changeset 1:6936f4215473

Add function to extract chroma for a given file

--- a/Vamp.ipynb	Sat Jul 11 09:38:10 2015 +0100
+++ b/Vamp.ipynb	Sat Jul 11 10:08:49 2015 +0100
@@ -193,18 +193,18 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 31,
    "metadata": {
     "collapsed": false
    },
    "outputs": [],
    "source": [
-    "data, rate = librosa.load(\"data/Music/piano-scale.wav\", 44100)"
+    "data, rate = librosa.load(\"data/Music/piano-scale.wav\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 32,
    "metadata": {
     "collapsed": false
    },
@@ -212,10 +212,10 @@
     {
      "data": {
       "text/plain": [
-       "44100"
+       "22050"
       ]
      },
-     "execution_count": 9,
+     "execution_count": 32,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -226,7 +226,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 37,
    "metadata": {
     "collapsed": false
    },
@@ -237,7 +237,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 38,
    "metadata": {
     "collapsed": false
    },
@@ -245,23 +245,334 @@
     {
      "data": {
       "text/plain": [
-       "{'matrix': ( 0.046439909,\n",
-       "  array([[ 0.        ,  0.23465359,  0.        , ...,  0.08958804,\n",
-       "           1.2546041 ,  0.28356144],\n",
-       "         [ 0.        ,  0.39042693,  0.00177656, ...,  0.09287024,\n",
-       "           1.21442342,  0.1496222 ],\n",
-       "         [ 0.        ,  0.52906221,  0.00219605, ...,  0.05372851,\n",
-       "           1.21060038,  0.06183077],\n",
-       "         ..., \n",
-       "         [ 1.29977727,  0.        ,  0.16230981, ...,  0.37326023,\n",
-       "           0.11922166,  0.38857883],\n",
-       "         [ 0.44108227,  0.0647972 ,  0.77132535, ...,  0.23604083,\n",
-       "           0.10995618,  0.39924181],\n",
-       "         [ 0.02858954,  0.54281044,  0.70990545, ...,  0.17574874,\n",
-       "           0.15729675,  0.1570534 ]], dtype=float32))}"
+       "{'matrix': ( 0.092879819,\n",
+       "  array([[  0.00000000e+00,   4.24873501e-01,   3.82973906e-03,\n",
+       "            3.82216311e+00,   2.37860933e-01,   3.82100488e-03,\n",
+       "            1.09032551e-02,   9.76738632e-01,   6.12066567e-01,\n",
+       "            0.00000000e+00,   1.22131228e+00,   1.42185569e-01],\n",
+       "         [  0.00000000e+00,   4.36535776e-01,   4.17109299e-03,\n",
+       "            3.84424448e+00,   2.35603973e-01,   5.66468760e-03,\n",
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+       "            3.02644782e-02,   1.14490044e+00,   8.25596377e-02],\n",
+       "         [  0.00000000e+00,   3.06452692e-01,   3.86287877e-03,\n",
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+       "            6.77153990e-02,   8.36059451e-01,   6.06808305e-01,\n",
+       "            4.31316085e-02,   1.03214538e+00,   6.54669628e-02],\n",
+       "         [  2.66693324e-01,   1.95837468e-01,   1.98197402e-02,\n",
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+       "            1.07280768e-01,   7.31590986e-01,   1.95100978e-01,\n",
+       "            4.64988917e-01,   8.68599772e-01,   0.00000000e+00],\n",
+       "         [  1.01754165e+00,   2.75092362e-03,   0.00000000e+00,\n",
+       "            3.51279712e+00,   0.00000000e+00,   1.89969325e+00,\n",
+       "            1.77711189e-01,   5.13349175e-01,   1.00919195e-01,\n",
+       "            8.15969646e-01,   7.14922309e-01,   6.61320984e-02],\n",
+       "         [  9.82037961e-01,   8.05798918e-03,   0.00000000e+00,\n",
+       "            2.88393307e+00,   0.00000000e+00,   3.11278105e+00,\n",
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+       "            7.14564979e-01,   6.82311237e-01,   4.24766727e-02],\n",
+       "         [  9.42771196e-01,   2.54417956e-02,   0.00000000e+00,\n",
+       "            2.20816970e+00,   2.43749879e-02,   3.53431177e+00,\n",
