Merge remote-tracking branch 'origin/develop'

.gitlab-ci.yml

@@ -3,6 +3,8 @@ image: registry.ritc.jp/ricos/simulation/femio/fistr_ricos:0.3.2py3.9
 default:
   before_script:
     - poetry config virtualenvs.create false
+    - python3.9 -m pip install vtk==9.2.6
+    - python3.9 -m pip install mayavi==4.8.1
     - poetry build
     - python3.9 -m pip install dist/femio-*.whl  # Only install root project, not dependencies
     # - poetry env use /usr/bin/python3.9

femio/fem_data.py

@@ -678,7 +678,9 @@ def flatten(indices, element_type):
         surface_indices, _ = self.extract_surface()
         if isinstance(surface_indices, dict):
             unique_indices = np.unique(np.concatenate([
-                flatten(v, k) for k, v in surface_indices.items()]))
+                flatten(v, k) for k, v in surface_indices.items()
+                if len(v) > 0
+            ]))
             surface_ids = {
                 t: self.nodes.ids[ids] for t, ids in surface_indices.items()
                 if t != 'polygon'}

femio/formats/polyvtk/write_polyvtk.py

@@ -1,6 +1,4 @@
 
-import fileinput
-
 import numpy as np
 from tvtk.api import tvtk
 
@@ -62,10 +60,6 @@ def write(self, file_name=None, *, overwrite=False):
         writer.set_input_data(unstructured_grid)
         writer.write()
 
-        # Replace int64 with int32 because tvtk has trouble to read it
-        with fileinput.input(file_name, inplace=True) as file:
-            for line in file:
-                print(line.replace('Int64', 'Int32'), end='')
         return file_name
 
     def _reorder_cell_data(self, data):

femio/graph_processor.py

@@ -500,7 +500,7 @@ def calculate_element_degree(self):
 
     @functools.lru_cache(maxsize=2)
     def calculate_adjacency_matrix(
-            self, *, mode='elemental', order1_only=True):
+            self, *, mode='elemental', order1_only=False):
         """Calculate graph adjacency matrix.
 
         Parameters
@@ -528,7 +528,7 @@ def calculate_adjacency_matrix(
         return adj
 
     @functools.lru_cache(maxsize=1)
-    def calculate_adjacency_matrix_element(self):
+    def calculate_adjacency_matrix_element(self, order1_only=False):
         """Calculate graph adjacency matrix regarding elements sharing the same
         node as connected.
 
@@ -541,11 +541,11 @@ def calculate_adjacency_matrix_element(self):
         print(dt.datetime.now())
         # raise ValueError(node_ids, element_data, )
         incidence_matrix = self.calculate_incidence_matrix(
-            order1_only=True)
+            order1_only=order1_only)
         return incidence_matrix.T.dot(incidence_matrix).tocsr()
 
     @functools.lru_cache(maxsize=1)
-    def calculate_adjacency_matrix_node(self, order1_only=True):
+    def calculate_adjacency_matrix_node(self, order1_only=False):
         """Calculate graph adjacency matrix regarding nodes connected with
         edges. Edges are defined by element shearing.
 
@@ -567,7 +567,7 @@ def calculate_adjacency_matrix_node(self, order1_only=True):
         return incidence_matrix.dot(incidence_matrix.T)
 
     @functools.lru_cache(maxsize=1)
-    def calculate_incidence_matrix(self, order1_only=True):
+    def calculate_incidence_matrix(self, order1_only=False):
         """Calculate graph incidence matrix, which is
         (n_node, n_element)-shaped matrix with bool.
 
@@ -617,7 +617,7 @@ def calculate_incidence_matrix(self, order1_only=True):
         return incidence_matrix
 
     @functools.lru_cache(maxsize=2)
-    def calculate_laplacian_matrix(self, mode='nodal', order1_only=True):
+    def calculate_laplacian_matrix(self, mode='nodal', order1_only=False):
         """Calculate edge-based graph incidence matrix, which is
         (n_edge, n_node)-shaped matrix with bool.
 
