Python: improve legend_location

Author: rmcdermo

Utilities/Python/FDS_verification_dataplot_inputs.csv

@@ -424,7 +424,9 @@ def read_csv_cached(path, **kwargs):
                 y_min=pp.Min_Ind if flip_axis else pp.Min_Dep,
                 y_max=pp.Max_Ind if flip_axis else pp.Max_Dep,
                 legend_location=matlab_legend_to_matplotlib(pp.Key_Position),
+                legend_expand=pp.Paper_Width_Factor,
                 plot_type=plot_type,
+                plot_title=pp.Plot_Title,
             )
 
         # --- Save measured (experimental) ---
@@ -530,15 +532,6 @@ def read_csv_cached(path, **kwargs):
                 figure_handle=f,                  # keep same figure
                 data_label=d2_key_labels[i],
                 line_style=d2_styles[i],
-                x_label=pp.Dep_Title if flip_axis else pp.Ind_Title,
-                y_label=pp.Ind_Title if flip_axis else pp.Dep_Title,
-                x_min=pp.Min_Dep if flip_axis else pp.Min_Ind,
-                x_max=pp.Max_Dep if flip_axis else pp.Max_Ind,
-                y_min=pp.Min_Ind if flip_axis else pp.Min_Dep,
-                y_max=pp.Max_Ind if flip_axis else pp.Max_Dep,
-                legend_location=matlab_legend_to_matplotlib(pp.Key_Position),
-                plot_type=plot_type,
-                plot_title=pp.Plot_Title,
             )
 
         # --- Interpolated, metric-aware model logic ---
@@ -800,7 +793,7 @@ def plot_to_fig(x_data,y_data,**kwargs):
         ax = fig.add_axes([left, bottom, ax_w, ax_h])
 
     # widen paper if legend is outside, keeping axes fixed in physical size
-    if kwargs.get('legend_location') == 'outside':
+    if (kwargs.get('legend_location') == 'outside') and (not using_existing_figure):
         legend_expand = kwargs.get('legend_expand', 1.25)
         old_size = fig.get_size_inches()
 
@@ -1339,14 +1332,13 @@ def get_plot_style(style="fds"):
 
 def matlab_legend_to_matplotlib(position):
     """
-    Convert a MATLAB legend position string to the corresponding matplotlib location string.
+    Convert a MATLAB legend position string to a matplotlib-compatible location.
+    """
+    if not isinstance(position, str):
+        return 'best'
 
-    Parameters:
-        position (str): MATLAB-style legend position (e.g., 'northeast', 'southwestoutside')
+    pos = position.strip().lower()
 
-    Returns:
-        str: Matplotlib-compatible legend location (e.g., 'upper right')
-    """
     mapping = {
         'north': 'upper center',
         'south': 'lower center',
@@ -1356,17 +1348,15 @@ def matlab_legend_to_matplotlib(position):
         'southeast': 'lower right',
         'southwest': 'lower left',
         'northwest': 'upper left',
-        'northeastoutside': 'center left',    # rough equivalent
-        'northwestoutside': 'center right',
-        'southeastoutside': 'center left',
-        'southwestoutside': 'center right',
+
+        # outside positions (MATLAB → Matplotlib approximations)
+        'eastoutside': 'outside',
+
         'best': 'best'
     }
 
-    if not isinstance(position, str):
-        return 'best'
+    return mapping.get(pos, 'best')
 
-    return mapping.get(position.strip().lower(), 'best')
 
 
 def define_plot_parameters(D, irow, lightweight=False):

