#!/usr/bin/env python # coding: utf-8 # In[1]: from astropy.io import fits import numpy as np from astropy.visualization import simple_norm import pylab as plt from astropy import wcs import os from reproject import reproject_interp import reproject import PIL #import pyavm import shutil # In[2]: def save_rgb(img, filename, avm=None, flip=-1): img = (img*256) img[img<0] = 0 img[img>255] = 255 img = img.astype('uint8') img = PIL.Image.fromarray(img[::flip,:,:]) img.save(filename) if avm is not None: base = os.path.basename(filename) dir = os.path.dirname(filename) avmname = os.path.join(dir, 'avm_'+base) avm.embed(filename, avmname) shutil.move(avmname, filename) return img # In[17]: image_filenames_pipe ={ "f150w": "/orange/adamginsburg/jwst/sgrb2/NB/F150W/pipeline/jw05365-o001_t001_nircam_clear-f150w-merged_i2d.fits", "f182m": "/orange/adamginsburg/jwst/sgrb2/NB/F182M/pipeline/jw05365-o001_t001_nircam_clear-f182m-merged_i2d.fits", "f187n": "/orange/adamginsburg/jwst/sgrb2/NB/F187N/pipeline/jw05365-o001_t001_nircam_clear-f187n-merged_i2d.fits", "f210m": "/orange/adamginsburg/jwst/sgrb2/NB/F210M/pipeline/jw05365-o001_t001_nircam_clear-f210m-merged_i2d.fits", "f212n": "/orange/adamginsburg/jwst/sgrb2/NB/F212N/pipeline/jw05365-o001_t001_nircam_clear-f212n-merged_i2d.fits", "f300m": "/orange/adamginsburg/jwst/sgrb2/NB/F300M/pipeline/jw05365-o001_t001_nircam_clear-f300m-merged_i2d.fits", "f360m": "/orange/adamginsburg/jwst/sgrb2/NB/F360M/pipeline/jw05365-o001_t001_nircam_clear-f360m-merged_i2d.fits", "f405n": "/orange/adamginsburg/jwst/sgrb2/NB/F405N/pipeline/jw05365-o001_t001_nircam_clear-f405n-merged_i2d.fits", "f410m": "/orange/adamginsburg/jwst/sgrb2/NB/F410M/pipeline/jw05365-o001_t001_nircam_clear-f410m-merged_i2d.fits", "f466n": "/orange/adamginsburg/jwst/sgrb2/NB/F466N/pipeline/jw05365-o001_t001_nircam_clear-f466n-merged_i2d.fits", # weird, the filename is different from what is downloaded with the STScI pipeline... "f480m": "/orange/adamginsburg/jwst/sgrb2/NB/F480M/pipeline/jw05365-o001_t001_nircam_clear-f480m-merged_i2d.fits", "f770w": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o002_t002_miri_f770w/jw05365-o002_t002_miri_f770w_i2d.fits", "f1280w": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o002_t002_miri_f1280w/jw05365-o002_t002_miri_f1280w_i2d.fits", "f2550w": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o002_t002_miri_f2550w/jw05365-o002_t002_miri_f2550w_i2d.fits", #"f770w": "/orange/adamginsburg/jwst/sgrb2/NB/data_reprojected/jw05365-o002_t002_miri_f770w_i2d_pipeline_v0.1_reprj_f466.fits", #"f1280w": "/orange/adamginsburg/jwst/sgrb2/NB/data_reprojected/jw05365-o002_t002_miri_f1280w_i2d_pipeline_v0.1_reprj_f466.fits", #"f2550w": "/orange/adamginsburg/jwst/sgrb2/NB/data_reprojected/jw05365-o002_t002_miri_f2550w_i2d_pipeline_v0.1_reprj_f466.fits", } image_sub_filenames_pipe = { "f405n-f410m": "/orange/adamginsburg/jwst/sgrb2/NB/F405_minus_F410cont_pipeline_v0.1.fits", "f410m-f405n": "/orange/adamginsburg/jwst/sgrb2/NB/F410_minus_F405_fractional_bandwidth_pipeline_v0.1.fits", "f212n-f210m": "/orange/adamginsburg/jwst/sgrb2/NB/F212_minus_F210cont_pipeline_v0.1.fits", "f187n-f182m": "/orange/adamginsburg/jwst/sgrb2/NB/F187_minus_F182cont.fits", } new_basepath = '/orange/adamginsburg/jwst/sgrb2/NB/data_reprojected/' repr466_image_filenames = {x: y.replace("i2d", "i2d_pipeline_v0.1_reprj_f466") for x,y in image_filenames_pipe.items()} repr466_image_filenames = {x: (new_basepath+os.path.basename(y)) for x,y in repr466_image_filenames.items()} repr466_image_sub_filenames = {x: y.replace("i2d", "i2d_reprj_f466") for x,y in image_sub_filenames_pipe.items()} repr466_image_sub_filenames = {x: (new_basepath+os.path.basename(y)) for x,y in