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    griffinboy

    @griffinboy

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    Best posts made by griffinboy

    • [Free Dsp] Analog Filter (24dB/oct)

      C++ analog filter node based on this paper:
      https://www.researchgate.net/publication/344876889_Moog_Ladder_Filter_Generalizations_Based_on_State_Variable_Filters

      To use it in a Hise project, open your project folder and place the script file (Griffin_LadderFilter.h) under:
      DspNetworks > ThirdParty

      e42f5f06-2019-435a-b3aa-53af5d916733-image.png

      Then open your Hise project and compile dsp networks as dll

      9cff98b4-dfb6-4981-8446-bb2e2b0deb05-image.png

      Now press OK, and you will be able to use the Node:

      566a05d5-188e-438f-9f83-cff680d55493-image.png

      The node should appear under the 'project' category when you open the scripnode node browser.

      Download the script here:

      Polyphonic (stereo):
      https://1drv.ms/u/c/6c19b197e5968b36/EYVQsJa9FlpKldok2ThVUwMBVf3KnemfEeccDyzASGbGJw?e=XNq1PU

      Monophonic (stereo):
      https://1drv.ms/u/c/6c19b197e5968b36/EcGw46UnqYJMk1cu3bH2QZQBSWTXAOL6ggsusNrF-LrtZQ?e=FvMeGr

      24dB / Octave Filter Response:

      9537ba2d-197d-435b-b862-998dbf3ae7bd-image.png

      posted in ScriptNode
      griffinboyG
      griffinboy
    • [Tutorial] How to create a c++ custom node

      How to create a custom node, as promised.
      I apologise in advance for the awful quality video (quite dry and boring)! But the good news is that I have some nicer quality ones in the pipeline. However I thought I should get this out as soon as possible since some people were waiting on it.
      Hope it helps.

      Windows only, I'll do a mac tutorial later.

      Template v1.1:

      // ==========================| NodeTemplate v1.0 : by Griffinboy |==========================
      
      #pragma once
      #include <JuceHeader.h>
      
      namespace project
      {
          using namespace juce;
          using namespace hise;
          using namespace scriptnode;
      
          template <int NV>
          // --- Replace with Name 
          struct ExternalNodeTemplate : public data::base
          {   // ------ Replace with Name 
              SNEX_NODE(ExternalNodeTemplate);
      
              struct MetadataClass
              { // --------- Replace with "Name"
                  SN_NODE_ID("ExternalNodeTemplate");
              };
      
              // ==========================| Node Properties |==========================
              static constexpr bool isModNode() { return false; }
              static constexpr bool isPolyphonic() { return NV > 1; }
              static constexpr bool hasTail() { return false; }
              static constexpr bool isSuspendedOnSilence() { return false; }
              static constexpr int getFixChannelAmount() { return 2; }
      
              static constexpr int NumTables = 0;
              static constexpr int NumSliderPacks = 0;
              static constexpr int NumAudioFiles = 0;
              static constexpr int NumFilters = 0;
              static constexpr int NumDisplayBuffers = 0;
      
              // ==========================| Global Variables |==========================
      
              // ==========================| Prepare |==========================
              // Called on init, and when sample rate changes
              void prepare(PrepareSpecs specs)
              {
                  float sampleRate = specs.sampleRate;
                  float numChannels = specs.numChannels;
      
                  leftChannelEffect.prepare(sampleRate, 5.0); // 5ms smoothing on the gain parameter
                  rightChannelEffect.prepare(sampleRate, 5.0);
              }
      
              // ==========================| Reset |==========================
              // Called when the plugin is reloaded
              void reset() {}
      
              // ==========================| Process |==========================
              // Blocks of audio enter the script here
              template <typename ProcessDataType>
              void process(ProcessDataType& data)
              {
                  // Convert the audio data to a fixed-channel format for efficient processing
                  auto& fixData = data.template as<ProcessData<getFixChannelAmount()>>();
      
      			// Get pointers to each channel's audio data
                  // Changes to these variables will now directly modify the original audio buffer
                  auto audioBlock = fixData.toAudioBlock();
                  auto* leftChannelData = audioBlock.getChannelPointer(0);
                  auto* rightChannelData = audioBlock.getChannelPointer(1);
      
                  // Get the number of samples (one channel) for this block
                  int numSamples = data.getNumSamples();
      
                  // Pass each channel's audio to the appropriate AudioEffect class
                  leftChannelEffect.process(leftChannelData, numSamples);
                  rightChannelEffect.process(rightChannelData, numSamples);
              }
      
              // ==========================| AudioEffect Class |==========================
              class AudioEffect
              {
              public:
                  AudioEffect(float initialGain = 1.0f)
                  {
                      smoothGain.set(initialGain); // Initialize sfloat with initial gain
                  }
      
                  void prepare(double sampleRate, double timeInMilliseconds)
                  {
                      smoothGain.prepare(sampleRate, timeInMilliseconds);
                  }
      
                  void process(float* samples, int numSamples)
                  {
                      for (int i = 0; i < numSamples; ++i)
                      {
                          samples[i] *= smoothGain.advance(); // Apply the gain using the smoothed parameter
                      }
                  }
      
                  void updateGain(float newGain)
                  {
                      smoothGain.set(newGain);
                  }
      
              private:
                  sfloat smoothGain; // Declare smoothGain variable, using sfloat type for smoothing
              };
      
              // ==========================| Set Parameter |==========================
              template <int P>
              void setParameter(double v)
              {
                  if (P == 0)
                      leftChannelEffect.updateGain(static_cast<float>(v)); // Update gain for left channel
                  else if (P == 1)
                      rightChannelEffect.updateGain(static_cast<float>(v)); // Update gain for right channel
              }
      
