mirror of
https://github.com/curioustorvald/tsvm.git
synced 2026-03-12 06:01:50 +09:00
mp3 decoding but slow
This commit is contained in:
minjaesong
@@ -1,6 +1,11 @@
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package net.torvald.tsvm
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import com.oracle.truffle.regex.util.TruffleReadOnlyMap
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import javazoom.jl.decoder.LayerIIIDecoder.pretab
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import net.torvald.tsvm.peripheral.AudioAdapter
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import org.graalvm.polyglot.Value
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import kotlin.math.cos
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import kotlin.math.sign
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/**
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* Created by minjaesong on 2022-12-31.
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@@ -13,13 +18,13 @@ class AudioJSR223Delegate(private val vm: VM) {
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return a
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}
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private fun getPlayhead(playhead: Int) = getFirstSnd()?.playheads?.get(playhead)
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fun setPcmMode(playhead: Int) { getPlayhead(playhead)?.isPcmMode = true }
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fun isPcmMode(playhead: Int) = getPlayhead(playhead)?.isPcmMode == true
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fun setTrackerMode(playhead: Int) { getPlayhead(playhead)?.isPcmMode = false }
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fun isTrackerMode(playhead: Int) = getPlayhead(playhead)?.isPcmMode == false
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fun setMasterVolume(playhead: Int, volume: Int) { getPlayhead(playhead)?.apply {
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masterVolume = volume and 255
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audioDevice.setVolume(masterVolume / 255f)
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@@ -61,8 +66,8 @@ class AudioJSR223Delegate(private val vm: VM) {
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fun getPcmData(index: Int) = getFirstSnd()?.pcmBin?.get(index.toLong())
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fun setPcmQueueCapacityIndex(playhead: Int, index: Int) { getPlayhead(playhead)?.pcmQueueSizeIndex = index }
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fun getPcmQueueCapacityIndex(playhead: Int, index: Int) { getPlayhead(playhead)?.pcmQueueSizeIndex }
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fun getPcmQueueCapacity(playhead: Int, index: Int) { getPlayhead(playhead)?.getPcmQueueCapacity() }
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fun getPcmQueueCapacityIndex(playhead: Int) { getPlayhead(playhead)?.pcmQueueSizeIndex }
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fun getPcmQueueCapacity(playhead: Int) = getPlayhead(playhead)?.getPcmQueueCapacity()
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fun resetParams(playhead: Int) {
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getPlayhead(playhead)?.resetParams()
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@@ -71,4 +76,329 @@ class AudioJSR223Delegate(private val vm: VM) {
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fun purgeQueue(playhead: Int) {
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getPlayhead(playhead)?.purgeQueue()
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}
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private val synthNWin = Array(64) { i -> FloatArray(32) { j -> cos(((16 + i) * (2 * j + 1)) * (Math.PI / 64.0)).toFloat() } }
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private val synthDtbl = floatArrayOf(0.000000000f, -0.000015259f, -0.000015259f, -0.000015259f,
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-0.000015259f, -0.000015259f, -0.000015259f, -0.000030518f,
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-0.000030518f, -0.000030518f, -0.000030518f, -0.000045776f,
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-0.000045776f, -0.000061035f, -0.000061035f, -0.000076294f,
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-0.000076294f, -0.000091553f, -0.000106812f, -0.000106812f,
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-0.000122070f, -0.000137329f, -0.000152588f, -0.000167847f,
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-0.000198364f, -0.000213623f, -0.000244141f, -0.000259399f,
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-0.000289917f, -0.000320435f, -0.000366211f, -0.000396729f,
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-0.000442505f, -0.000473022f, -0.000534058f, -0.000579834f,
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-0.000625610f, -0.000686646f, -0.000747681f, -0.000808716f,
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-0.000885010f, -0.000961304f, -0.001037598f, -0.001113892f,
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-0.001205444f, -0.001296997f, -0.001388550f, -0.001480103f,
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-0.001586914f, -0.001693726f, -0.001785278f, -0.001907349f,
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-0.002014160f, -0.002120972f, -0.002243042f, -0.002349854f,
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-0.002456665f, -0.002578735f, -0.002685547f, -0.002792358f,
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-0.002899170f, -0.002990723f, -0.003082275f, -0.003173828f,
