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noxdafox/clipspy | clips/classes.py | MessageHandler.undefine | def undefine(self):
"""Undefine the MessageHandler.
Python equivalent of the CLIPS undefmessage-handler command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndefmessageHandler(self._env, self._cls, self._idx) != 1:
raise CLIPSError... | python | def undefine(self):
"""Undefine the MessageHandler.
Python equivalent of the CLIPS undefmessage-handler command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndefmessageHandler(self._env, self._cls, self._idx) != 1:
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noxdafox/clipspy | clips/environment.py | Environment.load | def load(self, path):
"""Load a set of constructs into the CLIPS data base.
Constructs can be in text or binary format.
The Python equivalent of the CLIPS load command.
"""
try:
self._load_binary(path)
except CLIPSError:
self._load_text(path) | python | def load(self, path):
"""Load a set of constructs into the CLIPS data base.
Constructs can be in text or binary format.
The Python equivalent of the CLIPS load command.
"""
try:
self._load_binary(path)
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noxdafox/clipspy | clips/environment.py | Environment.save | def save(self, path, binary=False):
"""Save a set of constructs into the CLIPS data base.
If binary is True, the constructs will be saved in binary format.
The Python equivalent of the CLIPS load command.
"""
if binary:
ret = lib.EnvBsave(self._env, path.encode())
... | python | def save(self, path, binary=False):
"""Save a set of constructs into the CLIPS data base.
If binary is True, the constructs will be saved in binary format.
The Python equivalent of the CLIPS load command.
"""
if binary:
ret = lib.EnvBsave(self._env, path.encode())
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noxdafox/clipspy | clips/environment.py | Environment.batch_star | def batch_star(self, path):
"""Evaluate the commands contained in the specific path.
The Python equivalent of the CLIPS batch* command.
"""
if lib.EnvBatchStar(self._env, path.encode()) != 1:
raise CLIPSError(self._env) | python | def batch_star(self, path):
"""Evaluate the commands contained in the specific path.
The Python equivalent of the CLIPS batch* command.
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noxdafox/clipspy | clips/environment.py | Environment.build | def build(self, construct):
"""Build a single construct in CLIPS.
The Python equivalent of the CLIPS build command.
"""
if lib.EnvBuild(self._env, construct.encode()) != 1:
raise CLIPSError(self._env) | python | def build(self, construct):
"""Build a single construct in CLIPS.
The Python equivalent of the CLIPS build command.
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if lib.EnvBuild(self._env, construct.encode()) != 1:
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noxdafox/clipspy | clips/environment.py | Environment.eval | def eval(self, construct):
"""Evaluate an expression returning its value.
The Python equivalent of the CLIPS eval command.
"""
data = clips.data.DataObject(self._env)
if lib.EnvEval(self._env, construct.encode(), data.byref) != 1:
raise CLIPSError(self._env)
... | python | def eval(self, construct):
"""Evaluate an expression returning its value.
The Python equivalent of the CLIPS eval command.
"""
data = clips.data.DataObject(self._env)
if lib.EnvEval(self._env, construct.encode(), data.byref) != 1:
raise CLIPSError(self._env)
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noxdafox/clipspy | clips/environment.py | Environment.define_function | def define_function(self, function, name=None):
"""Define the Python function within the CLIPS environment.
If a name is given, it will be the function name within CLIPS.
Otherwise, the name of the Python function will be used.
The Python function will be accessible within CLIPS via it... | python | def define_function(self, function, name=None):
"""Define the Python function within the CLIPS environment.
If a name is given, it will be the function name within CLIPS.
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noxdafox/clipspy | clips/router.py | Router.activate | def activate(self):
"""Activate the Router."""
if lib.EnvActivateRouter(self._env, self._name.encode()) == 0:
raise RuntimeError("Unable to activate router %s" % self._name) | python | def activate(self):
"""Activate the Router."""
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noxdafox/clipspy | clips/router.py | Router.deactivate | def deactivate(self):
"""Deactivate the Router."""
if lib.EnvDeactivateRouter(self._env, self._name.encode()) == 0:
raise RuntimeError("Unable to deactivate router %s" % self._name) | python | def deactivate(self):
"""Deactivate the Router."""
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noxdafox/clipspy | clips/router.py | Router.delete | def delete(self):
"""Delete the Router."""
if lib.EnvDeleteRouter(self._env, self._name.encode()) == 0:
raise RuntimeError("Unable to delete router %s" % self._name) | python | def delete(self):
"""Delete the Router."""
if lib.EnvDeleteRouter(self._env, self._name.encode()) == 0:
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noxdafox/clipspy | clips/router.py | Router.add_to_environment | def add_to_environment(self, environment):
"""Add the router to the given environment."""
self._env = environment._env
self._userdata = ffi.new_handle(self)
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noxdafox/clipspy | clips/data.py | DataObject.value | def value(self):
"""Return the DATA_OBJECT stored value."""
dtype = lib.get_data_type(self._data)
dvalue = lib.get_data_value(self._data)
if dvalue == ffi.NULL:
return None
return self.python_value(dtype, dvalue) | python | def value(self):
"""Return the DATA_OBJECT stored value."""
dtype = lib.get_data_type(self._data)
dvalue = lib.get_data_value(self._data)
if dvalue == ffi.NULL:
return None
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noxdafox/clipspy | clips/data.py | DataObject.value | def value(self, value):
"""Sets the DATA_OBJECT stored value."""
