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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
test | save | 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
Returns:
str. The expanded filename ... | ndio/convert/png.py | 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
... | 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",
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"numpy",
"array",
"to",
"a",
"png",
"file",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/png.py#L31-L66 | [
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test | save_collection | 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 to a collection of files named
"my-image-0.png", "my... | ndio/convert/png.py | 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... | 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... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/png.py#L69-L105 | [
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test | load_collection | 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`.
... | ndio/convert/png.py | 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... | 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... | [
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"if"... | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/png.py#L108-L131 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | Status.print_workspace | Print workspace status. | yoda/subcommand/status.py | 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, ... | 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",
"workspace",
"status",
"."
] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/subcommand/status.py#L56-L65 | [
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test | Status.print_status | Print repository status. | yoda/subcommand/status.py | 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... | 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... | [
"Print",
"repository",
"status",
"."
] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/subcommand/status.py#L67-L78 | [
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"%",
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"repo_name",
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")",
",... | 109f0e9441130488b0155f05883ef6531cf46ee9 |
test | data.get_block_size | 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 the minimum available.
Returns:
int[3]: The xyz blo... | ndio/remote/data.py | 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... | 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... | [
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"for",
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"given",
"token",
"at",
"a",
"given",
"resolution",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/data.py#L87-L102 | [
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test | data.get_xy_slice | Return a binary-encoded, decompressed 2d image. You should
specify a 'token' and 'channel' pair. For image data, users
should use the channel 'image.'
Arguments:
token (str): Token to identify data to download
channel (str): Channel
resolution (int): Resolut... | ndio/remote/data.py | 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... | 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... | [
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"users",
"should",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/data.py#L125-L151 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | data.get_volume | Get a RAMONVolume volumetric cutout from the neurodata server.
Arguments:
token (str): Token to identify data to download
channel (str): Channel
resolution (int): Resolution level
Q_start (int): The lower bound of dimension 'Q'
Q_stop (int): The upper... | ndio/remote/data.py | 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... | 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... | [
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"cutout",
"from",
"the",
"neurodata",
"server",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/data.py#L167-L201 | [
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test | data.get_cutout | Get volumetric cutout data from the neurodata server.
Arguments:
token (str): Token to identify data to download
channel (str): Channel
resolution (int): Resolution level
Q_start (int): The lower bound of dimension 'Q'
Q_stop (int): The upper bound of... | ndio/remote/data.py | 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):
"""
... | 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):
"""
... | [
"Get",
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"data",
"from",
"the",
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"server",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/data.py#L203-L294 | [
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test | data.post_cutout | Post a cutout to the server.
Arguments:
token (str)
channel (str)
x_start (int)
y_start (int)
z_start (int)
data (numpy.ndarray): A numpy array of data. Pass in (x, y, z)
resolution (int : 0): Resolution at which to insert the ... | ndio/remote/data.py | 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... | 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... | [
"Post",
"a",
"cutout",
"to",
"the",
"server",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/data.py#L356-L399 | [
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"]... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | data._post_cutout_no_chunking_blosc | Accepts data in zyx. !!! | ndio/remote/data.py | 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... | 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... | [
"Accepts",
"data",
"in",
"zyx",
".",
"!!!"
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/data.py#L447-L470 | [
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test | load | 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 | ndio/convert/tiff.py | 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)
... | 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)
... | [
"Import",
"a",
"TIFF",
"file",
"into",
"a",
"numpy",
"array",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/tiff.py#L8-L28 | [
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test | save | 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 | ndio/convert/tiff.py | 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... | 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... | [
"Export",
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"array",
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"file",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/tiff.py#L31-L56 | [
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test | load_tiff_multipage | 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 input tiff file in xyz order | ndio/convert/tiff.py | 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... | 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... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/tiff.py#L98-L133 | [
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test | Config.write | Write config in configuration file.
Data must me a dict. | yoda/config.py | 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() | 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() | [
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"file",
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"Data",
"must",
"me",
"a",
"dict",
"."
] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/config.py#L50-L57 | [
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"file... | 109f0e9441130488b0155f05883ef6531cf46ee9 |
test | Bzr.clone | Clone repository from url. | yoda/adapter/bzr.py | def clone(self, url):
"""Clone repository from url."""
return self.execute("%s branch %s %s" % (self.executable,
url, self.path)) | def clone(self, url):
"""Clone repository from url."""
return self.execute("%s branch %s %s" % (self.executable,
url, self.path)) | [
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] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/adapter/bzr.py#L31-L34 | [
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] | 109f0e9441130488b0155f05883ef6531cf46ee9 |
test | get_version | Get version from package resources. | yoda/version.py | def get_version():
"""Get version from package resources."""
requirement = pkg_resources.Requirement.parse("yoda")
provider = pkg_resources.get_provider(requirement)
return provider.version | def get_version():
"""Get version from package resources."""
requirement = pkg_resources.Requirement.parse("yoda")
provider = pkg_resources.get_provider(requirement)
return provider.version | [
"Get",
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] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/version.py#L20-L24 | [
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] | 109f0e9441130488b0155f05883ef6531cf46ee9 |
test | mix_and_match | Mixing and matching positional args and keyword options. | examples/complex_example.py | 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 | 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 | [
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"positional",
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] | jmohr/compago | python | https://github.com/jmohr/compago/blob/8cd6a2894f7b69844b1e4f367344f51a8ef07baf/examples/complex_example.py#L33-L39 | [
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test | option_decorator | Same as mix_and_match, but using the @option decorator. | examples/complex_example.py | 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.'... | 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.'... | [
"Same",
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] | jmohr/compago | python | https://github.com/jmohr/compago/blob/8cd6a2894f7b69844b1e4f367344f51a8ef07baf/examples/complex_example.py#L43-L51 | [
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... | 8cd6a2894f7b69844b1e4f367344f51a8ef07baf |
test | load | 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 file | ndio/convert/nifti.py | 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... | 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... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/nifti.py#L8-L31 | [
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test | save | 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 numpy array to save to nifti
Returns:
S... | ndio/convert/nifti.py | 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... | 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... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/nifti.py#L34-L55 | [
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test | neuroRemote.ping | 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 | ndio/remote/neuroRemote.py | 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... | 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... | [
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"-",
"tokens",
"lookup",
"page",
")",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neuroRemote.py#L120-L131 | [
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test | neuroRemote.url | 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 | ndio/remote/neuroRemote.py | 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,
... | 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,
... | [
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"URL",
"appending",
"an",
"optional",
"suffix",
"(",
"uri",
"path",
")",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neuroRemote.py#L133-L144 | [
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] | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | neuroRemote.reserve_ids | 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 | ndio/remote/neuroRemote.py | 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... | 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... | [
"Requests",
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"of",
"next",
"-",
"available",
"-",
"IDs",
"from",
"the",
"server",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neuroRemote.py#L182-L198 | [
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test | neuroRemote.merge_ids | 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
delete (bool : False): Whether to delete after merging.
Returns:
... | ndio/remote/neuroRemote.py | 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
... | 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
... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neuroRemote.py#L201-L221 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | neuroRemote.create_channels | 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 dataset to download from
new_channels_data (dict): New channel data to u... | ndio/remote/neuroRemote.py | 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... | 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... | [
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"name",
"and",
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"project",
")",
"name",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neuroRemote.py#L224-L264 | [
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test | neuroRemote.propagate | 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 | ndio/remote/neuroRemote.py | 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_... | 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_... | [
"Kick",
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"propagate",
"function",
"on",
"the",
"remote",
"server",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neuroRemote.py#L269-L286 | [
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test | neuroRemote.get_propagate_status | 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 | ndio/remote/neuroRemote.py | 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... | 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... | [
"Get",
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"/",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neuroRemote.py#L289-L304 | [
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test | resources.create_project | Creates a project with the given parameters.
Arguments:
project_name (str): Project name
dataset_name (str): Dataset name project is based on
hostname (str): Hostname
s3backend (str): S3 region to save the data in
is_public (int): 1 is public. 0 is no... | ndio/remote/resources.py | def create_project(self,
project_name,
dataset_name,
hostname,
is_public,
s3backend=0,
kvserver='localhost',
kvengine='MySQL',
mdengine=... | def create_project(self,
project_name,
dataset_name,
hostname,
is_public,
s3backend=0,
kvserver='localhost',
kvengine='MySQL',
mdengine=... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L70-L119 | [
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test | resources.list_projects | 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 | ndio/remote/resources.py | 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/... | 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/... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L164-L182 | [
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"... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.create_token | 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 projec... | ndio/remote/resources.py | 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... | 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... | [
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"Dataset",
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"'/project/... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.get_token | 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 | ndio/remote/resources.py | 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... | 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... | [
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... | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L217-L238 | [
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")",
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"forma... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.delete_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 ... | ndio/remote/resources.py | 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
... | 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
... | [
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"str",... | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L240-L264 | [
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"fo... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.list_tokens | Lists a set of tokens that are public in Neurodata.
