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ZH: show fitting information in phase plots
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parent
2f6616734b
commit
97f7b0ba8c
2 changed files with 35 additions and 25 deletions
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@ -33,6 +33,7 @@ if __name__ == "__main__":
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####
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fname_dir = args.data_dir
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antennas_fname = path.join(fname_dir, beacon.antennas_fname)
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snr_fname = path.join(fname_dir, beacon.snr_fname)
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fig_dir = args.fig_dir # set None to disable saving
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@ -156,6 +157,8 @@ if __name__ == "__main__":
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##
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## Histogram
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##
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snrs = beacon.read_snr_file(snr_fname)
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fig = figlib.phase_comparison_figure(
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loc_c,
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actual_clock_phases,
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@ -163,6 +166,7 @@ if __name__ == "__main__":
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f_beacon=f_beacon,
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figsize=figsize,
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fit_gaussian=plot_residuals,
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mean_snr=snrs['mean']
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)
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if plot_residuals:
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@ -11,10 +11,13 @@ def phase_comparison_figure(
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f_beacon=None,
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hist_kwargs={},
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sc_kwargs={},
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text_kwargs={},
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colors=['blue', 'orange'],
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legend_on_scatter=True,
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secondary_axis='time',
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fit_gaussian=False,
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mean_snr=None,
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return_fit_info=False,
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**fig_kwargs
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):
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"""
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@ -22,7 +25,14 @@ def phase_comparison_figure(
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by both plotting the values, and the residuals.
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"""
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default_fig_kwargs = dict(sharex=True)
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default_hist_kwargs = dict(bins='sqrt', density=False, alpha=0.8, histtype='step')
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default_text_kwargs = dict(fontsize=14, verticalalignment='top')
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default_sc_kwargs = dict(alpha=0.6, ls='none')
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fig_kwargs = {**default_fig_kwargs, **fig_kwargs}
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hist_kwargs = {**default_hist_kwargs, **hist_kwargs}
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text_kwargs = {**default_text_kwargs, **text_kwargs}
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sc_kwargs = {**default_sc_kwargs, **sc_kwargs}
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do_hist_plot = hist_kwargs is not False
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do_scatter_plot = sc_kwargs is not False
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@ -46,41 +56,34 @@ def phase_comparison_figure(
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secax = axs[0].secondary_xaxis('top', functions=functions)
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# Histogram
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fit_info = {}
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if do_hist_plot:
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i=0
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default_hist_kwargs = dict(bins='sqrt', density=False, alpha=0.8, histtype='step')
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hist_kwargs = {**default_hist_kwargs, **hist_kwargs}
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axs[i].set_ylabel("#")
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_counts, _bins, _patches = axs[i].hist(measured_phases, color=colors[0], label='Measured', ls='solid', **hist_kwargs)
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this_kwargs = dict(
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ax = axs[i],
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text_kwargs=text_kwargs,
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hist_kwargs={**hist_kwargs, **dict(label='Measured', color=colors[0], ls='solid')},
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mean_snr=mean_snr,
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)
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if fit_gaussian:
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this_kwargs['fit_distr'] = 'gaussian'
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_, fit_info = fitted_histogram_figure(
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measured_phases,
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**this_kwargs
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)
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if not plot_residuals: # also plot the true clock phases
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_bins = fit_info['bins']
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axs[i].hist(true_phases, color=colors[1], label='Actual', ls='dashed', **{**hist_kwargs, **dict(bins=_bins)})
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if fit_gaussian:# Fit a gaussian to the histogram
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gauss_kwargs = dict(color=colors[0], ls='dotted')
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xs = np.linspace(min(_bins), max(_bins))
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mean, std = norm.fit(measured_phases)
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dx = _bins[1] - _bins[0]
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scale = len(measured_phases)*dx
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fit_ys = norm.pdf(xs, mean, std) * scale
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axs[i].axvline(mean, ls='dotted', color='k', lw=2)
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axs[i].plot( xs, fit_ys, label='fit', **gauss_kwargs)
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# put mean, sigma and chisq on plot
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text_str = f"$\\mu$ = {mean: .2e}\n$\\sigma$ = {std: .2e}"
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text_kwargs = dict( transform=axs[i].transAxes, fontsize=14, verticalalignment='top')
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axs[i].text(0.02, 0.95, text_str, **text_kwargs)
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# Scatter plot
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if do_scatter_plot:
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i=1
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default_sc_kwargs = dict(alpha=0.6, ls='none')
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sc_kwargs = {**default_sc_kwargs, **sc_kwargs}
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axs[i].set_ylabel("Antenna no.")
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axs[i].plot(measured_phases, np.arange(len(measured_phases)), marker='x' if plot_residuals else '3', color=colors[0], label='Measured', **sc_kwargs)
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@ -92,6 +95,9 @@ def phase_comparison_figure(
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fig.tight_layout()
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if return_fit_info:
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return fig, fit_info
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return fig
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@ -210,4 +216,4 @@ def fitted_histogram_figure(
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loc = (0.98, 0.95)
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ax.text(*loc, text_str, **{**text_kwargs, **dict(ha='right')})
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return fig, fit_info
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return fig, dict(fit_info=fit_info, counts=counts, bins=bins)
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