From 00d6fed1612fbbda80801a1b197cfbf788299f3c Mon Sep 17 00:00:00 2001
From: wendtalexander <wendtalexander@protonmail.com>
Date: Wed, 18 Jan 2023 09:16:34 +0100
Subject: [PATCH] adding with ittertools the combinations
---
code/chirpdetection.py | 34 ++++++++++++++++++++--------------
1 file changed, 20 insertions(+), 14 deletions(-)
diff --git a/code/chirpdetection.py b/code/chirpdetection.py
index 194bbdf..a5a2ff4 100644
--- a/code/chirpdetection.py
+++ b/code/chirpdetection.py
@@ -1,4 +1,4 @@
-import os
+import itertools
import numpy as np
from IPython import embed
@@ -598,25 +598,31 @@ def main(datapath: str) -> None:
bool_vector = np.ones(len(sort_chirps_electrodes), dtype=bool)
# make index vector
index_vector = np.arange(len(sort_chirps_electrodes))
+ # make it more than only two electrodes for the search after chirps
+ combinations_best_elctrodes = list(itertools.combinations(range(3), 2))
the_real_chirps = []
for chirp_index, seoc in enumerate(sort_chirps_electrodes):
if bool_vector[chirp_index] == False:
continue
- else:
- cm = index_vector[(sort_chirps_electrodes >= seoc) & (
- sort_chirps_electrodes <= seoc + config.chirp_window_threshold)]
-
- if set([0,1]).issubset(sort_electrodes[cm]):
- the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
- elif set([1,0]).issubset(sort_electrodes[cm]):
- the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
- elif set([0,2]).issubset(sort_electrodes[cm]):
- the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
- elif set([1,2]).issubset(sort_electrodes[cm]):
+ cm = index_vector[(sort_chirps_electrodes >= seoc) & (
+ sort_chirps_electrodes <= seoc + config.chirp_window_threshold)]
+
+ for combination in combinations_best_elctrodes:
+ if set(combination).issubset(sort_electrodes[cm]):
the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
-
- bool_vector[cm] = False
+ """
+ if set([0,1]).issubset(sort_electrodes[cm]):
+ the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
+ elif set([1,0]).issubset(sort_electrodes[cm]):
+ the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
+ elif set([0,2]).issubset(sort_electrodes[cm]):
+ the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
+ elif set([1,2]).issubset(sort_electrodes[cm]):
+ the_real_chirps.append(np.mean(sort_chirps_electrodes[cm]))
+ """
+
+ bool_vector[cm] = False
for ct in the_real_chirps:
axs[0, el].axvline(ct, color='b', lw=1)
embed()