In [1]:

    

%matplotlib inline
import matplotlib.pyplot as plt
from ds9norm import DS9Normalize
from astropy.io import fits

plt.rcParams['figure.figsize'] = (12, 12)
plt.rcParams['figure.dpi'] = 300
plt.rcParams['image.cmap'] = 'gist_heat'


    

In [3]:

    

data = fits.getdata('M51.fits')
figure, axs = plt.subplots(ncols=4, nrows=4, squeeze=False, tight_layout=True)

for ax, stretch in zip(axs[0], ['linear', 'sqrt', 'arcsinh', 'log']):
    ax.imshow(data, norm=DS9Normalize(stretch=stretch))
    ax.set_title(stretch)

for ax, contrast in zip(axs[1], [0.5, 1, 2, -1]):
    ax.imshow(data, norm=DS9Normalize(contrast=contrast))
    ax.set_title('Contrast = %0.1f' % contrast)

for ax, bias in zip(axs[2], [.2, .5, .8, .9]):
    ax.imshow(data, norm=DS9Normalize(bias=bias))
    ax.set_title('Bias = %0.1f' % bias)
    
for ax, (lo, hi) in zip(axs[3], [(0, 100), (1, 99), (5, 95), (10, 90)]):
    im = ax.imshow(data, norm=DS9Normalize(clip_lo=lo, clip_hi=hi))
    ax.set_title('%i-%i%%' % (lo, hi))
    
for ax in axs.ravel():
    ax.set_xticks([])
    ax.set_yticks([])
    
plt.savefig("gallery.png")