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0.003250122f, 0.003326416f, 0.003387451f, 0.003433228f,
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0.003463745f, 0.003479004f, 0.003479004f, 0.003463745f,
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0.003417969f, 0.003372192f, 0.003280640f, 0.003173828f,
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0.003051758f, 0.002883911f, 0.002700806f, 0.002487183f,
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0.002227783f, 0.001937866f, 0.001617432f, 0.001266479f,
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0.000869751f, 0.000442505f, -0.000030518f, -0.000549316f,
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-0.001098633f, -0.001693726f, -0.002334595f, -0.003005981f,
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-0.003723145f, -0.004486084f, -0.005294800f, -0.006118774f,
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-0.007003784f, -0.007919312f, -0.008865356f, -0.009841919f,
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-0.010848999f, -0.011886597f, -0.012939453f, -0.014022827f,
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-0.015121460f, -0.016235352f, -0.017349243f, -0.018463135f,
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-0.019577026f, -0.020690918f, -0.021789551f, -0.022857666f,
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-0.023910522f, -0.024932861f, -0.025909424f, -0.026840210f,
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-0.027725220f, -0.028533936f, -0.029281616f, -0.029937744f,
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-0.030532837f, -0.031005859f, -0.031387329f, -0.031661987f,
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-0.031814575f, -0.031845093f, -0.031738281f, -0.031478882f,
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0.031082153f, 0.030517578f, 0.029785156f, 0.028884888f,
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0.027801514f, 0.026535034f, 0.025085449f, 0.023422241f,
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0.021575928f, 0.019531250f, 0.017257690f, 0.014801025f,
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0.012115479f, 0.009231567f, 0.006134033f, 0.002822876f,
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-0.000686646f, -0.004394531f, -0.008316040f, -0.012420654f,
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-0.016708374f, -0.021179199f, -0.025817871f, -0.030609131f,
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-0.035552979f, -0.040634155f, -0.045837402f, -0.051132202f,
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-0.056533813f, -0.061996460f, -0.067520142f, -0.073059082f,
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-0.078628540f, -0.084182739f, -0.089706421f, -0.095169067f,
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-0.100540161f, -0.105819702f, -0.110946655f, -0.115921021f,
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-0.120697021f, -0.125259399f, -0.129562378f, -0.133590698f,
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-0.137298584f, -0.140670776f, -0.143676758f, -0.146255493f,
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-0.148422241f, -0.150115967f, -0.151306152f, -0.151962280f,
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-0.152069092f, -0.151596069f, -0.150497437f, -0.148773193f,
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-0.146362305f, -0.143264771f, -0.139450073f, -0.134887695f,
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-0.129577637f, -0.123474121f, -0.116577148f, -0.108856201f,
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0.100311279f, 0.090927124f, 0.080688477f, 0.069595337f,
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0.057617188f, 0.044784546f, 0.031082153f, 0.016510010f,
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0.001068115f, -0.015228271f, -0.032379150f, -0.050354004f,
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-0.069168091f, -0.088775635f, -0.109161377f, -0.130310059f,
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-0.152206421f, -0.174789429f, -0.198059082f, -0.221984863f,
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-0.246505737f, -0.271591187f, -0.297210693f, -0.323318481f,
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-0.349868774f, -0.376800537f, -0.404083252f, -0.431655884f,
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-0.459472656f, -0.487472534f, -0.515609741f, -0.543823242f,
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-0.572036743f, -0.600219727f, -0.628295898f, -0.656219482f,
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-0.683914185f, -0.711318970f, -0.738372803f, -0.765029907f,
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-0.791213989f, -0.816864014f, -0.841949463f, -0.866363525f,
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-0.890090942f, -0.913055420f, -0.935195923f, -0.956481934f,
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-0.976852417f, -0.996246338f, -1.014617920f, -1.031936646f,
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-1.048156738f, -1.063217163f, -1.077117920f, -1.089782715f,
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-1.101211548f, -1.111373901f, -1.120223999f, -1.127746582f,
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-1.133926392f, -1.138763428f, -1.142211914f, -1.144287109f,
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1.144989014f, 1.144287109f, 1.142211914f, 1.138763428f,
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1.133926392f, 1.127746582f, 1.120223999f, 1.111373901f,
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1.101211548f, 1.089782715f, 1.077117920f, 1.063217163f,
