INSTRUCTION stringlengths 1 8.43k | RESPONSE stringlengths 75 104k |
|---|---|
Export a numpy array to a png file. | def save(filename, numpy_data):
"""
Export a numpy array to a png file.
Arguments:
filename (str): A filename to which to save the png data
numpy_data (numpy.ndarray OR str): The numpy array to save to png.
OR a string: If a string is provded, it should be a binary png str
... |
Export a numpy array to a set of png files with each Z - index 2D array as its own 2D file. | def save_collection(png_filename_base, numpy_data, start_layers_at=1):
"""
Export a numpy array to a set of png files, with each Z-index 2D
array as its own 2D file.
Arguments:
png_filename_base: A filename template, such as "my-image-*.png"
which will lead t... |
Import all files matching the filename base given with png_filename_base. Images are ordered by alphabetical order which means that you * MUST * 0 - pad your numbers if they span a power of ten ( e. g. 0999 - 1000 or 09 - 10 ). This is handled automatically by its complementary function png. save_collection. Also look ... | def load_collection(png_filename_base):
"""
Import all files matching the filename base given with `png_filename_base`.
Images are ordered by alphabetical order, which means that you *MUST* 0-pad
your numbers if they span a power of ten (e.g. 0999-1000 or 09-10). This is
handled automatically by its... |
Print workspace status. | def print_workspace(self, name):
"""Print workspace status."""
path_list = find_path(name, self.config)
if len(path_list) == 0:
self.logger.error("No matches for `%s`" % name)
return False
for name, path in path_list.items():
self.print_status(name, ... |
Print repository status. | def print_status(self, repo_name, repo_path):
"""Print repository status."""
color = Color()
self.logger.info(color.colored(
"=> [%s] %s" % (repo_name, repo_path), "green"))
try:
repo = Repository(repo_path)
repo.status()
except RepositoryError... |
Gets the block - size for a given token at a given resolution. | def get_block_size(self, token, resolution=None):
"""
Gets the block-size for a given token at a given resolution.
Arguments:
token (str): The token to inspect
resolution (int : None): The resolution at which to inspect data.
If none is specified, uses th... |
Return a binary - encoded decompressed 2d image. You should specify a token and channel pair. For image data users should use the channel image. | def get_xy_slice(self, token, channel,
x_start, x_stop,
y_start, y_stop,
z_index,
resolution=0):
"""
Return a binary-encoded, decompressed 2d image. You should
specify a 'token' and 'channel' pair. For image dat... |
Get a RAMONVolume volumetric cutout from the neurodata server. | def get_volume(self, token, channel,
x_start, x_stop,
y_start, y_stop,
z_start, z_stop,
resolution=1,
block_size=DEFAULT_BLOCK_SIZE,
neariso=False):
"""
Get a RAMONVolume volumetric cutout f... |
Get volumetric cutout data from the neurodata server. | def get_cutout(self, token, channel,
x_start, x_stop,
y_start, y_stop,
z_start, z_stop,
t_start=0, t_stop=1,
resolution=1,
block_size=DEFAULT_BLOCK_SIZE,
neariso=False):
"""
... |
Post a cutout to the server. | def post_cutout(self, token, channel,
x_start,
y_start,
z_start,
data,
resolution=0):
"""
Post a cutout to the server.
Arguments:
token (str)
channel (str)
x_s... |
Accepts data in zyx. !!! | def _post_cutout_no_chunking_blosc(self, token, channel,
x_start, y_start, z_start,
data, resolution):
"""
Accepts data in zyx. !!!
"""
data = numpy.expand_dims(data, axis=0)
blosc_data = blosc.pack_arr... |
Import a TIFF file into a numpy array. | def load(tiff_filename):
"""
Import a TIFF file into a numpy array.
Arguments:
tiff_filename: A string filename of a TIFF datafile
Returns:
A numpy array with data from the TIFF file
"""
# Expand filename to be absolute
tiff_filename = os.path.expanduser(tiff_filename)
... |
Export a numpy array to a TIFF file. | def save(tiff_filename, numpy_data):
"""
Export a numpy array to a TIFF file.