dtype = TYPES[type(value)] if self._type is None else self._type
lib.set_data_type(self._data, dtype)
lib.set_data_value(self._data, self.clips_value(value)) | python | def value(self, value):
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noxdafox/clipspy | clips/data.py | DataObject.python_value | def python_value(self, dtype, dvalue):
"""Convert a CLIPS type into Python."""
try:
return CONVERTERS[dtype](dvalue)
except KeyError:
if dtype == clips.common.CLIPSType.MULTIFIELD:
return self.multifield_to_list()
if dtype == clips.common.CLIPS... | python | def python_value(self, dtype, dvalue):
"""Convert a CLIPS type into Python."""
try:
return CONVERTERS[dtype](dvalue)
except KeyError:
if dtype == clips.common.CLIPSType.MULTIFIELD:
return self.multifield_to_list()
if dtype == clips.common.CLIPS... | [
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noxdafox/clipspy | clips/data.py | DataObject.clips_value | def clips_value(self, dvalue):
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noxdafox/clipspy | clips/agenda.py | Agenda.agenda_changed | def agenda_changed(self):
"""True if any rule activation changes have occurred."""
value = bool(lib.EnvGetAgendaChanged(self._env))
lib.EnvSetAgendaChanged(self._env, int(False))
return value | python | def agenda_changed(self):
"""True if any rule activation changes have occurred."""
value = bool(lib.EnvGetAgendaChanged(self._env))
lib.EnvSetAgendaChanged(self._env, int(False))
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noxdafox/clipspy | clips/agenda.py | Agenda.rules | def rules(self):
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rule = lib.EnvGetNextDefrule(self._env, ffi.NULL)
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yield Rule(self._env, rule)
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noxdafox/clipspy | clips/agenda.py | Agenda.find_rule | def find_rule(self, rule):
"""Find a Rule by name."""
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noxdafox/clipspy | clips/agenda.py | Agenda.reorder | def reorder(self, module=None):
"""Reorder the Activations in the Agenda.
If no Module is specified, the current one is used.
To be called after changing the conflict resolution strategy.
"""
module = module._mdl if module is not None else ffi.NULL
lib.EnvReorderAgend... | python | def reorder(self, module=None):
"""Reorder the Activations in the Agenda.
If no Module is specified, the current one is used.
To be called after changing the conflict resolution strategy.
"""
module = module._mdl if module is not None else ffi.NULL
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noxdafox/clipspy | clips/agenda.py | Agenda.refresh | def refresh(self, module=None):
"""Recompute the salience values of the Activations on the Agenda
and then reorder the agenda.
The Python equivalent of the CLIPS refresh-agenda command.
If no Module is specified, the current one is used.
"""
module = module._mdl if modu... | python | def refresh(self, module=None):
"""Recompute the salience values of the Activations on the Agenda
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The Python equivalent of the CLIPS refresh-agenda command.
If no Module is specified, the current one is used.
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noxdafox/clipspy | clips/agenda.py | Agenda.activations | def activations(self):
"""Iterate over the Activations in the Agenda."""
activation = lib.EnvGetNextActivation(self._env, ffi.NULL)
while activation != ffi.NULL:
yield Activation(self._env, activation)
activation = lib.EnvGetNextActivation(self._env, activation) | python | def activations(self):
"""Iterate over the Activations in the Agenda."""
activation = lib.EnvGetNextActivation(self._env, ffi.NULL)
while activation != ffi.NULL:
yield Activation(self._env, activation)
activation = lib.EnvGetNextActivation(self._env, activation) | [
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noxdafox/clipspy | clips/agenda.py | Agenda.clear | def clear(self):
"""Deletes all activations in the agenda."""
if lib.EnvDeleteActivation(self._env, ffi.NULL) != 1:
raise CLIPSError(self._env) | python | def clear(self):
"""Deletes all activations in the agenda."""
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noxdafox/clipspy | clips/agenda.py | Rule.name | def name(self):
"""Rule name."""
return ffi.string(lib.EnvGetDefruleName(self._env, self._rule)).decode() | python | def name(self):
"""Rule name."""
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noxdafox/clipspy | clips/agenda.py | Rule.module | def module(self):
"""The module in which the Rule is defined.
Python equivalent of the CLIPS defrule-module command.
"""
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return Module(self._env, defm... | python | def module(self):
"""The module in which the Rule is defined.
Python equivalent of the CLIPS defrule-module command.
"""
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noxdafox/clipspy | clips/agenda.py | Rule.watch_firings | def watch_firings(self, flag):
"""Whether or not the Rule firings are being watched."""
lib.EnvSetDefruleWatchFirings(self._env, int(flag), self._rule) | python | def watch_firings(self, flag):
"""Whether or not the Rule firings are being watched."""
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noxdafox/clipspy | clips/agenda.py | Rule.watch_activations | def watch_activations(self, flag):
"""Whether or not the Rule Activations are being watched."""
lib.EnvSetDefruleWatchActivations(self._env, int(flag), self._rule) | python | def watch_activations(self, flag):
"""Whether or not the Rule Activations are being watched."""
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noxdafox/clipspy | clips/agenda.py | Rule.matches | def matches(self, verbosity=Verbosity.TERSE):
"""Shows partial matches and activations.
Returns a tuple containing the combined sum of the matches
for each pattern, the combined sum of partial matches
and the number of activations.
The verbosity parameter controls how much to o... | python | def matches(self, verbosity=Verbosity.TERSE):
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Returns a tuple containing the combined sum of the matches
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noxdafox/clipspy | clips/agenda.py | Rule.refresh | def refresh(self):
"""Refresh the Rule.
