Merge pull request #15666 from rmcdermo/master

Python: add usetex to plot_to_fig call

Author: rmcdermo

Utilities/Python/fdsplotlib.py

@@ -708,44 +708,39 @@ def get_data(E, spec, start_idx):
     return y, col_names
 
 
-def configure_fds_fonts():
+def configure_fds_fonts(**kwargs):
     import matplotlib.pyplot as plt
     import platform
 
     system = platform.system()
+    use_tex = kwargs.get('usetex', False)
 
     if system == "Linux":
-        # Linux: use Nimbus Roman as primary serif, with Times ahead of Times New Roman in the fallback chain
         primary_serif = "Nimbus Roman"
         serif_list = [
-            "Nimbus Roman",   # primary on Linux
+            "Nimbus Roman",
             "Times",
             "Times New Roman",
             "serif",
         ]
     else:
-        # macOS ("Darwin") and Windows: prefer Times, then Times New Roman
         primary_serif = "Times"
         serif_list = [
-            "Times",          # first choice
+            "Times",
             "Times New Roman",
             "Nimbus Roman",
             "serif",
         ]
 
     plt.rcParams.update({
-        # Core-14 fonts for small PDFs (Times-Roman in output)
         "pdf.use14corefonts": True,
-        "text.usetex": False,
+        "text.usetex": use_tex,
 
-        # Make serif the default everywhere
         "font.family": "serif",
         "font.serif": serif_list,
-
-        # If something explicitly requests 'sans-serif', try to keep it Times-like too
         "font.sans-serif": serif_list,
 
-        # Math text: follow the same primary serif
+        # Mathtext still matters when text.usetex=False
         "mathtext.fontset": "custom",
         "mathtext.rm": primary_serif,
         "mathtext.it": f"{primary_serif}:italic",
@@ -758,6 +753,13 @@ def configure_fds_fonts():
         "pdf.compression": 9,
     })
 
+    # Only for usetex=True, insert packages that Times-ify math
+    if use_tex:
+        plt.rcParams["text.latex.preamble"] = r"""
+            \usepackage{newtxtext}
+            \usepackage{newtxmath}
+            """
+
 
 def plot_to_fig(x_data,y_data,**kwargs):
     """
@@ -774,8 +776,6 @@ def plot_to_fig(x_data,y_data,**kwargs):
 
     plot_style = get_plot_style("fds")
 
-    configure_fds_fonts()
-
     # plt.rcParams.update({
     #     "pdf.use14corefonts": True,
     #     "text.usetex": False,
@@ -828,17 +828,33 @@ def plot_to_fig(x_data,y_data,**kwargs):
     # if figure handle is passed, append to current figure, else generate a new figure
     if kwargs.get('figure_handle'):
         fig = kwargs.get('figure_handle')
+
         if fig.axes:
             ax = fig.axes[0]
         else:
-            # Ensure we have at least one axes
             ax = fig.add_subplot(111)
+
         plt.figure(fig.number)
         using_existing_figure = True
+
+        # ---- restore original usetex for this figure ----
+        use_tex = getattr(fig, "_fds_usetex", False)
+        plt.rcParams["text.usetex"] = use_tex
+
     else:
         fig = plt.figure(figsize=figure_size)
         using_existing_figure = False
-        # Convert to fractions of the figure size:
+
+        # Take usetex from kwargs, default to False
+        use_tex = kwargs.get('usetex', False)
+
+        # ---- apply font settings before any text is drawn ----
+        configure_fds_fonts(usetex=use_tex)
+
+        # ---- record the choice on the figure for later calls ----
+        fig._fds_usetex = use_tex
+
+        # Create axes
         ax_w = plot_size[0] / figure_size[0]
         ax_h = plot_size[1] / figure_size[1]
         left   = plot_origin[0] / figure_size[0]

Utilities/Python/scripts/compression_wave.py

@@ -123,12 +123,13 @@ def clog(real_expr):
                              x_min=0, x_max=12.5, y_min=0, y_max=8,
                              revision_label=version_string,
                              x_label='Time (s)',
-                             y_label='Density (kg/m$^3$)')
+                             y_label=r'Density (kg/m$^3$)',
+                             usetex=True)
 
-fdsplotlib.plot_to_fig(x_data=t_FL4_16, y_data=rho_fds_FL4_16, marker_style='c--', data_label='FDS $N=16$', figure_handle=fig)
-fdsplotlib.plot_to_fig(x_data=t_FL4_32, y_data=rho_fds_FL4_32, marker_style='g--', data_label='FDS $N=32$', figure_handle=fig)
-fdsplotlib.plot_to_fig(x_data=t_FL4_64, y_data=rho_fds_FL4_64, marker_style='b--', data_label='FDS $N=64$', figure_handle=fig)
-fdsplotlib.plot_to_fig(x_data=t_FL4_128,y_data=rho_fds_FL4_128,marker_style='r--', data_label='FDS $N=128$',figure_handle=fig)
+fdsplotlib.plot_to_fig(x_data=t_FL4_16, y_data=rho_fds_FL4_16, marker_style='c--', data_label=r'FDS $N=16$', figure_handle=fig)
+fdsplotlib.plot_to_fig(x_data=t_FL4_32, y_data=rho_fds_FL4_32, marker_style='g--', data_label=r'FDS $N=32$', figure_handle=fig)
+fdsplotlib.plot_to_fig(x_data=t_FL4_64, y_data=rho_fds_FL4_64, marker_style='b--', data_label=r'FDS $N=64$', figure_handle=fig)
+fdsplotlib.plot_to_fig(x_data=t_FL4_128,y_data=rho_fds_FL4_128,marker_style='r--', data_label=r'FDS $N=128$',figure_handle=fig)
 
 plt.savefig(os.path.join(pltdir, 'compression_wave_time_series.pdf'), format='pdf')
 plt.close()
@@ -140,14 +141,15 @@ def clog(real_expr):
 e_FL2 = np.array([error_FL2_16, error_FL2_32, error_FL2_64, error_FL2_128])
 e_FL4 = np.array([error_FL4_16, error_FL4_32, error_FL4_64, error_FL4_128])
 
-fig = fdsplotlib.plot_to_fig(x_data=h, y_data=0.1*h, marker_style='k--', data_label=r'$O(\delta x)$',
+fig = fdsplotlib.plot_to_fig(x_data=h, y_data=0.1*h, marker_style='k--', data_label=r'${\cal O}(\delta x)$',
                              x_min=1e-2, x_max=1, y_min=1e-4, y_max=1e-1,
                              plot_type='loglog',
                              revision_label=version_string,
                              x_label='Grid Spacing (m)',
-                             y_label='L$_2$ Error (kg/m$^3$)')
+                             y_label=r'L2 Error (kg/m$^3$)',
+                             usetex=True)
 
-fdsplotlib.plot_to_fig(x_data=h, y_data=0.1*h**2, marker_style='k-', data_label=r'$O(\delta x^2)$', figure_handle=fig)
+fdsplotlib.plot_to_fig(x_data=h, y_data=0.1*h**2, marker_style='k-', data_label=r'${\cal O}(\delta x^2)$', figure_handle=fig)
 fdsplotlib.plot_to_fig(x_data=h, y_data=e_FL0, marker_style='b*-', data_label='Central', figure_handle=fig)
 fdsplotlib.plot_to_fig(x_data=h, y_data=e_FL2, marker_style='ro-', data_label='Superbee', figure_handle=fig)
 fdsplotlib.plot_to_fig(x_data=h, y_data=e_FL4, marker_style='g^-', data_label='CHARM', figure_handle=fig)