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STM07_tSNE_PCA.py
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#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Sun Apr 21 08:25:58 2024
"""
import numpy as np
from sklearn.manifold import TSNE, MDS
from sklearn.decomposition import IncrementalPCA
from sklearn.preprocessing import StandardScaler
from sklearn.pipeline import make_pipeline
from joblib import dump
import datetime
import sys
import os
corpus_speech_list = ['BibleTTS/akuapem-twi',
'BibleTTS/asante-twi',
'BibleTTS/ewe',
'BibleTTS/hausa',
'BibleTTS/lingala',
'BibleTTS/yoruba',
'Buckeye',
'EUROM',
'HiltonMoser2022_speech',
'LibriSpeech',
# 'LibriVox',
'MediaSpeech/AR',
'MediaSpeech/ES',
'MediaSpeech/FR',
'MediaSpeech/TR',
'MozillaCommonVoice/ab',
'MozillaCommonVoice/ar',
'MozillaCommonVoice/ba',
'MozillaCommonVoice/be',
'MozillaCommonVoice/bg',
'MozillaCommonVoice/bn',
'MozillaCommonVoice/br',
'MozillaCommonVoice/ca',
'MozillaCommonVoice/ckb',
'MozillaCommonVoice/cnh',
'MozillaCommonVoice/cs',
'MozillaCommonVoice/cv',
'MozillaCommonVoice/cy',
'MozillaCommonVoice/da',
'MozillaCommonVoice/de',
'MozillaCommonVoice/dv',
'MozillaCommonVoice/el',
'MozillaCommonVoice/en',
'MozillaCommonVoice/eo',
'MozillaCommonVoice/es',
'MozillaCommonVoice/et',
'MozillaCommonVoice/eu',
'MozillaCommonVoice/fa',
'MozillaCommonVoice/fi',
'MozillaCommonVoice/fr',
'MozillaCommonVoice/fy-NL',
'MozillaCommonVoice/ga-IE',
'MozillaCommonVoice/gl',
'MozillaCommonVoice/gn',
'MozillaCommonVoice/hi',
'MozillaCommonVoice/hu',
'MozillaCommonVoice/hy-AM',
'MozillaCommonVoice/id',
'MozillaCommonVoice/ig',
'MozillaCommonVoice/it',
'MozillaCommonVoice/ja',
'MozillaCommonVoice/ka',
'MozillaCommonVoice/kab',
'MozillaCommonVoice/kk',
'MozillaCommonVoice/kmr',
'MozillaCommonVoice/ky',
'MozillaCommonVoice/lg',
'MozillaCommonVoice/lt',
'MozillaCommonVoice/ltg',
'MozillaCommonVoice/lv',
'MozillaCommonVoice/mhr',
'MozillaCommonVoice/ml',
'MozillaCommonVoice/mn',
'MozillaCommonVoice/mt',
'MozillaCommonVoice/nan-tw',
'MozillaCommonVoice/nl',
'MozillaCommonVoice/oc',
'MozillaCommonVoice/or',
'MozillaCommonVoice/pl',
'MozillaCommonVoice/pt',
'MozillaCommonVoice/ro',
'MozillaCommonVoice/ru',
'MozillaCommonVoice/rw',
'MozillaCommonVoice/sr',
'MozillaCommonVoice/sv-SE',
'MozillaCommonVoice/sw',
'MozillaCommonVoice/ta',
'MozillaCommonVoice/th',
'MozillaCommonVoice/tr',
'MozillaCommonVoice/tt',
'MozillaCommonVoice/ug',
'MozillaCommonVoice/uk',
'MozillaCommonVoice/ur',
'MozillaCommonVoice/uz',
'MozillaCommonVoice/vi',
'MozillaCommonVoice/yo',
'MozillaCommonVoice/yue',
'MozillaCommonVoice/zh-CN',
'MozillaCommonVoice/zh-TW',
'primewords_chinese',
'room_reader',
'SpeechClarity',
'TAT-Vol2',
'thchs30',
'TIMIT',
'TTS_Javanese',
'zeroth_korean'
]
corpus_music_list = [
'IRMAS',
'Albouy2020Science',
# 'CD', # exclude CDs due to open source concern
'GarlandEncyclopedia',
'fma_large',
'ismir04_genre',
'MTG-Jamendo',
'HiltonMoser2022_song',
'NHS2',
'MagnaTagATune'
]
corpus_env_list = [
'SONYC',
'MacaulayLibrary',
]
# sort the corpora lists to make sure the order is replicable
corpus_speech_list.sort()
corpus_music_list.sort()
corpus_env_list.sort()
corpus_list_all = corpus_speech_list+corpus_music_list+corpus_env_list
for corp in corpus_list_all:
filename = 'STM_output/corpSTMnpy/'+corp.replace('/', '-')+'_STMall.npy'
if 'STM_all' not in locals():
STM_all = np.load(filename)
else:
STM_all = np.vstack((STM_all, np.load(filename)))
print(filename)
# %% run code
perplexity = int(sys.argv[1])
if perplexity == 0:
# PCA
pipeline = make_pipeline(StandardScaler(),IncrementalPCA())
pipeline.fit(STM_all)
dump(pipeline, 'model/STM/PCA/allSTM_pca-pipeline_'+datetime.datetime.now().strftime("%Y-%m-%d_%H-%M")+'.joblib')
# MDS (too big)
# mds = MDS(
# n_components=2,
# random_state=23,
# n_jobs=-1,
# verbose=1,
# )
# pipeline_MDS = make_pipeline(StandardScaler(), mds)
# STM_MDS = pipeline_MDS.fit_transform(STM_all)
# path = 'model/MDS/'+datetime.datetime.now().strftime("%Y-%m-%d_%H-%M")
# os.mkdir(path)
# dump(pipeline_MDS, path+'/allSTM_MDS-pipeline.joblib')
# dump(STM_MDS, path+'/allSTM_MDS-data.joblib')
else:
tsne = TSNE(n_components=2,
random_state=23,
perplexity=perplexity,
verbose=1,
n_jobs=-1)
STM_tsne = tsne.fit_transform(STM_all)
path = 'model/STM/tsne/perplexity'+str(perplexity)+'_'+datetime.datetime.now().strftime("%Y-%m-%d_%H-%M")
os.mkdir(path)
dump(tsne, path+'/tsne_model.joblib')
dump(STM_tsne, path+'/tsne_data.joblib')