use only the jupyter sphinx extension

Author: luisaFelixSalles

doc/source/user_guide/tutorials/plot/plotting_a_graph.rst

@@ -31,7 +31,7 @@ Define the data
 
 We will download a simple simulation result file available in our `Examples` package:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Import the ``ansys.dpf.core`` module, including examples files, the operators subpackage, the geometry module and the matplotlib
     from ansys.dpf import core as dpf
@@ -45,15 +45,15 @@ We will download a simple simulation result file available in our `Examples` pac
 The results will be mapped over a defined path of coordinates. So, start by creating
 a |Model| with the result file and extract the |MeshedRegion| from it:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Create the model
     my_model = dpf.Model(data_sources=result_file)
     my_meshed_region = my_model.metadata.meshed_region
 
 We choose to plot the displacement results field. Extract the displacements results from the model:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Get the displacement results
     my_disp = my_model.results.displacement.eval()
@@ -63,7 +63,7 @@ Create the line
 
 Create a |Line| passing through the mesh diagonal.
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Create the Line object
     my_line = geo.Line(coordinates=[[0.0, 0.06, 0.0], [0.03, 0.03, 0.03]],
@@ -75,7 +75,7 @@ Map displacement field to the line
 
 Compute the mapped displacement data using the |mapping| operator.
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Map the line coordinates with the displacement results and get the field
     mapped_disp_line = ops.mapping.on_coordinates(fields_container=my_disp,
@@ -92,43 +92,15 @@ Plot a graph of the displacement field along the specified |Line| length using t
 To get the |Line| length you can use the |Line| property :func:`path<ansys.dpf.core.geometry.Line.path>`.
 It gives the 1D line coordinates, by the number of points the line was discretized.
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Define the norm of the displacement field
     norm_disp = ops.math.norm(field=mapped_disp_line).eval()
     # Define the line points on the its length
     line_length_points = my_line.path
     # Plot the graph
-    plt.plot(line_length_points, norm_disp)
-    # Graph formating
-    plt.xlabel("Line length");  plt.ylabel("Displacement norm field"); plt.title("Displacement evolution on the line")
-    plt.show()
-
-.. rst-class:: sphx-glr-script-out
-
- .. jupyter-execute::
-    :hide-code:
-
-    from ansys.dpf import core as dpf
-    from ansys.dpf.core import examples
-    from ansys.dpf.core import operators as ops
-    from ansys.dpf.core import geometry as geo
-    import matplotlib.pyplot as plt
-    result_file = examples.find_static_rst()
-    my_model = dpf.Model(data_sources=result_file)
-    my_meshed_region = my_model.metadata.meshed_region
-    my_disp = my_model.results.displacement.eval()
-    my_line = geo.Line(coordinates=[[0.0, 0.06, 0.0], [0.03, 0.03, 0.03]],
-                       n_points=50
-                       )
-    mapped_disp_line = ops.mapping.on_coordinates(fields_container=my_disp,
-                                                  coordinates=my_line.mesh.nodes.coordinates_field,
-                                                  create_support=True,
-                                                  mesh=my_meshed_region
-                                                   ).eval()[0]
-    norm_disp = ops.math.norm(field=mapped_disp_line).eval()
-    line_length_points = my_line.path
     plt.plot(line_length_points, norm_disp.data)
+    # Graph formating
     plt.xlabel("Line length");  plt.ylabel("Displacement norm field"); plt.title("Displacement evolution on the line")
     plt.show()
 
@@ -144,7 +116,7 @@ Define the data
 Download the transient result example. This example is not included in DPF-Core
 by default to speed up the installation. Downloading this example should take only a few seconds.
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Import the ``ansys.dpf.core`` module, including examples files, the operators subpackage and the matplotlib
     from ansys.dpf import core as dpf
@@ -157,7 +129,7 @@ by default to speed up the installation. Downloading this example should take on
 The results will be mapped over a defined path of coordinates. So, start by creating
 a |Model| with the result file and extract the |MeshedRegion| from it:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Create the model
     my_model = dpf.Model(data_sources=result_file)
@@ -166,14 +138,14 @@ a |Model| with the result file and extract the |MeshedRegion| from it:
 We choose to plot the maximum and minimum displacement results over time.
 Extract the displacements results from the model for all the time frequencies:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Get the displacement results
     my_disp = my_model.results.displacement.on_all_time_freqs.eval()
 
