF_CLI_NAME",
",",
"config_dir",
"=",
"SF_CLI_CONFIG_DIR",
",",
"config_env_var_prefix",
"=",
"SF_CLI_ENV_VAR_PREFIX",
",",
"commands_loader_cls",
"=",
"SFCommandLoader",
",",
"help_cls",
... | 195d69816fb5a6e1e9ab0ab66b606b1248b4780d |
valid | drain_rois | Find all the ROIs in img and returns a similar volume with the ROIs
emptied, keeping only their border voxels.
This is useful for DTI tractography.
Parameters
----------
img: img-like object or str
Can either be:
- a file path to a Nifti image
- any object with get_data() a... | boyle/nifti/roi.py | def drain_rois(img):
"""Find all the ROIs in img and returns a similar volume with the ROIs
emptied, keeping only their border voxels.
This is useful for DTI tractography.
Parameters
----------
img: img-like object or str
Can either be:
- a file path to a Nifti image
- ... | def drain_rois(img):
"""Find all the ROIs in img and returns a similar volume with the ROIs
emptied, keeping only their border voxels.
This is useful for DTI tractography.
Parameters
----------
img: img-like object or str
Can either be:
- a file path to a Nifti image
- ... | [
"Find",
"all",
"the",
"ROIs",
"in",
"img",
"and",
"returns",
"a",
"similar",
"volume",
"with",
"the",
"ROIs",
"emptied",
"keeping",
"only",
"their",
"border",
"voxels",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L23-L60 | [
"def",
"drain_rois",
"(",
"img",
")",
":",
"img_data",
"=",
"get_img_data",
"(",
"img",
")",
"out",
"=",
"np",
".",
"zeros",
"(",
"img_data",
".",
"shape",
",",
"dtype",
"=",
"img_data",
".",
"dtype",
")",
"krn_dim",
"=",
"[",
"3",
"]",
"*",
"img_d... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | pick_rois | Return the `rois_img` only with the ROI values from `roi_values`.
Parameters
----------
rois_img: niimg-like
roi_values: list of int or float
The list of values from rois_img.
bg_val: int or float
The background value of `rois_img`.
Returns
-------
subset_rois_img: nib... | boyle/nifti/roi.py | def pick_rois(rois_img, roi_values, bg_val=0):
""" Return the `rois_img` only with the ROI values from `roi_values`.
Parameters
----------
rois_img: niimg-like
roi_values: list of int or float
The list of values from rois_img.
bg_val: int or float
The background value of `rois_... | def pick_rois(rois_img, roi_values, bg_val=0):
""" Return the `rois_img` only with the ROI values from `roi_values`.
Parameters
----------
rois_img: niimg-like
roi_values: list of int or float
The list of values from rois_img.
bg_val: int or float
The background value of `rois_... | [
"Return",
"the",
"rois_img",
"only",
"with",
"the",
"ROI",
"values",
"from",
"roi_values",
".",
"Parameters",
"----------",
"rois_img",
":",
"niimg",
"-",
"like"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L63-L90 | [
"def",
"pick_rois",
"(",
"rois_img",
",",
"roi_values",
",",
"bg_val",
"=",
"0",
")",
":",
"img",
"=",
"read_img",
"(",
"rois_img",
")",
"img_data",
"=",
"img",
".",
"get_data",
"(",
")",
"if",
"bg_val",
"==",
"0",
":",
"out",
"=",
"np",
".",
"zero... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | largest_connected_component | Return the largest connected component of a 3D array.
Parameters
-----------
volume: numpy.array
3D boolean array.
Returns
--------
volume: numpy.array
3D boolean array with only one connected component. | boyle/nifti/roi.py | def largest_connected_component(volume):
"""Return the largest connected component of a 3D array.
Parameters
-----------
volume: numpy.array
3D boolean array.
Returns
--------
volume: numpy.array
3D boolean array with only one connected component.
"""
# We use asarr... | def largest_connected_component(volume):
"""Return the largest connected component of a 3D array.
Parameters
-----------
volume: numpy.array
3D boolean array.
Returns
--------
volume: numpy.array
3D boolean array with only one connected component.
"""
# We use asarr... | [
"Return",
"the",
"largest",
"connected",
"component",
"of",
"a",
"3D",
"array",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L93-L118 | [
"def",
"largest_connected_component",
"(",
"volume",
")",
":",
"# We use asarray to be able to work with masked arrays.",
"volume",
"=",
"np",
".",
"asarray",
"(",
"volume",
")",
"labels",
",",
"num_labels",
"=",
"scn",
".",
"label",
"(",
"volume",
")",
"if",
"not... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | large_clusters_mask | Return as mask for `volume` that includes only areas where
the connected components have a size bigger than `min_cluster_size`
in number of voxels.
Parameters
-----------
volume: numpy.array
3D boolean array.
min_cluster_size: int
Minimum size in voxels that the connected compo... | boyle/nifti/roi.py | def large_clusters_mask(volume, min_cluster_size):
""" Return as mask for `volume` that includes only areas where
the connected components have a size bigger than `min_cluster_size`
in number of voxels.
Parameters
-----------
volume: numpy.array
3D boolean array.
min_cluster_size: ... | def large_clusters_mask(volume, min_cluster_size):
""" Return as mask for `volume` that includes only areas where
the connected components have a size bigger than `min_cluster_size`
in number of voxels.
Parameters
-----------
volume: numpy.array
3D boolean array.
min_cluster_size: ... | [
"Return",
"as",
"mask",
"for",
"volume",
"that",
"includes",
"only",
"areas",
"where",
"the",
"connected",
"components",
"have",
"a",
"size",
"bigger",
"than",
"min_cluster_size",
"in",
"number",
"of",
"voxels",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L121-L149 | [
"def",
"large_clusters_mask",
"(",
"volume",
",",
"min_cluster_size",
")",
":",
"labels",
",",
"num_labels",
"=",
"scn",
".",
"label",
"(",
"volume",
")",
"labels_to_keep",
"=",
"set",
"(",
"[",
"i",
"for",
"i",
"in",
"range",
"(",
"num_labels",
")",
"if... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | create_rois_mask | Look for the files in filelist containing the names in roislist, these files will be opened, binarised
and merged in one mask.
Parameters
----------
roislist: list of strings
Names of the ROIs, which will have to be in the names of the files in filelist.
filelist: list of strings
L... | boyle/nifti/roi.py | def create_rois_mask(roislist, filelist):
"""Look for the files in filelist containing the names in roislist, these files will be opened, binarised
and merged in one mask.
Parameters
----------
roislist: list of strings
Names of the ROIs, which will have to be in the names of the files in f... | def create_rois_mask(roislist, filelist):
"""Look for the files in filelist containing the names in roislist, these files will be opened, binarised
and merged in one mask.
Parameters
----------
roislist: list of strings
Names of the ROIs, which will have to be in the names of the files in f... | [
"Look",
"for",
"the",
"files",
"in",
"filelist",
"containing",
"the",
"names",
"in",
"roislist",
"these",
"files",
"will",
"be",
"opened",
"binarised",
"and",
"merged",
"in",
"one",
"mask",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L152-L179 | [
"def",
"create_rois_mask",
"(",
"roislist",
",",
"filelist",
")",
":",
"roifiles",
"=",
"[",
"]",
"for",
"roi",
"in",
"roislist",
":",
"try",
":",
"roi_file",
"=",
"search_list",
"(",
"roi",
",",
"filelist",
")",
"[",
"0",
"]",
"except",
"Exception",
"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | get_unique_nonzeros | Return a sorted list of the non-zero unique values of arr.
Parameters
----------
arr: numpy.ndarray
The data array
Returns
-------
list of items of arr. | boyle/nifti/roi.py | def get_unique_nonzeros(arr):
""" Return a sorted list of the non-zero unique values of arr.
Parameters
----------
arr: numpy.ndarray
The data array
Returns
-------
list of items of arr.
"""
rois = np.unique(arr)
rois = rois[np.nonzero(rois)]
rois.sort()
return... | def get_unique_nonzeros(arr):
""" Return a sorted list of the non-zero unique values of arr.
Parameters
----------
arr: numpy.ndarray
The data array
Returns
-------
list of items of arr.
"""
rois = np.unique(arr)
rois = rois[np.nonzero(rois)]
rois.sort()
return... | [
"Return",
"a",
"sorted",
"list",
"of",
"the",
"non",
"-",
"zero",
"unique",
"values",
"of",
"arr",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L182-L198 | [
"def",
"get_unique_nonzeros",
"(",
"arr",
")",
":",
"rois",
"=",
"np",
".",
"unique",
"(",
"arr",
")",
"rois",
"=",
"rois",
"[",
"np",
".",
"nonzero",
"(",
"rois",
")",
"]",
"rois",
".",
"sort",
"(",
")",
"return",
"rois"
] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | get_rois_centers_of_mass | Get the center of mass for each ROI in the given volume.
