id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 75 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
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47,400 | ternaris/marv | marv/cli.py | marvcli_develop_server | def marvcli_develop_server(port, public):
"""Run development webserver.
ATTENTION: By default it is only served on localhost. To run it
within a container and access it from the outside, you need to
forward the port and tell it to listen on all IPs instead of only
localhost.
"""
from flask_... | python | def marvcli_develop_server(port, public):
"""Run development webserver.
ATTENTION: By default it is only served on localhost. To run it
within a container and access it from the outside, you need to
forward the port and tell it to listen on all IPs instead of only
localhost.
"""
from flask_... | [
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ATTENTION: By default it is only served on localhost. To run it
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47,401 | ternaris/marv | marv/cli.py | marvcli_discard | def marvcli_discard(datasets, all_nodes, nodes, tags, comments, confirm):
"""Mark DATASETS to be discarded or discard associated data.
Without any options the specified datasets are marked to be
discarded via `marv cleanup --discarded`. Use `marv undiscard` to
undo this operation.
Otherwise, selec... | python | def marvcli_discard(datasets, all_nodes, nodes, tags, comments, confirm):
"""Mark DATASETS to be discarded or discard associated data.
Without any options the specified datasets are marked to be
discarded via `marv cleanup --discarded`. Use `marv undiscard` to
undo this operation.
Otherwise, selec... | [
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Without any options the specified datasets are marked to be
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47,402 | ternaris/marv | marv/cli.py | marvcli_undiscard | def marvcli_undiscard(datasets):
"""Undiscard DATASETS previously discarded."""
create_app()
setids = parse_setids(datasets, discarded=True)
dataset = Dataset.__table__
stmt = dataset.update()\
.where(dataset.c.setid.in_(setids))\
.values(discarded=False)
db.... | python | def marvcli_undiscard(datasets):
"""Undiscard DATASETS previously discarded."""
create_app()
setids = parse_setids(datasets, discarded=True)
dataset = Dataset.__table__
stmt = dataset.update()\
.where(dataset.c.setid.in_(setids))\
.values(discarded=False)
db.... | [
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47,403 | ternaris/marv | marv/cli.py | marvcli_restore | def marvcli_restore(file):
"""Restore previously dumped database"""
data = json.load(file)
site = create_app().site
site.restore_database(**data) | python | def marvcli_restore(file):
"""Restore previously dumped database"""
data = json.load(file)
site = create_app().site
site.restore_database(**data) | [
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47,404 | ternaris/marv | marv/cli.py | marvcli_query | def marvcli_query(ctx, list_tags, collections, discarded, outdated, path, tags, null):
"""Query datasets.
Use --collection=* to list all datasets across all collections.
"""
if not any([collections, discarded, list_tags, outdated, path, tags]):
click.echo(ctx.get_help())
ctx.exit(1)
... | python | def marvcli_query(ctx, list_tags, collections, discarded, outdated, path, tags, null):
"""Query datasets.
Use --collection=* to list all datasets across all collections.
"""
if not any([collections, discarded, list_tags, outdated, path, tags]):
click.echo(ctx.get_help())
ctx.exit(1)
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47,405 | ternaris/marv | marv/cli.py | marvcli_tag | def marvcli_tag(ctx, add, remove, datasets):
"""Add or remove tags to datasets"""
if not any([add, remove]) or not datasets:
click.echo(ctx.get_help())
ctx.exit(1)
app = create_app()
setids = parse_setids(datasets)
app.site.tag(setids, add, remove) | python | def marvcli_tag(ctx, add, remove, datasets):
"""Add or remove tags to datasets"""
if not any([add, remove]) or not datasets:
click.echo(ctx.get_help())
ctx.exit(1)
app = create_app()
setids = parse_setids(datasets)
app.site.tag(setids, add, remove) | [
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47,406 | ternaris/marv | marv/cli.py | marvcli_comment_add | def marvcli_comment_add(user, message, datasets):
"""Add comment as user for one or more datasets"""
app = create_app()
try:
db.session.query(User).filter(User.name==user).one()
except NoResultFound:
click.echo("ERROR: No such user '{}'".format(user), err=True)
sys.exit(1)
id... | python | def marvcli_comment_add(user, message, datasets):
"""Add comment as user for one or more datasets"""
app = create_app()
try:
db.session.query(User).filter(User.name==user).one()
except NoResultFound:
click.echo("ERROR: No such user '{}'".format(user), err=True)
sys.exit(1)
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47,407 | ternaris/marv | marv/cli.py | marvcli_comment_list | def marvcli_comment_list(datasets):
"""Lists comments for datasets.
Output: setid comment_id date time author message
"""
app = create_app()
ids = parse_setids(datasets, dbids=True)
comments = db.session.query(Comment)\
.options(db.joinedload(Comment.dataset))\
... | python | def marvcli_comment_list(datasets):
"""Lists comments for datasets.
Output: setid comment_id date time author message
"""
app = create_app()
ids = parse_setids(datasets, dbids=True)
comments = db.session.query(Comment)\
.options(db.joinedload(Comment.dataset))\
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47,408 | ternaris/marv | marv/cli.py | marvcli_comment_rm | def marvcli_comment_rm(ids):
"""Remove comments.
Remove comments by id as given in second column of: marv comment list
"""
app = create_app()
db.session.query(Comment)\
.filter(Comment.id.in_(ids))\
.delete(synchronize_session=False)
db.session.commit() | python | def marvcli_comment_rm(ids):
"""Remove comments.
Remove comments by id as given in second column of: marv comment list
"""
app = create_app()
db.session.query(Comment)\
.filter(Comment.id.in_(ids))\
.delete(synchronize_session=False)
db.session.commit() | [
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47,409 | ternaris/marv | marv/cli.py | marvcli_user_list | def marvcli_user_list():
"""List existing users"""
app = create_app()
for name in db.session.query(User.name).order_by(User.name):
click.echo(name[0]) | python | def marvcli_user_list():
"""List existing users"""
app = create_app()
for name in db.session.query(User.name).order_by(User.name):
click.echo(name[0]) | [
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47,410 | ternaris/marv | marv/cli.py | marvcli_user_rm | def marvcli_user_rm(ctx, username):
"""Remove a user"""
app = create_app()
try:
app.um.user_rm(username)
except ValueError as e:
ctx.fail(e.args[0]) | python | def marvcli_user_rm(ctx, username):
"""Remove a user"""
app = create_app()
try:
app.um.user_rm(username)
except ValueError as e:
ctx.fail(e.args[0]) | [
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47,411 | originell/sorl-watermark | sorl_watermarker/engines/base.py | WatermarkEngineBase.watermark | def watermark(self, image, options):
"""
Wrapper for ``_watermark``
Takes care of all the options handling.
"""
watermark_img = options.get("watermark", settings.THUMBNAIL_WATERMARK)
if not watermark_img:
raise AttributeError("No THUMBNAIL_WATERMARK defined o... | python | def watermark(self, image, options):
"""
Wrapper for ``_watermark``
Takes care of all the options handling.