+       "            2.98038125e-01,   2.00033054e-01,   3.14612798e-02,\n",
+       "            7.05746114e-01,   7.16595888e-01,   2.91427616e-02],\n",
+       "         [  9.13952529e-01,   0.00000000e+00,   0.00000000e+00,\n",
+       "            1.38729703e+00,   1.93949789e-02,   3.77868199e+00,\n",
+       "            2.35254109e-01,   1.48042396e-01,   1.09868713e-01,\n",
+       "            6.86089218e-01,   7.06140637e-01,   4.52662595e-02],\n",
+       "         [  7.64736056e-01,   0.00000000e+00,   0.00000000e+00,\n",
+       "            6.71625733e-01,   8.09735712e-03,   3.80770350e+00,\n",
+       "            1.18212968e-01,   1.45027727e-01,   1.41448304e-01,\n",
+       "            6.66033328e-01,   5.67650497e-01,   9.16916120e-04],\n",
+       "         [  3.80303353e-01,   7.37963186e-04,   8.07330489e-01,\n",
+       "            5.79400035e-03,   3.51414527e-03,   3.65109038e+00,\n",
+       "            1.32572628e-03,   1.70198345e+00,   4.49084640e-01,\n",
+       "            4.08069849e-01,   1.30995438e-01,   6.54952288e-01],\n",
+       "         [  6.44789517e-01,   1.91463605e-02,   1.01534832e+00,\n",
+       "            0.00000000e+00,   0.00000000e+00,   2.97579193e+00,\n",
+       "            0.00000000e+00,   2.95723677e+00,   2.57514745e-01,\n",
+       "            2.02719510e-01,   1.16316313e-02,   6.89639807e-01],\n",
+       "         [  6.48350954e-01,   3.55998091e-02,   9.91480291e-01,\n",
+       "            0.00000000e+00,   0.00000000e+00,   2.29414964e+00,\n",
+       "            1.80326179e-02,   3.42333341e+00,   1.88177288e-01,\n",
+       "            8.18119943e-02,   6.05384223e-02,   6.68154538e-01],\n",
+       "         [  7.30411291e-01,   3.45399342e-02,   1.05677223e+00,\n",
+       "            0.00000000e+00,   0.00000000e+00,   1.57214546e+00,\n",
+       "            3.68370973e-02,   3.63492155e+00,   1.83993116e-01,\n",
+       "            3.87695432e-02,   1.11736432e-01,   5.91368675e-01],\n",
+       "         [  6.96059704e-01,   6.38074502e-02,   9.83329117e-01,\n",
+       "            0.00000000e+00,   0.00000000e+00,   8.04103613e-01,\n",
+       "            3.10040992e-02,   3.68843269e+00,   4.68724109e-02,\n",
+       "            2.22536493e-02,   1.58476114e-01,   5.42322040e-01],\n",
+       "         [  4.15612608e-01,   2.48287967e-03,   7.15126038e-01,\n",
+       "            3.71358126e-01,   5.00436639e-03,   9.43841040e-02,\n",
+       "            4.15147632e-01,   3.73076868e+00,   5.02074718e-01,\n",
+       "            4.63929288e-02,   6.54523522e-02,   4.72613335e-01],\n",
+       "         [  6.50940478e-01,   1.97891891e-01,   1.75758898e-01,\n",
+       "            7.80113935e-01,   1.01064956e-02,   2.60821264e-02,\n",
+       "            4.72987115e-01,   2.77251506e+00,   1.90903246e+00,\n",
+       "            2.06915379e-01,   0.00000000e+00,   3.67915750e-01],\n",
+       "         [  7.99934924e-01,   3.07362080e-01,   1.15010314e-01,\n",
+       "            8.99490893e-01,   1.48295853e-02,   8.46333615e-03,\n",
+       "            4.64411795e-01,   1.90053177e+00,   2.61000252e+00,\n",
+       "            2.88172990e-01,   0.00000000e+00,   2.36573696e-01],\n",
+       "         [  8.44428301e-01,   5.05468726e-01,   1.13927245e-01,\n",
+       "            9.33207870e-01,   1.64283141e-02,   0.00000000e+00,\n",
+       "            3.93999994e-01,   1.32419717e+00,   2.98608017e+00,\n",
+       "            3.13605547e-01,   0.00000000e+00,   1.84952512e-01],\n",
+       "         [  7.61172056e-01,   7.23602951e-01,   1.17910549e-01,\n",
+       "            9.40936029e-01,   1.61284488e-02,   3.09127439e-02,\n",
+       "            2.97983408e-01,   8.62208724e-01,   3.22435474e+00,\n",
+       "            3.17345232e-01,   0.00000000e+00,   1.76184997e-01],\n",
