convert-ej-m-adapt2.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'\\nThis program makes learning ev-gmm.\\n'"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# -*- coding: utf-8 -*-\n",
    "\n",
    "\"\"\"\n",
    "This program makes learning ev-gmm.\n",
    "\"\"\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# __future__ module make compatible python2 and python3\n",
    "from __future__ import division, print_function\n",
    "\n",
    "# basic modules\n",
    "import os\n",
    "import os.path\n",
    "import time\n",
    "\n",
    "# for warning ignore\n",
    "import warnings\n",
    "#warning.filterwarnings('ignore')\n",
    "\n",
    "# for file system manupulation \n",
    "from shutil import rmtree \n",
    "import glob\n",
    "import argparse\n",
    "\n",
    "# for save object\n",
    "import pickle\n",
    "\n",
    "# for make glaph\n",
    "%matplotlib inline\n",
    "import matplotlib.pyplot as plt\n",
    "import seaborn as sns\n",
    "sns.set_style(\"whitegrid\")\n",
    "plt.rcParams['figure.figsize'] = (16, 5)\n",
    "import librosa.display\n",
    "\n",
    "# for scientific computing\n",
    "import numpy as np\n",
    "from numpy.linalg import norm \n",
    "from sklearn.decomposition import PCA\n",
    "from sklearn.mixture import GMM # GMM class cannot use after sklearn 0.20.0\n",
    "import sklearn.mixture\n",
    "#from sklearn.mixture.gaussian_mixture import _compute_precision_cholesky\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "import scipy.sparse\n",
    "from scipy.signal import firwin, lfilter\n",
    "\n",
    "# for display audio controler\n",
    "from IPython.display import Audio\n",
    "\n",
    "# for manuplate audio data\n",
    "import soundfile as sf\n",
    "import pyworld as pw\n",
    "import pysptk\n",
    "from dtw import dtw\n",
    "from fastdtw import fastdtw"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "class WORLD(object):\n",
    "    \"\"\"\n",
    "    WORLD based speech analyzer and synthezer.\n",
    "    \n",
    "    Ref : https://github.com/k2kobayashi/sprocket/\n",
    "    \"\"\"\n",
    "    def __init__(self, fs=16000, fftl=1024, shiftms=5.0, minf0=40.0, maxf0=500.0):\n",
    "        \"\"\"\n",
    "        Parameters\n",
    "        ----------\n",
    "        fs : int \n",
    "            Sampling frequency \n",
    "        fftl : int\n",
    "            FFT length\n",
    "        shiftms : float\n",
    "            Shift length [ms]\n",
    "        minf0 : float\n",
    "            Floor in F0 estimation\n",
    "        maxf0 : float\n",
    "            Seli in F0 estimation\n",
    "        \"\"\"\n",
    "        \n",
    "        self.fs = fs\n",
    "        self.fftl = fftl\n",
    "        self.shiftms = shiftms\n",
    "        self.minf0 = minf0\n",
    "        self.maxf0 = maxf0\n",
    "        \n",
    "    def analyze(self, x):\n",
    "        \"\"\"\n",
    "        Analyze acoustic featueres.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        x : array, shape(`T`)\n",
    "            monoral speech signal in time domain\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        f0 : array, shape(`T`)\n",
    "            F0 sequence\n",
    "        sp : array, shape(`T`, `fftl / 2 + 1`)\n",
    "            Spectral envelope sequence\n",
    "        ap : array, shape(`T`, `fftl / 2 + 1`)\n",
    "            aperiodicity sequence\n",
    "        \"\"\"\n",
    "        \n",
    "        f0, time_axis = pw.harvest(x, self.fs, f0_floor=self.minf0,\n",
    "                                   f0_ceil=self.maxf0, frame_period=self.shiftms)\n",
    "        sp = pw.cheaptrick(x, f0, time_axis, self.fs, fft_size=self.fftl)\n",
    "        ap = pw.d4c(x, f0, time_axis, self.fs, fft_size=self.fftl)\n",
    "        \n",
    "        assert sp.shape == ap.shape\n",
    "        \n",
    "        return f0, sp, ap\n",
    "    \n",
    "    def analyze_f0(self, x):\n",
    "        \"\"\"\n",
    "        Analyze f0.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        x : array, shape(`T`)\n",
    "            monoral speech signal in time domain\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        f0 : array, shape(`T`)\n",
    "            F0 sequence\n",
    "        \"\"\"\n",
    "\n",
    "        f0, time_axis = pw.harvest(x, self.fs, f0_floor=self.minf0,\n",
    "                                   f0_ceil=self.maxf0, frame_period=self.shiftms)\n",
    "        \n",
    "        assert f0.shape == x.shape()\n",
    "        \n",
    "        return f0\n",
    "    \n",
    "    def synthesis(self, f0, sp, ap):\n",
    "        \"\"\"\n",
    "        Re-synthesizes a speech waveform from acoustic featueres.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        f0 : array, shape(`T`)\n",
    "            F0 sequence\n",
    "        sp : array, shape(`T`, `fftl / 2 + 1`)\n",
    "            Spectral envelope sequence\n",
    "        ap : array, shape(`T`, `fftl / 2 + 1`)\n",
    "            aperiodicity sequence\n",
    "        \"\"\"\n",
    "\n",
    "        return pw.synthesize(f0, sp, ap, self.fs, frame_period=self.shiftms)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "class FeatureExtractor(object):\n",
    "    \"\"\"\n",
    "    Analyze acoustic features from a waveform.\n",
    "    \n",
    "    This class may have several types of estimeter like WORLD or STRAIGHT.\n",
    "    Default type is WORLD.\n",
    "    \n",
    "    Ref : https://github.com/k2kobayashi/sprocket/\n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__(self, analyzer='world', fs=16000, fftl=1024, \n",
    "                 shiftms=5.0, minf0=50.0, maxf0=500.0):\n",
    "        \"\"\"\n",
    "        Parameters\n",
    "        ----------\n",
    "        analyzer : str\n",
    "            Analyzer\n",
    "        fs : int \n",
    "            Sampling frequency \n",
    "        fftl : int\n",
    "            FFT length\n",
    "        shiftms : float\n",
    "            Shift length [ms]\n",
    "        minf0 : float\n",
    "            Floor in F0 estimation\n",
    "        maxf0 : float\n",
    "            Seli in F0 estimation\n",
    "        \"\"\"\n",
    "        \n",
    "        self.analyzer = analyzer\n",
    "        self.fs = fs\n",
    "        self.fftl = fftl\n",
    "        self.shiftms = shiftms\n",
    "        self.minf0 = minf0\n",
    "        self.maxf0 = maxf0\n",
    "    \n",
    "        if self.analyzer == 'world':\n",
    "            self.analyzer = WORLD(fs=self.fs, fftl=self.fftl, \n",
    "                                  minf0=self.minf0, maxf0=self.maxf0, shiftms=self.shiftms)\n",
    "        else:\n",
    "            raise('Analyzer Error : not support type, see FeatureExtractor class.')\n",
    "        \n",
    "        self._f0 = None\n",
    "        self._sp = None\n",
    "        self._ap = None\n",
    "        \n",
    "    def analyze(self, x):\n",
    "        \"\"\"\n",
    "        Analyze acoustic featueres.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        x : array, shape(`T`)\n",
    "            monoral speech signal in time domain\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        f0 : array, shape(`T`)\n",
    "            F0 sequence\n",
    "        sp : array, shape(`T`, `fftl / 2 + 1`)\n",
    "            Spectral envelope sequence\n",
    "        ap : array, shape(`T`, `fftl / 2 + 1`)\n",
    "            aperiodicity sequence\n",
    "        \"\"\"\n",
    "        \n",
    "        self.x = np.array(x, dtype=np.float)\n",
    "        self._f0, self._sp, self._ap = self.analyzer.analyze(self.x)\n",
    "        \n",
    "        # check f0 < 0\n",
    "        self._f0[self._f0 < 0] = 0\n",
    "        \n",
    "        if np.sum(self._f0) == 0.0:\n",
    "            print(\"Warning : F0 values are all zero.\")\n",
    "        \n",
    "        return self._f0, self._sp, self._ap\n",
    "    \n",
    "    def analyze_f0(self, x):\n",
    "        \"\"\"\n",
    "        Analyze f0.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        x : array, shape(`T`)\n",
    "            monoral speech signal in time domain\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        f0 : array, shape(`T`)\n",
    "            F0 sequence\n",
    "        \"\"\"\n",
    "\n",
    "        self.x = np.array(x, dtype=np.float)\n",
    "        self._f0 = self.analyzer.analyze_f0(self.x)\n",
    "\n",
    "        # check f0 < 0\n",
    "        self._f0[self._f0 < 0] = 0\n",
    "        \n",
    "        if np.sum(self._f0) == 0.0:\n",
    "            print(\"Warning : F0 values are all zero.\")\n",
    "        \n",
    "        return self._f0\n",
    "    \n",
    "    def mcep(self, dim=24, alpha=0.42):\n",
    "        \"\"\"\n",
    "        Convert mel-cepstrum sequence from spectral envelope.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        dim : int\n",
    "            mel-cepstrum dimension\n",
    "        alpha : float\n",
    "            parameter of all-path filter\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        mcep : array, shape(`T`, `dim + 1`)\n",
    "            mel-cepstrum sequence\n",
    "        \"\"\"        \n",
    "        \n",
    "        self._analyzed_check()\n",
    "        \n",
    "        return pysptk.sp2mc(self._sp, dim, alpha)\n",
    "    \n",
    "    def codeap(self):\n",
    "        \"\"\"\n",
    "        \"\"\"\n",
    "        self._analyzed_check()\n",
    "        \n",
    "        return pw.code_aperiodicity(self._ap, self.fs)\n",
    "    \n",
    "    def npow(self):\n",
    "        \"\"\"\n",
    "        Normalized power sequence from spectral envelope.\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        npow : vector, shape(`T`, `1`)\n",
    "            Normalized power sequence of the given waveform\n",
    "        \"\"\"\n",
    "        \n",
    "        self._analyzed_check()\n",
    "        \n",
    "        npow = np.apply_along_axis(self._spvec2pow, 1, self._sp)\n",
    "        \n",
    "        meanpow = np.mean(npow)\n",
    "        npow = 10.0 * np.log10(npow / meanpow)\n",
    "        \n",
    "        return npow\n",
    "    \n",
    "    def _spvec2pow(self, specvec):\n",
    "        \"\"\"\n",
    "        \"\"\"\n",
    "        fftl2 = len(specvec) - 1\n",
    "        fftl = fftl2 * 2\n",
    "        \n",
    "        power = specvec[0] + specvec[fftl2]\n",
    "        for k in range(1, fftl2):\n",
    "            power += 2.0 * specvec[k]\n",
    "        power /= fftl\n",
    "        \n",
    "        return power\n",
    "        \n",
    "    def _analyzed_check(self):\n",
    "        if self._f0 is None and self._sp is None and self._ap is None:\n",
    "            raise('Call FeatureExtractor.analyze() before this method.')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "class Synthesizer(object):\n",
    "    \"\"\"\n",
    "    Synthesize a waveform from acoustic features.\n",
    "    \n",
    "    Ref : https://github.com/k2kobayashi/sprocket/\n",
    "    \"\"\"\n",
    "    def __init__(self, fs=16000, fftl=1024, shiftms=5.0):\n",
    "        \"\"\"\n",
    "        Parameters\n",
    "        ----------\n",
    "        fs : int \n",
    "            Sampling frequency \n",
