diff --git a/COPYING.md b/COPYING.md index d9adde496..c190b5bbd 100644 --- a/COPYING.md +++ b/COPYING.md @@ -1,5 +1,3 @@ -*Terrarum* - Copyright (C) 2013-2023 Minjae Song ("CuriousTorvald") This program is free software: you can redistribute it and/or modify @@ -14,598 +12,3 @@ GNU General Public License for more details. You should have received a copy of the GNU General Public License along with this program. If not, see . - ----- - -*Terrarum Sans Bitmap* - -Copyright (c) 2017-2022 Minjae Song ("CuriousTorvald") and the contributors - -Permission is hereby granted, free of charge, to any person obtaining a copy -of this software and associated documentation files (the "Software"), to deal -in the Software without restriction, including without limitation the rights -to use, copy, modify, merge, publish, distribute, sublicense, and/or sell -copies of the Software, and to permit persons to whom the Software is -furnished to do so, subject to the following conditions: - -The above copyright notice and this permission notice shall be included in -all copies or substantial portions of the Software. - -THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR -IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, -FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE -AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER -LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, -OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN -THE SOFTWARE. - ----- - -*Joise* - -Copyright (C) 2013 Jason Taylor - -Licensed under the Apache License, Version 2.0 (the "License"); -you may not use this file except in compliance with the License. -You may obtain a copy of the License at - - http://www.apache.org/licenses/LICENSE-2.0 - -Unless required by applicable law or agreed to in writing, software -distributed under the License is distributed on an "AS IS" BASIS, -WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. -See the License for the specific language governing permissions and -limitations under the License. - -*Accidental Noise Library* - -Joise is a derivative work based on Josua Tippetts' C++ library: - - -Copyright (C) 2011 Joshua Tippetts - - This software is provided 'as-is', without any express or implied - warranty. 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If the source code for the -binary was not provided to you with the binary, you can also receive a copy of -the source code on physical media by submitting a written request to the -address listed below or by sending an email to Oracle using the following link: -http://www.oracle.com/goto/opensourcecode/request. - -Oracle America, Inc. -Attn: Senior Vice President -Development and Engineering Legal -500 Oracle Parkway, 10th Floor -Redwood Shores, CA 94065 - -Your request should include: -• The name of the binary for which you are requesting the source code -• The name and version number of the Oracle product containing the binary -• The date you received the Oracle product -• Your name -• Your company name (if applicable) -• Your return mailing address and email, and -• A telephone number in the event we need to reach you. - -We may charge you a fee to cover the cost of physical media and processing. -Your request must be sent -a. within three (3) years of the date you received the Oracle product that -included the binary that is the subject of your request, or -b. in the case of code licensed under the GPL v3 for as long as Oracle -offers spare parts or customer support for that product model. - -=========================================================================== diff --git a/src/net/torvald/terrarum/CreditSingleton.kt b/src/net/torvald/terrarum/CreditSingleton.kt index 8e2af4c02..25c9bfe6e 100644 --- a/src/net/torvald/terrarum/CreditSingleton.kt +++ b/src/net/torvald/terrarum/CreditSingleton.kt @@ -221,6 +221,67 @@ as well as the JVMCI and VisualVM modules, are released under version 2 of the GNU General Public License with the “Classpath” Exception. Copyright (c) 2015, 2019, Oracle and/or its affiliates. All rights reserved. + + + + + +$BULLET Jdsp + +Copyright (c) 2019 Sambit Paul + +Permission is hereby granted, free of charge, to any person obtaining a copy +of this software and associated documentation files (the "Software"), to deal +in the Software