Example/example re assembling fields

examples/01-mathematical-operations/matrix-operations.py

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+"""
+.. _ref_matrix-operations:
+
+Matrix Operations
+~~~~~~~~~~~~~~~~~
+
+This example shows how to do some matrix operations, including basic mathematical operations (power, add and multiply by
+a constant, add field containers and invert) and separating and assembling fields and fields containers.
+
+"""
+
+###############################################################################
+# Import the ``ansys.dpf.core`` module, included examples file, and the ``DpfPlotter``
+# module.
+from ansys.dpf import core as dpf
+from ansys.dpf.core import examples
+import ansys.dpf.core.operators.math as maths
+
+###############################################################################
+# Open an example and print the ``Model`` object. Here a result file from a crankshaft
+# under load simulation is used.
+# The :class:`Model <ansys.dpf.core.model.Model>` class helps to organize access
+# methods for the result by keeping track of the operators and data sources
+# used by the result file.
+#
+# Printing the model displays this metadata:
+#
+# - Analysis type
+# - Available results
+# - Size of the mesh
+# - Number of results
+#
+my_model = dpf.Model(examples.find_complex_rst())
+my_mesh = my_model.metadata.meshed_region
+# print(my_model)
+###############################################################################
+# Get the stress tensor and define it's scoping. Here, only three nodes will be take into account to facilitate the
+# results visualisation
+my_nodes_scoping = dpf.Scoping(ids=[38, 37, 36], location=dpf.locations.elemental)
+my_stress = my_model.results.stress(mesh_scoping=my_nodes_scoping).eval()
+
+# Here we need to average the result from 'elemental_nodal' to an 'elemental' location to
+# facilitate the visualisation of the plot
+my_avg_stress = dpf.operators.averaging.to_elemental_fc(fields_container=my_stress, mesh=my_mesh).eval()
+# print(my_avg_stress, my_avg_stress[0])
+
+#########################################################
+# Separating tensor by component
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+# If operations need to be done separetly in each tensor component, the
+# :func:'select_component()<ansys.dpf.core.fields_container.FieldsContainer.select_component>'.
+# Here, the stress tensor has 6 components by elementary data (symmetrical tensor XX,YY,ZZ,XY,YZ,XZ).
+
+for i in range(0, 6):  # Separating the results in different fields containers for each stress tensor component
+    globals()[f'stress_{i + 1}'] = my_avg_stress.select_component(i)
+
+################################################################################
+# Mathematical operation on each field
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+# Here we will do some basic mathematical operations on
+# Power
+# Compute the power operation for each elementary data
+stress_1 = maths.pow_fc(fields_container=stress_1, factor=2.0).eval()
+
+# Add constant
+# Each component of each field is added by 2
+stress_2 = maths.add_constant_fc(fields_container=stress_2, ponderation=2.0).eval()
+
+# Multiply by a constant
+# Each component of each field is multiplied by 3
+stress_3 = maths.scale_fc(fields_container=stress_3, ponderation=3.0).eval()
+
+# Add fields containers
+# Each component of each field is added by the correspondent component of the others fields
+stress_4 = maths.add_fc(fields_container1=stress_4, fields_container2=stress_5).eval()
+stress_5 = maths.add_fc(fields_container1=stress_5, fields_container2=stress_6).eval()
+
+#Invert
+# Compute the invert of each element of each field (1./X)
+stress_6 = maths.invert_fc(fields_container=stress_6).eval()
+
+################################################################################
+# Reassembling the stress tensor
+# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+# There are different methods to re-assemble the components
+
+# 1) With the class :class:'assemble_scalars_to_matrices_fc <ansys.dpf.core.operators.utility.assemble_scalars_to_matrices_fc.assemble_scalars_to_matrices_fc>'
+assemble_1 = dpf.operators.utility.assemble_scalars_to_matrices_fc(xx=stress_1, yy=stress_2, zz=stress_3,
+                                                                   xy=stress_4, yz=stress_5, xz=stress_6,
+                                                                   symmetrical=True).eval()
+print(assemble_1, assemble_1[0])
+