    "        fftl : int\n",
    "            FFT length\n",
    "        shiftms : float\n",
    "            Shift length [ms]\n",
    "        \"\"\"\n",
    "        \n",
    "        self.fs = fs\n",
    "        self.fftl = fftl\n",
    "        self.shiftms = shiftms\n",
    "    \n",
    "    def synthesis(self, f0, mcep, ap, rmcep=None, alpha=0.42):\n",
    "        \"\"\"\n",
    "        Re-synthesizes a speech waveform from acoustic featueres.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        f0 : array, shape(`T`)\n",
    "            F0 sequence\n",
    "        mcep : array, shape(`T`, `dim`)\n",
    "            mel-cepstrum sequence\n",
    "        ap : array, shape(`T`, `fftl / 2 + 1`)\n",
    "            aperiodicity sequence\n",
    "        rmcep : array, shape(`T`, `dim`)\n",
    "            array of reference mel-cepstrum sequence\n",
    "        alpha : float\n",
    "            parameter of all-path filter\n",
    "            \n",
    "        Returns\n",
    "        ----------\n",
    "        wav : array,\n",
    "            syntesized waveform\n",
    "        \"\"\"\n",
    "        \n",
    "        if rmcep is not None:\n",
    "            # power modification\n",
    "            mcep = mod_power(mcep, rmcep, alpha=alpha)\n",
    "        \n",
    "        sp = pysptk.mc2sp(mcep, alpha, self.fftl)\n",
    "        wav = pw.synthesize(f0, sp, ap, self.fs, frame_period=self.shiftms)\n",
    "        \n",
    "        return wav\n",
    "        \n",
    "    def synthesis_diff(self, x, diffmcep, rmcep=None, alpha=0.42):\n",
    "        \"\"\"\n",
    "        Re-synthesizes a speech waveform from acoustic featueres.\n",
    "        filtering with a differential mel-cepstrum.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        x : array, shape(`samples`)\n",
    "            array of waveform sequence\n",
    "        diffmcep : array, shape(`T`, `dim`)\n",
    "            array of differential mel-cepstrum sequence\n",
    "        rmcep : array, shape(`T`, `dim`)\n",
    "            array of reference mel-cepstrum sequence\n",
    "        alpha : float\n",
    "            parameter of all-path filter\n",
    "            \n",
    "        Returns\n",
    "        ----------\n",
    "        wav : array,\n",
    "            syntesized waveform\n",
    "        \"\"\"      \n",
    "        \n",
    "        x = x.astype(np.float64)\n",
    "        dim = diffmcep.shape[1] - 1 \n",
    "        shiftl = int(self.fs / 1000 * self.shiftms)\n",
    "        \n",
    "        if rmcep is not None:\n",
    "            # power modification\n",
    "            diffmcep = mod_power(rmcep + diffmcep, rmcep, alpha=alpha) - rmcep        \n",
    "        \n",
    "        # mc2b = transform mel-cepstrum to MLSA digital filter coefficients.\n",
    "        b = np.apply_along_axis(pysptk.mc2b, 1, diffmcep, alpha)\n",
    "        \n",
    "        mlsa_fil = pysptk.synthesis.Synthesizer(pysptk.synthesis.MLSADF(dim, alpha=alpha),\n",
    "                                                shiftl)\n",
    "        wav = mlsa_fil.synthesis(x, b)\n",
    "        \n",
    "        return wav\n",
    "    \n",
    "    def synthesis_sp(self, f0, sp, ap):\n",
    "        \"\"\"\n",
    "        Re-synthesizes a speech waveform from acoustic featueres.\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        f0 : array, shape(`T`)\n",
    "            F0 sequence\n",
    "        spc : array, shape(`T`, `dim`)\n",
    "            mel-cepstrum sequence\n",
    "        ap : array, shape(`T`, `fftl / 2 + 1`)\n",
    "            aperiodicity sequence\n",
    "            \n",
    "        Returns\n",
    "        ----------\n",
    "        wav : array,\n",
    "            syntesized waveform\n",
    "        \"\"\"      \n",
    "        \n",
    "        wav = pw.synthesize(f0, sp, ap, self.fs, frame_period=self.shiftms)\n",
    "        \n",
    "        return wav\n",
    "    \n",
    "def mod_power(cvmcep, rmcep, alpha=0.42, irlen=256):\n",
    "    \"\"\"\n",
    "    power modification based on inpuulse responce\n",
    "\n",
    "    Parameters\n",
    "    ----------\n",
    "    cvmcep : array, shape(`T`, `dim`)\n",
    "        array of converted mel-cepstrum\n",
    "    rmcep : arraym shape(`T`, `dim`)\n",
    "        array of reference mel-cepstrum\n",
    "    alpha : float\n",
    "        parameter of all-path filter\n",
    "    irlen : int\n",
    "        Length for IIR filter\n",
    "\n",
    "    Returns\n",
    "    ----------\n",
    "    modified_cvmcep : array, shape(`T`, `dim`)\n",
    "        array of power modified converted mel-cepstrum\n",
    "    \"\"\"\n",
    "\n",
    "    if rmcep.shape != cvmcep.shape:\n",
    "        raise ValueError(\n",
    "            \"The shape of the converted and reference mel-cepstrum are different : {} / {}.format(cvmcep.shape, rmcep.shape)\"\n",
    "        )\n",
    "\n",
    "    # mc2e = Compute energy from mel-cepstrum. e-option\n",
    "    cv_e = pysptk.mc2e(cvmcep, alpha=alpha, irlen=irlen)\n",
    "    r_e = pysptk.mc2e(rmcep, alpha=alpha, irlen=irlen)\n",
    "\n",
    "    dpow = np.log(r_e / cv_e) / 2\n",
    "\n",
    "    modified_cvmcep = np.copy(cvmcep)\n",
    "    modified_cvmcep[:, 0] += dpow\n",
    "\n",
    "    return modified_cvmcep"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# def util methods\n",
    "def melcd(array1, array2):\n",
    "    \"\"\"\n",
    "    calculate mel-cepstrum distortion\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    array1, array2 : array, shape(`T`, `dim`) or shape(`dim`)\n",
    "        Array of original and target.\n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    mcd : scala, number > 0\n",
    "        Scala of mel-cepstrum distoriton\n",
    "    \"\"\"\n",
    "    if array1.shape != array2.shape:\n",
    "        raise ValueError(\n",
    "            \"The shape of both array are different : {} / {}.format(array1.shape,array2.shape)\"\n",
    "        )    \n",
    "   \n",
    "    if array1.ndim == 2:\n",
    "        diff = array1 - array2\n",
    "        mcd = 10.0 / np.log(10) * np.mean(np.sqrt(2.0 * np.sum(diff ** 2, axis=1)))\n",
    "    elif array1.ndim == 1:\n",
    "        diff = array1 - array2\n",
    "        mcd = 10.0 / np.log(10) * np.sqrt(2.0 * np.sum(diff ** 2))\n",
    "    else:\n",
    "        raise ValueError(\"Dimension mismatch.\")\n",
    "        \n",
    "    return mcd\n",
    "\n",
    "def delta(data, win=[-1.0, 1.0, 0]):\n",
    "    \"\"\"\n",
    "    calculate delta component\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    data : array, shape(`T`, `dim`)\n",
    "        Array of static matrix sequence.\n",
    "    win : array, shape(`3`)\n",
    "        The shape of window matrix.\n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    delta : array, shape(`T`, `dim`)\n",
    "        Array of delta matrix sequence.\n",
    "    \"\"\"\n",
    "    \n",
    "    if data.ndim == 1:\n",
    "        # change vector into 1d-array\n",
    "        T = len(data)\n",
    "        dim = data.ndim\n",
    "        data = data.reshape(T, dim)\n",
    "    else:\n",
    "        T, dim = data.shape\n",
    "    \n",
    "    win = np.array(win, dtype=np.float64)\n",
    "    delta = np.zeros((T, dim))\n",
    "    \n",
    "    delta[0] = win[0] * data[0] + win[1] * data[1]\n",
    "    delta[-1] = win[0] * data[-2] + win[1] * data[-1]\n",
    "    \n",
    "    for i in range(len(win)):\n",
    "        delta[1:T - 1] += win[i] * delta[i:T - 2 + i]\n",
    "    \n",
    "    return delta\n",
    "\n",
    "def static_delta(data, win=[-1.0, 1.0, 0]):\n",
    "    \"\"\"\n",
    "    calculate static and delta component\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    data : array, shape(`T`, `dim`)\n",
    "        Array of static matrix sequence.\n",
    "    win : array, shape(`3`)\n",
    "        The shape of window matrix.\n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    sddata : array, shape(`T`, `dim * 2`)\n",
    "        Array of static and delta matrix sequence.\n",
    "    \"\"\"\n",
    "    \n",
    "    sddata = np.c_[data, delta(data, win)]\n",
    "    \n",
    "    assert sddata.shape[1] == data.shape[1] * 2\n",
    "    \n",
    "    return sddata\n",
    "\n",
    "def construct_static_and_delta_matrix(T, D, win=[-1.0, 1.0, 0]):\n",
    "    \"\"\"\n",
    "    calculate static and delta transformation matrix\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    T : scala, `T`\n",
    "        Scala of time length\n",
    "    D : scala, `D`\n",
    "        Scala of the number of dimension.\n",
    "    win : array, shape(`3`)\n",
    "        The shape of window matrix.\n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    W : array, shape(`2 * D * T`, `D * T`)\n",
    "        Array of static and delta transformation matrix.\n",
    "    \"\"\"\n",
    "    \n",
    "    static = [0, 1, 0]\n",
    "    delta = win\n",
    "    assert len(static) == len(delta)\n",
    "    \n",
    "    # generate full W\n",
    "    DT = D * T\n",
    "    ones = np.ones(DT)\n",
    "    row = np.arange(2 * DT).reshape(2 * T, D) # generate serial numbers\n",
    "    static_row = row[::2] # [1,2,3,4,5] => [1,3,5]\n",
    "    delta_row = row[1::2] # [1,2,3,4,5] => [2,4]\n",
    "    col = np.arange(DT)\n",
    "    \n",
    "    data = np.array([ones * static[0], ones * static[1],\n",
    "                      ones * static[2], ones * delta[0],\n",
    "                      ones * delta[1], ones * delta[2]]).flatten()\n",
    "    row = np.array([[static_row] * 3, [delta_row] * 3]).flatten()\n",
    "    col = np.array([[col - D, col, col + D] * 2]).flatten()\n",
    "\n",
    "    # remove component at first and end frame\n",
    "    valid_idx = np.logical_not(np.logical_or(col < 0, col >= DT))\n",
    "    \n",
    "    W = scipy.sparse.csr_matrix(\n",
    "        (data[valid_idx], (row[valid_idx], col[valid_idx])), shape=(2 * DT, DT))\n",
    "    W.eliminate_zeros()\n",
    "    \n",
    "    return W\n",
    "    \n",
    "def extfrm(data, npow, power_threshold=-20):\n",
    "    \"\"\"\n",
    "    Extract frame over the power threshold\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    data : array, shape(`T`, `dim`)\n",
    "        array of input data\n",
    "    npow : array, shape(`T`)\n",
    "        vector of normalized power sequence\n",
    "    threshold : scala\n",
    "        scala of power threshold [dB]\n",
    "        \n",
    "    Returns\n",
    "    ----------\n",
    "    data : array, shape(`T_ext`, `dim`)\n",
    "        remaining data after extracting frame\n",
    "        `T_ext` <= `T`\n",
    "    \"\"\"\n",
    "    T = data.shape[0]\n",
    "    if T != len(npow):\n",
    "        raise(\"Length of two vectors is different.\")\n",
    "        \n",
    "    valid_index = np.where(npow > power_threshold)\n",
    "    extdata = data[valid_index]\n",
    "    assert extdata.shape[0] <= T\n",
    "    \n",
    "    return extdata\n",
    "\n",
    "def estimate_twf(orgdata, tardata, distance='melcd', fast=True, otflag=None):\n",
    "    \"\"\"\n",
    "    time warping function estimator\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    orgdata : array, shape(`T_org`, `dim`)\n",