without restriction, including without limitation the rights +to use, copy, modify, merge, publish, distribute, sublicense, and/or sell +copies of the Software, and to permit persons to whom the Software is +furnished to do so, subject to the following conditions: + +The above copyright notice and this permission notice shall be included in all +copies or substantial portions of the Software. + +THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR +IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, +FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE +AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER +LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, +OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE +SOFTWARE. + + + + + +$BULLET Apache Commons Codec +Copyright 2002-2023 The Apache Software Foundation + +This product includes software developed at +The Apache Software Foundation (https://www.apache.org/). + + + + + +$BULLET Apache Commons CSV +Copyright 2005-2023 The Apache Software Foundation + +This product includes software developed at +The Apache Software Foundation (https://www.apache.org/). + + + + + +$BULLET Apache Commons Math + +Copyright 2001-2022 The Apache Software Foundation + +This product includes software developed at +The Apache Software Foundation (http://www.apache.org/). + +This product includes software developed for Orekit by +CS Systèmes d'Information (http://www.c-s.fr/) +Copyright 2010-2012 CS Systèmes d'Information """).split('\n') diff --git a/src/net/torvald/terrarum/audio/FFT.kt b/src/net/torvald/terrarum/audio/FFT.kt new file mode 100644 index 000000000..b62ee26af --- /dev/null +++ b/src/net/torvald/terrarum/audio/FFT.kt @@ -0,0 +1,304 @@ +package net.torvald.terrarum.audio + +import org.apache.commons.math3.exception.MathIllegalStateException +import org.apache.commons.math3.transform.DftNormalization +import org.apache.commons.math3.transform.TransformType +import org.apache.commons.math3.util.FastMath + +data class FComplex(var real: Float = 0f, var imaginary: Float = 0f) { + operator fun times(other: FComplex) = FComplex( + this.real * other.real - this.imaginary * other.imaginary, + this.real * other.imaginary + this.imaginary * other.real + ) +} + +/** + * Modification of the code form JDSP and Apache Commons Math + * + * Created by minjaesong on 2023-11-25. + */ +object FFT { + + // org.apache.commons.math3.transform.FastFouriesTransformer.java:370 + fun fft(signal: FloatArray): Array { + val dataRI = arrayOf(signal.copyOf(), FloatArray(signal.size)) + + transformInPlace(dataRI, DftNormalization.STANDARD, TransformType.FORWARD) + + val output = dataRI.toComplexArray() + + return getComplex(output, false) + } + + // org.apache.commons.math3.transform.FastFouriesTransformer.java:404 + fun ifftAndGetReal(y: Array): FloatArray { + val dataRI = Array(2) { FloatArray(y.size) } + for (i in y.indices) { + dataRI[0][i] = y[i].real + dataRI[1][i] = y[i].imaginary + } + + transformInPlace(dataRI, DftNormalization.STANDARD, TransformType.INVERSE) + + return dataRI[0] + } + + private fun Array.toComplexArray(): Array { + return Array(this[0].size) { + FComplex(this[0][it], this[1][it]) + } + } + + // com.github.psambit9791.jdsp.transform.FastFourier.java:190 + /** + * Returns the complex value of the fast fourier transformed sequence + * @param onlyPositive Set to True if non-mirrored output is required + * @throws java.lang.ExceptionInInitializerError if called before executing transform() method + * @return Complex[] The complex FFT output + */ + @Throws(ExceptionInInitializerError::class) + fun getComplex(output: Array, onlyPositive: Boolean): Array { + val dftout: Array = if (onlyPositive) { + val numBins: Int = output.size / 2 + 1 + Array(numBins) { FComplex() } + } + else { + Array(output.size) { FComplex() } + } + System.arraycopy(output, 0, dftout, 0, dftout.size) + return dftout + } + + // org.apache.commons.math3.transform.FastFouriesTransformer.java:214 + /** + * Computes the standard transform of the specified complex data. The + * computation is done in place. The input data is laid out as follows + *
    + *
  • {@code dataRI[0][i]} is the real part of the {@code i}-th data point,
    • + *
  • {@code dataRI[1][i]} is the imaginary part of the {@code i}-th data point.