              // ==========================| Create Parameters |==========================
              void createParameters(ParameterDataList& data)
              {
      
                  {   //                             { min, max,  step }                 { id } 
                      parameter::data p("Left Gain", { 0.1, 2.0, 0.01 }); registerCallback<0>(p);
                      p.setDefaultValue(1.0);
                      data.add(std::move(p));
                  }
                  {
                      parameter::data p("Right Gain", { 0.1, 2.0, 0.01 });
                      registerCallback<1>(p);
                      p.setDefaultValue(1.0);
                      data.add(std::move(p));
                  }
              }
      
              // ==========================| External Data |==========================
              void setExternalData(const ExternalData& data, int index) {}
      
              // ==========================| Handle HISE Event |==========================
              void handleHiseEvent(HiseEvent& e) {}
      
              // ==========================| Modulation Slot |==========================
              // ( first enable isModNode() at the top of script ) 
              /*
                  ModValue modValue;
                  int handleModulation(double& value)
                  {
                      return modValue.getChangedValue(value);
                  }
                  // Creates callback so that altering the 'modValue' var elsewhere will now update the mod slot
                  modValue.setModValue(0);
              */
      
              // processFrame: Needed for compiler, does nothing
              template <typename FrameDataType>
              void processFrame(FrameDataType& data) {}
      
          private:
              AudioEffect leftChannelEffect;
              AudioEffect rightChannelEffect;
          };
      }
      
      

      14434c25-0fb6-4abd-bcc3-10cdc249cdd1-image.png

      posted in Blog Entries
      griffinboyG
      griffinboy
    • [Free Dsp] Oberheim-8 Analog Filter

      Polyphonic 12db/oct Filter with keytracking.

      Created from a linear (non saturating) analysis of the OB8 lowpass.
      It's not a match for high resonance settings, but it has good intuition at low resonance. You are welcome to tune it further by modifying the code.

      CPU usage: ≈1%

      27f9a3b7-c78b-4610-b029-965bb2b4da1d-image.png

      Instructions for setup included inside the script.
      The "Eigen" header library is required:
      https://github.com/PX4/eigen

      Download the Filter Script here:
      https://1drv.ms/u/c/6c19b197e5968b36/ER8vuJpevI9Htt_WY8Mqs8sBBJ15n8JLf-MJdSNgwjZX5g?e=zXd7gZ

      Raw Code:

      #pragma once
      #include <JuceHeader.h>
      #include <cmath>
      #include "src\eigen-master\Eigen\Dense"
      
      
      /**
       
      ==============| by GriffinBoy (2025) |==============
      
      This node implements an OB8 2-SVF (State-Variable Filter) with global feedback
      using the Delay-Free method as described in DAFx-2020.
      
      Features:
      - Parameter smoothing via Juce's SmoothedValue class
      - Bilinear (TPT) transform implementation
      - Optimized 4x4 matrix inversion using the Eigen library
      - Recalculates matrices only when parameters change (dirty flags)
      - Keytracking support for cutoff frequency
      - (rough) Resonance compensation for frequency shift
      - (rough) Gain compensation for resonance control
      
      Integration Steps for HISE:
      1. Eigen Setup: Download and place the Eigen library under:
         ProjectName/DspNetworks/ThirdParty/src/eigen-master
      2. Create a 3rd party C++ node in HISE named "Griffin_OBFilter"
      3. Compile the initial DLL in HISE using "Compile dsp networks as .dll"
      4. Replace the generated "Griffin_OBFilter.h" (in ProjectName/DspNetworks/ThirdParty)
         with this header file you are reading now
      5. Re-compile the final DLL in HISE using "Compile dsp networks as .dll" 
      
      Continuous-Time System Definition:
        x1'(t) = -2*r*x1 - x2 - kf*x4 + input
        x2'(t) = x1
        x3'(t) = -2*r*x3 - x4 + x2
        x4'(t) = x3
      (Output is taken from state x4)
      
      Bilinear Transform:
        M = I - g*A,   N = I + g*A, where g = 2 * tan(pi * fc / fs)
        (M is inverted using Eigen's optimized fixed-size matrix inversion)
      
      Optimizations:
      - Precomputed reciprocals and constants
      - Eigen fixed-size matrices for 4x4 operations
      - Dirty flags for matrix recalculation only when parameters change
      
      Author: GriffinBoy (2025)
      License: UwU 
      */
      
      
      
      namespace project
      {
          using namespace juce;
          using namespace hise;
          using namespace scriptnode;
      
          template <int NV> // NV = Number of Voices
          struct Griffin_OBFilter : public data::base
          {
              SNEX_NODE(Griffin_OBFilter);
      
              struct MetadataClass { SN_NODE_ID("Griffin_OBFilter"); };
      
              static constexpr bool isModNode() { return false; }
              static constexpr bool isPolyphonic() { return NV > 1; }
              static constexpr bool hasTail() { return false; }
              static constexpr bool isSuspendedOnSilence() { return false; }
              static constexpr int  getFixChannelAmount() { return 2; }
      
              static constexpr int  NumTables = 0;
              static constexpr int  NumSliderPacks = 0;
              static constexpr int  NumAudioFiles = 0;
              static constexpr int  NumFilters = 0;
              static constexpr int  NumDisplayBuffers = 0;
      