"""
watermark_img = options.get("watermark", settings.THUMBNAIL_WATERMARK)
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47,412 | ternaris/marv | marv/config.py | make_funcs | def make_funcs(dataset, setdir, store):
"""Functions available for listing columns and filters."""
return {
'cat': lambda *lists: [x for lst in lists for x in lst],
'comments': lambda: None,
'detail_route': detail_route,
'format': lambda fmt, *args: fmt.format(*args),
'ge... | python | def make_funcs(dataset, setdir, store):
"""Functions available for listing columns and filters."""
return {
'cat': lambda *lists: [x for lst in lists for x in lst],
'comments': lambda: None,
'detail_route': detail_route,
'format': lambda fmt, *args: fmt.format(*args),
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47,413 | ternaris/marv | marv/config.py | make_summary_funcs | def make_summary_funcs(rows, ids):
"""Functions available for listing summary fields."""
return {
'len': len,
'list': lambda *x: filter(None, list(x)),
'max': max,
'min': min,
'rows': partial(summary_rows, rows, ids),
'sum': sum,
'trace': print_trace
} | python | def make_summary_funcs(rows, ids):
"""Functions available for listing summary fields."""
return {
'len': len,
'list': lambda *x: filter(None, list(x)),
'max': max,
'min': min,
'rows': partial(summary_rows, rows, ids),
'sum': sum,
'trace': print_trace
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47,414 | ternaris/marv | marv/collection.py | cached_property | def cached_property(func):
"""Create read-only property that caches its function's value"""
@functools.wraps(func)
def cached_func(self):
cacheattr = '_{}'.format(func.func_name)
try:
return getattr(self, cacheattr)
except AttributeError:
value = func(self)
... | python | def cached_property(func):
"""Create read-only property that caches its function's value"""
@functools.wraps(func)
def cached_func(self):
cacheattr = '_{}'.format(func.func_name)
try:
return getattr(self, cacheattr)
except AttributeError:
value = func(self)
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47,415 | ternaris/marv | marv_node/io.py | create_stream | def create_stream(name, **header):
"""Create a stream for publishing messages.
All keyword arguments will be used to form the header.
"""
assert isinstance(name, basestring), name
return CreateStream(parent=None, name=name, group=False, header=header) | python | def create_stream(name, **header):
"""Create a stream for publishing messages.
All keyword arguments will be used to form the header.
"""
assert isinstance(name, basestring), name
return CreateStream(parent=None, name=name, group=False, header=header) | [
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47,416 | ternaris/marv | marv_node/io.py | pull | def pull(handle, enumerate=False):
"""Pulls next message for handle.
Args:
handle: A :class:`.stream.Handle` or GroupHandle.
enumerate (bool): boolean to indicate whether a tuple ``(idx, msg)``
should be returned, not unlike Python's enumerate().
Returns:
A :class:`Pull... | python | def pull(handle, enumerate=False):
"""Pulls next message for handle.
Args:
handle: A :class:`.stream.Handle` or GroupHandle.
enumerate (bool): boolean to indicate whether a tuple ``(idx, msg)``
should be returned, not unlike Python's enumerate().
Returns:
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47,417 | originell/sorl-watermark | sorl_watermarker/parsers.py | parse_geometry | def parse_geometry(geometry, ratio=None):
"""
Enhanced parse_geometry parser with percentage support.
"""
if "%" not in geometry:
# fall back to old parser
return xy_geometry_parser(geometry, ratio)
# parse with float so geometry strings like "42.11%" are possible
return float(ge... | python | def parse_geometry(geometry, ratio=None):
"""
Enhanced parse_geometry parser with percentage support.
"""
if "%" not in geometry:
# fall back to old parser
return xy_geometry_parser(geometry, ratio)
# parse with float so geometry strings like "42.11%" are possible
return float(ge... | [
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47,418 | ternaris/marv | docs/tutorial/code/marv_tutorial/__init__.py | image | def image(cam):
"""Extract first image of input stream to jpg file.
Args:
cam: Input stream of raw rosbag messages.
Returns:
File instance for first image of input stream.
"""
# Set output stream title and pull first message
yield marv.set_header(title=cam.topic)
msg = yiel... | python | def image(cam):
"""Extract first image of input stream to jpg file.
Args:
cam: Input stream of raw rosbag messages.
Returns:
File instance for first image of input stream.
"""
# Set output stream title and pull first message
yield marv.set_header(title=cam.topic)
msg = yiel... | [
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47,419 | ternaris/marv | docs/tutorial/code/marv_tutorial/__init__.py | image_section | def image_section(image, title):
"""Create detail section with one image.
Args:
title (str): Title to be displayed for detail section.
image: marv image file.
Returns
One detail section.
"""
# pull first image
img = yield marv.pull(image)
if img is None:
ret... | python | def image_section(image, title):
"""Create detail section with one image.
Args:
title (str): Title to be displayed for detail section.
image: marv image file.
Returns
One detail section.
"""
# pull first image
img = yield marv.pull(image)
if img is None:
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47,420 | ternaris/marv | docs/tutorial/code/marv_tutorial/__init__.py | images | def images(cam):
"""Extract images from input stream to jpg files.
Args:
cam: Input stream of raw rosbag messages.
Returns:
File instances for images of input stream.
"""
# Set output stream title and pull first message
yield marv.set_header(title=cam.topic)
# Fetch and pr... | python | def images(cam):
"""Extract images from input stream to jpg files.
Args:
cam: Input stream of raw rosbag messages.
Returns:
File instances for images of input stream.
"""
# Set output stream title and pull first message
yield marv.set_header(title=cam.topic)
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47,421 | ternaris/marv | docs/tutorial/code/marv_tutorial/__init__.py | gallery_section | def gallery_section(images, title):
"""Create detail section with gallery.
Args:
title (str): Title to be displayed for detail section.
images: stream of marv image files
Returns
One detail section.
"""
# pull all images
imgs = []
while True:
img = yield mar... | python | def gallery_section(images, title):
"""Create detail section with gallery.
Args:
title (str): Title to be displayed for detail section.
images: stream of marv image files
Returns
One detail section.
"""
# pull all images
imgs = []
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47,422 | ternaris/marv | docs/tutorial/code/marv_tutorial/__init__.py | filesizes | def filesizes(images):
"""Stat filesize of files.
Args:
images: stream of marv image files
Returns:
Stream of filesizes
"""
# Pull each image and push its filesize
while True:
img = yield marv.pull(images)
if img is None:
break
yield marv.pus... | python | def filesizes(images):
"""Stat filesize of files.
Args:
images: stream of marv image files
Returns:
Stream of filesizes
"""
# Pull each image and push its filesize
while True:
img = yield marv.pull(images)
if img is None:
break
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47,423 | kolypto/py-good | good/helpers.py | name | def name(name, validator=None):
""" Set a name on a validator callable.
Useful for user-friendly reporting when using lambdas to populate the [`Invalid.expected`](#invalid) field:
```python
from good import Schema, name
Schema(lambda x: int(x))('a')
#-> Invalid: invalid literal for int(): exp... | python | def name(name, validator=None):
""" Set a name on a validator callable.
