# we turn the image in a single 1d array image_1d = util.image2array(ngc_data_resized) # map 2d image in 1d data array # we define the shapelet basis set we want the image to decompose in n_max = 150 # choice of number of shapelet basis functions, 150 is a high resolution number, but takes long beta = 10 # shapelet scale parameter (in units of resized pixels) # import the ShapeletSet class from lenstronomy.LightModel.Profiles.shapelets import ShapeletSet shapeletSet = ShapeletSet() # 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(
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)
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)