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已同步 2025-08-08 07:24:19 +08:00
Updates/corrections to RTM process.
这个提交包含在:
@@ -7,41 +7,58 @@ import numpy as np
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from scipy.constants import c
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from scipy.io import loadmat
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# Load B-scan data to be migrated
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matfile = Path(str(Path(__file__).parent.resolve()), 'bgr_6.mat')
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matcontents = loadmat(str(matfile))
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data = matcontents['data']
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# Specify trace interval (metres), sampling interval (seconds),
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# and create time vector for B-scan data
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trac_int = 0.005
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samp_int = 1.7578e-11
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time = np.linspace(0, samp_int * data.shape[1], data.shape[1])
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# Specify velocity/permittivity of B-scan data
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v = 0.12e9
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er = (c / v)**2
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# Reverse B-scan data to use as sources for RTM model
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data = np.flipud(data)
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# Title and file path for FDTD model output
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modeltitle = 'rtm_model'
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fn = Path(__file__)
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fn = Path(fn.parent, modeltitle)
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# FDTD discretisation
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dl = trac_int
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# Load B-scan data to be migrated
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matfile = Path(str(Path(__file__).parent.resolve()), 'bgr_6.mat')
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matcontents = loadmat(str(matfile))
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data = matcontents['data']
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data = np.transpose(data) # Transpose to rows: samples, cols: traces
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# FDTD domain - 2D
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# Specify trace interval, sampling interval, & create time vector for B-scan data
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trac_int = 0.005 # metres
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samp_int = 1.7578e-11 # seconds
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maxtime = samp_int * data.shape[0]
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time = np.linspace(0, maxtime, data.shape[0])
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# Specify velocity/permittivity of B-scan data
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v = 0.12e9
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# Depth used for calculating FDTD z-dimension
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depth = v * maxtime / 2
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# FDTD discretisation, 2D domain dims, and time window
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dl = 0.005 # metres
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pml_cells = 10
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extra_cells = 10 # Allow some extra cells after PML before placing sources
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x = (data.shape[0] + 2 * pml_cells + 2 * extra_cells) * dl
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y = (data.shape[1] + 2 * pml_cells + 2 * extra_cells) * dl
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z = trac_int
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x_cells = data.shape[1] + 2 * pml_cells + 2 * extra_cells
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x = x_cells * trac_int
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y_cells = 1
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y = y_cells * dl
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z_cells = int(np.ceil(depth / dl) + 2 * pml_cells + 2 * extra_cells)
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z = z_cells * dl
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# FDTD time window
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timewindow = (data.shape[1] - 1) * samp_int
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# Holds permittivity field to import into FDTD model
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er = np.ones((x_cells, y_cells, z_cells - (pml_cells + extra_cells)))
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er_value = np.around(4 * (c / v)**2, decimals=2) # 4xEr as velocity doubled
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er = er * er_value
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mat_ers = np.unique(er)
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# Write materials text file
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with open(fn.with_suffix('.txt'), 'w') as fmaterials:
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for i, mat_er in enumerate(mat_ers):
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er[er==mat_er] = i
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fmaterials.write(f'#material: {mat_er} 0 1 0 mat{i}\n')
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# Write permittivity HDF5 file
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with h5py.File(fn.with_suffix('.h5'), 'w') as fdata:
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fdata.attrs['Title'] = modeltitle
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fdata.attrs['dx_dy_dz'] = (dl, dl, dl)
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fdata['/data'] = er.astype('int16')
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# Build FDTD model
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scene = gprMax.Scene()
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@@ -49,31 +66,26 @@ scene = gprMax.Scene()
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title = gprMax.Title(name=modeltitle)
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domain = gprMax.Domain(p1=(x, y, z))
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dxdydz = gprMax.Discretisation(p1=(dl, dl, dl))
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time_window = gprMax.TimeWindow(time=timewindow)
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time_window = gprMax.TimeWindow(time=maxtime)
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scene.add(title)
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scene.add(domain)
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scene.add(dxdydz)
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scene.add(time_window)
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# Specify materials and geometry for FDTD
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# N.B Permittivity should be 4 x permittivity from B-scan, i.e 2 x velocity
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mat1 = gprMax.Material(er=4*er, se=0, mr=1, sm=0, id='mat1')
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b1 = gprMax.Box(p1=(0, 0, 0), p2=(domain.props.p1[0],
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domain.props.p1[1] - (pml_cells + extra_cells) * dl,
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domain.props.p1[2]), material_id='mat1')
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go = gprMax.GeometryObjectsRead(p1=(0, 0, 0), geofile=fn.with_suffix('.h5'),
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matfile=fn.with_suffix('.txt'))
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# Specify waveforms and sources from reversed B-scan data
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data = np.transpose(data) # Transpose to match shape of time vector
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for i in range(data.shape[1]):
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wv = gprMax.Waveform(wave_type='user',
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user_values=data[:,i], user_time=time,
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user_values=np.flipud(data[:,i]), user_time=time,