The Python equivalent of the CLIPS refresh command.
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"""Refresh the Rule.
The Python equivalent of the CLIPS refresh command.
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noxdafox/clipspy | clips/agenda.py | Rule.undefine | def undefine(self):
"""Undefine the Rule.
Python equivalent of the CLIPS undefrule command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndefrule(self._env, self._rule) != 1:
raise CLIPSError(self._env)
self._env = None | python | def undefine(self):
"""Undefine the Rule.
Python equivalent of the CLIPS undefrule command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndefrule(self._env, self._rule) != 1:
raise CLIPSError(self._env)
self._env = None | [
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noxdafox/clipspy | clips/agenda.py | Activation.name | def name(self):
"""Activation Rule name."""
return ffi.string(
lib.EnvGetActivationName(self._env, self._act)).decode() | python | def name(self):
"""Activation Rule name."""
return ffi.string(
lib.EnvGetActivationName(self._env, self._act)).decode() | [
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noxdafox/clipspy | clips/agenda.py | Activation.salience | def salience(self, salience):
"""Activation salience value."""
lib.EnvSetActivationSalience(self._env, self._act, salience) | python | def salience(self, salience):
"""Activation salience value."""
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noxdafox/clipspy | clips/agenda.py | Activation.delete | def delete(self):
"""Remove the activation from the agenda."""
if lib.EnvDeleteActivation(self._env, self._act) != 1:
raise CLIPSError(self._env)
self._env = None | python | def delete(self):
"""Remove the activation from the agenda."""
if lib.EnvDeleteActivation(self._env, self._act) != 1:
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self._env = None | [
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noxdafox/clipspy | clips/modules.py | Modules.globals_changed | def globals_changed(self):
"""True if any Global has changed."""
value = bool(lib.EnvGetGlobalsChanged(self._env))
lib.EnvSetGlobalsChanged(self._env, int(False))
return value | python | def globals_changed(self):
"""True if any Global has changed."""
value = bool(lib.EnvGetGlobalsChanged(self._env))
lib.EnvSetGlobalsChanged(self._env, int(False))
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noxdafox/clipspy | clips/modules.py | Modules.globals | def globals(self):
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while defglobal != ffi.NULL:
yield Global(self._env, defglobal)
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"""Iterates over the defined Globals."""
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noxdafox/clipspy | clips/modules.py | Modules.find_global | def find_global(self, name):
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"""Find the Global by its name."""
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noxdafox/clipspy | clips/modules.py | Modules.modules | def modules(self):
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noxdafox/clipspy | clips/modules.py | Modules.find_module | def find_module(self, name):
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noxdafox/clipspy | clips/modules.py | Global.value | def value(self):
"""Global value."""
data = clips.data.DataObject(self._env)
if lib.EnvGetDefglobalValue(
self._env, self.name.encode(), data.byref) != 1:
raise CLIPSError(self._env)
return data.value | python | def value(self):
"""Global value."""
data = clips.data.DataObject(self._env)
if lib.EnvGetDefglobalValue(
self._env, self.name.encode(), data.byref) != 1:
raise CLIPSError(self._env)
return data.value | [
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noxdafox/clipspy | clips/modules.py | Global.module | def module(self):
"""The module in which the Global is defined.
Python equivalent of the CLIPS defglobal-module command.
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"""The module in which the Global is defined.
Python equivalent of the CLIPS defglobal-module command.
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modname = ffi.string(lib.EnvDefglobalModule(self._env, self._glb))
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noxdafox/clipspy | clips/modules.py | Global.watch | def watch(self, flag):
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lib.EnvSetDefglobalWatch(self._env, int(flag), self._glb) | python | def watch(self, flag):
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noxdafox/clipspy | clips/modules.py | Global.undefine | def undefine(self):
"""Undefine the Global.
Python equivalent of the CLIPS undefglobal command.
The object becomes unusable after this method has been called.
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if lib.EnvUndefglobal(self._env, self._glb) != 1:
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"""Undefine the Global.
Python equivalent of the CLIPS undefglobal command.
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noxdafox/clipspy | clips/modules.py | Module.name | def name(self):
"""Global name."""
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lib.EnvGetDefmoduleName(self._env, self._mdl)).decode() | python | def name(self):
"""Global name."""
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noxdafox/clipspy | clips/functions.py | Functions.functions | def functions(self):
"""Iterates over the defined Globals."""
deffunction = lib.EnvGetNextDeffunction(self._env, ffi.NULL)
while deffunction != ffi.NULL:
yield Function(self._env, deffunction)
deffunction = lib.EnvGetNextDeffunction(self._env, deffunction) | python | def functions(self):
"""Iterates over the defined Globals."""
deffunction = lib.EnvGetNextDeffunction(self._env, ffi.NULL)
while deffunction != ffi.NULL:
yield Function(self._env, deffunction)
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noxdafox/clipspy | clips/functions.py | Functions.find_function | def find_function(self, name):
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noxdafox/clipspy | clips/functions.py | Functions.generics | def generics(self):
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"""Iterates over the defined Generics."""
defgeneric = lib.EnvGetNextDefgeneric(self._env, ffi.NULL)
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noxdafox/clipspy | clips/functions.py | Functions.find_generic | def find_generic(self, name):
"""Find the Generic by its name."""
defgeneric = lib.EnvFindDefgeneric(self._env, name.encode())
if defgeneric == ffi.NULL:
raise LookupError("Generic '%s' not found" % name)
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"""Find the Generic by its name."""