Arguments:
tiff_filename: A filename to which to save the TIFF data
numpy_data: The numpy array to save to TIFF
Returns:
String. The expanded filename that now holds the TIFF data
"""
# E... |
Load a multipage tiff into a single variable in x y z format. | def load_tiff_multipage(tiff_filename, dtype='float32'):
"""
Load a multipage tiff into a single variable in x,y,z format.
Arguments:
tiff_filename: Filename of source data
dtype: data type to use for the returned tensor
Returns:
Array containing contents from i... |
Write config in configuration file. Data must me a dict. | def write(self):
"""
Write config in configuration file.
Data must me a dict.
"""
file = open(self.config_file, "w+")
file.write(yaml.dump(dict(self), default_flow_style=False))
file.close() |
Clone repository from url. | def clone(self, url):
"""Clone repository from url."""
return self.execute("%s branch %s %s" % (self.executable,
url, self.path)) |
Get version from package resources. | def get_version():
"""Get version from package resources."""
requirement = pkg_resources.Requirement.parse("yoda")
provider = pkg_resources.get_provider(requirement)
return provider.version |
Mixing and matching positional args and keyword options. | def mix_and_match(name, greeting='Hello', yell=False):
'''Mixing and matching positional args and keyword options.'''
say = '%s, %s' % (greeting, name)
if yell:
print '%s!' % say.upper()
else:
print '%s.' % say |
Same as mix_and_match but using the | def option_decorator(name, greeting, yell):
'''Same as mix_and_match, but using the @option decorator.'''
# Use the @option decorator when you need more control over the
# command line options.
say = '%s, %s' % (greeting, name)
if yell:
print '%s!' % say.upper()
else:
print '%s.'... |
Import a nifti file into a numpy array. TODO: Currently only transfers raw data for compatibility with annotation and ND formats | def load(nifti_filename):
"""
Import a nifti file into a numpy array. TODO: Currently only
transfers raw data for compatibility with annotation and ND formats
Arguments:
nifti_filename (str): A string filename of a nifti datafile
Returns:
A numpy array with data from the nifti fi... |
Export a numpy array to a nifti file. TODO: currently using dummy headers and identity matrix affine transform. This can be expanded. | def save(nifti_filename, numpy_data):
"""
Export a numpy array to a nifti file. TODO: currently using dummy
headers and identity matrix affine transform. This can be expanded.
Arguments:
nifti_filename (str): A filename to which to save the nifti data
numpy_data (numpy.ndarray): The nu... |
Return the status - code of the API ( estimated using the public - tokens lookup page ). | def ping(self, suffix='public_tokens/'):
"""
Return the status-code of the API (estimated using the public-tokens
lookup page).
Arguments:
suffix (str : 'public_tokens/'): The url endpoint to check
Returns:
int: status code
"""
return sel... |
Return a constructed URL appending an optional suffix ( uri path ). | def url(self, suffix=""):
"""
Return a constructed URL, appending an optional suffix (uri path).
Arguments:
suffix (str : ""): The suffix to append to the end of the URL
Returns:
str: The complete URL
"""
return super(neuroRemote,
... |
Requests a list of next - available - IDs from the server. | def reserve_ids(self, token, channel, quantity):
"""
Requests a list of next-available-IDs from the server.
Arguments:
quantity (int): The number of IDs to reserve
Returns:
int[quantity]: List of IDs you've been granted
"""
quantity = str(quantit... |
Call the restful endpoint to merge two RAMON objects into one. | def merge_ids(self, token, channel, ids, delete=False):
"""
Call the restful endpoint to merge two RAMON objects into one.
Arguments:
token (str): The token to inspect
channel (str): The channel to inspect
ids (int[]): the list of the IDs to merge
... |
Creates channels given a dictionary in new_channels_data dataset name and token ( project ) name. | def create_channels(self, dataset, token, new_channels_data):
"""
Creates channels given a dictionary in 'new_channels_data'
, 'dataset' name, and 'token' (project) name.
