kastnerkyle

raise ValueError("DEPRECATED/FROZEN - see https://github.com/kastnerkyle/tools for the latest")

# License: BSD 3-clause
# Authors: Kyle Kastner
# Harvest, Cheaptrick, D4C, WORLD routines based on MATLAB code from M. Morise
# http://ml.cs.yamanashi.ac.jp/world/english/
# MGC code based on r9y9 (Ryuichi Yamamoto) MelGeneralizedCepstrums.jl
# Pieces also adapted from SPTK
from __future__ import division
import numpy as np

kastnerkyle

# Based on example here https://trac.ffmpeg.org/wiki/Encode/YouTube
text=$(basename $1 .wav)
ffmpeg -i $1 -filter_complex \
"[0:a]avectorscope=s=640x518,pad=1280:720[vs]; \
[0:a]showspectrum=mode=separate:color=intensity:scale=cbrt:s=640x518[ss]; \
[0:a]showwaves=s=1280x202:mode=line[sw]; \
[vs][ss]overlay=w[bg]; \
[bg][sw]overlay=0:H-h,drawtext=fontfile=/usr/share/fonts/truetype/fonts-japanese-gothic.ttf:fontcolor=white:x=10:y=10:text=$text[out]" \
-map "[out]" -map 0:a -c:v libx264 -preset fast -crf 18 -c:a copy $text.mkv

kastnerkyle

# Example from J.F. Sebastien on SO
# http://stackoverflow.com/questions/7894791/use-numpy-array-in-shared-memory-for-multiprocessing/7908612#7908612
import ctypes
import logging
import multiprocessing as mp

from contextlib import closing

import numpy as np

kastnerkyle

# Author: Kyle Kastner
# License: BSD 3-clause
# THEANO_FLAGS="optimizer=None,compute_test_value=raise" python tanh_rnn.py
import numpy as np
import theano
import theano.tensor as T
from scipy import linalg


class sgd(object):

kastnerkyle

# Author: Kyle Kastner
# License: BSD 3-Clause

# Inspired from blogpost by Justin Sermeno https://justinsermeno.com/posts/cfr/
# Extended with algorithms described by Oskari Tammelin http://jeskola.net/cfr/demo/ by 
# Particularly, solve has core game logic
# http://jeskola.net/cfr/demo/solve.js

# basecfr: http://poker.cs.ualberta.ca/publications/NIPS07-cfr.pdf 
# cfrplus: https://arxiv.org/abs/1407.5042

kastnerkyle

# Author: Kyle Kastner
# License: BSD 3-Clause
# Implementing http://mnemstudio.org/path-finding-q-learning-tutorial.htm
# Q-learning formula from http://sarvagyavaish.github.io/FlappyBirdRL/
# Visualization based on code from Gael Varoquaux gael.varoquaux@normalesup.org
# http://scikit-learn.org/stable/auto_examples/applications/plot_stock_market.html

import numpy as np
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

kastnerkyle

import gzip

def gzip_search(query: str, candidate_chunks: list[str], top_k: int=1):
    """
    文字列ベースで類似したテキストチャンクを推定するアルゴリズム.
    `query`, `chunk`, および`query + " " + chunk`をそれぞれgzipで圧縮し、編集距離のようなものをベースに評価する.

    Parameters:
        query (str): 検索クエリとして使用する文字列.
        top_k (int, optional): 返される類似チャンクの上位k個を指定する (default: 1).

kastnerkyle

# (C) Kyle Kastner, June 2014
# License: BSD 3 clause

from sklearn.base import BaseEstimator, TransformerMixin
from sklearn.utils import gen_batches
from scipy.linalg import eigh
from scipy.linalg import svd
import numpy as np

# From sklearn master

kastnerkyle

# Alec Radford, Indico, Kyle Kastner
# License: MIT
"""
Convolutional VAE in a single file.
Bringing in code from IndicoDataSolutions and Alec Radford (NewMu)
Additionally converted to use default conv2d interface instead of explicit cuDNN
"""
import theano
import theano.tensor as T
from theano.compat.python2x import OrderedDict

kastnerkyle

# (C) Kyle Kastner, June 2014
# License: BSD 3 clause

import scipy.stats as st
import numpy as np

class gmmhmm:
    #This class converted with modifications from https://code.google.com/p/hmm-speech-recognition/source/browse/Word.m
    def __init__(self, n_states):
        self.n_states = n_states