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]) 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