def _update_selection(self):
""" Sets the selection datasource's 'selection' metadata element
to a mask of all the points selected
"""
if self.selection_datasource is None:
return
selected_mask = zeros(self.selection_datasource._data.shape, dtype=numpy.int32)
data = self._get_data()
# Compose the selection mask from the cached selections first, then
# the active selection, taking into account the selection mode only
# for the active selection
for selection in self._previous_selections:
selected_mask |= (points_in_polygon(data, selection, False))
if self.selection_mode == 'exclude':
selected_mask |= (points_in_polygon(data, self._active_selection, False))
selected_mask = 1 - selected_mask
elif self.selection_mode == 'invert':
selected_mask = -1 * (selected_mask -points_in_polygon(data, self._active_selection, False))
else:
selected_mask |= (points_in_polygon(data, self._active_selection, False))
if sometrue(selected_mask != self.selection_datasource.metadata['selection']):
self.selection_datasource.metadata['selection'] = selected_mask
self.selection_changed = True
return
def _selection_changed(self):
data = np.logical_not(points_in_polygon(self.img_index, self.lasso.dataspace_points, False).astype(np.bool))
data = data.reshape((256, 256))
copy = self.img_data.copy()
copy[data] = 0
self.plotdata["mask_data"] = copy
self.plot2.request_redraw()
def is_in(self, point_x, point_y):
""" Test if a point is within this polygonal region """
point_array = array(((point_x, point_y), ))
vertices = array(self.points)
winding = self.inside_rule == "winding"
result = points_in_polygon(point_array, vertices, winding)
return result[0]
def is_in(self, point_x, point_y):
""" Test if a point is within this polygonal region """
point_array = array(((point_x, point_y),))
vertices = array(self.points)
winding = self.inside_rule == "winding"
result = points_in_polygon(point_array, vertices, winding)
return result[0]
def _eval ( self, model ):
""" Evaluates the result of the filter for the specified model.
"""
if len( self.points ) == 0:
return None
points = array( zip( getattr( model, self.x_value ),
getattr( model, self.y_value ) ) )
result = None
for items in self.points:
pip = points_in_polygon( points, array( items ) )
if result is None:
result = pip
else:
result = result | pip
return result
def hittest(self, screen_pt, threshold=7.0, return_distance=False):
""" Performs point-in-polygon testing or point/line proximity testing.
If self.hittest_type is "line" or "point", then behaves like the
parent class BaseXYPlot.hittest().
If self.hittest_type is "poly", then returns True if the given
point is inside the polygon, and False otherwise.
"""
if self.hittest_type in ("line", "point"):
return BaseXYPlot.hittest(self, screen_pt, threshold, return_distance)
data_pt = self.map_data(screen_pt, all_values=True)
index = self.index.get_data()
value = self.value.get_data()
poly = np.vstack((index,value)).T
if points_in_polygon([data_pt], poly)[0] == 1:
return True
else:
return False
def hittest(self, screen_pt, threshold=7.0, return_distance=False):
""" Performs point-in-polygon testing or point/line proximity testing.
If self.hittest_type is "line" or "point", then behaves like the
parent class BaseXYPlot.hittest().
If self.hittest_type is "poly", then returns True if the given
point is inside the polygon, and False otherwise.
"""
if self.hittest_type in ("line", "point"):
return BaseXYPlot.hittest(self, screen_pt, threshold, return_distance)
data_pt = self.map_data(screen_pt, all_values=True)
index = self.index.get_data()
value = self.value.get_data()
poly = np.vstack((index,value)).T
if points_in_polygon([data_pt], poly)[0] == 1:
return True
else:
return False
def find_star(self, x, y):
from enthought.kiva.agg import points_in_polygon
for star in self.stars[::-1]:
if points_in_polygon((x, y), star.polygon()):
return star
return None
