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shmuelamar/cbox | cbox/cli.py | cmd | def cmd(f):
"""wrapper for easily exposing a function as a CLI command.
including help message, arguments help and type.
Example Usage:
>>> import cbox
>>>
>>> @cbox.cmd
>>> def hello(name: str):
>>> '''greets a person by its name.
>>>
>>> :p... | python | def cmd(f):
"""wrapper for easily exposing a function as a CLI command.
including help message, arguments help and type.
Example Usage:
>>> import cbox
>>>
>>> @cbox.cmd
>>> def hello(name: str):
>>> '''greets a person by its name.
>>>
>>> :p... | [
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shmuelamar/cbox | cbox/cli.py | main | def main(func=None, argv=None, input_stream=stdin, output_stream=stdout,
error_stream=stderr, exit=True):
"""runs a function as a command.
runs a function as a command - reading input from `input_stream`, writing
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Example Usage:
... | python | def main(func=None, argv=None, input_stream=stdin, output_stream=stdout,
error_stream=stderr, exit=True):
"""runs a function as a command.
runs a function as a command - reading input from `input_stream`, writing
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Example Usage:
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shmuelamar/cbox | cbox/cliparser.py | _parse_docstring | def _parse_docstring(docstring):
"""parses docstring into its help message and params"""
params = {}
if not docstring:
return None, params
try:
help_msg = _DOCSTRING_REGEX.search(docstring).group()
help_msg = _strip_lines(help_msg)
except AttributeError:
help_msg = ... | python | def _parse_docstring(docstring):
"""parses docstring into its help message and params"""
params = {}
if not docstring:
return None, params
try:
help_msg = _DOCSTRING_REGEX.search(docstring).group()
help_msg = _strip_lines(help_msg)
except AttributeError:
help_msg = ... | [
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shmuelamar/cbox | cbox/utils.py | error2str | def error2str(e):
"""returns the formatted stacktrace of the exception `e`.
:param BaseException e: an exception to format into str
:rtype: str
"""
out = StringIO()
traceback.print_exception(None, e, e.__traceback__, file=out)
out.seek(0)
return out.read() | python | def error2str(e):
"""returns the formatted stacktrace of the exception `e`.
:param BaseException e: an exception to format into str
:rtype: str
"""
out = StringIO()
traceback.print_exception(None, e, e.__traceback__, file=out)
out.seek(0)
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shmuelamar/cbox | cbox/concurrency.py | get_runner | def get_runner(worker_type, max_workers=None, workers_window=None):
"""returns a runner callable.
:param str worker_type: one of `simple` or `thread`.
:param int max_workers: max workers the runner can spawn in parallel.
:param in workers_window: max number of jobs waiting to be done by the
worke... | python | def get_runner(worker_type, max_workers=None, workers_window=None):
"""returns a runner callable.
:param str worker_type: one of `simple` or `thread`.
:param int max_workers: max workers the runner can spawn in parallel.
:param in workers_window: max number of jobs waiting to be done by the
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shmuelamar/cbox | cbox/__main__.py | get_inline_func | def get_inline_func(inline_str, modules=None, **stream_kwargs):
"""returns a function decorated by `cbox.stream` decorator.
:param str inline_str: the inline function to execute,
can use `s` - local variable as the input line/char/raw
(according to `input_type` param).
:param str modules: comma... | python | def get_inline_func(inline_str, modules=None, **stream_kwargs):
"""returns a function decorated by `cbox.stream` decorator.
:param str inline_str: the inline function to execute,
can use `s` - local variable as the input line/char/raw
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rm-hull/OPi.GPIO | OPi/GPIO.py | setmode | def setmode(mode):
"""
You must call this method prior to using all other calls.
:param mode: the mode, one of :py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM`,
:py:attr:`GPIO.SUNXI`, or a `dict` or `object` representing a custom
pin mapping.
"""
if hasattr(mode, '__getitem__'):
s... | python | def setmode(mode):
"""
You must call this method prior to using all other calls.
:param mode: the mode, one of :py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM`,
:py:attr:`GPIO.SUNXI`, or a `dict` or `object` representing a custom
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rm-hull/OPi.GPIO | OPi/GPIO.py | setup | def setup(channel, direction, initial=None, pull_up_down=None):
"""
You need to set up every channel you are using as an input or an output.
:param channel: the channel based on the numbering system you have specified
(:py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM` or :py:attr:`GPIO.SUNXI`).
:param... | python | def setup(channel, direction, initial=None, pull_up_down=None):
"""
You need to set up every channel you are using as an input or an output.
:param channel: the channel based on the numbering system you have specified
(:py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM` or :py:attr:`GPIO.SUNXI`).
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rm-hull/OPi.GPIO | OPi/GPIO.py | input | def input(channel):
"""
Read the value of a GPIO pin.
:param channel: the channel based on the numbering system you have specified
(:py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM` or :py:attr:`GPIO.SUNXI`).
