Labeling By Mayority
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import shutil | |
import os | |
import pandas as pd | |
import numpy as np | |
def type_label(x): | |
labels = np.zeros(4) | |
for i in x: | |
labels[i] += 1 | |
return np.argmax(labels) | |
cluster_labels = {} | |
for filename in os.listdir('.'): | |
if filename.startswith('test_sequential_clustering') and filename.endswith('.csv'): | |
df = pd.read_csv(filename, sep=',') | |
for _, row in df.iterrows(): | |
if row['cluster'] not in cluster_labels: | |
cluster_labels[row['cluster']] = [] | |
cluster_labels[row['cluster']].append(row['type']) | |
for c in cluster_labels.keys(): | |
cluster_labels[c] = type_label(cluster_labels[c]) | |
cname = "test_sequential_seq_cluster_{}.wav".format(c) | |
if cluster_labels[c] == 2: | |
outname = "clicks_test_sequential_seq_cluster_{}.wav".format(c) | |
else: | |
outname = "shape_test_sequential_seq_cluster_{}.wav".format(c) | |
if os.path.exists(cname): | |
shutil.copyfile(cname, outname) | |
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