mirror of
https://gitlab.science.ru.nl/mthesis-edeboone/m-thesis-introduction.git
synced 2024-11-13 01:53:31 +01:00
255 lines
8.1 KiB
Python
Executable file
255 lines
8.1 KiB
Python
Executable file
#!/usr/bin/env python3
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__doc__ = \
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"""
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For each antenna i calculate the differences with the other antennas j,
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Do these sets of differences match upto an initial difference \Delta_{ii'}?
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"""
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from itertools import chain, combinations, product
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import numpy as np
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import matplotlib.pyplot as plt
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rng = np.random.default_rng()
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ns = 1e-9 # s
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km = 1e3 # m
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c_light = 3e8*ns # m/s
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class Antenna:
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"""
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Simple Antenna class
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"""
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def __init__(self,x=0,y=0,z=0,t0=0,name=""):
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self.x = x
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self.y = y
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self.z = z
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self.t = t0
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self.name = name
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def __repr__(self):
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cls = self.__class__.__name__
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return f'{cls}(x={self.x!r},y={self.y!r},z={self.z!r},t0={self.t!r},name={self.name!r})'
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def distance(x1, x2):
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"""
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Calculate the Euclidean distance between two locations x1 and x2
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"""
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assert type(x1) in [Antenna]
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x1 = np.array([x1.x, x1.y, x1.z])
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assert type(x2) in [Antenna]
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x2 = np.array([x2.x, x2.y, x2.z])
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return np.sqrt( np.sum( (x1-x2)**2 ) )
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def geometry_time(dist, x2=None, c_light=c_light):
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if x2 is not None:
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dist = distance(dist, x2)
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return dist/c_light
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def phase_mod(phase, low=np.pi):
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"""
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Modulo phase such that it falls within the
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interval $[-low, 2\pi - low)$.
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"""
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return (phase + low) % (2*np.pi) - low
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def antenna_triangles(antennas):
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return combinations(antennas, 3)
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def antenna_baselines(antennas):
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return combinations(antennas, 2)
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def add_spatial_time_delay(tx, antennas, time=geometry_time, t_scale=1):
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""" Modifies antennas inplace """
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for ant in antennas:
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ant.t += time(tx, ant)/t_scale
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def random_antenna(N_ant=1, antenna_ranges=[10e3,10e3,10e3], max_clock_skew=1):
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antennas = []
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for i in range(N_ant):
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loc = antenna_ranges*rng.random(3)
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if max_clock_skew is None:
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t0 = 0
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else:
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t0 = rng.normal(0, max_clock_skew)
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ant = Antenna(name=i, x=loc[0], y=loc[1], z=loc[1], t0=t0)
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antennas.append(ant)
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return antennas
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def single_baseline_referenced_sigmas(tx, baseline, all_antennas, phase_func=None):
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N_ant = len(all_antennas)
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baseline_ts = np.array([b.t for b in baseline])
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baseline_geo = np.array([geometry_time(tx,b) for b in baseline])
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not_baseline = lambda ant: ant not in baseline
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sigmas = np.empty( (N_ant-2, 2) )
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for j, ant in enumerate(filter(not_baseline, all_antennas)):
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t_diff = ant.t - baseline_ts
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geo_diff = geometry_time(tx, ant) - baseline_geo
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if phase_func is not None:
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sigmas[i] = phase_func(t_diff - geo_diff)
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else:
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sigmas[i] = t_diff - geo_diff
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return sigmas
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def reference_antenna_sigmas(tx, ref_ant, all_antennas, phase_func=None):
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N_ant = len(all_antennas)
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ref_geo = geometry_time(tx, ref_ant)
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sigmas = np.empty( (N_ant) )
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for i, ant in enumerate(all_antennas):
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if False and ant is ref_ant:
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sigmas[i] = 0
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t_diff = ant.t - ref_ant.t
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geo_diff = geometry_time(tx, ant) - ref_geo
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if phase_func is not None:
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sigmas[i] = phase_func(t_diff - geo_diff)
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else:
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sigmas[i] = t_diff - geo_diff
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return sigmas
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def all_sigmas_using_reference_antenna(tx, all_antennas, phase_func=None):
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N_ant = len(all_antennas)
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sigmas = np.empty( (N_ant,N_ant) )
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for i, ant in enumerate(all_antennas):
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sigmas[i] = reference_antenna_sigmas(tx, ant, all_antennas, phase_func=phase_func)
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return sigmas
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def main(tx, antennas, spatial_unit=None, time_unit=None, ref_idx = [0, 1, -2, -1], plot_phase=False, remove_minimum=True, f_beacon=50e6, scatter_kwargs={}):
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# Use each baseline once as a reference