Arguments:
token (str): Token to identify project
dataset (str): Dataset name to identify da... |
Kick off the propagate function on the remote server. | def propagate(self, token, channel):
"""
Kick off the propagate function on the remote server.
Arguments:
token (str): The token to propagate
channel (str): The channel to propagate
Returns:
boolean: Success
"""
if self.get_propagate_... |
Get the propagate status for a token/ channel pair. | def get_propagate_status(self, token, channel):
"""
Get the propagate status for a token/channel pair.
Arguments:
token (str): The token to check
channel (str): The channel to check
Returns:
str: The status code
"""
url = self.url('sd... |
Creates a project with the given parameters. | def create_project(self,
project_name,
dataset_name,
hostname,
is_public,
s3backend=0,
kvserver='localhost',
kvengine='MySQL',
mdengine=... |
Lists a set of projects related to a dataset. | def list_projects(self, dataset_name):
"""
Lists a set of projects related to a dataset.
Arguments:
dataset_name (str): Dataset name to search projects for
Returns:
dict: Projects found based on dataset query
"""
url = self.url() + "/nd/resource/... |
Creates a token with the given parameters. Arguments: project_name ( str ): Project name dataset_name ( str ): Dataset name project is based on token_name ( str ): Token name is_public ( int ): 1 is public. 0 is not public Returns: bool: True if project created false if not created. | def create_token(self,
token_name,
project_name,
dataset_name,
is_public):
"""
Creates a token with the given parameters.
Arguments:
project_name (str): Project name
dataset_name (str): Da... |
Get a token with the given parameters. Arguments: project_name ( str ): Project name dataset_name ( str ): Dataset name project is based on token_name ( str ): Token name Returns: dict: Token info | def get_token(self,
token_name,
project_name,
dataset_name):
"""
Get a token with the given parameters.
Arguments:
project_name (str): Project name
dataset_name (str): Dataset name project is based on
token... |
Delete a token with the given parameters. Arguments: project_name ( str ): Project name dataset_name ( str ): Dataset name project is based on token_name ( str ): Token name channel_name ( str ): Channel name project is based on Returns: bool: True if project deleted false if not deleted. | def delete_token(self,
token_name,
project_name,
dataset_name):
"""
Delete a token with the given parameters.
Arguments:
project_name (str): Project name
dataset_name (str): Dataset name project is based on
... |
Lists a set of tokens that are public in Neurodata. Arguments: Returns: dict: Public tokens found in Neurodata | def list_tokens(self):
"""
Lists a set of tokens that are public in Neurodata.
Arguments:
Returns:
dict: Public tokens found in Neurodata
"""
url = self.url() + "/nd/resource/public/token/"
req = self.remote_utils.get_url(url)
if req.status_co... |
Creates a dataset. | def create_dataset(self,
name,
x_img_size,
y_img_size,
z_img_size,
x_vox_res,
y_vox_res,
z_vox_res,
x_offset=0,
y... |
Returns info regarding a particular dataset. | def get_dataset(self, name):
"""
Returns info regarding a particular dataset.
Arugments:
name (str): Dataset name
Returns:
dict: Dataset information
"""
url = self.url() + "/resource/dataset/{}".format(name)
req = self.remote_utils.get_ur... |
Lists datasets in resources. Setting get_global_public to True will retrieve all public datasets in cloud. False will get user s public datasets. | def list_datasets(self, get_global_public):
"""
Lists datasets in resources. Setting 'get_global_public' to 'True'
will retrieve all public datasets in cloud. 'False' will get user's
public datasets.
Arguments:
get_global_public (bool): True if user wants all public ... |
Arguments: name ( str ): Name of dataset to delete | def delete_dataset(self, name):
"""
Arguments:
name (str): Name of dataset to delete
Returns:
bool: True if dataset deleted, False if not
"""
url = self.url() + "/resource/dataset/{}".format(name)
req = self.remote_utils.delete_url(url)
i... |
Create a new channel on the Remote using channel_data. | def create_channel(self,
channel_name,
project_name,
dataset_name,
channel_type,
dtype,
startwindow,
endwindow,
readonly=0,
... |
Gets info about a channel given its name name of its project and name of its dataset. | def get_channel(self, channel_name, project_name, dataset_name):
"""
Gets info about a channel given its name, name of its project
, and name of its dataset.
