def add_shape(self, f): #Create shape S = Shape(f, self.R, self.SHAPE_R) #Add to shape list S.shape_num = len(self.shape_list) self.shape_list.append(S) row = [] for k in range(len(self.shape_list)): T = self.shape_list[k] ift = real(ipfft(pft_mult(pft_rotate(S.pft, 2.*pi/6.), T.pft), 2*self.SHAPE_R+1,2*self.SHAPE_R+1)) Spad = imrotate(cpad(S.indicator, array([2*self.SHAPE_R+1,2*self.SHAPE_R+1])), 360./6.) Tpad = cpad(T.indicator, array([2*self.SHAPE_R+1,2*self.SHAPE_R+1])) pind = real(fftconvolve(Spad, Tpad, mode='same')) imshow(pind) imshow(ift) obst = to_ind(pind, 0.001) imshow(obst) cutoff = best_cutoff(ift, obst, S.radius + T.radius) print cutoff imshow(to_ind(ift, cutoff)) row.append(cutoff * self.tarea) self.cutoff_matrix.append(row) return S
from misc import *
import fourier_obstacle as obstacle
from polar import ipfft, pft_mult
import os
import pickle
db = obstacle.ShapeSet(32, 256)
db.add_shape(load_img("shape3.png"))
db.add_shape(load_img("shape4.png"))
A = db.shape_list[0]
B = db.shape_list[1]
pconv = ipfft(pft_mult(A.pft, B.pft), 513, 513)
imsave("test1.png", pconv)
imshow(pconv)
#Contstruct sampled convolution field
sconv = zeros((513, 513))
for i in range(513):
for j in range(513):
x = 257. - i
y = 257. - j
sconv[i, j] = db.potential(A, B, array([0., 0.]), array([x, y]), 0., pi/6.)
print x,y, sconv[i,j]
imsave("test2.png", sconv)
imshow(sconv)