Useful for user-friendly reporting when using lambdas to populate the [`Invalid.expected`](#invalid) field:
```python
from good import Schema, name
Schema(lambda x: int(x))('a')
#-> Invalid: invalid literal for int(): exp... | [
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47,424 | kolypto/py-good | good/validators/strings.py | stringmethod | def stringmethod(func):
""" Validator factory which call a single method on the string. """
method_name = func()
@wraps(func)
def factory():
def validator(v):
if not isinstance(v, six.string_types):
raise Invalid(_(u'Not a string'), get_type_name(six.text_type), get_... | python | def stringmethod(func):
""" Validator factory which call a single method on the string. """
method_name = func()
@wraps(func)
def factory():
def validator(v):
if not isinstance(v, six.string_types):
raise Invalid(_(u'Not a string'), get_type_name(six.text_type), get_... | [
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47,425 | kolypto/py-good | good/validators/dates.py | FixedOffset.parse_z | def parse_z(cls, offset):
""" Parse %z offset into `timedelta` """
assert len(offset) == 5, 'Invalid offset string format, must be "+HHMM"'
return timedelta(hours=int(offset[:3]), minutes=int(offset[0] + offset[3:])) | python | def parse_z(cls, offset):
""" Parse %z offset into `timedelta` """
assert len(offset) == 5, 'Invalid offset string format, must be "+HHMM"'
return timedelta(hours=int(offset[:3]), minutes=int(offset[0] + offset[3:])) | [
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47,426 | kolypto/py-good | good/validators/dates.py | FixedOffset.format_z | def format_z(cls, offset):
""" Format `timedelta` into %z """
sec = offset.total_seconds()
return '{s}{h:02d}{m:02d}'.format(s='-' if sec<0 else '+', h=abs(int(sec/3600)), m=int((sec%3600)/60)) | python | def format_z(cls, offset):
""" Format `timedelta` into %z """
sec = offset.total_seconds()
return '{s}{h:02d}{m:02d}'.format(s='-' if sec<0 else '+', h=abs(int(sec/3600)), m=int((sec%3600)/60)) | [
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47,427 | kolypto/py-good | good/validators/dates.py | DateTime.strptime | def strptime(cls, value, format):
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This also emulates `%z` support on Python 2.
:param value: Datetime string
:type value: str
:param format: Format to use for parsing
:type format: str
:rtype: datetime
... | python | def strptime(cls, value, format):
""" Parse a datetime string using the provided format.
This also emulates `%z` support on Python 2.
:param value: Datetime string
:type value: str
:param format: Format to use for parsing
:type format: str
:rtype: datetime
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47,428 | kolypto/py-good | misc/performance/performance.py | generate_random_type | def generate_random_type(valid):
""" Generate a random type and samples for it.
:param valid: Generate valid samples?
:type valid: bool
:return: type, sample-generator
:rtype: type, generator
"""
type = choice(['int', 'str'])
r = lambda: randrange(-1000000000, 1000000000)
if type ... | python | def generate_random_type(valid):
""" Generate a random type and samples for it.
:param valid: Generate valid samples?
:type valid: bool
:return: type, sample-generator
:rtype: type, generator
"""
type = choice(['int', 'str'])
r = lambda: randrange(-1000000000, 1000000000)
if type ... | [
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47,429 | kolypto/py-good | misc/performance/performance.py | generate_random_schema | def generate_random_schema(valid):
""" Generate a random plain schema, and a sample generation function.
:param valid: Generate valid samples?
:type valid: bool
:returns: schema, sample-generator
:rtype: *, generator
"""
schema_type = choice(['literal', 'type'])
if schema_type == 'lite... | python | def generate_random_schema(valid):
""" Generate a random plain schema, and a sample generation function.
:param valid: Generate valid samples?
:type valid: bool
:returns: schema, sample-generator
:rtype: *, generator
"""
schema_type = choice(['literal', 'type'])
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47,430 | kolypto/py-good | misc/performance/performance.py | generate_dict_schema | def generate_dict_schema(size, valid):
""" Generate a schema dict of size `size` using library `lib`.
In addition, it returns samples generator
:param size: Schema size
:type size: int
:param samples: The number of samples to generate
:type samples: int
:param valid: Generate valid samples... | python | def generate_dict_schema(size, valid):
""" Generate a schema dict of size `size` using library `lib`.
In addition, it returns samples generator
:param size: Schema size
:type size: int
:param samples: The number of samples to generate
:type samples: int
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47,431 | scot-dev/scot | scot/varbase.py | _calc_q_statistic | def _calc_q_statistic(x, h, nt):
"""Calculate Portmanteau statistics up to a lag of h.
"""
t, m, n = x.shape
# covariance matrix of x
c0 = acm(x, 0)
# LU factorization of covariance matrix
c0f = sp.linalg.lu_factor(c0, overwrite_a=False, check_finite=True)
q = np.zeros((3, h + 1))
... | python | def _calc_q_statistic(x, h, nt):
"""Calculate Portmanteau statistics up to a lag of h.
"""
t, m, n = x.shape
# covariance matrix of x
c0 = acm(x, 0)
# LU factorization of covariance matrix
c0f = sp.linalg.lu_factor(c0, overwrite_a=False, check_finite=True)
q = np.zeros((3, h + 1))
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47,432 | scot-dev/scot | scot/varbase.py | _calc_q_h0 | def _calc_q_h0(n, x, h, nt, n_jobs=1, verbose=0, random_state=None):
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"""
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"""Calculate q under the null hypothesis of whiteness.
"""
rng = check_random_state(random_state)
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q = par(func(rng.permutation(x.T).T, h, nt) for _ in range(n))
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47,433 | scot-dev/scot | scot/varbase.py | VARBase.copy | def copy(self):
"""Create a copy of the VAR model."""
other = self.__class__(self.p)
other.coef = self.coef.copy()
other.residuals = self.residuals.copy()
other.rescov = self.rescov.copy()
return other | python | def copy(self):
"""Create a copy of the VAR model."""
other = self.__class__(self.p)
other.coef = self.coef.copy()
other.residuals = self.residuals.copy()
other.rescov = self.rescov.copy()
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47,434 | scot-dev/scot | scot/varbase.py | VARBase.from_yw | def from_yw(self, acms):
"""Determine VAR model from autocorrelation matrices by solving the
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Parameters
----------
acms : array, shape (n_lags, n_channels, n_channels)
acms[l] contains the autocorrelation matrix at lag l. The highest
... | python | def from_yw(self, acms):
"""Determine VAR model from autocorrelation matrices by solving the
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Parameters
----------
acms : array, shape (n_lags, n_channels, n_channels)
acms[l] contains the autocorrelation matrix at lag l. The highest
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47,435 | scot-dev/scot | scot/varbase.py | VARBase.predict | def predict(self, data):
"""Predict samples on actual data.
The result of this function is used for calculating the residuals.
Parameters
----------
data : array, shape (trials, channels, samples) or (channels, samples)
Epoched or continuous data set.
Retur... | python | def predict(self, data):
"""Predict samples on actual data.
The result of this function is used for calculating the residuals.
Parameters
----------
data : array, shape (trials, channels, samples) or (channels, samples)
Epoched or continuous data set.
