def evaluate_grid_dstn(self, xlo, xhi, ylo, yhi, xstep=1., ystep=1.):
from mix import c_gauss_2d_grid
assert(self.D == 2)
NX = int(round(xhi - xlo + 1))
NY = int(round(yhi - ylo + 1))
result = np.zeros((NY, NX))
rtn = c_gauss_2d_grid(xlo, xstep, NX, ylo, ystep, NY,
self.amp, self.mean,self.var, result)
if rtn == -1:
raise RuntimeError('c_gauss_2d_grid failed')
return result
def evaluate_grid_dstn(self, xlo, xhi, ylo, yhi, xstep=1., ystep=1.):
from mix import c_gauss_2d_grid
assert (self.D == 2)
NX = int(round(xhi - xlo + 1))
NY = int(round(yhi - ylo + 1))
result = np.zeros((NY, NX))
rtn = c_gauss_2d_grid(xlo, xstep, NX, ylo, ystep, NY, self.amp,
self.mean, self.var, result)
if rtn == -1:
raise RuntimeError('c_gauss_2d_grid failed')
return result
def evaluate_grid_dstn(self, x0, x1, y0, y1, cx, cy):
'''
[x0,x1): (int) X values to evaluate
[y0,y1): (int) Y values to evaluate
(cx,cy): (float) pixel center of the MoG
'''
from mix import c_gauss_2d_grid
assert(self.D == 2)
result = np.zeros((y1-y0, x1-x0))
rtn = c_gauss_2d_grid(x0, x1, y0, y1, cx, cy,
self.amp, self.mean,self.var, result)
if rtn == -1:
raise RuntimeError('c_gauss_2d_grid failed')
return Patch(x0, y0, result)
amp = np.array([0.99, 0.01])
mean = np.array([[0.3, 0.7],[-0.3, -0.7],])
var = np.array([ [ [ 400., -100. ], [-100., 100.,] ],
[ [ 400., -100. ], [-100., 100.,] ], ])
dx = 1.
minval = 1e-9
else:
break
print 'args (approx1):', x0, x1, y0, y1, dx, dy, minval, amp, mean, var
rtn = c_gauss_2d_approx(x0, x1, y0, y1, dx, dy, minval, amp, mean, var, result)
if rtn == -1:
raise RuntimeError('c_gauss_2d_approx failed')
r2 = np.zeros((H,W))
rtn = c_gauss_2d_grid(x0 - dx, 1, W, y0 - dy, 1, H, amp, mean, var, r2)
if rtn == -1:
raise RuntimeError('c_gauss_2d_grid failed')
print 'Max difference:', np.max(np.abs(r2 - result))
plt.clf()
plt.imshow(np.log10(np.maximum(minval * 1e-3, r2)),
interpolation='nearest', origin='lower')
plt.colorbar()
plt.title('Grid')
ps.savefig()
plt.clf()
plt.imshow(np.log10(np.maximum(minval * 1e-3, result)),
interpolation='nearest', origin='lower')
elif j == 13:
var = np.array([ [ [ 4., 4. ], [4., 9.,] ], ])
minradius = 12
elif j == 14:
var = np.array([ [ [ 0.5, -0.6 ], [-0.6, 1.,] ], ])
minradius = 4
else:
break
print 'args (approx1):', x0, x1, y0, y1, dx, dy, minval, amp, mean, var
rtn = c_gauss_2d_approx(x0, x1, y0, y1, dx, dy, minval, amp, mean, var, result)
if rtn == -1:
raise RuntimeError('c_gauss_2d_approx failed')
r2 = np.zeros((H,W))
rtn = c_gauss_2d_grid(x0 - dx, 1, W, y0 - dy, 1, H, amp, mean, var, r2)
if rtn == -1:
raise RuntimeError('c_gauss_2d_grid failed')
print 'Max difference:', np.max(np.abs(r2 - result))
plt.clf()
plt.subplot(1,2,1)
plt.imshow(np.log10(np.maximum(minval * 1e-3, r2)),
interpolation='nearest', origin='lower')
plt.colorbar()
plt.title('Grid')
plt.subplot(1,2,2)
plt.imshow(np.log10(np.maximum(minval * 1e-3, result)),
interpolation='nearest', origin='lower')