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noxdafox/clipspy | clips/functions.py | Function.name | def name(self):
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noxdafox/clipspy | clips/functions.py | Function.module | def module(self):
"""The module in which the Function is defined.
Python equivalent of the CLIPS deffunction-module command.
"""
modname = ffi.string(lib.EnvDeffunctionModule(self._env, self._fnc))
defmodule = lib.EnvFindDefmodule(self._env, modname)
return Module(self... | python | def module(self):
"""The module in which the Function is defined.
Python equivalent of the CLIPS deffunction-module command.
"""
modname = ffi.string(lib.EnvDeffunctionModule(self._env, self._fnc))
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noxdafox/clipspy | clips/functions.py | Function.watch | def watch(self, flag):
"""Whether or not the Function is being watched."""
lib.EnvSetDeffunctionWatch(self._env, int(flag), self._fnc) | python | def watch(self, flag):
"""Whether or not the Function is being watched."""
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noxdafox/clipspy | clips/functions.py | Function.undefine | def undefine(self):
"""Undefine the Function.
Python equivalent of the CLIPS undeffunction command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndeffunction(self._env, self._fnc) != 1:
raise CLIPSError(self._env)
self._env... | python | def undefine(self):
"""Undefine the Function.
Python equivalent of the CLIPS undeffunction command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndeffunction(self._env, self._fnc) != 1:
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noxdafox/clipspy | clips/functions.py | Generic.undefine | def undefine(self):
"""Undefine the Generic.
Python equivalent of the CLIPS undefgeneric command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndefgeneric(self._env, self._gnc) != 1:
raise CLIPSError(self._env)
self._env = ... | python | def undefine(self):
"""Undefine the Generic.
Python equivalent of the CLIPS undefgeneric command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndefgeneric(self._env, self._gnc) != 1:
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noxdafox/clipspy | clips/functions.py | Method.undefine | def undefine(self):
"""Undefine the Method.
Python equivalent of the CLIPS undefmethod command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndefmethod(self._env, self._gnc, self._idx) != 1:
raise CLIPSError(self._env)
self... | python | def undefine(self):
"""Undefine the Method.
Python equivalent of the CLIPS undefmethod command.
The object becomes unusable after this method has been called.
"""
if lib.EnvUndefmethod(self._env, self._gnc, self._idx) != 1:
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mouradmourafiq/pandas-summary | pandas_summary/__init__.py | DataFrameSummary._get_deviation_of_mean | def _get_deviation_of_mean(self, series, multiplier=3):
"""
Returns count of values deviating of the mean, i.e. larger than `multiplier` * `std`.
:type series:
:param multiplier:
:return:
"""
capped_series = np.minimum(
series, series.mean() + multipli... | python | def _get_deviation_of_mean(self, series, multiplier=3):
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mouradmourafiq/pandas-summary | pandas_summary/__init__.py | DataFrameSummary._get_median_absolute_deviation | def _get_median_absolute_deviation(self, series, multiplier=3):
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Returns count of values larger than `multiplier` * `mad`
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mouradmourafiq/pandas-summary | pandas_summary/__init__.py | DataFrameSummary.get_columns | def get_columns(self, df, usage, columns=None):
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"""
Returns a `data_frame.columns`.
:param df: dataframe to select columns from
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taborlab/FlowCal | FlowCal/mef.py | clustering_gmm | def clustering_gmm(data,
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tol=1e-7,
min_covar=None,
scale='logicle'):
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Find clusters in an array using a Gaussian Mixture Model.
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n_clusters,
tol=1e-7,
min_covar=None,
scale='logicle'):
"""
Find clusters in an array using a Gaussian Mixture Model.
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taborlab/FlowCal | FlowCal/mef.py | fit_beads_autofluorescence | def fit_beads_autofluorescence(fl_rfi, fl_mef):
"""
Fit a standard curve using a beads model with autofluorescence.
Parameters
----------
fl_rfi : array
Fluorescence values of bead populations in units of Relative
Fluorescence Intensity (RFI).
fl_mef : array
Fluorescence... | python | def fit_beads_autofluorescence(fl_rfi, fl_mef):
"""
Fit a standard curve using a beads model with autofluorescence.
Parameters
----------
fl_rfi : array
Fluorescence values of bead populations in units of Relative
Fluorescence Intensity (RFI).
fl_mef : array
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taborlab/FlowCal | FlowCal/mef.py | plot_standard_curve | def plot_standard_curve(fl_rfi,
fl_mef,
beads_model,
std_crv,
xscale='linear',
yscale='linear',
xlim=None,
ylim=(1.,1e8)):
"""
Plot a standard c... | python | def plot_standard_curve(fl_rfi,
fl_mef,
beads_model,
std_crv,
xscale='linear',
yscale='linear',
xlim=None,
ylim=(1.,1e8)):
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taborlab/FlowCal | FlowCal/mef.py | get_transform_fxn | def get_transform_fxn(data_beads,
mef_values,
mef_channels,
clustering_fxn=clustering_gmm,
clustering_params={},
clustering_channels=None,
statistic_fxn=FlowCal.stats.median,
... | python | def get_transform_fxn(data_beads,
mef_values,
mef_channels,
clustering_fxn=clustering_gmm,
clustering_params={},
clustering_channels=None,
statistic_fxn=FlowCal.stats.median,
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taborlab/FlowCal | FlowCal/excel_ui.py | read_table | def read_table(filename, sheetname, index_col=None):
"""
Return the contents of an Excel table as a pandas DataFrame.