Arguments:
Returns:
dict: Public tokens found in Neurodata | ndio/remote/resources.py | 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... | 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... | [
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":",
"Returns",
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"dict",
":",
"Public",
"tokens",
"found",
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"Neurodata"
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L266-L279 | [
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"200",
... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.create_dataset | Creates a dataset.
Arguments:
name (str): Name of dataset
x_img_size (int): max x coordinate of image size
y_img_size (int): max y coordinate of image size
z_img_size (int): max z coordinate of image size
x_vox_res (float): x voxel resolution
... | ndio/remote/resources.py | 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... | 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... | [
"Creates",
"a",
"dataset",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L281-L343 | [
"def",
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",",
"z_offset",
"=",
"0",
",",
"scali... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.get_dataset | Returns info regarding a particular dataset.
Arugments:
name (str): Dataset name
Returns:
dict: Dataset information | ndio/remote/resources.py | 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... | 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... | [
"Returns",
"info",
"regarding",
"a",
"particular",
"dataset",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L345-L361 | [
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".",
"get_url",
"(",
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")",
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"req... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.list_datasets | 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 datasets in
cloud. False i... | ndio/remote/resources.py | 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 ... | 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 ... | [
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"will",
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"public",
"datasets",
"in",
"cloud",
".",
"False",
"will",
"get",
"user",
"s",
"public",
"datasets",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L363-L387 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.delete_dataset | Arguments:
name (str): Name of dataset to delete
Returns:
bool: True if dataset deleted, False if not | ndio/remote/resources.py | 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... | 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... | [
"Arguments",
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"str",
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":",
"Name",
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"to",
"delete"
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L389-L405 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.create_channel | Create a new channel on the Remote, using channel_data.
Arguments:
channel_name (str): Channel name
project_name (str): Project name
dataset_name (str): Dataset name
channel_type (str): Type of the channel (e.g. `neurodata.IMAGE`)
dtype (str): The dat... | ndio/remote/resources.py | def create_channel(self,
channel_name,
project_name,
dataset_name,
channel_type,
dtype,
startwindow,
endwindow,
readonly=0,
... | def create_channel(self,
channel_name,
project_name,
dataset_name,
channel_type,
dtype,
startwindow,
endwindow,
readonly=0,
... | [
"Create",
"a",
"new",
"channel",
"on",
"the",
"Remote",
"using",
"channel_data",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L415-L487 | [
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"=",
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",",
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"=",
"0",
... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | resources.get_channel | 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 (str): Dataset name
Returns:
dict: Channel info | ndio/remote/resources.py | 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... | 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... | [
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"about",
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"name",
"name",
"of",
"its",
"project",
"and",
"name",
"of",
"its",
"dataset",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/resources.py#L489-L511 | [
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".",
"f... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | Show.parse | Parse show subcommand. | yoda/subcommand/show.py | 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... | 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... | [
"Parse",
"show",
"subcommand",
"."
] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/subcommand/show.py#L40-L49 | [
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"add_m... | 109f0e9441130488b0155f05883ef6531cf46ee9 |
test | Show.execute | Execute show subcommand. | yoda/subcommand/show.py | 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() | 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() | [
"Execute",
"show",
"subcommand",
"."
] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/subcommand/show.py#L51-L56 | [
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":",... | 109f0e9441130488b0155f05883ef6531cf46ee9 |
test | Show.show_workspace | Show specific workspace. | yoda/subcommand/show.py | 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... | 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",
"specific",
"workspace",
"."
] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/subcommand/show.py#L58-L91 | [
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"color",
"=",
"Color",
"(",
")",
... | 109f0e9441130488b0155f05883ef6531cf46ee9 |
test | Show.show_all | Show details for all workspaces. | yoda/subcommand/show.py | def show_all(self):
"""Show details for all workspaces."""
for ws in self.workspace.list().keys():
self.show_workspace(ws)
print("\n\n") | def show_all(self):
"""Show details for all workspaces."""
for ws in self.workspace.list().keys():
self.show_workspace(ws)
print("\n\n") | [
"Show",
"details",
"for",
"all",
"workspaces",
"."
] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/subcommand/show.py#L93-L97 | [
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"\"\\n\\n\"",
")"
] | 109f0e9441130488b0155f05883ef6531cf46ee9 |
test | Remote.url | Get the base URL of the Remote.
Arguments:
None
Returns:
`str` base URL | ndio/remote/Remote.py | 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 | 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 | [
"Get",
"the",
"base",
"URL",
"of",
"the",
"Remote",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/Remote.py#L21-L32 | [
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"hostna... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | Remote.ping | Ping the server to make sure that you can access the base URL.
Arguments:
None
Returns:
`boolean` Successful access of server (or status code) | ndio/remote/Remote.py | 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... | 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... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/Remote.py#L34-L44 | [
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] | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | export_dae | 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:
boolean success | ndio/utils/mesh.py | 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:
... | 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:
... | [
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"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/utils/mesh.py#L5-L21 | [
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"... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | export_obj | 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:
boolean success | ndio/utils/mesh.py | 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:
... | 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:
... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/utils/mesh.py#L24-L40 | [
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"... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | export_ply | 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:
boolean success | ndio/utils/mesh.py | 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:
... | 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:
... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/utils/mesh.py#L43-L77 | [
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"... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | _guess_format_from_extension | 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 | ndio/convert/convert.py | 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
"""
... | 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
"""
... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/convert.py#L44-L71 | [
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"# - If it appears once, we can simply return that forma... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | open | 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 | ndio/convert/convert.py | 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... | 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... | [
"Reads",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/convert.py#L74-L93 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | convert | 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_fmt: Optional. The format of incoming data, if not guessable
... | ndio/convert/convert.py | 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... | 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... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/convert.py#L96-L161 | [
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"out_file... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | grute.build_graph | Builds a graph using the graph-services endpoint.
Arguments:
project (str): The project to use
site (str): The site in question
subject (str): The subject's identifier
session (str): The session (per subject)
scan (str): The scan identifier
... | ndio/remote/grute.py | 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.
... | 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.
... | [
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"-",
"services",
"endpoint",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/grute.py#L151-L231 | [
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test | grute.compute_invariants | Compute invariants from an existing GraphML file using the remote
grute graph services.
Arguments:
graph_file (str): The filename of the graphml file
input_format (str): One of grute.GraphFormats
invariants (str[]: Invariants.ALL)*: An array of grute.Invariants
... | ndio/remote/grute.py | 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:
... | 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:
... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/grute.py#L262-L329 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | grute.convert_graph | Convert a graph from one GraphFormat to another.
Arguments:
graph_file (str): Filename of the file to convert
input_format (str): A grute.GraphFormats
output_formats (str[]): A grute.GraphFormats
email (str: self.email)*: The email to notify
use_threa... | ndio/remote/grute.py | 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 ... | 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 ... | [
"Convert",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/grute.py#L356-L417 | [
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"email",
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"email",
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"self... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | to_dict | 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:
dict: A python dictionary of RAMON objects. | ndio/ramon/__init__.py | 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:
... | 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:
... | [
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"[",... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | to_json | 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_json(ramon))) # ALWAYS returns a list
...ev... | ndio/ramon/__init__.py | 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_... | 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_... | [
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"out_ramons",
"[",... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | from_json | 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: "segment",
metadata: {
... | ndio/ramon/__init__.py | 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... | 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... | [
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... | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/ramon/__init__.py#L226-L286 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | from_hdf5 | 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 each item in the hdf5 file at the same
time ... | ndio/ramon/__init__.py | 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... | 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... | [
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test | to_hdf5 | 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 | ndio/ramon/__init__.py | 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... | 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... | [
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"RAMON",
"object",
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"an",
"HDF5",
"file",
"object",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/ramon/__init__.py#L381-L484 | [
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test | AnnotationType.RAMON | Takes str or int, returns class type | ndio/ramon/__init__.py | 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... | 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... | [
"Takes",
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"returns",
"class",
"type"
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/ramon/__init__.py#L137-L149 | [
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"_r... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | neurodata.get_xy_slice | Return a binary-encoded, decompressed 2d image. You should
specify a 'token' and 'channel' pair. For image data, users
should use the channel 'image.'