:returns: This will return either :py:attr:`0` / :py:attr:`GPIO.LOW` /
:py:attr:`Fals... | python | def input(channel):
"""
Read the value of a GPIO pin.
:param channel: the channel based on the numbering system you have specified
(:py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM` or :py:attr:`GPIO.SUNXI`).
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rm-hull/OPi.GPIO | OPi/GPIO.py | output | def output(channel, state):
"""
Set the output state of a GPIO pin.
:param channel: the channel based on the numbering system you have specified
(:py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM` or :py:attr:`GPIO.SUNXI`).
:param state: can be :py:attr:`0` / :py:attr:`GPIO.LOW` / :py:attr:`False`
... | python | def output(channel, state):
"""
Set the output state of a GPIO pin.
:param channel: the channel based on the numbering system you have specified
(:py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM` or :py:attr:`GPIO.SUNXI`).
:param state: can be :py:attr:`0` / :py:attr:`GPIO.LOW` / :py:attr:`False`
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rm-hull/OPi.GPIO | OPi/GPIO.py | wait_for_edge | def wait_for_edge(channel, trigger, timeout=-1):
"""
This function is designed to block execution of your program until an edge
is detected.
:param channel: the channel based on the numbering system you have specified
(:py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM` or :py:attr:`GPIO.SUNXI`).
:p... | python | def wait_for_edge(channel, trigger, timeout=-1):
"""
This function is designed to block execution of your program until an edge
is detected.
:param channel: the channel based on the numbering system you have specified
(:py:attr:`GPIO.BOARD`, :py:attr:`GPIO.BCM` or :py:attr:`GPIO.SUNXI`).
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wq/django-swappable-models | swapper/__init__.py | is_swapped | def is_swapped(app_label, model):
"""
Returns the value of the swapped setting, or False if the model hasn't
been swapped.
"""
default_model = join(app_label, model)
setting = swappable_setting(app_label, model)
value = getattr(settings, setting, default_model)
if value != default_model:... | python | def is_swapped(app_label, model):
"""
Returns the value of the swapped setting, or False if the model hasn't
been swapped.
"""
default_model = join(app_label, model)
setting = swappable_setting(app_label, model)
value = getattr(settings, setting, default_model)
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wq/django-swappable-models | swapper/__init__.py | get_model_names | def get_model_names(app_label, models):
"""
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for model in models
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"""
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grimen/python-attributedict | attributedict/collections.py | AttributeDict.update | def update(self, entries = {}, *args, **kwargs):
"""
Update dictionary.
@example:
object.update({'foo': {'bar': 1}})
"""
if isinstance(entries, dict):
entries = self._reject_reserved_keys(entries)
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"""
Update dictionary.
@example:
object.update({'foo': {'bar': 1}})
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elyase/geotext | geotext/geotext.py | read_table | def read_table(filename, usecols=(0, 1), sep='\t', comment='#', encoding='utf-8', skip=0):
"""Parse data files from the data directory
Parameters
----------
filename: string
Full path to file
usecols: list, default [0, 1]
A list of two elements representing the columns to be parsed... | python | def read_table(filename, usecols=(0, 1), sep='\t', comment='#', encoding='utf-8', skip=0):
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"""Load information from the data directory
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"""Load information from the data directory
Returns
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A namedtuple with three fields: nationalities cities countries
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almarklein/pyelastix | pyelastix.py | _find_executables | def _find_executables(name):
""" Try to find an executable.
"""
exe_name = name + '.exe' * sys.platform.startswith('win')
env_path = os.environ.get(name.upper()+ '_PATH', '')
possible_locations = []
def add(*dirs):
for d in dirs:
if d and d not in possible_locations and ... | python | def _find_executables(name):
""" Try to find an executable.
"""
exe_name = name + '.exe' * sys.platform.startswith('win')
env_path = os.environ.get(name.upper()+ '_PATH', '')
possible_locations = []
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almarklein/pyelastix | pyelastix.py | get_elastix_exes | def get_elastix_exes():
""" Get the executables for elastix and transformix. Raises an error
if they cannot be found.
"""
if EXES:
if EXES[0]:
return EXES
else:
raise RuntimeError('No Elastix executable.')
# Find exe
elastix, ver = _find_executables('... | python | def get_elastix_exes():
""" Get the executables for elastix and transformix. Raises an error
if they cannot be found.
"""
if EXES:
if EXES[0]:
return EXES
else:
raise RuntimeError('No Elastix executable.')
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almarklein/pyelastix | pyelastix.py | _clear_dir | def _clear_dir(dirName):
""" Remove a directory and it contents. Ignore any failures.
"""
# If we got here, clear dir
for fname in os.listdir(dirName):
try:
os.remove( os.path.join(dirName, fname) )
except Exception:
pass
try:
os.rmdir(dirName)
e... | python | def _clear_dir(dirName):
""" Remove a directory and it contents. Ignore any failures.