+       "         [  5.59902191e-01,   9.25085902e-01,   1.03963248e-01,\n",
+       "            7.39642918e-01,   1.54185295e-02,   9.29588228e-02,\n",
+       "            1.31079197e-01,   5.94005942e-01,   3.27664280e+00,\n",
+       "            3.20019364e-01,   0.00000000e+00,   1.49048850e-01],\n",
+       "         [  9.98012815e-03,   3.04493338e-01,   3.59348059e-01,\n",
+       "            3.42505455e-01,   2.27598958e-02,   6.62563622e-01,\n",
+       "            6.89255744e-02,   3.01592648e-01,   3.33566928e+00,\n",
+       "            2.44367942e-01,   1.81877553e+00,   4.25202042e-01],\n",
+       "         [  0.00000000e+00,   2.79533565e-01,   5.98313987e-01,\n",
+       "            3.02214503e-01,   9.61515456e-02,   5.53717315e-01,\n",
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+       "            2.47154966e-01,   2.86118412e+00,   3.72229487e-01],\n",
+       "         [  0.00000000e+00,   3.05589288e-01,   6.22585654e-01,\n",
+       "            4.16841567e-01,   1.27011865e-01,   5.69701195e-01,\n",
+       "            5.27800582e-02,   0.00000000e+00,   1.87105262e+00,\n",
+       "            2.62221664e-01,   3.22219300e+00,   3.65786016e-01],\n",
+       "         [  0.00000000e+00,   3.15743983e-01,   5.84133804e-01,\n",
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+       "            2.95144320e-01,   3.35175133e+00,   3.35543007e-01],\n",
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+       "            3.39275956e-01,   3.32334256e+00,   3.23462993e-01],\n",
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+       "            2.71238238e-01,   2.34777525e-01,   2.68530667e-01,\n",
+       "            6.25236407e-02,   5.55525362e-01,   8.76341909e-02,\n",
+       "            3.85676146e-01,   3.50803518e+00,   1.15921743e-01],\n",
+       "         [  2.42944503e+00,   3.04761827e-01,   8.81233811e-03,\n",
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+       "            8.34576339e-02,   2.74303627e+00,   3.05163205e-01],\n",
+       "         [  2.93173909e+00,   3.84687483e-01,   0.00000000e+00,\n",
+       "            4.64963436e-01,   5.02562761e-01,   4.40405488e-01,\n",
+       "            9.35601220e-02,   5.99855423e-01,   4.21835780e-02,\n",
+       "            0.00000000e+00,   2.04308939e+00,   2.29302019e-01],\n",
+       "         [  3.11064768e+00,   3.45037937e-01,   0.00000000e+00,\n",
+       "            4.35747802e-01,   4.46496189e-01,   5.86265385e-01,\n",
+       "            1.94994181e-01,   6.88387334e-01,   5.12880310e-02,\n",
+       "            3.41151655e-02,   1.47539294e+00,   2.95632571e-01],\n",
+       "         [  3.14660192e+00,   3.45851243e-01,   0.00000000e+00,\n",
+       "            3.27035576e-01,   4.01277363e-01,   7.18494058e-01,\n",
+       "            2.06380174e-01,   7.44186819e-01,   5.21671437e-02,\n",
+       "            5.66334948e-02,   1.05946422e+00,   3.08677495e-01],\n",
+       "         [  3.00832653e+00,   2.96511710e-01,   1.24191833e+00,\n",
+       "            2.05115601e-01,   3.92820239e-01,   7.02235103e-01,\n",
+       "            1.92615509e-01,   4.40490246e-01,   4.54012230e-02,\n",
+       "            3.43948811e-01,   5.45665383e-01,   2.23220333e-01],\n",
+       "         [  2.18439913e+00,   3.06441188e-01,   2.59478569e+00,\n",
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+       "            1.38910234e-01,   1.26261845e-01,   3.31344366e-01,\n",
+       "            4.56126213e-01,   4.39321369e-01,   5.79001158e-02],\n",
+       "         [  1.26191056e+00,   3.65221322e-01,   2.80965567e+00,\n",
+       "            2.22944766e-01,   3.95260006e-01,   2.24513635e-01,\n",
+       "            1.00694381e-01,   2.74981081e-01,   3.84240508e-01,\n",
+       "            3.87172937e-01,   4.74732280e-01,   1.76805705e-02],\n",
