def display(self, report, full=False, nbins=100): # @UnusedVariable
""" Displays this diffeomorphism. """
from diffeo2d import diffeo_stats
print('getting stats')
stats = diffeo_stats(self.d)
angle = stats.angle
norm = stats.norm
print('getting colors')
norm_rgb = self.get_rgb_norm()
angle_rgb = self.get_rgb_angle()
info_rgb = self.get_rgb_info()
print('figures')
f = report.figure(cols=6)
f.data_rgb('norm_rgb', norm_rgb,
caption="Norm(D). white=0, blue=maximum (%.2f). " % np.max(norm))
f.data_rgb('phase_rgb', angle_rgb,
caption="Phase(D).")
if hasattr(self, 'variance_max'):
varmax_text = '(variance max %s)' % self.variance_max
else:
varmax_text = ''
f.data_rgb('var_rgb', info_rgb,
caption='Uncertainty (green=sure, red=unknown %s)' % varmax_text)
print('histogram of norm values')
with f.plot('norm_hist', caption='histogram of norm values') as pylab:
pylab.hist(norm.flat, nbins)
ax = pylab.gca()
ax.set_xlabel('pixels')
ax2 = ax.twiny()
new_tick_locations = ax.get_xticks() # np.array(range(40))
def tick_function(X):
x = float(X * 1.0 / self.get_shape()[0])
return '%.3f' % x
ax2.set_xticks(new_tick_locations)
ax2.set_xticklabels(map(tick_function, new_tick_locations))
ax2.set_xlabel('viewport fraction (unitless)')
print('histogram of certainty values')
angles = np.array(angle.flat)
valid_angles = angles[np.logical_not(np.isnan(angles))]
if len(valid_angles) > 0:
with f.plot('angle_hist', caption='histogram of angle values '
'(excluding where norm=0)') as pylab:
pylab.hist(valid_angles, nbins)
try:
with f.plot('var_hist',
caption='histogram of certainty values') as pylab:
pylab.hist(self.variance.flat, nbins)
except:
print('hist plot exception')
def make_hard(dd):
assert isinstance(dd, Diffeomorphism2D)
if use_isomorphism_heuristics:
stats = diffeo_stats(dd.d)
per = np.percentile(stats.norm, norm_percentile)
limit = per * factor
# / 3.0
# print('norm mean/mean: %g %g' % (np.mean(stats.norm), np.median(stats.norm)))
# for i in range(0, 100, 5):
# print(' %3d%% = %g' % (i, np.percentile(stats.norm, i)))
# limit = np.percentile(stats.norm, info_percentile)
# if limit <= 1:
# print('limit was %g' % limit)
# limit = 4
variance = (stats.norm > limit).astype('float')
logger.info('---hard choices---')
logger.info(' per: %g pixels * %g =' % (per, factor))
logger.info('limit: %g pixels' % limit)
logger.info(' vis: %.1f%% ' % (100 * np.mean(variance)))
else:
variance = (dd.variance > info_threshold).astype('float')
return Diffeomorphism2D(dd.d, variance)
def display(self, report, full=False, nbins=100): # @UnusedVariable
""" Displays this diffeomorphism. """
from diffeo2d import diffeo_stats
print('getting stats')
stats = diffeo_stats(self.d)
angle = stats.angle
norm = stats.norm
print('getting colors')
norm_rgb = self.get_rgb_norm()
angle_rgb = self.get_rgb_angle()
info_rgb = self.get_rgb_info()
print('figures')
f = report.figure(cols=6)
f.data_rgb('norm_rgb',
norm_rgb,
caption="Norm(D). white=0, blue=maximum (%.2f). " %
np.max(norm))
f.data_rgb('phase_rgb', angle_rgb, caption="Phase(D).")
if hasattr(self, 'variance_max'):
varmax_text = '(variance max %s)' % self.variance_max
else:
varmax_text = ''
f.data_rgb('var_rgb',
info_rgb,
caption='Uncertainty (green=sure, red=unknown %s)' %
varmax_text)
print('histogram of norm values')
with f.plot('norm_hist', caption='histogram of norm values') as pylab:
pylab.hist(norm.flat, nbins)
ax = pylab.gca()
ax.set_xlabel('pixels')
ax2 = ax.twiny()
new_tick_locations = ax.get_xticks() # np.array(range(40))
def tick_function(X):
x = float(X * 1.0 / self.get_shape()[0])
return '%.3f' % x
ax2.set_xticks(new_tick_locations)
ax2.set_xticklabels(map(tick_function, new_tick_locations))
ax2.set_xlabel('viewport fraction (unitless)')
print('histogram of certainty values')
angles = np.array(angle.flat)
valid_angles = angles[np.logical_not(np.isnan(angles))]
if len(valid_angles) > 0:
with f.plot('angle_hist',
caption='histogram of angle values '
'(excluding where norm=0)') as pylab:
pylab.hist(valid_angles, nbins)
try:
with f.plot('var_hist',
caption='histogram of certainty values') as pylab:
pylab.hist(self.variance.flat, nbins)
except:
print('hist plot exception')
