signature
stringlengths
8
3.44k
body
stringlengths
0
1.41M
docstring
stringlengths
1
122k
id
stringlengths
5
17
def set_calibration_reps(self, reps):
self.bs_calibrator.set_reps(reps)<EOL>self.tone_calibrator.set_reps(reps)<EOL>
Sets the number of repetitions for calibration stimuli :param reps: Number of times a unique stimulus is presented in calibration operations :type reps: int
f10676:c0:m11
def load_data_file(self, fname, filemode='<STR_LIT:a>'):
self.close_data()<EOL>self.datafile = open_acqdata(fname, filemode=filemode)<EOL>self.explorer.set(datafile=self.datafile)<EOL>self.protocoler.set(datafile=self.datafile)<EOL>self.charter.set(datafile=self.datafile)<EOL>self.bs_calibrator.set(datafile=self.datafile)<EOL>self.tone_calibrator.set(datafile=self.datafile)<...
Opens an existing data file to append to :param fname: File path of the location for the data file to open :type fname: str
f10676:c0:m12
def current_data_file(self):
return self.datafile.filename<EOL>
Name of the currently employed data file :returns: str -- File name of the open data file
f10676:c0:m13
def set_threshold(self, threshold):
self.explorer.set_threshold(threshold)<EOL>self.protocoler.set_threshold(threshold)<EOL>
Sets spike detection threshold :param threshold: electrical potential to determine spikes (V) :type threshold: float
f10676:c0:m14
def set(self, **kwargs):
self.explorer.set(**kwargs)<EOL>self.protocoler.set(**kwargs)<EOL>self.tone_calibrator.set(**kwargs)<EOL>self.charter.set(**kwargs)<EOL>self.bs_calibrator.set(**kwargs)<EOL>self.mphone_calibrator.set(**kwargs)<EOL>
Sets acquisition parameters for all acquisition types See :meth:`AbstractAcquisitionRunner<sparkle.run.abstract_acquisition.AbstractAcquisitionRunner.set>`
f10676:c0:m15
def current_stim(self):
return self.explorer.current_signal()<EOL>
The signal of the current search stimulus :returns: numpy.ndarray -- the voltage signal of the output
f10676:c0:m17
def run_explore(self, interval):
return self.explorer.run(interval)<EOL>
Runs the explore operation :param interval: The repetition interval between stimuli presentations (seconds) :type interval: float :returns: :py:class:`threading.Thread` -- the acquisition thread
f10676:c0:m18
def setup_protocol(self, interval):
return self.protocoler.setup(interval)<EOL>
Sets up the protocol operation for the current settings :param interval: The repetition interval between stimuli presentations (seconds) :type interval: float
f10676:c0:m19
def protocol_total_count(self):
return self.protocoler.count()<EOL>
The number of stimuli presentations (including reps) for the current protocol contents :returns: int -- number of presentations
f10676:c0:m20
def run_protocol(self):
return self.protocoler.run()<EOL>
Runs the protocol operation with the current settings :returns: :py:class:`threading.Thread` -- the acquisition thread
f10676:c0:m21
def set_mphone_calibration(self, sens, db):
self.bs_calibrator.set_mphone_calibration(sens, db)<EOL>self.tone_calibrator.set_mphone_calibration(sens, db)<EOL>
Sets the microphone calibration, for the purpose of calculating recorded dB levels :param sens: microphone sensitivity (V) :type sens: float :param db: dB SPL that the calibration was measured at :type db: int
f10676:c0:m22
def set_calibration_by_index(self, idx):
self.selected_calibration_index = idx<EOL>
Sets the calibration stimulus by it's index in the list of calibration stimuli, with tone curve always being last
f10676:c0:m23
def calibration_total_count(self):
if self.selected_calibration_index == <NUM_LIT:2>:<EOL><INDENT>return self.tone_calibrator.count()<EOL><DEDENT>else:<EOL><INDENT>return self.bs_calibrator.count()<EOL><DEDENT>
The number of stimuli presentations (including reps) for the current calibration selected :returns: int -- number of presentations
f10676:c0:m24
def run_calibration(self, interval, applycal):
if self.selected_calibration_index == <NUM_LIT:2>:<EOL><INDENT>self.tone_calibrator.apply_calibration(applycal)<EOL>self.tone_calibrator.setup(interval)<EOL>return self.tone_calibrator.run()<EOL><DEDENT>else:<EOL><INDENT>self.bs_calibrator.set_stim_by_index(self.selected_calibration_index)<EOL>self.bs_calibrator.apply_...