Arguments:
channel_name (str): Channel name
project_name (str): Project name
dataset_name (st... |
Parse show subcommand. | def parse(self):
"""Parse show subcommand."""
parser = self.subparser.add_parser(
"show",
help="Show workspace details",
description="Show workspace details.")
group = parser.add_mutually_exclusive_group(required=True)
group.add_argument('--all', acti... |
Execute show subcommand. | def execute(self, args):
"""Execute show subcommand."""
if args.name is not None:
self.show_workspace(slashes2dash(args.name))
elif args.all is not None:
self.show_all() |
Show specific workspace. | def show_workspace(self, name):
"""Show specific workspace."""
if not self.workspace.exists(name):
raise ValueError("Workspace `%s` doesn't exists." % name)
color = Color()
workspaces = self.workspace.list()
self.logger.info("<== %s workspace ==>" % color.colored(na... |
Show details for all workspaces. | def show_all(self):
"""Show details for all workspaces."""
for ws in self.workspace.list().keys():
self.show_workspace(ws)
print("\n\n") |
Get the base URL of the Remote. | def url(self, endpoint=''):
"""
Get the base URL of the Remote.
Arguments:
None
Returns:
`str` base URL
"""
if not endpoint.startswith('/'):
endpoint = "/" + endpoint
return self.protocol + "://" + self.hostname + endpoint |
Ping the server to make sure that you can access the base URL. | def ping(self, endpoint=''):
"""
Ping the server to make sure that you can access the base URL.
Arguments:
None
Returns:
`boolean` Successful access of server (or status code)
"""
r = requests.get(self.url() + "/" + endpoint)
return r.stat... |
Converts a dense annotation to a DAE using Marching Cubes ( PyMCubes ). | def export_dae(filename, cutout, level=0):
"""
Converts a dense annotation to a DAE, using Marching Cubes (PyMCubes).
Arguments:
filename (str): The filename to write out to
cutout (numpy.ndarray): The dense annotation
level (int): The level at which to run mcubes
Returns:
... |
Converts a dense annotation to a obj using Marching Cubes ( PyMCubes ). | def export_obj(filename, cutout, level=0):
"""
Converts a dense annotation to a obj, using Marching Cubes (PyMCubes).
Arguments:
filename (str): The filename to write out to
cutout (numpy.ndarray): The dense annotation
level (int): The level at which to run mcubes
Returns:
... |
Converts a dense annotation to a. PLY using Marching Cubes ( PyMCubes ). | def export_ply(filename, cutout, level=0):
"""
Converts a dense annotation to a .PLY, using Marching Cubes (PyMCubes).
Arguments:
filename (str): The filename to write out to
cutout (numpy.ndarray): The dense annotation
level (int): The level at which to run mcubes
Returns:
... |
Guess the appropriate data type from file extension. | def _guess_format_from_extension(ext):
"""
Guess the appropriate data type from file extension.
Arguments:
ext: The file extension (period optional)
Returns:
String. The format (without leading period),
or False if none was found or couldn't be guessed
"""
... |
Reads in a file from disk. | def open(in_file, in_fmt=None):
"""
Reads in a file from disk.
Arguments:
in_file: The name of the file to read in
in_fmt: The format of in_file, if you want to be explicit
Returns:
numpy.ndarray
"""
fmt = in_file.split('.')[-1]
if in_fmt:
fmt = in_fmt
f... |
Converts in_file to out_file guessing datatype in the absence of in_fmt and out_fmt. | def convert(in_file, out_file, in_fmt="", out_fmt=""):
"""
Converts in_file to out_file, guessing datatype in the absence of
in_fmt and out_fmt.