              //=========================================================================
              // Parameters (Raw Values)
              //=========================================================================
              float cutoffFrequency = 1000.0f;
              float resonance = 0.0f;    // Range: [0, 35]
              float keytrackAmount = 1.0f;
              float sampleRate = 44100.0f;
      
              //=========================================================================
              // Smoothing Objects for Per-Sample Smoothing
              //=========================================================================
              SmoothedValue<float> cutoffSmooth;
              SmoothedValue<float> resonanceSmooth;
              SmoothedValue<float> keytrackSmooth;
      
              //=========================================================================
              // Prepare Function
              // - Sets up voices and initializes smoothers.
              //=========================================================================
              void prepare(PrepareSpecs specs)
              {
                  sampleRate = specs.sampleRate;
                  filtersLeft.prepare(specs);
                  filtersRight.prepare(specs);
      
                  for (auto& v : filtersLeft)
                      v.prepare(sampleRate);
                  for (auto& v : filtersRight)
                      v.prepare(sampleRate);
      
                  // Set smoothing time (10ms)
                  cutoffSmooth.reset(sampleRate, 0.01);
                  resonanceSmooth.reset(sampleRate, 0.01);
                  keytrackSmooth.reset(sampleRate, 0.01);
      
                  cutoffSmooth.setCurrentAndTargetValue(cutoffFrequency);
                  resonanceSmooth.setCurrentAndTargetValue(resonance);
                  keytrackSmooth.setCurrentAndTargetValue(keytrackAmount);
              }
      
              void reset()
              {
                  for (auto& v : filtersLeft)
                      v.reset();
                  for (auto& v : filtersRight)
                      v.reset();
              }
      
              //=========================================================================
              // Process Audio
              // - Updates parameters per sample using smoothed values.
              //=========================================================================
              template <typename ProcessDataType>
              void process(ProcessDataType& data)
              {
                  auto& fixData = data.template as<ProcessData<getFixChannelAmount()>>();
                  auto audioBlock = fixData.toAudioBlock();
      
                  float* leftCh = audioBlock.getChannelPointer(0);
                  float* rightCh = audioBlock.getChannelPointer(1);
                  int numSamples = static_cast<int>(data.getNumSamples());
      
                  for (int i = 0; i < numSamples; ++i)
                  {
                      // Get per-sample smoothed parameter values
                      float cVal = cutoffSmooth.getNextValue();
                      float rVal = resonanceSmooth.getNextValue();
                      float kVal = keytrackSmooth.getNextValue();
      
                      // Update each voice with new smoothed parameters
                      for (auto& v : filtersLeft)
                      {
                          v.setCutoff(cVal);
                          v.setResonance(rVal);
                          v.setKeytrack(kVal);
                          v.applyChangesIfNeeded();
                      }
                      for (auto& v : filtersRight)
                      {
                          v.setCutoff(cVal);
                          v.setResonance(rVal);
                          v.setKeytrack(kVal);
                          v.applyChangesIfNeeded();
                      }
      
                      // Process sample for each voice in series
                      float outL = leftCh[i];
                      float outR = rightCh[i];
                      for (auto& v : filtersLeft)
                          outL = v.processSample(outL);
                      for (auto& v : filtersRight)
                          outR = v.processSample(outR);
      
                      leftCh[i] = outL;
                      rightCh[i] = outR;
                  }
              }
      
              template <typename FrameDataType>
              void processFrame(FrameDataType& data) {}
      
              //=========================================================================
              // AudioEffect Class: OB8-Style Voice-Level Filter
              // - Implements the filter logic with Eigen optimizations.
              //=========================================================================
              class AudioEffect
              {
              public:
                  AudioEffect() = default;
      
                  inline void prepare(float fs)
                  {
                      sampleRate = fs;
                      baseCutoff = 1000.0f;
                      resonance = 0.0f;
                      rDamping = 3.4f; // Fixed damping value
                      keytrackAmount = 1.0f;
                      storedNote = 60;
                      reset();
                      dirtyFlags = 0;
                      updateAll(); // Initial matrix calculations
                  }
      
                  inline void reset()
                  {
                      x.setZero();
                  }
      
                  //=====================================================================
                  // Parameter Setting Functions
                  //=====================================================================
                  enum Dirty : uint32_t
                  {
                      changedCutoff = 1 << 0,
                      changedResonance = 1 << 1,
                      changedKeytrack = 1 << 2,
                      changedNote = 1 << 3
                  };
      
                  inline void setCutoff(float c)
                  {
                      baseCutoff = c;
                      dirtyFlags |= changedCutoff;
                  }
                  inline void setResonance(float r)
                  {
                      resonance = r;
                      dirtyFlags |= changedResonance;
                  }
                  inline void setKeytrack(float kt)
                  {
                      keytrackAmount = kt;
                      dirtyFlags |= changedKeytrack;
                  }
                  inline void setNoteNumber(int n)
                  {
                      storedNote = n;
                      dirtyFlags |= changedNote;
                  }
                  inline void applyChangesIfNeeded()
                  {
                      if (dirtyFlags != 0)
                          updateAll();
                  }
      
                  //=====================================================================
                  // Process Sample Function
                  // - Processes a single sample and applies the filter.
                  //=====================================================================
                  inline float processSample(float input)
                  {
                      constexpr float noiseFloor = 0.005f;
                      input += noiseFloor * (noiseGen.nextFloat() - 0.5f); // Add slight noise for stability
      
