class TestShapeletSet(object):
"""
class to test Shapelets
"""
def setup(self):
self.shapeletSet = ShapeletSet()
self.shapelets = Shapelets(precalc=False)
self.x, self.y = util.make_grid(10, 0.1, 1)
def test_shapelet_set(self):
"""
:return:
"""
n_max = 2
beta = 1.
amp = [1, 0, 0, 0, 0, 0]
output = self.shapeletSet.function(np.array(1),
np.array(1),
amp,
n_max,
beta,
center_x=0,
center_y=0)
assert output == 0.20755374871029739
input = np.array(0.)
input += output
output = self.shapeletSet.function(self.x,
self.y,
amp,
n_max,
beta,
center_x=0,
center_y=0)
assert output[10] == 0.47957022395315946
output = self.shapeletSet.function(1,
1,
amp,
n_max,
beta,
center_x=0,
center_y=0)
assert output == 0.20755374871029739
n_max = -1
beta = 1.
amp = [1, 0, 0, 0, 0, 0]
output = self.shapeletSet.function(np.array(1),
np.array(1),
amp,
n_max,
beta,
center_x=0,
center_y=0)
assert output == 0
beta = 1.
amp = 1
shapelets = Shapelets(precalc=False, stable_cut=False)
output = shapelets.function(np.array(1),
np.array(1),
amp,
beta,
0,
0,
center_x=0,
center_y=0)
npt.assert_almost_equal(0.2075537487102974, output, decimal=8)
def test_shapelet_basis(self):
num_order = 5
beta = 1
numPix = 10
kernel_list = self.shapeletSet.shapelet_basis_2d(
num_order, beta, numPix)
assert kernel_list[0][4, 4] == 0.43939128946772255
def test_decomposition(self):
"""
:return:
"""
n_max = 2
beta = 10.
deltaPix = 1
amp = np.array([1, 1, 1, 1, 1, 1])
x, y = util.make_grid(100, deltaPix, 1)
input = self.shapeletSet.function(x,
y,
amp,
n_max,
beta,
center_x=0,
center_y=0)
amp_out = self.shapeletSet.decomposition(input,
x,
y,
n_max,
beta,
deltaPix,
center_x=0,
center_y=0)
for i in range(len(amp)):
npt.assert_almost_equal(amp_out[i], amp[i], decimal=4)
def test_function_split(self):
n_max = 2
beta = 10.
deltaPix = 0.1
amp = np.array([1, 1, 1, 1, 1, 1])
x, y = util.make_grid(10, deltaPix, 1)
function_set = self.shapeletSet.function_split(x,
y,
amp,
n_max,
beta,
center_x=0,
center_y=0)
test_flux = self.shapelets.function(x,
y,
amp=1.,
n1=0,
n2=0,
beta=beta,
center_x=0,
center_y=0)
print(np.shape(function_set))
print(np.shape(test_flux))
assert function_set[0][10] == test_flux[10]
def test_interpolate(self):
shapeletsInterp = Shapelets(interpolation=True)
x, y = 0.99, 0
beta = 0.5
flux_full = self.shapelets.function(x,
y,
amp=1.,
n1=0,
n2=0,
beta=beta,
center_x=0,
center_y=0)
flux_interp = shapeletsInterp.function(x,
y,
amp=1.,
n1=0,
n2=0,
beta=beta,
center_x=0,
center_y=0)
npt.assert_almost_equal(flux_interp, flux_full, decimal=10)
def test_hermval(self):
x = np.linspace(0, 2000, 2001)
n_array = [1, 2, 3, 0, 1]
import numpy.polynomial.hermite as hermite
out_true = hermite.hermval(x, n_array)
out_approx = self.shapelets.hermval(x, n_array)
shape_true = out_true * np.exp(-x**2 / 2.)
shape_approx = out_approx * np.exp(-x**2 / 2.)
npt.assert_almost_equal(shape_approx, shape_true, decimal=6)
x = 2
n_array = [1, 2, 3, 0, 1]
out_true = hermite.hermval(x, n_array)
out_approx = self.shapelets.hermval(x, n_array)
npt.assert_almost_equal(out_approx, out_true, decimal=6)
x = 2001
n_array = [1, 2, 3, 0, 1]
out_true = hermite.hermval(x, n_array)
out_approx = self.shapelets.hermval(x, n_array)
shape_true = out_true * np.exp(-x**2 / 2.)
shape_approx = out_approx * np.exp(-x**2 / 2.)