    "        array of source feature\n",
    "    tardata : array, shape(`T_tar`, `dim`)\n",
    "        array of target feature\n",
    "    distance : str \n",
    "        distance function\n",
    "    fast : bool\n",
    "        use fastdtw instead of dtw\n",
    "    otflag : str\n",
    "        Alignment into the length of specification\n",
    "        'org' : alignment into original length\n",
    "        'tar' : alignment into target length   \n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    twf : array, shape(`2`, `T`)\n",
    "        time warping function between original and target\n",
    "    \"\"\"\n",
    "    \n",
    "    if distance == 'melcd':\n",
    "        def distance_func(x, y): return melcd(x, y)\n",
    "    else:\n",
    "        raise ValueError('this distance method is not support.')\n",
    "    \n",
    "    if fast:\n",
    "        _, path = fastdtw(orgdata, tardata, dist=distance_func)\n",
    "        twf = np.array(path).T\n",
    "    else:\n",
    "        _, _, _, twf = dtw(orgdata, tardata, distance_func) \n",
    "        \n",
    "    if otflag is not None:\n",
    "        twf = modify_twf(twf, otflag=otflag)\n",
    "    \n",
    "    return twf\n",
    "\n",
    "def align_data(org_data, tar_data, twf):\n",
    "    \"\"\"\n",
    "    get aligned joint feature vector\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    org_data : array, shape(`T_org`, `dim_org`)\n",
    "        Acoustic feature vector of original speaker\n",
    "    tar_data : array, shape(`T_tar`, `dim_tar`)\n",
    "        Acoustic feature vector of target speaker\n",
    "    twf : array, shape(`2`, `T`)\n",
    "        time warping function between original and target\n",
    "        \n",
    "    Returns\n",
    "    ----------\n",
    "    jdata : array, shape(`T_new`, `dim_org + dim_tar`)\n",
    "        Joint feature vector between source and target\n",
    "    \"\"\"\n",
    "    \n",
    "    jdata = np.c_[org_data[twf[0]], tar_data[twf[1]]]\n",
    "    return jdata\n",
    "\n",
    "def modify_twf(twf, otflag=None):\n",
    "    \"\"\"\n",
    "    align specified length\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    twf : array, shape(`2`, `T`)\n",
    "        time warping function between original and target\n",
    "    otflag : str\n",
    "        Alignment into the length of specification\n",
    "        'org' : alignment into original length\n",
    "        'tar' : alignment into target length   \n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    mod_twf : array, shape(`2`, `T_new`)\n",
    "        time warping function of modified alignment\n",
    "    \"\"\"\n",
    "    \n",
    "    if otflag == 'org':\n",
    "        of, indice = np.unique(twf[0], return_index=True)\n",
    "        mod_twf = np.c_[of, twf[1][indice]].T\n",
    "    elif otflag == 'tar':\n",
    "        tf, indice = np.unique(twf[1], return_index=True)\n",
    "        mod_twf = np.c_[twf[0][indice], tf].T \n",
    "    \n",
    "    return mod_twf\n",
    "\n",
    "def low_cut_filter(x, fs, cutoff=70):\n",
    "    \"\"\"\n",
    "    low cut filter\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    x : array, shape('samples')\n",
    "        waveform sequence\n",
    "    fs : array, int\n",
    "        Sampling frequency\n",
    "    cutoff : float\n",
    "        cutoff frequency of low cut filter\n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    lct_x : array, shape('samples')\n",
    "        Low cut filtered waveform sequence\n",
    "    \"\"\"\n",
    "    \n",
    "    nyquist = fs // 2\n",
    "    norm_cutoff = cutoff / nyquist\n",
    "    \n",
    "    # low cut filter\n",
    "    fil = firwin(255, norm_cutoff, pass_zero=False)\n",
    "    lct_x = lfilter(fil, 1, x)\n",
    "    \n",
    "    return lct_x\n",
    "\n",
    "def extsddata(data, npow, power_threshold=-20):\n",
    "    \"\"\"\n",
    "    get power extract static and delta feature vector\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    data : array, shape(`T`, `dim`)\n",
    "        acoustic feature vector\n",
    "    npow : array, shape(`T`)\n",
    "        normalized power vector\n",
    "    power_threshold : float\n",
    "        power threshold\n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    extsddata : array, shape(`T_new`, `dim * 2`)\n",
    "        silence remove static and delta feature vector\n",
    "    \"\"\"\n",
    "    \n",
    "    extsddata = extfrm(static_delta(data), npow, power_threshold=power_threshold)\n",
    "    return extsddata\n",
    "\n",
    "def transform_jnt(array_list):\n",
    "    num_files = len(array_list)\n",
    "    for i in range(num_files):\n",
    "        if i == 0:\n",
    "            jnt = array_list[i]\n",
    "        else:\n",
    "            jnt = np.r_[jnt, array_list[i]]\n",
    "    return jnt\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "class F0statistics(object):\n",
    "    \"\"\"\n",
    "    Estimate F0 statistics and convert F0\n",
    "    \"\"\"\n",
    "    def __init__(self):\n",
    "        pass\n",
    "    \n",
    "    def estimate(self, f0list):\n",
    "        \"\"\"\n",
    "        estimate F0 statistics from list of f0\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        f0list : list, shape(`f0num`)\n",
    "            List of several F0 sequence\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        f0stats : array, shape(`[mean, std]`)\n",
    "            values of mean and standard deviation for log f0\n",
    "        \"\"\"\n",
    "        \n",
    "        n_files = len(f0list)\n",
    "        assert n_files != 0\n",
    "\n",
    "        for i in range(n_files):\n",
    "            f0 = f0list[i]\n",
    "            nonzero_indices = np.nonzero(f0)\n",
    "            if i == 0:\n",
    "                f0s = np.log(f0[nonzero_indices])\n",
    "            else:\n",
    "                f0s = np.r_[f0s, np.log(f0[nonzero_indices])]\n",
    "        \n",
    "        f0stats = np.array([np.mean(f0s), np.std(f0s)])\n",
    "        \n",
    "        return f0stats\n",
    "\n",
    "    def convert(self, f0, orgf0stats, tarf0stats):\n",
    "        \"\"\"\n",
    "        convert F0 based on F0 statistics\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        f0 : array, shape(`T`, `1`)\n",
    "            array of F0 sequence\n",
    "        orgf0stats : array, shape(`[mean, std]`)\n",
    "            vectors of mean and standard deviation of log f0 for original speaker\n",
    "        tarf0stats : array, shape(`[mean, std]`)\n",
    "            vectors of mean and standard deviation of log f0 for target speaker\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        cvf0 : array, shape(`T`, `1`)\n",
    "            array of converted F0 sequence\n",
    "        \"\"\"\n",
    "        \n",
    "        # get length and dimension\n",
    "        T = len(f0)\n",
    "        \n",
    "        # perform f0 conversion\n",
    "        cvf0 = np.zeros(T)\n",
    "        \n",
    "        nonzero_indices  = f0 > 0\n",
    "        cvf0[nonzero_indices] = np.exp((tarf0stats[1] / orgf0stats[1]) * (np.log(f0[nonzero_indices]) - orgf0stats[0]) + tarf0stats[0])\n",
    "        \n",
    "        return cvf0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "class GV(object):\n",
    "    \"\"\"\n",
    "    Estimate statistics and perform postfilter based on the GV statistics.\n",
    "    \"\"\"\n",
    "    def __init__(self):\n",
    "        pass\n",
    "    \n",
    "    def estimate(self, datalist):\n",
    "        \"\"\"\n",
    "        estimate GV statistics from list of data\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        datalist : list, shape(`num_data`)\n",
    "            List of several data ([T, dim]) sequence\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        gvstats : array, shape(`2`, `dim`)\n",
    "            array of mean and standard deviation for GV\n",
    "        \"\"\"\n",
    "        \n",
    "        n_files = len(datalist)\n",
    "        assert n_files != 0\n",
    "        \n",
    "        var = []\n",
    "        for i in range(n_files):\n",
    "            data = datalist[i]\n",
    "            var.append(np.var(data, axis=0))\n",
    "            \n",
    "        # calculate vm and vv\n",
    "        vm = np.mean(np.array(var), axis=0)\n",
    "        vv = np.var(np.array(var), axis=0)\n",
    "        gvstats = np.r_[vm, vv]\n",
    "        gvstats = gvstats.reshape(2, len(vm))\n",
    "        \n",
    "        return gvstats\n",
    "\n",
    "    def postfilter(self, data, gvstats, cvgvstats=None, alpha=1.0, startdim=1):\n",
    "        \"\"\"\n",
    "        perform postfilter based on GV statistics into data\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        data : array, shape(`T`, `dim`)\n",
    "            array of data sequence\n",
    "        gvstats : array, shape(`2`, `dim`)\n",
    "            array of mean and variance for target GV\n",
    "        cvgvstats : array, shape(`2`, `dim`)\n",
    "            array of mean and variance for converted GV\n",
    "        alpha : float\n",
    "            morphing coefficient between GV transformed data and data.\n",
    "            alpha * gvpf(data) + (1 - alpha) * data\n",
    "        startdim : int\n",
    "            start dimension to perform GV postfilter\n",
    "        \n",
    "        Returns\n",
    "        ----------\n",
    "        filtered_data : array, shape(`T`, `data`)\n",
    "            array of GV postfiltered data sequnece\n",
    "        \"\"\"\n",
    "        \n",
    "        # get length and dimension\n",
    "        T, dim = data.shape\n",
    "        assert gvstats is not None\n",
    "        assert dim == gvstats.shape[1]\n",
    "        \n",
    "        # calculate statics of input data\n",
    "        datamean = np.mean(data, axis=0)\n",
    "        \n",
    "        if cvgvstats is None:\n",
    "            # use variance of the given data\n",
    "            datavar = np.var(data, axis=0)\n",
    "        else:\n",
    "            # use variance of trained gv stats\n",
    "            datavar = cvgvstats[0]\n",
    "        \n",
    "        # perform GV postfilter\n",
    "        filterd = np.sqrt(gvstats[0, startdim:] / datavar[startdim:]) * (data[:, startdim:] - datamean[startdim:]) + datamean[startdim:]\n",
    "        \n",
    "        filterd_data = np.c_[data[:, :startdim], filterd]\n",
    "        \n",
    "        return alpha * filterd_data + (1 - alpha) * data"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "# 0. config path\n",
    "__versions = \"pre-stored-ej\"\n",
    "__same_path = \"./utterance/\" + __versions + \"/\"\n",
    "prepare_path = __same_path + \"output/\"\n",
    "pre_stored_source_list = __same_path + 'pre-source/**/V01/T01/**/*.wav'\n",
    "pre_stored_list = __same_path + \"pre/**/V01/T01/**/*.wav\"\n",
    "output_path = \"./utterance/old-test/orl/ej-m/4/adapt2/\"\n",
    "\n",
    "# 1. estimate features\n",
    "feat = FeatureExtractor()\n",
    "synthesizer = Synthesizer()\n",
    "\n",
    "org_f0list = None\n",
    "org_splist = None\n",
    "org_mceplist = None\n",
    "org_aplist = None\n",
    "org_npowlist = None\n",
    "org_codeaplist = None\n",
