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# 在末尾加上，显示当前在第几个窗口。
caption always "%{= kw}%-w%{= kG}%{+b}[%n %t]%{-b}%{= kw}%+w %=%d %M %0c %{g}%H%{-}" 

aqzlpm11

/////////// self defined ENUM_STR, have a string val
#define ENUM_STR_BEGIN(type_name) \
class type_name { 							\
	std::string v; 							\
public: 									\
	static std::set<std::string>* vals() { static std::set<std::string> s; return &s; }\
	type_name(const std::string& a): v(a){} \
	std::string toString() { return v; } 	\
	bool isValid() { return vals()->find(v) != vals()->end(); }

aqzlpm11

#encoding=utf-8
import cProfile
import pstats


def fun():
    return sum([i for i in range(10000000)])

if __name__ == "__main__":
    cProfile.run('fun()', "result")

aqzlpm11

from functools import lru_cache


@lru_cache(maxsize=2**20)
def LCS(a, b):
    """ Longest common subsequence """
    if len(a) == 0 or len(b) == 0:
        return 0

    res = max(

aqzlpm11

import bob.io.audio
import bob.kaldi # https://www.idiap.ch/software/bob/docs/bob/docs/stable/bob/doc/install.html
import matplotlib.pyplot as plt

def vad(sig, sr, vad_energy_mean_scale=0.5, vad_energy_th=9, vad_frames_context=20, vad_proportion_th=0.4):
    """ Energy Based Voice Activate Detection algorithm. (based on kaldi)
        Param:
            sig: list or np.array
                the signal, list of samples
            sr: int

aqzlpm11

import librosa
import wave
from pathlib import Path
import numpy as np
import os

all_in_one_wav = "@all_in_one.wav"
all_in_one_wav_info = "@all_in_one.txt"
all_in_one_label = "@all_in_one_vad.txt"
label_file = "@label.txt"

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import wave
import os


def is_wav(f):
    res = True
    try:
        wave.open(f)
    except wave.Error as e:
        res = False

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#ifndef __PYTHON_LIKE__
#define __PYTHON_LIKE__

#include <stdio.h>
#include <string>
#include <fstream>
#include <streambuf>
#include <vector>
#include <iostream>
#include <stdarg.h>

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# coding=utf-8

import os
from multiprocessing.dummy import Pool


def can_ping(ip):
    ret = os.system('ping -n 1 -w 1 %s > nul' % ip)
    can_ping = True if ret == 0 else False
    return can_ping, ip

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from sklearn import metrics
from scipy.optimize import brentq
from scipy.interpolate import interp1d
def cal_eer(score_true, score_false):
    """ 计算EER

    Args:
    scores_true: 正样例的分数列表
    scores_false: 负样例的分数列表