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ZH: indicate when k-finding find the same ks
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1 changed files with 19 additions and 2 deletions
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@ -11,6 +11,7 @@ from itertools import combinations, zip_longest, product
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import matplotlib.pyplot as plt
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import matplotlib.pyplot as plt
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import numpy as np
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import numpy as np
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from os import path
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from os import path
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import os
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from scipy.interpolate import interp1d
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from scipy.interpolate import interp1d
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from earsim import REvent
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from earsim import REvent
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@ -165,6 +166,11 @@ if __name__ == "__main__":
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antennas_fname = path.join(fname_dir, beacon.antennas_fname)
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antennas_fname = path.join(fname_dir, beacon.antennas_fname)
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time_diffs_fname = 'time_diffs.hdf5' if not True else antennas_fname
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time_diffs_fname = 'time_diffs.hdf5' if not True else antennas_fname
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## This is a file indicating whether the k-finding algorithm was
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## stopped early. This happens when the ks do not change between
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## two consecutive iterations.
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run_break_fname = path.join(fname_dir, 'ca_breaked_run')
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# create fig_dir
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# create fig_dir
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if fig_dir:
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if fig_dir:
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os.makedirs(fig_dir, exist_ok=True)
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os.makedirs(fig_dir, exist_ok=True)
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@ -267,6 +273,11 @@ if __name__ == "__main__":
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x_fine = np.linspace(-scale2d, scale2d, 40)
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x_fine = np.linspace(-scale2d, scale2d, 40)
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y_fine = np.linspace(-scale2d, scale2d, 40)
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y_fine = np.linspace(-scale2d, scale2d, 40)
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## Remove run_break_fname if it exists
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try:
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os.remove(run_break_fname)
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except OSError:
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pass
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##
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##
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## Do calculations on the grid
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## Do calculations on the grid
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@ -377,8 +388,14 @@ if __name__ == "__main__":
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# Abort if no improvement
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# Abort if no improvement
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if ( r!= 0 and (old_ks_per_loc == ks_per_loc[best_idx]).all() ):
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if ( r!= 0 and (old_ks_per_loc == ks_per_loc[best_idx]).all() ):
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print("No changes from previous grid, breaking")
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print("No changes from previous grid, breaking at iteration {r} out of {N_runs}")
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# TODO: notate this case somewhere
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try:
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with open(run_break_fname, 'wt', encoding='utf-8') as fp:
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fp.write(f"Breaked at grid iteration {r} out of {N_runs}")
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except:
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pass
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break
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break
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old_ks_per_loc = ks_per_loc[best_idx]
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old_ks_per_loc = ks_per_loc[best_idx]
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