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1.048156738f, 1.031936646f, 1.014617920f, 0.996246338f,
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0.976852417f, 0.956481934f, 0.935195923f, 0.913055420f,
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0.890090942f, 0.866363525f, 0.841949463f, 0.816864014f,
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0.791213989f, 0.765029907f, 0.738372803f, 0.711318970f,
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0.683914185f, 0.656219482f, 0.628295898f, 0.600219727f,
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0.572036743f, 0.543823242f, 0.515609741f, 0.487472534f,
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0.459472656f, 0.431655884f, 0.404083252f, 0.376800537f,
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0.349868774f, 0.323318481f, 0.297210693f, 0.271591187f,
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0.246505737f, 0.221984863f, 0.198059082f, 0.174789429f,
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0.152206421f, 0.130310059f, 0.109161377f, 0.088775635f,
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0.069168091f, 0.050354004f, 0.032379150f, 0.015228271f,
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-0.001068115f, -0.016510010f, -0.031082153f, -0.044784546f,
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-0.057617188f, -0.069595337f, -0.080688477f, -0.090927124f,
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0.100311279f, 0.108856201f, 0.116577148f, 0.123474121f,
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0.129577637f, 0.134887695f, 0.139450073f, 0.143264771f,
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0.146362305f, 0.148773193f, 0.150497437f, 0.151596069f,
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0.152069092f, 0.151962280f, 0.151306152f, 0.150115967f,
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0.148422241f, 0.146255493f, 0.143676758f, 0.140670776f,
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0.137298584f, 0.133590698f, 0.129562378f, 0.125259399f,
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0.120697021f, 0.115921021f, 0.110946655f, 0.105819702f,
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0.100540161f, 0.095169067f, 0.089706421f, 0.084182739f,
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0.078628540f, 0.073059082f, 0.067520142f, 0.061996460f,
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0.056533813f, 0.051132202f, 0.045837402f, 0.040634155f,
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0.035552979f, 0.030609131f, 0.025817871f, 0.021179199f,
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0.016708374f, 0.012420654f, 0.008316040f, 0.004394531f,
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0.000686646f, -0.002822876f, -0.006134033f, -0.009231567f,
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-0.012115479f, -0.014801025f, -0.017257690f, -0.019531250f,
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-0.021575928f, -0.023422241f, -0.025085449f, -0.026535034f,
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-0.027801514f, -0.028884888f, -0.029785156f, -0.030517578f,
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0.031082153f, 0.031478882f, 0.031738281f, 0.031845093f,
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0.031814575f, 0.031661987f, 0.031387329f, 0.031005859f,
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0.030532837f, 0.029937744f, 0.029281616f, 0.028533936f,
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0.027725220f, 0.026840210f, 0.025909424f, 0.024932861f,
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0.023910522f, 0.022857666f, 0.021789551f, 0.020690918f,
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0.019577026f, 0.018463135f, 0.017349243f, 0.016235352f,
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0.015121460f, 0.014022827f, 0.012939453f, 0.011886597f,
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0.010848999f, 0.009841919f, 0.008865356f, 0.007919312f,
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0.007003784f, 0.006118774f, 0.005294800f, 0.004486084f,
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0.003723145f, 0.003005981f, 0.002334595f, 0.001693726f,
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0.001098633f, 0.000549316f, 0.000030518f, -0.000442505f,
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-0.000869751f, -0.001266479f, -0.001617432f, -0.001937866f,
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-0.002227783f, -0.002487183f, -0.002700806f, -0.002883911f,
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-0.003051758f, -0.003173828f, -0.003280640f, -0.003372192f,
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-0.003417969f, -0.003463745f, -0.003479004f, -0.003479004f,
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-0.003463745f, -0.003433228f, -0.003387451f, -0.003326416f,
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0.003250122f, 0.003173828f, 0.003082275f, 0.002990723f,
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0.002899170f, 0.002792358f, 0.002685547f, 0.002578735f,
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0.002456665f, 0.002349854f, 0.002243042f, 0.002120972f,
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0.002014160f, 0.001907349f, 0.001785278f, 0.001693726f,
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0.001586914f, 0.001480103f, 0.001388550f, 0.001296997f,
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0.001205444f, 0.001113892f, 0.001037598f, 0.000961304f,