    "\n",
    "if os.path.exists(prepare_path + \"_org_f0.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_org_sp.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_org_ap.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_org_mcep.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_org_npow.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_org_codeap.pickle\"):\n",
    "        \n",
    "    with open(prepare_path + \"_org_f0.pickle\", 'rb') as f:    \n",
    "        org_f0list = pickle.load(f)\n",
    "    with open(prepare_path + \"_org_sp.pickle\", 'rb') as f:   \n",
    "        org_splist = pickle.load(f)\n",
    "    with open(prepare_path + \"_org_ap.pickle\", 'rb') as f:  \n",
    "        org_aplist = pickle.load(f)\n",
    "    with open(prepare_path + \"_org_mcep.pickle\", 'rb') as f:  \n",
    "        org_mceplist = pickle.load(f)\n",
    "    with open(prepare_path + \"_org_npow.pickle\", 'rb') as f:  \n",
    "        org_npowlist = pickle.load(f)\n",
    "    with open(prepare_path + \"_org_codeap.pickle\", 'rb') as f:  \n",
    "        org_codeaplist = pickle.load(f) \n",
    "else:\n",
    "    org_f0list = []\n",
    "    org_splist = []\n",
    "    org_mceplist = []\n",
    "    org_aplist = []\n",
    "    org_npowlist = []\n",
    "    org_codeaplist = []\n",
    "    ite = 0\n",
    "    for files in sorted(glob.iglob(pre_stored_source_list, recursive=True)):\n",
    "        wavf = files\n",
    "        x, fs = sf.read(wavf)\n",
    "        x = np.array(x, dtype=np.float)\n",
    "        x = low_cut_filter(x, fs, cutoff=70)\n",
    "        assert fs == 16000\n",
    "\n",
    "        print(\"extract acoustic featuers: \" + wavf)\n",
    "\n",
    "        f0, sp, ap = feat.analyze(x)\n",
    "        mcep = feat.mcep()\n",
    "        npow = feat.npow()\n",
    "        codeap = feat.codeap()\n",
    "        wav = synthesizer.synthesis_sp(f0, sp, ap)\n",
    "        wav = np.clip(wav, -32768, 32767)\n",
    "        sf.write(prepare_path + \"src_ansys_{}_.wav\".format(ite), wav, fs)\n",
    "\n",
    "        org_f0list.append(f0)\n",
    "        org_splist.append(sp)\n",
    "        org_mceplist.append(mcep)\n",
    "        org_aplist.append(ap)\n",
    "        org_npowlist.append(npow)\n",
    "        org_codeaplist.append(codeap)\n",
    "\n",
    "        wav = synthesizer.synthesis(f0, mcep, ap)\n",
    "        wav = np.clip(wav, -32768, 32767)\n",
    "        sf.write(prepare_path + \"src_mcep_{}_.wav\".format(ite), wav, fs)\n",
    "        ite = ite + 1\n",
    "\n",
    "    with open(prepare_path + \"_org_f0.pickle\", 'wb') as f:    \n",
    "        pickle.dump(org_f0list, f)\n",
    "    with open(prepare_path + \"_org_sp.pickle\", 'wb') as f:   \n",
    "        pickle.dump(org_splist, f)\n",
    "    with open(prepare_path + \"_org_npow.pickle\", 'wb') as f:   \n",
    "        pickle.dump(org_npowlist, f)\n",
    "    with open(prepare_path + \"_org_ap.pickle\", 'wb') as f:  \n",
    "        pickle.dump(org_aplist, f)\n",
    "    with open(prepare_path + \"_org_mcep.pickle\", 'wb') as f:  \n",
    "        pickle.dump(org_mceplist, f)\n",
    "    with open(prepare_path + \"_org_codeap.pickle\", 'wb') as f:  \n",
    "        pickle.dump(org_codeaplist, f) \n",
    "\n",
    "mid_f0list = None\n",
    "mid_mceplist = None\n",
    "mid_aplist = None\n",
    "mid_npowlist = None\n",
    "mid_splist = None\n",
    "mid_codeaplist = None        \n",
    "\n",
    "if os.path.exists(prepare_path + \"_mid_f0.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_mid_sp_0_.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_mid_ap_0_.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_mid_mcep.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_mid_npow.pickle\") \\\n",
    "    and os.path.exists(prepare_path + \"_mid_codeap.pickle\"):\n",
    "        \n",
    "    with open(prepare_path + \"_mid_f0.pickle\", 'rb') as f:    \n",
    "        mid_f0list = pickle.load(f)\n",
    "    for i in range(0, len(org_splist)*21, len(org_splist)):  \n",
    "        with open(prepare_path + \"_mid_sp_{}_.pickle\".format(i), 'rb') as f:\n",
    "            temp_splist = pickle.load(f)\n",
    "            if mid_splist is None:\n",
    "                mid_splist = temp_splist\n",
    "            else:\n",
    "                mid_splist = mid_splist + temp_splist\n",
    "    for i in range(0, len(org_aplist)*21, len(org_aplist)):  \n",
    "        with open(prepare_path + \"_mid_ap_{}_.pickle\".format(i), 'rb') as f:\n",
    "            temp_aplist = pickle.load(f)\n",
    "            if mid_aplist is None:\n",
    "                mid_aplist = temp_aplist\n",
    "            else:\n",
    "                mid_aplist = mid_aplist + temp_aplist    \n",
    "    with open(prepare_path + \"_mid_mcep.pickle\", 'rb') as f:  \n",
    "        mid_mceplist = pickle.load(f)\n",
    "    with open(prepare_path + \"_mid_npow.pickle\", 'rb') as f:  \n",
    "        mid_npowlist = pickle.load(f)\n",
    "    with open(prepare_path + \"_mid_codeap.pickle\", 'rb') as f:  \n",
    "        mid_codeaplist = pickle.load(f) \n",
    "else:        \n",
    "    mid_f0list = []\n",
    "    mid_mceplist = []\n",
    "    mid_aplist = []\n",
    "    mid_npowlist = []\n",
    "    mid_splist = []\n",
    "    mid_codeaplist = []\n",
    "    ite = 0\n",
    "    for files in sorted(glob.iglob(pre_stored_list, recursive=True)):\n",
    "        wavf = files\n",
    "        x, fs = sf.read(wavf)\n",
    "        x = np.array(x, dtype=np.float)\n",
    "        x = low_cut_filter(x, fs, cutoff=70)\n",
    "        assert fs == 16000\n",
    "\n",
    "        print(\"extract acoustic featuers: \" + wavf)\n",
    "\n",
    "        f0, sp, ap = feat.analyze(x)\n",
    "        mcep = feat.mcep()\n",
    "        npow = feat.npow()\n",
    "        codeap = feat.codeap()\n",
    "        name, ext = os.path.splitext(wavf)\n",
    "        wav = synthesizer.synthesis_sp(f0, sp, ap)\n",
    "        wav = np.clip(wav, -32768, 32767)\n",
    "        sf.write(prepare_path + \"mid_ansys_{}_.wav\".format(ite), wav, fs)\n",
    "\n",
    "        mid_f0list.append(f0)\n",
    "        mid_splist.append(sp)\n",
    "        mid_mceplist.append(mcep)\n",
    "        mid_aplist.append(ap)\n",
    "        mid_npowlist.append(npow)\n",
    "        mid_codeaplist.append(codeap)\n",
    "\n",
    "        wav = synthesizer.synthesis(f0, mcep, ap)\n",
    "        wav = np.clip(wav, -32768, 32767)\n",
    "        sf.write(prepare_path + \"mid_mcep_{}_.wav\".format(ite), wav, fs)\n",
    "        ite = ite + 1\n",
    "        \n",
    "    with open(prepare_path + \"_mid_f0.pickle\", 'wb') as f:\n",
    "        print(f)\n",
    "        pickle.dump(mid_f0list, f)\n",
    "    with open(prepare_path + \"_mid_npow.pickle\", 'wb') as f:\n",
    "        print(f)\n",
    "        pickle.dump(mid_npowlist, f)\n",
    "    for i in range(0, len(mid_splist), len(org_splist)):\n",
    "        with open(prepare_path + \"_mid_sp_{}_.pickle\".format(i), 'wb') as f:   \n",
    "            print(f)\n",
    "            pickle.dump(mid_splist[i:i+len(org_splist)], f)\n",
    "    for i in range(0, len(mid_aplist), len(org_aplist)):\n",
    "        with open(prepare_path + \"_mid_ap_{}_.pickle\".format(i), 'wb') as f:\n",
    "            print(f)\n",
    "            pickle.dump(mid_aplist[i:i+len(org_aplist)], f)\n",
    "    with open(prepare_path + \"_mid_mcep.pickle\", 'wb') as f:\n",
    "        print(f)\n",
    "        pickle.dump(mid_mceplist, f)\n",
    "    with open(prepare_path + \"_mid_codeap.pickle\", 'wb') as f:\n",
    "        print(f)\n",
    "        pickle.dump(mid_codeaplist, f) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "class GMMTrainer(object):\n",
    "    \"\"\"\n",
    "    this class offers the training of GMM with several types of covariance matrix.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    n_mix : int \n",
    "        the number of mixture components of the GMM\n",
    "    n_iter : int\n",
    "        the number of iteration for EM algorithm\n",
    "    covtype : str\n",
    "        the type of covariance matrix of the GMM\n",
    "        'full': full-covariance matrix\n",
    "    \n",
    "    Attributes\n",
    "    ---------\n",
    "    param : \n",
    "        sklearn-based model parameters of the GMM\n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__(self, n_mix=64, n_iter=100, covtype='full', params='wmc'):\n",
    "        self.n_mix = n_mix\n",
    "        self.n_iter = n_iter\n",
    "        self.covtype = covtype\n",
    "        self.params = params\n",
    "        self.param = sklearn.mixture.GMM(n_components=self.n_mix,\n",
    "                                                     covariance_type=self.covtype,\n",
    "                                                     n_iter=self.n_iter, params=self.params)\n",
    "        \n",
    "    def train(self, jnt):\n",
    "        \"\"\"\n",
    "        fit GMM parameter from given joint feature vector\n",
    "        \n",
    "        Parametes\n",
    "        ---------\n",
    "        jnt : array, shape(`T`, `jnt.shape[0]`)\n",
    "            joint feature vector of original and target feature vector consisting of static and delta components\n",
    "        \"\"\"\n",
    "        \n",
    "        if self.covtype == 'full':\n",
    "            self.param.fit(jnt)\n",
    "            \n",
    "        return\n",
    "    \n",
    "class GMMConvertor(object):\n",
    "    \"\"\"\n",
    "    this class offers the several conversion techniques such as Maximum Likelihood Parameter Generation (MLPG)\n",
    "    and Minimum Mean Square Error (MMSE).\n",
    "    \n",
    "    Parametes\n",
    "    ---------\n",
    "    n_mix : int\n",
    "        the number of mixture components of the GMM\n",
    "    covtype : str\n",
    "        the type of covariance matrix of the GMM\n",
    "        'full': full-covariance matrix\n",
    "    gmmmode : str\n",
    "        the type of the GMM for opening\n",
    "        `None` : Normal Joint Density - GMM (JD-GMM)\n",
    "    \n",
    "    Attributes\n",
    "    ---------\n",
    "    param : \n",
    "        sklearn-based model parameters of the GMM\n",
    "    w : shape(`n_mix`)\n",
    "        vector of mixture component weight of the GMM\n",
    "    jmean : shape(`n_mix`, `jnt.shape[0]`)\n",
    "        Array of joint mean vector of the GMM\n",
    "    jcov : shape(`n_mix`, `jnt.shape[0]`, `jnt.shape[0]`)\n",
    "        array of joint covariance matrix of the GMM\n",
    "    \"\"\"\n",
    "    \n",
    "    def __init__(self, n_mix=64, covtype='full', gmmmode=None):\n",
    "        self.n_mix = n_mix\n",
    "        self.covtype = covtype\n",
    "        self.gmmmode = gmmmode\n",
    "        \n",
    "    def open_from_param(self, param):\n",
    "        \"\"\"\n",
    "        open GMM from GMMTrainer\n",
    "        \n",
    "        Parameters\n",
    "        ----------\n",
    "        param : GMMTrainer\n",
    "            GMMTrainer class\n",
    "        \"\"\"\n",
    "        \n",
    "        self.param = param\n",
    "        self._deploy_parameters()\n",
    "        \n",
    "        return\n",
    "    \n",
    "    def convert(self, data, cvtype='mlpg'):\n",