    • + *
+ * + * @param dataRI the two dimensional array of real and imaginary parts of the data + * @param normalization the normalization to be applied to the transformed data + * @param type the type of transform (forward, inverse) to be performed + * @throws DimensionMismatchException if the number of rows of the specified + * array is not two, or the array is not rectangular + * @throws MathIllegalArgumentException if the number of data points is not + * a power of two + */ + private fun transformInPlace(dataRI: Array, normalization: DftNormalization, type: TransformType) { + val dataR = dataRI[0] + val dataI = dataRI[1] + val n = dataR.size + + if (n == 1) { + return + } + else if (n == 2) { + val srcR0 = dataR[0] + val srcI0 = dataI[0] + val srcR1 = dataR[1] + val srcI1 = dataI[1] + + // X_0 = x_0 + x_1 + dataR[0] = srcR0 + srcR1 + dataI[0] = srcI0 + srcI1 + // X_1 = x_0 - x_1 + dataR[1] = srcR0 - srcR1 + dataI[1] = srcI0 - srcI1 + normalizeTransformedData(dataRI, normalization, type) + return + } + + bitReversalShuffle2(dataR, dataI) + + // Do 4-term DFT. + + // Do 4-term DFT. + if (type == TransformType.INVERSE) { + var i0 = 0 + while (i0 < n) { + val i1 = i0 + 1 + val i2 = i0 + 2 + val i3 = i0 + 3 + val srcR0 = dataR[i0] + val srcI0 = dataI[i0] + val srcR1 = dataR[i2] + val srcI1 = dataI[i2] + val srcR2 = dataR[i1] + val srcI2 = dataI[i1] + val srcR3 = dataR[i3] + val srcI3 = dataI[i3] + + // 4-term DFT + // X_0 = x_0 + x_1 + x_2 + x_3 + dataR[i0] = srcR0 + srcR1 + srcR2 + srcR3 + dataI[i0] = srcI0 + srcI1 + srcI2 + srcI3 + // X_1 = x_0 - x_2 + j * (x_3 - x_1) + dataR[i1] = srcR0 - srcR2 + (srcI3 - srcI1) + dataI[i1] = srcI0 - srcI2 + (srcR1 - srcR3) + // X_2 = x_0 - x_1 + x_2 - x_3 + dataR[i2] = srcR0 - srcR1 + srcR2 - srcR3 + dataI[i2] = srcI0 - srcI1 + srcI2 - srcI3 + // X_3 = x_0 - x_2 + j * (x_1 - x_3) + dataR[i3] = srcR0 - srcR2 + (srcI1 - srcI3) + dataI[i3] = srcI0 - srcI2 + (srcR3 - srcR1) + i0 += 4 + } + } + else { + var i0 = 0 + while (i0 < n) { + val i1 = i0 + 1 + val i2 = i0 + 2 + val i3 = i0 + 3 + val srcR0 = dataR[i0] + val srcI0 = dataI[i0] + val srcR1 = dataR[i2] + val srcI1 = dataI[i2] + val srcR2 = dataR[i1] + val srcI2 = dataI[i1] + val srcR3 = dataR[i3] + val srcI3 = dataI[i3] + + // 4-term DFT + // X_0 = x_0 + x_1 + x_2 + x_3 + dataR[i0] = srcR0 + srcR1 + srcR2 + srcR3 + dataI[i0] = srcI0 + srcI1 + srcI2 + srcI3 + // X_1 = x_0 - x_2 + j * (x_3 - x_1) + dataR[i1] = srcR0 - srcR2 + (srcI1 - srcI3) + dataI[i1] = srcI0 - srcI2 + (srcR3 - srcR1) + // X_2 = x_0 - x_1 + x_2 - x_3 + dataR[i2] = srcR0 - srcR1 + srcR2 - srcR3 + dataI[i2] = srcI0 - srcI1 + srcI2 - srcI3 + // X_3 = x_0 - x_2 + j * (x_1 - x_3) + dataR[i3] = srcR0 - srcR2 + (srcI3 - srcI1) + dataI[i3] = srcI0 - srcI2 + (srcR1 - srcR3) + i0 += 4 + } + } + + var lastN0 = 4 + var lastLogN0 = 2 + while (lastN0 < n) { + val n0 = lastN0 shl 1 + val logN0 = lastLogN0 + 1 + val wSubN0R = W_SUB_N_R[logN0] + var wSubN0I = W_SUB_N_I[logN0] + if (type == TransformType.INVERSE) { + wSubN0I = -wSubN0I + } + + // Combine even/odd transforms of size lastN0 into a transform of size N0 (lastN0 * 2). + var