+       "         [  7.86665320e-01,   4.28954393e-01,   2.79063463e+00,\n",
+       "            7.49405324e-02,   4.68975574e-01,   8.31721872e-02,\n",
+       "            8.72962847e-02,   3.82763326e-01,   2.58825690e-01,\n",
+       "            4.56833392e-01,   6.89327657e-01,   5.52218931e-04],\n",
+       "         [  4.90005016e-01,   4.62761343e-01,   2.80114007e+00,\n",
+       "            1.18907534e-01,   5.40875375e-01,   1.64486691e-02,\n",
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+       "            5.03678620e-01,   7.10847795e-01,   0.00000000e+00],\n",
+       "         [  2.36238062e-01,   3.69124860e-01,   2.82183552e+00,\n",
+       "            1.80697158e-01,   6.88817382e-01,   1.39951361e-02,\n",
+       "            5.37864268e-01,   3.82996082e-01,   1.22262530e-01,\n",
+       "            4.25686419e-01,   6.97567821e-01,   7.95556381e-02],\n",
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+       "            9.64616984e-02,   6.56631172e-01,   7.67596722e-01],\n",
+       "         [  4.87397052e-02,   1.11710824e-01,   1.29404962e+00,\n",
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+       "            2.27738291e-01,   7.80090690e-02,   4.63864744e-01,\n",
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+       "            2.02242225e-01,   6.33005619e-01,   6.36139393e-01],\n",
+       "         [  0.00000000e+00,   1.59729302e-01,   5.63160956e-01,\n",
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+       "            1.67292710e-02,   6.44830540e-02,   3.82053375e-01,\n",
+       "            2.30036512e-01,   6.41077697e-01,   7.19606817e-01],\n",
+       "         [  1.01601861e-01,   1.35053426e-01,   4.94270504e-01,\n",
+       "            2.72599554e+00,   2.07036525e-01,   5.58281243e-01,\n",
+       "            1.79355443e-02,   1.60084516e-01,   4.13332999e-01,\n",
+       "            1.71134710e-01,   5.91188908e-01,   6.87856317e-01],\n",
+       "         [  6.55282319e-01,   8.25702786e-01,   3.65547568e-01,\n",
+       "            2.61289692e+00,   2.59670645e-01,   1.04963267e+00,\n",
+       "            4.81165834e-02,   3.15849423e-01,   1.72161579e-01,\n",
+       "            5.55535555e-02,   7.02293575e-01,   0.00000000e+00],\n",
+       "         [  4.07601535e-01,   6.87211990e-01,   1.23272218e-01,\n",
+       "            1.94597948e+00,   3.19280088e-01,   2.28375816e+00,\n",
+       "            1.15090497e-01,   2.34635770e-01,   2.20257968e-01,\n",
+       "            1.79057177e-02,   3.86087656e-01,   2.87233829e-01],\n",
+       "         [  3.40838343e-01,   7.37410903e-01,   6.19066618e-02,\n",
+       "            1.25022495e+00,   3.76976848e-01,   2.53835464e+00,\n",
+       "            1.14872441e-01,   3.07014585e-01,   7.35241473e-02,\n",
+       "            1.74420811e-02,   3.33599210e-01,   2.72628486e-01],\n",
+       "         [  3.40058148e-01,   7.83261955e-01,   1.24757998e-02,\n",
+       "            7.27869034e-01,   4.24460948e-01,   2.57241678e+00,\n",
+       "            1.85929120e-01,   3.75092894e-01,   1.09095741e-02,\n",
+       "            1.85117889e-02,   4.37867105e-01,   2.81926960e-01],\n",
+       "         [  3.99623871e-01,   8.03674221e-01,   0.00000000e+00,\n",
+       "            4.06002045e-01,   5.01794815e-01,   2.55927515e+00,\n",
+       "            2.29086712e-01,   4.14251059e-01,   1.00820372e-02,\n",
+       "            4.34694253e-02,   5.42886853e-01,   2.29092389e-01],\n",
+       "         [  2.21274644e-01,   8.54164898e-01,   1.96931660e-01,\n",
+       "            6.41752362e-01,   5.52872777e-01,   2.42982841e+00,\n",
+       "            2.90243834e-01,   1.04238832e+00,   8.71692784e-03,\n",
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+       "            7.16115117e-01,   1.33126259e-01,   1.84647813e-01],\n",
+       "         [  1.28237963e+00,   3.92461836e-01,   2.65830278e-01,\n",