    "        \"\"\"\n",
    "        convert data based on conditional probability density function\n",
    "        \n",
    "        Parametes\n",
    "        ---------\n",
    "        data : array, shape(`T`, `dim`)\n",
    "            original data will be converted\n",
    "        cvtype : str\n",
    "            type of conversion technique\n",
    "            `mlpg` : maximum likelihood parameter generation\n",
    "            \n",
    "        Returns\n",
    "        ----------\n",
    "        odata : array, shape(`T`, `dim`)\n",
    "            converted data\n",
    "        \"\"\"\n",
    "        \n",
    "        # estimate parameter sequence\n",
    "        cseq, wseq, mseq, covseq = self._gmmmap(data)\n",
    "        \n",
    "        if cvtype == 'mlpg':\n",
    "            odata = self._mlpg(mseq, covseq)\n",
    "        else:\n",
    "            raise ValueError('please choose conversion mode in `mlpg`.')\n",
    "        \n",
    "        return odata\n",
    "    \n",
    "    def _gmmmap(self, sddata):\n",
    "        # paramete for sequencial data\n",
    "        T, sddim = sddata.shape\n",
    "        \n",
    "        # estimate posterior sequence\n",
    "        wseq = self.pX.predict_proba(sddata)\n",
    "        \n",
    "        # estimate mixture sequence\n",
    "        cseq = np.argmax(wseq, axis=1)\n",
    "        \n",
    "        mseq = np.zeros((T, sddim))\n",
    "        covseq = np.zeros((T, sddim, sddim))\n",
    "        for t in range(T):\n",
    "            # read maximum likelihood mixture component in frame t\n",
    "            m = cseq[t]\n",
    "            \n",
    "            # conditional mean vector sequence\n",
    "            mseq[t] = self.meanY[m] + self.A[m] @ (sddata[t] - self.meanX[m])\n",
    "            \n",
    "            # conditional covariance sequence\n",
    "            covseq[t] = self.cond_cov_inv[m]\n",
    "        \n",
    "        return cseq, wseq, mseq, covseq\n",
    "    \n",
    "    def _mlpg(self, mseq, covseq):\n",
    "        # parameter for sequencial data\n",
    "        T, sddim = mseq.shape\n",
    "        \n",
    "        # prepare W\n",
    "        W = construct_static_and_delta_matrix(T, sddim // 2)\n",
    "        \n",
    "        # prepare D\n",
    "        D = get_diagonal_precision_matrix(T, sddim, covseq)\n",
    "        \n",
    "        # calculate W'D\n",
    "        WD = W.T @ D\n",
    "        \n",
    "        # W'DW\n",
    "        WDW = WD @ W\n",
    "        \n",
    "        # W'Dm\n",
    "        WDM = WD @ mseq.flatten()\n",
    "        \n",
    "        # estimate y = (W'DW)^-1 * W'Dm\n",
    "        odata = scipy.sparse.linalg.spsolve(WDW, WDM, use_umfpack=False).reshape(T, sddim // 2)\n",
    "        \n",
    "        return odata\n",
    "    \n",
    "    def _deploy_parameters(self):\n",
    "        # read JD-GMM parameters from self.param\n",
    "        self.W = self.param.weights_\n",
    "        self.jmean = self.param.means_\n",
    "        self.jcov = self.param.covars_\n",
    "        \n",
    "        # devide GMM parameters into source and target parameters\n",
    "        sddim = self.jmean.shape[1] // 2\n",
    "        self.meanX = self.jmean[:, 0:sddim]\n",
    "        self.meanY = self.jmean[:, sddim:]\n",
    "        self.covXX = self.jcov[:, :sddim, :sddim]\n",
    "        self.covXY = self.jcov[:, :sddim, sddim:]\n",
    "        self.covYX = self.jcov[:, sddim:, :sddim]\n",
    "        self.covYY = self.jcov[:, sddim:, sddim:]\n",
    "        \n",
    "        # change model parameter of GMM into that of gmmmode\n",
    "        if self.gmmmode is None:\n",
    "            pass\n",
    "        else:\n",
    "            raise ValueError('please choose GMM mode in [None]')\n",
    "            \n",
    "        # estimate parameters for conversion\n",
    "        self._set_Ab()\n",
    "        self._set_pX()\n",
    "        \n",
    "        return\n",
    "    \n",
    "    def _set_Ab(self):\n",
    "        # calculate A and b from self.jmean, self.jcov\n",
    "        sddim = self.jmean.shape[1] // 2\n",
    "        \n",
    "        # calculate inverse covariance for covariance XX in each mixture\n",
    "        self.covXXinv = np.zeros((self.n_mix, sddim, sddim))\n",
    "        for m in range(self.n_mix):\n",
    "            self.covXXinv[m] = np.linalg.inv(self.covXX[m])\n",
    "            \n",
    "        # calculate A, b, and conditional covariance given X\n",
    "        self.A = np.zeros((self.n_mix, sddim, sddim))\n",
    "        self.b = np.zeros((self.n_mix, sddim))\n",
    "        self.cond_cov_inv = np.zeros((self.n_mix, sddim, sddim))\n",
    "        for m in range(self.n_mix):\n",
    "            # calculate A (A = yxcov_m * xxcov_m^-1)\n",
    "            self.A[m] = self.covYX[m] @ self.covXXinv[m]\n",
    "            \n",
    "            # calculate b (b = mean^Y - A * mean^X)\n",
    "            self.b[m] = self.meanY[m] - self.A[m] @ self.meanX[m]\n",
    "            \n",
    "            # calculate conditional covariance (cov^(Y|X)^-1 = (yycov - A * xycov)^-1)\n",
    "            self.cond_cov_inv[m] = np.linalg.inv(self.covYY[m] - self.A[m] @ self.covXY[m])\n",
    "            \n",
    "        return\n",
    "    \n",
    "    def _set_pX(self):\n",
    "        # probability density function of X \n",
    "        self.pX = sklearn.mixture.GMM(n_components=self.n_mix, covariance_type=self.covtype)\n",
    "        self.pX.weights_ = self.W\n",
    "        self.pX.means_ = self.meanX\n",
    "        self.pX.covars_ = self.covXX\n",
    "        \n",
    "        # following function is required to estimate porsterior\n",
    "        # p(x | \\lambda^(X))\n",
    "        #self.pX.precisions_cholesky_ = _compute_precision_cholesky(self.covXX, self.covtype)\n",
    "        \n",
    "        return\n",
    "    \n",
    "def get_diagonal_precision_matrix(T, D, covseq):\n",
    "    return scipy.sparse.block_diag(covseq, format='csr')        "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "def get_alignment(odata, onpow, tdata, tnpow, opow=-20, tpow=-20, sd=0, cvdata=None, given_twf=None, otflag=None, distance='melcd'):\n",
    "    \"\"\"\n",
    "    get alignment between original and target.\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    odata : array, shape(`T`, `dim`)\n",
    "        acoustic feature vector of original\n",
    "    onpow : array, shape(`T`)\n",
    "        Normalized power vector of original\n",
    "    tdata : array, shape(`T`, `dim`)\n",
    "        acoustic feature vector of target\n",
    "    tnpow : array, shape(`T`)\n",
    "        Normalized power vector of target\n",
    "    opow : float\n",
    "        power threshold of original\n",
    "    tpow : float\n",
    "        power threshold of target\n",
    "    sd : int\n",
    "        start dimension to be used for alignment\n",
    "    cvdata : array, shape(`T`, `dim`)\n",
    "        converted original data\n",
    "    given_twf : array, shape(`T_new`, `dim * 2`)\n",
    "        Alignment given twf\n",
    "    otflag : str\n",
    "        Alignment into the length of specification\n",
    "        'org' : alignment into original length\n",
    "        'tar' : alignment into target length\n",
    "    distance : str\n",
    "        Distance function to be used\n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    jdata : array, shape(`T_new`, `dim * 2`)\n",
    "        joint static and delta feature vector\n",
    "    twf : array, shape(`T_new`, `dim * 2`)\n",
    "        Time warping function\n",
    "    mcd : float\n",
    "        Mel-cepstrum distortion between arrays\n",
    "    \"\"\"\n",
    "    \n",
    "    oexdata = extsddata(odata[:, sd:], onpow, power_threshold=opow)\n",
    "    texdata = extsddata(tdata[:, sd:], tnpow, power_threshold=tpow)\n",
    "    \n",
    "    if cvdata is None:\n",
    "        align_odata = oexdata\n",
    "    else:\n",
    "        cvexdata = extsddata(cvdata, onpow, power_threshold=opow)\n",
    "        align_odata = cvexdata\n",
    "    \n",
    "    if given_twf is None: \n",
    "        twf = estimate_twf(align_odata, texdata, distance=distance, fast=False, otflag=otflag)\n",
    "    else:\n",
    "        twf = given_twf\n",
    "    \n",
    "    jdata = align_data(oexdata, texdata, twf)\n",
    "    mcd = melcd(align_odata[twf[0]], texdata[twf[1]])\n",
    "    \n",
    "    return jdata, twf, mcd\n",
    "\n",
    "def align_feature_vectors(odata, onpows, tdata, tnpows, opow=-100, tpow=-100, itnum=3, sd=0, given_twfs=None, otflag=None):\n",
    "    \"\"\"\n",
    "    get alignment to create joint feature vector\n",
    "    \n",
    "    Parameters\n",
    "    ----------\n",
    "    odata : list, (`num_files`)\n",
    "        List of original feature vectors\n",
    "    onpow : list, (`num_files`)\n",
    "        List of original npows\n",
    "    tdata : list, (`num_files`)\n",
    "        List of target feature vectors\n",
    "    tnpow : list, (`num_files`)\n",
    "        List of target npows\n",
    "    opow : float\n",
    "        power threshold of original\n",
    "    tpow : float\n",
    "        power threshold of target\n",
    "    itnum : int\n",
    "        the number of iteration\n",
    "    sd : int\n",
    "        start dimension of feature vector to be used for alignment\n",
    "    given_twf : array, shape(`T_new`, `dim * 2`)\n",
    "        use given alignment while 1st iteration\n",
    "    otflag : str\n",
    "        Alignment into the length of specification\n",
    "        'org' : alignment into original length\n",
    "        'tar' : alignment into target length\n",
    "    distance : str\n",
    "        Distance function to be used\n",
    "    \n",
    "    Returns\n",
    "    ----------\n",
    "    jdata : array, shape(`T_new`, `dim * 2`)\n",
    "        joint static and delta feature vector\n",
    "    twf : array, shape(`T_new`, `dim * 2`)\n",
    "        Time warping function\n",
    "    mcd : float\n",
    "        Mel-cepstrum distortion between arrays\n",
    "    \"\"\"\n",
    "    \n",
    "    it = 1\n",
    "    num_files = len(odata)\n",
    "    cvgmm, cvdata = None, None\n",
    "    for it in range(1, itnum+1):\n",
    "        print('{}-th joint feature extraction starts.'.format(it))\n",
    "        \n",
    "        # alignment\n",
    "        twfs, jfvs = [], []\n",
    "        for i in range(num_files):\n",
    "            if it == 1 and given_twfs is not None:\n",
    "                gtwf = given_twfs[i]\n",
    "            else:\n",
    "                gtwf = None\n",
    "            \n",
    "            if it > 1:\n",
    "                cvdata = cvgmm.convert(static_delta(odata[i][:, sd:]))\n",
    "            \n",
    "            jdata, twf, mcd = get_alignment(odata[i], onpows[i], tdata[i], tnpows[i], opow=opow, tpow=tpow,\n",
    "                                            sd=sd, cvdata=cvdata, given_twf=gtwf, otflag=otflag)\n",
    "            twfs.append(twf)\n",
    "            jfvs.append(jdata)\n",
    "            print('distortion [dB] for {}-th file: {}'.format(i+1, mcd))\n",
    "            \n",
    "        jnt_data = transform_jnt(jfvs)\n",
