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)