Loading DataReductionGIANOB/Frame_Gofio.py +1 −1 Changes for DataReductionGIANOB/Frame_Gofio.py: 1 added line, 1 removed line. Original line number Diff line number Diff line Loading @@ -1629,7 +1629,7 @@ class Frame_Gofio: norm = mcolors.Normalize(vmin=np.min(am), vmax=np.max(am)) for i in range(nimages): color = cmap(norm(am[i])) print(f"{list_file[i]}: range wl [{np.min(curr_image.wl_cal)}, {np.max(curr_image.wl_cal)}]") print(f"SPC: {i}, range wl [{np.min(curr_image.wl_cal)}, {np.max(curr_image.wl_cal)}]; SNR: {np.sqrt(np.mean(data[i, :, :]))}, file {list_file[i]}") # sqrate root to obtain the SNR from the flux ax.plot(np.mean(wlen[i, :, :], axis=1), np.sqrt(np.mean(data[i, :, :], axis=1)), color=color) # Add labels, title Loading Loading
DataReductionGIANOB/Frame_Gofio.py +1 −1 Changes for DataReductionGIANOB/Frame_Gofio.py: 1 added line, 1 removed line. Original line number Diff line number Diff line Loading @@ -1629,7 +1629,7 @@ class Frame_Gofio: norm = mcolors.Normalize(vmin=np.min(am), vmax=np.max(am)) for i in range(nimages): color = cmap(norm(am[i])) print(f"{list_file[i]}: range wl [{np.min(curr_image.wl_cal)}, {np.max(curr_image.wl_cal)}]") print(f"SPC: {i}, range wl [{np.min(curr_image.wl_cal)}, {np.max(curr_image.wl_cal)}]; SNR: {np.sqrt(np.mean(data[i, :, :]))}, file {list_file[i]}") # sqrate root to obtain the SNR from the flux ax.plot(np.mean(wlen[i, :, :], axis=1), np.sqrt(np.mean(data[i, :, :], axis=1)), color=color) # Add labels, title Loading