Arguments:
token (str): Token to identify data to download
channel (str): Channel
resolution (int): Resolut... | ndio/remote/neurodata.py | 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... | 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... | [
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"pair",
".",
"For",
"image",
"data",
"users",
"should",
"use",
"the",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L122-L147 | [
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","... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | neurodata.get_volume | Get a RAMONVolume volumetric cutout from the neurodata server.
Arguments:
token (str): Token to identify data to download
channel (str): Channel
resolution (int): Resolution level
Q_start (int): The lower bound of dimension 'Q'
Q_stop (int): The upper... | ndio/remote/neurodata.py | 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... | 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",
"a",
"RAMONVolume",
"volumetric",
"cutout",
"from",
"the",
"neurodata",
"server",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L162-L189 | [
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test | neurodata.get_cutout | Get volumetric cutout data from the neurodata server.
Arguments:
token (str): Token to identify data to download
channel (str): Channel
resolution (int): Resolution level
Q_start (int): The lower bound of dimension 'Q'
Q_stop (int): The upper bound of... | ndio/remote/neurodata.py | 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):
"""
... | 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):
"""
... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L191-L225 | [
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"block_s... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | neurodata.post_cutout | Post a cutout to the server.
Arguments:
token (str)
channel (str)
x_start (int)
y_start (int)
z_start (int)
data (numpy.ndarray): A numpy array of data. Pass in (x, y, z)
resolution (int : 0): Resolution at which to insert the ... | ndio/remote/neurodata.py | 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... | 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... | [
"Post",
"a",
"cutout",
"to",
"the",
"server",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L230-L259 | [
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test | neurodata.create_project | Creates a project with the given parameters.
Arguments:
project_name (str): Project name
dataset_name (str): Dataset name project is based on
hostname (str): Hostname
s3backend (str): S3 region to save the data in
is_public (int): 1 is public. 0 is no... | ndio/remote/neurodata.py | def create_project(self,
project_name,
dataset_name,
hostname,
is_public,
s3backend=0,
kvserver='localhost',
kvengine='MySQL',
mdengine=... | def create_project(self,
project_name,
dataset_name,
hostname,
is_public,
s3backend=0,
kvserver='localhost',
kvengine='MySQL',
mdengine=... | [
"Creates",
"a",
"project",
"with",
"the",
"given",
"parameters",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L406-L441 | [
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test | neurodata.create_token | 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 projec... | ndio/remote/neurodata.py | 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... | 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... | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | neurodata.get_token | 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 | ndio/remote/neurodata.py | 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... | 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... | [
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... | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L490-L505 | [
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",",
"project_name",
",",
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")"
] | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | neurodata.delete_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 ... | ndio/remote/neurodata.py | 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
... | 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
... | [
"Delete",
"a",
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"with",
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"project_name",
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"(",
"str",
")",
":",
"Dataset",
"name",
"project",
"is",
"based",
"on",
"token_name",
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"str",... | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L507-L523 | [
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test | neurodata.create_dataset | Creates a dataset.
Arguments:
name (str): Name of dataset
x_img_size (int): max x coordinate of image size
y_img_size (int): max y coordinate of image size
z_img_size (int): max z coordinate of image size
x_vox_res (float): x voxel resolution
... | ndio/remote/neurodata.py | 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... | 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... | [
"Creates",
"a",
"dataset",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L549-L600 | [
"def",
"create_dataset",
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"scali... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | neurodata.create_channel | Create a new channel on the Remote, using channel_data.
Arguments:
channel_name (str): Channel name
project_name (str): Project name
dataset_name (str): Dataset name
channel_type (str): Type of the channel (e.g. `neurodata.IMAGE`)
dtype (str): The dat... | ndio/remote/neurodata.py | def create_channel(self,
channel_name,
project_name,
dataset_name,
channel_type,
dtype,
startwindow,
endwindow,
readonly=0,
... | def create_channel(self,
channel_name,
project_name,
dataset_name,
channel_type,
dtype,
startwindow,
endwindow,
readonly=0,
... | [
"Create",
"a",
"new",
"channel",
"on",
"the",
"Remote",
"using",
"channel_data",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L644-L694 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | neurodata.get_channel | 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 (str): Dataset name
Returns:
dict: Channel info | ndio/remote/neurodata.py | 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... | 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... | [
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"name",
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"of",
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"project",
"and",
"name",
"of",
"its",
"dataset",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/neurodata.py#L696-L710 | [
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test | neurodata.delete_channel | 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): Dataset name
Returns:
bool: True if channel deleted, False if not | ndio/remote/neurodata.py | 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... | 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... | [
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test | NDIngest.add_channel | 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 ch... | ndio/remote/ndingest.py | 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
... | 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
... | [
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test | NDIngest.add_project | 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)... | ndio/remote/ndingest.py | 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
... | 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
... | [
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test | NDIngest.add_dataset | Add a new dataset to the ingest.
