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