def evaluate_grid_approx3(self, x0, x1, y0, y1, fx, fy, minval,
derivs=False, minradius=3, doslice=True,
maxmargin=100):
'''
minval: small value at which to stop evaluating
[x0,x1): (int) X values to evaluate
[y0,y1): (int) Y values to evaluate
(fx,fy): (float) pixel offset of the MoG; ie, evaluate MoG shifted by
this amount.
'maxmargin': don't render sources more than this distance outside the box.
If 'doslice' is True, slices the images down to the non-zero
bounding-box.
If 'derivs' is True, computes and returns x and y derivatives too.
Unlike evaluate_grid_approx, returns a Patch object.
'''
from tractor.mix import c_gauss_2d_approx3
result = np.zeros((y1 - y0, x1 - x0))
xderiv = yderiv = None
if derivs:
xderiv = np.zeros_like(result)
yderiv = np.zeros_like(result)
# guess:
cx = int(self.mean[0, 0] + fx)
cy = int(self.mean[0, 1] + fy)
if (cx < x0 - maxmargin or cx > x1 + maxmargin or
cy < y0 - maxmargin or cy > y1 + maxmargin):
return None
try:
rtn, sx0, sx1, sy0, sy1 = c_gauss_2d_approx3(
int(x0), int(x1), int(y0), int(y1),
float(fx), float(fy), float(minval),
self.amp, self.mean, self.var,
result, xderiv, yderiv,
cx, cy, int(minradius))
except:
print('failure calling c_gauss_2d_approx3:')
print(x0, x1, y0, y1)
print(fx, fy, minval)
print(cx, cy, minradius)
print('-->', int(x0), int(x1), int(y0), int(y1))
print('-->', float(fx), float(fy), float(minval))
print('-->', cx, cy, int(minradius))
raise
assert(rtn == 0)
if doslice:
slc = slice(sy0, sy1), slice(sx0, sx1)
result = result[slc].copy()
if derivs:
xderiv = xderiv[slc].copy()
yderiv = yderiv[slc].copy()
x0 += sx0
y0 += sy0
if derivs:
return (Patch(x0, y0, result), Patch(x0, y0, xderiv),
Patch(x0, y0, yderiv))
return Patch(x0, y0, result)
plt.imshow(result2 - r2,
interpolation='nearest', origin='lower')
plt.colorbar()
plt.title('Approx 2 - Grid')
plt.suptitle('j = %i' % j)
ps.savefig()
assert(np.all(np.abs(r2 - result2) < minval))
result3 = np.zeros((H, W))
xderiv, yderiv, mask = None, None, None
xc, yc = int(mean[0, 0] + dx), int(mean[0, 1] + dy)
args = (x0, x1, y0, y1, dx, dy, minval, amp, mean, var,
result3, xderiv, yderiv, xc, yc, minradius)
print('args (approx3):', args)
rtn = c_gauss_2d_approx3(*args)
if rtn == -1:
raise RuntimeError('c_gauss_2d_approx3 failed')
print('Max difference 3:', np.max(np.abs(r2 - result3)))
plt.clf()
plt.subplot(1, 2, 1)
plt.imshow(np.log10(np.maximum(minval * 1e-3, result3)),
interpolation='nearest', origin='lower')
plt.colorbar()
plt.title('Approx 3')
plt.subplot(1, 2, 2)
plt.imshow(result3 - r2,
interpolation='nearest', origin='lower')
plt.colorbar()