你已经派生过 gprMax
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https://gitee.com/sunhf/gprMax.git
已同步 2025-08-08 07:24:19 +08:00
Added a pre-commit config file and reformatted all the files accordingly by using it.
这个提交包含在：
Sai-Suraj-27
@@ -28,41 +28,45 @@ import numpy as np
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logger = logging.getLogger(__name__)
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# Create/setup plot figure
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#colors = ['#E60D30', '#5CB7C6', '#A21797', '#A3B347'] # Plot colours from http://tools.medialab.sciences-po.fr/iwanthue/index.php
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#colorIDs = ["#62a85b", "#9967c7", "#b3943f", "#6095cd", "#cb5c42", "#c95889"]
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# colors = ['#E60D30', '#5CB7C6', '#A21797', '#A3B347'] # Plot colours from http://tools.medialab.sciences-po.fr/iwanthue/index.php
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# colorIDs = ["#62a85b", "#9967c7", "#b3943f", "#6095cd", "#cb5c42", "#c95889"]
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colorIDs = ["#79c72e", "#5774ff", "#ff7c2c", "#4b4e80", "#d7004e", "#007545", "#ff83ec"]
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#colorIDs = ["#ba0044", "#b2d334", "#470055", "#185300", "#ff96b1", "#3e2700", "#0162a9", "#fdb786"]
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# colorIDs = ["#ba0044", "#b2d334", "#470055", "#185300", "#ff96b1", "#3e2700", "#0162a9", "#fdb786"]
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colors = itertools.cycle(colorIDs)
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# for i in range(2):
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# next(colors)
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lines = itertools.cycle(('--', ':', '-.', '-'))
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markers = ['o', 'd', '^', 's', '*']
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lines = itertools.cycle(("--", ":", "-.", "-"))
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markers = ["o", "d", "^", "s", "*"]
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parts = Path(__file__).parts
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path = 'rxs/rx1/'
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basename = 'pml_3D_pec_plate'
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PMLIDs = ['CFS-PML', 'HORIPML-1', 'HORIPML-2', 'MRIPML-1', 'MRIPML-2']
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path = "rxs/rx1/"
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basename = "pml_3D_pec_plate"
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PMLIDs = ["CFS-PML", "HORIPML-1", "HORIPML-2", "MRIPML-1", "MRIPML-2"]
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maxerrors = []
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testmodels = ['pml_3D_pec_plate_' + s for s in PMLIDs]
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testmodels = ["pml_3D_pec_plate_" + s for s in PMLIDs]
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fig, ax = plt.subplots(subplot_kw=dict(xlabel='Iterations', ylabel='Error [dB]'), figsize=(20, 10), facecolor='w', edgecolor='w')
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fig, ax = plt.subplots(
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subplot_kw=dict(xlabel="Iterations", ylabel="Error [dB]"), figsize=(20, 10), facecolor="w", edgecolor="w"
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)
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for x, model in enumerate(testmodels):
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# Open output file and read iterations
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fileref = h5py.File(Path(*parts[:-1], basename, basename + '_ref.h5'), 'r')
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filetest = h5py.File(Path(*parts[:-1], basename, basename + str(x + 1) + '.h5'), 'r')
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fileref = h5py.File(Path(*parts[:-1], basename, basename + "_ref.h5"), "r")
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filetest = h5py.File(Path(*parts[:-1], basename, basename + str(x + 1) + ".h5"), "r")
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# Get available field output component names
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outputsref = list(fileref[path].keys())
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outputstest = list(filetest[path].keys())
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if outputsref != outputstest:
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logger.exception('Field output components do not match reference solution')
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logger.exception("Field output components do not match reference solution")
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raise ValueError
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# Check that type of float used to store fields matches
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if filetest[path + outputstest[0]].dtype != fileref[path + outputsref[0]].dtype:
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logger.warning(f'Type of floating point number in test model ({filetest[path + outputstest[0]].dtype}) '
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f'does not match type in reference solution ({fileref[path + outputsref[0]].dtype})\n')
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logger.warning(
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f"Type of floating point number in test model ({filetest[path + outputstest[0]].dtype}) "
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f"does not match type in reference solution ({fileref[path + outputsref[0]].dtype})\n"
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)
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floattyperef = fileref[path + outputsref[0]].dtype
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floattypetest = filetest[path + outputstest[0]].dtype
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# logger.info(f'Data type: {floattypetest}')
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@@ -72,19 +76,19 @@ for x, model in enumerate(testmodels):
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# timeref = np.linspace(0, (fileref.attrs['Iterations'] - 1) * fileref.attrs['dt'], num=fileref.attrs['Iterations']) / 1e-9
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# timetest = np.zeros((filetest.attrs['Iterations']), dtype=floattypetest)
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# timetest = np.linspace(0, (filetest.attrs['Iterations'] - 1) * filetest.attrs['dt'], num=filetest.attrs['Iterations']) / 1e-9