@@ -645,7 +645,7 @@ def calculate_laplacian_matrix(self, mode='nodal', order1_only=True):
         return adj_wo_loop - degree
 
     @functools.lru_cache(maxsize=1)
-    def calculate_edge_gradient_matrix(self, mode='nodal', order1_only=True):
+    def calculate_edge_gradient_matrix(self, mode='nodal', order1_only=False):
         """Calculate edge-based graph gradient matrix, which is
         (n_edge, n_vertex)-shaped matrix with bool. n_vertex can be either
         n_node or n_element, depending on the `mode` option.
@@ -682,7 +682,7 @@ def calculate_edge_gradient_matrix(self, mode='nodal', order1_only=True):
     @functools.lru_cache(maxsize=15)
     def calculate_n_hop_adj(
             self, mode='elemental', n_hop=1, include_self_loop=True,
-            order1_only=True):
+            order1_only=False):
         if mode == 'elemental':
             adj = self.calculate_adjacency_matrix_element()
 

femio/signal_processor.py

@@ -48,7 +48,7 @@ def convert_nodal2elemental(
         return elemental_data
 
     def convert_elemental2nodal(
-            self, elemental_data, mode='mean', order1_only=True,
+            self, elemental_data, mode='mean', order1_only=False,
             raise_negative_volume=True, weight=None, incidence=None):
         """Convert elemental data to nodal data.
 
@@ -283,7 +283,7 @@ def calculate_moving_average_elemental_data(
         return averaged_data
 
     def calculate_moving_average_nodal_data(
-            self, nodal_data, *, hops=1, weight=.1, order1_only=True):
+            self, nodal_data, *, hops=1, weight=.1, order1_only=False):
         """Perform moving average according with adjacency of the mesh.
 
         Args:
@@ -324,7 +324,7 @@ def calculate_moving_average_nodal_data(
         return averaged_data
 
     def calculate_median_filter(
-            self, data, *, mode='elemental', hops=1, order1_only=True):
+            self, data, *, mode='elemental', hops=1, order1_only=False):
         """Perform median filter according with adjacency of the mesh.
 
         Args:
@@ -358,7 +358,7 @@ def calculate_median_filter(
         return filtered_data
 
     def calculate_frame_expansion_adjs(
-            self, data, mode='nodal', n_hop=1, order1_only=True, **kwargs):
+            self, data, mode='nodal', n_hop=1, order1_only=False, **kwargs):
         """Calculate frame expansion adjacency matrices.
 
         Parameters
@@ -402,7 +402,7 @@ def calculate_frame_expansion_adjs(
 
     @functools.lru_cache(maxsize=10)
     def calculate_frame_tensor_adjs(
-            self, mode='elemental', n_hop=1, order1_only=True, tensor_rank=1):
+            self, mode='elemental', n_hop=1, order1_only=False, tensor_rank=1):
         """Calculate frame adjacency matrices F s.t. phi = F phi,
         based on frame which are set of relative vectors coming from mesh
         topology.
@@ -654,7 +654,7 @@ def calculate_elemental_spatial_gradients(
             grad_adj.dot(elemental_data) for grad_adj in grad_adjs], axis=1)
 
     def calculate_nodal_spatial_gradients(
-            self, nodal_data, n_hop=1, kernel=None, order1_only=True,
+            self, nodal_data, n_hop=1, kernel=None, order1_only=False,
             normals=None, **kwargs):
         """Calculate spatial gradient (not graph gradient) w.r.t nodal
         data.
@@ -693,7 +693,7 @@ def calculate_nodal_spatial_gradients(
             for grad_adj in grad_adjs], axis=1)
 
     def calculate_spatial_gradient_adjacency_matrices(
-            self, mode='elemental', n_hop=1, kernel=None, order1_only=True,
+            self, mode='elemental', n_hop=1, kernel=None, order1_only=False,
             use_effective_volume=True, moment_matrix=False,
             consider_volume=True, normals=None, normal_weight=1.,
             normal_weight_factor=None, adj=None,
@@ -897,7 +897,7 @@ def sum_axis_1_with_weight(x):
         return grad_adjs
 
     def calculate_spatial_gradient_incidence_matrix(
-            self, mode='nodal', order1_only=True,
+            self, mode='nodal', order1_only=False,
             moment_matrix=True, normals=None, normal_weight=1., **kwargs):
         """Calculate spatial gradient (not graph gradient) incidence matrix.
 

pyproject.toml

@@ -20,8 +20,8 @@ numpy-stl    = "^2.13"
 pandas       = "^1.0"
 scipy        = "^1.7.0"
 lxml = "^4.6.3"
-vtk = "^9.0.3"
-mayavi = "^4.7.3"
+vtk = "^9.2.6"
+mayavi = "^4.8.1"
 PyQt5 = {version = "^5.14.0", optional = true}
 
 [tool.poetry.extras]