Python StimulusModel.repCount方法代码示例

# 需要导入模块: from sparkle.stim.stimulus_model import StimulusModel [as 别名]
# 或者: from sparkle.stim.stimulus_model.StimulusModel import repCount [as 别名]
    def test_edit_model(self):
        tests = ProtocolTabelModel()
        tests.setReferenceVoltage(100, 0.1)
        model = QProtocolTabelModel(tests)
        stim = StimulusModel()
        component = PureTone()
        stim.insertComponent(component, 0,0)
        model.insertTest(stim,0)

        assert stim.repCount() == 1

        newreps = 3
        headers = model.allHeaders()
        repidx = headers.index('Reps')
        lenidx = headers.index('Length')
        totalidx = headers.index('Total')
        model.setData(model.index(0,repidx), newreps, QtCore.Qt.EditRole)

        assert stim.repCount() == newreps
        assert model.data(model.index(0,repidx), role=QtCore.Qt.DisplayRole) == newreps
        assert model.data(model.index(0,lenidx), role=QtCore.Qt.DisplayRole) == 1
        assert model.data(model.index(0,totalidx), role=QtCore.Qt.DisplayRole) == newreps

# 需要导入模块: from sparkle.stim.stimulus_model import StimulusModel [as 别名]
# 或者: from sparkle.stim.stimulus_model.StimulusModel import repCount [as 别名]
class CalibrationRunner(AbstractCalibrationRunner):
    """Handles Calibration acquistion, where there is a single unique 
    stimulus used to capture the frequency response of the system.
    This class may hold many different types of stimuli (currently 2),
    but only one is presented per calibration run."""
    def __init__(self, *args):
        super(AbstractCalibrationRunner, self).__init__(*args)

        self.player = FinitePlayer()

        self.stimulus = StimulusModel()
        # # insert stim component... either noise or chirp
        self.stim_components = [WhiteNoise(), FMSweep()]
        self.stimulus.insertComponent(self.stim_components[0])
        self.protocol_model.insert(self.stimulus, 0)

        # reference tone for setting the refence voltage==db
        self.refstim = StimulusModel()
        tone = PureTone()
        tone.setRisefall(0.001)
        self.refstim.insertComponent(tone, 0,0)
        self.reftone = tone

        self.save_data = True
        self.group_name = 'calibration_'

        self.calibration_vector = None
        self.calibration_freqs = None
        self.calibration_frange = None

    def get_stims(self):
        """Gets the stimuli available for setting as the current calibration stimulus
        
        :returns: list<:class:`StimulusModel<sparkle.stim.stimulus_model.StimulusModel>`>
        """
        return self.stim_components

    def set_stim_by_index(self, index):
        """Sets the stimulus to be generated to the one referenced by index

        :param index: index number of stimulus to set from this class's internal list of stimuli
        :type index: int
        """
        # remove any current components
        self.stimulus.clearComponents()
        # add one to index because of tone curve
        self.stimulus.insertComponent(self.stim_components[index])

    def set_duration(self, dur):
        """See :meth:`AbstractCalibrationRunner<sparkle.run.calibration_runner.AbstractCalibrationRunner.set_duration>`"""
        # this may be set at any time, and is not checked before run, so set
        # all stim components
        for comp in self.stim_components:
            comp.setDuration(dur)
        self.reftone.setDuration(dur)

    def _initialize_run(self):
       
        self.player.set_aochan(self.aochan)
        self.player.set_aichan(self.aichan)

        if self.apply_cal:
            self.protocol_model.setCalibration(self.calibration_vector, self.calibration_freqs, self.calibration_frange)
            # calibration testing doesn't save anything
            self.save_data = False
        else:
            data_items = self.datafile.keys()
            self.current_dataset_name = next_str_num(self.group_name, data_items)
            
            self.datafile.init_group(self.current_dataset_name, mode='calibration')
            
            logger = logging.getLogger('main')
            logger.debug('Calibrating with fs %s' %  self.stimulus.samplerate())

