Fix doc getting started

docs/source/_static/custom.css

@@ -6,4 +6,13 @@
 
 .bd-content .sd-card .sd-card-body, .bd-content .sd-card .sd-card-footer {
     background-color: transparent;
-}
+}
+
+.sd-card-text {
+    font-family: var(--pst-font-family-base);
+    font-size: var(--pst-font-size-base);
+}
+
+.sd-sphinx-override .code {
+   background-color: var(--pst-color-surface);
+}

docs/source/_static/simple_example.rst

@@ -12,8 +12,6 @@ extract results:
 
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     DPF Model
@@ -54,6 +52,4 @@ extract results:
 
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  .. figure:: images/plotting/simple_example.png

docs/source/getting_started/index.rst

@@ -4,16 +4,134 @@
 Getting started
 ===============
 
-DPF-Core is a Python gRPC client communicating with the ``Ans.Dpf.Grpc`` 
-server. To use the native DPF server, you must have a local installation of
-Ansys 2021 R1 or later. For more information on getting a licensed copy of Ansys,
-visit the `Ansys website <https://www.ansys.com/>`_.
+The Data Processing Framework (DPF) provides numerical simulation users and engineers with a toolbox
+for accessing and transforming simulation data. DPF can access data from Ansys solver
+result (RST) files as well as from several neutral file formats, including CSV, HDF5, and VTK.
+This **workflow-based** framework allows you to perform complex preprocessing and
+postprocessing operations on large amounts of simulation data.
+
+PyDPF-Core is a Python client API communicating with a **DPF Server**, either
+through the network using gRPC or directly in the same process.
+
+
+Installing PyDPF-Core
+---------------------
+
+In a Python environment, run the following command to install PyDPF-Core:
+
+.. code::
+
+   pip install ansys-dpf-core
+
+For more installation options, see :ref:`Installation section <installation>`.
+
+
+Installing DPF Server
+---------------------
+
+#. DPF Server is packaged within the **Ansys Unified Installer** starting with Ansys 2021 R1.
+   To use it, install Ansys following the installer instructions. If you experience problems,
+   see  :ref:`Environment variable section <ref_compatibility>`. For information on getting
+   a licensed copy of Ansys, visit the `Ansys website <https://www.ansys.com/>`_.
+
+#. DPF Server is available as a **standalone** package (independent of the Ansys installer) on the `Ansys Customer Portal <https://support.ansys.com/Home/HomePage>`_.
+   As explained in :ref:`Ansys licensing section <ref_getting_started_with_dpf_server>`,
+   DPF Server is protected by an Ansys license mechanism. Once you have access to an
+   Ansys license, install DPF Server:
+
+.. card::
+
+    * Download the ansys_dpf_server_win_v2023.2.pre0.zip or ansys_dpf_server_lin_v2023.2.pre0.zip
+      file as appropriate.
+    * Unzip the package and go to the root folder of the unzipped package
+      (ansys_dpf_server_win_v2023.2.pre0 or ansys_dpf_server_lin_v2023.2.pre0).
+    * In a Python environment, run the following command:
+
+    .. code::
+
+        pip install -e .
+
+    * DPF Server is protected using the license terms specified in the
+    ``DPFUserLicensingAgreement.txt`` file, which is available on the
+    Ansys Customer Portal. To accept these terms, you must set the
+    following environment flag:
+
+    .. code::
+
+        ANSYS_DPF_ACCEPT_LA=Y
+
+
+
+For installation methods that do not use pip, such as using **Docker containers**, see
+:ref:`ref_getting_started_with_dpf_server`.
+
+
+Use PyDPF-Core
+--------------
+
+In the same Python environment, run the following command to use PyDPF-Core:
+
+.. code:: python
+
+    >>> from ansys.dpf import core as dpf
+    >>> from ansys.dpf.core import examples
+    >>> model = dpf.Model(examples.download_crankshaft())
+    >>> print(model)
+
+
+.. rst-class:: sphx-glr-script-out
+
+ .. code-block:: none
+
+    DPF Model
+    ------------------------------
+    Static analysis
+    Unit system: MKS: m, kg, N, s, V, A, degC
+    Physics Type: Mechanical
+    Available results:
+         -  displacement: Nodal Displacement
+         -  velocity: Nodal Velocity
+         -  acceleration: Nodal Acceleration
+         -  reaction_force: Nodal Force
+         -  stress: ElementalNodal Stress
+         -  elemental_volume: Elemental Volume
+         -  stiffness_matrix_energy: Elemental Energy-stiffness matrix
+         -  artificial_hourglass_energy: Elemental Hourglass Energy
+         -  thermal_dissipation_energy: Elemental thermal dissipation energy
+         -  kinetic_energy: Elemental Kinetic Energy
+         -  co_energy: Elemental co-energy
+         -  incremental_energy: Elemental incremental energy
+         -  elastic_strain: ElementalNodal Strain
+         -  structural_temperature: ElementalNodal Temperature
+    ------------------------------
+    DPF  Meshed Region:
+      69762 nodes
+      39315 elements
+      Unit: m
+      With solid (3D) elements
+    ------------------------------
+    DPF  Time/Freq Support:
+      Number of sets: 3
+    Cumulative     Time (s)       LoadStep       Substep
+    1              1.000000       1              1
+    2              2.000000       1              2
+    3              3.000000       1              3
+
+
+
+.. code:: python
+
+    >>> over_time_disp = model.results.displacement().eval()
+    >>> over_time_disp[0].plot()
+
+
+.. figure:: ../images/plotting/crankshaft_disp.png
+
 
