def display(self, workspace, figure):
if self.show_window:
figure.set_subplots((1, 1))
figure.clf()
ax = figure.subplot(0, 0)
gridding = cpg.CPGridInfo()
gridding.deserialize(workspace.display_data.gridding)
self.display_grid(workspace.display_data.background_image,
gridding,
workspace.display_data.image_set_number, ax)
def decoder(dct, buffers=buffers):
if '__ndarray__' in dct:
buf = buffer(buffers[dct['idx']])
return np.frombuffer(buf, dtype=dct['dtype']).reshape(
dct['shape']).copy()
if '__buffer__' in dct:
return buffer(buffers[dct['idx']])
if '__CPGridInfo__' in dct:
grid = cpg.CPGridInfo()
grid.deserialize(dct)
return grid
return dct
def build_grid_info(self,
first_x,
first_y,
first_row,
first_col,
second_x,
second_y,
second_row,
second_col,
image_shape=None):
'''Populate and return a CPGridInfo based on two cell locations'''
first_row, first_col =\
self.canonical_row_and_column(first_row, first_col)
second_row, second_col =\
self.canonical_row_and_column(second_row, second_col)
gridding = cpg.CPGridInfo()
gridding.x_spacing = (float(first_x - second_x) /
float(first_col - second_col))
gridding.y_spacing = (float(first_y - second_y) /
float(first_row - second_row))
gridding.x_location_of_lowest_x_spot = int(first_x - first_col *
gridding.x_spacing)
gridding.y_location_of_lowest_y_spot = int(first_y - first_row *
gridding.y_spacing)
gridding.rows = self.grid_rows.value
gridding.columns = self.grid_columns.value
gridding.left_to_right = (self.origin
in (NUM_TOP_LEFT, NUM_BOTTOM_LEFT))
gridding.top_to_bottom = (self.origin in (NUM_TOP_LEFT, NUM_TOP_RIGHT))
gridding.total_width = int(gridding.x_spacing * gridding.columns)
gridding.total_height = int(gridding.y_spacing * gridding.rows)
line_left_x = int(gridding.x_location_of_lowest_x_spot -
gridding.x_spacing / 2)
line_top_y = int(gridding.y_location_of_lowest_y_spot -
gridding.y_spacing / 2)
#
# Make a 2 x columns array of x-coordinates of vertical lines (x0=x1)
#
gridding.vert_lines_x = np.tile(
(np.arange(gridding.columns + 1) * gridding.x_spacing +
line_left_x), (2, 1)).astype(int)
#
# Make a 2 x rows array of y-coordinates of horizontal lines (y0=y1)
#
gridding.horiz_lines_y = np.tile(
(np.arange(gridding.rows + 1) * gridding.y_spacing + line_top_y),
(2, 1)).astype(int)
#
# Make a 2x columns array of y-coordinates of vertical lines
# all of which are from line_top_y to the bottom
#
gridding.vert_lines_y = np.transpose(
np.tile((line_top_y, line_top_y + gridding.total_height),
(gridding.columns + 1, 1))).astype(int)
gridding.horiz_lines_x = np.transpose(
np.tile((line_left_x, line_left_x + gridding.total_width),
(gridding.rows + 1, 1))).astype(int)
gridding.x_locations = (
gridding.x_location_of_lowest_x_spot +
np.arange(gridding.columns) * gridding.x_spacing).astype(int)
gridding.y_locations = (
gridding.y_location_of_lowest_y_spot +
np.arange(gridding.rows) * gridding.y_spacing).astype(int)
#
# The spot table has the numbering for each spot in the grid
#
gridding.spot_table = np.arange(gridding.rows * gridding.columns) + 1
if self.ordering == NUM_BY_COLUMNS:
gridding.spot_table.shape = (gridding.rows, gridding.columns)
else:
gridding.spot_table.shape = (gridding.columns, gridding.rows)
gridding.spot_table = np.transpose(gridding.spot_table)
if self.origin in (NUM_BOTTOM_LEFT, NUM_BOTTOM_RIGHT):
# Flip top and bottom
gridding.spot_table = gridding.spot_table[::-1, :]
if self.origin in (NUM_TOP_RIGHT, NUM_BOTTOM_RIGHT):
# Flip left and right
gridding.spot_table = gridding.spot_table[:, ::-1]
if image_shape is not None:
gridding.image_height = image_shape[0]
gridding.image_width = image_shape[1]
else:
# guess the image shape by adding the same border to the right
# and bottom that we have on the left and top
top_edge = int(gridding.y_location_of_lowest_y_spot -
gridding.y_spacing / 2)
right_edge = int(gridding.x_location_of_lowest_x_spot +
gridding.x_spacing / 2)
gridding.image_height = \
top_edge * 2 + gridding.y_spacing * gridding.rows
gridding.image_width = \
right_edge * 2 + gridding.x_spacing * gridding.columns
return gridding