"""
# If we got here, clear dir
for fname in os.listdir(dirName):
try:
os.remove( os.path.join(dirName, fname) )
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almarklein/pyelastix | pyelastix.py | get_tempdir | def get_tempdir():
""" Get the temporary directory where pyelastix stores its temporary
files. The directory is specific to the current process and the
calling thread. Generally, the user does not need this; directories
are automatically cleaned up. Though Elastix log files are also
written here.
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""" Get the temporary directory where pyelastix stores its temporary
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almarklein/pyelastix | pyelastix.py | _clear_temp_dir | def _clear_temp_dir():
""" Clear the temporary directory.
"""
tempdir = get_tempdir()
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try:
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""" Clear the temporary directory.
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almarklein/pyelastix | pyelastix.py | _get_image_paths | def _get_image_paths(im1, im2):
""" If the images are paths to a file, checks whether the file exist
and return the paths. If the images are numpy arrays, writes them
to disk and returns the paths of the new files.
"""
paths = []
for im in [im1, im2]:
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# Gr... | python | def _get_image_paths(im1, im2):
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almarklein/pyelastix | pyelastix.py | _system3 | def _system3(cmd, verbose=False):
""" Execute the given command in a subprocess and wait for it to finish.
A thread is run that prints output of the process if verbose is True.
"""
# Init flag
interrupted = False
# Create progress
if verbose > 0:
progress = Progress()
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""" Execute the given command in a subprocess and wait for it to finish.
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"""
# Init flag
interrupted = False
# Create progress
if verbose > 0:
progress = Progress()
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almarklein/pyelastix | pyelastix.py | _get_dtype_maps | def _get_dtype_maps():
""" Get dictionaries to map numpy data types to ITK types and the
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"""
# Define pairs
tmp = [ (np.float32, 'MET_FLOAT'), (np.float64, 'MET_DOUBLE'),
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(np.uint16, 'MET_USHORT'), (... | python | def _get_dtype_maps():
""" Get dictionaries to map numpy data types to ITK types and the
other way around.
"""
# Define pairs
tmp = [ (np.float32, 'MET_FLOAT'), (np.float64, 'MET_DOUBLE'),
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almarklein/pyelastix | pyelastix.py | _read_image_data | def _read_image_data( mhd_file):
""" Read the resulting image data and return it as a numpy array.
"""
tempdir = get_tempdir()
# Load description from mhd file
fname = tempdir + '/' + mhd_file
des = open(fname, 'r').read()
# Get data filename and load raw data
match = re.findal... | python | def _read_image_data( mhd_file):
""" Read the resulting image data and return it as a numpy array.
"""
tempdir = get_tempdir()
# Load description from mhd file
fname = tempdir + '/' + mhd_file
des = open(fname, 'r').read()
# Get data filename and load raw data
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almarklein/pyelastix | pyelastix.py | _get_fixed_params | def _get_fixed_params(im):
""" Parameters that the user has no influence on. Mostly chosen
bases on the input images.
"""
p = Parameters()
if not isinstance(im, np.ndarray):
return p
# Dimension of the inputs
p.FixedImageDimension = im.ndim
p.MovingImageDimension =... | python | def _get_fixed_params(im):
""" Parameters that the user has no influence on. Mostly chosen
bases on the input images.
"""
p = Parameters()
if not isinstance(im, np.ndarray):
return p
# Dimension of the inputs
p.FixedImageDimension = im.ndim
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almarklein/pyelastix | pyelastix.py | get_advanced_params | def get_advanced_params():
""" Get `Parameters` struct with parameters that most users do not
want to think about.
"""
p = Parameters()
# Internal format used during the registration process
p.FixedInternalImagePixelType = "float"
p.MovingInternalImagePixelType = "float"
#... | python | def get_advanced_params():
""" Get `Parameters` struct with parameters that most users do not
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"""
p = Parameters()
# Internal format used during the registration process
p.FixedInternalImagePixelType = "float"
p.MovingInternalImagePixelType = "float"
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almarklein/pyelastix | pyelastix.py | _write_parameter_file | def _write_parameter_file(params):
""" Write the parameter file in the format that elaxtix likes.
"""
# Get path
path = os.path.join(get_tempdir(), 'params.txt')
# Define helper function
def valToStr(val):
if val in [True, False]:
return '"%s"' % str(val).lower()
... | python | def _write_parameter_file(params):
""" Write the parameter file in the format that elaxtix likes.
"""
# Get path
path = os.path.join(get_tempdir(), 'params.txt')
# Define helper function
def valToStr(val):
if val in [True, False]:
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pypa/readme_renderer | readme_renderer/markdown.py | _highlight | def _highlight(html):
"""Syntax-highlights HTML-rendered Markdown.
Plucks sections to highlight that conform the the GitHub fenced code info
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Args:
html (str): The rendered HTML.
Returns:
str: The HTML with Pygments s... | python | def _highlight(html):
"""Syntax-highlights HTML-rendered Markdown.