repr466_image_sub_filenames.items()} # In[19]: tgt_header = fits.getheader(image_filenames_pipe['f466n'], ext=('SCI', 1)) #tgt_header = fits.getheader('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f480m/jw05365-o001_t001_nircam_clear-f480m_i2d.fits', ext=('SCI', 1)) #wcs.WCS(tgt_header) #AVM = pyavm.AVM.from_header(tgt_header) # In[20]: for filtername in image_sub_filenames_pipe: if not os.path.exists(repr466_image_sub_filenames[filtername]): print(f"Reprojecting {filtername} {image_sub_filenames_pipe[filtername]} to {repr466_image_sub_filenames[filtername]}") result,_ = reproject_interp(image_sub_filenames_pipe[filtername], tgt_header, hdu_in='SCI') hdu = fits.PrimaryHDU(data=result, header=tgt_header) hdu.writeto(repr466_image_sub_filenames[filtername], overwrite=True) # In[21]: for filtername in image_filenames_pipe: if not os.path.exists(repr466_image_filenames[filtername]): print(f"Reprojecting {filtername} {image_filenames_pipe[filtername]} to {repr466_image_filenames[filtername]}") result,_ = reproject_interp(image_filenames_pipe[filtername], tgt_header, hdu_in='SCI') hdu = fits.PrimaryHDU(data=result, header=tgt_header) hdu.writeto(repr466_image_filenames[filtername], overwrite=True) # In[ ]: # In[7]: image_filenames ={ "f150w": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f150w/jw05365-o001_t001_nircam_clear-f150w_i2d.fits", "f182m": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f182m/jw05365-o001_t001_nircam_clear-f182m_i2d.fits", "f187n": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f187n/jw05365-o001_t001_nircam_clear-f187n_i2d.fits", "f210m": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f210m/jw05365-o001_t001_nircam_clear-f210m_i2d.fits", "f212n": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f212n/jw05365-o001_t001_nircam_clear-f212n_i2d.fits", "f300m": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f300m/jw05365-o001_t001_nircam_clear-f300m_i2d.fits", "f360m": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f360m/jw05365-o001_t001_nircam_clear-f360m_i2d.fits", "f405n": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_f405n-f444w/jw05365-o001_t001_nircam_f405n-f444w_i2d.fits", "f410m": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f410m/jw05365-o001_t001_nircam_clear-f410m_i2d.fits", "f466n": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_f444w-f466n/jw05365-o001_t001_nircam_f444w-f466n_i2d.fits", "f480m": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f480m/jw05365-o001_t001_nircam_clear-f480m_i2d.fits", "f770w": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o002_t002_miri_f770w/jw05365-o002_t002_miri_f770w_i2d.fits", "f1280w": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o002_t002_miri_f1280w/jw05365-o002_t002_miri_f1280w_i2d.fits", "f2550w": "/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o002_t002_miri_f2550w/jw05365-o002_t002_miri_f2550w_i2d.fits", } image_sub_filenames = { "f182m-f187n": "/orange/adamginsburg/jwst/sgrb2/NB/F182_minus_F187_fractional_bandwidth.fits", "f187n-f182m": "/orange/adamginsburg/jwst/sgrb2/NB/F187_minus_F182cont.fits", "f210m-f212n": "/orange/adamginsburg/jwst/sgrb2/NB/F210_minus_F212_fractional_bandwidth.fits", "f212n-f210m": "/orange/adamginsburg/jwst/sgrb2/NB/F212_minus_F210cont.fits", "f405n-f410m": "/orange/adamginsburg/jwst/sgrb2/NB/F405_minus_F410cont.fits", "f410m-f405n": "/orange/adamginsburg/jwst/sgrb2/NB/F410_minus_F405_fractional_bandwidth.fits", # TODO "f466n-f410m": "/orange/adamginsburg/jwst/sgrb2/NB/F466_minus_F410.fits", "f466n-f405n": "/orange/adamginsburg/jwst/sgrb2/NB/F466_minus_F405.fits", "f466n-f480m": "/orange/adamginsburg/jwst/sgrb2/NB/F466_minus_F480cont.fits", "f480m-f466n": "/orange/adamginsburg/jwst/sgrb2/NB/F480_minus_F466_fractional_bandwidth.fits", "f480m-f300m": "/orange/adamginsburg/jwst/sgrb2/NB/F480-F300.fits", "f480m-f360m": "/orange/adamginsburg/jwst/sgrb2/NB/F480M-F360M_no_bandpass_correction.fits", } new_basepath = '/orange/adamginsburg/jwst/sgrb2/NB/data_reprojected/' repr480_image_filenames = {x: y.replace("i2d", "i2d_reprj_f480") for x,y in image_filenames.items()} repr480_image_filenames = {x: (new_basepath+os.path.basename(y)) for x,y in repr480_image_filenames.items()} repr480_image_sub_filenames = {x: y.replace("i2d", "i2d_reprj_f480") for x,y in image_sub_filenames.items()} repr480_image_sub_filenames = {x: (new_basepath+os.path.basename(y)) for x,y in repr480_image_sub_filenames.items()} # In[10]: import pyavm # In[ ]: tgt_header = fits.getheader(image_filenames['f480m'], ext=('SCI', 1)) tgt_header = fits.getheader('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f480m/jw05365-o001_t001_nircam_clear-f480m_i2d.fits', ext=('SCI', 1)) #wcs.WCS(tgt_header) AVM = pyavm.AVM.from_header(tgt_header) # In[12]: for filtername in image_filenames: if not os.path.exists(repr480_image_filenames[filtername]): print(f"Reprojecting {filtername} {image_filenames[filtername]} to {repr480_image_filenames[filtername]}") result,_ = reproject.reproject_interp(image_filenames[filtername], tgt_header, hdu_in='SCI') hdu = fits.PrimaryHDU(data=result, header=tgt_header) hdu.writeto(repr480_image_filenames[filtername], overwrite=True) # In[13]: for filtername in image_sub_filenames: if not os.path.exists(repr480_image_sub_filenames[filtername]): print(f"Reprojecting {filtername} {image_sub_filenames[filtername]} to {repr480_image_sub_filenames[filtername]}") result,_ = reproject.reproject_interp(image_sub_filenames[filtername], tgt_header, hdu_in='SCI') hdu = fits.PrimaryHDU(data=result, header=tgt_header) hdu.writeto(repr480_image_sub_filenames[filtername], overwrite=True) # In[14]: rgb = np.array([ fits.getdata(repr480_image_filenames['f210m']), fits.getdata(repr480_image_filenames['f300m']), fits.getdata(repr480_image_filenames['f360m']) ]).swapaxes(0,2).swapaxes(0,1) # In[15]: rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,0]), simple_norm(rgb[:,:,1], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,1]), simple_norm(rgb[:,:,2], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) plt.figure(figsize=(24,10)) plt.imshow(rgb_scaled, origin='lower') plt.xticks([]); plt.yticks([]); # In[15]: # rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,0]), # simple_norm(rgb[:,:,1], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,1]), # simple_norm(rgb[:,:,2], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) # plt.figure(figsize=(24,10)) # plt.imshow(rgb_scaled, origin='lower') # plt.xticks([]); # plt.yticks([]); # In[16]: png_path = '/orange/adamginsburg/jwst/sgrb2/pngs' save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_210-300-360.png', avm=AVM) # In[17]: rgb2 = np.array([ fits.getdata(repr480_image_filenames['f210m']), fits.getdata(repr480_image_filenames['f300m']), fits.getdata(repr480_image_filenames['f480m']) ]).swapaxes(0,2).swapaxes(0,1) # In[18]: rgb_scaled2 = np.array([simple_norm(rgb2[:,:,0], stretch='asinh', min_percent=1, max_percent=99)(rgb2[:,:,0]), simple_norm(rgb2[:,:,1], stretch='asinh', min_percent=1, max_percent=99)(rgb2[:,:,1]), simple_norm(rgb2[:,:,2], stretch='asinh', min_percent=1, max_percent=99)(rgb2[:,:,2])]).swapaxes(0,2).swapaxes(0,1) plt.figure(figsize=(24,10)) plt.imshow(rgb_scaled2, origin='lower') plt.xticks([]); plt.yticks([]); # In[19]: rgb_scaled.shape # In[20]: # save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_210-300-480.png', avm=AVM) # In[21]: # rgb3 = np.array([ # fits.getdata(repr480_image_filenames['f480m']), # fits.getdata(repr480_image_filenames['f300m']), # fits.getdata(repr480_image_filenames['f210m']), # ]).swapaxes(0,2).swapaxes(0,1) # save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_480-300-210.png', avm=AVM) # In[ ]: # In[ ]: # In[22]: F150W = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f150w/jw05365-o001_t001_nircam_clear-f150w_i2d.fits') F182M = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f182m/jw05365-o001_t001_nircam_clear-f182m_i2d.fits') F187N = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f187n/jw05365-o001_t001_nircam_clear-f187n_i2d.fits') F210M = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f210m/jw05365-o001_t001_nircam_clear-f210m_i2d.fits') F212N = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f212n/jw05365-o001_t001_nircam_clear-f212n_i2d.fits') F300M = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f300m/jw05365-o001_t001_nircam_clear-f300m_i2d.fits') F360M = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f360m/jw05365-o001_t001_nircam_clear-f360m_i2d.fits') F405N = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_f405n-f444w/jw05365-o001_t001_nircam_f405n-f444w_i2d.fits') F410M = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f410m/jw05365-o001_t001_nircam_clear-f410m_i2d.fits') F466N = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_f444w-f466n/jw05365-o001_t001_nircam_f444w-f466n_i2d.fits') F480M = fits.open('/orange/adamginsburg/jwst/sgrb2/mastDownload/JWST/jw05365-o001_t001_nircam_clear-f480m/jw05365-o001_t001_nircam_clear-f480m_i2d.fits') # In[23]: import reproject # In[ ]: # In[ ]: # In[24]: Bra = fits.open('/orange/adamginsburg/jwst/sgrb2/NB/F405_minus_F410cont.fits') # In[25]: Bra['SCI'].data.shape # In[26]: F480M['SCI'].data.shape # In[27]: F410M['SCI'].data.shape # In[28]: F360M['SCI'].data.shape # In[29]: F480data = F480M['SCI'].data[:2507,:5649] F410data = F410M['SCI'].data[:2507,:5649] F300data = F300M['SCI'].data[:2507,:5649] Bradata = Bra['SCI'].data[:2507,:5649] F360data = F360M['SCI'].data[:2507,:5649] F466data = F466N['SCI'].data[:2507,:5649] #F405data = F405N['SCI'].data[:2507,:5650] # In[30]: rgb = np.array([F466data, F410data, F300data]).swapaxes(0,2).swapaxes(0,1) # In[31]: # rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='asinh', min_percent=1, max_percent=98)(rgb[:,:,0]), # simple_norm(rgb[:,:,1], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,1]), # simple_norm(rgb[:,:,2], stretch='asinh', min_percent=1, max_percent=98)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) # plt.figure(figsize=(24,10)) # plt.imshow(rgb_scaled, origin='lower') # plt.xticks([]); # plt.yticks([]); # In[32]: #save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_466-410-300.png', avm=AVM) # In[33]: rgb = np.array([F480data, F410data, F360data]).swapaxes(0,2).swapaxes(0,1) # In[ ]: # In[34]: # rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='asinh', min_percent=1, max_percent=98.5)(rgb[:,:,0]), # simple_norm(rgb[:,:,1], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,1]), # simple_norm(rgb[:,:,2], stretch='asinh', min_percent=1, max_percent=98.5)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) # plt.figure(figsize=(12,5)) # plt.imshow(rgb_scaled, origin='lower') # plt.xticks([]); # plt.yticks([]); # In[35]: save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_480-410-360.png', avm=AVM) # In[40]: F480data.shape, fits.getdata(repr480_image_filenames['f187n']).shape # In[58]: rgb = np.array([fits.getdata(repr480_image_filenames['f480m']), fits.getdata(repr480_image_filenames['f405n']), fits.getdata(repr480_image_filenames['f187n'])]).swapaxes(0,2).swapaxes(0,1) save_rgb(rgb/np.nanmedian(rgb), f'{png_path}/SgrB2_RGB_480-405-187.png', avm=AVM) # In[62]: rgb = np.array([fits.getdata(repr480_image_filenames['f480m']), fits.getdata(repr480_image_filenames['f405n']), fits.getdata(repr480_image_filenames['f187n'])]).swapaxes(0,2).swapaxes(0,1) rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='asinh', min_percent=1, max_percent=97)(rgb[:,:,0]), simple_norm(rgb[:,:,1], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,1]), simple_norm(rgb[:,:,2], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_480-405-187_scaled.png', avm=AVM) # In[43]: # list of filters from long to short so it's in RGB order filternames = list(image_filenames.keys())[::-1] for f1, f2, f3 in zip (filternames, filternames[1:], filternames[2:]): print(f1,f2,f3) rgb = np.array([ fits.getdata(repr480_image_filenames[f1]), fits.getdata(repr480_image_filenames[f2]), fits.getdata(repr480_image_filenames[f3]), ]).swapaxes(0,2).swapaxes(0,1) rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,0]), simple_norm(rgb[:,:,1], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,1]), simple_norm(rgb[:,:,2], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_{f1[1:4]}-{f2[1:4]}-{f3[1:4]}.png', avm=AVM) # In[44]: filternames_sub = list(image_sub_filenames.keys())[::-1] for f1, f2, f3 in zip (filternames_sub, filternames_sub[1:], filternames_sub[2:]): print(f1,f2,f3) rgb = np.array([ fits.getdata(repr480_image_sub_filenames[f1]), fits.getdata(repr480_image_sub_filenames[f2]), fits.getdata(repr480_image_sub_filenames[f3]), ]).swapaxes(0,2).swapaxes(0,1) rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='asinh', min_percent=5, max_percent=99)(rgb[:,:,0]), simple_norm(rgb[:,:,1], stretch='asinh', min_percent=5, max_percent=99)(rgb[:,:,1]), simple_norm(rgb[:,:,2], stretch='asinh', min_percent=5, max_percent=99)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_{f1}_{f2}_{f3}.png', avm=AVM) # In[45]: rgb.shape, rgb_scaled.shape # In[60]: rgb = np.array([fits.getdata(repr480_image_filenames['f480m']), fits.getdata(repr480_image_sub_filenames['f405n-f410m']), fits.getdata(repr480_image_sub_filenames['f187n-f182m'])]).swapaxes(0,2).swapaxes(0,1) save_rgb(rgb/np.nanmedian(rgb), f'{png_path}/SgrB2_RGB_480-405m410-187m182.png', avm=AVM) # In[63]: rgb = np.array([fits.getdata(repr480_image_filenames['f480m']), fits.getdata(repr480_image_sub_filenames['f405n-f410m']), fits.getdata(repr480_image_sub_filenames['f187n-f182m'])]).swapaxes(0,2).swapaxes(0,1) rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='asinh', min_percent=1, max_percent=97)(rgb[:,:,0]), simple_norm(rgb[:,:,1], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,1]), simple_norm(rgb[:,:,2], stretch='asinh', min_percent=1, max_percent=99)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_480-405m410-187m182_scaled.png', avm=AVM) # In[47]: repr480_image_sub_filenames rgb = np.array([fits.getdata(repr480_image_sub_filenames['f480m-f360m']), fits.getdata(repr480_image_sub_filenames['f405n-f410m']), fits.getdata(repr480_image_sub_filenames['f187n-f182m'])]).swapaxes(0,2).swapaxes(0,1) rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='asinh', min_percent=5, max_percent=99)(rgb[:,:,0]), simple_norm(rgb[:,:,1], stretch='asinh', min_percent=5, max_percent=99)(rgb[:,:,1]), simple_norm(rgb[:,:,2], stretch='asinh', min_percent=5, max_percent=99)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_480m360-405m410-187m182_scaled.png', avm=AVM) rgb_scaled = np.array([simple_norm(rgb[:,:,0], stretch='log', min_percent=5, max_percent=99)(rgb[:,:,0]), simple_norm(rgb[:,:,1], stretch='log', min_percent=5, max_percent=99)(rgb[:,:,1]), simple_norm(rgb[:,:,2], stretch='log', min_percent=5, max_percent=99)(rgb[:,:,2])]).swapaxes(0,2).swapaxes(0,1) save_rgb(rgb_scaled, f'{png_path}/SgrB2_RGB_480m360-405m410-187m182_logscaled.png', avm=AVM)