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author | Matthias P. Braendli <matthias.braendli@mpb.li> | 2017-12-29 09:30:47 +0100 |
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committer | Matthias P. Braendli <matthias.braendli@mpb.li> | 2017-12-29 09:30:47 +0100 |
commit | 0c0f828c6bccee3aeb3049cb8b5bb480153cd3b6 (patch) | |
tree | 520dc4ff15dbc8dba056ea03d762d570b243f27d /dpd/src/subsample_align.py | |
parent | 9234155749be0c9ee3ae1269f47c2240d302c21a (diff) | |
parent | 8e3338479c180418a05ab030c60ba01c2a8615ca (diff) | |
download | dabmod-0c0f828c6bccee3aeb3049cb8b5bb480153cd3b6.tar.gz dabmod-0c0f828c6bccee3aeb3049cb8b5bb480153cd3b6.tar.bz2 dabmod-0c0f828c6bccee3aeb3049cb8b5bb480153cd3b6.zip |
Merge branch 'next' into outputRefactoring
Diffstat (limited to 'dpd/src/subsample_align.py')
-rwxr-xr-x | dpd/src/subsample_align.py | 10 |
1 files changed, 3 insertions, 7 deletions
diff --git a/dpd/src/subsample_align.py b/dpd/src/subsample_align.py index 68f3591..20ae56b 100755 --- a/dpd/src/subsample_align.py +++ b/dpd/src/subsample_align.py @@ -7,14 +7,10 @@ import datetime import logging import os - -logging_path = os.path.dirname(logging.getLoggerClass().root.handlers[0].baseFilename) - import numpy as np from scipy import optimize import matplotlib.pyplot as plt - def gen_omega(length): if (length % 2) == 1: raise ValueError("Needs an even length array.") @@ -32,7 +28,7 @@ def gen_omega(length): return omega -def subsample_align(sig, ref_sig, plot=False): +def subsample_align(sig, ref_sig, plot_location=None): """Do subsample alignment for sig relative to the reference signal ref_sig. The delay between the two must be less than sample @@ -72,13 +68,13 @@ def subsample_align(sig, ref_sig, plot=False): if optim_result.success: best_tau = optim_result.x - if plot: + if plot_location is not None: corr = np.vectorize(correlate_for_delay) ixs = np.linspace(-1, 1, 100) taus = corr(ixs) dt = datetime.datetime.now().isoformat() - tau_path = (logging_path + "/" + dt + "_tau.svg") + tau_path = (plot_location + "/" + dt + "_tau.png") plt.plot(ixs, taus) plt.title("Subsample correlation, minimum is best: {}".format(best_tau)) plt.savefig(tau_path) |