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ZH: show sigma_phase matrix as a plot

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Eric Teunis de Boone 2022-12-22 16:33:19 +01:00
parent 37943a19b0
commit 755426e156
1 changed files with 65 additions and 7 deletions
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72
simulations/airshower_beacon_simulation/bd_antenna_phase_deltas.py
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@ -4,6 +4,8 @@
import h5py
from itertools import combinations, zip_longest
import matplotlib.pyplot as plt
from matplotlib.colors import Normalize
import matplotlib as mpl
import numpy as np
import aa_generate_beacon as beacon
@ -50,17 +52,53 @@ if __name__ == "__main__":
idx = (name2idx(b[0]), name2idx(b[1]))
if idx[0] == idx[1]:
# hopefully 0
pass
sigma_phase_matrix[(idx[0], idx[1])] = true_phase_diffs[i]
sigma_phase_matrix[(idx[1], idx[0])] = true_phase_diffs[i]
sigma_phase_matrix[(idx[0], idx[1])] = lib.phase_mod(true_phase_diffs[i])
sigma_phase_matrix[(idx[1], idx[0])] = lib.phase_mod(true_phase_diffs[i])
# for each row j subtract the 0,j element from the whole row
# and apply phase_mod
first_row = sigma_phase_matrix[0]
mat_kwargs = dict(
norm = Normalize(vmin=-np.pi, vmax=+np.pi),
cmap = mpl.cm.get_cmap('Spectral_r')
)
sigma_phase_matrix = sigma_phase_matrix - first_row[:,np.newaxis]
sigma_phase_matrix = lib.phase_mod(sigma_phase_matrix)
# Show Matrix as figure
if True:
fig, ax = plt.subplots()
ax.set_title("Measured phase differences Baseline i,j")
ax.set_ylabel("Antenna no. i")
ax.set_xlabel("Antenna no. j")
im = ax.imshow(sigma_phase_matrix, interpolation='none', **mat_kwargs)
fig.colorbar(im, ax=ax)
if fig_dir:
fig.savefig(path.join(fig_dir, __file__ + f".matrix.original.pdf"))
# Modify the matrix to let each column represent multiple
# measurements of the same baseline (j,0) phase difference
if True:
# for each row j subtract the 0,j element from the whole row
# and apply phase_mod
first_row = (sigma_phase_matrix[0,:] * np.ones_like(sigma_phase_matrix)).T
# Show subtraction Matrix as figure
if True:
fig, ax = plt.subplots()
ax.set_title("Subtraction matrix i,j")
ax.set_ylabel("Antenna no. i")
ax.set_xlabel("Antenna no. j")
im = ax.imshow(first_row, interpolation='none', **mat_kwargs)
fig.colorbar(im, ax=ax)
if fig_dir:
fig.savefig(path.join(fig_dir, __file__ + f".matrix.first_row.pdf"))
sigma_phase_matrix = sigma_phase_matrix - first_row
sigma_phase_matrix = lib.phase_mod(sigma_phase_matrix)
# Except for the first row, these are all separate measurements
# Condense into phase offset per antenna
@ -72,6 +110,26 @@ if __name__ == "__main__":
mean_sigma_phase = np.nanmean(sigma_phase_matrix[my_mask], axis=0)
std_sigma_phase = np.nanstd( sigma_phase_matrix[my_mask], axis=0)
# Show resulting matrix as figure
if True:
fig, axs = plt.subplots(2,1, sharex=True)
axs[0].set_title("Modified measured phase differences Baseline 0,j")
axs[0].set_ylabel("Antenna no. 0")
axs[-1].set_xlabel("Antenna no. j")
im = axs[0].imshow(sigma_phase_matrix, interpolation='none', **mat_kwargs)
fig.colorbar(im, ax=axs)
axs[0].set_aspect('auto')
colours = [mat_kwargs['cmap'](mat_kwargs['norm'](x)) for x in mean_sigma_phase]
axs[1].set_ylabel("Mean Baseline Phase (0, j)[rad]")
axs[1].errorbar(np.arange(N_ant), mean_sigma_phase, yerr=std_sigma_phase, ls='none')
axs[1].scatter(np.arange(N_ant), mean_sigma_phase, c=colours,s=4)
if fig_dir:
fig.savefig(path.join(fig_dir, __file__ + f".matrix.modified.pdf"))
# write into antenna hdf5
with h5py.File(antennas_fname, 'a') as fp:
group = fp['antennas']