FEAT: New class ReportPlotter to handle all matplotlib plot (#5297)

Co-authored-by: maxcapodi78 <Shark78>
Co-authored-by: Samuelopez-ansys <samuel.lopez@ansys.com>
Co-authored-by: Sébastien Morais <146729917+SMoraisAnsys@users.noreply.github.com>
Co-authored-by: Samuel Lopez <85613111+Samuelopez-ansys@users.noreply.github.com>

_unittest/test_12_1_PostProcessing.py

@@ -308,6 +308,11 @@ def test_09_manipulate_report(self):
         assert self.aedtapp.post.create_report_from_configuration(
             os.path.join(self.local_scratch.path, f"{plot.plot_name}.json"), solution_name=self.aedtapp.nominal_sweep
         )
+        assert self.aedtapp.post.create_report_from_configuration(
+            os.path.join(self.local_scratch.path, f"{plot.plot_name}.json"),
+            solution_name=self.aedtapp.nominal_sweep,
+            matplotlib=True,
+        )
         assert self.aedtapp.post.create_report(
             expressions="MaxMagDeltaS",
             variations={"Pass": ["All"]},
@@ -760,6 +765,7 @@ def test_67_sweep_from_json(self):
         local_path = os.path.dirname(os.path.realpath(__file__))
         dict_vals = read_json(os.path.join(local_path, "example_models", "report_json", "Modal_Report_Simple.json"))
         assert self.aedtapp.post.create_report_from_configuration(report_settings=dict_vals)
+        assert self.aedtapp.post.create_report_from_configuration(report_settings=dict_vals, matplotlib=True)
 
     @pytest.mark.skipif(
         config["desktopVersion"] < "2022.2", reason="Not working in non graphical in version lower than 2022.2"
@@ -769,6 +775,9 @@ def test_70_sweep_from_json(self):
         assert self.aedtapp.post.create_report_from_configuration(
             os.path.join(local_path, "example_models", "report_json", "Modal_Report.json")
         )
+        assert self.aedtapp.post.create_report_from_configuration(
+            os.path.join(local_path, "example_models", "report_json", "Modal_Report.json"), matplotlib=True
+        )
 
     def test_74_dynamic_update(self):
         val = self.aedtapp.post.update_report_dynamically

_unittest/test_46_FarField.py

@@ -26,9 +26,9 @@
 import shutil
 
 from ansys.aedt.core.visualization.advanced.farfield_visualization import FfdSolutionData
+from ansys.aedt.core.visualization.plot.matplotlib import ReportPlotter
 
 # from _unittest.conftest import config
-from matplotlib.figure import Figure
 import pytest
 from pyvista.plotting.plotter import Plotter
 
@@ -150,9 +150,9 @@ def test_04_far_field_data(self, local_scratch):
         ffdata.plot_cut(output_file=img3, show=False)
         assert os.path.exists(img3)
         curve_2d = ffdata.plot_cut(show=False)
-        assert isinstance(curve_2d, Figure)
+        assert isinstance(curve_2d, ReportPlotter)
         data = ffdata.plot_3d_chart(show=False)
-        assert isinstance(data, Figure)
+        assert isinstance(data, ReportPlotter)
 
         img4 = os.path.join(self.local_scratch.path, "ff_3d1.jpg")
         ffdata.plot_3d(
@@ -161,6 +161,59 @@ def test_04_far_field_data(self, local_scratch):
         assert os.path.exists(img4)
         data_pyvista = ffdata.plot_3d(quantity="RealizedGain", show=False, background=[255, 0, 0], show_geometry=False)
         assert isinstance(data_pyvista, Plotter)
+        matplot_lib = ffdata.plot_cut(
+            quantity="RealizedGain",
+            primary_sweep="theta",
+            secondary_sweep_value=[-180, -75, 75],
+            title=f"Azimuth at {ffdata.frequency}Hz",
+            quantity_format="dB10",
+        )
+        matplot_lib.add_note(
+            "Hello Pyaedt2",
+            [10, -10],
+            color=(1, 1, 0),
+            bold=True,
+            italic=True,
+            back_color=(0, 0, 1),
+            background_visibility=True,
+        )
+
+        matplot_lib.traces_by_index[0].trace_style = "--"
+        matplot_lib.x_scale = "log"
+        _ = matplot_lib.plot_2d()
+        matplot_lib.add_note(
+            "Hello Pyaedt",
+            [0, -10],
+            color=(1, 1, 0),
+            bold=False,
+            italic=False,
+            background_visibility=False,
+        )
+        matplot_lib.x_scale = "linear"
+        matplot_lib.traces_by_index[0].trace_color = (1, 0, 0)
+        matplot_lib.grid_enable_minor_x = True
+        _ = matplot_lib.plot_2d()
+
+        matplot_lib.traces["Phi=-180"].symbol_style = "v"
+        _ = matplot_lib.plot_2d()
+
+        matplot_lib.apply_style("dark_background")
+        matplot_lib.add_limit_line(
+            [[0, 20, 120], [15, 5, 5]],
+            properties={
+                "trace_color": (1, 0, 0),
+            },
+            name="LimitLine1",
+        )
+        _ = matplot_lib.plot_2d()
+
+        matplot_lib.traces_by_index[0].trace_color = (1, 0, 0)
+        matplot_lib.grid_enable_minor_x = True
+
+        matplot_lib.grid_enable_minor_x = False
+        matplot_lib.grid_enable_minor_y = False
+
+        _ = matplot_lib.plot_2d()
 