Plucks sections to highlight that conform the the GitHub fenced code info
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streeter/pelican-gist | pelican_gist/plugin.py | render_code | def render_code(code, filetype, pygments_style):
"""Renders a piece of code into HTML. Highlights syntax if filetype is specfied"""
if filetype:
lexer = pygments.lexers.get_lexer_by_name(filetype)
formatter = pygments.formatters.HtmlFormatter(style=pygments_style)
return pygments.highlig... | python | def render_code(code, filetype, pygments_style):
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biosustain/optlang | optlang/gurobi_interface.py | _constraint_lb_and_ub_to_gurobi_sense_rhs_and_range_value | def _constraint_lb_and_ub_to_gurobi_sense_rhs_and_range_value(lb, ub):
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if lb is None and ub is None:
raise Exception("Free constraint ...")
elif lb is None:
sense = '<'
rhs = float(ub)
range_value = 0.
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... | python | def _constraint_lb_and_ub_to_gurobi_sense_rhs_and_range_value(lb, ub):
"""Helper function used by Constraint and Model"""
if lb is None and ub is None:
raise Exception("Free constraint ...")
elif lb is None:
sense = '<'
rhs = float(ub)
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biosustain/optlang | optlang/expression_parsing.py | parse_optimization_expression | def parse_optimization_expression(obj, linear=True, quadratic=False, expression=None, **kwargs):
"""
Function for parsing the expression of a Constraint or Objective object.
Parameters
----------
object: Constraint or Objective
The optimization expression to be parsed
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Function for parsing the expression of a Constraint or Objective object.
Parameters
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object: Constraint or Objective
The optimization expression to be parsed
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biosustain/optlang | optlang/interface.py | Variable.clone | def clone(cls, variable, **kwargs):
"""
Make a copy of another variable. The variable being copied can be of the same type or belong to
a different solver interface.
Example
----------
>>> var_copy = Variable.clone(old_var)
"""
return cls(variable.name, l... | python | def clone(cls, variable, **kwargs):
"""
Make a copy of another variable. The variable being copied can be of the same type or belong to
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Example
----------
>>> var_copy = Variable.clone(old_var)
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biosustain/optlang | optlang/interface.py | Variable.set_bounds | def set_bounds(self, lb, ub):
"""
Change the lower and upper bounds of a variable.
"""
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raise ValueError(
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"""
Change the lower and upper bounds of a variable.
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biosustain/optlang | optlang/interface.py | Variable.to_json | def to_json(self):
"""
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Example
--------
>>> import json
>>> with open("path_to_file.json", "w") as outfile:
>>> json.dump(var.to_json(), outfile)
"""
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biosustain/optlang | optlang/interface.py | Constraint.clone | def clone(cls, constraint, model=None, **kwargs):
"""
Make a copy of another constraint. The constraint being copied can be of the same type or belong to
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Parameters
----------
constraint: interface.Constraint (or subclass)
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biosustain/optlang | optlang/interface.py | Constraint.to_json | def to_json(self):
"""
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Example
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>>> import json
>>> with open("path_to_file.json", "w") as outfile:
>>> json.dump(constraint.to_json(), outfile)
"""
... | python | def to_json(self):
"""
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Example
--------
>>> import json
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>>> json.dump(constraint.to_json(), outfile)
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biosustain/optlang | optlang/interface.py | Objective.clone | def clone(cls, objective, model=None, **kwargs):
"""
Make a copy of an objective. The objective being copied can be of the same type or belong to
a different solver interface.
Example
----------
>>> new_objective = Objective.clone(old_objective)
"""
retur... | python | def clone(cls, objective, model=None, **kwargs):
"""
Make a copy of an objective. The objective being copied can be of the same type or belong to
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Example
----------
>>> new_objective = Objective.clone(old_objective)
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... | python | def to_json(self):
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biosustain/optlang | optlang/interface.py | Objective.from_json | def from_json(cls, json_obj, variables=None):
"""
Constructs an Objective from the provided json-object.
Example
--------
>>> import json
>>> with open("path_to_file.json") as infile:
>>> obj = Objective.from_json(json.load(infile))
"""
if var... | python | def from_json(cls, json_obj, variables=None):
"""
Constructs an Objective from the provided json-object.
Example
--------
>>> import json
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biosustain/optlang | optlang/interface.py | Model.clone | def clone(cls, model, use_json=True, use_lp=False):
"""
Make a copy of a model. The model being copied can be of the same type or belong to
a different solver interface. This is the preferred way of copying models.
Example
----------
>>> new_model = Model.clone(old_model... | python | def clone(cls, model, use_json=True, use_lp=False):
"""
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biosustain/optlang | optlang/interface.py | Model.add | def add(self, stuff, sloppy=False):
"""Add variables and constraints.
Parameters
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stuff : iterable, Variable, Constraint
Either an iterable containing variables and constraints or a single variable or constraint.
sloppy : bool
Check constraints... | python | def add(self, stuff, sloppy=False):
"""Add variables and constraints.
Parameters
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stuff : iterable, Variable, Constraint
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biosustain/optlang | optlang/interface.py | Model.remove | def remove(self, stuff):
"""Remove variables and constraints.