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47,436 | scot-dev/scot | scot/varbase.py | VARBase.is_stable | def is_stable(self):
"""Test if VAR model is stable.
This function tests stability of the VAR model as described in [1]_.
Returns
-------
out : bool
True if the model is stable.
References
----------
.. [1] H. Lütkepohl, "New Introduction to... | python | def is_stable(self):
"""Test if VAR model is stable.
This function tests stability of the VAR model as described in [1]_.
Returns
-------
out : bool
True if the model is stable.
References
----------
.. [1] H. Lütkepohl, "New Introduction to... | [
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47,437 | scot-dev/scot | scot/datasets.py | fetch | def fetch(dataset="mi", datadir=datadir):
"""Fetch example dataset.
If the requested dataset is not found in the location specified by
`datadir`, the function attempts to download it.
Parameters
----------
dataset : str
Which dataset to load. Currently only 'mi' is supported.
datad... | python | def fetch(dataset="mi", datadir=datadir):
"""Fetch example dataset.
If the requested dataset is not found in the location specified by
`datadir`, the function attempts to download it.
Parameters
----------
dataset : str
Which dataset to load. Currently only 'mi' is supported.
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47,438 | kolypto/py-good | good/schema/compiler.py | CompiledSchema.supports_undefined | def supports_undefined(self):
""" Test whether this schema supports Undefined.
A Schema that supports `Undefined`, when given `Undefined`, should return some value (other than `Undefined`)
without raising errors.
This is designed to support a very special case like that:
```py... | python | def supports_undefined(self):
""" Test whether this schema supports Undefined.
A Schema that supports `Undefined`, when given `Undefined`, should return some value (other than `Undefined`)
without raising errors.
This is designed to support a very special case like that:
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47,439 | kolypto/py-good | good/schema/compiler.py | CompiledSchema.get_schema_type | def get_schema_type(cls, schema):
""" Get schema type for the argument
:param schema: Schema to analyze
:return: COMPILED_TYPE constant
:rtype: str|None
"""
schema_type = type(schema)
# Marker
if issubclass(schema_type, markers.Marker):
retur... | python | def get_schema_type(cls, schema):
""" Get schema type for the argument
:param schema: Schema to analyze
:return: COMPILED_TYPE constant
:rtype: str|None
"""
schema_type = type(schema)
# Marker
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47,440 | kolypto/py-good | good/schema/compiler.py | CompiledSchema.priority | def priority(self):
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:rtype: int
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47,441 | kolypto/py-good | good/schema/compiler.py | CompiledSchema.sort_schemas | def sort_schemas(cls, schemas_list):
""" Sort the provided list of schemas according to their priority.
This also supports markers, and markers of a single type are also sorted according to the priority of the wrapped schema.
:type schemas_list: list[CompiledSchema]
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""" Sort the provided list of schemas according to their priority.
This also supports markers, and markers of a single type are also sorted according to the priority of the wrapped schema.
:type schemas_list: list[CompiledSchema]
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47,442 | kolypto/py-good | good/schema/compiler.py | CompiledSchema.sub_compile | def sub_compile(self, schema, path=None, matcher=False):
""" Compile a sub-schema
:param schema: Validation schema
:type schema: *
:param path: Path to this schema, if any
:type path: list|None
:param matcher: Compile a matcher?
:type matcher: bool
:rtype... | python | def sub_compile(self, schema, path=None, matcher=False):
""" Compile a sub-schema
:param schema: Validation schema
:type schema: *
:param path: Path to this schema, if any
:type path: list|None
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47,443 | kolypto/py-good | good/schema/compiler.py | CompiledSchema.Invalid | def Invalid(self, message, expected):
""" Helper for Invalid errors.
Typical use:
err_type = self.Invalid(_(u'Message'), self.name)
raise err_type(<provided-value>)
Note: `provided` and `expected` are unicode-typecasted automatically
:type message: unicode
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""" Helper for Invalid errors.
Typical use:
err_type = self.Invalid(_(u'Message'), self.name)
raise err_type(<provided-value>)
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47,444 | kolypto/py-good | good/schema/compiler.py | CompiledSchema.get_schema_compiler | def get_schema_compiler(self, schema):
""" Get compiler method for the provided schema
:param schema: Schema to analyze
:return: Callable compiled
:rtype: callable|None
"""
# Schema type
schema_type = self.get_schema_type(schema)
if schema_type is None:
... | python | def get_schema_compiler(self, schema):
""" Get compiler method for the provided schema
:param schema: Schema to analyze
:return: Callable compiled
:rtype: callable|None
"""
# Schema type
schema_type = self.get_schema_type(schema)
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47,445 | kolypto/py-good | good/schema/compiler.py | CompiledSchema.compile_schema | def compile_schema(self, schema):
""" Compile the current schema into a callable validator
:return: Callable validator
:rtype: callable
:raises SchemaError: Schema compilation error
"""
compiler = self.get_schema_compiler(schema)
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:rtype: callable
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"""
compiler = self.get_schema_compiler(schema)
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47,446 | kolypto/py-good | good/schema/compiler.py | CompiledSchema._compile_schema | def _compile_schema(self, schema):
""" Compile another schema """
assert self.matcher == schema.matcher
self.name = schema.name
self.compiled_type = schema.compiled_type
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47,447 | scot-dev/scot | scot/matfiles.py | loadmat | def loadmat(filename):
"""This function should be called instead of direct spio.loadmat
as it cures the problem of not properly recovering python dictionaries
from mat files. It calls the function check keys to cure all entries
which are still mat-objects
"""
data = sploadmat(filename, struct_as... | python | def loadmat(filename):
"""This function should be called instead of direct spio.loadmat
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47,448 | scot-dev/scot | scot/matfiles.py | _check_keys | def _check_keys(dictionary):
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... | python | def _check_keys(dictionary):
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47,449 | scot-dev/scot | scot/matfiles.py | _todict | def _todict(matobj):
"""
a recursive function which constructs from matobjects nested dictionaries
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dictionary = {}
#noinspection PyProtectedMember
for strg in matobj._fieldnames:
elem = matobj.__dict__[strg]
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"""
a recursive function which constructs from matobjects nested dictionaries
"""
dictionary = {}
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47,450 | scot-dev/scot | scot/plainica.py | plainica | def plainica(x, reducedim=0.99, backend=None, random_state=None):
""" Source decomposition with ICA.
Apply ICA to the data x, with optional PCA dimensionality reduction.
Parameters
----------
x : array, shape (n_trials, n_channels, n_samples) or (n_channels, n_samples)
data set
reduced... | python | def plainica(x, reducedim=0.99, backend=None, random_state=None):
""" Source decomposition with ICA.
Apply ICA to the data x, with optional PCA dimensionality reduction.
