!ls

import matplotlib.pyplot as plt
import matplotlib.image as mpimg
%matplotlib inline
import numpy as np

img = mpimg.imread('IMG_4489.JPG')

img

plt.imshow(img[700:2000,3200:4200,0])
plt.colorbar()

print len(img), len(img[0]), len(img[0][0])

plt.plot(img[1800,3200:4200,0])

def _line(x,*p):
    a,b,c,d = p
    return a*np.exp(-(x-b)**2/(2*c**2))+d

def _mline(x,*p):
    a,b,c,d,e,f,g = p
    return a*np.exp(-(x-b)**2/(2*c**2))+d+e*np.exp(-(x-f)**2/(2*g**2))

line = img[1800,3200:4200,0]

from scipy.optimize import curve_fit
x = np.arange(len(line))
p0 = [35,550,150,5]
coeff, var_matrix = curve_fit(_line,x,line,p0=p0)

p0 = [30,525,40,0,35,590,40]
coeff, var_matrix = curve_fit(_mline,x,line,p0=p0)

print coeff

yfit = [_line(xx,*tuple(coeff)) for xx in x]
plt.hold()
plt.plot(x,line,'*',yfit,'-')

multi_yfit = [_mline(xx,*tuple(coeff)) for xx in x]
#plt.hold()
plt.plot(x,line,'*',yfit,'-',multi_yfit,'x')
#plt.plot(line)
#plt.plot(yfit)
#plt.plot(multi_yfit)



plt.plot(img[1350,3200:4200,0])

plt.imshow(img[1100:1600,3400:3900,0])
plt.colorbar()

def _2Dline(x,y,*p):
    a,b,c,d,e = p
    return a*np.exp(-((x-b)**2+(y-c)**2)/(2*d**2))+e

data = img[1100:1600,3400:3900,0]
p0 = [500,250,250,100,0]
coeff, var_matrix = curve_fit(_2Dline,x,data,p0=p0)