Parameters
----------
stuff : iterable, str, Variable, Constraint
Either an iterable containing variables and constraints to be removed from the model or a single variable or contstraint (or their names).
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stuff : iterable, str, Variable, Constraint
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biosustain/optlang | optlang/interface.py | Model.update | def update(self, callback=int):
"""Process all pending model modifications."""
# print(self._pending_modifications)
add_var = self._pending_modifications.add_var
if len(add_var) > 0:
self._add_variables(add_var)
self._pending_modifications.add_var = []
cal... | python | def update(self, callback=int):
"""Process all pending model modifications."""
# print(self._pending_modifications)
add_var = self._pending_modifications.add_var
if len(add_var) > 0:
self._add_variables(add_var)
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biosustain/optlang | optlang/interface.py | Model.optimize | def optimize(self):
"""
Solve the optimization problem using the relevant solver back-end.
The status returned by this method tells whether an optimal solution was found,
if the problem is infeasible etc. Consult optlang.statuses for more elaborate explanations
of each status.
... | python | def optimize(self):
"""
Solve the optimization problem using the relevant solver back-end.
The status returned by this method tells whether an optimal solution was found,
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biosustain/optlang | optlang/interface.py | Model.to_json | def to_json(self):
"""
Returns a json-compatible object from the model that can be saved using the json module.
Variables, constraints and objective contained in the model will be saved. Configurations
will not be saved.
Example
--------
>>> import json
>... | python | def to_json(self):
"""
Returns a json-compatible object from the model that can be saved using the json module.
Variables, constraints and objective contained in the model will be saved. Configurations
will not be saved.
Example
--------
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biosustain/optlang | optlang/util.py | solve_with_glpsol | def solve_with_glpsol(glp_prob):
"""Solve glpk problem with glpsol commandline solver. Mainly for testing purposes.
# Examples
# --------
# >>> problem = glp_create_prob()
# ... glp_read_lp(problem, None, "../tests/data/model.lp")
# ... solution = solve_with_glpsol(problem)
# ... print 'as... | python | def solve_with_glpsol(glp_prob):
"""Solve glpk problem with glpsol commandline solver. Mainly for testing purposes.
# Examples
# --------
# >>> problem = glp_create_prob()
# ... glp_read_lp(problem, None, "../tests/data/model.lp")
# ... solution = solve_with_glpsol(problem)
# ... print 'as... | [
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biosustain/optlang | optlang/util.py | glpk_read_cplex | def glpk_read_cplex(path):
"""Reads cplex file and returns glpk problem.
Returns
-------
glp_prob
A glpk problems (same type as returned by glp_create_prob)
"""
from swiglpk import glp_create_prob, glp_read_lp
problem = glp_create_prob()
glp_read_lp(problem, None, path)
ret... | python | def glpk_read_cplex(path):
"""Reads cplex file and returns glpk problem.
Returns
-------
glp_prob
A glpk problems (same type as returned by glp_create_prob)
"""
from swiglpk import glp_create_prob, glp_read_lp
problem = glp_create_prob()
glp_read_lp(problem, None, path)
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biosustain/optlang | optlang/util.py | expr_to_json | def expr_to_json(expr):
"""
Converts a Sympy expression to a json-compatible tree-structure.
"""
if isinstance(expr, symbolics.Mul):
return {"type": "Mul", "args": [expr_to_json(arg) for arg in expr.args]}
elif isinstance(expr, symbolics.Add):
return {"type": "Add", "args": [expr_to_... | python | def expr_to_json(expr):
"""
Converts a Sympy expression to a json-compatible tree-structure.
"""
if isinstance(expr, symbolics.Mul):
return {"type": "Mul", "args": [expr_to_json(arg) for arg in expr.args]}
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biosustain/optlang | optlang/util.py | parse_expr | def parse_expr(expr, local_dict=None):
"""
Parses a json-object created with 'expr_to_json' into a Sympy expression.
If a local_dict argument is passed, symbols with be looked up by name, and a new symbol will
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"""
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"""
Parses a json-object created with 'expr_to_json' into a Sympy expression.
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biosustain/optlang | optlang/scipy_interface.py | Problem.set_variable_bounds | def set_variable_bounds(self, name, lower, upper):
"""Set the bounds of a variable"""
self.bounds[name] = (lower, upper)
self._reset_solution() | python | def set_variable_bounds(self, name, lower, upper):
"""Set the bounds of a variable"""
self.bounds[name] = (lower, upper)
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biosustain/optlang | optlang/scipy_interface.py | Problem.add_constraint | def add_constraint(self, name, coefficients={}, ub=0):
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The constraint can only have an upper bound. To make a constraint with a lower bound, multiply
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biosustain/optlang | optlang/scipy_interface.py | Problem.remove_variable | def remove_variable(self, name):
"""Remove a variable from the problem."""
index = self._get_var_index(name)
# Remove from matrix
self._A = np.delete(self.A, index, 1)
# Remove from bounds
del self.bounds[name]
# Remove from var list
del self._variables[na... | python | def remove_variable(self, name):
"""Remove a variable from the problem."""
