def test_get_output_for_cropped(self, crop_layer):
from numpy.testing import assert_array_almost_equal as aeq
x0 = numpy.random.random((5, 3))
x1 = numpy.random.random((4, 2))
inputs = [theano.shared(x0), theano.shared(x1)]
result = crop_layer.get_output_for(inputs).eval()
desired_result = 2 * x0[:4, :2] - x1[:4, :2]
aeq(result, desired_result)
def test_get_output_for_cropped(self, crop_layer):
from numpy.testing import assert_array_almost_equal as aeq
x0 = numpy.random.random((5, 3))
x1 = numpy.random.random((4, 2))
inputs = [theano.shared(x0),
theano.shared(x1)]
result = crop_layer.get_output_for(inputs).eval()
desired_result = 2*x0[:4, :2] - x1[:4, :2]
aeq(result, desired_result)
def test_slice_layer():
from lasagne.layers import SliceLayer, InputLayer, get_output_shape,\
get_output
from numpy.testing import assert_array_almost_equal as aeq
in_shp = (3, 5, 2)
l_inp = InputLayer(in_shp)
l_slice_ax0 = SliceLayer(l_inp, axis=0, indices=0)
l_slice_ax1 = SliceLayer(l_inp, axis=1, indices=slice(3, 5))
l_slice_ax2 = SliceLayer(l_inp, axis=-1, indices=-1)
x = np.arange(np.prod(in_shp)).reshape(in_shp).astype('float32')
x1 = x[0]
x2 = x[:, 3:5]
x3 = x[:, :, -1]
assert get_output_shape(l_slice_ax0) == x1.shape
assert get_output_shape(l_slice_ax1) == x2.shape
assert get_output_shape(l_slice_ax2) == x3.shape
aeq(get_output(l_slice_ax0, x).eval(), x1)
aeq(get_output(l_slice_ax1, x).eval(), x2)
aeq(get_output(l_slice_ax2, x).eval(), x3)
# test slicing None dimension
in_shp = (2, None, 2)
l_inp = InputLayer(in_shp)
l_slice_ax1 = SliceLayer(l_inp, axis=1, indices=slice(3, 5))
assert get_output_shape(l_slice_ax1) == (2, None, 2)
aeq(get_output(l_slice_ax1, x).eval(), x2)
def test_slice_layer():
from lasagne.layers import SliceLayer, InputLayer, get_output_shape,\
get_output
from numpy.testing import assert_array_almost_equal as aeq
in_shp = (3, 5, 2)
l_inp = InputLayer(in_shp)
l_slice_ax0 = SliceLayer(l_inp, axis=0, indices=0)
l_slice_ax1 = SliceLayer(l_inp, axis=1, indices=slice(3, 5))
l_slice_ax2 = SliceLayer(l_inp, axis=-1, indices=-1)
x = np.arange(np.prod(in_shp)).reshape(in_shp).astype('float32')
x1 = x[0]
x2 = x[:, 3:5]
x3 = x[:, :, -1]
assert get_output_shape(l_slice_ax0) == x1.shape
assert get_output_shape(l_slice_ax1) == x2.shape
assert get_output_shape(l_slice_ax2) == x3.shape
aeq(get_output(l_slice_ax0, x).eval(), x1)
aeq(get_output(l_slice_ax1, x).eval(), x2)
aeq(get_output(l_slice_ax2, x).eval(), x3)
# test slicing None dimension
in_shp = (2, None, 2)
l_inp = InputLayer(in_shp)
l_slice_ax1 = SliceLayer(l_inp, axis=1, indices=slice(3, 5))
assert get_output_shape(l_slice_ax1) == (2, None, 2)
aeq(get_output(l_slice_ax1, x).eval(), x2)
def test_mapping_to_physical(self):
"Test mapping to the physical parameterization."
map = generate_mapping('kipping', 'physical')
aeq(map(self.p_k).pv, self.p_p.pv)
def test_mapping_to_orbit(self):
"Test mapping to the orbit parameterization."
aeq(self.p_k.map_to_orbit().pv, self.p_o.pv)
def test_mapping_to_kipping(self):
"Test mapping the physical parameterization to the Kipping parameterization."
map = generate_mapping('physical', 'kipping')
aeq(map(self.p_p).pv, self.p_k.pv)
def test_mapping_to_orbit(self):
"Map the orbit parameterization to itself"
p_o = TransitParameterization('orbit', p_orbit)
aeq(p_o.map_to_orbit().pv, p_o.pv)
def test_minimization(self):
de = DiffEvol(lambda P:np.sum((P-1)**2), [[-2, 2], [-2, 2], [-2, 2]], 40, 100)
aeq(de()[1], np.ones(3), 7, 'DiffEvol fitter fails to find the minimum.')
def test_mapping_to_physical(self):
"Test mapping to the physical parameterization."
map = generate_mapping('kipping', 'physical')
aeq(map(self.p_k).pv, self.p_p.pv)
def test_mapping_to_orbit(self):
"Test mapping to the orbit parameterization."
aeq(self.p_k.map_to_orbit().pv, self.p_o.pv)
def test_mapping_to_kipping(self):
"Test mapping the physical parameterization to the Kipping parameterization."
map = generate_mapping('physical', 'kipping')
aeq(map(self.p_p).pv, self.p_k.pv)
def test_mapping_to_orbit(self):
"Map the orbit parameterization to itself"
p_o = TransitParameterization('orbit', p_orbit)
aeq(p_o.map_to_orbit().pv, p_o.pv)
