%pylab inline
import matplotlib.image as mpimg
from scipy import ndimage

img1 = mpimg.imread('1125150738.jpg')
img1 = img1[800:1400,1000:3500,0]
img1 = ndimage.rotate(img1,-3.5)

img2 = mpimg.imread('1125150738a.jpg')
img2 = img2[800:1400,1000:3500,0]
img2 = ndimage.rotate(img2,-3.5)

img1sum = img1[350:450,500:2100].sum(axis=0)
img2sum = img2[400:500,500:2100].sum(axis=0)

fig, ((ax1, ax2),(ax3, ax4)) = plt.subplots(2,2,figsize=(10,4))

im1 = ax1.imshow(img1[100:600,500:2100])
im2 = ax2.imshow(img2[100:600,500:2100])

im1.set_cmap('Reds')
im2.set_cmap('Reds')

ax3.plot((img1sum-img1sum.min())/float32(img1sum.max()-img1sum.min()))
ax4.plot((img2sum-img2sum.min())/float32(img2sum.max()-img2sum.min()))

ax1.set_ylim(100,500)
ax2.set_ylim(100,500)
ax3.set_ylim(0,1.1)
ax4.set_ylim(0,1.1)

ax1.set_axis_off()
ax2.set_axis_off()

ax4.set_yticklabels([])

ax3.set_ylabel('normalized intensity')
ax3.set_xlabel('pixel')
ax4.set_xlabel('pixel')

ax1.text(800,0,r'$d = 100$ $\mu$m',ha='center')
ax2.text(800,0,r'$d = 200$ $\mu$m',ha='center')

fig.subplots_adjust(hspace=0, wspace = 0.07)

fig.savefig('single_slit_diffraction.png',dpi=300,bbox_inches='tight',pad_inches=0.05)