Parameters
----------
filename : str
Name of the Excel file to read.
sheetname : str or int
Name or index of the sheet inside the Excel file to read.
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"""
Return the contents of an Excel table as a pandas DataFrame.
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filename : str
Name of the Excel file to read.
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taborlab/FlowCal | FlowCal/excel_ui.py | write_workbook | def write_workbook(filename, table_list, column_width=None):
"""
Write an Excel workbook from a list of tables.
Parameters
----------
filename : str
Name of the Excel file to write.
table_list : list of ``(str, DataFrame)`` tuples
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"""
Write an Excel workbook from a list of tables.
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----------
filename : str
Name of the Excel file to write.
table_list : list of ``(str, DataFrame)`` tuples
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taborlab/FlowCal | FlowCal/excel_ui.py | process_beads_table | def process_beads_table(beads_table,
instruments_table,
base_dir=".",
verbose=False,
plot=False,
plot_dir=None,
full_output=False,
get_transform_fxn_kwa... | python | def process_beads_table(beads_table,
instruments_table,
base_dir=".",
verbose=False,
plot=False,
plot_dir=None,
full_output=False,
get_transform_fxn_kwa... | [
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taborlab/FlowCal | FlowCal/excel_ui.py | process_samples_table | def process_samples_table(samples_table,
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beads_table=None,
base_dir=".",
verbose=False,
plot=False,
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beads_table=None,
base_dir=".",
verbose=False,
plot=False,
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taborlab/FlowCal | FlowCal/excel_ui.py | add_beads_stats | def add_beads_stats(beads_table, beads_samples, mef_outputs=None):
"""
Add stats fields to beads table.
The following information is added to each row:
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- Number of Events
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Add stats fields to beads table.
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- Notes (warnings, errors) resulting from the analysis
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taborlab/FlowCal | FlowCal/excel_ui.py | add_samples_stats | def add_samples_stats(samples_table, samples):
"""
Add stats fields to samples table.
The following information is added to each row:
- Notes (warnings, errors) resulting from the analysis
- Number of Events
- Acquisition Time (s)
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taborlab/FlowCal | FlowCal/excel_ui.py | generate_histograms_table | def generate_histograms_table(samples_table, samples, max_bins=1024):
"""
Generate a table of histograms as a DataFrame.
Parameters
----------
samples_table : DataFrame
Table specifying samples to analyze. For more information about the
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"""
Generate a table of histograms as a DataFrame.
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taborlab/FlowCal | FlowCal/excel_ui.py | generate_about_table | def generate_about_table(extra_info={}):
"""
Make a table with information about FlowCal and the current analysis.
Parameters
----------
extra_info : dict, optional
Additional keyword:value pairs to include in the table.
Returns
-------
about_table : DataFrame
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"""
Make a table with information about FlowCal and the current analysis.
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extra_info : dict, optional
Additional keyword:value pairs to include in the table.
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taborlab/FlowCal | FlowCal/excel_ui.py | show_open_file_dialog | def show_open_file_dialog(filetypes):
"""
Show an open file dialog and return the path of the file selected.
Parameters
----------
filetypes : list of tuples
Types of file to show on the dialog. Each tuple on the list must
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Show an open file dialog and return the path of the file selected.
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taborlab/FlowCal | FlowCal/excel_ui.py | run | def run(input_path=None,
output_path=None,
verbose=True,
plot=True,
hist_sheet=False):
"""
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... | Run the MS Excel User Interface.
This function performs the following:
1. If `input_path` is not specified, show a dialog to choose an input
Excel file.
2. Extract data from the Instruments, Beads, and Samples tables.
3. Process all the bead samples specified in the Beads table.
4. Gen... | [
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taborlab/FlowCal | FlowCal/excel_ui.py | run_command_line | def run_command_line(args=None):
"""
Entry point for the FlowCal and flowcal console scripts.
Parameters
----------
args: list of strings, optional
Command line arguments. If None or not specified, get arguments
from ``sys.argv``.
See Also
----------
FlowCal.excel_ui.ru... | python | def run_command_line(args=None):
"""
Entry point for the FlowCal and flowcal console scripts.
Parameters
----------
args: list of strings, optional
Command line arguments. If None or not specified, get arguments
from ``sys.argv``.
See Also
----------
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Command line arguments. If None or not specified, get arguments
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taborlab/FlowCal | FlowCal/io.py | read_fcs_header_segment | def read_fcs_header_segment(buf, begin=0):
"""
Read HEADER segment of FCS file.
Parameters
----------
buf : file-like object
Buffer containing data to interpret as HEADER segment.
begin : int
Offset (in bytes) to first byte of HEADER segment in `buf`.
Returns
-------
... | python | def read_fcs_header_segment(buf, begin=0):
"""
Read HEADER segment of FCS file.
Parameters
----------
buf : file-like object
Buffer containing data to interpret as HEADER segment.
begin : int
Offset (in bytes) to first byte of HEADER segment in `buf`.
Returns
-------
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taborlab/FlowCal | FlowCal/io.py | read_fcs_text_segment | def read_fcs_text_segment(buf, begin, end, delim=None, supplemental=False):
"""
Read TEXT segment of FCS file.
Parameters
----------
buf : file-like object
Buffer containing data to interpret as TEXT segment.
begin : int
Offset (in bytes) to first byte of TEXT segment in `buf`.
