ZH: show sigma_phase matrix as a plot

simulations/airshower_beacon_simulation/bd_antenna_phase_deltas.py

@@ -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
@@ -50,16 +52,52 @@ 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[0], idx[1])] = lib.phase_mod(true_phase_diffs[i])
-        sigma_phase_matrix[(idx[1], idx[0])] = true_phase_diffs[i]
+        sigma_phase_matrix[(idx[1], idx[0])] = lib.phase_mod(true_phase_diffs[i])
 
+    mat_kwargs = dict(
+        norm = Normalize(vmin=-np.pi, vmax=+np.pi),
+        cmap = mpl.cm.get_cmap('Spectral_r')
+    )
+
+    # 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]
+        first_row = (sigma_phase_matrix[0,:] * np.ones_like(sigma_phase_matrix)).T
 
-    sigma_phase_matrix = sigma_phase_matrix - first_row[:,np.newaxis]
+        # 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
@@ -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']