     def test_05_antenna_plot(self, array_test):
         ffdata = array_test.get_antenna_data(sphere="3D")
@@ -171,7 +224,7 @@ def test_05_antenna_plot(self, array_test):
         img1 = os.path.join(self.local_scratch.path, "contour.jpg")
         assert ffdata.farfield_data.plot_contour(
             quantity="RealizedGain",
-            title="Contour at {}Hz".format(ffdata.farfield_data.frequency),
+            title=f"Contour at {ffdata.farfield_data.frequency}Hz",
             output_file=img1,
             show=False,
         )
@@ -186,7 +239,7 @@ def test_05_antenna_plot(self, array_test):
             quantity="RealizedGain",
             primary_sweep="theta",
             secondary_sweep_value=[-180, -75, 75],
-            title="Azimuth at {}Hz".format(ffdata.farfield_data.frequency),
+            title=f"Azimuth at {ffdata.farfield_data.frequency}Hz",
             output_file=img2,
             show=False,
         )
@@ -197,7 +250,7 @@ def test_05_antenna_plot(self, array_test):
             quantity="RealizedGain",
             primary_sweep="phi",
             secondary_sweep_value=30,
-            title="Azimuth at {}Hz".format(ffdata.farfield_data.frequency),
+            title=f"Azimuth at {ffdata.farfield_data.frequency}Hz",
             output_file=img3,
             show=False,
         )
@@ -208,7 +261,7 @@ def test_05_antenna_plot(self, array_test):
             quantity="RealizedGain",
             primary_sweep="phi",
             secondary_sweep_value=30,
-            title="Azimuth at {}Hz".format(ffdata.farfield_data.frequency),
+            title=f"Azimuth at {ffdata.farfield_data.frequency}Hz",
             output_file=img3_polar,
             show=False,
             is_polar=True,

doc/source/API/visualization/plot.rst

@@ -45,10 +45,7 @@ PyAEDT benefits of `matplotlib <https://matplotlib.org/>`_ package and allows to
    :toctree: _autosummary
    :nosignatures:
 
-   plot_polar_chart
-   plot_3d_chart
-   plot_2d_chart
-   plot_contour
+   ReportPlotter
    is_notebook
 
 

src/ansys/aedt/core/generic/settings.py

@@ -218,6 +218,7 @@ def __init__(self):
             else:
                 pyaedt_settings_path = os.path.join(os.environ["APPDATA"], "pyaedt_settings.yaml")
         self.load_yaml_configuration(pyaedt_settings_path)
+        self.__block_figure_plot = False
 
     # ########################## Logging properties ##########################
 
@@ -230,6 +231,16 @@ def logger(self):
     def logger(self, val):
         self.__logger = val
 
+    @property
+    def block_figure_plot(self):
+        """Block matplotlib figure plot during python script run until the user close it manually.
+        Default is ``False``."""
+        return self.__block_figure_plot
+
+    @block_figure_plot.setter
+    def block_figure_plot(self, val):
+        self.__block_figure_plot = val
+
     @property
     def enable_desktop_logs(self):
         """Enable or disable the logging to the AEDT message window."""

src/ansys/aedt/core/modeler/pcb/object_3d_layout.py

@@ -851,7 +851,7 @@ def plot(
         show_legend=True,
         save_plot=None,
         outline=None,
-        size=(2000, 1000),
+        size=(1920, 1440),
         plot_components_on_top=False,
         plot_components_on_bottom=False,
         show=True,

src/ansys/aedt/core/visualization/advanced/farfield_visualization.py

@@ -36,11 +36,8 @@
 from ansys.aedt.core.generic.general_methods import open_file
 from ansys.aedt.core.generic.general_methods import pyaedt_function_handler
 from ansys.aedt.core.visualization.advanced.touchstone_parser import read_touchstone
+from ansys.aedt.core.visualization.plot.matplotlib import ReportPlotter
 from ansys.aedt.core.visualization.plot.matplotlib import is_notebook
-from ansys.aedt.core.visualization.plot.matplotlib import plot_2d_chart
-from ansys.aedt.core.visualization.plot.matplotlib import plot_3d_chart
-from ansys.aedt.core.visualization.plot.matplotlib import plot_contour
-from ansys.aedt.core.visualization.plot.matplotlib import plot_polar_chart
 from ansys.aedt.core.visualization.plot.pyvista import ModelPlotter
 from ansys.aedt.core.visualization.plot.pyvista import get_structured_mesh
 
@@ -829,7 +826,7 @@ def plot_contour(
 
         Returns
         -------
-        :class:`matplotlib.pyplot.Figure`
+        :class:`ansys.aedt.core.visualization.plot.matplotlib.ReportPlotter`
             Matplotlib figure object.
 