npt.assert_almost_equal(shape_approx, shape_true, decimal=6)
source_cut = circular_mask(pix, (int(pix/2),int(pix/2)),20)*source_ALL #applying a circular mask of 20pix radius around the galaxy
# SHAPELET DECOMPOSITION
x, y = util.make_grid(numPix=numPix, deltapix=deltaPix) # make a coordinate grid
image_1d = util.image2array(source_cut) # we turn the image in a single 1d array
# we define the shapelet basis set we want the image to decompose in
n_max = 50 # choice of number of shapelet basis functions, 150 is a high resolution number, but takes long
beta = 2 # shapelet scale parameter (in units of resized pixels)
# decompose image and return the shapelet coefficients
coeff_ngc = shapeletSet.decomposition(image_1d, x, y, n_max, beta, 1., center_x=0, center_y=0)
# reconstruct the galaxy with the shapelet coefficients
image_reconstructed = shapeletSet.function(x, y, coeff_ngc, n_max, beta, center_x=0, center_y=0)
# turn 1d array back into 2d image
image_reconstructed_2d = util.array2image(image_reconstructed)
#***********************************************************************************************************************************#
# PLOT #
#***********************************************************************************************************************************#
f, axes = plt.subplots(1, 2, figsize=(20, 10), sharex=False, sharey=False)
ax = axes[0]
im = ax.matshow(source_ALL, origin='lower')
ax.set_title("original image")
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
# decompose image and return the shapelet coefficients
coeff_ngc = shapeletSet.decomposition(image_1d,
x,
y,
n_max,
beta,
1.,
center_x=0,
center_y=0)
print(len(coeff_ngc), 'number of coefficients') # number of coefficients
# reconstruct NGC1300 with the shapelet coefficients
image_reconstructed = shapeletSet.function(x,
y,
coeff_ngc,
n_max,
beta,
center_x=0,
center_y=0)
# turn 1d array back into 2d image
image_reconstructed_2d = util.array2image(
image_reconstructed) # map 1d data vector in 2d image
f, axes = plt.subplots(1, 4, figsize=(16, 4), sharex=False, sharey=False)
ax = axes[0]
im = ax.matshow(ngc_square, origin='lower')
ax.set_title("original image")
ax.get_xaxis().set_visible(False)
ax.get_yaxis().set_visible(False)
ax.autoscale(False)
class TestShapeletSet(object):
"""
class to test Shapelets
"""
def setup(self):
self.shapeletSet = ShapeletSet()
self.shapelets = Shapelets(precalc=False)
self.x, self.y = util.make_grid(10, 0.1, 1)
def test_shapelet_set(self):
"""
:return:
"""
n_max = 2
beta = 1.
amp = [1, 0, 0, 0, 0, 0]
output = self.shapeletSet.function(np.array(1),
np.array(1),
amp,
n_max,
beta,
center_x=0,
center_y=0)
assert output == 0.20755374871029739
input = np.array(0.)
input += output
output = self.shapeletSet.function(self.x,
self.y,
amp,
n_max,
beta,
center_x=0,
center_y=0)
assert output[10] == 0.47957022395315946
output = self.shapeletSet.function(1,
1,
amp,
n_max,
beta,
center_x=0,
center_y=0)
assert output == 0.20755374871029739
def test_shapelet_basis(self):
num_order = 5
beta = 1
numPix = 10
kernel_list = self.shapeletSet.shapelet_basis_2d(
num_order, beta, numPix)
assert kernel_list[0][4, 4] == 0.43939128946772255
def test_decomposition(self):
"""
:return:
"""
n_max = 2
beta = 10.
deltaPix = 1
amp = np.array([1, 1, 1, 1, 1, 1])
x, y = util.make_grid(100, deltaPix, 1)
input = self.shapeletSet.function(x,
y,
amp,
n_max,
beta,
center_x=0,
center_y=0)
amp_out = self.shapeletSet.decomposition(input,
x,
y,
n_max,
beta,
deltaPix,
center_x=0,
center_y=0)
for i in range(len(amp)):
npt.assert_almost_equal(amp_out[i], amp[i], decimal=4)
def test_function_split(self):
n_max = 2
beta = 10.
deltaPix = 0.1
amp = np.array([1, 1, 1, 1, 1, 1])
x, y = util.make_grid(10, deltaPix, 1)
function_set = self.shapeletSet.function_split(x,
y,
amp,
n_max,
beta,
center_x=0,
center_y=0)
test_flux = self.shapelets.function(x,
y,
amp=1.,
n1=0,
n2=0,
beta=beta,
center_x=0,
center_y=0)
print(np.shape(function_set))
print(np.shape(test_flux))
assert function_set[0][10] == test_flux[10]
def test_interpolate(self):
shapeletsInterp = Shapelets(interpolation=True)
x, y = 0.99, 0
beta = 0.5
flux_full = self.shapelets.function(x,
y,
amp=1.,
n1=0,
n2=0,
beta=beta,
center_x=0,
center_y=0)
flux_interp = shapeletsInterp.function(x,
y,
amp=1.,
n1=0,
n2=0,
beta=beta,
center_x=0,
center_y=0)
npt.assert_almost_equal(flux_interp, flux_full, decimal=10)