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0.000885010f, 0.000808716f, 0.000747681f, 0.000686646f,
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0.000625610f, 0.000579834f, 0.000534058f, 0.000473022f,
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0.000442505f, 0.000396729f, 0.000366211f, 0.000320435f,
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0.000289917f, 0.000259399f, 0.000244141f, 0.000213623f,
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0.000198364f, 0.000167847f, 0.000152588f, 0.000137329f,
|
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0.000122070f, 0.000106812f, 0.000106812f, 0.000091553f,
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0.000076294f, 0.000076294f, 0.000061035f, 0.000061035f,
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0.000045776f, 0.000045776f, 0.000030518f, 0.000030518f,
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0.000030518f, 0.000030518f, 0.000015259f, 0.000015259f,
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0.000015259f, 0.000015259f, 0.000015259f, 0.000015259f,)
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private val imdctWinData = Array(4) { DoubleArray(36) }
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private val cosN12 = Array(6) { DoubleArray(12) }
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private val cosN36 = Array(18) { DoubleArray(36) }
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init {
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for (i in 0 until 36) {
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imdctWinData[0][i] = Math.sin(Math.PI / 36 * (i + 0.5));
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}
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for (i in 0 until 18) {
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imdctWinData[1][i] = Math.sin(Math.PI / 36 * (i + 0.5));
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}
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for (i in 18 until 24) {
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imdctWinData[1][i] = 1.0;
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}
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for (i in 24 until 30) {
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imdctWinData[1][i] = Math.sin(Math.PI / 12 * (i + 0.5 - 18.0));
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}
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for (i in 30 until 36) {
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imdctWinData[1][i] = 0.0;
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}
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for (i in 0 until 12) {
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imdctWinData[2][i] = Math.sin(Math.PI / 12 * (i + 0.5));
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}
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for (i in 12 until 36) {
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imdctWinData[2][i] = 0.0;
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}
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for (i in 0 until 6) {
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imdctWinData[3][i] = 0.0;
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}
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for (i in 6 until 12) {
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imdctWinData[3][i] = Math.sin(Math.PI / 12 * (i + 0.5 - 6.0));
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}
|
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for (i in 12 until 18) {
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imdctWinData[3][i] = 1.0;
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}
|
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for (i in 18 until 36) {
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imdctWinData[3][i] = Math.sin(Math.PI / 36 * (i + 0.5));
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}
|
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|
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val cosN12_N = 12
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for (i in 0 until 6) {
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for (j in 0 until 12) {
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cosN12[i][j] = Math.cos(Math.PI / (2 * cosN12_N) * (2*j + 1 + cosN12_N/2) * (2*i + 1));
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}
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}
|
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|
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val cosN36_N = 36
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for (i in 0 until 18) {
|
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for (j in 0 until 36) {
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cosN36[i][j] = Math.cos(Math.PI / (2 * cosN36_N) * (2*j + 1 + cosN36_N/2) * (2*i + 1));
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}
|
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}
|
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}
|
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|
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private fun ImdctWin(inData: DoubleArray, blockType: Int): DoubleArray {
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val out = DoubleArray(36)
|
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|
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if (blockType == 2) {
|
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val iwd = imdctWinData[blockType];
|
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val N = 12;
|
