Added a pre-commit config file and reformatted all the files accordingly by using it.

2025-08-08 07:24:19 +08:00 · 2023-06-26 16:09:39 +05:30
--- a/toolboxes/AntennaPatterns/plot_fields.py
+++ b/toolboxes/AntennaPatterns/plot_fields.py
@@ -17,8 +17,11 @@ logger = logging.getLogger(__name__)


 # Parse command line arguments
-parser = argparse.ArgumentParser(description='Plot field patterns from a simulation with receivers positioned in circles around an antenna. This module should be used after the field pattern data has been processed and stored using the initial_save.py module.', usage='cd gprMax; python -m user_libs.AntennaPatterns.plot_fields numpyfile')
-parser.add_argument('numpyfile', help='name of numpy file including path')
+parser = argparse.ArgumentParser(
+    description="Plot field patterns from a simulation with receivers positioned in circles around an antenna. This module should be used after the field pattern data has been processed and stored using the initial_save.py module.",
+    usage="cd gprMax; python -m user_libs.AntennaPatterns.plot_fields numpyfile",
+)
+parser.add_argument("numpyfile", help="name of numpy file including path")
 # parser.add_argument('hertzian', help='name of numpy file including path')
 args = parser.parse_args()
 patterns = np.load(args.numpyfile)
@@ -28,7 +31,7 @@ patterns = np.load(args.numpyfile)
 # User configurable parameters

 # Pattern type (E or H)
-type = 'H'
+type = "H"

 # Relative permittivity of half-space for homogeneous materials (set to None for inhomogeneous)
 epsr = 5
@@ -52,33 +55,45 @@ step = 12
 # Critical angle and velocity
 if epsr:
    mr = 1
-    z1 = np.sqrt(mr / epsr) * config.sim_config.em_consts['z0']
-    v1 = config.sim_config.em_consts['c'] / np.sqrt(epsr)
-    thetac = np.round(np.rad2deg(np.arcsin(v1 / config.sim_config.em_consts['c'])))
+    z1 = np.sqrt(mr / epsr) * config.sim_config.em_consts["z0"]
+    v1 = config.sim_config.em_consts["c"] / np.sqrt(epsr)
+    thetac = np.round(np.rad2deg(np.arcsin(v1 / config.sim_config.em_consts["c"])))
    wavelength = v1 / f

 # Print some useful information
-logger.info('Centre frequency: {} GHz'.format(f / 1e9))
+logger.info("Centre frequency: {} GHz".format(f / 1e9))
 if epsr:
-    logger.info('Critical angle for Er {} is {} degrees'.format(epsr, thetac))
-    logger.info('Wavelength: {:.3f} m'.format(wavelength))
-    logger.info('Observation distance(s) from {:.3f} m ({:.1f} wavelengths) to {:.3f} m ({:.1f} wavelengths)'.format(radii[0], radii[0] / wavelength, radii[-1], radii[-1] / wavelength))
-    logger.info('Theoretical boundary between reactive & radiating near-field (0.62*sqrt((D^3/wavelength): {:.3f} m'.format(0.62 * np.sqrt((D**3) / wavelength)))
-    logger.info('Theoretical boundary between radiating near-field & far-field (2*D^2/wavelength): {:.3f} m'.format((2 * D**2) / wavelength))
+    logger.info("Critical angle for Er {} is {} degrees".format(epsr, thetac))
+    logger.info("Wavelength: {:.3f} m".format(wavelength))
+    logger.info(
+        "Observation distance(s) from {:.3f} m ({:.1f} wavelengths) to {:.3f} m ({:.1f} wavelengths)".format(
+            radii[0], radii[0] / wavelength, radii[-1], radii[-1] / wavelength
+        )
+    )
+    logger.info(
+        "Theoretical boundary between reactive & radiating near-field (0.62*sqrt((D^3/wavelength): {:.3f} m".format(
+            0.62 * np.sqrt((D**3) / wavelength)
+        )
+    )
+    logger.info(
+        "Theoretical boundary between radiating near-field & far-field (2*D^2/wavelength): {:.3f} m".format(
+            (2 * D**2) / wavelength
+        )
+    )

 # Setup figure
-fig = plt.figure(num=args.numpyfile, figsize=(8, 8), facecolor='w', edgecolor='w')
+fig = plt.figure(num=args.numpyfile, figsize=(8, 8), facecolor="w", edgecolor="w")
 ax = plt.subplot(111, polar=True)
-cmap = plt.cm.get_cmap('rainbow')
-ax.set_prop_cycle('color', [cmap(i) for i in np.linspace(0, 1, len(radii))])
+cmap = plt.cm.get_cmap("rainbow")
+ax.set_prop_cycle("color", [cmap(i) for i in np.linspace(0, 1, len(radii))])