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+       "            1.88410890e+00,   6.18165620e-02,   1.11190535e-01,\n",
+       "            7.35562921e-01,   1.46628782e-01,   2.16038465e-01],\n",
+       "         [  1.46619773e+00,   6.95142090e-01,   5.86333722e-02,\n",
+       "            1.41803074e+00,   3.91344428e-02,   7.88339317e-01,\n",
+       "            2.13004708e+00,   5.14635704e-02,   1.19873025e-01,\n",
+       "            6.36887312e-01,   1.01486251e-01,   1.36954829e-01],\n",
+       "         [  1.72535515e+00,   0.00000000e+00,   1.75226301e-01,\n",
+       "            1.46466148e+00,   1.00414872e-01,   4.09084558e-01,\n",
+       "            2.29177713e+00,   3.26842070e-02,   3.69000554e-01,\n",
+       "            1.16747692e-01,   1.46897867e-01,   1.32895947e-01]], dtype=float32))}"
       ]
      },
-     "execution_count": 11,
+     "execution_count": 38,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -272,7 +583,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 12,
+   "execution_count": 39,
    "metadata": {
     "collapsed": false
    },
@@ -283,7 +594,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 40,
    "metadata": {
     "collapsed": false
    },
@@ -291,18 +602,18 @@
     {
      "data": {
       "text/plain": [
-       "<matplotlib.image.AxesImage at 0x7fe7fbd4fcf8>"
+       "<matplotlib.image.AxesImage at 0x7fe7fbb9cbe0>"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 40,
      "metadata": {},
      "output_type": "execute_result"
     },
     {
      "data": {
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IMExpTgzdky8RVzkkfa41dvi9Zo9vHV3i+le3yZ47A1cSgZfsCNxQqjonfdir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\nWUIqUgI9X9MoGh4QIg9lSEnJ9Qnj8nS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4E7Am00eShiaDZY8r5CV9nyZ10pkrbptepraBLy5uo+xeeHzjaF571lXFVVfwvDth2T6h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\nhAAAAABJRU5ErkJggg==\n",
       "text/plain": [
-       "<matplotlib.figure.Figure at 0x7fe81c8958d0>"
+       "<matplotlib.figure.Figure at 0x7fe7fbc10fd0>"
       ]
      },
      "metadata": {},
@@ -315,7 +626,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 41,
    "metadata": {
     "collapsed": true
    },
@@ -326,7 +637,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 42,
    "metadata": {
     "collapsed": true
    },
@@ -337,7 +648,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 16,
+   "execution_count": 43,
    "metadata": {
     "collapsed": true
    },
@@ -348,7 +659,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 44,
    "metadata": {
     "collapsed": true
    },
@@ -359,7 +670,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 18,
+   "execution_count": 45,
    "metadata": {
     "collapsed": true
    },
@@ -370,6 +681,48 @@
   },
   {
    "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "import os"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 54,
+   "metadata": {
+    "collapsed": true
+   },
+   "outputs": [],
+   "source": [
+    "def extract_chroma(audiofile):\n",
+    "    data, rate = librosa.load(audiofile)\n",
+    "    out = vamp.collect(data, rate,\n",
+    "                       plugin_key = \"nnls-chroma:nnls-chroma\",\n",
+    "                       output = \"chroma\",\n",
+    "                       process_timestamp_method = vamp.vampyhost.SHIFT_DATA)\n",
+    "    step, chroma = out[\"matrix\"]\n",
+    "    out_file = open(os.path.splitext(audiofile)[0] + \"_chroma.csv\", \"w\")\n",
+    "    csv.writer(out_file).writerows(chroma)\n",
+    "    out_file.close()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 55,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "extract_chroma(\"data/Music/piano-scale.wav\")"
+   ]
+  },
+  {
+   "cell_type": "code",
    "execution_count": null,
    "metadata": {
     "collapsed": true