ax[0].plot(u, v, '.', c=c)
ax[1].plot(u, v, '.r',markersize=1)
fareyImage[u,v] = 255
if i == maxLines:
break
#ax[0].set_title('Sampling (colour per line) for prime size:'+str(p))
#ax[1].set_title('Sampling (same colour per line) for prime size:'+str(p))
ax[0].set_title('Sampling (colour per line) for dyadic size:'+str(M))
ax[1].set_title('Sampling (same colour per line) for dyadic size:'+str(M))
#ax[0].set_xlim([0,M])
#ax[0].set_ylim([0,M])
#ax[1].set_xlim([0,M])
#ax[1].set_ylim([0,M])
#imageio.imsave("farey_image_"+str(p)+"_"+str(K)+".png", fareyImage)
imageio.imsave("farey_image_"+str(M)+"_"+str(K)+".png", fareyImage)
plt.show()
fig,
plt.plot(pValues, qValues, 'ro')
plt.show()
fig,
plt.gca().invert_yaxis()
maxLines = len(mValues)
old_u = M/2
old_v = M/2
#maxLines = 12
#color=iter(cm.rainbow(np.linspace(0,1,len(lines))))
for i, mValues in enumerate(mValues):
def createFractal4(reduction, N, proportion):
#parameters
M = 2*N
twoQuads = True
angles, lengths = mojette.angleSet_Symmetric(N,N,1,True,50)
perpAngle = farey.farey(1,0)
angles.append(perpAngle)
powerSpect = np.zeros((M,M))
#compute lines
centered = True
mLines = []
sLines = []
mValues = []
sValues = []
pValues = []
qValues = []
for angle in angles:
m, s, p, q, inv = farey.toFinite(angle, M)
pValues.append(p)
qValues.append(q)
if m not in mValues and m < M:
u, v = radon.getSliceCoordinates2(m, powerSpect, centered, M)
mLines.append((u,v))
mValues.append(m)
#second quadrant
if twoQuads:
if m != 0 and m != M: #dont repeat these
m = M-m
if m not in mValues and m < M:
u, v = radon.getSliceCoordinates2(m, powerSpect, centered, M)
mLines.append((u,v))
mValues.append(m)
i = (len(mValues)+len(sValues))/float(M)
if i >= 1:
break
ss = []
ss.append(M)
ss.extend(range(0, N/2))
maxLines = len(ss)
for i,s in enumerate(ss):
u, v = radon.getSliceCoordinates2(s, powerSpect, centered, M)
sLines.append((u,v))
sValues.append(s)
i = (len(mValues)+len(sValues))/float(M)
if i >= 1.5:
break
length = 0
fig, ax = plt.subplots(nrows=1, ncols=2, figsize=(16, 8))
plt.gray()
plt.tight_layout()
maxLines = len(sLines+mLines)
i = 0
ax[0].imshow(powerSpect)
ax[1].imshow(powerSpect)
color=iter(cm.jet(np.linspace(0,1,maxLines+1)))
fareyImage = np.zeros_like(powerSpect)
fareyImage1 = np.zeros_like(powerSpect)
for i, sLine in enumerate(sLines):
u, v = sLine
ax[1].plot(u, v, '.w',markersize=1)
fareyImage[u,v] = 1
length = length + 1
i = np.count_nonzero(fareyImage)/float((M*M))
if i >= reduction*proportion:
break
maxLines = len(mLines)
for i, mLine in enumerate(mLines):
u, v = mLine
ax[0].plot(u, v, '.r', markersize=1)
ax[1].plot(u, v, '.r',markersize=1)
fareyImage[u,v] = 1
fareyImage1[u,v] = 1
length = length + 1
i = np.count_nonzero(fareyImage)/float((M*M))
if i >= reduction:
break
print("Proportion of M:", (length/float(M)))
print("Non-zero elements with holes: ", np.count_nonzero(fareyImage1)/float((M*M)) * 100)
print("Non-zero elements without holes: ", np.count_nonzero(fareyImage)/float((M*M)) * 100)
print("Absolute difference percentage extra filled in is ", (np.count_nonzero(fareyImage)- np.count_nonzero(fareyImage1))/float((M*M)) *100)
withHoles = np.count_nonzero(fareyImage1)/float((M*M)) * 100
withoutHoles = np.count_nonzero(fareyImage)/float((M*M)) * 100
percentage = (withoutHoles - withHoles)/float(withHoles) * 100
print("Percentage difference percentage extra filled in is ", percentage)
ax[0].set_title('Sampling (colour per line) for dyadic size:'+str(M))
ax[1].set_title('Sampling (same colour per line) for dyadic size:'+str(M))
imageio.imsave("farey_image_"+str(M)+"_"+".png", fareyImage)
plt.show()
lines = mLines + sLines
return fareyImage, lines
# -*- coding: utf-8 -*-
"""
Test Read PGM member
Created on Sun Jan 25 21:52:38 2015
@author: shakes
"""
import _libpath #add custom libs
import finitetransform.imageio as imageio
saveImage = False
image, depth = imageio.readPGM("../data/lena512.pgm")
print "Image dtype:", image.dtype
if saveImage:
imageio.imsave("../data/lena.png", image)
#Plot
import matplotlib.pyplot as plt
plt.gray()
plt.imshow(image)
plt.axis('off')
plt.title('Image')
plt.show()