... | python | def read_fcs_text_segment(buf, begin, end, delim=None, supplemental=False):
"""
Read TEXT segment of FCS file.
Parameters
----------
buf : file-like object
Buffer containing data to interpret as TEXT segment.
begin : int
Offset (in bytes) to first byte of TEXT segment in `buf`.
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taborlab/FlowCal | FlowCal/io.py | read_fcs_data_segment | def read_fcs_data_segment(buf,
begin,
end,
datatype,
num_events,
param_bit_widths,
big_endian,
param_ranges=None):
"""
Read DATA s... | python | def read_fcs_data_segment(buf,
begin,
end,
datatype,
num_events,
param_bit_widths,
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param_ranges=None):
"""
Read DATA s... | [
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taborlab/FlowCal | FlowCal/io.py | FCSData.acquisition_time | def acquisition_time(self):
"""
Acquisition time, in seconds.
The acquisition time is calculated using the 'time' channel by
default (channel name is case independent). If the 'time' channel
is not available, the acquisition_start_time and
acquisition_end_time, extracted... | python | def acquisition_time(self):
"""
Acquisition time, in seconds.
The acquisition time is calculated using the 'time' channel by
default (channel name is case independent). If the 'time' channel
is not available, the acquisition_start_time and
acquisition_end_time, extracted... | [
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taborlab/FlowCal | FlowCal/io.py | FCSData.amplification_type | def amplification_type(self, channels=None):
"""
Get the amplification type used for the specified channel(s).
Each channel uses one of two amplification types: linear or
logarithmic. This function returns, for each channel, a tuple of
two numbers, in which the first number indi... | python | def amplification_type(self, channels=None):
"""
Get the amplification type used for the specified channel(s).
Each channel uses one of two amplification types: linear or
logarithmic. This function returns, for each channel, a tuple of
two numbers, in which the first number indi... | [
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taborlab/FlowCal | FlowCal/io.py | FCSData.detector_voltage | def detector_voltage(self, channels=None):
"""
Get the detector voltage used for the specified channel(s).
The detector voltage for channel "n" is extracted from the $PnV
parameter, if available.
Parameters
----------
channels : int, str, list of int, list of st... | python | def detector_voltage(self, channels=None):
"""
Get the detector voltage used for the specified channel(s).
The detector voltage for channel "n" is extracted from the $PnV
parameter, if available.
Parameters
----------
channels : int, str, list of int, list of st... | [
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taborlab/FlowCal | FlowCal/io.py | FCSData.amplifier_gain | def amplifier_gain(self, channels=None):
"""
Get the amplifier gain used for the specified channel(s).
The amplifier gain for channel "n" is extracted from the $PnG
parameter, if available.
Parameters
----------
channels : int, str, list of int, list of str
... | python | def amplifier_gain(self, channels=None):
"""
Get the amplifier gain used for the specified channel(s).
The amplifier gain for channel "n" is extracted from the $PnG
parameter, if available.
Parameters
----------
channels : int, str, list of int, list of str
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taborlab/FlowCal | FlowCal/io.py | FCSData.range | def range(self, channels=None):
"""
Get the range of the specified channel(s).
The range is a two-element list specifying the smallest and largest
values that an event in a channel should have. Note that with
floating point data, some events could have values outside the
... | python | def range(self, channels=None):
"""
Get the range of the specified channel(s).
The range is a two-element list specifying the smallest and largest
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taborlab/FlowCal | FlowCal/io.py | FCSData.resolution | def resolution(self, channels=None):
"""
Get the resolution of the specified channel(s).
The resolution specifies the number of different values that the
events can take. The resolution is directly obtained from the $PnR
parameter.
Parameters
----------
... | python | def resolution(self, channels=None):
"""
Get the resolution of the specified channel(s).
The resolution specifies the number of different values that the
events can take. The resolution is directly obtained from the $PnR
parameter.
Parameters
----------
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taborlab/FlowCal | FlowCal/io.py | FCSData.hist_bins | def hist_bins(self, channels=None, nbins=None, scale='logicle', **kwargs):
"""
Get histogram bin edges for the specified channel(s).
These cover the range specified in ``FCSData.range(channels)`` with
a number of bins `nbins`, with linear, logarithmic, or logicle
spacing.
... | python | def hist_bins(self, channels=None, nbins=None, scale='logicle', **kwargs):
"""
Get histogram bin edges for the specified channel(s).
These cover the range specified in ``FCSData.range(channels)`` with
a number of bins `nbins`, with linear, logarithmic, or logicle
spacing.
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taborlab/FlowCal | FlowCal/io.py | FCSData._parse_time_string | def _parse_time_string(time_str):
"""
Get a datetime.time object from a string time representation.
The start and end of acquisition are stored in the optional keyword
parameters $BTIM and $ETIM. The following formats are used
according to the FCS standard:
- FCS 2.0... | python | def _parse_time_string(time_str):
"""
Get a datetime.time object from a string time representation.
The start and end of acquisition are stored in the optional keyword
parameters $BTIM and $ETIM. The following formats are used
according to the FCS standard:
- FCS 2.0... | [
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taborlab/FlowCal | FlowCal/io.py | FCSData._parse_date_string | def _parse_date_string(date_str):
"""
Get a datetime.date object from a string date representation.
The FCS standard includes an optional keyword parameter $DATE in
which the acquistion date is stored. In FCS 2.0, the date is saved
as 'dd-mmm-yy', whereas in FCS 3.0 and 3.1 the ... | python | def _parse_date_string(date_str):
"""
Get a datetime.date object from a string date representation.
