本文整理匯總了Python中sparkle.stim.stimulus_model.StimulusModel.setReorderFunc方法的典型用法代碼示例。如果您正苦於以下問題：Python StimulusModel.setReorderFunc方法的具體用法？Python StimulusModel.setReorderFunc怎麽用？Python StimulusModel.setReorderFunc使用的例子？那麽, 這裏精選的方法代碼示例或許可以為您提供幫助。您也可以進一步了解該方法所在類sparkle.stim.stimulus_model.StimulusModel的用法示例。
在下文中一共展示了StimulusModel.setReorderFunc方法的1個代碼示例，這些例子默認根據受歡迎程度排序。您可以為喜歡或者感覺有用的代碼點讚，您的評價將有助於係統推薦出更棒的Python代碼示例。
示例1: TestStimModel
# 需要導入模塊: from sparkle.stim.stimulus_model import StimulusModel [as 別名]
# 或者: from sparkle.stim.stimulus_model.StimulusModel import setReorderFunc [as 別名]
#.........這裏部分代碼省略.........
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()
clone = StimulusModel.loadFromTemplate(template)
clone.setReferenceVoltage(100, 0.1)
signals0, docs0, ovld = model.expandedStim()
signals1, docs1, ovld = clone.expandedStim()
assert clone.stimid != 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() == model.repCount()
def test_template_with_auto_params_randomized(self):
self.model.setRepCount(7)
component = PureTone()
component.setIntensity(34)
self.model.insertComponent(component, 0,0)
nsteps = self.add_auto_param(self.model)
self.model.setReorderFunc(order_function('random'), 'random')
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)
assert clone.reorderName == self.model.reorderName
# how to check if signal sets are the same?
assert clone.repCount() == self.model.repCount()
def test_template_tuning_curve(self):
tcf = TCFactory()
model = tcf.create()
model.setReferenceVoltage(100, 0.1)
model.setRepCount(7)
template = model.templateDoc()
clone = StimulusModel.loadFromTemplate(template)
clone.setReferenceVoltage(100, 0.1)
signals0, docs0, ovld = model.expandedStim()
signals1, docs1, ovld = clone.expandedStim()
assert clone.stimid != model.stimid
assert len(signals0) == len(signals1)