Apply suggestions from code review

Co-authored-by: Paul Profizi <[email protected]>

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

@@ -17,8 +17,7 @@
 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.
+Open an example and print the ``Model`` object
 # 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.
@@ -34,23 +33,22 @@
 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
+# Get the stress tensor and define its scoping. Only three nodes will be taken into account to facilitate the
+# visualization.
 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
+# We need to average the result from 'elemental_nodal' to an 'elemental' location to plot it.
 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])
+print(my_avg_stress, my_avg_stress[0])
 
 #########################################################
 # Separating tensor by component
 # ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
-# If operations need to be done separetly in each tensor component, the
+# If operations need to be done separately in each tensor component, use
 # :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).
+# Here, the stress tensor has 6 components per 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)
@@ -64,20 +62,20 @@
 # 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
+# Add a constant
+# Add 2 to each value in the field
 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
+# Multiply each value in the field 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
+# Each value 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
+# Invert
 # Compute the invert of each element of each field (1./X)
 stress_6 = maths.invert_fc(fields_container=stress_6).eval()
 
@@ -87,7 +85,7 @@
 
 # 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>'
+# 1) With the operator :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()