Parameters
----------
vol: numpy ndarray
Volume with different values for each ROI.
Returns
-------
OrderedDict
Each entry in the dict has the ROI value as key and the center_of_mass coordinate as value. | boyle/nifti/roi.py | def get_rois_centers_of_mass(vol):
"""Get the center of mass for each ROI in the given volume.
Parameters
----------
vol: numpy ndarray
Volume with different values for each ROI.
Returns
-------
OrderedDict
Each entry in the dict has the ROI value as key and the center_of_m... | def get_rois_centers_of_mass(vol):
"""Get the center of mass for each ROI in the given volume.
Parameters
----------
vol: numpy ndarray
Volume with different values for each ROI.
Returns
-------
OrderedDict
Each entry in the dict has the ROI value as key and the center_of_m... | [
"Get",
"the",
"center",
"of",
"mass",
"for",
"each",
"ROI",
"in",
"the",
"given",
"volume",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L228-L250 | [
"def",
"get_rois_centers_of_mass",
"(",
"vol",
")",
":",
"from",
"scipy",
".",
"ndimage",
".",
"measurements",
"import",
"center_of_mass",
"roisvals",
"=",
"np",
".",
"unique",
"(",
"vol",
")",
"roisvals",
"=",
"roisvals",
"[",
"roisvals",
"!=",
"0",
"]",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | partition_timeseries | Partition the timeseries in tsvol according to the ROIs in roivol.
If a mask is given, will use it to exclude any voxel outside of it.
The outdict indicates whether you want a dictionary for each set of timeseries keyed by the ROI value
or a list of timeseries sets. If True and roi_img is not None will ret... | boyle/nifti/roi.py | def partition_timeseries(image, roi_img, mask_img=None, zeroe=True, roi_values=None, outdict=False):
"""Partition the timeseries in tsvol according to the ROIs in roivol.
If a mask is given, will use it to exclude any voxel outside of it.
The outdict indicates whether you want a dictionary for each set of ... | def partition_timeseries(image, roi_img, mask_img=None, zeroe=True, roi_values=None, outdict=False):
"""Partition the timeseries in tsvol according to the ROIs in roivol.
If a mask is given, will use it to exclude any voxel outside of it.
The outdict indicates whether you want a dictionary for each set of ... | [
"Partition",
"the",
"timeseries",
"in",
"tsvol",
"according",
"to",
"the",
"ROIs",
"in",
"roivol",
".",
"If",
"a",
"mask",
"is",
"given",
"will",
"use",
"it",
"to",
"exclude",
"any",
"voxel",
"outside",
"of",
"it",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L253-L326 | [
"def",
"partition_timeseries",
"(",
"image",
",",
"roi_img",
",",
"mask_img",
"=",
"None",
",",
"zeroe",
"=",
"True",
",",
"roi_values",
"=",
"None",
",",
"outdict",
"=",
"False",
")",
":",
"img",
"=",
"read_img",
"(",
"image",
")",
"rois",
"=",
"read_... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | _partition_data | Extracts the values in `datavol` that are in the ROI with value `roivalue` in `roivol`.
The ROI can be masked by `maskvol`.
Parameters
----------
datavol: numpy.ndarray
4D timeseries volume or a 3D volume to be partitioned
roivol: numpy.ndarray
3D ROIs volume
roivalue: int or ... | boyle/nifti/roi.py | def _partition_data(datavol, roivol, roivalue, maskvol=None, zeroe=True):
""" Extracts the values in `datavol` that are in the ROI with value `roivalue` in `roivol`.
The ROI can be masked by `maskvol`.
Parameters
----------
datavol: numpy.ndarray
4D timeseries volume or a 3D volume to be pa... | def _partition_data(datavol, roivol, roivalue, maskvol=None, zeroe=True):
""" Extracts the values in `datavol` that are in the ROI with value `roivalue` in `roivol`.
The ROI can be masked by `maskvol`.
Parameters
----------
datavol: numpy.ndarray
4D timeseries volume or a 3D volume to be pa... | [
"Extracts",
"the",
"values",
"in",
"datavol",
"that",
"are",
"in",
"the",
"ROI",
"with",
"value",
"roivalue",
"in",
"roivol",
".",
"The",
"ROI",
"can",
"be",
"masked",
"by",
"maskvol",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L350-L394 | [
"def",
"_partition_data",
"(",
"datavol",
",",
"roivol",
",",
"roivalue",
",",
"maskvol",
"=",
"None",
",",
"zeroe",
"=",
"True",
")",
":",
"if",
"maskvol",
"is",
"not",
"None",
":",
"# get all masked time series within this roi r",
"indices",
"=",
"(",
"roivo... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | _extract_timeseries_dict | Partition the timeseries in tsvol according to the ROIs in roivol.
If a mask is given, will use it to exclude any voxel outside of it.
Parameters
----------
tsvol: numpy.ndarray
4D timeseries volume or a 3D volume to be partitioned
roivol: numpy.ndarray
3D ROIs volume
maskvol:... | boyle/nifti/roi.py | def _extract_timeseries_dict(tsvol, roivol, maskvol=None, roi_values=None, zeroe=True):
"""Partition the timeseries in tsvol according to the ROIs in roivol.
If a mask is given, will use it to exclude any voxel outside of it.
Parameters
----------
tsvol: numpy.ndarray
4D timeseries volume o... | def _extract_timeseries_dict(tsvol, roivol, maskvol=None, roi_values=None, zeroe=True):
"""Partition the timeseries in tsvol according to the ROIs in roivol.
If a mask is given, will use it to exclude any voxel outside of it.
Parameters
----------
tsvol: numpy.ndarray
4D timeseries volume o... | [
"Partition",
"the",
"timeseries",
"in",
"tsvol",
"according",
"to",
"the",
"ROIs",
"in",
"roivol",
".",
"If",
"a",
"mask",
"is",
"given",
"will",
"use",
"it",
"to",
"exclude",
"any",
"voxel",
"outside",
"of",
"it",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L397-L439 | [
"def",
"_extract_timeseries_dict",
"(",
"tsvol",
",",
"roivol",
",",
"maskvol",
"=",
"None",
",",
"roi_values",
"=",
"None",
",",
"zeroe",
"=",
"True",
")",
":",
"_check_for_partition",
"(",
"tsvol",
",",
"roivol",
",",
"maskvol",
")",
"# get unique values of ... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | _extract_timeseries_list | Partition the timeseries in tsvol according to the ROIs in roivol.
If a mask is given, will use it to exclude any voxel outside of it.
Parameters
----------
tsvol: numpy.ndarray
4D timeseries volume or a 3D volume to be partitioned
roivol: numpy.ndarray
3D ROIs volume
maskvol:... | boyle/nifti/roi.py | def _extract_timeseries_list(tsvol, roivol, maskvol=None, roi_values=None, zeroe=True):
"""Partition the timeseries in tsvol according to the ROIs in roivol.
If a mask is given, will use it to exclude any voxel outside of it.
Parameters
----------
tsvol: numpy.ndarray
4D timeseries volume o... | def _extract_timeseries_list(tsvol, roivol, maskvol=None, roi_values=None, zeroe=True):
"""Partition the timeseries in tsvol according to the ROIs in roivol.
If a mask is given, will use it to exclude any voxel outside of it.
Parameters
----------
tsvol: numpy.ndarray
4D timeseries volume o... | [
"Partition",
"the",
"timeseries",
"in",
"tsvol",
"according",
"to",
"the",
"ROIs",
"in",
"roivol",
".",
"If",
"a",
"mask",
"is",
"given",
"will",
"use",
"it",
"to",
"exclude",
"any",
"voxel",
"outside",
"of",
"it",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L442-L483 | [
"def",
"_extract_timeseries_list",
"(",
"tsvol",
",",
"roivol",
",",
"maskvol",
"=",
"None",
",",
"roi_values",
"=",
"None",
",",
"zeroe",
"=",
"True",
")",
":",
"_check_for_partition",
"(",
"tsvol",
",",
"roivol",
",",
"maskvol",
")",
"if",
"roi_values",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | get_3D_from_4D | Pick one 3D volume from a 4D nifti image file
Parameters
----------
image: img-like object or str
Volume defining different ROIs.
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 ... | boyle/nifti/roi.py | def get_3D_from_4D(image, vol_idx=0):
"""Pick one 3D volume from a 4D nifti image file
Parameters
----------
image: img-like object or str
Volume defining different ROIs.
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affine() methods,... | def get_3D_from_4D(image, vol_idx=0):
"""Pick one 3D volume from a 4D nifti image file
Parameters
----------
image: img-like object or str
Volume defining different ROIs.