Arguments:
in_file: The name of the (existing) datafile to read
out_file: The name of the file to create with converted data
in_f... |
Builds a graph using the graph - services endpoint. | def build_graph(self, project, site, subject, session, scan,
size, email=None, invariants=Invariants.ALL,
fiber_file=DEFAULT_FIBER_FILE, atlas_file=None,
use_threads=False, callback=None):
"""
Builds a graph using the graph-services endpoint.
... |
Compute invariants from an existing GraphML file using the remote grute graph services. | def compute_invariants(self, graph_file, input_format,
invariants=Invariants.ALL, email=None,
use_threads=False, callback=None):
"""
Compute invariants from an existing GraphML file using the remote
grute graph services.
Arguments:
... |
Convert a graph from one GraphFormat to another. | def convert_graph(self, graph_file, input_format, output_formats,
email=None, use_threads=False, callback=None):
"""
Convert a graph from one GraphFormat to another.
Arguments:
graph_file (str): Filename of the file to convert
input_format (str): A ... |
Converts a RAMON object list to a JSON - style dictionary. Useful for going from an array of RAMONs to a dictionary indexed by ID. | def to_dict(ramons, flatten=False):
"""
Converts a RAMON object list to a JSON-style dictionary. Useful for going
from an array of RAMONs to a dictionary, indexed by ID.
Arguments:
ramons (RAMON[]): A list of RAMON objects
flatten (boolean: False): Not implemented
Returns:
... |
Converts RAMON objects into a JSON string which can be directly written out to a. json file. You can pass either a single RAMON or a list. If you pass a single RAMON it will still be exported with the ID as the key. In other words: | def to_json(ramons, flatten=False):
"""
Converts RAMON objects into a JSON string which can be directly written out
to a .json file. You can pass either a single RAMON or a list. If you pass
a single RAMON, it will still be exported with the ID as the key. In other
words:
type(from_json(to_... |
Converts JSON to a python list of RAMON objects. if cutout is provided the cutout attribute of the RAMON object is populated. Otherwise it s left empty. json should be an ID - level dictionary like so: | def from_json(json, cutout=None):
"""
Converts JSON to a python list of RAMON objects. if `cutout` is provided,
the `cutout` attribute of the RAMON object is populated. Otherwise, it's
left empty. `json` should be an ID-level dictionary, like so:
{
16: {
type: "segme... |
Converts an HDF5 file to a RAMON object. Returns an object that is a child - - class of RAMON ( though it s determined at run - time what type is returned ). | def from_hdf5(hdf5, anno_id=None):
"""
Converts an HDF5 file to a RAMON object. Returns an object that is a child-
-class of RAMON (though it's determined at run-time what type is returned).
Accessing multiple IDs from the same file is not supported, because it's
not dramatically faster to access e... |
Exports a RAMON object to an HDF5 file object. | def to_hdf5(ramon, hdf5=None):
"""
Exports a RAMON object to an HDF5 file object.
Arguments:
ramon (RAMON): A subclass of RAMONBase
hdf5 (str): Export filename
Returns:
hdf5.File
Raises:
InvalidRAMONError: if you pass a non-RAMON object
"""
if issubclass(ty... |
Takes str or int returns class type | def RAMON(typ):
"""
Takes str or int, returns class type
"""
if six.PY2:
lookup = [str, unicode]
elif six.PY3:
lookup = [str]
if type(typ) is int:
return _ramon_types[typ]
elif type(typ) in lookup:
return _ramon_typ... |
Return a binary - encoded decompressed 2d image. You should specify a token and channel pair. For image data users should use the channel image. | def get_xy_slice(self, token, channel,
x_start, x_stop,
y_start, y_stop,
z_index,
resolution=0):
"""
Return a binary-encoded, decompressed 2d image. You should
specify a 'token' and 'channel' pair. For image dat... |
Get a RAMONVolume volumetric cutout from the neurodata server. | def get_volume(self, token, channel,
x_start, x_stop,
y_start, y_stop,
z_start, z_stop,
resolution=1,
block_size=DEFAULT_BLOCK_SIZE,
neariso=False):
"""
Get a RAMONVolume volumetric cutout f... |
Get volumetric cutout data from the neurodata server. | def get_cutout(self, token, channel,
x_start, x_stop,
y_start, y_stop,
z_start, z_stop,
t_start=0, t_stop=1,
resolution=1,
block_size=DEFAULT_BLOCK_SIZE,
neariso=False):
"""
... |
Post a cutout to the server. | def post_cutout(self, token, channel,
x_start,
y_start,
z_start,
data,
resolution=0):
"""
Post a cutout to the server.
