185 lines
6.1 KiB
Python
Executable File
185 lines
6.1 KiB
Python
Executable File
#!/usr/bin/env python3
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import numpy as np
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import matplotlib.pyplot as plt
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import numpy.fft as ft
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import aa_generate_beacon as beacon
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from view_orig_ant0 import plot_antenna_geometry
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import lib
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from earsim import Antenna
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if __name__ == "__main__":
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from os import path
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import sys
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import matplotlib
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import os
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if os.name == 'posix' and "DISPLAY" not in os.environ:
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matplotlib.use('Agg')
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from scriptlib import MyArgumentParser
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parser = MyArgumentParser()
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parser.add_argument('ant_idx', default=[72], nargs='*', type=int, help='Antenna Indices')
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parser.add_argument('-p', '--polarisations', choices=['x', 'y', 'z', 'b', 'AxB', 'n', 'b+n'], action='append', help='Default: x,y,z')
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parser.add_argument('--geom', action='store_true', help='Make a figure containg the geometry from tx to antenna(s)')
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parser.add_argument('--ft', action='store_true', help='Add FT strenghts of antenna traces')
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args = parser.parse_args()
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figsize = (12,8)
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plot_ft_amplitude = args.ft
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plot_geometry = args.geom
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fig_dir = args.fig_dir
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show_plots = args.show_plots
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if not args.polarisations:
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args.polarisations = ['x','y', 'z']
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####
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fname_dir = args.data_dir
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antennas_fname = path.join(fname_dir, beacon.antennas_fname)
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tx_fname = path.join(fname_dir, beacon.tx_fname)
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f_beacon, tx, antennas = beacon.read_beacon_hdf5(antennas_fname)
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_, __, txdata = beacon.read_tx_file(tx_fname)
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beacon_amp = np.max(txdata['amplitudes'])# mu V/m
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idx = args.ant_idx
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if not idx:
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if not True:
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idx = [0, 1, len(antennas)//2, len(antennas)//2+1, -2, -1]
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elif not True:
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idx = np.arange(1, 20, 2, dtype=int)
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elif True:
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# center 6 antennas
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names = [55, 56, 57, 65, 66, 45, 46]
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idx = [ i for i, ant in enumerate(antennas) if int(ant.name) in names ]
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for i_fig in range(2):
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name_dist=''
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if i_fig == 1: #read in the raw_traces
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_, __, antennas = beacon.read_beacon_hdf5(antennas_fname, traces_key='prefiltered_traces')
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name_dist='.raw'
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fig1, axs = plt.subplots(1+plot_ft_amplitude*1 +0*1, figsize=figsize)
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if not plot_ft_amplitude:
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axs = [axs]
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axs[0].set_xlabel('t [ns]')
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axs[0].set_ylabel('[$\mu$V/m]')
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if i_fig == 1:
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axs[0].set_title("UnFiltered traces")
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else:
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axs[0].set_title("Filtered traces")
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if True:
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axs[0].set_xlim(-250, 250)
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if plot_ft_amplitude:
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axs[1].set_xlabel('f [GHz]')
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axs[1].set_ylabel('Power')
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if len(axs) > 2:
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axs[2].set_ylabel("Phase")
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axs[2].set_xlabel('f [GHz]')
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axs[2].set_ylim(-np.pi,+np.pi)
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colorlist = []
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for i in idx:
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ant = antennas[i]
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n_samples = len(ant.t)
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samplerate = (ant.t[-1] - ant.t[0])/n_samples
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axs[0].axvline(ant.t[0], color='k', alpha=0.5)
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mydict = {}
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for p in args.polarisations:
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pattr = 'E'+str(p)
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if p == 'b':
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pattr = 'beacon'
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elif p == 'n':
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pattr = 'noise'
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elif p == 'AxB':
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pattr = 'E_AxB'
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elif p =='b+n':
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mydict[p] = getattr(ant,'noise') + beacon_amp*getattr(ant, 'beacon')
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continue
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mydict[p] = getattr(ant, pattr)
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if 'b' in mydict:
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mydict['b'] *= beacon_amp
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for j, (direction, trace) in enumerate(mydict.items()):
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l = axs[0].plot(ant.t, trace, label=f"$E_{{{direction}}}$ {ant.name}", alpha=0.7)
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#if False and j == 0 and 't0' in ant.attrs:
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# axs[0].axvline(ant.attrs['t0'], color=l[0].get_color(), alpha=0.5)
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colorlist.append(l[0].get_color())
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if not plot_ft_amplitude:
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continue
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fft, freqs = lib.get_freq_spec(trace, 1/samplerate)
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axs[1].plot(freqs, np.abs(fft)**2, color=l[0].get_color())
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if True:
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cft = lib.direct_fourier_transform(f_beacon, ant.t, trace)
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amp = (cft[0]**2 + cft[1]**2)
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#axs[0].axhline(amp, color=l[0].get_color())
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print(amp)
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phase = np.arctan2(cft[0],cft[1])
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axs[1].plot(f_beacon, amp, color=l[0].get_color(), marker='3', alpha=0.8, ms=30)
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if len(axs) > 2:
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axs[2].plot(f_beacon, phase, color=l[0].get_color(), marker='3', alpha=0.8, ms=30)
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if plot_ft_amplitude:
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fig1.legend(loc='center right', ncol=min(2, len(idx)))
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else:
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axs[0].legend(loc='upper right', ncol=min(3, len(idx)))
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# Keep trace plot symmetric around 0
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max_lim = max(np.abs(axs[0].get_ylim()))
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axs[0].set_ylim(-max_lim, max_lim)
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# Keep spectrum between 0 and 100 MHz
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if len(axs) > 1:
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xlims = axs[1].get_xlim()
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axs[1].set_xlim(max(0, xlims[0]), min(0.1, xlims[1]))
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if False: # extra zoom
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axs[1].set_xlim(f_beacon - 0.01, f_beacon + 0.01)
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if fig_dir:
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fig1.savefig(path.join(fig_dir, path.basename(__file__) + f".trace{name_dist}.pdf"))
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if plot_geometry:
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if len(mydict) == 1:
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geom_colorlist = colorlist
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else:
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# only take the colour belonging to mydict[0]
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geom_colorlist = [ colorlist[len(mydict)*(i)] for i in range(len(colorlist)//len(mydict)) ]
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fig2, axs2 = plt.subplots(1, figsize=figsize)
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plot_antenna_geometry(antennas, ax=axs2, plot_max_values=False, color='grey', plot_names=False)
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plot_antenna_geometry([ antennas[i] for i in idx], ax=axs2, colors=geom_colorlist, plot_max_values=False)
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axs2.plot(tx.x, tx.y, marker='X', color='k')
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axs2.set_title("Geometry with selected antennas")
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if fig_dir:
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fig2.savefig(path.join(fig_dir, path.basename(__file__) + f".geom.pdf"))
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if show_plots:
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plt.show()
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