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affine() methods,... | [
"Pick",
"one",
"3D",
"volume",
"from",
"a",
"4D",
"nifti",
"image",
"file"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/roi.py#L486-L523 | [
"def",
"get_3D_from_4D",
"(",
"image",
",",
"vol_idx",
"=",
"0",
")",
":",
"img",
"=",
"check_img",
"(",
"image",
")",
"hdr",
",",
"aff",
"=",
"get_img_info",
"(",
"img",
")",
"if",
"len",
"(",
"img",
".",
"shape",
")",
"!=",
"4",
":",
"raise",
"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | HdfDataBuffer.create_hdf_file | :return: h5py DataSet | boyle/databuffer.py | def create_hdf_file(self):
"""
:return: h5py DataSet
"""
mode = 'w'
if not self._overwrite and os.path.exists(self._fname):
mode = 'a'
self._hdf_file = h5py.File(self._fname, mode)
if self._hdf_basepath == '/':
self._group = self._hdf_fil... | def create_hdf_file(self):
"""
:return: h5py DataSet
"""
mode = 'w'
if not self._overwrite and os.path.exists(self._fname):
mode = 'a'
self._hdf_file = h5py.File(self._fname, mode)
if self._hdf_basepath == '/':
self._group = self._hdf_fil... | [
":",
"return",
":",
"h5py",
"DataSet"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L99-L112 | [
"def",
"create_hdf_file",
"(",
"self",
")",
":",
"mode",
"=",
"'w'",
"if",
"not",
"self",
".",
"_overwrite",
"and",
"os",
".",
"path",
".",
"exists",
"(",
"self",
".",
"_fname",
")",
":",
"mode",
"=",
"'a'",
"self",
".",
"_hdf_file",
"=",
"h5py",
"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | HdfDataBuffer.get_dataset | Returns a h5py dataset given its registered name.
:param ds_name: string
Name of the dataset to be returned.
:return: | boyle/databuffer.py | def get_dataset(self, ds_name, mode='r'):
"""
Returns a h5py dataset given its registered name.
:param ds_name: string
Name of the dataset to be returned.
:return:
"""
if ds_name in self._datasets:
return self._datasets[ds_name]
else:
... | def get_dataset(self, ds_name, mode='r'):
"""
Returns a h5py dataset given its registered name.
:param ds_name: string
Name of the dataset to be returned.
:return:
"""
if ds_name in self._datasets:
return self._datasets[ds_name]
else:
... | [
"Returns",
"a",
"h5py",
"dataset",
"given",
"its",
"registered",
"name",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L114-L126 | [
"def",
"get_dataset",
"(",
"self",
",",
"ds_name",
",",
"mode",
"=",
"'r'",
")",
":",
"if",
"ds_name",
"in",
"self",
".",
"_datasets",
":",
"return",
"self",
".",
"_datasets",
"[",
"ds_name",
"]",
"else",
":",
"return",
"self",
".",
"create_empty_dataset... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | HdfDataBuffer.create_empty_dataset | Creates a Dataset with unknown size.
Resize it before using.
:param ds_name: string
:param dtype: dtype
Datatype of the dataset
:return: h5py DataSet | boyle/databuffer.py | def create_empty_dataset(self, ds_name, dtype=np.float32):
"""
Creates a Dataset with unknown size.
Resize it before using.
:param ds_name: string
:param dtype: dtype
Datatype of the dataset
:return: h5py DataSet
"""
if ds_name in self._datasets... | def create_empty_dataset(self, ds_name, dtype=np.float32):
"""
Creates a Dataset with unknown size.
Resize it before using.
:param ds_name: string
:param dtype: dtype
Datatype of the dataset
:return: h5py DataSet
"""
if ds_name in self._datasets... | [
"Creates",
"a",
"Dataset",
"with",
"unknown",
"size",
".",
"Resize",
"it",
"before",
"using",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L128-L147 | [
"def",
"create_empty_dataset",
"(",
"self",
",",
"ds_name",
",",
"dtype",
"=",
"np",
".",
"float32",
")",
":",
"if",
"ds_name",
"in",
"self",
".",
"_datasets",
":",
"return",
"self",
".",
"_datasets",
"[",
"ds_name",
"]",
"ds",
"=",
"self",
".",
"_grou... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | HdfDataBuffer.create_dataset | Saves a Numpy array in a dataset in the HDF file, registers it as
ds_name and returns the h5py dataset.
:param ds_name: string
Registration name of the dataset to be registered.
:param data: Numpy ndarray
:param dtype: dtype
Datatype of the dataset
:return: h5... | boyle/databuffer.py | def create_dataset(self, ds_name, data, attrs=None, dtype=None):
"""
Saves a Numpy array in a dataset in the HDF file, registers it as
ds_name and returns the h5py dataset.
:param ds_name: string
Registration name of the dataset to be registered.
:param data: Numpy ndar... | def create_dataset(self, ds_name, data, attrs=None, dtype=None):
"""
Saves a Numpy array in a dataset in the HDF file, registers it as
ds_name and returns the h5py dataset.
:param ds_name: string
Registration name of the dataset to be registered.
:param data: Numpy ndar... | [
"Saves",
"a",
"Numpy",
"array",
"in",
"a",
"dataset",
"in",
"the",
"HDF",
"file",
"registers",
"it",
"as",
"ds_name",
"and",
"returns",
"the",
"h5py",
"dataset",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L149-L183 | [
"def",
"create_dataset",
"(",
"self",
",",
"ds_name",
",",
"data",
",",
"attrs",
"=",
"None",
",",
"dtype",
"=",
"None",
")",
":",
"if",
"ds_name",
"in",
"self",
".",
"_datasets",
":",
"ds",
"=",
"self",
".",
"_datasets",
"[",
"ds_name",
"]",
"if",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | HdfDataBuffer.save | See create_dataset. | boyle/databuffer.py | def save(self, ds_name, data, dtype=None):
"""
See create_dataset.
"""
return self.create_dataset(ds_name, data, dtype) | def save(self, ds_name, data, dtype=None):
"""
See create_dataset.
"""
return self.create_dataset(ds_name, data, dtype) | [
"See",
"create_dataset",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L185-L189 | [
"def",
"save",
"(",
"self",
",",
"ds_name",
",",
"data",
",",
"dtype",
"=",
"None",
")",
":",
"return",
"self",
".",
"create_dataset",
"(",
"ds_name",
",",
"data",
",",
"dtype",
")"
] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NumpyHDFStore._fill_missing_values | Will get the names of the index colums of df, obtain their ranges from
range_values dict and return a reindexed version of df with the given
range values.
:param df: pandas DataFrame
:param range_values: dict or array-like
Must contain for each index column of df an entry with ... | boyle/databuffer.py | def _fill_missing_values(df, range_values, fill_value=0, fill_method=None):
"""
Will get the names of the index colums of df, obtain their ranges from
range_values dict and return a reindexed version of df with the given
range values.
:param df: pandas DataFrame
:param ... | def _fill_missing_values(df, range_values, fill_value=0, fill_method=None):
"""
Will get the names of the index colums of df, obtain their ranges from
range_values dict and return a reindexed version of df with the given
range values.