index = self._get_var_index(name)
# Remove from matrix
self._A = np.delete(self.A, index, 1)
# Remove from bounds
del self.bounds[name]
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biosustain/optlang | optlang/scipy_interface.py | Problem.remove_constraint | def remove_constraint(self, name):
"""Remove a constraint from the problem"""
index = self._get_constraint_index(name)
# Remove from matrix
self._A = np.delete(self.A, index, 0)
# Remove from upper_bounds
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# R... | python | def remove_constraint(self, name):
"""Remove a constraint from the problem"""
index = self._get_constraint_index(name)
# Remove from matrix
self._A = np.delete(self.A, index, 0)
# Remove from upper_bounds
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biosustain/optlang | optlang/scipy_interface.py | Problem.set_constraint_bound | def set_constraint_bound(self, name, value):
"""Set the upper bound of a constraint."""
index = self._get_constraint_index(name)
self.upper_bounds[index] = value
self._reset_solution() | python | def set_constraint_bound(self, name, value):
"""Set the upper bound of a constraint."""
index = self._get_constraint_index(name)
self.upper_bounds[index] = value
self._reset_solution() | [
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biosustain/optlang | optlang/scipy_interface.py | Problem.get_var_primal | def get_var_primal(self, name):
"""Get the primal value of a variable. Returns None if the problem has not bee optimized."""
if self._var_primals is None:
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index = self._get_var_index(name)
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"""Get the primal value of a variable. Returns None if the problem has not bee optimized."""
if self._var_primals is None:
return None
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biosustain/optlang | optlang/scipy_interface.py | Problem.get_constraint_slack | def get_constraint_slack(self, name):
"""Get the value of the slack variable of a constraint."""
if self._slacks is None:
return None
else:
index = self._get_constraint_index(name)
return self._slacks[index] | python | def get_constraint_slack(self, name):
"""Get the value of the slack variable of a constraint."""
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biosustain/optlang | optlang/scipy_interface.py | Problem.optimize | def optimize(self, method="simplex", verbosity=False, tolerance=1e-9, **kwargs):
"""Run the linprog function on the problem. Returns None."""
c = np.array([self.objective.get(name, 0) for name in self._variables])
if self.direction == "max":
c *= -1
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"""Run the linprog function on the problem. Returns None."""
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biosustain/optlang | optlang/scipy_interface.py | Problem.objective_value | def objective_value(self):
"""Returns the optimal objective value"""
if self._f is None:
raise RuntimeError("Problem has not been optimized yet")
if self.direction == "max":
return -self._f + self.offset
else:
return self._f + self.offset | python | def objective_value(self):
"""Returns the optimal objective value"""
if self._f is None:
raise RuntimeError("Problem has not been optimized yet")
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return -self._f + self.offset
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | install | def install(application, io_loop=None, **kwargs):
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | PublishingMixin.amqp_publish | def amqp_publish(self, exchange, routing_key, body, properties=None):
"""Publish a message to RabbitMQ
:param str exchange: The exchange to publish the message to
:param str routing_key: The routing key to publish the message with
:param bytes body: The message body to send
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | Client.publish | def publish(self, exchange, routing_key, body, properties=None):
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | Client.on_delivery_confirmation | def on_delivery_confirmation(self, method_frame):
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | Client.close | def close(self):
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"""
if not self.closable:
LOGGER.warning('Closed called while %s', self.state_description)
raise ConnectionStateError(self.state_description)
... | python | def close(self):
"""Cleanly shutdown the connection to RabbitMQ
:raises: sprockets.mixins.amqp.ConnectionStateError
"""
if not self.closable:
LOGGER.warning('Closed called while %s', self.state_description)
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | Client._reconnect | def _reconnect(self):
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"""
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | Client.on_connection_open | def on_connection_open(self, connection):
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:type connection: pika.TornadoConnection
"""
LOGGER.debug('Connection opened')
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"""This method is called by pika once the connection to RabbitMQ has
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:type connection: pika.TornadoConnection
"""
LOGGER.debug('Connection opened')
connection.add_on_connection_blocked_callback(
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | Client.on_connection_open_error | def on_connection_open_error(self, connection, error):
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:type connection: pika.TornadoConnection
:param Exception error: The exception indicating failure
"""
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"""Invoked if the connection to RabbitMQ can not be made.