Runs the calibration operation with the current settings :param interval: The repetition interval between stimuli presentations (seconds) :type interval: float :param applycal: Whether to apply a previous saved calibration to this run :type applycal: bool :returns: :py:class:`th...
f10676:c0:m25
def start_chart(self):
self.charter.start_chart()<EOL>
Starts the chart acquistion
f10676:c0:m27
def stop_chart(self):
self.charter.stop_chart()<EOL>
Halts the chart acquisition
f10676:c0:m28
def run_chart_protocol(self, interval):
self.charter.setup(interval)<EOL>return self.charter.run()<EOL>
Runs the stimuli presentation during a chart acquisition :param interval: The repetition interval between stimuli presentations (seconds) :type interval: float :returns: :py:class:`threading.Thread` -- the acquisition thread
f10676:c0:m29
def process_calibration(self, save=True, calf=<NUM_LIT>):
if self.selected_calibration_index == <NUM_LIT:2>:<EOL><INDENT>raise Exception("<STR_LIT>")<EOL><DEDENT>else:<EOL><INDENT>results, calname, freq, db = self.bs_calibrator.process_calibration(save)<EOL><DEDENT>return calname, db<EOL>
Processes a completed calibration :param save: Wether to save this calibration to file :type save: bool :param calf: Frequency for which to reference attenuation curve from :type calf: int :returns: str -- name of a saved calibration
f10676:c0:m30
def halt(self):
self.explorer.halt()<EOL>self.protocoler.halt()<EOL>self.bs_calibrator.halt()<EOL>self.tone_calibrator.halt()<EOL>self.charter.halt()<EOL>self.mphone_calibrator.halt()<EOL>
Halts any/all running operations
f10676:c0:m32
def close_data(self):
<EOL>if self.datafile is not None:<EOL><INDENT>if self.datafile.filemode != '<STR_LIT:r>':<EOL><INDENT>self.datafile.set_metadata('<STR_LIT>', {'<STR_LIT>': self.current_cellid})<EOL><DEDENT>self.datafile.close()<EOL>self.datafile = None<EOL><DEDENT>
Closes the current data file
f10676:c0:m33
def protocol_model(self):
return self.protocoler.protocol_model<EOL>
Gets the model for the protocol operation :returns: :class:`ProtocolModel<sparkle.run.protocol_model.ProtocolTabelModel>`
f10676:c0:m34
def calibration_stimulus(self, mode):
if mode == '<STR_LIT>':<EOL><INDENT>return self.tone_calibrator.stimulus<EOL><DEDENT>elif mode =='<STR_LIT>':<EOL><INDENT>return self.bs_calibrator.stimulus<EOL><DEDENT>
Gets the stimulus model for calibration :param mode: Type of stimulus to get: tone or noise :type mode: str :returns: :class:`StimulusModel<sparkle.stim.stimulus_model.StimulusModel>`
f10676:c0:m36
def explore_genrate(self):
return self.explorer.stimulus().samplerate()<EOL>
Gets the ouput samplerate for the search operation :returns: int -- the outgoing samplerate
f10676:c0:m37
def calibration_genrate(self):
return self.bs_calibrator.stimulus.samplerate()<EOL>
Gets the ouput samplerate for the calibration operation :returns: int -- the outgoing samplerate
f10676:c0:m38
def calibration_range(self):
return self.tone_calibrator.stimulus.autoParamRanges()<EOL>
Gets the range of the frequencies and intensities in the calibration tone curve :returns: list -- nested list of frequencies and intensities
f10676:c0:m39
def calibration_template(self):
temp = {}<EOL>temp['<STR_LIT>'] = self.tone_calibrator.stimulus.templateDoc()<EOL>comp_doc = []<EOL>for calstim in self.bs_calibrator.get_stims():<EOL><INDENT>comp_doc.append(calstim.stateDict())<EOL><DEDENT>temp['<STR_LIT>'] = comp_doc<EOL>return temp<EOL>
Gets the template documentation for the both the tone curve calibration and noise calibration :returns: dict -- all information necessary to recreate calibration objects
f10676:c0:m40
def load_calibration_template(self, template):
self.tone_calibrator.stimulus.clearComponents()<EOL>self.tone_calibrator.stimulus.loadFromTemplate(template['<STR_LIT>'], self.tone_calibrator.stimulus)<EOL>comp_doc = template['<STR_LIT>']<EOL>for state, calstim in zip(comp_doc, self.bs_calibrator.get_stims()):<EOL><INDENT>calstim.loadState(state)<EOL><DEDENT>
Reloads calibration settings from saved template doc :param template: Values for calibration stimuli (see calibration_template function) :type template: dict
f10676:c0:m41
def clear_protocol(self):
self.protocoler.clear()<EOL>
Clears all tests from the protocol acquisition
f10676:c0:m42
def set_group_comment(self, comment):
self.protocoler.set_comment(self.current_cellid, comment)<EOL>
Sets a comment for the last executed protocol group, to be saved as doc to the appropriate place in the data file.
f10676:c0:m43
def attenuator_connection(self, connect=True):
<EOL>acquisition_modules = [self.explorer, self.protocoler, self.bs_calibrator, self.tone_calibrator, self.charter]<EOL>if connect:<EOL><INDENT>if not acquisition_modules[<NUM_LIT:0>].player.attenuator_connected():<EOL><INDENT>for module in acquisition_modules:<EOL><INDENT>success = module.player.connect_attenuator()<E...
