fix/2d quad tri

ansys/dpf/core/meshed_region.py

@@ -183,15 +183,19 @@ def __str__(self):
     #     self._message = skin.get_output(0, types.meshed_region)
     #     return MeshedRegion(self._channel, skin, self._model, name)
 
-    def _as_vtk(self, as_linear=True):
+    def _as_vtk(self, as_linear=True, include_ids=False):
         """Convert DPF mesh to a pyvista unstructured grid"""
         from ansys.dpf.core.vtk_helper import dpf_mesh_to_vtk
         nodes = self.nodes.coordinates_field.data
         etypes = self.elements.element_types_field.data
         conn = self.elements.connectivities_field.data
         grid = dpf_mesh_to_vtk(nodes, etypes, conn, as_linear)
-        grid['node_ids'] = self.nodes.scoping.ids
-        grid['element_ids'] = self.elements.scoping.ids
+
+        # consider adding this when scoping request is faster
+        if include_ids:
+            grid['node_ids'] = self.nodes.scoping.ids
+            grid['element_ids'] = self.elements.scoping.ids
+
         return grid
 
     @property
@@ -290,7 +294,8 @@ def plot(self, field_or_fields_container=None, notebook=None,
                                    off_screen, show_axes, **kwargs)
 
         # otherwise, simply plot self
-        return pl.plot_mesh(notebook)
+        kwargs['notebook'] = notebook
+        return pl.plot_mesh(**kwargs)
 
 
 class Node:
@@ -642,13 +647,13 @@ def mapping_id_to_index(self):
             self._mapping_id_to_index = self._build_mapping_id_to_index()
         return self._mapping_id_to_index
 
-    def map_scoping(self, scope):
+    def map_scoping(self, external_scope):
         """Return the indices to map the scoping of these elements to
         the scoping of a field.
 
         Parameters
         ----------
-        scope : scoping.Scoping
+        external_scope : scoping.Scoping
             Scoping to map to.
 
         Returns
@@ -657,6 +662,9 @@ def map_scoping(self, scope):
             List of indices to map from the external scope to the
             scoping of these nodes.
 
+        mask : numpy.ndarray
+            Members of the external scope that are in the node scoping.
+
         Examples
         --------
         Return the indices that map a field to a nodes collection.
@@ -667,9 +675,10 @@ def map_scoping(self, scope):
         >>> nodes = model.metadata.meshed_region.nodes
         >>> disp = model.results.displacements()
         >>> field = disp.outputs.field_containers()[0]
-        >>> ind = nodes.map_scoping(field.scoping)
-        >>> ind
+        >>> ind, mask = nodes.map_scoping(field.scoping)
+        >>> ind, mask
         array([ 508,  509,  909, ..., 3472, 3471, 3469])
+        array([True, True, True, ..., True, True, True])
 
         These indices can then be used to remap ``nodes.coordinates`` to
         match the order of the field data.  That way the field data matches the
@@ -678,10 +687,12 @@ def map_scoping(self, scope):
         >>> mapped_nodes = nodes.coordinates[ind]
 
         """
-        if scope.location in ['Elemental', 'NodalElemental']:
+        if external_scope.location in ['Elemental', 'NodalElemental']:
             raise ValueError('Input scope location must be "Nodal"')
-        return np.array(list(map(self.mapping_id_to_index.get, scope.ids)))
-
+        arr = np.array(list(map(self.mapping_id_to_index.get, external_scope.ids)))
+        mask = arr != None
+        ind = arr[mask].astype(np.int)
+        return ind, mask
 
 class Elements():
     """Elements belonging to a ``meshed_region``.
@@ -899,13 +910,13 @@ def mapping_id_to_index(self) -> dict:
             self._mapping_id_to_index = self._build_mapping_id_to_index()
         return self._mapping_id_to_index
 
-    def map_scoping(self, scope):
+    def map_scoping(self, external_scope):
         """Return the indices to map the scoping of these elements to
         the scoping of a field.
 
         Parameters
         ----------
-        scope : scoping.Scoping
+        external_scope : scoping.Scoping
             Scoping to map to.
 
         Returns
@@ -914,6 +925,9 @@ def map_scoping(self, scope):
             List of indices to map from the external scope to the
             scoping of these elements.
 
+        mask : numpy.ndarray
+            Members of the external scope that are in the element scoping.
+
         Examples
         --------
         Return the indices that map a field to an elements collection.
@@ -924,7 +938,7 @@ def map_scoping(self, scope):
         >>> elements = model.metadata.meshed_region.elements
         >>> vol = model.results.volume()
         >>> field = vol.outputs.field_containers()[0]
-        >>> ind = elements.map_scoping(field.scoping)
+        >>> ind, mask = elements.map_scoping(field.scoping)
         >>> ind
         [66039
          11284,
@@ -942,6 +956,9 @@ def map_scoping(self, scope):
         >>> mapped_data = field.data[ind]
 
         """
-        if scope.location in ['Nodal', 'NodalElemental']:
-            raise ValueError('Input scope location must be "Elemental"')
-        return np.array(list(map(self.mapping_id_to_index.get, scope.ids)))
+        if external_scope.location in ['Nodal', 'NodalElemental']:
+            raise ValueError('Input scope location must be "Nodal"')
+        arr = np.array(list(map(self.mapping_id_to_index.get, external_scope.ids)))
+        mask = arr != None
+        ind = arr[mask].astype(np.int)
+        return ind, mask

ansys/dpf/core/plotter.py

@@ -19,7 +19,7 @@ class Plotter:
     def __init__(self, mesh):
         self._mesh = mesh
 
-    def plot_mesh(self, notebook=None):
+    def plot_mesh(self, **kwargs):
         """Plot the mesh using pyvista.
 