         Examples
@@ -860,19 +857,25 @@ def plot_contour(
         ph, th = np.meshgrid(data["Phi"], data["Theta"][select])
         # Convert to radians for polar plot.
         ph = np.radians(ph) if polar else ph
-
-        return plot_contour(
-            plot_data=[data_to_plot, th, ph],
-            xlabel=r"$\phi$ (Degrees)",
-            ylabel=r"$\theta$ (Degrees)",
-            title=title,
-            levels=levels,
+        new = ReportPlotter()
+        new.show_legend = False
+        new.title = title
+        props = {
+            "x_label": r"$\phi$ (Degrees)",
+            "y_label": r"$\theta$ (Degrees)",
+        }
+
+        new.add_trace([data_to_plot, th, ph], 2, props)
+        _ = new.plot_contour(
+            trace=0,
             polar=polar,
-            snapshot_path=output_file,
+            levels=levels,
             max_theta=max_theta,
             color_bar=quantity_format,
+            snapshot_path=output_file,
             show=show,
         )
+        return new
 
     @pyaedt_function_handler()
     def plot_cut(
@@ -924,7 +927,7 @@ def plot_cut(
 
         Returns
         -------
-        :class:`matplotlib.pyplot.Figure`
+        :class:`ansys.aedt.core.visualization.plot.matplotlib.ReportPlotter`
             Matplotlib figure object.
             If ``show=True``, a Matplotlib figure instance of the plot is returned.
             If ``show=False``, the plotted curve is returned.
@@ -963,7 +966,7 @@ def plot_cut(
                 y = conversion_function(y, quantity_format)
                 if not isinstance(y, np.ndarray):  # pragma: no cover
                     raise Exception("Format of quantity is wrong.")
-                curves.append([x, y, "{}={}".format(y_key, el)])
+                curves.append([x, y, f"{y_key}={el}"])
         elif isinstance(secondary_sweep_value, list):
             list_inserted = []
             for el in secondary_sweep_value:
@@ -973,36 +976,28 @@ def plot_cut(
                     y = conversion_function(y, quantity_format)
                     if not isinstance(y, np.ndarray):  # pragma: no cover
                         raise Exception("Format of quantity is wrong.")
-                    curves.append([x, y, "{}={}".format(y_key, el)])
+                    curves.append([x, y, f"{y_key}={el}"])
                     list_inserted.append(theta_idx)
         else:
             theta_idx = self.__find_nearest(data[y_key], secondary_sweep_value)
             y = temp[theta_idx]
             y = conversion_function(y, quantity_format)
             if not isinstance(y, np.ndarray):  # pragma: no cover
                 raise Exception("Wrong format quantity.")
-            curves.append([x, y, "{}={}".format(y_key, data[y_key][theta_idx])])
-
+            curves.append([x, y, f"{y_key}={data[y_key][theta_idx]}"])
+
+        new = ReportPlotter()
+        new.show_legend = show_legend
+        new.title = title
+        props = {"x_label": x_key, "y_label": quantity}
+        for pdata in curves:
+            name = pdata[2] if len(pdata) > 2 else "Trace"
+            new.add_trace(pdata[:2], 0, props, name=name)
         if is_polar:
-            return plot_polar_chart(
-                curves,
-                xlabel=x_key,
-                ylabel=quantity,
-                title=title,
-                snapshot_path=output_file,
-                show_legend=show_legend,
-                show=show,
-            )
+            _ = new.plot_polar(traces=None, snapshot_path=output_file, show=show)
         else:
-            return plot_2d_chart(
-                curves,
-                xlabel=x_key,
-                ylabel=quantity,
-                title=title,
-                snapshot_path=output_file,
-                show_legend=show_legend,
-                show=show,
-            )
+            _ = new.plot_2d(None, output_file, show)
+        return new
 
     @pyaedt_function_handler()
     def plot_3d_chart(
@@ -1041,10 +1036,9 @@ def plot_3d_chart(
 
         Returns
         -------
-        :class:`matplotlib.pyplot.Figure`
+        :class:`ansys.aedt.core.visualization.plot.matplotlib.ReportPlotter`
             Matplotlib figure object.
-            If ``show=True``, a Matplotlib figure instance of the plot is returned.
-            If ``show=False``, the plotted curve is returned.
+
 
         Examples
         --------
@@ -1078,7 +1072,13 @@ def plot_3d_chart(
         x = r * np.sin(theta_grid) * np.cos(phi_grid)
         y = r * np.sin(theta_grid) * np.sin(phi_grid)
         z = r * np.cos(theta_grid)
-        return plot_3d_chart([x, y, z], xlabel="Theta", ylabel="Phi", title=title, snapshot_path=output_file, show=show)
+        new = ReportPlotter()
+        new.show_legend = False
+        new.title = title
+        props = {"x_label": "Theta", "y_label": "Phi", "z_label": quantity}
+        new.add_trace([x, y, z], 2, props, quantity)
+        _ = new.plot_3d(trace=0, snapshot_path=output_file, show=show)
+        return new
 
     @pyaedt_function_handler()
     def plot_3d(