 .. toctree::
-   :maxdepth: 3
+   :hidden:
 
    compatibility
    install
    dependencies
-   docker
 

docs/source/user_guide/fields_container.rst

@@ -30,8 +30,6 @@ This example uses the ``elastic_strain`` operator to access a fields container:
 
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     DPF elastic_strain(s)Fields Container
@@ -76,8 +74,6 @@ Access the field:
 
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     20
@@ -105,7 +101,6 @@ To access fields for more complex requests, you can use the
 
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@@ -130,8 +125,6 @@ Here is a more real-word example:
 
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      DPF elastic_strain_1.s_elshape:0 Field
@@ -159,8 +152,6 @@ time complex IDs are available in the fields container:
 
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     DPF  Time/Freq Support: 
@@ -216,8 +207,6 @@ You can get an overview of a field's metadata by printing the field:
 
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    DPF elastic_strain_0.01s Field
@@ -246,8 +235,6 @@ To access the scoping of the field, use the ``scoping`` attribute:
 
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     DPF scoping: 
@@ -301,8 +288,6 @@ units of the data:
 
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      'Pa'
@@ -451,8 +436,6 @@ average of a field:
 
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     [[ 4.65393066e-04 -2.47955322e-05  0.00000000e+00  7.68026390e+02

docs/source/user_guide/model.rst

@@ -31,8 +31,6 @@ To understand what is available in the result file, you can print the model
 
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     DPF Model
@@ -88,8 +86,6 @@ This example shows you get the analysis type:
 
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     'static'
@@ -105,8 +101,6 @@ This example shows how you get mesh information:
 
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     3751
@@ -128,8 +122,6 @@ This example shows how you get time sets:
 
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     [1.]
@@ -151,8 +143,6 @@ This example shows how you view available results:
 
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     Static analysis

docs/source/user_guide/operators.rst

@@ -77,8 +77,6 @@ operator by printing it:
 
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     DPF U Operator: 
@@ -138,8 +136,6 @@ Because several other examples use the ``Model`` class, this example uses the
 
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   DPF  DataSources: 
@@ -179,8 +175,6 @@ class from the operator:
 
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     DPF displacement(s)Fields Container
@@ -202,8 +196,6 @@ like this one:
 
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     DPFServerException: U<-Data sources are not defined.
@@ -240,8 +232,6 @@ displacement data on the client side to compute the maximum:
 
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     array([8.20217171e-07, 6.26510654e-06, 0.00000000e+00])
@@ -262,8 +252,6 @@ On an industrial model, however, you should use code like this:
 
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     array([8.20217171e-07, 6.26510654e-06, 0.00000000e+00])
@@ -374,8 +362,6 @@ operators:
 
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      array([[ 2.,  4.,  6.],
@@ -394,8 +380,6 @@ operators:
 
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      array([[4., 5., 6.],
@@ -448,8 +432,6 @@ Python client is not on the same machine as the server:
 
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      C:\Users\cbellot\AppData\Local\Temp\dataProcessingTemp17168