            self.datafile.init_data(self.current_dataset_name, mode='calibration', 
                                    dims=(self.stimulus.repCount(), self.stimulus.duration()*self.stimulus.samplerate()))

            info = {'samplerate_ad': self.player.aifs}
            self.datafile.set_metadata(self.current_dataset_name, info)
            # point is to output the signal at the specificed voltage, to we set
            # the intensity of the components to match whatever the caldb is now
            self.save_data = True
            self.stimulus.component(0,0).setIntensity(self.caldb)
            print 'USING {} V, {} Hz, {} dBSPL'.format(self.calv, self.calf, self.caldb)
            self.reftone.setIntensity(self.caldb)
            self.reftone.setFrequency(self.calf)
            self.protocol_model.insert(self.refstim,0)
            self.calname = None
            self.protocol_model.setCalibration(None, None, None)

            self.datafile.init_data(self.current_dataset_name, mode='calibration',
                                    nested_name='reference_tone',
                                    dims=(self.stimulus.repCount(), self.stimulus.duration()*self.stimulus.samplerate()))

    def _initialize_test(self, test):
        assert test.samplerate() == self.player.aifs

    def _process_response(self, response, trace_info, irep):
        if self.save_data:
            if trace_info['components'][0]['stim_type'] == 'Pure Tone':
#.........这里部分代码省略.........

# 需要导入模块: from sparkle.stim.stimulus_model import StimulusModel [as 别名]
# 或者: from sparkle.stim.stimulus_model.StimulusModel import repCount [as 别名]

#.........这里部分代码省略.........
        signal, atten, ovld = self.model.signal()
        assert atten == 0
        print 'maxv', DEVICE_MAXV, 'signal max', np.amax(signal), 'overload', ovld
        assert round(np.amax(signal),2) == DEVICE_MAXV
        # do math to make this more accurate
        assert ovld > 0

    def test_corrent_number_of_traces(self):
        self.model = self.stim_with_double_auto()
        n = self.model.traceCount()
        sig, doc, over = self.model.expandedStim()
        assert len(sig) == n

    def test_template_no_auto_params(self):
        self.model.setRepCount(7)
        component = PureTone()
        component.setIntensity(34)
        self.model.insertComponent(component, 0,0)
        vocal = Vocalization()
        vocal.setFile(sample.samplewav())
        self.model.insertComponent(vocal, 1,0)

        template = self.model.templateDoc()

        clone = StimulusModel.loadFromTemplate(template)
        clone.setReferenceVoltage(100, 0.1)

        signal0, atten0, ovld = clone.signal()
        signal1, atten1, ovld = self.model.signal()

        assert clone.stimid != self.model.stimid
        np.testing.assert_array_equal(signal0, signal1)
        assert atten0 == atten1
        assert clone.repCount() == self.model.repCount()

    def test_template_with_auto_params(self):
        self.model.setRepCount(7)
        component = PureTone()
        component.setIntensity(34)
        self.model.insertComponent(component, 0,0)
        nsteps = self.add_auto_param(self.model) 

        template = self.model.templateDoc()

        clone = StimulusModel.loadFromTemplate(template)
        clone.setReferenceVoltage(100, 0.1)

        signals0, docs0, ovld = self.model.expandedStim()
        signals1, docs1, ovld = clone.expandedStim()

        assert clone.stimid != self.model.stimid
        assert len(signals0) == len(signals1)
        for i in range(len(signals0)):
            signal0, atten0 = signals0[i]
            signal1, atten1 = signals1[i]
            np.testing.assert_array_equal(signal0, signal1)
            assert atten0 == atten1
            assert_equal(docs0[i], docs1[i])

        assert clone.repCount() == self.model.repCount()

    def test_template_with_auto_params_vocal(self):
        model = self.stim_with_double_auto()

        template = model.templateDoc()