Arguments:
dataset_name (str): Dataset Name is the overarching name of the
research effort. Standard naming convention is to do
LabNamePublicationYear or LeadResearcherCurrentYear.
imagesize (int, int, int): Image size is ... | ndio/remote/ndingest.py | 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... | 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... | [
"Add",
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"new",
"dataset",
"to",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/ndingest.py#L136-L180 | [
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test | NDIngest.nd_json | Genarate ND json object. | ndio/remote/ndingest.py | 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'] ... | 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'] ... | [
"Genarate",
"ND",
"json",
"object",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/ndingest.py#L192-L204 | [
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test | NDIngest.dataset_dict | Generate the dataset dictionary | ndio/remote/ndingest.py | 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... | 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",
"dataset",
"dictionary"
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/ndingest.py#L220-L236 | [
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test | NDIngest.channel_dict | Generate the project dictionary. | ndio/remote/ndingest.py | 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... | 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... | [
"Generate",
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"project",
"dictionary",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/ndingest.py#L238-L259 | [
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test | NDIngest.project_dict | Genarate the project dictionary. | ndio/remote/ndingest.py | 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... | 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... | [
"Genarate",
"the",
"project",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/ndingest.py#L261-L277 | [
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test | NDIngest.identify_imagesize | Identify the image size using the data location and other parameters | ndio/remote/ndingest.py | 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(
... | 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(
... | [
"Identify",
"the",
"image",
"size",
"using",
"the",
"data",
"location",
"and",
"other",
"parameters"
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/ndingest.py#L279-L300 | [
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"shape"... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | NDIngest.verify_path | Verify the path supplied. | ndio/remote/ndingest.py | 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... | 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... | [
"Verify",
"the",
"path",
"supplied",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/ndingest.py#L302-L409 | [
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test | NDIngest.put_data | Try to post data to the server. | ndio/remote/ndingest.py | 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),
... | 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),
... | [
"Try",
"to",
"post",
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"to",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/ndingest.py#L452-L465 | [
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"UR... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | NDIngest.post_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 Fals... | ndio/remote/ndingest.py | 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.
... | 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.
... | [
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test | NDIngest.output_json | Arguments:
file_name(str : '/tmp/ND.json'): The file name to store the json to
Returns:
None | ndio/remote/ndingest.py | 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 =... | 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 =... | [
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test | find_path | Find path for given workspace and|or repository. | yoda/__init__.py | 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... | 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... | [
"Find",
"path",
"for",
"given",
"workspace",
"and|or",
"repository",
"."
] | Numergy/yoda | python | https://github.com/Numergy/yoda/blob/109f0e9441130488b0155f05883ef6531cf46ee9/yoda/__init__.py#L17-L49 | [
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test | metadata.get_public_tokens | Get a list of public tokens available on this server.
Arguments:
None
Returns:
str[]: list of public tokens | ndio/remote/metadata.py | 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() | 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() | [
"Get",
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"available",
"on",
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"server",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/metadata.py#L44-L55 | [
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test | metadata.get_public_datasets_and_tokens | 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] | ndio/remote/metadata.py | 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 =... | 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 =... | [
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/metadata.py#L70-L90 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | metadata.get_proj_info | Return the project info for a given token.
Arguments:
token (str): Token to return information for
Returns:
JSON: representation of proj_info | ndio/remote/metadata.py | 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... | 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",
"project",
"info",
"for",
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"given",
"token",
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] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/metadata.py#L104-L115 | [
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... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | metadata.get_image_size | 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 resolution at which to get image bounds.