Parameters
----------
x : array, shape (n_trials, n_channels, n_samples) or (n_channels, n_samples)
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47,451 | scot-dev/scot | scot/var.py | _msge_with_gradient_underdetermined | def _msge_with_gradient_underdetermined(data, delta, xvschema, skipstep, p):
"""Calculate mean squared generalization error and its gradient for
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"""
t, m, l = data.shape
d = None
j, k = 0, 0
nt = np.ceil(t / skipstep)
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"""Calculate mean squared generalization error and its gradient for
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t, m, l = data.shape
d = None
j, k = 0, 0
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47,452 | scot-dev/scot | scot/var.py | _msge_with_gradient_overdetermined | def _msge_with_gradient_overdetermined(data, delta, xvschema, skipstep, p):
"""Calculate mean squared generalization error and its gradient for
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"""
t, m, l = data.shape
d = None
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"""Calculate mean squared generalization error and its gradient for
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47,453 | scot-dev/scot | scot/var.py | _get_msge_with_gradient | def _get_msge_with_gradient(data, delta, xvschema, skipstep, p):
"""Calculate mean squared generalization error and its gradient,
automatically selecting the best function.
"""
t, m, l = data.shape
n = (l - p) * t
underdetermined = n < m * p
if underdetermined:
return _msge_with_gr... | python | def _get_msge_with_gradient(data, delta, xvschema, skipstep, p):
"""Calculate mean squared generalization error and its gradient,
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"""
t, m, l = data.shape
n = (l - p) * t
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47,454 | scot-dev/scot | scot/var.py | VAR.optimize_order | def optimize_order(self, data, min_p=1, max_p=None):
"""Determine optimal model order by minimizing the mean squared
generalization error.
Parameters
----------
data : array, shape (n_trials, n_channels, n_samples)
Epoched data set on which to optimize the model orde... | python | def optimize_order(self, data, min_p=1, max_p=None):
"""Determine optimal model order by minimizing the mean squared
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47,455 | scot-dev/scot | scot/eegtopo/geo_spherical.py | Point.fromvector | def fromvector(cls, v):
"""Initialize from euclidean vector"""
w = v.normalized()
return cls(w.x, w.y, w.z) | python | def fromvector(cls, v):
"""Initialize from euclidean vector"""
w = v.normalized()
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47,456 | scot-dev/scot | scot/eegtopo/geo_spherical.py | Point.list | def list(self):
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return [self._pos3d.x, self._pos3d.y, self._pos3d.z] | python | def list(self):
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47,457 | scot-dev/scot | scot/eegtopo/geo_spherical.py | Point.distance | def distance(self, other):
"""Distance to another point on the sphere"""
return math.acos(self._pos3d.dot(other.vector)) | python | def distance(self, other):
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return math.acos(self._pos3d.dot(other.vector)) | [
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47,458 | scot-dev/scot | scot/eegtopo/geo_spherical.py | Point.distances | def distances(self, points):
"""Distance to other points on the sphere"""
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47,459 | scot-dev/scot | scot/eegtopo/geo_euclidean.py | Vector.fromiterable | def fromiterable(cls, itr):
"""Initialize from iterable"""
x, y, z = itr
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47,460 | scot-dev/scot | scot/eegtopo/geo_euclidean.py | Vector.fromvector | def fromvector(cls, v):
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47,461 | scot-dev/scot | scot/eegtopo/geo_euclidean.py | Vector.norm2 | def norm2(self):
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47,462 | scot-dev/scot | scot/eegtopo/geo_euclidean.py | Vector.rotate | def rotate(self, l, u):
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"""rotate l radians around axis u"""
cl = math.cos(l)
sl = math.sin(l)
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47,463 | scot-dev/scot | scot/utils.py | cuthill_mckee | def cuthill_mckee(matrix):
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Permute a symmetric binary matrix into a band matrix form with a small bandwidth.
Parameters
----------
matrix : ndarray, dtype=bool, shape = [n, n]
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Permute a symmetric binary matrix into a band matrix form with a small bandwidth.
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47,464 | scot-dev/scot | scot/connectivity.py | connectivity | def connectivity(measure_names, b, c=None, nfft=512):
"""Calculate connectivity measures.
Parameters
----------
measure_names : str or list of str
Name(s) of the connectivity measure(s) to calculate. See
:class:`Connectivity` for supported measures.
b : array, shape (n_channels, n_c... | python | def connectivity(measure_names, b, c=None, nfft=512):
"""Calculate connectivity measures.
Parameters
----------
measure_names : str or list of str
Name(s) of the connectivity measure(s) to calculate. See
:class:`Connectivity` for supported measures.
b : array, shape (n_channels, n_c... | [
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47,465 | scot-dev/scot | scot/connectivity.py | Connectivity.Cinv | def Cinv(self):
"""Inverse of the noise covariance."""
try:
return np.linalg.inv(self.c)
except np.linalg.linalg.LinAlgError:
print('Warning: non-invertible noise covariance matrix c.')
return np.eye(self.c.shape[0]) | python | def Cinv(self):
"""Inverse of the noise covariance."""
try:
return np.linalg.inv(self.c)
except np.linalg.linalg.LinAlgError:
print('Warning: non-invertible noise covariance matrix c.')
return np.eye(self.c.shape[0]) | [
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47,466 | scot-dev/scot | scot/connectivity.py | Connectivity.A | def A(self):
"""Spectral VAR coefficients.
.. math:: \mathbf{A}(f) = \mathbf{I} - \sum_{k=1}^{p} \mathbf{a}^{(k)}
\mathrm{e}^{-2\pi f}
"""
return fft(np.dstack([np.eye(self.m), -self.b]),
self.nfft * 2 - 1)[:, :, :self.nfft] | python | def A(self):
"""Spectral VAR coefficients.
.. math:: \mathbf{A}(f) = \mathbf{I} - \sum_{k=1}^{p} \mathbf{a}^{(k)}
\mathrm{e}^{-2\pi f}
"""
return fft(np.dstack([np.eye(self.m), -self.b]),
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47,467 | scot-dev/scot | scot/connectivity.py | Connectivity.S | def S(self):
"""Cross-spectral density.
.. math:: \mathbf{S}(f) = \mathbf{H}(f) \mathbf{C} \mathbf{H}'(f)
"""
if self.c is None:
raise RuntimeError('Cross-spectral density requires noise '
'covariance matrix c.')
H = self.H()
# ... | python | def S(self):
"""Cross-spectral density.
.. math:: \mathbf{S}(f) = \mathbf{H}(f) \mathbf{C} \mathbf{H}'(f)
"""
if self.c is None:
raise RuntimeError('Cross-spectral density requires noise '
'covariance matrix c.')
H = self.H()
# ... | [
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47,468 | scot-dev/scot | scot/connectivity.py | Connectivity.G | def G(self):
"""Inverse cross-spectral density.
.. math:: \mathbf{G}(f) = \mathbf{A}(f) \mathbf{C}^{-1} \mathbf{A}'(f)
"""
if self.c is None:
raise RuntimeError('Inverse cross spectral density requires '
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"""Inverse cross-spectral density.
.. math:: \mathbf{G}(f) = \mathbf{A}(f) \mathbf{C}^{-1} \mathbf{A}'(f)
"""
if self.c is None:
raise RuntimeError('Inverse cross spectral density requires '
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47,469 | scot-dev/scot | scot/connectivity.py | Connectivity.pCOH | def pCOH(self):
"""Partial coherence.