The FCS standard includes an optional keyword parameter $DATE in
which the acquistion date is stored. In FCS 2.0, the date is saved
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taborlab/FlowCal | FlowCal/io.py | FCSData._name_to_index | def _name_to_index(self, channels):
"""
Return the channel indices for the specified channel names.
Integers contained in `channel` are returned unmodified, if they
are within the range of ``self.channels``.
Parameters
----------
channels : int or str or list of... | python | def _name_to_index(self, channels):
"""
Return the channel indices for the specified channel names.
Integers contained in `channel` are returned unmodified, if they
are within the range of ``self.channels``.
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----------
channels : int or str or list of... | [
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taborlab/FlowCal | setup.py | find_version | def find_version(file_path):
"""
Scrape version information from specified file path.
"""
with open(file_path, 'r') as f:
file_contents = f.read()
version_match = re.search(r"^__version__\s*=\s*['\"]([^'\"]*)['\"]",
file_contents, re.M)
if version_match:
... | python | def find_version(file_path):
"""
Scrape version information from specified file path.
"""
with open(file_path, 'r') as f:
file_contents = f.read()
version_match = re.search(r"^__version__\s*=\s*['\"]([^'\"]*)['\"]",
file_contents, re.M)
if version_match:
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taborlab/FlowCal | FlowCal/gate.py | start_end | def start_end(data, num_start=250, num_end=100, full_output=False):
"""
Gate out first and last events.
Parameters
----------
data : FCSData or numpy array
NxD flow cytometry data where N is the number of events and D is
the number of parameters (aka channels).
num_start, num_en... | python | def start_end(data, num_start=250, num_end=100, full_output=False):
"""
Gate out first and last events.
Parameters
----------
data : FCSData or numpy array
NxD flow cytometry data where N is the number of events and D is
the number of parameters (aka channels).
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NxD flow cytometry data where N is the number of events and D is
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taborlab/FlowCal | FlowCal/gate.py | high_low | def high_low(data, channels=None, high=None, low=None, full_output=False):
"""
Gate out high and low values across all specified channels.
Gate out events in `data` with values in the specified channels which
are larger than or equal to `high` or less than or equal to `low`.
Parameters
-------... | python | def high_low(data, channels=None, high=None, low=None, full_output=False):
"""
Gate out high and low values across all specified channels.
Gate out events in `data` with values in the specified channels which
are larger than or equal to `high` or less than or equal to `low`.
Parameters
-------... | [
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Gate out events in `data` with values in the specified channels which
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data : FCSData or numpy array
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taborlab/FlowCal | FlowCal/gate.py | ellipse | def ellipse(data, channels,
center, a, b, theta=0,
log=False, full_output=False):
"""
Gate that preserves events inside an ellipse-shaped region.
Events are kept if they satisfy the following relationship::
(x/a)**2 + (y/b)**2 <= 1
where `x` and `y` are the coordinates... | python | def ellipse(data, channels,
center, a, b, theta=0,
log=False, full_output=False):
"""
Gate that preserves events inside an ellipse-shaped region.
Events are kept if they satisfy the following relationship::
(x/a)**2 + (y/b)**2 <= 1
where `x` and `y` are the coordinates... | [
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taborlab/FlowCal | FlowCal/gate.py | density2d | def density2d(data,
channels=[0,1],
bins=1024,
gate_fraction=0.65,
xscale='logicle',
yscale='logicle',
sigma=10.0,
full_output=False):
"""
Gate that preserves events in the region with highest density.
Gate ou... | python | def density2d(data,
channels=[0,1],
bins=1024,
gate_fraction=0.65,
xscale='logicle',
yscale='logicle',
sigma=10.0,
full_output=False):
"""
Gate that preserves events in the region with highest density.
Gate ou... | [
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Gate out all events in `data` but those near regions of highest
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Parameters
----------
data : FCSData or numpy array
NxD flow cytometry data where N is the number of events and D is
... | [
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taborlab/FlowCal | FlowCal/transform.py | transform | def transform(data, channels, transform_fxn, def_channels = None):
"""
Apply some transformation function to flow cytometry data.
This function is a template transformation function, intended to be
used by other specific transformation functions. It performs basic
checks on `channels` and `data`. I... | python | def transform(data, channels, transform_fxn, def_channels = None):
"""
Apply some transformation function to flow cytometry data.
This function is a template transformation function, intended to be
used by other specific transformation functions. It performs basic
checks on `channels` and `data`. I... | [
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taborlab/FlowCal | FlowCal/transform.py | to_rfi | def to_rfi(data,
channels=None,
amplification_type=None,
amplifier_gain=None,
resolution=None):
"""
Transform flow cytometry data to Relative Fluorescence Units (RFI).
If ``amplification_type[0]`` is different from zero, data has been
taken using a log amplif... | python | def to_rfi(data,
channels=None,
amplification_type=None,
amplifier_gain=None,
resolution=None):
"""
Transform flow cytometry data to Relative Fluorescence Units (RFI).
If ``amplification_type[0]`` is different from zero, data has been
taken using a log amplif... | [
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following operation is applied::
y = a[1]*10^(a[0] * (x/r))
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taborlab/FlowCal | FlowCal/transform.py | to_mef | def to_mef(data, channels, sc_list, sc_channels = None):
"""
Transform flow cytometry data using a standard curve function.