 # Critical angle window and air/subsurface interface lines
 if epsr:
-    ax.plot([0, np.deg2rad(180 - thetac)], [min, 0], color='0.7', lw=2)
-    ax.plot([0, np.deg2rad(180 + thetac)], [min, 0], color='0.7', lw=2)
-ax.plot([np.deg2rad(270), np.deg2rad(90)], [0, 0], color='0.7', lw=2)
-ax.annotate('Air', xy=(np.deg2rad(270), 0), xytext=(8, 8), textcoords='offset points')
-ax.annotate('Ground', xy=(np.deg2rad(270), 0), xytext=(8, -15), textcoords='offset points')
+    ax.plot([0, np.deg2rad(180 - thetac)], [min, 0], color="0.7", lw=2)
+    ax.plot([0, np.deg2rad(180 + thetac)], [min, 0], color="0.7", lw=2)
+ax.plot([np.deg2rad(270), np.deg2rad(90)], [0, 0], color="0.7", lw=2)
+ax.annotate("Air", xy=(np.deg2rad(270), 0), xytext=(8, 8), textcoords="offset points")
+ax.annotate("Ground", xy=(np.deg2rad(270), 0), xytext=(8, -15), textcoords="offset points")

 # Plot patterns
 for patt in range(0, len(radii)):
@@ -86,12 +101,12 @@ for patt in range(0, len(radii)):
    pattplot = pattplot / np.max(np.max(patterns))  # Normalise, based on set of patterns

    # Calculate power (ignore warning from taking a log of any zero values)
-    with np.errstate(divide='ignore'):
+    with np.errstate(divide="ignore"):
        power = 10 * np.log10(pattplot)
    # Replace any NaNs or Infs from zero division
    power[np.invert(np.isfinite(power))] = 0

-    ax.plot(theta, power, label='{:.2f}m'.format(radii[patt]), marker='.', ms=6, lw=1.5)
+    ax.plot(theta, power, label="{:.2f}m".format(radii[patt]), marker=".", ms=6, lw=1.5)

 # Add Hertzian dipole plot
 # hertzplot1 = np.append(hertzian[0, :], hertzian[0, 0]) # Append start value to close circle
@@ -102,8 +117,8 @@ for patt in range(0, len(radii)):
 # ax.plot(theta, 10 * np.log10(hertzplot2), label='Inf. dipole, 0.58m', color='black', ls='--', lw=3)

 # Theta axis options
-ax.set_theta_zero_location('N')
-ax.set_theta_direction('clockwise')
+ax.set_theta_zero_location("N")
+ax.set_theta_direction("clockwise")
 ax.set_thetagrids(np.arange(0, 360, 30))

 # Radial axis options
@@ -111,19 +126,21 @@ ax.set_rmax(0)
 ax.set_rlabel_position(45)
 ax.set_yticks(np.arange(min, step, step))
 yticks = ax.get_yticks().tolist()
-yticks[-1] = '0 dB'
+yticks[-1] = "0 dB"
 ax.set_yticklabels(yticks)

 # Grid and legend
 ax.grid(True)
 handles, existlabels = ax.get_legend_handles_labels()
-leg = ax.legend([handles[0], handles[-1]], [existlabels[0], existlabels[-1]], ncol=2, loc=(0.27, -0.12), frameon=False)  # Plot just first and last legend entries
+leg = ax.legend(
+    [handles[0], handles[-1]], [existlabels[0], existlabels[-1]], ncol=2, loc=(0.27, -0.12), frameon=False
+)  # Plot just first and last legend entries
 # leg = ax.legend([handles[0], handles[-3], handles[-2], handles[-1]], [existlabels[0], existlabels[-3], existlabels[-2], existlabels[-1]], ncol=4, loc=(-0.13,-0.12), frameon=False)
 [legobj.set_linewidth(2) for legobj in leg.legendHandles]

 # Save a pdf of the plot
-savename = os.path.splitext(args.numpyfile)[0] + '.pdf'
-fig.savefig(savename, dpi=None, format='pdf', bbox_inches='tight', pad_inches=0.1)
+savename = os.path.splitext(args.numpyfile)[0] + ".pdf"
+fig.savefig(savename, dpi=None, format="pdf", bbox_inches="tight", pad_inches=0.1)
 # savename = os.path.splitext(args.numpyfile)[0] + '.png'
 # fig.savefig(savename, dpi=150, format='png', bbox_inches='tight', pad_inches=0.1)