                      // State update and output calculation (Eigen optimized)
                      Eigen::Vector4f temp = N * x + gB * input;
                      Eigen::Vector4f newX = MInv * temp;
                      float out = C.dot(newX) * gainComp;
                      x = newX;
                      return out;
                  }
      
              private:
                  //=====================================================================
                  // Update All Parameters Function
                  // - Recalculates matrices and inversion when parameters change.
                  //=====================================================================
                  inline void updateAll()
                  {
                      // Keytracking calculation
                      float semitones = (static_cast<float>(storedNote) - 60.0f) * keytrackAmount;
                      float noteFactor = std::exp2f(0.0833333f * semitones);
                      float fc = baseCutoff * noteFactor;
      
                      // Cutoff frequency clamping [20 Hz, 20 kHz]
                      if (fc < 20.0f)
                          fc = 20.0f;
                      if (fc > 20000.0f)
                          fc = 20000.0f;
      
                      // Compensation offset for frequency shift (empirical)
                      float compensationOffset = 0.44f * fc - 30.0f;
                      if (compensationOffset < 0.0f)
                          compensationOffset = 0.0f;
      
                      // Resonance compensation
                      fc -= (resonance / 35.0f) * compensationOffset;
      
                      // Re-clamp cutoff after compensation
                      if (fc < 20.0f)
                          fc = 20.0f;
                      if (fc > 20000.0f)
                          fc = 20000.0f;
      
                      // TPT Warped frequency and g parameter
                      const float fsRecip = 1.0f / sampleRate;
                      const float factor = MathConstants<float>::pi * fc * fsRecip;
                      const float warped = std::tan(factor);
                      g = 2.0f * warped;
      
                      // Matrix construction and inversion
                      buildContinuousTimeSystem();
                      buildDiscreteTimeMatrices();
                      MInv = M.inverse();
                      C = Ccont; // Set output vector
      
                      // Gain Compensation (Resonance dependent)
                      if (dirtyFlags & changedResonance)
                      {
                          gainComp = std::pow(10.0f, (std::sqrt(resonance / 35.0f) * 22.0f) / 20.0f);
                      }
      
                      dirtyFlags = 0; // Clear dirty flags
                  }
      
      
                  //=====================================================================
                  // Build Continuous-Time System Function
                  // - Defines the continuous-time state-space matrices (Acont, Bcont, Ccont).
                  //=====================================================================
                  inline void buildContinuousTimeSystem()
                  {
                      const float twoR = 2.0f * rDamping;
                      Acont.setZero();
                      Bcont.setZero();
                      Ccont.setZero();
      
                      // State equations (matrix A)
                      Acont(0, 0) = -twoR;
                      Acont(0, 1) = -1.0f;
                      Acont(0, 3) = -resonance;
                      Acont(1, 0) = 1.0f;
                      Acont(2, 1) = 1.0f;
                      Acont(2, 2) = -twoR;
                      Acont(2, 3) = -1.0f;
                      Acont(3, 2) = 1.0f;
      
                      // Input matrix B (input to x1')
                      Bcont(0) = 1.0f;
      
                      // Output matrix C (output from x4)
                      Ccont(3) = 1.0f;
                  }
      
                  //=====================================================================
                  // Build Discrete-Time Matrices Function
                  // - Discretizes the continuous-time system using TPT transform (M, N, gB).
                  //=====================================================================
                  inline void buildDiscreteTimeMatrices()
                  {
                      Eigen::Matrix4f gA = g * Acont;
                      M = Eigen::Matrix4f::Identity() - gA;
                      N = Eigen::Matrix4f::Identity() + gA;
                      gB = g * Bcont;
                  }
      
                  //=====================================================================
                  // Member Variables (AudioEffect)
                  //=====================================================================
                  float sampleRate = 44100.0f;
                  float baseCutoff = 1000.0f;
                  float resonance = 0.0f;
                  float rDamping = 3.4f;        // Fixed damping parameter
                  float keytrackAmount = 1.0f;
                  int storedNote = 60;
                  float g = 0.0f;             // Warped frequency parameter
      
                  Eigen::Vector4f x = Eigen::Vector4f::Zero();         // State vector
                  Eigen::Matrix4f Acont = Eigen::Matrix4f::Zero();    // Continuous-time A matrix
                  Eigen::Vector4f Bcont = Eigen::Vector4f::Zero();     // Continuous-time B matrix
                  Eigen::Vector4f Ccont = Eigen::Vector4f::Zero();     // Continuous-time C matrix
                  Eigen::Matrix4f M = Eigen::Matrix4f::Zero();         // Discrete-time M matrix
                  Eigen::Matrix4f N = Eigen::Matrix4f::Zero();         // Discrete-time N matrix
                  Eigen::Matrix4f MInv = Eigen::Matrix4f::Zero();      // Inverted M matrix
                  Eigen::Vector4f gB = Eigen::Vector4f::Zero();        // Discrete-time gB matrix
                  Eigen::Vector4f C = Eigen::Vector4f::Zero();         // Discrete-time C matrix (output)
      
                  float gainComp = 1.0f;          // Gain compensation factor
                  uint32_t dirtyFlags = 0;        // Flags to track parameter changes
                  juce::Random noiseGen;          // Random number generator for noise
              };
      