:param df: pandas DataFrame
:param ... | [
"Will",
"get",
"the",
"names",
"of",
"the",
"index",
"colums",
"of",
"df",
"obtain",
"their",
"ranges",
"from",
"range_values",
"dict",
"and",
"return",
"a",
"reindexed",
"version",
"of",
"df",
"with",
"the",
"given",
"range",
"values",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L225-L263 | [
"def",
"_fill_missing_values",
"(",
"df",
",",
"range_values",
",",
"fill_value",
"=",
"0",
",",
"fill_method",
"=",
"None",
")",
":",
"idx_colnames",
"=",
"df",
".",
"index",
".",
"names",
"idx_colranges",
"=",
"[",
"range_values",
"[",
"x",
"]",
"for",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NumpyHDFStore.get | Retrieve pandas object or group of Numpy ndarrays
stored in file
Parameters
----------
key : object
Returns
-------
obj : type of object stored in file | boyle/databuffer.py | def get(self, key):
"""
Retrieve pandas object or group of Numpy ndarrays
stored in file
Parameters
----------
key : object
Returns
-------
obj : type of object stored in file
"""
node = self.get_node(key)
if node is None:... | def get(self, key):
"""
Retrieve pandas object or group of Numpy ndarrays
stored in file
Parameters
----------
key : object
Returns
-------
obj : type of object stored in file
"""
node = self.get_node(key)
if node is None:... | [
"Retrieve",
"pandas",
"object",
"or",
"group",
"of",
"Numpy",
"ndarrays",
"stored",
"in",
"file"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L265-L286 | [
"def",
"get",
"(",
"self",
",",
"key",
")",
":",
"node",
"=",
"self",
".",
"get_node",
"(",
"key",
")",
"if",
"node",
"is",
"None",
":",
"raise",
"KeyError",
"(",
"'No object named %s in the file'",
"%",
"key",
")",
"if",
"hasattr",
"(",
"node",
",",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NumpyHDFStore.put | Store object in HDFStore
Parameters
----------
key : str
value : {Series, DataFrame, Panel, Numpy ndarray}
format : 'fixed(f)|table(t)', default is 'fixed'
fixed(f) : Fixed format
Fast writing/reading. Not-appendable, nor searchable
tab... | boyle/databuffer.py | def put(self, key, value, attrs=None, format=None, append=False, **kwargs):
"""
Store object in HDFStore
Parameters
----------
key : str
value : {Series, DataFrame, Panel, Numpy ndarray}
format : 'fixed(f)|table(t)', default is 'fixed'
fixed(f) : Fi... | def put(self, key, value, attrs=None, format=None, append=False, **kwargs):
"""
Store object in HDFStore
Parameters
----------
key : str
value : {Series, DataFrame, Panel, Numpy ndarray}
format : 'fixed(f)|table(t)', default is 'fixed'
fixed(f) : Fi... | [
"Store",
"object",
"in",
"HDFStore"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L288-L348 | [
"def",
"put",
"(",
"self",
",",
"key",
",",
"value",
",",
"attrs",
"=",
"None",
",",
"format",
"=",
"None",
",",
"append",
"=",
"False",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"not",
"isinstance",
"(",
"value",
",",
"np",
".",
"ndarray",
")",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NumpyHDFStore._push_dfblock | :param key: string
:param df: pandas Dataframe
:param ds_name: string | boyle/databuffer.py | def _push_dfblock(self, key, df, ds_name, range_values):
"""
:param key: string
:param df: pandas Dataframe
:param ds_name: string
"""
#create numpy array and put into hdf_file
vals_colranges = [range_values[x] for x in df.index.names]
nu_shape = [len(x) f... | def _push_dfblock(self, key, df, ds_name, range_values):
"""
:param key: string
:param df: pandas Dataframe
:param ds_name: string
"""
#create numpy array and put into hdf_file
vals_colranges = [range_values[x] for x in df.index.names]
nu_shape = [len(x) f... | [
":",
"param",
"key",
":",
"string",
":",
"param",
"df",
":",
"pandas",
"Dataframe",
":",
"param",
"ds_name",
":",
"string"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L350-L362 | [
"def",
"_push_dfblock",
"(",
"self",
",",
"key",
",",
"df",
",",
"ds_name",
",",
"range_values",
")",
":",
"#create numpy array and put into hdf_file",
"vals_colranges",
"=",
"[",
"range_values",
"[",
"x",
"]",
"for",
"x",
"in",
"df",
".",
"index",
".",
"nam... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | NumpyHDFStore.put_df_as_ndarray | Returns a PyTables HDF Array from df in the shape given by its index columns range values.
:param key: string object
:param df: pandas DataFrame
:param range_values: dict or array-like
Must contain for each index column of df an entry with all the values
within the range of th... | boyle/databuffer.py | def put_df_as_ndarray(self, key, df, range_values, loop_multiindex=False,
unstack=False, fill_value=0, fill_method=None):
"""Returns a PyTables HDF Array from df in the shape given by its index columns range values.
:param key: string object
:param df: pandas DataFram... | def put_df_as_ndarray(self, key, df, range_values, loop_multiindex=False,
unstack=False, fill_value=0, fill_method=None):
"""Returns a PyTables HDF Array from df in the shape given by its index columns range values.
:param key: string object
:param df: pandas DataFram... | [
"Returns",
"a",
"PyTables",
"HDF",
"Array",
"from",
"df",
"in",
"the",
"shape",
"given",
"by",
"its",
"index",
"columns",
"range",
"values",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/databuffer.py#L364-L449 | [
"def",
"put_df_as_ndarray",
"(",
"self",
",",
"key",
",",
"df",
",",
"range_values",
",",
"loop_multiindex",
"=",
"False",
",",
"unstack",
"=",
"False",
",",
"fill_value",
"=",
"0",
",",
"fill_method",
"=",
"None",
")",
":",
"idx_colnames",
"=",
"df",
".... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | ImageContainer.get_data | Get the data in the image.
If save_copy is True, will perform a deep copy of the data and return it.
Parameters
----------
smoothed: (optional) bool
If True and self._smooth_fwhm > 0 will smooth the data before masking.
masked: (optional) bool
If True a... | boyle/image/base.py | def get_data(self, safe_copy=False):
"""Get the data in the image.
If save_copy is True, will perform a deep copy of the data and return it.
Parameters
----------
smoothed: (optional) bool
If True and self._smooth_fwhm > 0 will smooth the data before masking.
... | def get_data(self, safe_copy=False):
"""Get the data in the image.
If save_copy is True, will perform a deep copy of the data and return it.
Parameters
----------
smoothed: (optional) bool
If True and self._smooth_fwhm > 0 will smooth the data before masking.
... | [
"Get",
"the",
"data",
"in",
"the",
"image",
".",
"If",
"save_copy",
"is",
"True",
"will",
"perform",
"a",
"deep",
"copy",
"of",
"the",
"data",
"and",
"return",
"it",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L100-L123 | [
"def",
"get_data",
"(",
"self",
",",
"safe_copy",
"=",
"False",
")",
":",
"if",
"safe_copy",
":",
"data",
"=",
"get_data",
"(",
"self",
".",
"img",
")",
"else",
":",
"data",
"=",
"self",
".",
"img",
".",
"get_data",
"(",
"caching",
"=",
"self",
"."... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | MedicalImage.smooth_fwhm | Set a smoothing Gaussian kernel given its FWHM in mm. | boyle/image/base.py | def smooth_fwhm(self, fwhm):
""" Set a smoothing Gaussian kernel given its FWHM in mm. """
if fwhm != self._smooth_fwhm:
self._is_data_smooth = False
self._smooth_fwhm = fwhm | def smooth_fwhm(self, fwhm):
""" Set a smoothing Gaussian kernel given its FWHM in mm. """
if fwhm != self._smooth_fwhm:
self._is_data_smooth = False
self._smooth_fwhm = fwhm | [
"Set",
"a",
"smoothing",
"Gaussian",
"kernel",
"given",
"its",
"FWHM",
"in",
"mm",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L178-L182 | [
"def",
"smooth_fwhm",
"(",
"self",
",",
"fwhm",
")",
":",
"if",
"fwhm",
"!=",
"self",
".",
"_smooth_fwhm",
":",
"self",
".",
"_is_data_smooth",
"=",
"False",
"self",
".",
"_smooth_fwhm",
"=",
"fwhm"
] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | MedicalImage.get_data | Get the data in the image.
If save_copy is True, will perform a deep copy of the data and return it.
Parameters
----------
smoothed: (optional) bool
If True and self._smooth_fwhm > 0 will smooth the data before masking.
masked: (optional) bool
If True a... | boyle/image/base.py | def get_data(self, smoothed=True, masked=True, safe_copy=False):
"""Get the data in the image.
If save_copy is True, will perform a deep copy of the data and return it.
Parameters
----------
smoothed: (optional) bool
If True and self._smooth_fwhm > 0 will smooth the... | def get_data(self, smoothed=True, masked=True, safe_copy=False):
"""Get the data in the image.
If save_copy is True, will perform a deep copy of the data and return it.
Parameters
----------
smoothed: (optional) bool
If True and self._smooth_fwhm > 0 will smooth the... | [
"Get",
"the",
"data",
"in",
"the",
"image",
".",
"If",
"save_copy",
"is",
"True",
"will",
"perform",
"a",
"deep",
"copy",
"of",
"the",
"data",
"and",
"return",
"it",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L198-L248 | [
"def",
"get_data",
"(",
"self",
",",
"smoothed",
"=",
"True",
",",
"masked",
"=",
"True",
",",
"safe_copy",
"=",
"False",
")",
":",
"if",
"not",
"safe_copy",
"and",
"smoothed",
"==",
"self",
".",
"_is_data_smooth",
"and",
"masked",
"==",
"self",
".",
"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | MedicalImage.apply_mask | First set_mask and the get_masked_data.
Parameters
----------
mask_img: nifti-like image, NeuroImage or str
3D mask array: True where a voxel should be used.
Can either be:
- a file path to a Nifti image
- any object with get_data() and get_affin... | boyle/image/base.py | def apply_mask(self, mask_img):
"""First set_mask and the get_masked_data.
Parameters
----------
mask_img: nifti-like image, NeuroImage or str
3D mask array: True where a voxel should be used.
Can either be:
- a file path to a Nifti image
... | def apply_mask(self, mask_img):
"""First set_mask and the get_masked_data.
Parameters
----------
mask_img: nifti-like image, NeuroImage or str
3D mask array: True where a voxel should be used.