This function accepts a list of standard curves (`sc_list`) and a list
of channels to which those standard curves should be applied
(`sc_channels`). `to_mef` automatically che... | python | def to_mef(data, channels, sc_list, sc_channels = None):
"""
Transform flow cytometry data using a standard curve function.
This function accepts a list of standard curves (`sc_list`) and a list
of channels to which those standard curves should be applied
(`sc_channels`). `to_mef` automatically che... | [
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taborlab/FlowCal | FlowCal/plot.py | hist1d | def hist1d(data_list,
channel=0,
xscale='logicle',
bins=256,
histtype='stepfilled',
normed_area=False,
normed_height=False,
xlabel=None,
ylabel=None,
xlim=None,
ylim=None,
title=None,
lege... | python | def hist1d(data_list,
channel=0,
xscale='logicle',
bins=256,
histtype='stepfilled',
normed_area=False,
normed_height=False,
xlabel=None,
ylabel=None,
xlim=None,
ylim=None,
title=None,
lege... | [
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Parameters
----------
data_list : FCSData or numpy array or list of FCSData or numpy array
Flow cytometry data to plot.
channel : int or str, optional
Channel from where to take the events to plot. If ndim == 1,
ch... | [
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taborlab/FlowCal | FlowCal/plot.py | density2d | def density2d(data,
channels=[0,1],
bins=1024,
mode='mesh',
normed=False,
smooth=True,
sigma=10.0,
colorbar=False,
xscale='logicle',
yscale='logicle',
xlabel=None,
y... | python | def density2d(data,
channels=[0,1],
bins=1024,
mode='mesh',
normed=False,
smooth=True,
sigma=10.0,
colorbar=False,
xscale='logicle',
yscale='logicle',
xlabel=None,
y... | [
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`density2d` has two plotting modes which are selected using the `mode`
argument. With ``mode=='mesh'``, this function plots the data as a true
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taborlab/FlowCal | FlowCal/plot.py | scatter2d | def scatter2d(data_list,
channels=[0,1],
xscale='logicle',
yscale='logicle',
xlabel=None,
ylabel=None,
xlim=None,
ylim=None,
title=None,
color=None,
savefig=None,
**... | python | def scatter2d(data_list,
channels=[0,1],
xscale='logicle',
yscale='logicle',
xlabel=None,
ylabel=None,
xlim=None,
ylim=None,
title=None,
color=None,
savefig=None,
**... | [
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Parameters
----------
data_list : array or FCSData or list of array or list of FCSData
Flow cytometry data to plot.
channels : list of int, list of str
Two channels to use for the plot.
savefig : str, optional
... | [
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taborlab/FlowCal | FlowCal/plot.py | scatter3d | def scatter3d(data_list,
channels=[0,1,2],
xscale='logicle',
yscale='logicle',
zscale='logicle',
xlabel=None,
ylabel=None,
zlabel=None,
xlim=None,
ylim=None,
zlim=None,
... | python | def scatter3d(data_list,
channels=[0,1,2],
xscale='logicle',
yscale='logicle',
zscale='logicle',
xlabel=None,
ylabel=None,
zlabel=None,
xlim=None,
ylim=None,
zlim=None,
... | [
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----------
data_list : array or FCSData or list of array or list of FCSData
Flow cytometry data to plot.
channels : list of int, list of str
Three channels to use for the plot.
savefig : str, optional
... | [
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taborlab/FlowCal | FlowCal/plot.py | density_and_hist | def density_and_hist(data,
gated_data=None,
gate_contour=None,
density_channels=None,
density_params={},
hist_channels=None,
hist_params={},
figsize=None,
... | python | def density_and_hist(data,
gated_data=None,
gate_contour=None,
density_channels=None,
density_params={},
hist_channels=None,
hist_params={},
figsize=None,
... | [
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This function calls `hist1d` and `density2d` to plot a density diagram
and a number of histograms in different subplots of the same plot using
one single function call. Setting `density_channels` to None will not
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] | train | https://github.com/taborlab/FlowCal/blob/031a7af82acb1d46879a8e384a1a00f27f0bdc7a/FlowCal/plot.py#L1625-L1759 |
taborlab/FlowCal | FlowCal/plot.py | scatter3d_and_projections | def scatter3d_and_projections(data_list,
channels=[0,1,2],
xscale='logicle',
yscale='logicle',
zscale='logicle',
xlabel=None,
ylabel=None,
... | python | def scatter3d_and_projections(data_list,
channels=[0,1,2],
xscale='logicle',
yscale='logicle',
zscale='logicle',
xlabel=None,
ylabel=None,
... | [
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`scatter3d_and_projections` creates a 3D scatter plot and three 2D
projected scatter plots in four different axes for each FCSData object
in `data_list`, in the same figure.
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----------
data_list : FCSData object, or lis... | [
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taborlab/FlowCal | FlowCal/plot.py | _InterpolatedInverseTransform.transform_non_affine | def transform_non_affine(self, x, mask_out_of_range=True):
"""
Transform a Nx1 numpy array.
Parameters
----------
x : array
Data to be transformed.
mask_out_of_range : bool, optional
Whether to mask input values out of range.
Return
... | python | def transform_non_affine(self, x, mask_out_of_range=True):
"""
Transform a Nx1 numpy array.
Parameters
----------
x : array
Data to be transformed.
mask_out_of_range : bool, optional
Whether to mask input values out of range.
Return
... | [
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Parameters
----------
x : array
Data to be transformed.
mask_out_of_range : bool, optional
Whether to mask input values out of range.
Return
------
array or masked array
Transformed data. | [
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