              //=========================================================================
              // Parameter Setting (Per Sample Update)
              //=========================================================================
              template <int P>
              void setParameter(double val)
              {
                  if (P == 0)
                  {
                      cutoffFrequency = static_cast<float>(val);
                      cutoffSmooth.setTargetValue(cutoffFrequency);
                  }
                  else if (P == 1)
                  {
                      resonance = static_cast<float>(val);
                      if (resonance < 0.0f)
                          resonance = 0.0f;
                      if (resonance > 35.0f)
                          resonance = 35.0f;
                      resonanceSmooth.setTargetValue(resonance);
                  }
                  else if (P == 2)
                  {
                      keytrackAmount = static_cast<float>(val);
                      keytrackSmooth.setTargetValue(keytrackAmount);
                  }
              }
      
              void createParameters(ParameterDataList& data)
              {
                  {
                      parameter::data p("Cutoff Frequency", { 100.0, 20000.0, 1.0 });
                      registerCallback<0>(p);
                      p.setDefaultValue(1000.0f);
                      data.add(std::move(p));
                  }
                  {
                      parameter::data p("Resonance", { 0.0, 35.0, 0.01 });
                      registerCallback<1>(p);
                      p.setDefaultValue(0.0f);
                      data.add(std::move(p));
                  }
                  {
                      parameter::data p("Keytrack Amount", { -1.0, 1.0, 0.5 });
                      registerCallback<2>(p);
                      p.setDefaultValue(0.0f);
                      data.add(std::move(p));
                  }
              }
      
              void setExternalData(const ExternalData& data, int index) {}
      
              //=========================================================================
              // Note Handling
              //=========================================================================
              void handleHiseEvent(HiseEvent& e)
              {
                  if (e.isNoteOn())
                  {
                      filtersLeft.get().setNoteNumber(e.getNoteNumber());
                      filtersLeft.get().applyChangesIfNeeded();
      
                      filtersRight.get().setNoteNumber(e.getNoteNumber());
                      filtersRight.get().applyChangesIfNeeded();
                  }
              }
      
          private:
              PolyData<AudioEffect, NV> filtersLeft;
              PolyData<AudioEffect, NV> filtersRight;
          };
      }
      

      *edit: As an extra, I include a resonant ladder filter, which has an extremely wide range for resonance, from ultra soft to spiky. Setup is the same as the OB Filter, this script replaces the same effect. Rename the node if you want to use it separately.

      #pragma once
      #include <JuceHeader.h>
      #include <cmath>
      #include "src\eigen-master\Eigen\Dense"
      
      // Werner Filter
      
      namespace project
      {
          using namespace juce;
          using namespace hise;
          using namespace scriptnode;
      
          template <int NV> // NV = number of voices
          struct Griffin_OBFilter : public data::base
          {
              SNEX_NODE(Griffin_OBFilter);
      
              struct MetadataClass
              {
                  SN_NODE_ID("Griffin_OBFilter");
              };
      
              static constexpr bool isModNode() { return false; }
              static constexpr bool isPolyphonic() { return NV > 1; }
              static constexpr bool hasTail() { return false; }
              static constexpr bool isSuspendedOnSilence() { return false; }
              static constexpr int  getFixChannelAmount() { return 2; }
      
              static constexpr int  NumTables = 0;
              static constexpr int  NumSliderPacks = 0;
              static constexpr int  NumAudioFiles = 0;
              static constexpr int  NumFilters = 0;
              static constexpr int  NumDisplayBuffers = 0;
      
              // Outer-level parameters and smoothing objects
              float cutoffFrequency = 1000.0f;
              // Combined resonance/damping control
              float resonance = 0.0f;
              float keytrackAmount = 1.0f;
              float rDamp = 1.06f;  // SVF damping (r)
              float sampleRate = 44100.0f;
      
              SmoothedValue<float> cutoffSmooth;
              SmoothedValue<float> resonanceSmooth;
              SmoothedValue<float> keytrackSmooth;
              SmoothedValue<float> dampingSmooth;
      
              void prepare(PrepareSpecs specs)
              {
                  sampleRate = specs.sampleRate;
                  // Prepare voice-level filters
                  filtersLeft.prepare(specs);
                  filtersRight.prepare(specs);
      
                  for (auto& fl : filtersLeft)
                      fl.prepare(sampleRate);
                  for (auto& fr : filtersRight)
                      fr.prepare(sampleRate);
      
                  // Initialize per-sample smoothing (10ms ramp time)
                  cutoffSmooth.reset(sampleRate, 0.01);
                  resonanceSmooth.reset(sampleRate, 0.01);
                  keytrackSmooth.reset(sampleRate, 0.01);
                  dampingSmooth.reset(sampleRate, 0.01);
      
                  cutoffSmooth.setCurrentAndTargetValue(cutoffFrequency);
                  resonanceSmooth.setCurrentAndTargetValue(resonance);
                  keytrackSmooth.setCurrentAndTargetValue(keytrackAmount);
                  dampingSmooth.setCurrentAndTargetValue(rDamp);
              }
      
              void reset()
              {
                  for (auto& fl : filtersLeft)
                      fl.reset();
                  for (auto& fr : filtersRight)
                      fr.reset();
              }
      
              // Per-sample processing with parameter smoothing
              template <typename ProcessDataType>
              void process(ProcessDataType& data)
              {
                  auto& fixData = data.template as<ProcessData<getFixChannelAmount()>>();
                  auto audioBlock = fixData.toAudioBlock();
      
                  float* leftChannelData = audioBlock.getChannelPointer(0);
                  float* rightChannelData = audioBlock.getChannelPointer(1);
                  int numSamples = static_cast<int>(data.getNumSamples());
      
                  for (int i = 0; i < numSamples; ++i)
                  {
                      // Get per-sample smoothed parameters
                      float cVal = cutoffSmooth.getNextValue();
                      float rVal = resonanceSmooth.getNextValue();
                      float ktVal = keytrackSmooth.getNextValue();
                      float dVal = dampingSmooth.getNextValue();
      