Can either be:
- a file path to a Nifti image
... | [
"First",
"set_mask",
"and",
"the",
"get_masked_data",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L259-L278 | [
"def",
"apply_mask",
"(",
"self",
",",
"mask_img",
")",
":",
"self",
".",
"set_mask",
"(",
"mask_img",
")",
"return",
"self",
".",
"get_data",
"(",
"masked",
"=",
"True",
",",
"smoothed",
"=",
"True",
",",
"safe_copy",
"=",
"True",
")"
] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | MedicalImage.set_mask | Sets a mask img to this. So every operation to self, this mask will be taken into account.
Parameters
----------
mask_img: nifti-like image, NeuroImage or str
3D mask array: True where a voxel should be used.
Can either be:
- a file path to a Nifti image
... | boyle/image/base.py | def set_mask(self, mask_img):
"""Sets a mask img to this. So every operation to self, this mask will be taken into account.
Parameters
----------
mask_img: nifti-like image, NeuroImage or str
3D mask array: True where a voxel should be used.
Can either be:
... | def set_mask(self, mask_img):
"""Sets a mask img to this. So every operation to self, this mask will be taken into account.
Parameters
----------
mask_img: nifti-like image, NeuroImage or str
3D mask array: True where a voxel should be used.
Can either be:
... | [
"Sets",
"a",
"mask",
"img",
"to",
"this",
".",
"So",
"every",
"operation",
"to",
"self",
"this",
"mask",
"will",
"be",
"taken",
"into",
"account",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L280-L304 | [
"def",
"set_mask",
"(",
"self",
",",
"mask_img",
")",
":",
"mask",
"=",
"load_mask",
"(",
"mask_img",
",",
"allow_empty",
"=",
"True",
")",
"check_img_compatibility",
"(",
"self",
".",
"img",
",",
"mask",
",",
"only_check_3d",
"=",
"True",
")",
"# this wil... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | MedicalImage._mask_data | Return the data masked with self.mask
Parameters
----------
data: np.ndarray
Returns
-------
masked np.ndarray
Raises
------
ValueError if the data and mask dimensions are not compatible.
Other exceptions related to numpy computations. | boyle/image/base.py | def _mask_data(self, data):
"""Return the data masked with self.mask
Parameters
----------
data: np.ndarray
Returns
-------
masked np.ndarray
Raises
------
ValueError if the data and mask dimensions are not compatible.
Other exce... | def _mask_data(self, data):
"""Return the data masked with self.mask
Parameters
----------
data: np.ndarray
Returns
-------
masked np.ndarray
Raises
------
ValueError if the data and mask dimensions are not compatible.
Other exce... | [
"Return",
"the",
"data",
"masked",
"with",
"self",
".",
"mask"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L306-L330 | [
"def",
"_mask_data",
"(",
"self",
",",
"data",
")",
":",
"self",
".",
"_check_for_mask",
"(",
")",
"msk_data",
"=",
"self",
".",
"mask",
".",
"get_data",
"(",
")",
"if",
"self",
".",
"ndim",
"==",
"3",
":",
"return",
"data",
"[",
"msk_data",
"]",
"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | MedicalImage.apply_smoothing | Set self._smooth_fwhm and then smooths the data.
See boyle.nifti.smooth.smooth_imgs.
Returns
-------
the smoothed data deepcopied. | boyle/image/base.py | def apply_smoothing(self, smooth_fwhm):
"""Set self._smooth_fwhm and then smooths the data.
See boyle.nifti.smooth.smooth_imgs.
Returns
-------
the smoothed data deepcopied.
"""
if smooth_fwhm <= 0:
return
old_smooth_fwhm = self._smooth_fw... | def apply_smoothing(self, smooth_fwhm):
"""Set self._smooth_fwhm and then smooths the data.
See boyle.nifti.smooth.smooth_imgs.
Returns
-------
the smoothed data deepcopied.
"""
if smooth_fwhm <= 0:
return
old_smooth_fwhm = self._smooth_fw... | [
"Set",
"self",
".",
"_smooth_fwhm",
"and",
"then",
"smooths",
"the",
"data",
".",
"See",
"boyle",
".",
"nifti",
".",
"smooth",
".",
"smooth_imgs",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L332-L353 | [
"def",
"apply_smoothing",
"(",
"self",
",",
"smooth_fwhm",
")",
":",
"if",
"smooth_fwhm",
"<=",
"0",
":",
"return",
"old_smooth_fwhm",
"=",
"self",
".",
"_smooth_fwhm",
"self",
".",
"_smooth_fwhm",
"=",
"smooth_fwhm",
"try",
":",
"data",
"=",
"self",
".",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | MedicalImage.mask_and_flatten | Return a vector of the masked data.
Returns
-------
np.ndarray, tuple of indices (np.ndarray), tuple of the mask shape | boyle/image/base.py | def mask_and_flatten(self):
"""Return a vector of the masked data.
Returns
-------
np.ndarray, tuple of indices (np.ndarray), tuple of the mask shape
"""
self._check_for_mask()
return self.get_data(smoothed=True, masked=True, safe_copy=False)[self.get_mask_indic... | def mask_and_flatten(self):
"""Return a vector of the masked data.
Returns
-------
np.ndarray, tuple of indices (np.ndarray), tuple of the mask shape
"""
self._check_for_mask()
return self.get_data(smoothed=True, masked=True, safe_copy=False)[self.get_mask_indic... | [
"Return",
"a",
"vector",
"of",
"the",
"masked",
"data",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L355-L365 | [
"def",
"mask_and_flatten",
"(",
"self",
")",
":",
"self",
".",
"_check_for_mask",
"(",
")",
"return",
"self",
".",
"get_data",
"(",
"smoothed",
"=",
"True",
",",
"masked",
"=",
"True",
",",
"safe_copy",
"=",
"False",
")",
"[",
"self",
".",
"get_mask_indi... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | MedicalImage.unmask | Use self.mask to reshape arr and self.img to get an affine and header to create
a new self.img using the data in arr.
If self.has_mask() is False, will return the same arr. | boyle/image/base.py | def unmask(self, arr):
"""Use self.mask to reshape arr and self.img to get an affine and header to create
a new self.img using the data in arr.
If self.has_mask() is False, will return the same arr.
"""
self._check_for_mask()
if 1 > arr.ndim > 2:
raise ValueE... | def unmask(self, arr):
"""Use self.mask to reshape arr and self.img to get an affine and header to create
a new self.img using the data in arr.
If self.has_mask() is False, will return the same arr.
"""
self._check_for_mask()
if 1 > arr.ndim > 2:
raise ValueE... | [
"Use",
"self",
".",
"mask",
"to",
"reshape",
"arr",
"and",
"self",
".",
"img",
"to",
"get",
"an",
"affine",
"and",
"header",
"to",
"create",
"a",
"new",
"self",
".",
"img",
"using",
"the",
"data",
"in",
"arr",
".",
"If",
"self",
".",
"has_mask",
"(... | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L367-L382 | [
"def",
"unmask",
"(",
"self",
",",
"arr",
")",
":",
"self",
".",
"_check_for_mask",
"(",
")",
"if",
"1",
">",
"arr",
".",
"ndim",
">",
"2",
":",
"raise",
"ValueError",
"(",
"'The given array has {} dimensions while my mask has {}. '",
"'Masked data must be 1D or 2... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | MedicalImage.to_file | Save this object instance in outpath.
Parameters
----------
outpath: str
Output file path | boyle/image/base.py | def to_file(self, outpath):
"""Save this object instance in outpath.
Parameters
----------
outpath: str
Output file path
"""
if not self.has_mask() and not self.is_smoothed():
save_niigz(outpath, self.img)
else:
save_niigz(outp... | def to_file(self, outpath):
"""Save this object instance in outpath.
Parameters
----------
outpath: str
Output file path
"""
if not self.has_mask() and not self.is_smoothed():
save_niigz(outpath, self.img)
else:
save_niigz(outp... | [
"Save",
"this",
"object",
"instance",
"in",
"outpath",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/image/base.py#L384-L396 | [
"def",
"to_file",
"(",
"self",
",",
"outpath",
")",
":",
"if",
"not",
"self",
".",
"has_mask",
"(",
")",
"and",
"not",
"self",
".",
"is_smoothed",
"(",
")",
":",
"save_niigz",
"(",
"outpath",
",",
"self",
".",
"img",
")",
"else",
":",
"save_niigz",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | setup_logging | Setup logging configuration. | boyle/utils/logger.py | def setup_logging(log_config_file=op.join(op.dirname(__file__), 'logger.yml'),
log_default_level=LOG_LEVEL,
env_key=MODULE_NAME.upper() + '_LOG_CFG'):
"""Setup logging configuration."""
path = log_config_file
value = os.getenv(env_key, None)
if value:
path = v... | def setup_logging(log_config_file=op.join(op.dirname(__file__), 'logger.yml'),
log_default_level=LOG_LEVEL,
env_key=MODULE_NAME.upper() + '_LOG_CFG'):
"""Setup logging configuration."""
path = log_config_file
value = os.getenv(env_key, None)
if value:
path = v... | [
"Setup",
"logging",
"configuration",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/utils/logger.py#L13-L31 | [
"def",
"setup_logging",
"(",
"log_config_file",
"=",
"op",
".",
"join",
"(",
"op",
".",
"dirname",
"(",
"__file__",
")",
",",
"'logger.yml'",
")",
",",
"log_default_level",
"=",
"LOG_LEVEL",
",",
"env_key",
"=",
"MODULE_NAME",
".",
"upper",
"(",
")",
"+",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | _read_meta_header | Return a dictionary of meta data from meta header file.
