DOCS: Revert changes to use webp (#4716)

doc/source/API/Application.rst

@@ -3,7 +3,7 @@ Application and solvers
 The PyAEDT API includes classes for different applications available in Ansys Electronics Desktop (AEDT).
 You must initialize AEDT to get access to all PyAEDT modules and methods.
 
-.. image:: ../Resources/aedt_2.webp
+.. image:: ../Resources/aedt_2.png
   :width: 800
   :alt: Ansys Electronics Desktop (AEDT) is a platform that enables true electronics system design.
 

doc/source/API/index.rst

@@ -15,7 +15,7 @@ and Mechanical solvers for comprehensive multiphysics analysis.
 Tight integration among these solutions provides unprecedented ease of use for setup and
 faster resolution of complex simulations for design and optimization.
 
-.. image:: ../Resources/aedt_2.webp
+.. image:: ../Resources/aedt_2.png
   :width: 800
   :alt: AEDT Applications
   :target: https://www.ansys.com/products/electronics

doc/source/Getting_started/About.rst

@@ -26,7 +26,7 @@ and mechanical solvers for comprehensive multiphysics analysis.
 Tight integration among these solutions provides unprecedented ease of use for setup and
 faster resolution of complex simulations for design and optimization.
 
-.. image:: ../Resources/aedt_collage.webp
+.. image:: ../Resources/aedt_collage.jpg
   :width: 800
   :alt: AEDT Applications
   :target: https://www.ansys.com/products/electronics

doc/source/Getting_started/Installation.rst

@@ -33,13 +33,13 @@ In order to do that you can:
     Please note that AEDT 2023 R1 and lower requires Python 3.7 wheelhouse while AEDT 2023 R2
     and higher requires the Python 3.10 wheelhouse.
 
-.. image:: ../Resources/wheelhouse_installation.webp
+.. image:: ../Resources/wheelhouse_installation.png
   :width: 800
   :alt: PyAEDT run script
 
 Starting from 2023R2, buttons are available in the Automation Tab as in the example below.
 
-.. image:: ../Resources/toolkits_ribbon.webp
+.. image:: ../Resources/toolkits_ribbon.png
   :width: 800
   :alt: PyAEDT toolkit buttons available in AEDT
 
@@ -55,13 +55,13 @@ There are three options:
 
 - Open source PyAEDT toolkits. Open source PyAEDT toolkits following the `common library <https://aedt.common.toolkit.docs.pyansys.com/>`_ standard.
 
-.. image:: ../Resources/toolkit_manager_1.webp
+.. image:: ../Resources/toolkit_manager_1.png
   :width: 800
   :alt: PyAEDT toolkit manager 1
 
 The user can select the AEDT application to install the specific workflow.
 
-.. image:: ../Resources/toolkit_manager_2.webp
+.. image:: ../Resources/toolkit_manager_2.png
   :width: 400
   :alt: PyAEDT toolkit manager 2
 

doc/source/Getting_started/index.rst

@@ -72,7 +72,7 @@ and Mechanical solvers for comprehensive multiphysics analysis.
 Tight integration among these solutions provides unprecedented ease of use for setup and
 faster resolution of complex simulations for design and optimization.
 
-.. image:: ../Resources/aedt_3.webp
+.. image:: ../Resources/aedt_3.png
   :width: 800
   :alt: AEDT Applications
   :target: https://www.ansys.com/products/electronics

doc/source/User_guide/intro.rst

@@ -17,7 +17,7 @@ You can initiate AEDT in non-graphical mode from Python using this code:
 
 The preceding code launches AEDT and initializes a new Circuit design.
 
