def plot_result(self):
global_ncc = self.get_global_ncc(smooth_len=5)
if isinstance(global_ncc, np.ndarray):
mean_global_ncc_scales = self.get_mean_ncc_scales(smooth_len=5)
fig, ax0 = self.stack.add_subplots("Global NCC", ncols=1)
peaks = nputils.find_peaks(global_ncc,
3,
global_ncc.mean() +
2 * global_ncc.std(),
fit_gaussian=True)
peaks = sorted(peaks,
key=lambda p: global_ncc[tuple(p)],
reverse=True)
if len(peaks) < 10:
for peak in peaks:
p = (np.array(peak) / float(self.factor) -
np.array([self.bounds[0], self.bounds[2]]))
print "Peak at %s (norm:%s, intensity:%s, pix:%s)" % (
p[::-1], np.linalg.norm(p), global_ncc[tuple(peak)],
peak)
ax0.imshow(global_ncc, extent=self.global_ncc_extent)
plotutils.img_axis(ax0)
for scale, ncc in nputils.get_items_sorted_by_keys(
mean_global_ncc_scales):
if ncc.ndim != 2:
continue
fig, ax = self.stack.add_subplots("Global NCC scale %s" %
scale,
ncols=1)
ax.imshow(ncc, extent=self.global_ncc_extent)
plotutils.img_axis(ax)
def save(self, filename):
l = []
for epoch, (x, y) in nputils.get_items_sorted_by_keys(self.cores):
r, theta = nputils.coord_xy_to_rtheta(x, y)
l.append([epoch.strftime("%Y-%m-%d"), 0, r, np.degrees(theta)])
np.savetxt(filename, l, ['%s', '%s', '%s', '%s'])
def plot_result(self):
global_ncc = self.get_global_ncc(smooth_len=5)
if isinstance(global_ncc, np.ndarray):
mean_global_ncc_scales = self.get_mean_ncc_scales(smooth_len=5)
fig, ax0 = self.stack.add_subplots("Global NCC", ncols=1)
peaks = nputils.find_peaks(global_ncc, 3, global_ncc.mean() + 2 * global_ncc.std(), fit_gaussian=True)
peaks = sorted(peaks, key=lambda p: global_ncc[tuple(p)], reverse=True)
if len(peaks) < 10:
for peak in peaks:
p = (np.array(peak) / float(self.factor) - np.array([self.bounds[0], self.bounds[2]]))
print "Peak at %s (norm:%s, intensity:%s, pix:%s)" % (p[::-1], np.linalg.norm(p), global_ncc[tuple(peak)], peak)
ax0.imshow(global_ncc, extent=self.global_ncc_extent)
plotutils.img_axis(ax0)
for scale, ncc in nputils.get_items_sorted_by_keys(mean_global_ncc_scales):
if ncc.ndim != 2:
continue
fig, ax = self.stack.add_subplots("Global NCC scale %s" % scale, ncols=1)
ax.imshow(ncc, extent=self.global_ncc_extent)
plotutils.img_axis(ax)
def get_result(self):
return nputils.get_items_sorted_by_keys(self.global_ncc_scales)
def get_result(self):
return nputils.get_items_sorted_by_keys(self.global_ncc_scales)