Parameters
----------
filename: str
Path to a .mhd file
Returns
-------
meta_dict: dict
A dictionary with the .mhd header content. | boyle/mhd/read.py | def _read_meta_header(filename):
"""Return a dictionary of meta data from meta header file.
Parameters
----------
filename: str
Path to a .mhd file
Returns
-------
meta_dict: dict
A dictionary with the .mhd header content.
"""
fileIN = open(filename, 'r')
line ... | def _read_meta_header(filename):
"""Return a dictionary of meta data from meta header file.
Parameters
----------
filename: str
Path to a .mhd file
Returns
-------
meta_dict: dict
A dictionary with the .mhd header content.
"""
fileIN = open(filename, 'r')
line ... | [
"Return",
"a",
"dictionary",
"of",
"meta",
"data",
"from",
"meta",
"header",
"file",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/mhd/read.py#L20-L50 | [
"def",
"_read_meta_header",
"(",
"filename",
")",
":",
"fileIN",
"=",
"open",
"(",
"filename",
",",
"'r'",
")",
"line",
"=",
"fileIN",
".",
"readline",
"(",
")",
"meta_dict",
"=",
"{",
"}",
"tag_flag",
"=",
"[",
"False",
"]",
"*",
"len",
"(",
"MHD_TA... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | load_raw_data_with_mhd | Return a dictionary of meta data from meta header file.
Parameters
----------
filename: str
Path to a .mhd file
Returns
-------
data: numpy.ndarray
n-dimensional image data array.
meta_dict: dict
A dictionary with the .mhd header content. | boyle/mhd/read.py | def load_raw_data_with_mhd(filename):
"""Return a dictionary of meta data from meta header file.
Parameters
----------
filename: str
Path to a .mhd file
Returns
-------
data: numpy.ndarray
n-dimensional image data array.
meta_dict: dict
A dictionary with the .m... | def load_raw_data_with_mhd(filename):
"""Return a dictionary of meta data from meta header file.
Parameters
----------
filename: str
Path to a .mhd file
Returns
-------
data: numpy.ndarray
n-dimensional image data array.
meta_dict: dict
A dictionary with the .m... | [
"Return",
"a",
"dictionary",
"of",
"meta",
"data",
"from",
"meta",
"header",
"file",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/mhd/read.py#L53-L98 | [
"def",
"load_raw_data_with_mhd",
"(",
"filename",
")",
":",
"meta_dict",
"=",
"_read_meta_header",
"(",
"filename",
")",
"dim",
"=",
"int",
"(",
"meta_dict",
"[",
"'NDims'",
"]",
")",
"assert",
"(",
"meta_dict",
"[",
"'ElementType'",
"]",
"in",
"MHD_TO_NUMPY_T... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | get_3D_from_4D | Return a 3D volume from a 4D nifti image file
Parameters
----------
filename: str
Path to the 4D .mhd file
vol_idx: int
Index of the 3D volume to be extracted from the 4D volume.
Returns
-------
vol, hdr
The data array and the new 3D image header. | boyle/mhd/read.py | def get_3D_from_4D(filename, vol_idx=0):
"""Return a 3D volume from a 4D nifti image file
Parameters
----------
filename: str
Path to the 4D .mhd file
vol_idx: int
Index of the 3D volume to be extracted from the 4D volume.
Returns
-------
vol, hdr
The data arra... | def get_3D_from_4D(filename, vol_idx=0):
"""Return a 3D volume from a 4D nifti image file
Parameters
----------
filename: str
Path to the 4D .mhd file
vol_idx: int
Index of the 3D volume to be extracted from the 4D volume.
Returns
-------
vol, hdr
The data arra... | [
"Return",
"a",
"3D",
"volume",
"from",
"a",
"4D",
"nifti",
"image",
"file"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/mhd/read.py#L101-L137 | [
"def",
"get_3D_from_4D",
"(",
"filename",
",",
"vol_idx",
"=",
"0",
")",
":",
"def",
"remove_4th_element_from_hdr_string",
"(",
"hdr",
",",
"fieldname",
")",
":",
"if",
"fieldname",
"in",
"hdr",
":",
"hdr",
"[",
"fieldname",
"]",
"=",
"' '",
".",
"join",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | _safe_cache | A wrapper for mem.cache that flushes the cache if the version
number of nibabel has changed. | boyle/utils/cache_mixin.py | def _safe_cache(memory, func, **kwargs):
""" A wrapper for mem.cache that flushes the cache if the version
number of nibabel has changed.
"""
cachedir = memory.cachedir
if cachedir is None or cachedir in __CACHE_CHECKED:
return memory.cache(func, **kwargs)
version_file = os.path.jo... | def _safe_cache(memory, func, **kwargs):
""" A wrapper for mem.cache that flushes the cache if the version
number of nibabel has changed.
"""
cachedir = memory.cachedir
if cachedir is None or cachedir in __CACHE_CHECKED:
return memory.cache(func, **kwargs)
version_file = os.path.jo... | [
"A",
"wrapper",
"for",
"mem",
".",
"cache",
"that",
"flushes",
"the",
"cache",
"if",
"the",
"version",
"number",
"of",
"nibabel",
"has",
"changed",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/utils/cache_mixin.py#L31-L90 | [
"def",
"_safe_cache",
"(",
"memory",
",",
"func",
",",
"*",
"*",
"kwargs",
")",
":",
"cachedir",
"=",
"memory",
".",
"cachedir",
"if",
"cachedir",
"is",
"None",
"or",
"cachedir",
"in",
"__CACHE_CHECKED",
":",
"return",
"memory",
".",
"cache",
"(",
"func"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | cache | Return a joblib.Memory object.
The memory_level determines the level above which the wrapped
function output is cached. By specifying a numeric value for
this level, the user can to control the amount of cache memory
used. This function will cache the function call or not
depending on the cache lev... | boyle/utils/cache_mixin.py | def cache(func, memory, func_memory_level=None, memory_level=None,
**kwargs):
""" Return a joblib.Memory object.
The memory_level determines the level above which the wrapped
function output is cached. By specifying a numeric value for
this level, the user can to control the amount of cache m... | def cache(func, memory, func_memory_level=None, memory_level=None,
**kwargs):
""" Return a joblib.Memory object.
The memory_level determines the level above which the wrapped
function output is cached. By specifying a numeric value for
this level, the user can to control the amount of cache m... | [
"Return",
"a",
"joblib",
".",
"Memory",
"object",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/utils/cache_mixin.py#L93-L160 | [
"def",
"cache",
"(",
"func",
",",
"memory",
",",
"func_memory_level",
"=",
"None",
",",
"memory_level",
"=",
"None",
",",
"*",
"*",
"kwargs",
")",
":",
"verbose",
"=",
"kwargs",
".",
"get",
"(",
"'verbose'",
",",
"0",
")",
"# memory_level and func_memory_l... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | CacheMixin._cache | Return a joblib.Memory object.
The memory_level determines the level above which the wrapped
function output is cached. By specifying a numeric value for
this level, the user can to control the amount of cache memory
used. This function will cache the function call or not
depend... | boyle/utils/cache_mixin.py | def _cache(self, func, func_memory_level=1, **kwargs):
""" Return a joblib.Memory object.
The memory_level determines the level above which the wrapped
function output is cached. By specifying a numeric value for
this level, the user can to control the amount of cache memory
use... | def _cache(self, func, func_memory_level=1, **kwargs):
""" Return a joblib.Memory object.
The memory_level determines the level above which the wrapped
function output is cached. By specifying a numeric value for
this level, the user can to control the amount of cache memory
use... | [
"Return",
"a",
"joblib",
".",
"Memory",
"object",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/utils/cache_mixin.py#L174-L223 | [
"def",
"_cache",
"(",
"self",
",",
"func",
",",
"func_memory_level",
"=",
"1",
",",
"*",
"*",
"kwargs",
")",
":",
"verbose",
"=",
"getattr",
"(",
"self",
",",
"'verbose'",
",",
"0",
")",
"# Creates attributes if they don't exist",
"# This is to make creating the... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | save_niigz | Saves a volume into a Nifti (.nii.gz) file.
Parameters
----------
vol: Numpy 3D or 4D array
Volume with the data to be saved.
file_path: string
Output file name path
affine: (optional) 4x4 Numpy array
Array with the affine transform of the file.