Checks the connection to the attenuator, and attempts to connect if not connected. Will also set an appropriate ouput minimum for stimuli, if connection successful :returns: bool - whether there is a connection
f10676:c0:m44
def get_stimuli_models():
package_path = os.path.dirname(__file__)<EOL>mod = '<STR_LIT:.>'.join(get_stimuli_models.__module__.split('<STR_LIT:.>'))<EOL>if mod == '<STR_LIT:__main__>':<EOL><INDENT>mod = '<STR_LIT>'<EOL><DEDENT>else:<EOL><INDENT>mod = mod + '<STR_LIT:.>'<EOL><DEDENT>module_files = glob.glob(package_path+os.sep+'<STR_LIT>')<EOL>mo...
Returns all subclasses of AbstractStimulusComponent in python files, in this package
f10679:m0
def get_component(comp_name, class_list):
for comp_class in class_list:<EOL><INDENT>if comp_class.name == comp_name:<EOL><INDENT>return comp_class()<EOL><DEDENT><DEDENT>else:<EOL><INDENT>return None<EOL><DEDENT>
Returns an implementation of the class refered to by *comp_name* if it is in *class_list*
f10681:m0
def setUserTag(self, tag):
self._userTag = tag<EOL>
Sets a string, significant to the user
f10681:c0:m1
def userTag(self):
return self._userTag<EOL>
Returns a saved string, set by user
f10681:c0:m2
def setStimType(self, t):
self._stimType = t<EOL>
Sets the stimulus type this model represents, intention is to determine editor type
f10681:c0:m3
def stimType(self):
return self._stimType<EOL>
Stimulus type of this model (e.g. custom, tuning curve)
f10681:c0:m4
def setReferenceVoltage(self, caldb, calv):
self.caldb = caldb<EOL>self.calv = calv<EOL>
Sets the reference point to determine what outgoing voltage will produce what intensity, used to calculate the proper output amplitude of components :param caldb: calibration intensity in dbSPL :type caldb: float :param calv: calibration voltage that was used to record the intensity pr...
f10681:c0:m5
def setCalibration(self, dbBoostArray, frequencies, frange):
if dbBoostArray is not None and frequencies is not None:<EOL><INDENT>logger = logging.getLogger('<STR_LIT>')<EOL>if dbBoostArray.shape != frequencies.shape:<EOL><INDENT>logger.error("<STR_LIT>")<EOL>return<EOL><DEDENT>if frange is None:<EOL><INDENT>frange = (frequencies[<NUM_LIT:0>], frequencies[-<NUM_LIT:1>])<EOL><DED...
Sets the calibration to use with this stimulus, creates a filter that will be applied to output signal generated by this model. Set arguments to `None` to clear calibration. :param dbBoostArray: frequency response of the system (in dB) :type dbBoostArray: numpy.ndarray :param f...
f10681:c0:m6
def updateCalibration(self):
if self.samplerate() != self._calibration_fs:<EOL><INDENT>self.setCalibration(self._attenuationVector, self._calFrequencies, self._calFrange)<EOL><DEDENT>
Updates the current calibration according to intenal values. For example, if the stimulus samplerate changes the calibration needs to be recalculated.
f10681:c0:m7
@staticmethod<EOL><INDENT>def clearCache():<DEDENT>
StimulusModel.kernelCache = {}<EOL>
clears the calibration filters stored in the cache
f10681:c0:m8
def samplerate(self):
rates = []<EOL>for track in self._segments:<EOL><INDENT>for component in track:<EOL><INDENT>if component.__class__.__name__ == '<STR_LIT>':<EOL><INDENT>if component.samplerate() is not None:<EOL><INDENT>rates.append(component.samplerate())<EOL><DEDENT><DEDENT><DEDENT><DEDENT>if len(set(rates)) > <NUM_LIT:1>:<EOL><INDEN...