    "        \n",
    "        if it != itnum:\n",
    "            # train GMM, if not final iteration\n",
    "            datagmm = GMMTrainer()\n",
    "            datagmm.train(jnt_data)\n",
    "            cvgmm = GMMConvertor()\n",
    "            cvgmm.open_from_param(datagmm.param)\n",
    "        it += 1\n",
    "    return jfvs, twfs    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# 2. estimate twf and jnt\n",
    "if os.path.exists(prepare_path + \"_jnt_mcep_0_.pickle\"):\n",
    "    pass\n",
    "else:\n",
    "    for i in range(0, len(mid_mceplist), len(org_mceplist)):\n",
    "        org_mceps = org_mceplist\n",
    "        org_npows = org_npowlist\n",
    "        mid_mceps = mid_mceplist[i:i+len(org_mceps)]\n",
    "        mid_npows = mid_npowlist[i:i+len(org_npows)]\n",
    "        assert len(org_mceps) == len(mid_mceps)\n",
    "        assert len(org_npows) == len(mid_npows)\n",
    "        assert len(org_mceps) == len(org_npows)\n",
    "\n",
    "        # dtw between original and target 0-th and silence\n",
    "        print(\"## alignment mcep 0-th and silence ##\")\n",
    "        jmceps, twfs = align_feature_vectors(org_mceps, org_npows, mid_mceps, mid_npows, opow=-15, tpow=-15, sd=1)\n",
    "        jnt_mcep = transform_jnt(jmceps)\n",
    "\n",
    "        # save joint feature vectors\n",
    "        with open(prepare_path + \"_jnt_mcep_{}_.pickle\".format(i), 'wb') as f:   \n",
    "            print(f)\n",
    "            pickle.dump(jnt_mcep, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<_io.BufferedReader name='./utterance/pre-stored-ej/output/initgmm.pickle'>\n"
     ]
    }
   ],
   "source": [
    "# 3. make EV-GMM\n",
    "initgmm, initgmm_codeap = None, None\n",
    "if os.path.exists(prepare_path + \"initgmm.pickle\"):\n",
    "    with open(prepare_path + \"initgmm.pickle\".format(i), 'rb') as f:   \n",
    "        print(f)\n",
    "        initgmm = pickle.load(f)\n",
    "else:\n",
    "    jnt, jnt_codeap = None, []\n",
    "    for i in range(0, len(mid_mceplist), len(org_mceplist)):\n",
    "        with open(prepare_path + \"_jnt_mcep_{}_.pickle\".format(i), 'rb') as f:  \n",
    "            temp_jnt = pickle.load(f)\n",
    "            if jnt is None:\n",
    "                jnt = temp_jnt\n",
    "            else:\n",
    "                jnt = np.r_[jnt, temp_jnt]\n",
    "\n",
    "    # train initial gmm\n",
    "    initgmm = GMMTrainer()\n",
    "    initgmm.train(jnt)\n",
    "\n",
    "    with open(prepare_path + \"initgmm.pickle\", 'wb') as f:   \n",
    "        print(f)\n",
    "        pickle.dump(initgmm, f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# get initial gmm params\n",
    "init_W = initgmm.param.weights_\n",
    "init_jmean = initgmm.param.means_\n",
    "init_jcov = initgmm.param.covars_\n",
    "sddim = init_jmean.shape[1] // 2\n",
    "init_meanX = init_jmean[:, :sddim]\n",
    "init_meanY = init_jmean[:, sddim:]\n",
    "init_covXX = init_jcov[:, :sddim, :sddim]\n",
    "init_covXY = init_jcov[:, :sddim, sddim:]\n",
    "init_covYX = init_jcov[:, sddim:, :sddim]\n",
    "init_covYY = init_jcov[:, sddim:, sddim:]\n",
    "fitted_source = init_meanX\n",
    "fitted_target = init_meanY\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "sv = None\n",
    "if os.path.exists(prepare_path + \"_sv.npy\"):\n",
    "    sv = np.array(sv)\n",
    "    sv = np.load(prepare_path + '_sv.npy')\n",
    "else:\n",
    "    depengmm, depenjnt = None, None\n",
    "    sv = []\n",
    "    for i in range(0, len(mid_mceplist), len(org_mceplist)):\n",
    "        with open(prepare_path + \"_jnt_mcep_{}_.pickle\".format(i), 'rb') as f:  \n",
    "            depenjnt = pickle.load(f)\n",
    "            depengmm = GMMTrainer(params='m')\n",
    "            depengmm.param.weights_ = init_W\n",
    "            depengmm.param.means_ = init_jmean\n",
    "            depengmm.param.covars_ = init_jcov\n",
    "            depengmm.train(depenjnt)\n",
    "            sv.append(depengmm.param.means_)\n",
    "    sv = np.array(sv)\n",
    "    np.save(prepare_path + \"_sv\", sv)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_mix = 64\n",
    "S = int(len(mid_mceplist) / len(org_mceplist))\n",
    "assert S == 22\n",
    "\n",
    "source_pca = sklearn.decomposition.PCA()\n",
    "source_pca.fit(sv[:,:,:sddim].reshape((S, n_mix*sddim)))\n",
    "\n",
    "target_pca = sklearn.decomposition.PCA()\n",
    "target_pca.fit(sv[:,:,sddim:].reshape((S, n_mix*sddim)))\n",
    "\n",
    "eigenvectors = source_pca.components_.reshape((n_mix, sddim, S)), target_pca.components_.reshape((n_mix, sddim, S)) \n",
    "biasvectors = source_pca.mean_.reshape((n_mix, sddim)), target_pca.mean_.reshape((n_mix, sddim))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A11.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A14.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A17.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A18.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A19.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A20.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A21.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A22.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A23.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A24.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A25.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A26.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A27.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A28.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A29.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A30.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A31.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A32.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A33.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A34.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A35.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A36.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A37.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A38.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A39.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A40.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A41.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A42.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A43.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A44.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A45.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A46.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A47.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A48.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A49.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A50.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A51.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A52.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A53.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A54.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A55.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A56.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A57.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A58.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/input/EJM10/V01/T01/TIMIT/000/A59.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/ATR503/A/A01.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/ATR503/A/A02.wav\n"
     ]
    }
   ],
   "source": [
    "# estimate statistic features\n",
    "for_convert_source = __same_path + 'input/EJM10/V01/T01/TIMIT/000/*.wav'\n",
    "for_convert_target = __same_path + 'adaptation/EJM04/V01/T01/ATR503/A/*.wav'\n",
    "\n",
    "src_f0list = []\n",
    "src_splist = []\n",
    "src_mceplist = []\n",
    "src_aplist = []\n",
    "src_npowlist = []\n",
    "src_codeaplist = []\n",
    "ite = 0\n",
    "if os.path.exists(__same_path + 'input/EJM10/V01/T01/TIMIT/000/A11.wav'):\n",
    "    for files in sorted(glob.iglob(for_convert_source, recursive=True)):\n",
    "        wavf = files\n",
    "        x, fs = sf.read(wavf)\n",
    "        x = np.array(x, dtype=np.float)\n",
    "        x = low_cut_filter(x, fs, cutoff=70)\n",
    "        assert fs == 16000\n",
    "\n",
    "        print(\"extract acoustic featuers: \" + wavf)\n",
    "\n",
    "        f0, sp, ap = feat.analyze(x)\n",
    "        mcep = feat.mcep()\n",
    "        npow = feat.npow()\n",
    "        codeap = feat.codeap()\n",
    "        wav = synthesizer.synthesis_sp(f0, sp, ap)\n",
    "        wav = np.clip(wav, -32768, 32767)\n",
    "        sf.write(output_path + \"input_ansys_{}_.wav\".format(ite), wav, fs)\n",
    "\n",
    "        src_f0list.append(f0)\n",
    "        src_splist.append(sp)\n",
    "        src_mceplist.append(mcep)\n",
    "        src_aplist.append(ap)\n",
    "        src_npowlist.append(npow)\n",
    "        src_codeaplist.append(codeap)\n",
    "\n",
    "        wav = synthesizer.synthesis(f0, mcep, ap)\n",
    "        wav = np.clip(wav, -32768, 32767)\n",
    "        sf.write(output_path + \"input_mcep_{}_.wav\".format(ite), wav, fs)\n",
    "        ite = ite + 1\n",
    "\n",
    "else:\n",
    "    raise ValueError(\"No such files.\")\n",
    "tar_f0list = []\n",
    "tar_mceplist = []\n",
    "tar_aplist = []\n",
    "tar_npowlist = []\n",
    "tar_splist = []\n",
    "tar_codeaplist = []\n",
    "ite = 0\n",
    "\n",
    "if os.path.exists(__same_path + 'adaptation/EJM04/V01/T01/ATR503/A/A01.wav'):\n",
    "    for files in sorted(glob.iglob(for_convert_target, recursive=True)):\n",
    "        wavf = files\n",
    "        x, fs = sf.read(wavf)\n",
    "        x = np.array(x, dtype=np.float)\n",
    "        x = low_cut_filter(x, fs, cutoff=70)\n",
    "        assert fs == 16000\n",
    "\n",
    "        print(\"extract acoustic featuers: \" + wavf)\n",
    "\n",
    "        f0, sp, ap = feat.analyze(x)\n",
    "        mcep = feat.mcep()\n",
    "        npow = feat.npow()\n",
    "        codeap = feat.codeap()\n",
    "        name, ext = os.path.splitext(wavf)\n",
    "        wav = synthesizer.synthesis_sp(f0, sp, ap)\n",
    "        wav = np.clip(wav, -32768, 32767)\n",
    "        sf.write(output_path + \"target_ansys_{}_.wav\".format(ite), wav, fs)\n",
    "\n",
    "        tar_f0list.append(f0)\n",
    "        tar_splist.append(sp)\n",
    "        tar_mceplist.append(mcep)\n",
    "        tar_aplist.append(ap)\n",
    "        tar_npowlist.append(npow)\n",
    "        tar_codeaplist.append(codeap)\n",
    "\n",
    "        wav = synthesizer.synthesis(f0, mcep, ap)\n",
    "        wav = np.clip(wav, -32768, 32767)\n",
    "        sf.write(output_path + \"target_mcep_{}_.wav\".format(ite), wav, fs)\n",
    "        ite = ite + 1\n",
    "else:\n",
    "    raise ValueError(\"No such files.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "f0statis = F0statistics()\n",
    "tarf0stats = f0statis.estimate(tar_f0list)\n",
    "srcf0stats = f0statis.estimate(org_f0list)\n",
    "\n",
    "gv = GV()\n",
    "srcgvstats = gv.estimate(org_mceplist)\n",
    "targvstats = gv.estimate(tar_mceplist)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "adapt:  1 / 2\n",
      "epoch =  0\n",