-.. image:: ../Resources/aedt_first_page.webp
+.. image:: ../Resources/aedt_first_page.png
   :width: 800
   :alt: AEDT launched
 

doc/source/User_guide/mesh.rst

@@ -16,7 +16,7 @@ All mesh operations are conveniently listed within the mesh object:
     my_mesh_op.update()
 
 
-.. image:: ../Resources/Mesh_Operations.webp
+.. image:: ../Resources/Mesh_Operations.png
   :width: 800
   :alt: Mesh object List
 

doc/source/User_guide/modeler.rst

@@ -18,7 +18,7 @@ The following code creates a box and changes the color to red:
 
 
 
-.. image:: ../Resources/aedt_box.webp
+.. image:: ../Resources/aedt_box.png
   :width: 800
   :alt: Modeler Object
 

doc/source/User_guide/postprocessing.rst

@@ -15,7 +15,7 @@ To use PyAEDT to create a report in AEDT, you can follow this general structure:
     hfss.post.create_report(["db(S11)", "db(S12)"])
 
 
-.. image:: ../Resources/sparams.webp
+.. image:: ../Resources/sparams.jpg
   :width: 800
   :alt: AEDT report
 
@@ -34,7 +34,7 @@ You can also generate reports in Matplotlib:
     plt = solution.plot(solution.expressions)  # Matplotlib axes object.
 
 
-.. image:: ../Resources/sparams_w_matplotlib.webp
+.. image:: ../Resources/sparams_w_matplotlib.jpg
   :width: 800
   :alt: S-Parameters report created with Matplotlib
 
@@ -97,7 +97,7 @@ PyAEDT leverages PyVista to export and plot fields outside AEDT, generating imag
         )
 
 
-.. image:: ../Resources/pyvista_plot.webp
+.. image:: ../Resources/pyvista_plot.jpg
   :width: 800
   :alt: Postprocessing features
 

doc/source/User_guide/setup.rst

@@ -19,7 +19,7 @@ essential components of the simulation process:
     new_setup = m3d.create_setup("New_Setup")
 
 
-.. image:: ../Resources/Setups.webp
+.. image:: ../Resources/Setups.png
   :width: 800
   :alt: Setup Editing and Creation
 

doc/source/User_guide/variables.rst

@@ -13,7 +13,7 @@ for the variable name, a project-wide variable is created:
          hfss["$dim"] = "1mm"  # project variable
 
 
-.. image:: ../Resources/aedt_variables.webp
+.. image:: ../Resources/aedt_variables.png
   :width: 800
   :alt: Variable Management
 
@@ -36,7 +36,7 @@ access the ``variable_manager`` object for a more comprehensive set of functions
         '34 * $PrjVar1/$PrjVar2'
 
 
-.. image:: ../Resources/variables_advanced.webp
+.. image:: ../Resources/variables_advanced.png
   :width: 600
   :alt: Variable Management
 
@@ -54,7 +54,7 @@ optimetrics setups by allowing you to read existing configurations, make edits,
     m3d.parametrics.add("Rload", 0.1, 1, 0.1)
 
 
-.. image:: ../Resources/Optimetrics_Parametric.webp
+.. image:: ../Resources/Optimetrics_Parametric.png
   :width: 800
   :alt: Optimetrics creation
 

doc/source/conf.py

@@ -28,7 +28,7 @@
 # Additionally, when documenting images in formats other than the supported ones, 
 # make sure to specify their types.
 from sphinx.builders.latex import LaTeXBuilder
-LaTeXBuilder.supported_image_types = ["image/png", "image/pdf", "image/svg+xml", "image/webp" ]
+LaTeXBuilder.supported_image_types = ["image/png", "image/pdf", "image/svg+xml"]
 