Returns the generation rate for this stimulus :returns: int -- the output samplerate (Hz)
f10681:c0:m9
def setAutoParams(self, params):
self._autoParams = params<EOL>
Overwrites the AutoParameterModel for this stimulus :param params: model to assign :type params: :class:`AutoParameterModel<sparkle.stim.auto_parameter_model.AutoParameterModel>`
f10681:c0:m10
def autoParams(self):
return self._autoParams<EOL>
Returns the AutoParameterModel for this stimulus, which holds the auto-test information :returns: :class:`AutoParameterModel<sparkle.stim.auto_parameter_model.AutoParameterModel>`
f10681:c0:m11
def rowCount(self):
return len(self._segments)<EOL>
Returns the number of tracks :returns: int -- number of rows
f10681:c0:m12
def columnCount(self, row=None):
if row is not None:<EOL><INDENT>wholerow = self._segments[row]<EOL>return len(wholerow)<EOL><DEDENT>else:<EOL><INDENT>column_lengths = [len(x) for x in self._segments]<EOL>return max(column_lengths)<EOL><DEDENT>
Returns the number of components in a track, or the max number of components in any row, if none given :param row: track to get count for :type row: int :returns: int -- number of components for *row*
f10681:c0:m13
def componentCount(self):
return sum([self.columnCountForRow(x) for x in range(self.rowCount())])<EOL>
Returns the total number of components in stimulus :returns: number of components (not including expanded auto-params)
f10681:c0:m15
def component(self, row, col):
try:<EOL><INDENT>comp = self._segments[row][col]<EOL><DEDENT>except:<EOL><INDENT>print('<STR_LIT>')<EOL>return None<EOL><DEDENT>return comp<EOL>
Gets the components for the location :param row: track the component is in :type row: int :param col: the ith member of the track :type col: int :returns: :class:`AbstractStimulusComponent<sparkle.stim.abstract_component.AbstractStimulusComponent>`
f10681:c0:m16
def insertComponent(self, comp, row=<NUM_LIT:0>, col=<NUM_LIT:0>):
if row > len(self._segments) -<NUM_LIT:1>:<EOL><INDENT>self.insertEmptyRow()<EOL><DEDENT>self._segments[row].insert(col, comp)<EOL>self.updateCalibration()<EOL>
Inserts component into model :param comp: Component to insert into the stimulus :type comp: :class:`AbstractStimulusComponent<sparkle.stim.abstract_component.AbstractStimulusComponent>` :param row: Track number to place comp in :type row: int :param col: location in track to ins...
f10681:c0:m17
def overwriteComponent(self, comp, row, col):
self._segments[row][col] = comp<EOL>self.updateCalibration()<EOL>
Overwrites the component at the specficied location with a provided one. :param comp: New component to insert :type comp: :class:`AbstractStimulusComponent<sparkle.stim.abstract_component.AbstractStimulusComponent>` :param row: track location of existing component to overwrite :type row...
f10681:c0:m18
def insertEmptyRow(self):
self._segments.append([])<EOL>
Appends an empty track at the end
f10681:c0:m19
def removeLastRow(self):
lastrow = self._segments.pop(len(self._segments)-<NUM_LIT:1>)<EOL>if len(lastrow) > <NUM_LIT:0>:<EOL><INDENT>raise Exception("<STR_LIT>")<EOL><DEDENT>
Removes the last track
f10681:c0:m20
def removeRow(self, row):
self._segments.pop(row)<EOL>
Removes the track at row, empty or not
f10681:c0:m21
def removeComponent(self, row,col):
self._segments[row].pop(col)<EOL>if self.columnCountForRow(-<NUM_LIT:1>) == <NUM_LIT:0>:<EOL><INDENT>self.removeRow(len(self._segments)-<NUM_LIT:1>)<EOL><DEDENT>self.updateCalibration()<EOL>
Removes the component at the given location :param row: track location of existing component to remove :type row: int :param col: location in track of existing component to remove :type col: int
f10681:c0:m22
def clearComponents(self):
self._segments = []<EOL>self._autoParams.clearParameters()<EOL>
Removes all components
f10681:c0:m23
def indexByComponent(self, component):
for row, rowcontents in enumerate(self._segments):<EOL><INDENT>if component in rowcontents:<EOL><INDENT>column = rowcontents.index(component)<EOL>return (row, column)<EOL><DEDENT><DEDENT>
Returns a location for the given component, or None if it is not in the model :param component: Component to get index for :type component: :class:`AbstractStimulusComponent<sparkle.stim.abstract_component.AbstractStimulusComponent>` :returns: (int, int) -- (row, column) of component
f10681:c0:m24
def traceCount(self):
nsegs = sum([len(track) for track in self._segments])<EOL>if nsegs == <NUM_LIT:0>:<EOL><INDENT>return <NUM_LIT:0><EOL><DEDENT>ntraces = <NUM_LIT:1><EOL>for irow in range(self._autoParams.nrows()):<EOL><INDENT>ntraces = ntraces*self._autoParams.numSteps(irow)<EOL><DEDENT>return ntraces<EOL>
The number of unique stimului for this stimulus object :returns: int -- The expanded trace count
f10681:c0:m25
def loopCount(self):
return self._nloops<EOL>
The number of times to run through a set of autoparameters :returns: the number of times the auto-parameters and looped through
f10681:c0:m26
def setLoopCount(self, count):
self._nloops = count<EOL>
Sets the number of times to loop through an entire set of autoparameters
f10681:c0:m27
def repCount(self):
return self._nreps<EOL>
Returns the number of repetitions each unique stimulus is presented
f10681:c0:m28
def setRepCount(self, count):
if count > <NUM_LIT:0>:<EOL><INDENT>self._nreps = count<EOL><DEDENT>
Sets the number of repetitions each unique stimulus is presented
f10681:c0:m29
def contains(self, stimtype):
for track in self._segments:<EOL><INDENT>for component in track:<EOL><INDENT>if component.__class__.__name__ == stimtype:<EOL><INDENT>return True<EOL><DEDENT><DEDENT><DEDENT>return False<EOL>
Returns whether the specified stimlus type is a component in this stimulus :param stimtype: :class:`AbstractStimulusComponent<sparkle.stim.abstract_component.AbstractStimulusComponent>` subclass class name to test for membership in the components of this stimulus :type stimtype: str :returns: b...
