def test_doublegaussian(self):
t = np.linspace(0,100)
dt = equations.DoubleGaussian()
assert dt.parameters == {'midpoint_2': 0.0, 'midpoint_1': 0.0,
'amp_2': 1.0, 'amp_1': 0.5, 'sigma_2': 10.0,
'sigma_1': 20.0}
np.testing.assert_allclose( dt.evaluate(t)[10:], dt.evaluate(t[10:]))
def test_doublegaussian(self):
dt = equations.DoubleGaussian()
assert dt.parameters == {
'midpoint_2': 0.0,
'midpoint_1': 0.0,
'amp_2': 1.0,
'amp_1': 0.5,
'sigma_2': 10.0,
'sigma_1': 20.0
}
def test_spatialpattern(self):
dt = patterns.SpatialPattern()
dt.spatial = equations.DoubleGaussian()
dt.configure_space(numpy.arange(100).reshape((10, 10)))
dt.configure()
summary = dt.summary_info()
assert summary['Type'] == 'SpatialPattern'
assert dt.space.shape == (10, 10)
assert isinstance(dt.spatial, equations.DoubleGaussian)
assert dt.spatial_pattern.shape, (10, 1)
def test_spatialpattern(self):
dt = patterns.SpatialPattern()
dt.spatial = equations.DoubleGaussian()
dt.spatial_pattern = numpy.arange(100).reshape((10, 10))
dt.configure_space(numpy.arange(100).reshape((10, 10)))
dt.configure()
summary = dt.summary_info
self.assertEqual(summary['Type'], 'SpatialPattern')
self.assertEqual(dt.space.shape, (10, 10))
self.assertTrue(isinstance(dt.spatial, equations.DoubleGaussian))
self.assertTrue(dt.spatial_pattern.shape, (10, 1))
def test_doublegaussian(self):
dt = equations.DoubleGaussian()
self.assertEqual(
dt.parameters, {
'midpoint_2': 0.0,
'midpoint_1': 0.0,
'amp_2': 1.0,
'amp_1': 0.5,
'sigma_2': 10.0,
'sigma_1': 20.0
})
self.assertEqual(
dt.ui_equation, '(amp_1 * 2.71**(-((var-midpoint_1)**2 / '
'(2.0 * sigma_1**2)))) - (amp_2 * 2.71**(-((var-midpoint_2)**2 / (2.0 * sigma_2**2))))'
)
