def testMinima(self):
"""
Test the correct computation of all local minima
for a bistable potential.
"""
#Predict result
x0, curv, mask = fixedPoints(
numpy.array([self.LAMBDA]), kappa1=self.kappa1
)
expectedResult = DC.FieldContainer(
numpy.extract(curv[0]>0,x0[0]),
unit = self.xField.unit,
longname = 'position of the local minima of electric potential',
shortname = 'x_0'
)
#Retrieve result from worker
w = MRA.MRA(None)
w.paramScale.value = "1.0m"
result = w.mra(self.V)
#Testing
i = numpy.array(range(self.n))
index = numpy.logical_and(self.u > 0.7, self.u < 0.72)
index = MRA.findMinima(self.V.data, 5)
numpy.testing.assert_array_almost_equal(
result[r'x_{min}'].data, expectedResult.data, 4
)
def testMinima(self):
"""
Test the correct computation of all local minima
for a bistable potential.
"""
#Predict result
x0, curv, mask = fixedPoints(
numpy.array([self.LAMBDA]), kappa1=self.kappa1
)
expectedResult = DC.FieldContainer(
numpy.extract(curv[0]>0,x0[0]),
unit = self.xField.unit,
longname = 'position of the local minima of electric potential',
shortname = 'x_0'
)
#Retrieve result from worker
w = MRA.MRA(None)
w.paramScale.value = "1.0m"
result = w.mra(self.V)
#Testing
i = numpy.array(range(self.n))
index = numpy.logical_and(self.u > 0.7, self.u < 0.72)
index = MRA.findMinima(self.V.data, 5)
numpy.testing.assert_array_almost_equal(
result[r'x_{min}'].data, expectedResult.data, 4
)
def testPlateau(self):
"""Test the correct computation of a local minimum."""
self.assertEqual(numpy.array([3]), MRA.findMinima(self.p, 5)[0])
def testFindMinimum(self):
"""Test the correct computation of a local minimum."""
self.assertEqual(numpy.argmin(self.a), MRA.findMinima(self.a, 5)[0])
def testPlateau(self):
"""Test the correct computation of a local minimum."""
self.assertEqual(numpy.array([3]), MRA.findMinima(self.p, 5)[0])
def testFindMinimum(self):
"""Test the correct computation of a local minimum."""
self.assertEqual(numpy.argmin(self.a), MRA.findMinima(self.a, 5)[0])