This is needed if v... | boyle/nifti/storage.py | def save_niigz(filepath, vol, header=None, affine=None):
"""Saves a volume into a Nifti (.nii.gz) file.
Parameters
----------
vol: Numpy 3D or 4D array
Volume with the data to be saved.
file_path: string
Output file name path
affine: (optional) 4x4 Numpy array
Array wi... | def save_niigz(filepath, vol, header=None, affine=None):
"""Saves a volume into a Nifti (.nii.gz) file.
Parameters
----------
vol: Numpy 3D or 4D array
Volume with the data to be saved.
file_path: string
Output file name path
affine: (optional) 4x4 Numpy array
Array wi... | [
"Saves",
"a",
"volume",
"into",
"a",
"Nifti",
"(",
".",
"nii",
".",
"gz",
")",
"file",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/storage.py#L24-L75 | [
"def",
"save_niigz",
"(",
"filepath",
",",
"vol",
",",
"header",
"=",
"None",
",",
"affine",
"=",
"None",
")",
":",
"# delayed import because could not install nipy on Python 3 on OSX",
"we_have_nipy",
"=",
"False",
"try",
":",
"import",
"nipy",
".",
"core",
".",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | spatialimg_to_hdfgroup | Saves a Nifti1Image into an HDF5 group.
Parameters
----------
h5group: h5py Group
Output HDF5 file path
spatial_img: nibabel SpatialImage
Image to be saved
h5path: str
HDF5 group path where the image data will be saved.
Datasets will be created inside the given gro... | boyle/nifti/storage.py | def spatialimg_to_hdfgroup(h5group, spatial_img):
"""Saves a Nifti1Image into an HDF5 group.
Parameters
----------
h5group: h5py Group
Output HDF5 file path
spatial_img: nibabel SpatialImage
Image to be saved
h5path: str
HDF5 group path where the image data will be sav... | def spatialimg_to_hdfgroup(h5group, spatial_img):
"""Saves a Nifti1Image into an HDF5 group.
Parameters
----------
h5group: h5py Group
Output HDF5 file path
spatial_img: nibabel SpatialImage
Image to be saved
h5path: str
HDF5 group path where the image data will be sav... | [
"Saves",
"a",
"Nifti1Image",
"into",
"an",
"HDF5",
"group",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/storage.py#L78-L108 | [
"def",
"spatialimg_to_hdfgroup",
"(",
"h5group",
",",
"spatial_img",
")",
":",
"try",
":",
"h5group",
"[",
"'data'",
"]",
"=",
"spatial_img",
".",
"get_data",
"(",
")",
"h5group",
"[",
"'affine'",
"]",
"=",
"spatial_img",
".",
"get_affine",
"(",
")",
"if",... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | spatialimg_to_hdfpath | Saves a Nifti1Image into an HDF5 file.
Parameters
----------
file_path: string
Output HDF5 file path
spatial_img: nibabel SpatialImage
Image to be saved
h5path: string
HDF5 group path where the image data will be saved.
Datasets will be created inside the given gro... | boyle/nifti/storage.py | def spatialimg_to_hdfpath(file_path, spatial_img, h5path=None, append=True):
"""Saves a Nifti1Image into an HDF5 file.
Parameters
----------
file_path: string
Output HDF5 file path
spatial_img: nibabel SpatialImage
Image to be saved
h5path: string
HDF5 group path where... | def spatialimg_to_hdfpath(file_path, spatial_img, h5path=None, append=True):
"""Saves a Nifti1Image into an HDF5 file.
Parameters
----------
file_path: string
Output HDF5 file path
spatial_img: nibabel SpatialImage
Image to be saved
h5path: string
HDF5 group path where... | [
"Saves",
"a",
"Nifti1Image",
"into",
"an",
"HDF5",
"file",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/storage.py#L111-L157 | [
"def",
"spatialimg_to_hdfpath",
"(",
"file_path",
",",
"spatial_img",
",",
"h5path",
"=",
"None",
",",
"append",
"=",
"True",
")",
":",
"if",
"h5path",
"is",
"None",
":",
"h5path",
"=",
"'/img'",
"mode",
"=",
"'w'",
"if",
"os",
".",
"path",
".",
"exist... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | hdfpath_to_nifti1image | Returns a nibabel Nifti1Image from a HDF5 group datasets
Parameters
----------
file_path: string
HDF5 file path
h5path:
HDF5 group path in file_path
Returns
-------
nibabel Nifti1Image | boyle/nifti/storage.py | def hdfpath_to_nifti1image(file_path, h5path):
"""Returns a nibabel Nifti1Image from a HDF5 group datasets
Parameters
----------
file_path: string
HDF5 file path
h5path:
HDF5 group path in file_path
Returns
-------
nibabel Nifti1Image
"""
with h5py.File(fil... | def hdfpath_to_nifti1image(file_path, h5path):
"""Returns a nibabel Nifti1Image from a HDF5 group datasets
Parameters
----------
file_path: string
HDF5 file path
h5path:
HDF5 group path in file_path
Returns
-------
nibabel Nifti1Image
"""
with h5py.File(fil... | [
"Returns",
"a",
"nibabel",
"Nifti1Image",
"from",
"a",
"HDF5",
"group",
"datasets"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/storage.py#L160-L176 | [
"def",
"hdfpath_to_nifti1image",
"(",
"file_path",
",",
"h5path",
")",
":",
"with",
"h5py",
".",
"File",
"(",
"file_path",
",",
"'r'",
")",
"as",
"f",
":",
"return",
"hdfgroup_to_nifti1image",
"(",
"f",
"[",
"h5path",
"]",
")"
] | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | hdfgroup_to_nifti1image | Returns a nibabel Nifti1Image from a HDF5 group datasets
Parameters
----------
h5group: h5py.Group
HDF5 group
Returns
-------
nibabel Nifti1Image | boyle/nifti/storage.py | def hdfgroup_to_nifti1image(h5group):
"""Returns a nibabel Nifti1Image from a HDF5 group datasets
Parameters
----------
h5group: h5py.Group
HDF5 group
Returns
-------
nibabel Nifti1Image
"""
try:
data = h5group['data'][:]
affine = h5group['affine'][:]
... | def hdfgroup_to_nifti1image(h5group):
"""Returns a nibabel Nifti1Image from a HDF5 group datasets
Parameters
----------
h5group: h5py.Group
HDF5 group
Returns
-------
nibabel Nifti1Image
"""
try:
data = h5group['data'][:]
affine = h5group['affine'][:]
... | [
"Returns",
"a",
"nibabel",
"Nifti1Image",
"from",
"a",
"HDF5",
"group",
"datasets"
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/storage.py#L179-L206 | [
"def",
"hdfgroup_to_nifti1image",
"(",
"h5group",
")",
":",
"try",
":",
"data",
"=",
"h5group",
"[",
"'data'",
"]",
"[",
":",
"]",
"affine",
"=",
"h5group",
"[",
"'affine'",
"]",
"[",
":",
"]",
"extra",
"=",
"None",
"if",
"'extra'",
"in",
"h5group",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | get_nifti1hdr_from_h5attrs | Transforms an H5py Attributes set to a dict.
Converts unicode string keys into standard strings
and each value into a numpy array.
Parameters
----------
h5attrs: H5py Attributes
Returns
--------
dict | boyle/nifti/storage.py | def get_nifti1hdr_from_h5attrs(h5attrs):
"""Transforms an H5py Attributes set to a dict.
Converts unicode string keys into standard strings
and each value into a numpy array.
Parameters
----------
h5attrs: H5py Attributes
Returns
--------
dict
"""
hdr = nib.Nifti1Header()
... | def get_nifti1hdr_from_h5attrs(h5attrs):
"""Transforms an H5py Attributes set to a dict.
Converts unicode string keys into standard strings
and each value into a numpy array.
Parameters
----------
h5attrs: H5py Attributes
Returns
--------
dict
"""
hdr = nib.Nifti1Header()
... | [
"Transforms",
"an",
"H5py",
"Attributes",
"set",
"to",
"a",
"dict",
".",
"Converts",
"unicode",
"string",
"keys",
"into",
"standard",
"strings",
"and",
"each",
"value",
"into",
"a",
"numpy",
"array",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/storage.py#L209-L226 | [
"def",
"get_nifti1hdr_from_h5attrs",
"(",
"h5attrs",
")",
":",
"hdr",
"=",
"nib",
".",
"Nifti1Header",
"(",
")",
"for",
"k",
"in",
"list",
"(",
"h5attrs",
".",
"keys",
"(",
")",
")",
":",
"hdr",
"[",
"str",
"(",
"k",
")",
"]",
"=",
"np",
".",
"ar... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | all_childnodes_to_nifti1img | Returns in a list all images found under h5group.
