Figure showing time gradient

This commit is contained in:
Eric Teunis de Boone 2022-10-11 18:25:14 +02:00
parent 2e9d66cde6
commit 4d05ba4058

View file

@ -0,0 +1,192 @@
#!/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 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):
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
sigmas[j] = t_diff - geo_diff
return sigmas
def reference_antenna_sigmas(tx, ref_ant, all_antennas):
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
sigmas[i] = t_diff - geo_diff
return sigmas
def all_sigmas_using_reference_antenna(tx, all_antennas):
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)
return sigmas
def main(tx, antennas, spatial_unit=None, time_unit=None, ref_idx = [0, 1, -2, -1]):
# Use each baseline once as a reference
# and loop over the remaining antennas
N_ant = len(antennas)
fig = None
baseline = [antennas[0], antennas[1]]
#for i, baseline in enumerate(antenna_baselines(antennas)):
if False:
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:
sigmas = all_sigmas_using_reference_antenna(tx, antennas)
fig, axs = plt.subplots(2,2, sharex=True, sharey=True)
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]])
fig.colorbar(sc, ax=ax, label='t' if time_unit is None else 't ['+time_unit+']')
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)
args = parser.parse_args()
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
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')
###### 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()