.. math:: \mathrm{pCOH}_{ij}(f) = \\frac{G_{ij}(f)}
{\sqrt{G_{ii}(f) G_{jj}(f)}}
References
----------
P. J. Franaszczuk, K. J. Blinowska, M. Kowalczyk. The application of
parametric m... | python | def pCOH(self):
"""Partial coherence.
.. math:: \mathrm{pCOH}_{ij}(f) = \\frac{G_{ij}(f)}
{\sqrt{G_{ii}(f) G_{jj}(f)}}
References
----------
P. J. Franaszczuk, K. J. Blinowska, M. Kowalczyk. The application of
parametric m... | [
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.. math:: \mathrm{pCOH}_{ij}(f) = \\frac{G_{ij}(f)}
{\sqrt{G_{ii}(f) G_{jj}(f)}}
References
----------
P. J. Franaszczuk, K. J. Blinowska, M. Kowalczyk. The application of
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47,470 | scot-dev/scot | scot/connectivity.py | Connectivity.PDC | def PDC(self):
"""Partial directed coherence.
.. math:: \mathrm{PDC}_{ij}(f) = \\frac{A_{ij}(f)}
{\sqrt{A_{:j}'(f) A_{:j}(f)}}
References
----------
L. A. Baccalá, K. Sameshima. Partial directed coherence: a new concept
in ... | python | def PDC(self):
"""Partial directed coherence.
.. math:: \mathrm{PDC}_{ij}(f) = \\frac{A_{ij}(f)}
{\sqrt{A_{:j}'(f) A_{:j}(f)}}
References
----------
L. A. Baccalá, K. Sameshima. Partial directed coherence: a new concept
in ... | [
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L. A. Baccalá, K. Sameshima. Partial directed coherence: a new concept
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47,471 | scot-dev/scot | scot/connectivity.py | Connectivity.ffPDC | def ffPDC(self):
"""Full frequency partial directed coherence.
.. math:: \mathrm{ffPDC}_{ij}(f) =
\\frac{A_{ij}(f)}{\sqrt{\sum_f A_{:j}'(f) A_{:j}(f)}}
"""
A = self.A()
return np.abs(A * self.nfft / np.sqrt(np.sum(A.conj() * A, axis=(0, 2),
... | python | def ffPDC(self):
"""Full frequency partial directed coherence.
.. math:: \mathrm{ffPDC}_{ij}(f) =
\\frac{A_{ij}(f)}{\sqrt{\sum_f A_{:j}'(f) A_{:j}(f)}}
"""
A = self.A()
return np.abs(A * self.nfft / np.sqrt(np.sum(A.conj() * A, axis=(0, 2),
... | [
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47,472 | scot-dev/scot | scot/connectivity.py | Connectivity.PDCF | def PDCF(self):
"""Partial directed coherence factor.
.. math:: \mathrm{PDCF}_{ij}(f) =
\\frac{A_{ij}(f)}{\sqrt{A_{:j}'(f) \mathbf{C}^{-1} A_{:j}(f)}}
References
----------
L. A. Baccalá, K. Sameshima. Partial directed coherence: a new concept
in neural structur... | python | def PDCF(self):
"""Partial directed coherence factor.
.. math:: \mathrm{PDCF}_{ij}(f) =
\\frac{A_{ij}(f)}{\sqrt{A_{:j}'(f) \mathbf{C}^{-1} A_{:j}(f)}}
References
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.. math:: \mathrm{PDCF}_{ij}(f) =
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L. A. Baccalá, K. Sameshima. Partial directed coherence: a new concept
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47,473 | scot-dev/scot | scot/connectivity.py | Connectivity.GPDC | def GPDC(self):
"""Generalized partial directed coherence.
.. math:: \mathrm{GPDC}_{ij}(f) = \\frac{|A_{ij}(f)|}
{\sigma_i \sqrt{A_{:j}'(f) \mathrm{diag}(\mathbf{C})^{-1} A_{:j}(f)}}
References
----------
L. Faes, S. Erla, G. Nollo. Measuring connectivity in linear
... | python | def GPDC(self):
"""Generalized partial directed coherence.
.. math:: \mathrm{GPDC}_{ij}(f) = \\frac{|A_{ij}(f)|}
{\sigma_i \sqrt{A_{:j}'(f) \mathrm{diag}(\mathbf{C})^{-1} A_{:j}(f)}}
References
----------
L. Faes, S. Erla, G. Nollo. Measuring connectivity in linear
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47,474 | scot-dev/scot | scot/connectivity.py | Connectivity.DTF | def DTF(self):
"""Directed transfer function.
.. math:: \mathrm{DTF}_{ij}(f) = \\frac{H_{ij}(f)}
{\sqrt{H_{i:}(f) H_{i:}'(f)}}
References
----------
M. J. Kaminski, K. J. Blinowska. A new method of the description of the
in... | python | def DTF(self):
"""Directed transfer function.
.. math:: \mathrm{DTF}_{ij}(f) = \\frac{H_{ij}(f)}
{\sqrt{H_{i:}(f) H_{i:}'(f)}}
References
----------
M. J. Kaminski, K. J. Blinowska. A new method of the description of the
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47,475 | scot-dev/scot | scot/connectivity.py | Connectivity.ffDTF | def ffDTF(self):
"""Full frequency directed transfer function.
.. math:: \mathrm{ffDTF}_{ij}(f) =
\\frac{H_{ij}(f)}{\sqrt{\sum_f H_{i:}(f) H_{i:}'(f)}}
References
----------
A. Korzeniewska, M. Mańczak, M. Kaminski, K. J. Blinowska, S. Kasicki.
Determi... | python | def ffDTF(self):
"""Full frequency directed transfer function.
.. math:: \mathrm{ffDTF}_{ij}(f) =
\\frac{H_{ij}(f)}{\sqrt{\sum_f H_{i:}(f) H_{i:}'(f)}}
References
----------
A. Korzeniewska, M. Mańczak, M. Kaminski, K. J. Blinowska, S. Kasicki.
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47,476 | scot-dev/scot | scot/connectivity.py | Connectivity.GDTF | def GDTF(self):
"""Generalized directed transfer function.
.. math:: \mathrm{GPDC}_{ij}(f) = \\frac{\sigma_j |H_{ij}(f)|}
{\sqrt{H_{i:}(f) \mathrm{diag}(\mathbf{C}) H_{i:}'(f)}}
References
----------
L. Faes, S. Erla, G. Nollo. Measuring connectivity in linear
... | python | def GDTF(self):
"""Generalized directed transfer function.
.. math:: \mathrm{GPDC}_{ij}(f) = \\frac{\sigma_j |H_{ij}(f)|}
{\sqrt{H_{i:}(f) \mathrm{diag}(\mathbf{C}) H_{i:}'(f)}}
References
----------
L. Faes, S. Erla, G. Nollo. Measuring connectivity in linear
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47,477 | kolypto/py-good | good/schema/errors.py | Invalid.enrich | def enrich(self, expected=None, provided=None, path=None, validator=None):
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This works with both Invalid and MultipleInvalid (thanks to `Invalid` being iterable):
in the latter case, the defaults are applied to all collected errors.
