def _update_ranges(self):
# Here we get the module's source since the input of this
# component may not in general represent the entire object.
if not self.auto_update_range:
return
src = get_module_source(self.inputs[0])
dataset = self._get_source_dataset(src)
sc = dataset.point_data.scalars
if sc is not None:
sc_array = sc.to_array()
has_nan = numpy.isnan(sc_array).any()
if has_nan:
rng = (float(numpy.nanmin(sc_array)),
float(numpy.nanmax(sc_array)))
else:
rng = sc.range
else:
error('Cannot contour: No scalars in input data!')
rng = (0.0, 1.0)
if rng != self._current_range:
self.set(_data_min=rng[0],
_data_max=rng[1],
trait_change_notify=False)
self._clip_contours(rng)
self._current_range = rng
def _update_ranges(self):
# Here we get the module's source since the input of this
# component may not in general represent the entire object.
if not self.auto_update_range:
return
src = get_module_source(self.inputs[0])
dsh = DataSetHelper(src.outputs[0])
name, rng = dsh.get_range('scalars', 'point')
if name is None:
error('Cannot contour: No scalars in input data!')
rng = (0.0, 1.0)
if rng != self._current_range:
self.trait_set(_data_min=rng[0], _data_max=rng[1],
trait_change_notify=False)
self._clip_contours(rng)
self._current_range = rng
def _update_ranges(self):
# Here we get the module's source since the input of this
# component may not in general represent the entire object.
if not self.auto_update_range:
return
src = get_module_source(self.inputs[0])
dsh = DataSetHelper(src.outputs[0])
name, rng = dsh.get_range('scalars', 'point')
if name is None:
error('Cannot contour: No scalars in input data!')
rng = (0.0, 1.0)
if rng != self._current_range:
self.trait_set(_data_min=rng[0],
_data_max=rng[1],
trait_change_notify=False)
self._clip_contours(rng)
self._current_range = rng
def _update_ranges(self):
# Here we get the module's source since the input of this
# component may not in general represent the entire object.
if not self.auto_update_range:
return
src = get_module_source(self.inputs[0])
sc = src.outputs[0].point_data.scalars
if sc is not None:
sc_array = sc.to_array()
has_nan = numpy.isnan(sc_array).any()
if has_nan:
rng = (float(numpy.nanmin(sc_array)),
float(numpy.nanmax(sc_array)))
else:
rng = sc.range
else:
error('Cannot contour: No scalars in input data!')
rng = (0.0, 1.0)
if rng != self._current_range:
self.set(_data_min=rng[0], _data_max=rng[1],
trait_change_notify=False)
self._clip_contours(rng)
self._current_range = rng