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for (i in 0 until 3) {
|
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for (p in 0 until N) {
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var sum = 0.0;
|
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for (m in 0 until N/2) {
|
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sum += inData[i+3*m] * cosN12[m][p];
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}
|
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out[6*i+p+6] += sum * iwd[p];
|
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}
|
||||
}
|
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return out;
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}
|
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|
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val N = 36;
|
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val iwd = imdctWinData[blockType]
|
||||
for (p in 0 until N) {
|
||||
var sum = 0.0;
|
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for (m in 0 until N/2) {
|
||||
sum += inData[m] * cosN36[m][p];
|
||||
}
|
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out[p] = sum * iwd[p];
|
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}
|
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return out;
|
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}
|
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|
||||
|
||||
|
||||
|
||||
private fun FloatArray.typedArraySet(xs: List<Float>, index: Int) {
|
||||
for (i in xs.indices) {
|
||||
this[i + index] = xs[i]
|
||||
}
|
||||
}
|
||||
|
||||
private fun Value.grch(gr: Long, ch: Long) = this.getArrayElement(gr).getArrayElement(ch)
|
||||
|
||||
fun mp3_hybridSynthesis(sideInfo: Value, mainDataIs: Value, storeCh: Value, gr: Long, ch: Long) {
|
||||
// Loop through all 32 subbands
|
||||
for (sb in 0 until 32) {
|
||||
// Determine blocktype for this subband
|
||||
var bt = sideInfo.getMember("BlockType").grch(gr,ch).asInt();
|
||||
if ((sideInfo.getMember("WinSwitchFlag").grch(gr,ch).asInt() == 1) &&
|
||||
(sideInfo.getMember("MixedBlockFlag").grch(gr,ch).asInt() == 1) && (sb < 2)) {
|
||||
bt = 0;
|
||||
}
|
||||
// Do the inverse modified DCT and windowing
|
||||
val inData = DoubleArray(18)
|
||||
for (i in 0 until 18) {
|
||||
inData[i] = mainDataIs.grch(gr,ch).getArrayElement(sb * 18L + i).asDouble()
|
||||
}
|
||||
val rawout = ImdctWin(inData, bt);
|
||||
// Overlapp add with stored vector into main_data vector
|
||||
for (i in 0L until 18L) {
|
||||
val storeChSb = storeCh.getArrayElement(sb.toLong())
|
||||
|
||||
mainDataIs.grch(gr,ch).setArrayElement(sb * 18 + i, rawout[i.toInt()] + storeChSb.getArrayElement(i).asDouble())
|
||||
storeChSb.setArrayElement(i, rawout[i.toInt() + 18])
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fun mp3_subbandSynthesis(nch: Int, frame: Value, gr: Long, ch: Long, out_ptr: Int) {
|
||||
val u_vec = FloatArray(512)
|
||||
val s_vec = FloatArray(32)
|
||||
|
||||
val frameV_vec_ch = frame.getMember("v_vec").getArrayElement(ch)
|
||||
val d = frame.getMember("mainData").getMember("Is").grch(gr,ch)
|
||||
|
||||
// Setup the n_win windowing vector and the v_vec intermediate vector
|
||||
for (ss in 0 until 18) { // Loop through 18 samples in 32 subbands
|
||||
// v_vec: Array(2)
|
||||
// v_vec[ch]: Float32Array(1024) -- instance of TypedArray
|
||||
frameV_vec_ch.invokeMember("set",
|
||||
frameV_vec_ch.invokeMember("slice", 0, 1024 - 64),
|
||||
64
|
||||
)
|
||||
//frame.v_vec[ch].set(frame.v_vec[ch].slice(0, 1024 - 64), 64); // copy(f.v_vec[ch][64:1024],
|
||||
// f.v_vec[ch][0:1024-64])
|
||||
|
||||
//var d = frame.mainData.Is[gr][ch];
|
||||
for (i in 0 until 32) { // Copy next 32 time samples to a temp vector
|
||||
s_vec[i] = d.getArrayElement(i * 18L + ss).asDouble().toFloat()
|
||||
//s_vec[i] = d[i * 18 + ss];
|
||||
}
|
||||
for (i in 0 until 64) { // Matrix multiply input with n_win[][] matrix
|
||||
var sum = 0f
|
||||
for (j in 0 until 32) {
|
||||
sum += synthNWin[i][j] * s_vec[j];
|
||||
}
|
||||
frameV_vec_ch.setArrayElement(i.toLong(), sum)
|
||||
//frame.v_vec[ch][i] = sum;
|
||||
}
|
||||
|
||||
val v = frameV_vec_ch
|
||||
//var v = frame.v_vec[ch];
|
||||
for (i in 0 until 512 step 64) { // Build the U vector
|
||||
u_vec.typedArraySet(((i shl 1) until (i shl 1) + 32).map { v.getArrayElement(it.toLong()).asDouble().toFloat() }, i)
|
||||
//u_vec.set(v.slice((i shl 1), (i shl 1) + 32), i); // copy(u_vec[i:i+32],
|
||||
// v[(i<<1):(i<<1)+32])
|
||||
|
||||
u_vec.typedArraySet(((i shl 1) + 96 until (i shl 1) + 128).map { v.getArrayElement(it.toLong()).asDouble().toFloat() }, i + 32)
|
||||
//u_vec.set(v.slice((i shl 1) + 96, (i shl 1) + 128), i + 32); // copy(u_vec[i+32:i+64],
|
||||
// v[(i<<1)+96:(i<<1)+128])
|
||||
}
|
||||
for (i in 0 until 512) { // Window by u_vec[i] with synthDtbl[i]
|
||||
u_vec[i] *= synthDtbl[i];
|
||||
}
|
||||
for (i in 0 until 32) { // Calc 32 samples,store in outdata vector
|
||||
var sum = 0f
|
||||
for (j in 0 until 512 step 32) {
|
||||
sum += u_vec[j + i];
|
||||
}
|
||||
// sum now contains time sample 32*ss+i. Convert to 16-bit signed int
|
||||
val samp = (sum * 32767).coerceIn(-32767f, 32767f)
|
||||
val s = samp.toInt()
|
||||
val idx = if (nch == 1) {
|
||||
2 * (32*ss + i)
|
||||
} else {
|
||||
4 * (32*ss + i)
|
||||
}
|
||||
if (ch == 0L) {
|
||||
vm.poke(out_ptr.toLong() + idx, s.toByte())
|
||||
vm.poke(out_ptr.toLong() + idx + 1, (s ushr 8).toByte())
|
||||
} else {
|
||||
vm.poke(out_ptr.toLong() + idx + 2, s.toByte())
|
||||
vm.poke(out_ptr.toLong() + idx + 3, (s ushr 8).toByte())
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user