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:param Exception error: The exception indicating failure
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | Client.on_connection_blocked | def on_connection_blocked(self, method_frame):
"""This method is called by pika if RabbitMQ sends a connection blocked
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:param pika.amqp_object.Method method_frame: The blocked method frame
"""
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"""This method is called by pika if RabbitMQ sends a connection blocked
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | Client.on_connection_closed | def on_connection_closed(self, connection, reply_code, reply_text):
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sprockets/sprockets.mixins.amqp | sprockets/mixins/amqp/__init__.py | Client.on_basic_return | def on_basic_return(self, _channel, method, properties, body):
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Factory method to create a Mail instance from a Guerrillamail response
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pmelchior/proxmin | examples/parabola.py | grad_f | def grad_f(xy):
"""Gradient of f"""
return np.array([grad_fx(xy[0],xy[1]),grad_fy(xy[0],xy[1])]) | python | def grad_f(xy):
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pmelchior/proxmin | examples/parabola.py | prox_circle | def prox_circle(xy, step):
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radius = 0.5
# exclude interior of circle
#if (dxy**2).sum() < radius**2:
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phi = np.arctan2(dxy[1], dxy[0])
return c... | python | def prox_circle(xy, step):
"""Projection onto circle"""
center = np.array([0,0])
dxy = xy - center
radius = 0.5
# exclude interior of circle
#if (dxy**2).sum() < radius**2:
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pmelchior/proxmin | examples/parabola.py | prox_xline | def prox_xline(x, step):
"""Projection onto line in x"""
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pmelchior/proxmin | examples/parabola.py | prox_yline | def prox_yline(y, step):
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pmelchior/proxmin | examples/parabola.py | prox_line | def prox_line(xy, step):
"""2D projection onto 2 lines"""
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pmelchior/proxmin | examples/parabola.py | prox_lim | def prox_lim(xy, step, boundary=None):
"""Proximal projection operator"""
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if boundary == "line":
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# default: do nothing
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"""Proximal projection operator"""
if boundary == "circle":
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if boundary == "line":
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# default: do nothing
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pmelchior/proxmin | examples/parabola.py | prox_gradf12 | def prox_gradf12(x, step, j=None, Xs=None):
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pmelchior/proxmin | examples/parabola.py | prox_gradf_lim12 | def prox_gradf_lim12(x, step, j=None, Xs=None, boundary=None):
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"""1D projection operator"""
# TODO: split boundary in x1 and x2 and use appropriate operator
if j == 0:
x -= step*grad_fx(Xs[0][0], Xs[1][0])
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pmelchior/proxmin | proxmin/algorithms.py | pgm | def pgm(X, prox_f, step_f, accelerated=False, relax=None, e_rel=1e-6, max_iter=1000, traceback=None):
"""Proximal Gradient Method
Adapted from Combettes 2009, Algorithm 3.4.
The accelerated version is Algorithm 3.6 with modifications
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X: initial X, will be update... | python | def pgm(X, prox_f, step_f, accelerated=False, relax=None, e_rel=1e-6, max_iter=1000, traceback=None):
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pmelchior/proxmin | proxmin/algorithms.py | admm | def admm(X, prox_f, step_f, prox_g=None, step_g=None, L=None, e_rel=1e-6, e_abs=0, max_iter=1000, traceback=None):
"""Alternating Direction Method of Multipliers
This method implements the linearized ADMM from Parikh & Boyd (2014).
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X: initial X will be updated
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pmelchior/proxmin | proxmin/algorithms.py | bpgm | def bpgm(X, proxs_f, steps_f_cb, update_order=None, accelerated=False, relax=None, max_iter=1000, e_rel=1e-6, traceback=None):
"""Block Proximal Gradient Method.
Also know as Alternating Proximal Gradient Method, it performs Proximal
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Also know as Alternating Proximal Gradient Method, it performs Proximal
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Args:
X: list of initial Xs, will be updated
proxs_f: proxed function f
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pmelchior/proxmin | proxmin/utils.py | get_step_f | def get_step_f(step_f, lR2, lS2):
"""Update the stepsize of given the primal and dual errors.
See Boyd (2011), section 3.4.1
"""
mu, tau = 10, 2
if lR2 > mu*lS2:
return step_f * tau
elif lS2 > mu*lR2:
return step_f / tau
return step_f | python | def get_step_f(step_f, lR2, lS2):
"""Update the stepsize of given the primal and dual errors.
See Boyd (2011), section 3.4.1
"""
mu, tau = 10, 2
if lR2 > mu*lS2:
return step_f * tau
elif lS2 > mu*lR2:
return step_f / tau
return step_f | [
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pmelchior/proxmin | proxmin/utils.py | update_variables | def update_variables(X, Z, U, prox_f, step_f, prox_g, step_g, L):
"""Update the primal and dual variables
Note: X, Z, U are updated inline
Returns: LX, R, S
"""
if not hasattr(prox_g, '__iter__'):
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dX = step_f/step_g * L.T.dot(L.dot(X) - Z + U)
... | python | def update_variables(X, Z, U, prox_f, step_f, prox_g, step_g, L):
"""Update the primal and dual variables
Note: X, Z, U are updated inline
Returns: LX, R, S
"""
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pmelchior/proxmin | proxmin/utils.py | get_variable_errors | def get_variable_errors(X, L, LX, Z, U, step_g, e_rel, e_abs=0):
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For a given linear operator A, (and its dot product with X to save time),
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"""Get the errors in a single multiplier method step
For a given linear operator A, (and its dot product with X to save time),
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pmelchior/proxmin | proxmin/utils.py | check_constraint_convergence | def check_constraint_convergence(X, L, LX, Z, U, R, S, step_f, step_g, e_rel, e_abs):
"""Calculate if all constraints have converged.