 from sphinx.writers.latex import CR
 from sphinx.writers.latex import LaTeXTranslator
@@ -139,20 +139,20 @@ def setup(app):
 # extensions coming with Sphinx_PyAEDT (named 'sphinx.ext.*') or your custom
 # ones.
 extensions = [
-    "sphinx.ext.intersphinx",
+    "ansys_sphinx_theme.extension.linkcode",
+    "numpydoc",
+    "recommonmark",
     "sphinx.ext.autodoc",
-    "sphinx.ext.todo",
     "sphinx.ext.autosummary",
-    "sphinx.ext.intersphinx",
     "sphinx.ext.coverage",
-    "sphinx_copybutton",
-    "sphinx_design",
     "sphinx.ext.graphviz",
-    "sphinx.ext.mathjax",
+    "sphinx.ext.imgconverter",
     "sphinx.ext.inheritance_diagram",
-    "numpydoc",
-    "ansys_sphinx_theme.extension.linkcode",
-    "recommonmark",
+    "sphinx.ext.intersphinx",
+    "sphinx.ext.mathjax",
+    "sphinx.ext.todo",
+    "sphinx_copybutton",
+    "sphinx_design",
 ]
 
 # Intersphinx mapping

pyaedt/generic/plot.py

@@ -99,14 +99,13 @@ def is_notebook():
     bool
     """
     try:
-        from IPython import get_ipython
-
         shell = get_ipython().__class__.__name__
-        # Check if shell is Jupyter notebook or QTconsole
-        return shell == "ZMQInteractiveShell"
-    # Probably standard Python interpreter
+        if shell == "ZMQInteractiveShell":
+            return True  # Jupyter notebook or qtconsole
+        else:
+            return False
     except NameError:
-        return False
+        return False  # Probably standard Python interpreter
 
 
 def is_float(istring):
@@ -386,7 +385,7 @@ def plot_polar_chart(
 
 @pyaedt_function_handler()
 @update_plot_settings
-def plot_3d_chart(plot_data, size=(2000, 1000), xlabel="", ylabel="", title="", snapshot_path=None, show=True):
+def plot_3d_chart(plot_data, size=(2000, 1000), xlabel="", ylabel="", title="", snapshot_path=None):
     """Create a Matplotlib 3D plot based on a list of data.
 
     Parameters
@@ -404,9 +403,6 @@ def plot_3d_chart(plot_data, size=(2000, 1000), xlabel="", ylabel="", title="",
         Plot Title label.
     snapshot_path : str
         Full path to image file if a snapshot is needed.
-    show : bool, optional
-        Whether to render the figure. The default is ``True``. If ``False``, the
-        figure is not drawn.
 
     Returns
     -------
@@ -436,16 +432,14 @@ def plot_3d_chart(plot_data, size=(2000, 1000), xlabel="", ylabel="", title="",
     fig.set_size_inches(size[0] / dpi, size[1] / dpi)
     if snapshot_path:
         fig.savefig(snapshot_path)
-    if show:
+    else:
         fig.show()
     return fig
 
 
 @pyaedt_function_handler()
 @update_plot_settings
-def plot_2d_chart(
-    plot_data, size=(2000, 1000), show_legend=True, xlabel="", ylabel="", title="", snapshot_path=None, show=True
-):
+def plot_2d_chart(plot_data, size=(2000, 1000), show_legend=True, xlabel="", ylabel="", title="", snapshot_path=None):
     """Create a Matplotlib plot based on a list of data.
     Parameters
     ----------
@@ -465,9 +459,6 @@ def plot_2d_chart(
     snapshot_path : str, optional
         Full path to image file if a snapshot is needed.
         The default value is ``None``.
-    show : bool, optional
-        Whether to render the figure. The default is ``True``. If ``False``, the
-        figure is not drawn.
 
     Returns
     -------
@@ -498,7 +489,7 @@ def plot_2d_chart(
 
     if snapshot_path:
         fig.savefig(snapshot_path)
-    if show:
+    elif not is_notebook():
         fig.show()
     return fig
 
@@ -549,10 +540,9 @@ def plot_matplotlib(
         Default is `False`.
     annotations : list, optional
         List of annotations to add to the plot. The format is [x, y, string, dictionary of font options].
-        The default is ``None``.
+        Default is `None`.
     show : bool, optional
-        Whether to render the figure. The default is ``True``. If ``False``, the
-        figure is not drawn.
+        Whether to show the plot or return the matplotlib object. Default is `True`.
 
