def only_display_image(figure, shape):
"""Set up a figure so that the image occupies the entire figure
figure - a matplotlib figure
shape - i/j size of the image being displayed
"""
assert isinstance(figure, matplotlib.figure.Figure)
figure.set_frameon(False)
ax = figure.axes[0]
ax.set_axis_off()
figure.subplots_adjust(0, 0, 1, 1, 0, 0)
dpi = figure.dpi
width = float(shape[1]) / dpi
height = float(shape[0]) / dpi
figure.set_figheight(height)
figure.set_figwidth(width)
bbox = matplotlib.transforms.Bbox(numpy.array([[0.0, 0.0], [width, height]]))
transform = matplotlib.transforms.Affine2D(
numpy.array([[dpi, 0, 0], [0, dpi, 0], [0, 0, 1]])
)
figure.bbox = matplotlib.transforms.TransformedBbox(bbox, transform)
def run(self, workspace):
"""Run the module
workspace - The workspace contains
pipeline - instance of cpp for this run
image_set - the images in the image set being processed
object_set - the objects (labeled masks) in this image set
measurements - the measurements for this run
frame - the parent frame to whatever frame is created. None means don't draw.
"""
background_image = self.get_background_image(workspace, None)
if (self.each_or_once == EO_ONCE
and self.get_good_gridding(workspace) is not None):
gridding = self.get_good_gridding(workspace)
if self.auto_or_manual == AM_AUTOMATIC:
gridding = self.run_automatic(workspace)
elif self.manual_choice == MAN_COORDINATES:
gridding = self.run_coordinates(workspace)
elif self.manual_choice == MAN_MOUSE:
gridding = workspace.interaction_request(
self, background_image,
workspace.measurements.image_set_number)
self.set_good_gridding(workspace, gridding)
workspace.set_grid(self.grid_image.value, gridding)
#
# Save measurements
#
self.add_measurement(
workspace,
F_X_LOCATION_OF_LOWEST_X_SPOT,
gridding.x_location_of_lowest_x_spot,
)
self.add_measurement(
workspace,
F_Y_LOCATION_OF_LOWEST_Y_SPOT,
gridding.y_location_of_lowest_y_spot,
)
self.add_measurement(workspace, F_ROWS, gridding.rows)
self.add_measurement(workspace, F_COLUMNS, gridding.columns)
self.add_measurement(workspace, F_X_SPACING, gridding.x_spacing)
self.add_measurement(workspace, F_Y_SPACING, gridding.y_spacing)
# update background image
background_image = self.get_background_image(workspace, gridding)
workspace.display_data.gridding = gridding.serialize()
workspace.display_data.background_image = background_image
workspace.display_data.image_set_number = (
workspace.measurements.image_set_number)
if self.wants_image:
import matplotlib.transforms
import matplotlib.figure
import matplotlib.backends.backend_agg
from cellprofiler.gui.tools import figure_to_image
figure = matplotlib.figure.Figure()
canvas = matplotlib.backends.backend_agg.FigureCanvasAgg(figure)
ax = figure.add_subplot(1, 1, 1)
self.display_grid(background_image, gridding,
workspace.measurements.image_set_number, ax)
#
# This is the recipe for just showing the axis
#
figure.set_frameon(False)
ax.set_axis_off()
figure.subplots_adjust(0, 0, 1, 1, 0, 0)
ai = ax.images[0]
shape = ai.get_size()
dpi = figure.dpi
width = float(shape[1]) / dpi
height = float(shape[0]) / dpi
figure.set_figheight(height)
figure.set_figwidth(width)
bbox = matplotlib.transforms.Bbox(
np.array([[0.0, 0.0], [width, height]]))
transform = matplotlib.transforms.Affine2D(
np.array([[dpi, 0, 0], [0, dpi, 0], [0, 0, 1]]))
figure.bbox = matplotlib.transforms.TransformedBbox(
bbox, transform)
image_pixels = figure_to_image(figure, dpi=dpi)
image = cpi.Image(image_pixels)
workspace.image_set.add(self.save_image_name.value, image)
def run(self, workspace):
"""Run the module
workspace - The workspace contains
pipeline - instance of cpp for this run
image_set - the images in the image set being processed
object_set - the objects (labeled masks) in this image set
measurements - the measurements for this run
frame - the parent frame to whatever frame is created. None means don't draw.
"""
background_image = self.get_background_image(workspace, None)
if (self.each_or_once == EO_ONCE and
self.get_good_gridding(workspace) is not None):
gridding = self.get_good_gridding(workspace)
if self.auto_or_manual == AM_AUTOMATIC:
gridding = self.run_automatic(workspace)
elif self.manual_choice == MAN_COORDINATES:
gridding = self.run_coordinates(workspace)
elif self.manual_choice == MAN_MOUSE:
gridding = workspace.interaction_request(self, background_image,
workspace.measurements.image_set_number)
self.set_good_gridding(workspace, gridding)
workspace.set_grid(self.grid_image.value, gridding)
#
# Save measurements
#
self.add_measurement(workspace, F_X_LOCATION_OF_LOWEST_X_SPOT,
gridding.x_location_of_lowest_x_spot)
self.add_measurement(workspace, F_Y_LOCATION_OF_LOWEST_Y_SPOT,
gridding.y_location_of_lowest_y_spot)
self.add_measurement(workspace, F_ROWS, gridding.rows)
self.add_measurement(workspace, F_COLUMNS, gridding.columns)
self.add_measurement(workspace, F_X_SPACING, gridding.x_spacing)
self.add_measurement(workspace, F_Y_SPACING, gridding.y_spacing)
# update background image
background_image = self.get_background_image(workspace, gridding)
workspace.display_data.gridding = gridding.serialize()
workspace.display_data.background_image = background_image
workspace.display_data.image_set_number = workspace.measurements.image_set_number
if self.wants_image:
import matplotlib.transforms
import matplotlib.figure
import matplotlib.backends.backend_agg
from cellprofiler.gui.tools import figure_to_image
figure = matplotlib.figure.Figure()
canvas = matplotlib.backends.backend_agg.FigureCanvasAgg(figure)
ax = figure.add_subplot(1, 1, 1)
self.display_grid(background_image, gridding,
workspace.measurements.image_set_number, ax)
#
# This is the recipe for just showing the axis
#
figure.set_frameon(False)
ax.set_axis_off()
figure.subplots_adjust(0, 0, 1, 1, 0, 0)
ai = ax.images[0]
shape = ai.get_size()
dpi = figure.dpi
width = float(shape[1]) / dpi
height = float(shape[0]) / dpi
figure.set_figheight(height)
figure.set_figwidth(width)
bbox = matplotlib.transforms.Bbox(
np.array([[0.0, 0.0], [width, height]]))
transform = matplotlib.transforms.Affine2D(
np.array([[dpi, 0, 0],
[0, dpi, 0],
[0, 0, 1]]))
figure.bbox = matplotlib.transforms.TransformedBbox(bbox, transform)
image_pixels = figure_to_image(figure, dpi=dpi)
image = cpi.Image(image_pixels)
workspace.image_set.add(self.save_image_name.value, image)