Arguments:
token (str)
channel (str)
x_s... |
Creates a project with the given parameters. | def create_project(self,
project_name,
dataset_name,
hostname,
is_public,
s3backend=0,
kvserver='localhost',
kvengine='MySQL',
mdengine=... |
Creates a token with the given parameters. Arguments: project_name ( str ): Project name dataset_name ( str ): Dataset name project is based on token_name ( str ): Token name is_public ( int ): 1 is public. 0 is not public Returns: bool: True if project created false if not created. | def create_token(self,
token_name,
project_name,
dataset_name,
is_public):
"""
Creates a token with the given parameters.
Arguments:
project_name (str): Project name
dataset_name (str): Da... |
Get a token with the given parameters. Arguments: project_name ( str ): Project name dataset_name ( str ): Dataset name project is based on token_name ( str ): Token name Returns: dict: Token info | def get_token(self,
token_name,
project_name,
dataset_name):
"""
Get a token with the given parameters.
Arguments:
project_name (str): Project name
dataset_name (str): Dataset name project is based on
token... |
Delete a token with the given parameters. Arguments: project_name ( str ): Project name dataset_name ( str ): Dataset name project is based on token_name ( str ): Token name channel_name ( str ): Channel name project is based on Returns: bool: True if project deleted false if not deleted. | def delete_token(self,
token_name,
project_name,
dataset_name):
"""
Delete a token with the given parameters.
Arguments:
project_name (str): Project name
dataset_name (str): Dataset name project is based on
... |
Creates a dataset. | def create_dataset(self,
name,
x_img_size,
y_img_size,
z_img_size,
x_vox_res,
y_vox_res,
z_vox_res,
x_offset=0,
y... |
Create a new channel on the Remote using channel_data. | def create_channel(self,
channel_name,
project_name,
dataset_name,
channel_type,
dtype,
startwindow,
endwindow,
readonly=0,
... |
Gets info about a channel given its name name of its project and name of its dataset. | def get_channel(self, channel_name, project_name, dataset_name):
"""
Gets info about a channel given its name, name of its project
, and name of its dataset.
Arguments:
channel_name (str): Channel name
project_name (str): Project name
dataset_name (st... |
Deletes a channel given its name name of its project and name of its dataset. | def delete_channel(self, channel_name, project_name, dataset_name):
"""
Deletes a channel given its name, name of its project
, and name of its dataset.
Arguments:
channel_name (str): Channel name
project_name (str): Project name
dataset_name (str): D... |
Arguments: channel_name ( str ): Channel Name is the specific name of a specific series of data. Standard naming convention is to do ImageTypeIterationNumber or NameSubProjectName. datatype ( str ): The data type is the storage method of data in the channel. It can be uint8 uint16 uint32 uint64 or float32. channel_type... | def add_channel(self, channel_name, datatype, channel_type,
data_url, file_format, file_type, exceptions=None,
resolution=None, windowrange=None, readonly=None):
"""
Arguments:
channel_name (str): Channel Name is the specific name of a
... |
Arguments: project_name ( str ): Project name is the specific project within a dataset s name. If there is only one project associated with a dataset then standard convention is to name the project the same as its associated dataset. token_name ( str ): The token name is the default token. If you do not wish to specify... | def add_project(self, project_name, token_name=None, public=None):
"""
Arguments:
project_name (str): Project name is the specific project within
a dataset's name. If there is only one project associated
with a dataset then standard convention is to name the
... |
Add a new dataset to the ingest. | def add_dataset(self, dataset_name, imagesize, voxelres, offset=None,
timerange=None, scalinglevels=None, scaling=None):
"""
Add a new dataset to the ingest.