Defaults to 0, ... | ndio/remote/metadata.py | 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... | 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... | [
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"you",
"want",
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"download",
"the",
"entirety",
"of",
"a",
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"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/metadata.py#L136-L158 | [
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"not",
"in",
"info",
"[",
"'dataset'",
"]... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | metadata.set_metadata | 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 (convenience) or an error message.
Throws:
... | ndio/remote/metadata.py | 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... | 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... | [
"Insert",
"new",
"metadata",
"into",
"the",
"OCP",
"metadata",
"database",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/metadata.py#L160-L182 | [
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")",
"... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | metadata.add_subvolume | Adds a new subvolume to a token/channel.
Arguments:
token (str): The token to write to in LIMS
channel (str): Channel to add in the subvolume. Can be `None`
x_start (int): Start in x dimension
x_stop (int): Stop in x dimension
y_start (int): Start in ... | ndio/remote/metadata.py | 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): ... | 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): ... | [
"Adds",
"a",
"new",
"subvolume",
"to",
"a",
"token",
"/",
"channel",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/metadata.py#L200-L247 | [
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")",
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"self",
... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | remote_utils.get_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 | ndio/remote/remote_utils.py | 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... | 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... | [
"Get",
"a",
"response",
"object",
"for",
"a",
"given",
"url",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/remote_utils.py#L19-L42 | [
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"_user_token",
")",
"}",
",",
"verify",
... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | remote_utils.post_url | 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
json (dict): json info to send
Returns:
obj: Post request object | ndio/remote/remote_utils.py | 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... | 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... | [
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"resquest",
"object",
"taking",
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"a",
"url",
"user",
"token",
"and",
"possible",
"json",
"information",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/remote_utils.py#L44-L78 | [
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"_user_token",
... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | remote_utils.delete_url | 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 | ndio/remote/remote_utils.py | 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 (... | 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 (... | [
"Returns",
"a",
"delete",
"resquest",
"object",
"taking",
"in",
"a",
"url",
"and",
"user",
"token",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/remote_utils.py#L80-L97 | [
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"=",
"{",
"'Author... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | remote_utils.ping | Ping the server to make sure that you can access the base URL.
Arguments:
None
Returns:
`boolean` Successful access of server (or status code) | ndio/remote/remote_utils.py | 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... | 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... | [
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"server",
"to",
"make",
"sure",
"that",
"you",
"can",
"access",
"the",
"base",
"URL",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/remote/remote_utils.py#L99-L109 | [
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"+",
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"+",
"endpoint",
")",
"return",
"r",
".",
"status_code"
] | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | load | 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 | ndio/convert/hdf5.py | 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)
... | 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)
... | [
"Import",
"a",
"HDF5",
"file",
"into",
"a",
"numpy",
"array",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/hdf5.py#L7-L29 | [
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"# n... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | save | 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 | ndio/convert/hdf5.py | 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
"""
... | 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
"""
... | [
"Export",
"a",
"numpy",
"array",
"to",
"a",
"HDF5",
"file",
"."
] | neurodata/ndio | python | https://github.com/neurodata/ndio/blob/792dd5816bc770b05a3db2f4327da42ff6253531/ndio/convert/hdf5.py#L32-L53 | [
"def",
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"\"w... | 792dd5816bc770b05a3db2f4327da42ff6253531 |
test | ProcessExecutor.run | return values of execute are set as result of the task
returned by ensure_future(), obtainable via task.result() | ribosome/process.py | 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... | 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... | [
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"returned",
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"ensure_future",
"()",
"obtainable",
"via",
"task",
".",
"result",
"()"
] | tek/ribosome | python | https://github.com/tek/ribosome/blob/b2ce9e118faa46d93506cbbb5f27ecfbd4e8a1cc/ribosome/process.py#L170-L186 | [
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"... | b2ce9e118faa46d93506cbbb5f27ecfbd4e8a1cc |
test | infer_gaps_in_tree | Adds a character matrix to DendroPy tree and infers gaps using
Fitch's algorithm.
Infer gaps in sequences at ancestral nodes. | pyasr/gaps.py | 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_... | 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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] | Zsailer/pyasr | python | https://github.com/Zsailer/pyasr/blob/f9a05912ae2409a4cb2d8bac878bb5230c8824b4/pyasr/gaps.py#L3-L28 | [
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"to_f... | f9a05912ae2409a4cb2d8bac878bb5230c8824b4 |
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