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kind='linear', fill_value='extrapolate',
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id='mypulse' + str(i + 1))
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scene.add(wv)
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src = gprMax.HertzianDipole(polarisation='z',
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src = gprMax.HertzianDipole(polarisation='y',
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p1=((pml_cells + extra_cells) * dl + i * trac_int,
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domain.props.p1[1] - (pml_cells + extra_cells) * dl, 0),
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0, domain.props.p1[2] - (pml_cells + extra_cells) * dl),
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waveform_id='mypulse' + str(i + 1))
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scene.add(src)
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@@ -81,47 +93,63 @@ gv = gprMax.GeometryView(p1=(0, 0, 0), p2=domain.props.p1, dl=(dl, dl, dl),
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filename=fn.with_suffix('').parts[-1],
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output_type='n')
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# Snapshot of at end of time window will be RTM result
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# Snapshot at end of time window is RTM result
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fileext = '.h5' # Can also be '.vti' for a VTK format
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snap = gprMax.Snapshot(p1=(0, 0, 0), p2=domain.props.p1, dl=(dl, dl, dl),
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filename=fn.with_suffix('').parts[-1] + '_rtm_result',
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fileext=fileext, time=timewindow)
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snap = gprMax.Snapshot(p1=((pml_cells + extra_cells) * dl,
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0,
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(pml_cells + extra_cells) * dl),
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p2=(domain.props.p1[0] - (pml_cells + extra_cells) * dl,
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dl,
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domain.props.p1[2] - (pml_cells + extra_cells) * dl),
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dl=(dl, dl, dl),
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filename=fn.with_suffix('').parts[-1] + '_rtm_result',
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fileext=fileext, time=maxtime)
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scene.add(mat1)
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scene.add(b1)
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scene.add(go)
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scene.add(gv)
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scene.add(snap)
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# Run FDTD model
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gprMax.run(scenes=[scene], n=1, geometry_only=False, outputfile=fn)
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#gprMax.run(scenes=[scene], n=1, geometry_only=False, outputfile=fn)
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# Open RTM results file
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filename = Path(str(fn) + '_snaps', fn.with_suffix('').parts[-1] + '_rtm_result' + fileext)
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fieldcomponent = 'Ez'
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f = h5py.File(filename, 'r')
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outputdata = f[fieldcomponent]
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outputdata = np.array(outputdata)
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time = f.attrs['time']
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f.close()
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fieldcomponent = 'Ey'
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with h5py.File(filename, 'r') as f:
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outputdata = f[fieldcomponent]
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outputdata = np.array(outputdata)
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time = f.attrs['time']
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# Manipulation/processing of outputdata
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outputdata = outputdata.squeeze()
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outputdata = outputdata.transpose()
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# Plot RTM result
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fig = plt.figure(num=str(filename), figsize=(20, 10), facecolor='w', edgecolor='w')
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plt.imshow(outputdata, extent=[0, outputdata.shape[1], time, 0],
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interpolation='nearest', aspect='auto', cmap='gray',
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vmin=-np.amax(np.abs(outputdata)), vmax=np.amax(np.abs(outputdata)))
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plt.xlabel('Trace number')
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plt.ylabel('Time [s]')
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min_max_plt = (-1000, 1000)
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fig, (ax1, ax2) = plt.subplots(nrows=2, ncols=1, num=str(filename),
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figsize=(15, 10), facecolor='w', edgecolor='w')
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orig_plt = ax1.imshow(data, extent=[0, data.shape[1] * trac_int,
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(data.shape[0] * samp_int) / 2 * v, 0], interpolation='nearest',
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aspect='auto', cmap='viridis', vmin=-np.amax(np.abs(data)),
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vmax=np.amax(np.abs(data)))
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ax1.set_xlabel('Distance [m]')
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ax1.set_ylabel('Depth [m]')
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ax1.title.set_text('Original')
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ax1.grid(which='both', axis='both', linestyle='-.')
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cb1 = plt.colorbar(orig_plt, ax=ax1)
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cb1.set_label(fieldcomponent + ' [V/m]')
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# Grid properties
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ax = fig.gca()
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ax.grid(which='both', axis='both', linestyle='-.')
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cb = plt.colorbar()
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cb.set_label(fieldcomponent + ' [V/m]')
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rtm_plt = ax2.imshow(np.flipud(outputdata),
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extent=[0, outputdata.shape[1] * dl, depth, 0],
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interpolation='nearest', aspect='auto', cmap='viridis',
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vmin=-np.amax(np.abs(outputdata)),
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vmax=np.amax(np.abs(outputdata)))
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ax2.set_xlabel('Distance [m]')
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ax2.set_ylabel('Depth [m]')
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ax2.title.set_text('RTM')
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ax2.grid(which='both', axis='both', linestyle='-.')
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cb2 = plt.colorbar(rtm_plt, ax=ax2)
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cb2.set_label(fieldcomponent + ' [V/m]')
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# Save a PDF/PNG of the figure
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# fig.savefig(filename.with_suffix('.pdf'), dpi=None, format='pdf',
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@@ -129,4 +157,4 @@ cb.set_label(fieldcomponent + ' [V/m]')
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# fig.savefig(filename.with_suffix('.png'), dpi=150, format='png',
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# bbox_inches='tight', pad_inches=0.1)
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plt.show()
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plt.show()
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