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# and loop over the remaining antennas
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N_ant = len(antennas)
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fig = None
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default_scatter_kwargs = {}
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#for i, baseline in enumerate(antenna_baselines(antennas)):
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if False:
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baseline = [antennas[0], antennas[1]]
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sigmas = single_baseline_referenced_sigmas(tx, baseline, antennas)
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print("Baseline {},{}".format(baseline[0].name, baseline[1].name))
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print(sigmas)
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print(-1*np.diff(sigmas, axis=1))
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print("Direct", np.diff([a.t for a in baseline]))
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print()
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if True:
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if plot_phase:
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phase_func = lambda t: phase_mod(2*np.pi* f_beacon * t)
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color_label='$\\varphi$'
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default_scatter_kwargs['cmap'] = 'Spectral_r'
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default_scatter_kwargs['vmin'] = -np.pi
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default_scatter_kwargs['vmax'] = +np.pi
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else:
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color_label='t' if time_unit is None else 't ['+time_unit+']'
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phase_func = None
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scatter_kwargs = { **default_scatter_kwargs, **scatter_kwargs }
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sigmas = all_sigmas_using_reference_antenna(tx, antennas, phase_func=phase_func)
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if remove_minimum:
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if True:
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# actually use the time diffs with the first ref ant
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# required for phase alignment
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mins = sigmas[0]
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else:
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mins = -1*np.min(sigmas, axis=-1)
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sigmas = sigmas + mins[:, np.newaxis]
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if plot_phase:
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# Redo the phase mod
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sigmas = phase_mod(sigmas)
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fig, axs = plt.subplots(2,2, sharex=True, sharey=True)
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title = ""
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if remove_minimum:
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title += '$\sigma_{0j}$ added'
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if remove_minimum and plot_phase:
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title += ', '
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if plot_phase:
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t_scaler = 1
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if time_unit == 'ns':
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t_scaler = 1e9
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title += 'f= {:2.0f}MHz'.format(f_beacon*t_scaler/1e6)
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fig.suptitle(title)
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antenna_locs = list(zip(*[(ant.x, ant.y) for ant in antennas]))
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for i, ax in enumerate(axs.flat):
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ax.set_title("Ref Antenna: {}".format(ref_idx[i]))
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ax.set_xlabel('x' if spatial_unit is None else 'x [{}]'.format(spatial_unit))
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ax.set_ylabel('y' if spatial_unit is None else 'y [{}]'.format(spatial_unit))
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sc = ax.scatter(*antenna_locs, c=sigmas[ref_idx[i]], **scatter_kwargs)
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fig.colorbar(sc, ax=ax, label=color_label)
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ax.plot(antennas[ref_idx[i]].x, antennas[ref_idx[i]].y, 'rx')
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return fig, sigmas
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if __name__ == "__main__":
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from argparse import ArgumentParser
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from os import path
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rng = np.random.default_rng(1)
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parser = ArgumentParser(description=__doc__)
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parser.add_argument("fname", metavar="path/to/figure[/]", nargs="?", help="Location for generated figure, will append __file__ if a directory. If not supplied, figure is shown.")
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parser.add_argument('num_ant', help='Number of antennas to use', nargs='?', default=5, type=int)
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parser.add_argument('--remove-min', action='store_true')
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command_group = parser.add_mutually_exclusive_group(required=False)
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command_group.add_argument('--time', help='Calculate times (Default)', action='store_true')
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command_group.add_argument('--phase', help='Calculate wrapped phases', action='store_true')
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args = parser.parse_args()
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args.rm_minimum = True
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args.plot_phase = args.phase
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del args.time, args.phase
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if args.fname == 'none':
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args.fname = None
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if args.fname is not None:
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if path.isdir(args.fname):
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args.fname = path.join(args.fname, path.splitext(path.basename(__file__))[0]) # leave off extension
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if not path.splitext(args.fname)[1]:
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args.fname = [ args.fname+ext for ext in ['.pdf', '.png'] ]
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######
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antenna_ranges = np.array([10*km,10*km,5*km])
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antenna_max_clock_skew = 100*ns/ns # 0.1 us
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f_beacon = 50e6*ns # 50 MHz
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tx = Antenna(name='tx', x=-300*km, y=200*km, z=0)
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antennas = random_antenna(args.num_ant, antenna_ranges, antenna_max_clock_skew)
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add_spatial_time_delay(tx, antennas)
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fig, sigmas = main(tx, antennas, spatial_unit='m', time_unit='ns', plot_phase=args.plot_phase, remove_minimum=args.rm_minimum, f_beacon=f_beacon)
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###### Output
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if args.fname is not None:
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if isinstance(args.fname, str):
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args.fname = [args.fname]
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for fname in args.fname:
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plt.savefig(fname)
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else:
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plt.show()
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