destEvenStartIndex = 0 + while (destEvenStartIndex < n) { + val destOddStartIndex = destEvenStartIndex + lastN0 + var wSubN0ToRR = 1f + var wSubN0ToRI = 0f + for (r in 0 until lastN0) { + val grR = dataR[destEvenStartIndex + r] + val grI = dataI[destEvenStartIndex + r] + val hrR = dataR[destOddStartIndex + r] + val hrI = dataI[destOddStartIndex + r] + + // dest[destEvenStartIndex + r] = Gr + WsubN0ToR * Hr + dataR[destEvenStartIndex + r] = grR + wSubN0ToRR * hrR - wSubN0ToRI * hrI + dataI[destEvenStartIndex + r] = grI + wSubN0ToRR * hrI + wSubN0ToRI * hrR + // dest[destOddStartIndex + r] = Gr - WsubN0ToR * Hr + dataR[destOddStartIndex + r] = grR - (wSubN0ToRR * hrR - wSubN0ToRI * hrI) + dataI[destOddStartIndex + r] = grI - (wSubN0ToRR * hrI + wSubN0ToRI * hrR) + + // WsubN0ToR *= WsubN0R + val nextWsubN0ToRR = wSubN0ToRR * wSubN0R - wSubN0ToRI * wSubN0I + val nextWsubN0ToRI = wSubN0ToRR * wSubN0I + wSubN0ToRI * wSubN0R + wSubN0ToRR = nextWsubN0ToRR + wSubN0ToRI = nextWsubN0ToRI + } + destEvenStartIndex += n0 + } + lastN0 = n0 + lastLogN0 = logN0 + } + + normalizeTransformedData(dataRI, normalization, type) + } + + + /** + * Applies the proper normalization to the specified transformed data. + * + * @param dataRI the unscaled transformed data + * @param normalization the normalization to be applied + * @param type the type of transform (forward, inverse) which resulted in the specified data + */ + private fun normalizeTransformedData( + dataRI: Array, + normalization: DftNormalization, type: TransformType + ) { + val dataR = dataRI[0] + val dataI = dataRI[1] + val n = dataR.size + assert(dataI.size == n) + when (normalization) { + DftNormalization.STANDARD -> if (type == TransformType.INVERSE) { + val scaleFactor = 1f / n.toFloat() + var i = 0 + while (i < n) { + dataR[i] *= scaleFactor + dataI[i] *= scaleFactor + i++ + } + } + + DftNormalization.UNITARY -> { + val scaleFactor = (1.0 / FastMath.sqrt(n.toDouble())).toFloat() + var i = 0 + while (i < n) { + dataR[i] *= scaleFactor + dataI[i] *= scaleFactor + i++ + } + } + + else -> throw MathIllegalStateException() + } + } + + /** + * Performs identical index bit reversal shuffles on two arrays of identical + * size. Each element in the array is swapped with another element based on + * the bit-reversal of the index. For example, in an array with length 16, + * item at binary index 0011 (decimal 3) would be swapped with the item at + * binary index 1100 (decimal 12). + * + * @param a the first array to be shuffled + * @param b the second array to be shuffled + */ + private fun bitReversalShuffle2(a: FloatArray, b: FloatArray) { + val n = a.size + assert(b.size == n) + val halfOfN = n shr 1 + var j = 0 + for (i in 0 until n) { + if (i < j) { + // swap indices i & j + var temp = a[i] + a[i] = a[j] + a[j] = temp + temp = b[i] + b[i] = b[j] + b[j] = temp + } + var k = halfOfN + while (k in 1..j) { + j -= k + k = k shr 1 + } + j += k + } + } + + private val W_SUB_N_R = FFTConsts.W_SUB_N_R.map { it.toFloat() }.toFloatArray() + private val W_SUB_N_I = FFTConsts.W_SUB_N_I.map { it.toFloat() }.toFloatArray() + +} \ No newline at end of