      "epoch =  1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  16\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  17\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  18\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  19\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  20\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  21\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  22\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  23\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  24\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  25\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  26\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  27\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  28\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  29\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  30\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  31\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  32\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  33\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  34\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  35\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  36\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  37\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  38\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  39\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  40\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  41\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  42\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  43\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  44\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  45\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  46\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  47\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  48\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  49\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  50\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  51\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  52\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  53\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  54\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  55\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  56\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  57\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  58\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  59\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  60\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  61\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  62\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  63\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  64\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  65\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  66\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  67\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  68\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  69\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  70\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  71\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  72\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  73\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  74\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  75\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  76\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  77\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  78\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  79\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  80\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  81\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  82\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  83\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  84\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  85\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  86\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  87\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  88\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  89\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  90\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  91\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  92\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  93\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  94\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  95\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  96\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  97\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  98\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  99\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "adapt:  2 / 2\n",
      "epoch =  0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  1\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  2\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  3\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  4\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  5\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  6\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  7\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  8\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  9\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  10\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  11\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  12\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  13\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  14\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  15\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  16\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  17\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  18\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  19\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  20\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  21\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  22\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  23\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  24\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  25\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  26\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  27\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  28\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  29\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  30\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  31\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  32\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  33\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  34\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  35\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  36\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  37\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  38\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  39\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  40\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  41\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  42\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  43\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  44\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  45\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  46\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  47\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  48\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  49\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  50\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  51\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  52\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  53\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  54\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  55\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  56\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  57\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  58\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  59\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  60\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  61\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  62\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  63\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  64\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  65\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  66\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  67\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  68\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  69\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  70\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  71\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  72\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  73\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  74\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  75\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  76\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  77\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  78\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  79\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  80\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  81\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  82\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  83\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  84\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  85\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  86\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  87\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  88\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  89\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  90\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  91\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  92\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  93\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  94\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  95\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  96\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  97\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  98\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "epoch =  99\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "# 5. fitting target\n",
    "epoch = 100\n",
    "\n",
    "fitgmm = sklearn.mixture.GMM(n_components=n_mix,\n",
    "                             covariance_type='full',\n",
    "                             n_iter=100)\n",
    "fitgmm.weights_ = init_W\n",
    "fitgmm.means_ = init_meanY\n",
    "fitgmm.covars_ = init_covYY\n",
    "\n",
    "for i in range(len(tar_mceplist)):\n",
    "    print(\"adapt: \", i+1, \"/\", len(tar_mceplist))\n",
    "    target = tar_mceplist[i]\n",
    "    target_pow = target[:, 0]\n",
    "    target = target[:, 1:]\n",
    "    for x in range(epoch):\n",
    "        print(\"epoch = \", x)\n",
    "        predict = fitgmm.predict_proba(np.atleast_2d(static_delta(target)))\n",