Parameters
----------
h5group: h5py.Group
HDF group
Returns
-------
list of nifti1Image | boyle/nifti/storage.py | def all_childnodes_to_nifti1img(h5group):
"""Returns in a list all images found under h5group.
Parameters
----------
h5group: h5py.Group
HDF group
Returns
-------
list of nifti1Image
"""
child_nodes = []
def append_parent_if_dataset(name, obj):
if isinstance(obj... | def all_childnodes_to_nifti1img(h5group):
"""Returns in a list all images found under h5group.
Parameters
----------
h5group: h5py.Group
HDF group
Returns
-------
list of nifti1Image
"""
child_nodes = []
def append_parent_if_dataset(name, obj):
if isinstance(obj... | [
"Returns",
"in",
"a",
"list",
"all",
"images",
"found",
"under",
"h5group",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/storage.py#L229-L252 | [
"def",
"all_childnodes_to_nifti1img",
"(",
"h5group",
")",
":",
"child_nodes",
"=",
"[",
"]",
"def",
"append_parent_if_dataset",
"(",
"name",
",",
"obj",
")",
":",
"if",
"isinstance",
"(",
"obj",
",",
"h5py",
".",
"Dataset",
")",
":",
"if",
"name",
".",
... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | insert_volumes_in_one_dataset | Inserts all given nifti files from file_list into one dataset in fname.
This will not check if the dimensionality of all files match.
Parameters
----------
file_path: string
HDF5 file path
h5path: string
file_list: list of strings
newshape: tuple or lambda function
If Non... | boyle/nifti/storage.py | def insert_volumes_in_one_dataset(file_path, h5path, file_list, newshape=None,
concat_axis=0, dtype=None, append=True):
"""Inserts all given nifti files from file_list into one dataset in fname.
This will not check if the dimensionality of all files match.
Parameters
-... | def insert_volumes_in_one_dataset(file_path, h5path, file_list, newshape=None,
concat_axis=0, dtype=None, append=True):
"""Inserts all given nifti files from file_list into one dataset in fname.
This will not check if the dimensionality of all files match.
Parameters
-... | [
"Inserts",
"all",
"given",
"nifti",
"files",
"from",
"file_list",
"into",
"one",
"dataset",
"in",
"fname",
".",
"This",
"will",
"not",
"check",
"if",
"the",
"dimensionality",
"of",
"all",
"files",
"match",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/nifti/storage.py#L255-L382 | [
"def",
"insert_volumes_in_one_dataset",
"(",
"file_path",
",",
"h5path",
",",
"file_list",
",",
"newshape",
"=",
"None",
",",
"concat_axis",
"=",
"0",
",",
"dtype",
"=",
"None",
",",
"append",
"=",
"True",
")",
":",
"def",
"isalambda",
"(",
"v",
")",
":"... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | treefall | Generate all combinations of the elements of iterable and its subsets.
Parameters
----------
iterable: list, set or dict or any iterable object
Returns
-------
A generator of all possible combinations of the iterable.
Example:
-------
>>> for i in treefall([1, 2, 3, 4, 5]): print(... | boyle/dicom/itertools.py | def treefall(iterable):
"""
Generate all combinations of the elements of iterable and its subsets.
Parameters
----------
iterable: list, set or dict or any iterable object
Returns
-------
A generator of all possible combinations of the iterable.
Example:
-------
>>> for i ... | def treefall(iterable):
"""
Generate all combinations of the elements of iterable and its subsets.
Parameters
----------
iterable: list, set or dict or any iterable object
Returns
-------
A generator of all possible combinations of the iterable.
Example:
-------
>>> for i ... | [
"Generate",
"all",
"combinations",
"of",
"the",
"elements",
"of",
"iterable",
"and",
"its",
"subsets",
"."
] | Neurita/boyle | python | https://github.com/Neurita/boyle/blob/2dae7199849395a209c887d5f30506e1de8a9ad9/boyle/dicom/itertools.py#L5-L32 | [
"def",
"treefall",
"(",
"iterable",
")",
":",
"num_elems",
"=",
"len",
"(",
"iterable",
")",
"for",
"i",
"in",
"range",
"(",
"num_elems",
",",
"-",
"1",
",",
"-",
"1",
")",
":",
"for",
"c",
"in",
"combinations",
"(",
"iterable",
",",
"i",
")",
":... | 2dae7199849395a209c887d5f30506e1de8a9ad9 |
valid | get_reliabledictionary_list | List existing reliable dictionaries.
List existing reliable dictionaries and respective schema for given application and service.
:param application_name: Name of the application.
:type application_name: str
:param service_name: Name of the service.
:type service_name: str | rcctl/rcctl/custom_reliablecollections.py | def get_reliabledictionary_list(client, application_name, service_name):
"""List existing reliable dictionaries.
List existing reliable dictionaries and respective schema for given application and service.
:param application_name: Name of the application.
:type application_name: str
:param service... | def get_reliabledictionary_list(client, application_name, service_name):
"""List existing reliable dictionaries.
List existing reliable dictionaries and respective schema for given application and service.
:param application_name: Name of the application.
:type application_name: str
:param service... | [
"List",
"existing",
"reliable",
"dictionaries",
"."
] | shalabhms/reliable-collections-cli | python | https://github.com/shalabhms/reliable-collections-cli/blob/195d69816fb5a6e1e9ab0ab66b606b1248b4780d/rcctl/rcctl/custom_reliablecollections.py#L12-L25 | [
"def",
"get_reliabledictionary_list",
"(",
"client",
",",
"application_name",
",",
"service_name",
")",
":",
"cluster",
"=",
"Cluster",
".",
"from_sfclient",
"(",
"client",
")",
"service",
"=",
"cluster",
".",
"get_application",
"(",
"application_name",
")",
".",
... | 195d69816fb5a6e1e9ab0ab66b606b1248b4780d |
valid | get_reliabledictionary_schema | Query Schema information for existing reliable dictionaries.
Query Schema information existing reliable dictionaries for given application and service.
:param application_name: Name of the application.
:type application_name: str
:param service_name: Name of the service.
:type service_name: str
... | rcctl/rcctl/custom_reliablecollections.py | def get_reliabledictionary_schema(client, application_name, service_name, dictionary_name, output_file=None):
"""Query Schema information for existing reliable dictionaries.
Query Schema information existing reliable dictionaries for given application and service.
:param application_name: Name of the appl... | def get_reliabledictionary_schema(client, application_name, service_name, dictionary_name, output_file=None):
"""Query Schema information for existing reliable dictionaries.
Query Schema information existing reliable dictionaries for given application and service.
:param application_name: Name of the appl... | [
"Query",
"Schema",
"information",
"for",
"existing",
"reliable",
"dictionaries",
"."
] | shalabhms/reliable-collections-cli | python | https://github.com/shalabhms/reliable-collections-cli/blob/195d69816fb5a6e1e9ab0ab66b606b1248b4780d/rcctl/rcctl/custom_reliablecollections.py#L27-L51 | [
"def",
"get_reliabledictionary_schema",
"(",
"client",
",",
"application_name",
",",
"service_name",
",",
"dictionary_name",
",",
"output_file",
"=",
"None",
")",
":",
"cluster",
"=",
"Cluster",
".",
"from_sfclient",
"(",
"client",
")",
"dictionary",
"=",
"cluster... | 195d69816fb5a6e1e9ab0ab66b606b1248b4780d |
valid | query_reliabledictionary | Query existing reliable dictionary.
Query existing reliable dictionaries for given application and service.
:param application_name: Name of the application.
:type application_name: str
:param service_name: Name of the service.
:type service_name: str
:param dictionary_name: Name of the reliab... | rcctl/rcctl/custom_reliablecollections.py | def query_reliabledictionary(client, application_name, service_name, dictionary_name, query_string, partition_key=None, partition_id=None, output_file=None):
"""Query existing reliable dictionary.
Query existing reliable dictionaries for given application and service.
:param application_name: Name of the ... | def query_reliabledictionary(client, application_name, service_name, dictionary_name, query_string, partition_key=None, partition_id=None, output_file=None):
"""Query existing reliable dictionary.
Query existing reliable dictionaries for given application and service.
:param application_name: Name of the ... | [
"Query",
"existing",
"reliable",
"dictionary",
"."
] | shalabhms/reliable-collections-cli | python | https://github.com/shalabhms/reliable-collections-cli/blob/195d69816fb5a6e1e9ab0ab66b606b1248b4780d/rcctl/rcctl/custom_reliablecollections.py#L78-L124 | [
"def",
"query_reliabledictionary",
"(",
"client",
",",
"application_name",
",",
"service_name",
",",
"dictionary_name",
",",
"query_string",
",",
"partition_key",
"=",
"None",
",",
"partition_id",
"=",
"None",
",",
"output_file",
"=",
"None",
")",
":",
"cluster",
... | 195d69816fb5a6e1e9ab0ab66b606b1248b4780d |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.