 Define the minimum and maximum displacements for all results:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Define the min_max operator with the normed displacement
     min_max_op = ops.min_max.min_max_fc(fields_container=ops.math.norm_fc(my_disp))
@@ -186,33 +158,12 @@ Plot a graph of the minimum and maximum displacements over time
 
 Plot a graph of the minimum and maximum displacements over time using the matplotlib library.
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Define the time frequencies from the model
     time_data = my_model.metadata.time_freq_support.time_frequencies.data
     # Plot the graph
     plt.plot(time_data, max_disp.data, "r", label="Max")
     plt.plot(time_data, min_disp.data, "b", label="Min")
     # Graph formating
-    plt.xlabel("Time (s)"); plt.ylabel("Displacement (m)"); plt.legend(); plt.show()
-
-.. rst-class:: sphx-glr-script-out
-
- .. jupyter-execute::
-    :hide-code:
-
-    from ansys.dpf import core as dpf
-    from ansys.dpf.core import examples
-    from ansys.dpf.core import operators as ops
-    import matplotlib.pyplot as plt
-    result_file = examples.download_transient_result()
-    my_model = dpf.Model(data_sources=result_file)
-    my_meshed_region = my_model.metadata.meshed_region
-    my_disp = my_model.results.displacement.on_all_time_freqs.eval()
-    min_max_op = ops.min_max.min_max_fc(fields_container=ops.math.norm_fc(my_disp))
-    max_disp = min_max_op.eval(pin=1)
-    min_disp = min_max_op.eval(pin=0)
-    time_data = my_model.metadata.time_freq_support.time_frequencies.data
-    plt.plot(time_data, max_disp.data, "r", label="Max")
-    plt.plot(time_data, min_disp.data, "b", label="Min")
     plt.xlabel("Time (s)"); plt.ylabel("Displacement (m)"); plt.legend(); plt.show()

doc/source/user_guide/tutorials/plot/plotting_data_on_deformed_mesh.rst

@@ -19,7 +19,7 @@ Define the data
 In this tutorial we will download a simulation result file available
 in our ``Examples`` package:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Import the ``ansys.dpf.core`` module, including examples files and operators subpackage
     from ansys.dpf import core as dpf
@@ -33,32 +33,20 @@ metadata, by opening a DataSources or a Streams, and to instanciate results prov
 
 Printing the model displays the available results.
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Create the model
     my_model = dpf.Model(data_sources=result_file)
     # Print the model
     print(my_model)
 
-.. rst-class:: sphx-glr-script-out
-
- .. jupyter-execute::
-    :hide-code:
-
-    from ansys.dpf import core as dpf
-    from ansys.dpf.core import examples
-    from ansys.dpf.core import operators as ops
-    result_file = examples.find_multishells_rst()
-    my_model = dpf.Model(data_sources=result_file)
-    print(my_model)
-
 
 To deform the mesh we need a result with a homogeneous unit dimension, a distance unit.
 Thus, to deform the mesh we need the displacement result.
 
 Extract the displacements results from the model:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Get the displacement results
     my_disp_result = my_model.results.displacement
@@ -71,7 +59,7 @@ to work with the XX stress tensor component result.
 Fot more information about extracting results from a result file check
 the :ref:`ref_tutorials_import_data` tutorials section.
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Extract the stress result
     my_stress = my_model.results.stress()
@@ -80,7 +68,7 @@ As the stress result is in a ``ElementalNodal`` location we have to change it.
 Here we define the new location with a input of the
 :class:`stress() <ansys.dpf.core.operators.result.stress.stress>` operator.
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Define the desired location as an input of the results operator
     my_stress.inputs.requested_location(dpf.locations.nodal)
@@ -91,7 +79,7 @@ To get the results only for the XX stress component we have to use
 the :func:`select_component() <ansys.dpf.core.fields_container.FieldsContainer.select_component>`
 method:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Define the component to get.
     # The stress tensor has 6 components per elementary data (symmetrical tensor XX,YY,ZZ,XY,YZ,XZ).
@@ -107,7 +95,7 @@ The geometry can be defined by a |MeshedRegion| or by a |MeshesContainer|.
 