                      // Update all voices with the current smoothed values
                      for (auto& fl : filtersLeft)
                      {
                          fl.setCutoff(cVal);
                          fl.setResonance(rVal);
                          fl.setKeytrack(ktVal);
                          fl.setDamping(dVal);
                          fl.applyChangesIfNeeded();
                      }
                      for (auto& fr : filtersRight)
                      {
                          fr.setCutoff(cVal);
                          fr.setResonance(rVal);
                          fr.setKeytrack(ktVal);
                          fr.setDamping(dVal);
                          fr.applyChangesIfNeeded();
                      }
      
                      // Process the sample for each voice in series
                      float inL = leftChannelData[i];
                      float inR = rightChannelData[i];
      
                      for (auto& fl : filtersLeft)
                          inL = fl.processSample(inL);
                      for (auto& fr : filtersRight)
                          inR = fr.processSample(inR);
      
                      leftChannelData[i] = inL;
                      rightChannelData[i] = inR;
                  }
              }
      
              template <typename FrameDataType>
              void processFrame(FrameDataType& data) {}
      
              // Voice-level effect: Two 2nd-order SVFs + global feedback, EXACT delay-free method
              class AudioEffect
              {
              public:
                  AudioEffect() = default;
      
                  void prepare(float fs)
                  {
                      sampleRate = fs;
                      baseCutoff = 1000.0f;
                      resonance = 0.0f;
                      rDamping = 1.06f;
                      keytrackAmount = 1.0f;
                      storedNote = 60;
      
                      reset();
                      dirtyFlags = 0;
                      updateAll(); // Build A, B, C, compute g, discretize & invert, etc.
                  }
      
                  void reset()
                  {
                      x = Eigen::Vector4f::Zero();
                  }
      
                  // Dirty flag enum for parameter changes
                  enum Dirty : uint32_t
                  {
                      changedCutoff = 1 << 0,
                      changedResonance = 1 << 1,
                      changedDamping = 1 << 2,
                      changedKeytrack = 1 << 3,
                      changedNote = 1 << 4
                  };
      
                  inline void setCutoff(float c)
                  {
                      baseCutoff = c;
                      dirtyFlags |= changedCutoff;
                  }
                  inline void setResonance(float r)
                  {
                      resonance = r;
                      dirtyFlags |= changedResonance;
                  }
                  inline void setDamping(float d)
                  {
                      rDamping = d;
                      dirtyFlags |= changedDamping;
                  }
                  inline void setKeytrack(float kt)
                  {
                      keytrackAmount = kt;
                      dirtyFlags |= changedKeytrack;
                  }
                  inline void setNoteNumber(int n)
                  {
                      storedNote = n;
                      dirtyFlags |= changedNote;
                  }
                  inline void applyChangesIfNeeded()
                  {
                      if (dirtyFlags != 0)
                          updateAll();
                  }
      
                  // Process a single sample using the discrete-time state update
                  inline float processSample(float input)
                  {
                      Eigen::Vector4f temp = N * x + gB * input;
                      Eigen::Vector4f newX = MInv * temp;
                      float out = C.dot(newX) * gainComp;
                      x = newX;
                      return out;
                  }
      
              private:
                  inline void updateAll()
                  {
                      // Compute effective cutoff with keytracking
                      float semitones = (static_cast<float>(storedNote) - 60.0f) * keytrackAmount;
                      float noteFactor = std::exp2f(0.0833333f * semitones);
                      float fc = baseCutoff * noteFactor;
                      if (fc < 20.0f)
                          fc = 20.0f;
                      float limit = 0.49f * sampleRate;
                      if (fc > limit)
                          fc = limit;
      
                      // Compute TPT warp coefficient: g = 2 * tan(pi * (fc / fs))
                      float norm = fc / sampleRate;
                      float warped = std::tan(MathConstants<float>::pi * norm);
                      g = 2.0f * warped;
      
                      // Build continuous-time state-space (Acont, Bcont, Ccont)
                      buildContinuousTimeSystem();
                      // Build discrete-time matrices via TPT: M = I - g*Acont, N = I + g*Acont, and gB = g*Bcont
                      buildDiscreteTimeMatrices();
                      // Invert M using Eigen's fixed-size matrix inversion
                      MInv = M.inverse();
                      // For output, C (discrete-time) equals Ccont
                      C = Ccont;
      
                      // Apply gain compensation: design so that resonance=3 produces an 11 dB boost.
                      gainComp = std::pow(10.0f, (std::sqrt(resonance / 3.0f) * 11.0f) / 20.0f);
      
                      dirtyFlags = 0;
                  }
      
                  inline void buildContinuousTimeSystem()
                  {
                      // Using damping (rDamping) and feedback gain (resonance)
                      const float r = rDamping;
                      const float kf = resonance;
      
                      Acont << -2.0f * r, -1.0f, 0.0f, -kf,
                          1.0f, 0.0f, 0.0f, 0.0f,
                          0.0f, 1.0f, -2.0f * r, -1.0f,
                          0.0f, 0.0f, 1.0f, 0.0f;
                      Bcont << 1.0f, 0.0f, 0.0f, 0.0f;
                      Ccont << 0.0f, 0.0f, 0.0f, 1.0f;
                  }
      
                  inline void buildDiscreteTimeMatrices()
                  {
                      M = Eigen::Matrix4f::Identity() - g * Acont;
                      N = Eigen::Matrix4f::Identity() + g * Acont;
                      gB = g * Bcont;
                  }
      
                  float sampleRate = 44100.0f;
                  float baseCutoff = 1000.0f;
                  float resonance = 0.0f;
                  float rDamping = 1.06f;
                  float keytrackAmount = 1.0f;
                  int storedNote = 60;
                  float g = 0.0f;
                  float gainComp = 1.0f;
                  uint32_t dirtyFlags = 0;
      