The... | python | def enrich(self, expected=None, provided=None, path=None, validator=None):
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47,478 | kolypto/py-good | good/schema/errors.py | MultipleInvalid.flatten | def flatten(cls, errors):
""" Unwind `MultipleErrors` to have a plain list of `Invalid`
:type errors: list[Invalid|MultipleInvalid]
:rtype: list[Invalid]
"""
ers = []
for e in errors:
if isinstance(e, MultipleInvalid):
ers.extend(cls.flatten(e... | python | def flatten(cls, errors):
""" Unwind `MultipleErrors` to have a plain list of `Invalid`
:type errors: list[Invalid|MultipleInvalid]
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47,479 | scot-dev/scot | scot/eegtopo/warp_layout.py | warp_locations | def warp_locations(locations, y_center=None, return_ellipsoid=False, verbose=False):
""" Warp EEG electrode locations to spherical layout.
EEG Electrodes are warped to a spherical layout in three steps:
1. An ellipsoid is least-squares-fitted to the electrode locations.
2. Electrodes are displa... | python | def warp_locations(locations, y_center=None, return_ellipsoid=False, verbose=False):
""" Warp EEG electrode locations to spherical layout.
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47,480 | scot-dev/scot | scot/eegtopo/warp_layout.py | _project_on_ellipsoid | def _project_on_ellipsoid(c, r, locations):
"""displace locations to the nearest point on ellipsoid surface"""
p0 = locations - c # original locations
l2 = 1 / np.sum(p0**2 / r**2, axis=1, keepdims=True)
p = p0 * np.sqrt(l2) # initial approximation (projection of points towards center of ellipsoid)
... | python | def _project_on_ellipsoid(c, r, locations):
"""displace locations to the nearest point on ellipsoid surface"""
p0 = locations - c # original locations
l2 = 1 / np.sum(p0**2 / r**2, axis=1, keepdims=True)
p = p0 * np.sqrt(l2) # initial approximation (projection of points towards center of ellipsoid)
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47,481 | scot-dev/scot | scot/datatools.py | cut_segments | def cut_segments(x2d, tr, start, stop):
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Parameters
----------
x2d : array, shape (m, n)
Input data with m signals and n samples.
tr : list of int
Trigger positions.
start : int
Window start (offset relative to trigger).
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"""Cut continuous signal into segments.
Parameters
----------
x2d : array, shape (m, n)
Input data with m signals and n samples.
tr : list of int
Trigger positions.
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Window start (offset relative to trigger).
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47,482 | scot-dev/scot | scot/datatools.py | cat_trials | def cat_trials(x3d):
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Parameters
----------
x3d : array, shape (t, m, n)
Segmented input data with t trials, m signals, and n samples.
Returns
-------
x2d : array, shape (m, t * n)
Trials are concatenated along the second axis.
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"""Concatenate trials along time axis.
Parameters
----------
x3d : array, shape (t, m, n)
Segmented input data with t trials, m signals, and n samples.
Returns
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x2d : array, shape (m, t * n)
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47,483 | scot-dev/scot | scot/datatools.py | dot_special | def dot_special(x2d, x3d):
"""Segment-wise dot product.
This function calculates the dot product of x2d with each trial of x3d.
Parameters
----------
x2d : array, shape (p, m)
Input argument.
x3d : array, shape (t, m, n)
Segmented input data with t trials, m signals, and n samp... | python | def dot_special(x2d, x3d):
"""Segment-wise dot product.
This function calculates the dot product of x2d with each trial of x3d.
Parameters
----------
x2d : array, shape (p, m)
Input argument.
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47,484 | scot-dev/scot | scot/datatools.py | randomize_phase | def randomize_phase(data, random_state=None):
"""Phase randomization.
This function randomizes the spectral phase of the input data along the
last dimension.
Parameters
----------
data : array
Input array.
Returns
-------
out : array
Array of same shape as data.
... | python | def randomize_phase(data, random_state=None):
"""Phase randomization.
This function randomizes the spectral phase of the input data along the
last dimension.
Parameters
----------
data : array
Input array.
Returns
-------
out : array
Array of same shape as data.
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47,485 | scot-dev/scot | scot/datatools.py | acm | def acm(x, l):
"""Compute autocovariance matrix at lag l.
This function calculates the autocovariance matrix of `x` at lag `l`.
Parameters
----------
x : array, shape (n_trials, n_channels, n_samples)
Signal data (2D or 3D for multiple trials)
l : int
Lag
Returns
-----... | python | def acm(x, l):
"""Compute autocovariance matrix at lag l.
This function calculates the autocovariance matrix of `x` at lag `l`.
Parameters
----------
x : array, shape (n_trials, n_channels, n_samples)
Signal data (2D or 3D for multiple trials)
l : int
Lag
Returns
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47,486 | scot-dev/scot | scot/connectivity_statistics.py | jackknife_connectivity | def jackknife_connectivity(measures, data, var, nfft=512, leaveout=1, n_jobs=1,
verbose=0):
"""Calculate jackknife estimates of connectivity.
For each jackknife estimate a block of trials is left out. This is repeated
until each trial was left out exactly once. The number of esti... | python | def jackknife_connectivity(measures, data, var, nfft=512, leaveout=1, n_jobs=1,
verbose=0):
"""Calculate jackknife estimates of connectivity.
For each jackknife estimate a block of trials is left out. This is repeated
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47,487 | scot-dev/scot | scot/connectivity_statistics.py | bootstrap_connectivity | def bootstrap_connectivity(measures, data, var, nfft=512, repeats=100,
num_samples=None, n_jobs=1, verbose=0,
random_state=None):
"""Calculate bootstrap estimates of connectivity.
To obtain a bootstrap estimate trials are sampled randomly with replacement
... | python | def bootstrap_connectivity(measures, data, var, nfft=512, repeats=100,
num_samples=None, n_jobs=1, verbose=0,
random_state=None):
"""Calculate bootstrap estimates of connectivity.
To obtain a bootstrap estimate trials are sampled randomly with replacement
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47,488 | scot-dev/scot | scot/connectivity_statistics.py | significance_fdr | def significance_fdr(p, alpha):
"""Calculate significance by controlling for the false discovery rate.
This function determines which of the p-values in `p` can be considered
significant. Correction for multiple comparisons is performed by
controlling the false discovery rate (FDR). The FDR is the maxi... | python | def significance_fdr(p, alpha):
"""Calculate significance by controlling for the false discovery rate.
This function determines which of the p-values in `p` can be considered
significant. Correction for multiple comparisons is performed by
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47,489 | kolypto/py-good | good/schema/util.py | register_type_name | def register_type_name(t, name):
""" Register a human-friendly name for the given type. This will be used in Invalid errors
:param t: The type to register
:type t: type
:param name: Name for the type
:type name: unicode
"""
assert isinstance(t, type)
assert isinstance(name, unicode)
... | python | def register_type_name(t, name):
""" Register a human-friendly name for the given type. This will be used in Invalid errors
:param t: The type to register
:type t: type
:param name: Name for the type
:type name: unicode
"""
assert isinstance(t, type)
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47,490 | kolypto/py-good | good/schema/util.py | get_type_name | def get_type_name(t):
""" Get a human-friendly name for the given type.
