def add_to_axes(self, axes):
"""Add the overlay to the axes."""
rect_width = self.pickets[0].sample_width * 2
for mlc_num, mlc in enumerate(self.pickets[0].mlc_meas):
# get pass/fail status of all measurements across pickets for that MLC
if self.settings.action_tolerance is not None:
if all(
picket.mlc_passed_action(mlc_num)
for picket in self.pickets):
color = 'b'
elif all(
picket.mlc_passed(mlc_num) for picket in self.pickets):
color = 'm'
else:
color = 'r'
elif all(picket.mlc_passed(mlc_num) for picket in self.pickets):
color = 'b'
else:
color = 'r'
# create a rectangle overlay
if self.settings.orientation == orientations['UD']:
r = Rectangle(self.image.shape[1],
rect_width,
center=(self.image.center.x, mlc.center.y))
else:
r = Rectangle(rect_width,
self.image.shape[0],
center=(mlc.center.x, self.image.center.y))
r.add_to_axes(axes.axes,
edgecolor='none',
fill=True,
alpha=0.1,
facecolor=color)
def add_to_axes(self, axes):
rect_width = self.pickets[0].sample_width*2
for mlc_num, mlc in enumerate(self.pickets[0].mlc_meas):
# get pass/fail status of all measurements across pickets for that MLC
if self.settings.action_tolerance is not None:
if all(picket.mlc_passed_action(mlc_num) for picket in self.pickets):
color = 'b'
elif all(picket.mlc_passed(mlc_num) for picket in self.pickets):
color = 'm'
else:
color = 'r'
elif all(picket.mlc_passed(mlc_num) for picket in self.pickets):
color = 'b'
else:
color = 'r'
# create a rectangle overlay
if self.settings.orientation == orientations['UD']:
r = Rectangle(self.image.shape[1], rect_width, center=(self.image.center.x, mlc.center.y))
else:
r = Rectangle(rect_width, self.image.shape[0], center=(mlc.center.y, self.image.center.y))
r.add_to_axes(axes.axes, edgecolor='none', fill=True, alpha=0.1, facecolor=color)
def plot_analyzed_image(self, guard_rails=True, mlc_peaks=True, overlay=True, show=True):
"""Plot the analyzed image.
Parameters
----------
guard_rails : bool
Do/don't plot the picket "guard rails".
mlc_peaks : bool
Do/don't plot the MLC positions.
overlay : bool
Do/don't plot the alpha overlay of the leaf status.
"""
# plot the image
plt.clf()
ax = plt.imshow(self.image.array, cmap=plt.cm.Greys)
# plot guard rails and mlc peaks as desired
for p_num, picket in enumerate(self.pickets):
if guard_rails:
picket.add_guards_to_axes(ax.axes)
if mlc_peaks:
for idx, mlc_meas in enumerate(picket.mlc_meas):
if not mlc_meas.passed:
color = 'r'
elif self._action_lvl_set and not mlc_meas.passed_action:
color = 'm'
else:
color = 'b'
mlc_meas.add_to_axes(ax.axes, color=color, width=1.5)
# plot the overlay if desired.
if overlay:
for mlc_num, mlc in enumerate(self.pickets[0].mlc_meas):
below_tol = True
if self._action_lvl_set:
below_action = True
for picket in self.pickets:
if not picket.mlc_passed(mlc_num):
below_tol = False
if self._action_lvl_set and not picket.mlc_passed_action(mlc_num):
below_action = False
if below_tol:
if self._action_lvl_set and not below_action:
color = 'm'
else:
color = 'g'
else:
color = 'r'
if self.orientation == orientations['UD']:
r = Rectangle(max(self.image.shape)*2, self._sm_lf_meas_wdth, (mlc.center.x, mlc.center.y))
else:
r = Rectangle(self._sm_lf_meas_wdth, max(self.image.shape) * 2, (mlc.center.x, mlc.center.y))
r.add_to_axes(ax.axes, edgecolor='none', fill=True, alpha=0.1, facecolor=color)
plt.xlim([0, self.image.shape[1]])
plt.ylim([0, self.image.shape[0]])
plt.axis('off')
if show:
plt.show()