                  Eigen::Matrix4f Acont = Eigen::Matrix4f::Zero();
                  Eigen::Vector4f Bcont = Eigen::Vector4f::Zero();
                  Eigen::Vector4f Ccont = Eigen::Vector4f::Zero();
                  Eigen::Matrix4f M = Eigen::Matrix4f::Zero();
                  Eigen::Matrix4f N = Eigen::Matrix4f::Zero();
                  Eigen::Matrix4f MInv = Eigen::Matrix4f::Zero();
                  Eigen::Vector4f gB = Eigen::Vector4f::Zero();
                  Eigen::Vector4f C = Eigen::Vector4f::Zero();
                  Eigen::Vector4f x = Eigen::Vector4f::Zero();
              };
      
              // External parameter setters with combined resonance/damping control.
              template <int P>
              void setParameter(double val)
              {
                  if (P == 0)
                  {
                      cutoffFrequency = static_cast<float>(val);
                      cutoffSmooth.setTargetValue(cutoffFrequency);
                      for (auto& fl : filtersLeft)
                      {
                          fl.setCutoff(cutoffFrequency);
                          fl.applyChangesIfNeeded();
                      }
                      for (auto& fr : filtersRight)
                      {
                          fr.setCutoff(cutoffFrequency);
                          fr.applyChangesIfNeeded();
                      }
                  }
                  else if (P == 1)
                  {
                      float extRes = static_cast<float>(val);
                      // Using a threshold of 1.0 within the control range [0, 1.3]
                      if (extRes >= 1.0f)
                      {
                          float t = (extRes - 1.0f) / 0.3f; // t in [0,1] for extRes in [1.0,1.3]
                          resonance = t * 2.0f;  // Map from 0 to 2.0
                          rDamp = 0.6f;
                      }
                      else
                      {
                          resonance = 0.0f; // Hold resonance at its lowest value
                          // Map extRes in [0,1] to rDamp in [2.0,0.6]
                          rDamp = 0.6f + ((1.0f - extRes) / 1.0f) * (2.0f - 0.6f);
                      }
                      resonanceSmooth.setTargetValue(resonance);
                      dampingSmooth.setTargetValue(rDamp);
                      for (auto& fl : filtersLeft)
                      {
                          fl.setResonance(resonance);
                          fl.setDamping(rDamp);
                          fl.applyChangesIfNeeded();
                      }
                      for (auto& fr : filtersRight)
                      {
                          fr.setResonance(resonance);
                          fr.setDamping(rDamp);
                          fr.applyChangesIfNeeded();
                      }
                  }
                  else if (P == 2)
                  {
                      keytrackAmount = static_cast<float>(val);
                      keytrackSmooth.setTargetValue(keytrackAmount);
                      for (auto& fl : filtersLeft)
                      {
                          fl.setKeytrack(keytrackAmount);
                          fl.applyChangesIfNeeded();
                      }
                      for (auto& fr : filtersRight)
                      {
                          fr.setKeytrack(keytrackAmount);
                          fr.applyChangesIfNeeded();
                      }
                  }
              }
      
              // Parameter definitions for the UI (SVF Damping removed)
              void createParameters(ParameterDataList& data)
              {
                  {
                      parameter::data p("Cutoff Frequency", { 20.0, 20000.0, 1.0 });
                      registerCallback<0>(p);
                      p.setDefaultValue(1000.0f);
                      data.add(std::move(p));
                  }
                  {
                      parameter::data p("Resonance", { 0.0, 1.2, 0.01 });
                      registerCallback<1>(p);
                      p.setDefaultValue(1.0f);
                      data.add(std::move(p));
                  }
                  {
                      parameter::data p("Keytrack Amount", { -1.0, 1.0, 0.01 });
                      registerCallback<2>(p);
                      p.setDefaultValue(0.0f);
                      data.add(std::move(p));
                  }
              }
      
              void setExternalData(const ExternalData& data, int index) {}
      
              // Handle note on events for keytracking
              void handleHiseEvent(HiseEvent& e)
              {
                  if (e.isNoteOn())
                  {
                      filtersLeft.get().setNoteNumber(e.getNoteNumber());
                      filtersLeft.get().applyChangesIfNeeded();
      
                      filtersRight.get().setNoteNumber(e.getNoteNumber());
                      filtersRight.get().applyChangesIfNeeded();
                  }
              }
      
          private:
              PolyData<AudioEffect, NV> filtersLeft;
              PolyData<AudioEffect, NV> filtersRight;
          };
      }
      
      
      posted in C++ Development
      griffinboyG
      griffinboy
    • [Free dsp] C++ FFT

      For @ustk

      Simple FFT implementation using Juce
      (C++ scriptnode)

      https://1drv.ms/u/c/6c19b197e5968b36/EcVjEd7aayFHhItxr2gISeMBUD15DXs-oPHNg9Os9pYXWA?e=EW0gfm

      By default it's a spectral lowpass filter (silences fft bins above the cutoff).
      It has been implemented into a sampler, and into a real-time effect.

      If you want to fully understand how the scripts work, ask chat gpt to walk through the code.