f10681:c0:m30
def purgeAutoSelected(self):
params = self._autoParams.allData()<EOL>for p in params:<EOL><INDENT>comps_to_remove = []<EOL>for comp in p['<STR_LIT>']:<EOL><INDENT>if self.indexByComponent(comp) is None:<EOL><INDENT>comps_to_remove.append(comp)<EOL><DEDENT><DEDENT>for orphaned in comps_to_remove:<EOL><INDENT>p['<STR_LIT>'].remove(orphaned)<EOL><DED...
Clears out orphaned auto parameters
f10681:c0:m31
def cleanComponents(self):
for row in self._segments:<EOL><INDENT>for comp in row:<EOL><INDENT>comp.clean()<EOL><DEDENT><DEDENT>
Removes and references to UI objects from components. Allows them to be serializable
f10681:c0:m32
def autoParamRanges(self):
return self._autoParams.ranges()<EOL>
Returns the expanded auto parameters, individually See :meth:`AutoParameterModel<sparkle.stim.auto_parameter_model.AutoParameterModel.ranges>`
f10681:c0:m33
def expandFunction(self, func, args=[]):
<EOL>params = self._autoParams.allData()<EOL>steps = self.autoParamRanges()<EOL>ntraces = <NUM_LIT:1><EOL>for p in steps:<EOL><INDENT>ntraces = ntraces*len(p)<EOL><DEDENT>varylist = [[None for x in range(len(params))] for y in range(ntraces)]<EOL>x = <NUM_LIT:1><EOL>for iset, step_set in enumerate(steps):<EOL><INDENT>f...
applies the given function to each of this stimulus's memerships when autoparamters are applied :param func: callable to execute for each version of the stimulus :type instancemethod: :param args: arguments to feed to func :type args: list :returns: list<results of *func*>, one ...
f10681:c0:m34
def setReorderFunc(self, func, name=None):
self.reorder = func<EOL>self.reorderName = name<EOL>
Sets the function that reorders the expanded signals of this stimulus :param func: a function which takes the template doc as an argument :type func: callable :param name: a name to assign the function (for documentation purposes) :type name: str
f10681:c0:m35
def expandedStim(self):
logger = logging.getLogger('<STR_LIT>')<EOL>logger.debug("<STR_LIT>")<EOL>signals = self.expandFunction(self.signal)<EOL>docs = self.expandFunction(self.componentDoc)<EOL>overloads = []<EOL>for s, d in zip(signals, docs):<EOL><INDENT>d['<STR_LIT>'] = s[<NUM_LIT:2>]<EOL>overloads.append(s[<NUM_LIT:2>])<EOL><DEDENT>signa...
Apply the autoparameters to this stimulus and return a list of the resulting stimuli, a complimentary list of doc dictionaries, and a complimentary list of undesired attenuations. :returns: list<numpy.ndarray>, list<dict>, list<float> -- the signals, their doc, undesired attenuations (dB)
f10681:c0:m36
def templateDoc(self):
doc = dict(list(self.componentDoc(False).items()) + list(self.testDoc().items()))<EOL>autoparams = copy.deepcopy(self._autoParams.allData())<EOL>for p in autoparams:<EOL><INDENT>selection = p['<STR_LIT>']<EOL>serializable_selection = []<EOL>for component in selection:<EOL><INDENT>idx = self.indexByComponent(component)<...
JSON serializable template to will all necessary details to recreate this stimulus in another session. :returns: dict
f10681:c0:m37
@staticmethod<EOL><INDENT>def loadFromTemplate(template, stim=None):<DEDENT>
if stim is None:<EOL><INDENT>stim = StimulusModel()<EOL><DEDENT>stim.setRepCount(template['<STR_LIT>'])<EOL>stim.setUserTag(template.get('<STR_LIT>', '<STR_LIT>'))<EOL>component_classes = get_stimuli_models()<EOL>for comp_doc in template['<STR_LIT>']:<EOL><INDENT>comp = get_component(comp_doc['<STR_LIT>'], component_cl...
