def testInitLinearModel(self):
self.assertRaises(ValueError, lambda: LinearModel(self.regressorList, ["only 1 name"]))
linearModel = LinearModel(self.regressorList, self.regressorNames)
self.assertTrue(linearModel.nParameters() == self.nParameters)
self.assertTrue(linearModel.regressorNames() == self.regressorNames)
self.assertTrue(linearModel.nObservations() == self.nObservations)
def testInitLinearModel(self):
self.assertRaises(ValueError, lambda : LinearModel(self.regressorList, ["only 1 name"]))
linearModel = LinearModel(self.regressorList, self.regressorNames)
self.assertTrue(linearModel.nParameters() == self.nParameters)
self.assertTrue(linearModel.regressorNames() == self.regressorNames)
self.assertTrue(linearModel.nObservations() == self.nObservations)
def testCopyLinearModel(self):
linearModel = LinearModel(self.regressorList, self.regressorNames)
linearModel2 = linearModel.copy()
self.assertTrue(linearModel2.nParameters() == self.nParameters)
self.assertTrue(np.alltrue(linearModel2.designMatrix() == self.designMatrix))
self.assertTrue(linearModel2.regressorNames() == self.regressorNames)
self.assertTrue(id(linearModel2.designMatrix()) != id(linearModel.designMatrix()))
self.assertTrue(id(linearModel2.regressorNames()) != id(linearModel.regressorNames()))
def testCopyLinearModel(self):
linearModel = LinearModel(self.regressorList, self.regressorNames)
linearModel2 = linearModel.copy()
self.assertTrue(linearModel2.nParameters() == self.nParameters)
self.assertTrue(np.alltrue(linearModel2.designMatrix() == self.designMatrix))
self.assertTrue(linearModel2.regressorNames() == self.regressorNames)
self.assertTrue(id(linearModel2.designMatrix()) != id(linearModel.designMatrix()))
self.assertTrue(id(linearModel2.regressorNames()) != id(linearModel.regressorNames()))
def testAddLinearModel(self):
linearModel = LinearModel(self.regressorList, self.regressorNames)
linearModel2 = LinearModel(self.RegressorList2, self.RegressorNames2)
linearModel = linearModel + linearModel2
self.assertTrue(linearModel.nParameters() == self.newnParameters)
self.assertTrue(np.alltrue(linearModel.designMatrix() == self.newModelMatrix))
self.assertTrue(linearModel.regressorNames() == self.regressorNames + self.RegressorNames2)
self.assertTrue(linearModel._covMatrixObserv == None)
self.assertRaises(TypeError, lambda lm : lm + 1.0, linearModel)
self.assertRaises(ValueError, lambda x,y : LinearModel(x,y) + LinearModel(x[:-1,:],y),
self.designMatrix, self.regressorNames)
def testAddLinearModel(self):
linearModel = LinearModel(self.regressorList, self.regressorNames)
linearModel2 = LinearModel(self.RegressorList2, self.RegressorNames2)
linearModel = linearModel + linearModel2
self.assertTrue(linearModel.nParameters() == self.newnParameters)
self.assertTrue(np.alltrue(linearModel.designMatrix() == self.newModelMatrix))
self.assertTrue(linearModel.regressorNames() == self.regressorNames + self.RegressorNames2)
self.assertTrue(linearModel._covMatrixObserv == None)
self.assertRaises(TypeError, lambda lm: lm + 1.0, linearModel)
self.assertRaises(
ValueError,
lambda x, y: LinearModel(x, y) + LinearModel(x[:-1, :], y),
self.designMatrix,
self.regressorNames,
)
