vmax_qpl = max(numpy.abs(qpl_fit).max(), numpy.abs(qpl_sym_fit).max())
fig = img.axs[0][1].imshow(dpl_fit, vmin=-vmax_dpl, vmax=vmax_dpl)
img.figure.colorbar(fig, ax=img.axs[0][1])
fig = img.axs[1][1].imshow(dpl_fit_sym, vmin=-vmax_dpl, vmax=vmax_dpl)
img.figure.colorbar(fig, ax=img.axs[1][1])
fig = img.axs[0][2].imshow(qpl_fit, vmin=-vmax_qpl, vmax=vmax_qpl)
img.figure.colorbar(fig, ax=img.axs[0][2])
fig = img.axs[1][2].imshow(qpl_sym_fit, vmin=-vmax_qpl, vmax=vmax_qpl)
img.figure.colorbar(fig, ax=img.axs[1][2])
for i in range(2):
for j in range(3):
if j > 0:
img.del_ticks(i, j, [0, 1])
img.set_label(i, j, 0, "+ G1 -")
img.set_label(i, j, 1, "- G2 +")
img.axs[i][j].set_title(titles[i][j])
pic_name = pic_path + "/%s_%d_compare.png" % (pic_nm, rank)
img.save_img(pic_name)
img.close_img()
# #################################################################################
# # x & y grid, raidus ....
# img = Image_Plot()
# img.subplots(2, 5)
#
import matplotlib.pyplot as plt
from matplotlib import cm
psf_type = "Moffat"
psf_flux = 1
psf_scale = 4
stamp_size = 48
seed = 56525
fq = Fourier_Quad(stamp_size, seed)
img = Image_Plot()
img.subplots(1, 1)
fig = img.axs[0][0].imshow(fq.kx2 + fq.ky2)
img.figure.colorbar(fig, ax=img.axs[0][0])
img.axs[0][0].set_title("$k^2$")
img.del_ticks(0, 0, [0, 1])
img.save_img("E:/kxy.png")
img.show_img()
pst_num = 50
gal_fluxs = [4000, 16000, 32000, 100000]
steps = [0.6, 1, 2, 4]
fq = Fourier_Quad(stamp_size, seed)
max_radius = 7
pts = fq.ran_pts(pst_num, max_radius, step=1)
print(pts)
gal_img = fq.convolve_psf(pts, psf_scale, gal_fluxs[2] / pst_num, psf_type)
noise_1 = fq.draw_noise(0, 1)
dpl_stack[i * xy_bin_num:(i + 1) * xy_bin_num,
j * xy_bin_num:(j + 1) * xy_bin_num] = dpl_sym
dpl_fit_stack[i * xy_bin_num:(i + 1) * xy_bin_num,
j * xy_bin_num:(j + 1) * xy_bin_num] = dpl_sym_fit
qpl_stack[i * xy_bin_num:(i + 1) * xy_bin_num,
j * xy_bin_num:(j + 1) * xy_bin_num] = qpl_sym
qpl_fit_stack[i * xy_bin_num:(i + 1) * xy_bin_num,
j * xy_bin_num:(j + 1) * xy_bin_num] = qpl_sym_fit
img = Image_Plot(fig_x=15, fig_y=15)
img.subplots(1, 1)
fig = img.axs[0][0].imshow(dpl_stack)
img.figure.colorbar(fig, ax=img.axs[0][0])
img.del_ticks(0, 0, [0, 1])
pic_name = pic_path + "/%s_%d_compare_2d_dpl.png" % (pic_nm, rank)
img.save_img(pic_name)
img.close_img()
img = Image_Plot(fig_x=15, fig_y=15)
img.subplots(1, 1)
fig = img.axs[0][0].imshow(dpl_fit_stack)
img.figure.colorbar(fig, ax=img.axs[0][0])
img.del_ticks(0, 0, [0, 1])
pic_name = pic_path + "/%s_%d_compare_2d_dpl_fit.png" % (pic_nm, rank)
img.save_img(pic_name)
img.close_img()
img = Image_Plot(fig_x=15, fig_y=15)
img.subplots(1, 1)