Loads the stimlus to the state provided by a template :param template: dict that includes all info nesessary to recreate stim :type template: dict :param stim: Stimulus to apply to, creates a new model if None :type stim: StimulusModel
f10681:c0:m38
def duration(self):
durs = []<EOL>for track in self._segments:<EOL><INDENT>durs.append(sum([comp.duration() for comp in track]))<EOL><DEDENT>return max(durs)<EOL>
The duration of this stimulus :returns: float -- duration in seconds
f10681:c0:m40
def signal(self, force_fs=False):
assert None not in self.voltage_limits, '<STR_LIT>'<EOL>if force_fs:<EOL><INDENT>samplerate = force_fs<EOL><DEDENT>else:<EOL><INDENT>samplerate = self.samplerate()<EOL><DEDENT>track_signals = []<EOL>max_db = max([comp.intensity() for t in self._segments for comp in t])<EOL>atten = <NUM_LIT:0><EOL>for track in self._seg...
The current stimulus in signal representation, this is the sum of its components :param force_fs: Allow to use a different samplerate than the default, should be used to recreate historical signals only :type force_fs: int :returns: numpy.ndarray -- voltage signal for this stimulus
f10681:c0:m41
def componentDoc(self, starttime=True):
samplerate = self.samplerate()<EOL>doc_list = []<EOL>for row, track in enumerate(self._segments):<EOL><INDENT>start_time = <NUM_LIT:0><EOL>for col, component in enumerate(track):<EOL><INDENT>info = component.stateDict()<EOL>info['<STR_LIT>'] = component.name<EOL>if starttime:<EOL><INDENT>info['<STR_LIT>'] = start_time<...
The documentation for the components, as a dict :returns dict -- values are the generation samplerate, and a list of the individual component docs
f10681:c0:m42
def updateComponentStartVals(self):
self._autoParams.updateComponentStartVals()<EOL>
Go through selected components for each auto parameter and set the start value
f10681:c0:m44
def containsPval(self, paramName, value):
<EOL>params = self._autoParams.allData()<EOL>steps = self.autoParamRanges()<EOL>pnames = [p['<STR_LIT>'] for p in params]<EOL>if paramName in pnames:<EOL><INDENT>pidx = pnames.index(paramName)<EOL>return value in steps[pidx]<EOL><DEDENT>else:<EOL><INDENT>return False<EOL><DEDENT>
Returns true if *value* for parameter type *paramName* is in the auto parameters :param paramName: the name of the auto-parameter to match, e.g. 'frequency' :type paramName: str :param value: the value of the parameter to search for :returns: bool
f10681:c0:m45
def warning(self):
signals, docs, overs = self.expandedStim()<EOL>if np.any(np.array(overs) > <NUM_LIT:0>):<EOL><INDENT>msg = '<STR_LIT>'.format(np.amax(overs))<EOL>return msg<EOL><DEDENT>return <NUM_LIT:0><EOL>
Checks Stimulus for any warning conditions :returns: str -- warning message, if any, 0 otherwise
f10681:c0:m46
def verifyExpanded(self, samplerate):
results = self.expandFunction(self.verifyComponents, args=(samplerate,))<EOL>msg = [x for x in results if x]<EOL>if len(msg) > <NUM_LIT:0>:<EOL><INDENT>return msg[<NUM_LIT:0>]<EOL><DEDENT>else:<EOL><INDENT>return <NUM_LIT:0><EOL><DEDENT>
Checks the expanded parameters for invalidating conditions :param samplerate: generation samplerate (Hz), passed on to component verification :type samplerate: int :returns: str -- error message, if any, 0 otherwise
f10681:c0:m47
def verifyComponents(self, samplerate):
<EOL>components = [comp for track in self._segments for comp in track]<EOL>for comp in components:<EOL><INDENT>msg = comp.verify(samplerate=samplerate)<EOL>if msg:<EOL><INDENT>return msg<EOL><DEDENT><DEDENT>return <NUM_LIT:0><EOL>
Checks the current components for invalidating conditions :param samplerate: generation samplerate (Hz), passed on to component verification :type samplerate: int :returns: str -- error message, if any, 0 otherwise
f10681:c0:m48
def verify(self, windowSize=None):
if self.samplerate() is None:<EOL><INDENT>return "<STR_LIT>"<EOL><DEDENT>msg = self._autoParams.verify()<EOL>if msg:<EOL><INDENT>return msg<EOL><DEDENT>if self.traceCount() == <NUM_LIT:0>:<EOL><INDENT>return "<STR_LIT>"<EOL><DEDENT>if windowSize is not None:<EOL><INDENT>durations = self.expandFunction(self.duration)<EO...