Utilities/Python/fdsplotlib.py

@@ -469,13 +469,14 @@ def read_prt5(filename, precision, *varargin):
     STIME, XP, YP, ZP, QP = read_prt5(ddir + chid[i] + '_1.prt5', 'real*4')
 
     if j[i] == 1:
-        fdsplotlib.plot_to_fig(x_data=XP[-1, :], y_data=QP[-1, :, 0, 0]/QP[-1, :, 0, 1], figure_handle=fig, marker_style='bo', data_label='FDS part')
+        fdsplotlib.plot_to_fig(x_data=XP[-1, :], y_data=QP[-1, :, 0, 0]/QP[-1, :, 0, 1], figure_handle=fig, marker_style='bo')
         v = np.abs(c_d * a_p * 0.5*rho_g*(XP[-1, :]**2) - QP[-1, :, 0, 0]/QP[-1, :, 0, 1])
     elif j[i] == 2:
-        fdsplotlib.plot_to_fig(x_data=YP[-1, :], y_data=QP[-1, :, 0, 0]/QP[-1, :, 0, 1], figure_handle=fig, marker_style='ro', data_label='FDS part')
+        fdsplotlib.plot_to_fig(x_data=YP[-1, :], y_data=QP[-1, :, 0, 0]/QP[-1, :, 0, 1], figure_handle=fig, marker_style='ro')
         v = np.abs(c_d * a_p * 0.5*rho_g*(YP[-1, :]**2) - QP[-1, :, 0, 0]/QP[-1, :, 0, 1])
     elif j[i] == 3:
-        fdsplotlib.plot_to_fig(x_data=ZP[-1, :], y_data=QP[-1, :, 0, 0]/QP[-1, :, 0, 1], figure_handle=fig, marker_style='go', data_label='FDS part')
+        fds_key_label = 'FDS part' if i==2 else None
+        fdsplotlib.plot_to_fig(x_data=ZP[-1, :], y_data=QP[-1, :, 0, 0]/QP[-1, :, 0, 1], figure_handle=fig, marker_style='go', data_label=fds_key_label)
         v = np.abs(c_d * a_p * 0.5*rho_g*(ZP[-1, :]**2) - QP[-1, :, 0, 0]/QP[-1, :, 0, 1])
 
     err = np.linalg.norm(v)/len(v)

Utilities/Python/scripts/fluid_part.py

@@ -104,7 +104,8 @@ def virtual_wind(phi_s_x: float, phi_s_y: float) -> tuple[float, float]:
                 plot_title=f'Level set spread rate (LS_ellipse_*ms_{slope:02d}deg)',
                 x_label='x (m)',
                 y_label='y (m)',
-                data_label=f'FDS {U} m/s'
+                data_label=f'FDS {U} m/s',
+                legend_location='lower right',
             )
         else:
             fdsplotlib.plot_to_fig(x_data=x_pts,

Utilities/Python/scripts/level_set_ellipse.py

@@ -58,7 +58,8 @@
       plot_title = 'Radiative Flux from a Hot Square Plate',
       data_label='Exact',
       y_label='Radiative Heat Flux (kW/m$^2$)',
-      x_label='Distance from Plate (m)')
+      x_label='Distance from Plate (m)',
+      legend_location='lower left')
 
 fdsplotlib.plot_to_fig(x_data=1-flux_20[0], y_data=flux_20[1], marker_style='r-',
       figure_handle=fig,

Utilities/Python/scripts/radiating_polygon.py

@@ -58,7 +58,8 @@
     revision_label=version_string,
     plot_title='Initialized bulk density (tree_shapes)',
     x_label=r'Input volume (m$^3$)',
-    y_label='Tree crown mass (kg)'
+    y_label='Tree crown mass (kg)',
+    legend_location='lower right',
 )
 
 # Plot results

Utilities/Python/scripts/tree_shapes.py

@@ -154,7 +154,8 @@ def energy_decay(chid, N):
                              x_min=0, x_max=0.7, y_min=0, y_max=0.07,
                              revision_label=version_string,
                              x_label='Time (s)',
-                             y_label='Kinetic Energy (m$^2$/s$^2$)')
+                             y_label='Kinetic Energy (m$^2$/s$^2$)',
+                             legend_location='upper right')
 
     if chid == 'csmag_32':
         M = pd.read_csv(outdir + 'mu0_32_devc.csv', skiprows=2, header=None).values