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timeref = np.zeros((fileref.attrs['Iterations']), dtype=floattyperef)
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timeref = np.linspace(0, (fileref.attrs['Iterations'] - 1), num=fileref.attrs['Iterations'])
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timetest = np.zeros((filetest.attrs['Iterations']), dtype=floattypetest)
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timetest = np.linspace(0, (filetest.attrs['Iterations'] - 1), num=filetest.attrs['Iterations'])
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timeref = np.zeros((fileref.attrs["Iterations"]), dtype=floattyperef)
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timeref = np.linspace(0, (fileref.attrs["Iterations"] - 1), num=fileref.attrs["Iterations"])
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timetest = np.zeros((filetest.attrs["Iterations"]), dtype=floattypetest)
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timetest = np.linspace(0, (filetest.attrs["Iterations"] - 1), num=filetest.attrs["Iterations"])
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# Arrays for storing field data
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dataref = np.zeros((fileref.attrs['Iterations'], len(outputsref)), dtype=floattyperef)
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datatest = np.zeros((filetest.attrs['Iterations'], len(outputstest)), dtype=floattypetest)
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dataref = np.zeros((fileref.attrs["Iterations"], len(outputsref)), dtype=floattyperef)
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datatest = np.zeros((filetest.attrs["Iterations"], len(outputstest)), dtype=floattypetest)
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for ID, name in enumerate(outputsref):
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dataref[:, ID] = fileref[path + str(name)][:]
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datatest[:, ID] = filetest[path + str(name)][:]
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if np.any(np.isnan(datatest[:, ID])):
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logger.exception('Test data contains NaNs')
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logger.exception("Test data contains NaNs")
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raise ValueError
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fileref.close()
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@@ -94,18 +98,20 @@ for x, model in enumerate(testmodels):
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datadiffs = np.zeros(datatest.shape, dtype=np.float64)
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for i in range(len(outputstest)):
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maxi = np.amax(np.abs(dataref[:, i]))
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datadiffs[:, i] = np.divide(np.abs(datatest[:, i] - dataref[:, i]), maxi, out=np.zeros_like(dataref[:, i]), where=maxi != 0) # Replace any division by zero with zero
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datadiffs[:, i] = np.divide(
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np.abs(datatest[:, i] - dataref[:, i]), maxi, out=np.zeros_like(dataref[:, i]), where=maxi != 0
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) # Replace any division by zero with zero
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# Calculate power (ignore warning from taking a log of any zero values)
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with np.errstate(divide='ignore'):
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with np.errstate(divide="ignore"):
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datadiffs[:, i] = 20 * np.log10(datadiffs[:, i])
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# Replace any NaNs or Infs from zero division
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datadiffs[:, i][np.invert(np.isfinite(datadiffs[:, i]))] = 0
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# Print maximum error value
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start = 210
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maxerrors.append(f': {np.amax(datadiffs[start::, 1]):.1f} [dB]')
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logger.info(f'{model}: Max. error {maxerrors[x]}')
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maxerrors.append(f": {np.amax(datadiffs[start::, 1]):.1f} [dB]")
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logger.info(f"{model}: Max. error {maxerrors[x]}")
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# Plot diffs (select column to choose field component, 0-Ex, 1-Ey etc..)
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ax.plot(timeref[start::], datadiffs[start::, 1], color=next(colors), lw=2, ls=next(lines), label=model)
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@@ -114,16 +120,16 @@ for x, model in enumerate(testmodels):
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ax.set_yticks(np.arange(-160, 0, step=20))
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ax.set_ylim([-160, -20])
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ax.set_axisbelow(True)
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ax.grid(color=(0.75,0.75,0.75), linestyle='dashed')
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ax.grid(color=(0.75, 0.75, 0.75), linestyle="dashed")
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mylegend = list(map(add, PMLIDs, maxerrors))
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legend = ax.legend(mylegend, loc=1, fontsize=14)
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frame = legend.get_frame()
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frame.set_edgecolor('white')
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frame.set_edgecolor("white")
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frame.set_alpha(0)
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plt.show()
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# Save a PDF/PNG of the figure
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#fig.savefig(basepath + '.pdf', dpi=None, format='pdf', bbox_inches='tight', pad_inches=0.1)
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#fig.savefig(savename + '.png', dpi=150, format='png', bbox_inches='tight', pad_inches=0.1)
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# fig.savefig(basepath + '.pdf', dpi=None, format='pdf', bbox_inches='tight', pad_inches=0.1)
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# fig.savefig(savename + '.png', dpi=150, format='png', bbox_inches='tight', pad_inches=0.1)
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