         Parameters
@@ -30,26 +30,33 @@ def plot_mesh(self, notebook=None):
             external to the notebook with an interactive window.  When
             ``True``, always plot within a notebook.
 
+        **kwargs : optional
+            Additional keyword arguments for the plotter.  See
+            ``help(pyvista.plot)`` for additional keyword arguments.
         """
-        return self._mesh.grid.plot(notebook=notebook)
-
+        kwargs.setdefault('color', 'w')
+        kwargs.setdefault('show_edges', True)
+        return self._mesh.grid.plot(**kwargs)
+
     def plot_chart(self, fields_container):
-        """Plot the minimum/maximum result values over time 
-        if the time_freq_support contains several time_steps 
-        (for example: transient analysis)
+        """Plot the minimum/maximum result values over time.
+
+        This is a valid method if the time_freq_support contains
+        several time_steps (for example, a transient analysis)
 
         Parameters
         ----------
-        field_container
-            dpf.core.FieldsContainer that must contains a result for each time step of the time_freq_support.
+        field_container : dpf.core.FieldsContainer
+            A fields container that must contains a result for each
+            time step of the time_freq_support.
 
         Examples
         --------
         >>> from ansys.dpf import core
         >>> model = core.Model('file.rst')
         >>> stress = model.results.stress()
         >>> scoping = core.Scoping()
-        >>> scoping.ids = list(range(1, len(model.metadata.time_freq_support.frequencies) + 1))
+        >>> scoping.ids = range(1, len(model.metadata.time_freq_support.frequencies) + 1)
         >>> stress.inputs.time_scoping.connect(scoping)
         >>> fc = stress.outputs.fields_container()
         >>> plotter = core.plotter.Plotter(model.metadata.meshed_region)
@@ -65,8 +72,8 @@ def plot_chart(self, fields_container):
         minmaxOp.inputs.connect(normOp.outputs)
         fieldMin = minmaxOp.outputs.field_min()
         fieldMax = minmaxOp.outputs.field_max()
-        pyplot.plot(time_field.data,fieldMax.data,'r',label='Maximum')
-        pyplot.plot(time_field.data,fieldMin.data,'b',label='Minimum')
+        pyplot.plot(time_field.data, fieldMax.data, 'r', label='Maximum')
+        pyplot.plot(time_field.data, fieldMin.data, 'b', label='Minimum')
         unit = tfq.frequencies.unit
         if unit == "Hz":
             pyplot.xlabel("frequencies (Hz)")
@@ -76,7 +83,7 @@ def plot_chart(self, fields_container):
             pyplot.xlabel(unit)
         substr = fields_container[0].name.split("_")
         pyplot.ylabel(substr[0] + fieldMin.unit)
-        pyplot.title( substr[0] + ": min/max values over time")
+        pyplot.title(substr[0] + ": min/max values over time")
         return pyplot.legend()
 
     def plot_contour(self, field_or_fields_container, notebook=None,
@@ -181,8 +188,8 @@ def plot_contour(self, field_or_fields_container, notebook=None,
             overall_data = np.full(len(mesh_location), np.nan)
 
         for field in fields_container:
-            ind = mesh_location.map_scoping(field.scoping)
-            overall_data[ind] = field.data
+            ind, mask = mesh_location.map_scoping(field.scoping)
+            overall_data[ind] = field.data[mask]
 
         # create the plotter and add the meshes
         plotter = pv.Plotter(notebook=notebook, off_screen=off_screen)
@@ -233,4 +240,3 @@ def _plot_contour_using_vtk_file(self, fields_container, notebook=None):
         plotter.add_mesh(grid, scalars=val, stitle=field_name, show_edges=True)
         plotter.add_axes()
         plotter.show()
-

ansys/dpf/core/vtk_helper.py

@@ -180,6 +180,15 @@ def compute_offset():
             cells[cell_pos + 7] = cells[cell_pos + 3]
             cells[cell_pos + 8] = cells[cell_pos + 4]
 
+        anstri6_mask = etypes == 4  # kAnsTri6 = 4
+        if np.any(anstri6_mask):
+            if offset is None:
+                offset = compute_offset()
+            cell_pos = offset[anstri6_mask]
+            cells[cell_pos + 4] = cells[cell_pos + 1]
+            cells[cell_pos + 5] = cells[cell_pos + 2]
+            cells[cell_pos + 6] = cells[cell_pos + 3]
+
     else:
         vtk_cell_type = VTK_MAPPING[etypes]
 

examples/01-static-transient/00-basic_transient.py

@@ -154,7 +154,7 @@
 # to match the order of nodes in the mesh.
 
 nodes = meshed_region.nodes
-ind = nodes.map_scoping(field.scoping)
+ind, mask = nodes.map_scoping(field.scoping)
 
 # show that the order of the remapped node scoping matches the field scoping
 print('Scoping matches:', np.allclose(np.array(nodes.scoping.ids)[ind],

tests/test_meshregion.py

@@ -29,7 +29,7 @@ def test_get_mesh_from_model(simple_bar_model):
 
 def test_vtk_grid_from_model(simple_bar_model):
     mesh = simple_bar_model.metadata.meshed_region
-    grid = mesh.grid
+    grid = mesh._as_vtk(include_ids=True)
     assert np.allclose(grid['element_ids'], mesh.elements.scoping.ids)
     assert np.allclose(grid['node_ids'], mesh.nodes.scoping.ids)
     assert all(grid.celltypes == vtk.VTK_HEXAHEDRON)