gistfile1.py

#Part03-e12 radial_fade:

import os
import numpy as np
import matplotlib.pyplot as plt

# comment this when submitting
#uncomment when testing locally
os.chdir("C:/Users/fnsuc/OneDrive - University of Helsinki/Tilasto/python_data_analysis/hy-data-analysis-with-python-spring-2020/part03-e12_radial_fade")
print(os. getcwd())

# def center(a):
#     return (0,0)   # note the order: (center_y, center_x)

a= np.random.randint(0, 5, size=(3, 3))
#print('a',a)
def center(a):
    painting=a.copy()
    #print(painting.shape)
    y=(painting.shape[1]-1)/2
    x=(painting.shape[0]-1)/2
    return (x,y) # OBS! check order!!!!!

print(a)
print('shape', a.shape)
print('center', center(a))
#print('center_painting', center("src/painting.png"))

# print(center(plt.imread("src/painting.png")))


# def radial_distance(a):
#     return np.array([[]])

def radial_distance(a):
    c = center(a)
    #d=np.asarray(c).reshape(2,1)
    dist = np.zeros((a.shape[0],a.shape[1]))
    for h in range(dist.shape[0]):
        for w in range(dist.shape[1]):
            dist[h, w] = np.sqrt(np.sum((np.array([h, w])-c)**2))
    return dist

#print('radial distance', radial_distance(a))

def scale(a, tmin=0.0, tmax=1.0):
    if a.min()==a.max():
        return a*0 # edit: was "return a", now corrected and should work
    else:
        return ((a-a.min())/(a.max()-a.min()))

#print('scale', scale(a))


def radial_mask(a):
    #frame = np.zeros((a.shape[0],a.shape[1]))
	img2 = a.copy()
	a_dist = radial_distance(img2)
	a_scaled = scale(a_dist)
	mask = 1-a_scaled
	return mask

#print('mask',radial_mask(a))
#print(radial_mask(a))
#print(radial_mask(a)[:,:,np.newaxis])



def radial_fade(a):
    img2 = a.copy()
    m=radial_mask(img2).reshape(img2.shape[0],img2.shape[1],1)
    r=img2*m
    #img2=img2*radial_mask(img2)[:,:,np.newaxis]
    #img2=img2.reshape((img2.shape[0],img2.shape[1]))
    return r

#print('fade', radial_fade(a))
# print('a',a)
# print('shape',a.shape)

def main():
    filename="src/painting.png"
    #filename="src/orange.png"
    image=plt.imread(filename)
    #image=image[0:1, 0:5, :]
    print('mask',radial_mask(image))
    fig, ax = plt.subplots(3,1)
    ax[0].imshow(image)
    ax[1].imshow(radial_mask(image))
    ax[2].imshow(radial_fade(image))
    plt.show(fig)

if __name__ == "__main__":
    main()