Merge pull request #7 from Renumics/performance_01

Performance 01

.github/workflows/workflow.yml

@@ -59,7 +59,7 @@ jobs:
         python-version: "3.9"
     - name: check
       run: |
-        poetry run pylint mesh2vec tests scripts docs/examples
+        poetry run pylint mesh2vec tests docs/examples
 
   audit:
     needs: [prepare-linux, prepare-win]
@@ -95,7 +95,7 @@ jobs:
         python-version: ${{ matrix.python-version }}
     - name: test
       run: |
-        poetry run sphinx-build docs/source build/documentation/ -W -b html # autodocs contain tests && poetry run sphinx-build docs/source build/documentation/ -W -b doctest
+        poetry run sphinx-build docs/source build/documentation/ -W -b html && poetry run sphinx-build docs/source build/documentation/ -W -b doctest
 
   unit-tests:
     needs: [prepare-linux, prepare-win]

.gitignore

@@ -4,4 +4,8 @@
 /docs/source/generated*
 __pycache__
 /data/tmp_*
-/data/*internal*
+/data/*internal*
+.DS_Store
+.venv/
+.ipynb_checkpoints
+data/data/temp_hg.joblib

docs/examples/plot_stress.py

@@ -6,7 +6,6 @@
 # pylint: disable=pointless-statement
 from pathlib import Path
 import numpy as np
-import pandas as pd
 from lasso.dyna import ArrayType
 from mesh2vec.mesh2vec_cae import Mesh2VecCae
 
@@ -19,34 +18,25 @@
     Path("../../data/hat/Hatprofile.k"),
     json_mesh_file=Path("../../data/hat/cached_hat_key.json"),
 )
-hg.add_feature_from_d3plot(
+
+
+def mean_over_components_all_layers(v):
+    """get mean over all components and all layers"""
+    return np.mean(v, axis=-1)
+
+
+fature_name = hg.add_feature_from_d3plot(
     ArrayType.element_shell_stress,
     Path("../../data/hat/HAT.d3plot"),
-    timestep=1,
-    shell_layer=0,
+    timestep=-1,
+    shell_layer=mean_over_components_all_layers,
 )
 
 
-# %%
-# Plot Feature locally
-# ------------------------
-hg.add_features_from_dataframe(
-    pd.DataFrame(
-        {
-            "vtx_id": hg.vtx_ids(),
-            "y-stress": [v[1] for v in hg.features()[ArrayType.element_shell_stress + "_1_0"]],
-        }
-    )
-)
-name = hg.aggregate("y-stress", 0, np.mean)
-fig = hg.get_visualization_plotly(str(name))
-fig.update_layout(title=name)
-fig
-
 # %%
 # Aggregate Feature and plot
 # ---------------------------
-name = hg.aggregate("y-stress", 1, np.mean)
+name = hg.aggregate(fature_name, 1, lambda x: np.mean(np.mean(x)))
 fig = hg.get_visualization_plotly(str(name))
 fig.update_layout(title=name)
 fig