file diff --git a/src/net/torvald/terrarum/audio/FFTConsts.java b/src/net/torvald/terrarum/audio/FFTConsts.java new file mode 100644 index 000000000..cf2768bd6 --- /dev/null +++ b/src/net/torvald/terrarum/audio/FFTConsts.java @@ -0,0 +1,55 @@ +package net.torvald.terrarum.audio; + +/** + * Created by minjaesong on 2023-11-25. + */ +public class FFTConsts { + + // org.apache.commons.math3.transform.FastFouriesTransformer.java:58 + /** + * {@code W_SUB_N_R[i]} is the real part of + * {@code exp(- 2 * i * pi / n)}: + * {@code W_SUB_N_R[i] = cos(2 * pi/ n)}, where {@code n = 2^i}. + */ + public static final double[] W_SUB_N_R = + { 0x1.0p0, -0x1.0p0, 0x1.1a62633145c07p-54, 0x1.6a09e667f3bcdp-1 + , 0x1.d906bcf328d46p-1, 0x1.f6297cff75cbp-1, 0x1.fd88da3d12526p-1, 0x1.ff621e3796d7ep-1 + , 0x1.ffd886084cd0dp-1, 0x1.fff62169b92dbp-1, 0x1.fffd8858e8a92p-1, 0x1.ffff621621d02p-1 + , 0x1.ffffd88586ee6p-1, 0x1.fffff62161a34p-1, 0x1.fffffd8858675p-1, 0x1.ffffff621619cp-1 + , 0x1.ffffffd885867p-1, 0x1.fffffff62161ap-1, 0x1.fffffffd88586p-1, 0x1.ffffffff62162p-1 + , 0x1.ffffffffd8858p-1, 0x1.fffffffff6216p-1, 0x1.fffffffffd886p-1, 0x1.ffffffffff621p-1 + , 0x1.ffffffffffd88p-1, 0x1.fffffffffff62p-1, 0x1.fffffffffffd9p-1, 0x1.ffffffffffff6p-1 + , 0x1.ffffffffffffep-1, 0x1.fffffffffffffp-1, 0x1.0p0, 0x1.0p0 + , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 + , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 + , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 + , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 + , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 + , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 + , 0x1.0p0, 0x1.0p0, 0x1.0p0, 0x1.0p0 + , 0x1.0p0, 0x1.0p0, 0x1.0p0 }; + + /** + * {@code W_SUB_N_I[i]} is the imaginary part of + * {@code exp(- 2 * i * pi / n)}: + * {@code W_SUB_N_I[i] = -sin(2 * pi/ n)}, where {@code n = 2^i}. + */ + public static final double[] W_SUB_N_I = + { 0x1.1a62633145c07p-52, -0x1.1a62633145c07p-53, -0x1.0p0, -0x1.6a09e667f3bccp-1 + , -0x1.87de2a6aea963p-2, -0x1.8f8b83c69a60ap-3, -0x1.917a6bc29b42cp-4, -0x1.91f65f10dd814p-5 + , -0x1.92155f7a3667ep-6, -0x1.921d1fcdec784p-7, -0x1.921f0fe670071p-8, -0x1.921f8becca4bap-9 + , -0x1.921faaee6472dp-10, -0x1.921fb2aecb36p-11, -0x1.921fb49ee4ea6p-12, -0x1.921fb51aeb57bp-13 + , -0x1.921fb539ecf31p-14, -0x1.921fb541ad59ep-15, -0x1.921fb5439d73ap-16, -0x1.921fb544197ap-17 + , -0x1.921fb544387bap-18, -0x1.921fb544403c1p-19, -0x1.921fb544422c2p-20, -0x1.921fb54442a83p-21 + , -0x1.921fb54442c73p-22, -0x1.921fb54442cefp-23, -0x1.921fb54442d0ep-24, -0x1.921fb54442d15p-25 + , -0x1.921fb54442d17p-26, -0x1.921fb54442d18p-27, -0x1.921fb54442d18p-28, -0x1.921fb54442d18p-29 + , -0x1.921fb54442d18p-30, -0x1.921fb54442d18p-31, -0x1.921fb54442d18p-32, -0x1.921fb54442d18p-33 + , -0x1.921fb54442d18p-34, -0x1.921fb54442d18p-35, -0x1.921fb54442d18p-36, -0x1.921fb54442d18p-37 + , -0x1.921fb54442d18p-38, -0x1.921fb54442d18p-39, -0x1.921fb54442d18p-40, -0x1.921fb54442d18p-41 + , -0x1.921fb54442d18p-42, -0x1.921fb54442d18p-43, -0x1.921fb54442d18p-44, -0x1.921fb54442d18p-45 + , -0x1.921fb54442d18p-46, -0x1.921fb54442d18p-47, -0x1.921fb54442d18p-48, -0x1.921fb54442d18p-49 + , -0x1.921fb54442d18p-50, -0x1.921fb54442d18p-51, -0x1.921fb54442d18p-52, -0x1.921fb54442d18p-53 + , -0x1.921fb54442d18p-54, -0x1.921fb54442d18p-55, -0x1.921fb54442d18p-56, -0x1.921fb54442d18p-57 + , -0x1.921fb54442d18p-58, -0x1.921fb54442d18p-59, -0x1.921fb54442d18p-60 }; + +} diff --git a/src/net/torvald/terrarum/audio/TerrarumAudioFilter.kt b/src/net/torvald/terrarum/audio/TerrarumAudioFilter.kt index a247a2f20..fc10151a5 100644 --- a/src/net/torvald/terrarum/audio/TerrarumAudioFilter.kt +++ b/src/net/torvald/terrarum/audio/TerrarumAudioFilter.kt @@ -1,7 +1,5 @@ package net.torvald.terrarum.audio -import com.github.psambit9791.jdsp.transform.FastFourier -import com.github.psambit9791.jdsp.transform.InverseFastFourier import com.jme3.math.FastMath import com.jme3.math.FastMath.sin import net.torvald.terrarum.audio.AudioMixer.SPEED_OF_SOUND @@ -9,7 +7,6 @@ import net.torvald.terrarum.audio.TerrarumAudioMixerTrack.Companion.BUFFER_SIZE import net.torvald.terrarum.audio.TerrarumAudioMixerTrack.Companion.SAMPLING_RATED import net.torvald.terrarum.audio.TerrarumAudioMixerTrack.Companion.SAMPLING_RATEF import net.torvald.terrarum.roundToFloat -import org.apache.commons.math3.complex.Complex import java.io.File import kotlin.math.absoluteValue import kotlin.math.roundToInt @@ -298,12 +295,11 @@ class Reverb(val delayMS: Float = 36f, var feedback: Float = 0.92f, var lowpass: } } -class Convolv(ir: File, val gain: Float = decibelsToFullscale(-12.0).toFloat()): TerrarumAudioFilter() { +class Convolv(ir: File, val gain: Float = decibelsToFullscale(-24.0).toFloat()): TerrarumAudioFilter() { private val fftLen: Int - private val convFFT: Array> - private val inbuf: Array -// private val outbuf: Array + private val convFFT: Array> + private val inbuf: Array private val BLOCKSIZE = BUFFER_SIZE / 4 @@ -317,8 +313,8 @@ class Convolv(ir: File, val gain: Float = decibelsToFullscale(-12.0).toFloat()): println("IR Sample Count = $sampleCount; FFT Length = $fftLen") - val conv = Array(2) { DoubleArray(fftLen) } - inbuf = Array(2) { DoubleArray(fftLen) } + val conv = Array(2) { FloatArray(fftLen) } + inbuf = Array(2) { FloatArray(fftLen) } // outbuf = Array(2) { DoubleArray(fftLen) } ir.inputStream().let { @@ -331,8 +327,8 @@ class Convolv(ir: File, val gain: Float = decibelsToFullscale(-12.0).toFloat()): it.read().and(255).shl(8) or it.read().and(255).shl(16) or it.read().and(255).shl(24)) - conv[0][i] = f1.toDouble() - conv[1][i] = f2.toDouble() + conv[0][i] = f1 + conv[1][i] = f2 } it.close() @@ -340,7 +336,7 @@ class Convolv(ir: File, val gain: Float = decibelsToFullscale(-12.0).toFloat()): // fourier-transform the 'conv' convFFT = Array(2) { - FastFourier(conv[it]).let { it.transform(); it.getComplex(false) } + FFT.fft(conv[it]) } println("convFFT Length = ${convFFT[0].size}") @@ -354,72 +350,33 @@ class Convolv(ir: File, val gain: Float = decibelsToFullscale(-12.0).toFloat()): val t1 = System.nanoTime() for (ch in outbuf1.indices) { + push(inbuf1[ch].applyGain(gain), inbuf[ch]) - push(inbuf1[ch].toDoubleArray(gain), inbuf[ch]) - - val