m-thesis-introduction/simulations/10_timegradient_per_ref_ant.py

256 lines
8.1 KiB
Python
Executable File

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