Arguments:
dataset_name (str): Dataset Name is the overarching name of the
research effor... |
Genarate ND json object. | def nd_json(self, dataset, project, channel_list, metadata):
"""
Genarate ND json object.
"""
nd_dict = {}
nd_dict['dataset'] = self.dataset_dict(*dataset)
nd_dict['project'] = self.project_dict(*project)
nd_dict['metadata'] = metadata
nd_dict['channels'] ... |
Generate the dataset dictionary | def dataset_dict(
self, dataset_name, imagesize, voxelres,
offset, timerange, scalinglevels, scaling):
"""Generate the dataset dictionary"""
dataset_dict = {}
dataset_dict['dataset_name'] = dataset_name
dataset_dict['imagesize'] = imagesize
dataset_dict['voxel... |
Generate the project dictionary. | def channel_dict(self, channel_name, datatype, channel_type, data_url,
file_format, file_type, exceptions, resolution,
windowrange, readonly):
"""
Generate the project dictionary.
"""
channel_dict = {}
channel_dict['channel_name'] = chann... |
Genarate the project dictionary. | def project_dict(self, project_name, token_name, public):
"""
Genarate the project dictionary.
"""
project_dict = {}
project_dict['project_name'] = project_name
if token_name is not None:
if token_name == '':
project_dict['token_name'] = projec... |
Identify the image size using the data location and other parameters | def identify_imagesize(self, image_type, image_path='/tmp/img.'):
"""
Identify the image size using the data location and other parameters
"""
dims = ()
try:
if (image_type.lower() == 'png'):
dims = np.shape(ndpng.load('{}{}'.format(
... |
Verify the path supplied. | def verify_path(self, data, verifytype):
"""
Verify the path supplied.
"""
# Insert try and catch blocks
try:
token_name = data["project"]["token_name"]
except:
token_name = data["project"]["project_name"]
channel_names = list(data["channe... |
Try to post data to the server. | def put_data(self, data):
"""
Try to post data to the server.
"""
URLPath = self.oo.url("autoIngest/")
# URLPath = 'https://{}/ca/autoIngest/'.format(self.oo.site_host)
try:
response = requests.post(URLPath, data=json.dumps(data),
... |
Arguments: file_name ( str ): The file name of the json file to post ( optional ). If this is left unspecified it is assumed the data is in the AutoIngest object. dev ( bool ): If pushing to a microns dev branch server set this to True if not leave False. verifytype ( enum ): Set http verification type by checking the ... | def post_data(self, file_name=None, legacy=False,
verifytype=VERIFY_BY_SLICE):
"""
Arguments:
file_name (str): The file name of the json file to post (optional).
If this is left unspecified it is assumed the data is in the
AutoIngest object.
... |
Arguments: file_name ( str:/ tmp/ ND. json ): The file name to store the json to | def output_json(self, file_name='/tmp/ND.json'):
"""
Arguments:
file_name(str : '/tmp/ND.json'): The file name to store the json to
Returns:
None
"""
complete_example = (
self.dataset, self.project, self.channels, self.metadata)
data =... |
Find path for given workspace and|or repository. | def find_path(name, config, wsonly=False):
"""Find path for given workspace and|or repository."""
workspace = Workspace(config)
config = config["workspaces"]
path_list = {}
if name.find('/') != -1:
wsonly = False
try:
ws, repo = name.split('/')
except ValueError... |
Get a list of public tokens available on this server. | def get_public_tokens(self):
"""
Get a list of public tokens available on this server.
Arguments:
None
Returns:
str[]: list of public tokens
"""
r = self.remote_utils.get_url(self.url() + "public_tokens/")
return r.json() |
NOTE: VERY SLOW! Get a dictionary relating key: dataset to value: [ tokens ] that rely on that dataset. | def get_public_datasets_and_tokens(self):
"""
NOTE: VERY SLOW!