 
     Returns
@@ -646,10 +636,10 @@ def plot_contour(
     levels : int, optional
         Color map levels. The default is ``64``.
     snapshot_path : str, optional
-        Full path to save the image to. The default is ``None``.
+        Full path to save the image save. The default is ``None``.
     show : bool, optional
-        Whether to render the figure. The default is ``True``. If ``False``, the
-        figure is not drawn.
+        Whether to render the figure. The default is ``True``. If
+        ``False``, the image is not drawn.
 
     Returns
     -------

pyaedt/modules/AdvancedPostProcessing.py

@@ -340,20 +340,17 @@ def plot_field_from_fieldplot(
         project_path : str, optional
             Path for saving the image file. The default is ``""``.
         mesh_plot : bool, optional
-            Whether to create and plot the mesh over the fields. The
-            default is ``False``.
+            Whether to create and plot the mesh over the fields. The default is ``False``.
         image_format : str, optional
-            Format of the image file. Options are ``"jpg"``,
-            ``"png"``, ``"svg"``, and ``"webp"``. The default is
-            ``"jpg"``.
+            Format of the image file. Options are ``"jpg"``, ``"png"``, ``"svg"``, and ``"webp"``.
+            The default is ``"jpg"``.
         view : str, optional
            View to export. Options are ``"isometric"``, ``"xy"``, ``"xz"``, ``"yz"``.
         plot_label : str, optional
             Type of the plot. The default is ``"Temperature"``.
         plot_folder : str, optional
             Plot folder to update before exporting the field.
-            The default is ``None``, in which case all plot
-            folders are updated.
+            The default is ``None``, in which case all plot folders are updated.
         show : bool, optional
             Export Image without plotting on UI.
         scale_min : float, optional
@@ -497,9 +494,8 @@ def plot_field(
         export_path : str, optional
             Image export path. Default is ``None`` to not export the image.
         image_format : str, optional
-            Format of the image file. Options are ``"jpg"``,
-            ``"png"``, ``"svg"``, and ``"webp"``. The default is
-            ``"jpg"``.
+            Format of the image file. Options are ``"jpg"``, ``"png"``, ``"svg"``, and ``"webp"``.
+            The default is ``"jpg"``.
         keep_plot_after_generation : bool, optional
             Either to keep the Field Plot in AEDT after the generation is completed. Default is ``False``.
         dark_mode : bool, optional
@@ -811,13 +807,7 @@ def animate_fields_from_aedtplt(
 
     @pyaedt_function_handler()
     def create_3d_plot(
-        self,
-        solution_data,
-        nominal_sweep=None,
-        nominal_value=None,
-        primary_sweep="Theta",
-        secondary_sweep="Phi",
-        show=True,
+        self, solution_data, nominal_sweep=None, nominal_value=None, primary_sweep="Theta", secondary_sweep="Phi"
     ):
         """Create a 3D plot using Matplotlib.
 
@@ -833,20 +823,17 @@ def create_3d_plot(
             Primary sweep. The default is ``"Theta"``.
         secondary_sweep : str, optional
             Secondary sweep. The default is ``"Phi"``.
-        show : bool, optional
-            Whether to render the figure. The default is ``True``. If ``False``, the
-            figure is not drawn.
 
         Returns
         -------
-        :class:`matplotlib.plt`
-            Matplotlib fig object.
+         bool
+             ``True`` when successful, ``False`` when failed.
         """
         if nominal_value:
             solution_data.intrinsics[nominal_sweep] = nominal_value
         if nominal_value:
             solution_data.primary_sweep = primary_sweep
-        return solution_data.plot_3d(x_axis=primary_sweep, y_axis=secondary_sweep, show=show)
+        return solution_data.plot_3d(x_axis=primary_sweep, y_axis=secondary_sweep)
 
     @pyaedt_function_handler(frames_list="frames", output_gif_path="gif_path")
     def plot_scene(