# 需要导入模块: from sparkle.stim.stimulus_model import StimulusModel [as 别名]
# 或者: from sparkle.stim.stimulus_model.StimulusModel import repCount [as 别名]
class SearchRunner(AbstractAcquisitionRunner):
    """Handles the presentation of data where changes are allowed to
    be made to the stimulus while running"""
    def __init__(self, *args):
        self._stimulus = StimulusModel()

        super(SearchRunner, self).__init__(*args)

        self.player = FinitePlayer()
        self.save_data = False
        self.set_name = 'explore_1'

        # stimuli_types = get_stimuli_models()
        # self._explore_stimuli = [x() for x in stimuli_types if x.explore]

        # self.delay = Silence()
        # self._stimulus.insertfComponent(self.delay)

    def stimulus(self):
        """Gets a list of all the stimuli this runner has access to. Order
        of the list matches the index order which stimuli can be set by.

        :returns: (subclasses of) list<:class:`AbstractStimulusComponent<sparkle.stim.abstract_component.AbstractStimulusComponent>`>
        """
        return self._stimulus

    def set_calibration(self, attenuations, freqs, frange, calname):
        """See :meth:`AbstractAcquisitionRunner<sparkle.run.abstract_acquisition.AbstractAcquisitionRunner.set_calibration>`"""
        self._stimulus.setCalibration(attenuations, freqs, frange)

    def update_reference_voltage(self):
        """See :meth:`AbstractAcquisitionRunner<sparkle.run.abstract_acquisition.AbstractAcquisitionRunner.update_reference_voltage>`"""
        self._stimulus.setReferenceVoltage(self.caldb, self.calv)

    # def set_delay(self, duration):
    #     self.delay.setDuration(duration)

    # def set_stim_by_index(self, index):
    #     """Sets the stimulus to be generated to the one referenced by index

    #     :param index: index number of stimulus to set from this class's internal list of stimuli
    #     :type index: int
    #     """
    #     # remove any current components
    #     self._stimulus.clearComponents()
    #     self._stimulus.insertComponent(self.delay)
    #     self._stimulus.insertComponent(self._explore_stimuli[index], 0, 1)
    #     signal, atten, overload = self._stimulus.signal()
    #     self.player.set_stim(signal, self._stimulus.samplerate(), attenuation=atten)
    #     self.putnotify('over_voltage', (overload,))
    #     return signal, overload

    def reset_stim(self):
        signal, atten, overload = self._stimulus.signal()
        self.player.set_stim(signal, self._stimulus.samplerate(), attenuation=atten)
        self.putnotify('over_voltage', (overload,))
        self.nreps = self._stimulus.repCount()
        self.irep = 0
        return signal, overload

    def set_current_stim_parameter(self, param, val):
        """Sets a parameter on the current stimulus

        :param param: name of the parameter of the stimulus to set
        :type param: str
        :param val: new value to set the parameter to
        """
        component = self._stimulus.component(0,1)
        component.set(param, val)

    def current_signal(self):
        """Signal of the currently set stimulus

        :returns: numpy.ndarray
        """
        return self._stimulus.signal()

    # def stim_names(self):
    #     """The names of the all the stimuli this class can generate, in order

    #     :returns: list<str>
    #     """
    #     stim_names = []
    #     for stim in self._explore_stimuli:
    #         stim_names.append(stim.name)
    #     return stim_names

    def run(self, interval):
        """See :meth:`AbstractAcquisitionRunner<sparkle.run.abstract_acquisition.AbstractAcquisitionRunner.run>`"""
        self._halt = False
        
        # TODO: some error checking to make sure valid paramenters are set
        if self.save_data:
            # initize data set
            self.current_dataset_name = self.set_name
            self.datafile.init_data(self.current_dataset_name, self.aitimes.shape, mode='open')
            self.set_name = increment_title(self.set_name)

        # save the start time and set last tick to expired, so first
        # acquisition loop iteration executes immediately
#.........这里部分代码省略.........