Using the stopping criteria from Boyd 2011, Sec 3.3.1, calculate whether the
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"""
if isinstance(L, list):
M = l... | python | def check_constraint_convergence(X, L, LX, Z, U, R, S, step_f, step_g, e_rel, e_abs):
"""Calculate if all constraints have converged.
Using the stopping criteria from Boyd 2011, Sec 3.3.1, calculate whether the
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pmelchior/proxmin | proxmin/utils.py | check_convergence | def check_convergence(newX, oldX, e_rel):
"""Check that the algorithm converges using Langville 2014 criteria
Uses the check from Langville 2014, Section 5, to check if the NMF
algorithm has converged.
"""
# Calculate the norm for columns and rows, which can be used for debugging
# Otherwise sk... | python | def check_convergence(newX, oldX, e_rel):
"""Check that the algorithm converges using Langville 2014 criteria
Uses the check from Langville 2014, Section 5, to check if the NMF
algorithm has converged.
"""
# Calculate the norm for columns and rows, which can be used for debugging
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pmelchior/proxmin | proxmin/utils.py | Traceback._store_variable | def _store_variable(self, j, key, m, value):
"""Store a copy of the variable in the history
"""
if hasattr(value, 'copy'):
v = value.copy()
else:
v = value
self.history[j][key][m].append(v) | python | def _store_variable(self, j, key, m, value):
"""Store a copy of the variable in the history
"""
if hasattr(value, 'copy'):
v = value.copy()
else:
v = value
self.history[j][key][m].append(v) | [
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pmelchior/proxmin | proxmin/utils.py | Traceback.update_history | def update_history(self, it, j=0, M=None, **kwargs):
"""Add the current state for all kwargs to the history
"""
# Create a new entry in the history for new variables (if they don't exist)
if not np.any([k in self.history[j] for k in kwargs]):
for k in kwargs:
... | python | def update_history(self, it, j=0, M=None, **kwargs):
"""Add the current state for all kwargs to the history
"""
# Create a new entry in the history for new variables (if they don't exist)
if not np.any([k in self.history[j] for k in kwargs]):
for k in kwargs:
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pmelchior/proxmin | examples/unmixing.py | generateComponent | def generateComponent(m):
"""Creates oscillating components to be mixed"""
freq = 25*np.random.random()
phase = 2*np.pi*np.random.random()
x = np.arange(m)
return np.cos(x/freq-phase)**2 | python | def generateComponent(m):
"""Creates oscillating components to be mixed"""
freq = 25*np.random.random()
phase = 2*np.pi*np.random.random()
x = np.arange(m)
return np.cos(x/freq-phase)**2 | [
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pmelchior/proxmin | examples/unmixing.py | generateAmplitudes | def generateAmplitudes(k):
"""Makes mixing coefficients"""
res = np.array([np.random.random() for i in range(k)])
return res/res.sum() | python | def generateAmplitudes(k):
"""Makes mixing coefficients"""
res = np.array([np.random.random() for i in range(k)])
return res/res.sum() | [
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pmelchior/proxmin | examples/unmixing.py | add_noise | def add_noise(Y, sigma):
"""Adds noise to Y"""
return Y + np.random.normal(0, sigma, Y.shape) | python | def add_noise(Y, sigma):
"""Adds noise to Y"""
return Y + np.random.normal(0, sigma, Y.shape) | [
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pmelchior/proxmin | proxmin/nmf.py | nmf | def nmf(Y, A, S, W=None, prox_A=operators.prox_plus, prox_S=operators.prox_plus, proxs_g=None, steps_g=None, Ls=None, slack=0.9, update_order=None, steps_g_update='steps_f', max_iter=1000, e_rel=1e-3, e_abs=0, traceback=None):
"""Non-negative matrix factorization.
This method solves the NMF problem
min... | python | def nmf(Y, A, S, W=None, prox_A=operators.prox_plus, prox_S=operators.prox_plus, proxs_g=None, steps_g=None, Ls=None, slack=0.9, update_order=None, steps_g_update='steps_f', max_iter=1000, e_rel=1e-3, e_abs=0, traceback=None):
"""Non-negative matrix factorization.
This method solves the NMF problem
min... | [
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pmelchior/proxmin | proxmin/operators.py | prox_zero | def prox_zero(X, step):
"""Proximal operator to project onto zero
"""
return np.zeros(X.shape, dtype=X.dtype) | python | def prox_zero(X, step):
"""Proximal operator to project onto zero
"""
return np.zeros(X.shape, dtype=X.dtype) | [
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pmelchior/proxmin | proxmin/operators.py | prox_unity | def prox_unity(X, step, axis=0):
"""Projection onto sum=1 along an axis
"""
return X / np.sum(X, axis=axis, keepdims=True) | python | def prox_unity(X, step, axis=0):
"""Projection onto sum=1 along an axis
"""
return X / np.sum(X, axis=axis, keepdims=True) | [
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