Get a dictionary relating key:dataset to value:[tokens] that rely
on that dataset.
Arguments:
None
Returns:
dict: relating key:dataset to value:[tokens]
"""
datasets =... |
Return the project info for a given token. | def get_proj_info(self, token):
"""
Return the project info for a given token.
Arguments:
token (str): Token to return information for
Returns:
JSON: representation of proj_info
"""
r = self.remote_utils.get_url(self.url() + "{}/info/".format(tok... |
Return the size of the volume ( 3D ). Convenient for when you want to download the entirety of a dataset. | def get_image_size(self, token, resolution=0):
"""
Return the size of the volume (3D). Convenient for when you want
to download the entirety of a dataset.
Arguments:
token (str): The token for which to find the dataset image bounds
resolution (int : 0): The resol... |
Insert new metadata into the OCP metadata database. | def set_metadata(self, token, data):
"""
Insert new metadata into the OCP metadata database.
Arguments:
token (str): Token of the datum to set
data (str): A dictionary to insert as metadata. Include `secret`.
Returns:
json: Info of the inserted ID (c... |
Adds a new subvolume to a token/ channel. | def add_subvolume(self, token, channel, secret,
x_start, x_stop,
y_start, y_stop,
z_start, z_stop,
resolution, title, notes):
"""
Adds a new subvolume to a token/channel.
Arguments:
token (str): ... |
Get a response object for a given url. | def get_url(self, url):
"""
Get a response object for a given url.
Arguments:
url (str): The url make a get to
token (str): The authentication token
Returns:
obj: The response object
"""
try:
req = requests.get(url, header... |
Returns a post resquest object taking in a url user token and possible json information. | def post_url(self, url, token='', json=None, data=None, headers=None):
"""
Returns a post resquest object taking in a url, user token, and
possible json information.
Arguments:
url (str): The url to make post to
token (str): The authentication token
j... |
Returns a delete resquest object taking in a url and user token. | def delete_url(self, url, token=''):
"""
Returns a delete resquest object taking in a url and user token.
Arguments:
url (str): The url to make post to
token (str): The authentication token
Returns:
obj: Delete request object
"""
if (... |
Ping the server to make sure that you can access the base URL. | def ping(self, url, endpoint=''):
"""
Ping the server to make sure that you can access the base URL.
Arguments:
None
Returns:
`boolean` Successful access of server (or status code)
"""
r = self.get_url(url + "/" + endpoint)
return r.status... |
Import a HDF5 file into a numpy array. | def load(hdf5_filename):
"""
Import a HDF5 file into a numpy array.
Arguments:
hdf5_filename: A string filename of a HDF5 datafile
Returns:
A numpy array with data from the HDF5 file
"""
# Expand filename to be absolute
hdf5_filename = os.path.expanduser(hdf5_filename)
... |
Export a numpy array to a HDF5 file. | def save(hdf5_filename, array):
"""
Export a numpy array to a HDF5 file.
Arguments:
hdf5_filename (str): A filename to which to save the HDF5 data
array (numpy.ndarray): The numpy array to save to HDF5
Returns:
String. The expanded filename that now holds the HDF5 data
"""
... |
return values of execute are set as result of the task returned by ensure_future () obtainable via task. result () | def run(self, job: Job) -> Future[Result]:
''' return values of execute are set as result of the task
returned by ensure_future(), obtainable via task.result()
'''
if not self.watcher_ready:
self.log.error(f'child watcher unattached when executing {job}')
job.canc... |
Adds a character matrix to DendroPy tree and infers gaps using Fitch s algorithm. | def infer_gaps_in_tree(df_seq, tree, id_col='id', sequence_col='sequence'):
"""Adds a character matrix to DendroPy tree and infers gaps using
Fitch's algorithm.
Infer gaps in sequences at ancestral nodes.
"""
taxa = tree.taxon_namespace
# Get alignment as fasta
alignment = df_seq.phylo.to_... |
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