inputFFT = FastFourier(inbuf[ch]).let { it.transform(); it.getComplex(false) } - - val Ny = inputFFT.size// + convFFT[ch].size - 1 - -// println("inputFFT.size=${inputFFT.size} convFFT[ch].size=${convFFT[ch].size} Ny=$Ny") + val inputFFT = FFT.fft(inbuf[ch]) val Y = multiply(inputFFT, convFFT[ch]) - val y = real(ifft(Y)) + val y = FFT.ifftAndGetReal(Y) -// val u = y.sliceArray(Ny - BLOCKSIZE until Ny).toFloatArray(gain) // y size == Ny - val u = y.takeLast(BLOCKSIZE).map { it.toFloat() }.toFloatArray() - -// println("y size: ${y.size}; Ny=$Ny") + val u = y.takeLast(BLOCKSIZE).toFloatArray() System.arraycopy(u, 0, outbuf1[ch], 0, BLOCKSIZE) } val t2 = System.nanoTime() val ptime = (t2 - t1).toDouble() val realtime = BLOCKSIZE / SAMPLING_RATED * 1000000000L - if (realtime >= ptime) { -// println("Processing speed: ${realtime / ptime}x FASTER than realtime") - } - else { -// println("Processing speed: ${ptime / realtime}x SLOWER than realtime") - } + println("Processing speed: ${realtime / ptime}x") } - private fun real(cs: Array): DoubleArray { - return cs.map { it.real }.toDoubleArray() + private fun multiply(X: Array, H: Array): Array { + return Array(X.size) { X[it] * H[it] } } - private fun ifft(y: Array): Array { - return InverseFastFourier(y, false).let { it.transform(); it.complex } - } - - private fun multiply(X: Array, H: Array): Array { - if (X.size != H.size) throw IllegalArgumentException() - return Array(X.size) { - //X[it].multiply(H[it]) - - // following is a snippet of the code from org.apache.commons.math3.complex.multiply, - // to remove the non-necessary sanity checks - val a = X[it] - val b = H[it] - val re = a.real * b.real - a.imaginary * b.imaginary - val im = a.real * b.imaginary + a.imaginary * b.real - Complex(re, im) - } - } - - - private fun push(sample: Double, buf: DoubleArray) { - System.arraycopy(buf, 1, buf, 0, buf.size - 1) - buf[buf.lastIndex] = sample - } - - private fun push(samples: DoubleArray, buf: DoubleArray) { + private fun push(samples: FloatArray, buf: FloatArray) { System.arraycopy(buf, samples.size, buf, 0, buf.size - samples.size) System.arraycopy(samples, 0, buf, buf.size - samples.size, samples.size) } - private fun FloatArray.toDoubleArray(gain: Float = 1f) = this.map { it.toDouble() * gain }.toDoubleArray() - private fun DoubleArray.toFloatArray(gain: Float = 1f) = this.map { it.toFloat() * gain }.toFloatArray() + private fun FloatArray.applyGain(gain: Float = 1f) = this.map { it * gain }.toFloatArray() } object XYtoMS: TerrarumAudioFilter() { diff --git a/src/net/torvald/terrarum/audio/TerrarumAudioMixerTrack.kt b/src/net/torvald/terrarum/audio/TerrarumAudioMixerTrack.kt index b410423b2..4dfe89b99 100644 --- a/src/net/torvald/terrarum/audio/TerrarumAudioMixerTrack.kt +++ b/src/net/torvald/terrarum/audio/TerrarumAudioMixerTrack.kt @@ -21,9 +21,6 @@ class TerrarumAudioMixerTrack(val name: String, val isMaster: Boolean = false, v const val SAMPLING_RATEF = 48000f const val SAMPLING_RATED = 48000.0 const val BUFFER_SIZE = 512 // n ms -> 384 * n - - const val INDEX_BGM = 0 - const val INDEX_AMB = 1 } val hash = getHashStr()