Checks the stimulus, including expanded parameters for invalidating conditions :param windowSize: acquistion (recording) window size (seconds) :type windowSize: float :returns: str -- error message, if any, 0 otherwise
f10681:c0:m49
def amplitude(self, caldb, calv, atten=<NUM_LIT:0>):
amp = (<NUM_LIT:10> ** (float(self._intensity+atten-caldb)/<NUM_LIT:20>)*calv)<EOL>return amp<EOL>
Calculates the voltage amplitude for this stimulus, using internal intensity value and the given reference intensity & voltage :param caldb: calibration intensity in dbSPL :type caldb: float :param calv: calibration voltage that was used to record the intensity provided :type ca...
f10682:c0:m8
def signal(self, fs, atten, caldb, calv):
raise NotImplementedError<EOL>
Creates a signal representation of this stimulus, in the form of a vector of numbers representing electric potential. caldb and calv are used to determine the amplitude of the signal. Must be implemented by subclass :param fs: Generation samplerate (Hz) at which this signal wil...
f10682:c0:m9
def verify(self, **kwargs):
if '<STR_LIT>' in kwargs:<EOL><INDENT>if kwargs['<STR_LIT>'] < self._duration:<EOL><INDENT>return "<STR_LIT>"<EOL><DEDENT><DEDENT>if self._risefall > self._duration:<EOL><INDENT>return "<STR_LIT>"<EOL><DEDENT>return <NUM_LIT:0><EOL>
Checks this component for invalidating conditions :returns: str -- message if error, 0 otherwise
f10682:c0:m10
def auto_details(self):
return {'<STR_LIT>':{'<STR_LIT>':'<STR_LIT:s>', '<STR_LIT>':<NUM_LIT:0.>, '<STR_LIT>':<NUM_LIT>},<EOL>'<STR_LIT>':{'<STR_LIT>':'<STR_LIT>', '<STR_LIT>':<NUM_LIT:0>, '<STR_LIT>':<NUM_LIT>}, <EOL>'<STR_LIT>':{'<STR_LIT>':'<STR_LIT:s>', '<STR_LIT>':<NUM_LIT:0>, '<STR_LIT>':<NUM_LIT:0.1>}}<EOL>
A collection of the parameter names that are available to be set using auto-paramter manipulation. Subclasses should re-implement and add to this list :returns: dict<dict> -- {'parametername': {'label':str, 'unit':str, 'min':float, 'max':float},}
f10682:c0:m11
def stateDict(self):
state = {<EOL>'<STR_LIT>' : self._duration,<EOL>'<STR_LIT>' : self._intensity,<EOL>'<STR_LIT>' : self._risefall,<EOL>'<STR_LIT>' : self.name<EOL>}<EOL>return state<EOL>
Saves internal values to be loaded later :returns: dict -- {'parametername': value, ...}
f10682:c0:m12
def loadState(self, state):
self._duration = state['<STR_LIT>']<EOL>self._intensity = state['<STR_LIT>']<EOL>self._risefall = state['<STR_LIT>']<EOL>
Loads previously saved values to this component. :param state: return value from `stateDict` :type state: dict
f10682:c0:m13
def nrows(self):
return len(self._parameters)<EOL>
The number of auto-parameters :returns: int -- parameter count
f10683:c0:m1
def clearParameters(self):
self._parameters = []<EOL>
Clears all parameters out of this model
f10683:c0:m2
def param(self, row):
return self._parameters[row]<EOL>
Gets the parameter indexed by *row* :param row: the ith parameter number :type row: int :returns: dict -- the parameter
f10683:c0:m3
def selection(self, row):
return self._parameters[row]['<STR_LIT>']<EOL>
Gets the component selection for parameter number *row* :param row: the ith parameter number :type row: int :returns: list<:class:`AbstractStimulusComponent<sparkle.stim.abstract_component.AbstractStimulusComponent>`>
f10683:c0:m4
def allData(self):
return self._parameters<EOL>
Gets a list of all the parameters in this model :returns: list<dict> -- all parameters
f10683:c0:m5
def toggleSelection(self, row, component):
selection = self._parameters[row]['<STR_LIT>']<EOL>if component in selection:<EOL><INDENT>selection.remove(component)<EOL><DEDENT>else:<EOL><INDENT>selection.append(component)<EOL><DEDENT>
Toggles the *component* in or out of the selection for parameter *row* :param row: the ith parameter number :type row: int :param component: the component to toggle its selection membership :type component: :class:`AbstractStimulusComponent<sparkle.stim.abstract_component.Abstr...
f10683:c0:m6
def setVerifiedValue(self, row, field, value):
if self._parameters[row]['<STR_LIT>'] == '<STR_LIT:filename>':<EOL><INDENT>return <EOL><DEDENT>if field == '<STR_LIT>':<EOL><INDENT>self.setParamValue(row, parameter=value)<EOL><DEDENT>elif field in ['<STR_LIT:start>', '<STR_LIT>', '<STR_LIT>']:<EOL><INDENT>if self.checkLimits(row, value):<EOL><INDENT>kwd = {field : va...