 Define the |MeshedRegion| from the |Model|:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Define the meshed region
     my_meshed_region = my_model.metadata.meshed_region
@@ -117,7 +105,7 @@ There are different ways to obtain a |MeshesContainer|.
 Here we get a |MeshesContainer| by using the :class:`split_mesh <ansys.dpf.core.operators.mesh.split_mesh.split_mesh>`
 operator. It splits the mesh by material by default:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Define the meshed region
     my_meshes = ops.mesh.split_mesh(mesh=my_meshed_region).eval()
@@ -129,7 +117,7 @@ or a :class:`FieldsContainer<ansys.dpf.core.field.Field>`.
 The procedures are the same for a |MeshedRegion| and a |MeshesContainer|. For this reason we will show only
 one plot for the |MeshesContainer|
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Define the plot formating
     my_scale_factor = 0.001
@@ -165,112 +153,36 @@ one plot for the |MeshesContainer|
                            text="e",
                            window_size=my_window_size)
 
-.. rst-class:: sphx-glr-script-out
-
- .. jupyter-execute::
-    :hide-code:
-
-    my_meshed_region = my_model.metadata.meshed_region
-    my_meshes = ops.mesh.split_mesh(mesh=my_meshed_region).eval()
-    my_disp_result = my_model.results.displacement
-    my_stress = my_model.results.stress()
-    my_stress.inputs.requested_location(dpf.locations.nodal)
-    fc_stress = my_stress.eval()
-    my_disp_result = my_model.results.displacement
-    my_stress = my_model.results.stress()
-    my_scale_factor = 0.001
-    my_window_size=[350,350]
-    my_meshed_region.plot( deform_by=my_disp_result,
-                           scale_factor=my_scale_factor,
-                           text="a",
-                           window_size=my_window_size)
-    my_disp_op = my_disp_result()
-    my_meshed_region.plot( deform_by=my_disp_op,
-                           scale_factor=my_scale_factor,
-                           text="b",
-                           window_size=my_window_size)
-    my_disp_fc = my_disp_result.eval()
-    my_meshed_region.plot( deform_by=my_disp_fc,
-                           scale_factor=my_scale_factor,
-                           text="c",
-                           font_size=5,
-                           window_size=my_window_size)
-    my_disp_field = my_disp_fc[0]
-    my_meshed_region.plot( deform_by=my_disp_field,
-                           scale_factor=my_scale_factor,
-                           text="d",
-                           window_size=my_window_size)
-    my_meshes.plot( deform_by=my_disp_field,
-                           scale_factor=my_scale_factor,
-                           text="e",
-                           window_size=my_window_size)
-
 Plot data on the deformed geometry
 ----------------------------------
 
 Plot the data on its mesh support
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-Plotting the data in DPF means plotting the |Field| or |FieldsContainer| that contains the data.
+Plotting the data in DPF means plotting the |Field| that contains the data.
 
 Plot the stress results on the deformed geometry:
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Define the stress field
     stress_field = fc_stress[0]
-    # Plot the results on a deformed geometry. The data is in a:
-    # a) Field
-    stress_field.plot( deform_by=my_disp_field,
-                        scale_factor=my_scale_factor)
-
-.. rst-class:: sphx-glr-script-out
-
- .. jupyter-execute::
-    :hide-code:
-
-    stress_field = fc_stress[0]
+    # Plot the results on a deformed geometry. The data is in a Field
     stress_field.plot( deform_by=my_disp_field,
                         scale_factor=my_scale_factor)
 
 Plot the mesh and add the stress data on top of that
 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
 
-The data to be plotted in a |MeshedRegion| can be in a |Field| or in a |FieldsContainer|
+The data to be plotted in a |MeshedRegion| can be in a |Field|.
 
-.. code-block:: python
+.. jupyter-execute::
 
     # Plot the MeshedRegion and the stress in a Field
-    my_meshed_region.plot( field_or_fields_container=stress_field
-                           deform_by=my_disp_field,
-                           scale_factor=my_scale_factor)
-
-.. rst-class:: sphx-glr-script-out
-
- .. jupyter-execute::
-    :hide-code:
-
     my_meshed_region.plot( field_or_fields_container=stress_field,
                            deform_by=my_disp_field,
                            scale_factor=my_scale_factor)
 
-The data to be plotted in a |MeshesContainer| must be in a |FieldsContainer|
-
-.. code-block:: python
-
-    # Plot the MeshesContainer and the stress in a FieldsContainer
-    my_meshes.plot( fields_container=fc_stress
-                    deform_by=my_disp_field,
-                    scale_factor=my_scale_factor)
-
-.. rst-class:: sphx-glr-script-out
-
- .. jupyter-execute::
-    :hide-code:
-
-    my_meshed_region.plot( field_or_fields_container=stress_field,
-                           deform_by=my_disp_field,
-                           scale_factor=my_scale_factor)
 
 .. rubric:: Footnotes