:type t: type|None
:rtype: unicode
"""
# Lookup in the mapping
try:
return __type_names[t]
except KeyError:
# Specific types
if issubclass(t, six.integer_types):
return _(u'Integer nu... | python | def get_type_name(t):
""" Get a human-friendly name for the given type.
:type t: type|None
:rtype: unicode
"""
# Lookup in the mapping
try:
return __type_names[t]
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47,491 | kolypto/py-good | good/schema/util.py | get_callable_name | def get_callable_name(c):
""" Get a human-friendly name for the given callable.
:param c: The callable to get the name for
:type c: callable
:rtype: unicode
"""
if hasattr(c, 'name'):
return six.text_type(c.name)
elif hasattr(c, '__name__'):
return six.text_type(c.__name__) ... | python | def get_callable_name(c):
""" Get a human-friendly name for the given callable.
:param c: The callable to get the name for
:type c: callable
:rtype: unicode
"""
if hasattr(c, 'name'):
return six.text_type(c.name)
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47,492 | kolypto/py-good | good/schema/util.py | get_primitive_name | def get_primitive_name(schema):
""" Get a human-friendly name for the given primitive.
:param schema: Schema
:type schema: *
:rtype: unicode
"""
try:
return {
const.COMPILED_TYPE.LITERAL: six.text_type,
const.COMPILED_TYPE.TYPE: get_type_name,
const.C... | python | def get_primitive_name(schema):
""" Get a human-friendly name for the given primitive.
:param schema: Schema
:type schema: *
:rtype: unicode
"""
try:
return {
const.COMPILED_TYPE.LITERAL: six.text_type,
const.COMPILED_TYPE.TYPE: get_type_name,
const.C... | [
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47,493 | kolypto/py-good | good/schema/util.py | primitive_type | def primitive_type(schema):
""" Get schema type for the primitive argument.
Note: it does treats markers & schemas as callables!
:param schema: Value of a primitive type
:type schema: *
:return: const.COMPILED_TYPE.*
:rtype: str|None
"""
schema_type = type(schema)
# Literal
if... | python | def primitive_type(schema):
""" Get schema type for the primitive argument.
Note: it does treats markers & schemas as callables!
:param schema: Value of a primitive type
:type schema: *
:return: const.COMPILED_TYPE.*
:rtype: str|None
"""
schema_type = type(schema)
# Literal
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47,494 | kolypto/py-good | good/schema/util.py | commajoin_as_strings | def commajoin_as_strings(iterable):
""" Join the given iterable with ',' """
return _(u',').join((six.text_type(i) for i in iterable)) | python | def commajoin_as_strings(iterable):
""" Join the given iterable with ',' """
return _(u',').join((six.text_type(i) for i in iterable)) | [
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47,495 | scot-dev/scot | scot/plotting.py | prepare_topoplots | def prepare_topoplots(topo, values):
"""Prepare multiple topo maps for cached plotting.
.. note:: Parameter `topo` is modified by the function by calling :func:`~eegtopo.topoplot.Topoplot.set_values`.
Parameters
----------
topo : :class:`~eegtopo.topoplot.Topoplot`
Scalp maps are created w... | python | def prepare_topoplots(topo, values):
"""Prepare multiple topo maps for cached plotting.
.. note:: Parameter `topo` is modified by the function by calling :func:`~eegtopo.topoplot.Topoplot.set_values`.
Parameters
----------
topo : :class:`~eegtopo.topoplot.Topoplot`
Scalp maps are created w... | [
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.. note:: Parameter `topo` is modified by the function by calling :func:`~eegtopo.topoplot.Topoplot.set_values`.
Parameters
----------
topo : :class:`~eegtopo.topoplot.Topoplot`
Scalp maps are created with this class
values : array, shape = [... | [
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47,496 | scot-dev/scot | scot/plotting.py | plot_topo | def plot_topo(axis, topo, topomap, crange=None, offset=(0,0),
plot_locations=True, plot_head=True):
"""Draw a topoplot in given axis.
.. note:: Parameter `topo` is modified by the function by calling :func:`~eegtopo.topoplot.Topoplot.set_map`.
Parameters
----------
axis : axis
... | python | def plot_topo(axis, topo, topomap, crange=None, offset=(0,0),
plot_locations=True, plot_head=True):
"""Draw a topoplot in given axis.
.. note:: Parameter `topo` is modified by the function by calling :func:`~eegtopo.topoplot.Topoplot.set_map`.
Parameters
----------
axis : axis
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Parameters
----------
axis : axis
Axis to draw into.
topo : :class:`~eegtopo.topoplot.Topoplot`
This object draws the topo plot
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47,497 | scot-dev/scot | scot/plotting.py | plot_sources | def plot_sources(topo, mixmaps, unmixmaps, global_scale=None, fig=None):
"""Plot all scalp projections of mixing- and unmixing-maps.
.. note:: Parameter `topo` is modified by the function by calling :func:`~eegtopo.topoplot.Topoplot.set_map`.
Parameters
----------
topo : :class:`~eegtopo.topoplot.... | python | def plot_sources(topo, mixmaps, unmixmaps, global_scale=None, fig=None):
"""Plot all scalp projections of mixing- and unmixing-maps.
.. note:: Parameter `topo` is modified by the function by calling :func:`~eegtopo.topoplot.Topoplot.set_map`.
Parameters
----------
topo : :class:`~eegtopo.topoplot.... | [
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Parameters
----------
topo : :class:`~eegtopo.topoplot.Topoplot`
This object draws the topo plot
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47,498 | scot-dev/scot | scot/plotting.py | plot_connectivity_topos | def plot_connectivity_topos(layout='diagonal', topo=None, topomaps=None, fig=None):
"""Place topo plots in a figure suitable for connectivity visualization.
.. note:: Parameter `topo` is modified by the function by calling :func:`~eegtopo.topoplot.Topoplot.set_map`.
Parameters
----------
layout : ... | python | def plot_connectivity_topos(layout='diagonal', topo=None, topomaps=None, fig=None):
"""Place topo plots in a figure suitable for connectivity visualization.
.. note:: Parameter `topo` is modified by the function by calling :func:`~eegtopo.topoplot.Topoplot.set_map`.
Parameters
----------
layout : ... | [
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Parameters
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layout : str
'diagonal' -> place topo plots on diagonal.
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47,499 | scot-dev/scot | scot/plotting.py | plot_connectivity_significance | def plot_connectivity_significance(s, fs=2, freq_range=(-np.inf, np.inf), diagonal=0, border=False, fig=None):
"""Plot significance.
Significance is drawn as a background image where dark vertical stripes indicate freuquencies where a evaluates to
True.
Parameters
----------
a : array, shape (... | python | def plot_connectivity_significance(s, fs=2, freq_range=(-np.inf, np.inf), diagonal=0, border=False, fig=None):
"""Plot significance.
Significance is drawn as a background image where dark vertical stripes indicate freuquencies where a evaluates to
True.
Parameters
----------
a : array, shape (... | [
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a : array, shape (n_channels, n_channels, n_fft), dtype bool
Significance
fs : float
Sampling frequency
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