Sets the *value* for *field* in the parameter indexed by *row*, only if the value is within set limits :param row: the ith parameter number :type row: int :param field: detail of the parameter to set :type field: str :param value: pre-scaled value to assign to field
f10683:c0:m7
def setParamValue(self, row, **kwargs):
param = self._parameters[row]<EOL>for key, val in list(kwargs.items()):<EOL><INDENT>param[key] = val<EOL><DEDENT>
Sets the arguments as field=val for parameter indexed by *row* :param row: the ith parameter number :type row: int
f10683:c0:m8
def paramValue(self, row, field):
if field == '<STR_LIT>':<EOL><INDENT>return self.numSteps(row)<EOL><DEDENT>if field in ['<STR_LIT:start>', '<STR_LIT>', '<STR_LIT>'] and self._parameters[row]['<STR_LIT>'] == '<STR_LIT:filename>':<EOL><INDENT>return '<STR_LIT:->'<EOL><DEDENT>else:<EOL><INDENT>param = self._parameters[row]<EOL>return param[field]<EOL><D...
Gets the value for *field* for parameter indexed by *row* :param row: the ith parameter number :type row: int :param field: detail of the parameter to set :type field: str :returns: value -- type appropriate to parameter
f10683:c0:m9
def overwriteParam(self, row, param):
if row == -<NUM_LIT:1>:<EOL><INDENT>row = self.nrows() - <NUM_LIT:1><EOL><DEDENT>self._parameters[row] = param<EOL>
Assigns *param* to index *row*, overwritting the parameter at that location :param row: the ith parameter number :type row: int :param param: parameter to set :type param: dict
f10683:c0:m10
def numSteps(self, row):
param = self._parameters[row]<EOL>return self.nStepsForParam(param)<EOL>
Gets the number of steps for the parameter at index *row* will yeild
f10683:c0:m11
def nStepsForParam(self, param):
if param['<STR_LIT>'] == '<STR_LIT:filename>':<EOL><INDENT>return len(param['<STR_LIT>'])<EOL><DEDENT>else:<EOL><INDENT>if param['<STR_LIT>'] > <NUM_LIT:0>:<EOL><INDENT>if abs(param['<STR_LIT:start>'] - param['<STR_LIT>']) < param['<STR_LIT>']:<EOL><INDENT>return <NUM_LIT:0><EOL><DEDENT>nsteps = np.around(abs(param['<S...
Gets the number of steps *parameter* will yeild :param param: parameter to get the expansion count for :type param: dict
f10683:c0:m12
def getDetail(self, row, detail_field):
param = self._parameters[row]<EOL>param_type = param['<STR_LIT>']<EOL>components = param['<STR_LIT>']<EOL>if len(components) == <NUM_LIT:0> or param_type == '<STR_LIT>':<EOL><INDENT>return None<EOL><DEDENT>matching_details = []<EOL>for comp in components:<EOL><INDENT>alldetails = comp.auto_details()<EOL>if not param_ty...
Gets the value of the detail *detail_field* of paramter at index *row* from its selected components `auto_details`. All of the selected components value for *detail_field* must match :param row: the ith parameter number :type row: int :param detail_field: auto_details me...
f10683:c0:m13
def isFieldValid(self, row, field):
param = self._parameters[row]<EOL>if param['<STR_LIT>'] == '<STR_LIT>':<EOL><INDENT>return False<EOL><DEDENT>if field == '<STR_LIT>':<EOL><INDENT>return self.numSteps(row) != <NUM_LIT:0><EOL><DEDENT>if param['<STR_LIT>'] == '<STR_LIT:filename>':<EOL><INDENT>return True<EOL><DEDENT>if field == '<STR_LIT>':<EOL><INDENT>r...
Verifies the value in *field* for parameter at index *row* :param row: the ith parameter number :type row: int :param field: detail of the parameter to check :type field: str :returns: bool -- True if valid
f10683:c0:m14
def findFileParam(self, comp):
for p in self._parameters:<EOL><INDENT>if p['<STR_LIT>'] == '<STR_LIT:filename>' and comp in p['<STR_LIT>']:<EOL><INDENT>return p['<STR_LIT>']<EOL><DEDENT><DEDENT>
Finds the filename auto-parameter that component *comp* is in, and returns all the filenames for that parameter. Notes this assumes that *comp* will only be in a single filename auto-parameter. :param comp: Component to search parameter membership for :type comp: :class:`AbstractStimulu...
f10683:c0:m15
def checkLimits(self, row, value):
<EOL>param = self._parameters[row]<EOL>components = param['<STR_LIT>']<EOL>if len(components) == <NUM_LIT:0>:<EOL><INDENT>return False<EOL><DEDENT>ptype = param['<STR_LIT>']<EOL>mins = []<EOL>maxs = []<EOL>for comp in components:<EOL><INDENT>try:<EOL><INDENT>details = comp.auto_details()[ptype]<EOL>mins.append(details[...
Check that *value* is within the minimum and maximum allowable range for the parameter at index *row* :param row: the ith parameter number :type row: int :param value: the candidate value to for start or stop fields :returns: bool -- True if *value* within range
f10683:c0:m16