    "        \n",
    "        y = np.sum([predict[:, k:k+1] * (static_delta(target) - biasvectors[1][k]) for k in range(n_mix)], axis=1)\n",
    "        gamma = np.sum(predict, axis=0)\n",
    "        \n",
    "        left = np.sum([gamma[k] * np.dot(eigenvectors[1][k].T,\n",
    "                                         np.linalg.solve(fitgmm.covars_, eigenvectors[1])[k])\n",
    "                                                        for k in range(n_mix)], axis=0)\n",
    "        right = np.sum([np.dot(eigenvectors[1][k].T,\n",
    "                               np.linalg.solve(fitgmm.covars_, y)[k])\n",
    "                        for k in range(n_mix)], axis=0)\n",
    "        weight = np.linalg.solve(left, right)\n",
    "        \n",
    "        fitted_target = np.dot(eigenvectors[1], weight) + biasvectors[1]\n",
    "        fitgmm.means_ = fitted_target"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "def mcepconvert(source, weights, jmean, meanX, covarXX, covarXY, covarYX, covarYY,\n",
    "                fitted_source, fitted_target):\n",
    "    \n",
    "    M = 64\n",
    "    # set pX\n",
    "    px = sklearn.mixture.GMM(n_components=M, covariance_type='full', n_iter=100)\n",
    "    px.weights_ = weights\n",
    "    px.means_ = meanX\n",
    "    px.covars_ = covarXX\n",
    "    \n",
    "    # set Ab\n",
    "    sddim = jmean.shape[1] // 2\n",
    "    covXXinv = np.zeros((M, sddim, sddim))\n",
    "    for m in range(M):\n",
    "        covXXinv[m] = np.linalg.inv(covarXX[m])\n",
    "    A = np.zeros((M, sddim, sddim))\n",
    "    b = np.zeros((M, sddim))\n",
    "    cond_cov_inv = np.zeros((M, sddim, sddim))\n",
    "    for m in range(M):\n",
    "        A[m] = covarYX[m] @ covXXinv[m]\n",
    "        b[m] = fitted_target[m] - A[m] @ meanX[m]\n",
    "        cond_cov_inv[m] = np.linalg.inv(covarYY[m] - A[m] @ covarXY[m])\n",
    "        \n",
    "    # _gmmmap\n",
    "    T, sddim = source.shape\n",
    "    wseq = px.predict_proba(source)\n",
    "    cseq = np.argmax(wseq, axis=1)\n",
    "    mseq = np.zeros((T, sddim))\n",
    "    covseq = np.zeros((T, sddim, sddim))\n",
    "    for t in range(T):\n",
    "        m = cseq[t]\n",
    "        mseq[t] = fitted_target[m] + A[m] @ (source[t] - meanX[m])\n",
    "        covseq[t] = cond_cov_inv[m]\n",
    "        \n",
    "    # _mlpg\n",
    "    T, sddim = mseq.shape\n",
    "    W = construct_static_and_delta_matrix(T, sddim // 2)\n",
    "    D = get_diagonal_precision_matrix(T, sddim, covseq)\n",
    "    WD = W.T @ D\n",
    "    WDW = WD @ W\n",
    "    WDM = WD @ mseq.flatten()\n",
    "    \n",
    "    output = scipy.sparse.linalg.spsolve(WDW, WDM, use_umfpack=False).reshape(T, sddim // 2)\n",
    "    return output"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:57: DeprecationWarning: Class GMM is deprecated; The class GMM is deprecated in 0.18 and will be  removed in 0.20. Use class GaussianMixture instead.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n",
      "/home/higa/anaconda3/lib/python3.6/site-packages/sklearn/utils/deprecation.py:75: DeprecationWarning: Function log_multivariate_normal_density is deprecated; The function log_multivariate_normal_density is deprecated in 0.18 and will be removed in 0.20.\n",
      "  warnings.warn(msg, category=DeprecationWarning)\n"
     ]
    }
   ],
   "source": [
    "# learn cvgvstats \n",
    "cv_mceps = []\n",
    "for i in range(len(src_mceplist)):\n",
    "    temp_mcep = src_mceplist[i]\n",
    "    temp_mcep_0th = temp_mcep[:, 0]\n",
    "    temp_mcep = temp_mcep[:, 1:]\n",
    "    sta_mcep = static_delta(temp_mcep)\n",
    "    cvmcep_wopow = np.array(mcepconvert(sta_mcep, init_W, init_jmean, init_meanX,\n",
    "                                        init_covXX, init_covXY, init_covYX, init_covYY,\n",
    "                                        fitted_source, fitted_target))\n",
    "    cvmcep = np.c_[temp_mcep_0th, cvmcep_wopow]\n",
    "    cv_mceps.append(cvmcep)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "cvgvstats = gv.estimate(cv_mceps)\n",
    "\n",
    "for i in range(len(src_mceplist)):\n",
    "    cvmcep_wGV = gv.postfilter(cv_mceps[i], targvstats, cvgvstats=cvgvstats)\n",
    "    cvf0 = f0statis.convert(src_f0list[i], srcf0stats, tarf0stats)\n",
    "    wav = synthesizer.synthesis(cvf0, cvmcep_wGV, src_aplist[i], rmcep=src_mceplist[i])\n",
    "    sf.write(output_path + \"cv_{}_.wav\".format(i), wav, 16000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "for i in range(len(src_mceplist)):\n",
    "    wav = synthesizer.synthesis(src_f0list[i], src_mceplist[i], src_aplist[i])\n",
    "    sf.write(output_path + \"mcep_{}_.wav\".format(i), wav, 16000)\n",
    "    wav = synthesizer.synthesis_sp(src_f0list[i], src_splist[i], src_aplist[i])\n",
    "    sf.write(output_path + \"ansys_{}_.wav\".format(i), wav, 16000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7fc73486a828>]"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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GYRDo5seeEwfYuXsnFtOpQ3UdhsH4WE9a2h2Mj/HEl3LS0yuwGw7KGiuI8Ajt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\niIiIyOIYjBIREREREZHF/f+uf2vfsAKTxgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fc7336eea20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cvf0 = f0statis.convert(src_f0list[0], srcf0stats, tarf0stats)\n",
    "plt.plot(cvf0)\n",
    "plt.plot(src_f0list[0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [],
   "source": [
    "cvmcep_wGV = gv.postfilter(cv_mceps[0], srcgvstats, cvgvstats=cvgvstats)\n",
    "cvf0 = f0statis.convert(src_f0list[0], srcf0stats, tarf0stats)\n",
    "wav = synthesizer.synthesis(cvf0, cvmcep_wGV, src_aplist[0], rmcep=src_mceplist[0])\n",
    "sf.write(output_path + \"te.wav\", wav, 16000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A11.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A14.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A17.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A18.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A19.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A20.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A21.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A22.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A23.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A24.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A25.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A26.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A27.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A28.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A29.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A30.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A31.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A32.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A33.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A34.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A35.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A36.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A37.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A38.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A39.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A40.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A41.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A42.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A43.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A44.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A45.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A46.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A47.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A48.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A49.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A50.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A51.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A52.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A53.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A54.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A55.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A56.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A57.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A58.wav\n",
      "extract acoustic featuers: ./utterance/pre-stored-ej/adaptation/EJM04/V01/T01/TIMIT/000/A59.wav\n"
     ]
    }
   ],
   "source": [
    "# org-cv distance\n",
    "with open(output_path + \"melcd_org-cv.txt\", \"w\") as outfile:\n",
    "    outfile.write(\"adapt2 org-cv mcd.\\n\")\n",
    "    for i in range(len(src_mceplist)):\n",
    "        temp_mcep = src_mceplist[i]\n",
    "        temp_mcep_0th = temp_mcep[:, 0]\n",
    "        temp_mcep = temp_mcep[:, 1:]\n",
    "        \n",
    "        temp_cv = cv_mceps[i]\n",
    "        temp_cv_0th = temp_cv[:, 0]\n",
    "        temp_cv = temp_cv[:, 1:]\n",
    "        \n",
    "        _, _, mcd = get_alignment(temp_mcep, temp_mcep_0th, temp_cv, temp_cv_0th, opow=-15, tpow=-15, sd=1)\n",
    "        outfile.write(\"{0},{1}\\n\".format(i, mcd))\n",
    "\n",
    "# cv-target distance\n",
    "# read target files and analyze mceps\n",
    "targets_mceplist = []\n",
    "targets_list = __same_path + 'adaptation/EJM04/V01/T01/TIMIT/000/*.wav'\n",
    "for files in sorted(glob.iglob(targets_list, recursive=True)):\n",
    "    wavf = files\n",
    "    x, fs = sf.read(wavf)\n",
    "    x = np.array(x, dtype=np.float)\n",
    "    x = low_cut_filter(x, fs, cutoff=70)\n",
    "    assert fs == 16000\n",
    "    print(\"extract acoustic featuers: \" + wavf)\n",
    "\n",
    "    f0, sp, ap = feat.analyze(x)\n",
    "    mcep = feat.mcep()\n",
    "    targets_mceplist.append(mcep)\n",
    "\n",
    "with open(output_path + \"melcd_cv-target.txt\", \"w\") as outfile:\n",
    "    outfile.write(\"adapt2 cv-target mcd.\\n\")\n",
    "    \n",
    "    for i in range(len(src_mceplist)):\n",
    "        temp_mcep = targets_mceplist[i]\n",
    "        temp_mcep_0th = temp_mcep[:, 0]\n",
    "        temp_mcep = temp_mcep[:, 1:]\n",
    "        \n",
    "        temp_cv = cv_mceps[i]\n",
    "        temp_cv_0th = temp_cv[:, 0]\n",
    "        temp_cv = temp_cv[:, 1:]\n",
    "        \n",
    "        _, _, mcd = get_alignment(temp_cv, temp_cv_0th, temp_mcep, temp_mcep_0th, opow=-15, tpow=-15, sd=1)\n",
    "        outfile.write(\"{0},{1}\\n\".format(i, mcd))\n",
    "\n",
    "# org-target distance\n",
    "with open(output_path + \"melcd_org-target.txt\", \"w\") as outfile:\n",
    "    outfile.write(\"adapt2 org-target mcd.\\n\")\n",
    "    \n",
    "    for i in range(len(src_mceplist)):\n",
    "\n",
    "        temp_mcep = src_mceplist[i]\n",
    "        temp_mcep_0th = temp_mcep[:, 0]\n",
    "        temp_mcep = temp_mcep[:, 1:]\n",
    "        \n",
    "        temp_mcep2 = targets_mceplist[i]\n",
    "        temp_mcep2_0th = temp_mcep2[:, 0]\n",
    "        temp_mcep2 = temp_mcep2[:, 1:]\n",
    "        \n",
    "        \n",
    "        _, _, mcd = get_alignment(temp_mcep, temp_mcep_0th, temp_mcep2, temp_mcep2_0th, opow=-15, tpow=-15, sd=1)\n",
    "        outfile.write(\"{0},{1}\\n\".format(i, mcd))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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