      Christoph's own Hise FFT implementation is likely better: but this'll be a good starting point if you need a custom implementation. If you want to extend it, I recommend investigating a multi resolution approach (Constant Q). This simple fft uses a han window at one resolution, resulting in the general smearing of content and transients. I'd like to improve this aspect in the future.

      posted in C++ Development
      griffinboyG
      griffinboy
    • [Free Dsp] Lookahead Limiter (true peak)

      Lookahead Limiter designed for low distortion.
      It's not as fancy as Pro-L but it does the trick.
      Oversample it for True Peak limiting.

      Stereo Only
      CPU: (0.2%)

      *Important warning: DAW latency correction!
      The latency changes depending on attack time in this script, but in hise it's common to report a single latency value to the host. The solution to this is to either report the max latency to the host (measure from the max attack time), or to leave the attack time fixed, so that you can report a single latency value that won't change. You should be fine leaving it at 1 - 10 ms. A bit of attack (lookahead) is needed for smooth limiting.

      Download the script here:

      https://1drv.ms/u/c/6c19b197e5968b36/EQFgIcgl83VJviZoznFZWnEBleCXFfAD-KejdhTV9Q6IwQ?e=EyH8fM

      Setup tutorial:

      1. Create a 3rd party C++ node in HISE named "Griffin_Limiter"
      2. Compile the initial DLL in HISE using "Compile dsp networks as .dll"
      3. Replace the generated "Griffin_Limiter.h" (located in ProjectName/DspNetworks/ThirdParty) with my limiter header file
      4. Re-compile the final DLL in HISE using "Compile dsp networks as .dll"
      

      Ignore the audio artefacts in the video. My encoder is being a fool. The sound quality of the dsp is fine.

      You can read the script here:
      Griffin_Limiter.h:

      #pragma once
      #include <JuceHeader.h>
      #include <cstdint>
      #include <cmath>
      #include <vector>
      #include <algorithm>
      #include <limits>
      #include <cstring>
      
      /**
      
      ==============| by GriffinBoy (2025) |==============
      
      This node implements a Lookahead Stereo Limiter
      
      Features:
      - ExpSmootherCascade: Four-stage exponential smoothing with separate attack and release coefficients.
      - PeakHoldCascade: Eight-stage peak detection cascade for accurate envelope following.
      - Integrated lookahead
      - Parameter smoothing 
      
      Integration Steps for HISE:
      1. Create a 3rd party C++ node in HISE named " Griffin_Limiter "
      2. Compile the initial DLL in HISE using "Compile dsp networks as .dll"
      3. Replace the generated "Griffin_Limiter.h" (located in ProjectName/DspNetworks/ThirdParty) with this header file you are reading now
      4. Re-compile the final DLL in HISE using "Compile dsp networks as .dll"
      
      Author: GriffinBoy (2025)
      License: UwU
      
      Based on the following paper:
      Sanfilippo, D. (2022).Envelope following via cascaded exponential smoothers for low - distortion peak limiting and maximisation.In Proceedings of the International Faust Conference, Saint - Étienne, France.
      
      */
      
      
      namespace project
      {
      
      #ifndef M_PI
      #define M_PI 3.14159265358979323846
      #endif
      
          using namespace juce;
          using namespace hise;
          using namespace scriptnode;
      
          namespace FunctionsClasses {
      
              //------------------------------------------------------------------------------
              // DelaySmooth: A delay line with smooth crossfading between two integer delay
              // lines to produce a click-free, Doppler-free delay variation.
              // Fixed types: head = uint16_t and sample type = float.
              class DelaySmooth {
              private:
                  const size_t bufferLen = 2ul << (8 * sizeof(uint16_t) - 1); 
                  size_t delay = 0;
                  size_t interpolationTime = 1024;
                  size_t lowerDelay = 0;
                  size_t upperDelay = 0;
                  float interpolation = 0.0f;
                  float interpolationStep = 1.0f / float(interpolationTime);
                  float increment = interpolationStep;
                  uint16_t lowerReadPtr = 0;
                  uint16_t upperReadPtr = 0;
                  uint16_t writePtr = 0;
                  std::vector<float> bufferLeft;
                  std::vector<float> bufferRight;
              public:
                  void SetDelay(size_t _delay) { delay = _delay; }
                  void SetInterpolationTime(size_t _interpTime) {
                      interpolationTime = std::max<size_t>(1, _interpTime);
                      interpolationStep = 1.0f / float(interpolationTime);
                  }
                  void Reset() {
                      std::fill(bufferLeft.begin(), bufferLeft.end(), 0.0f);
                      std::fill(bufferRight.begin(), bufferRight.end(), 0.0f);
                  }
                  void Process(float** xVec, float** yVec, size_t vecLen) {
                      float* xLeft = xVec[0];
                      float* xRight = xVec[1];
                      float* yLeft = yVec[0];
                      float* yRight = yVec[1];
                      for (size_t n = 0; n < vecLen; n++) {
                          bufferLeft[writePtr] = xLeft[n];
                          bufferRight[writePtr] = xRight[n];
                          bool lowerReach = (interpolation == 0.0f);
                          bool upperReach = (interpolation == 1.0f);
                          bool lowerDelayChanged = (delay != lowerDelay);
                          bool upperDelayChanged = (delay != upperDelay);
                          bool startDownwardInterp = (upperReach && upperDelayChanged);
                          bool startUpwardInterp = (lowerReach && lowerDelayChanged);
                          float incrementPathsUp[2] = { increment, interpolationStep };
                          float incrementPathsDown[2] = { incrementPathsUp[startUpwardInterp], -interpolationStep };
                          increment = incrementPathsDown[startDownwardInterp];
                          size_t lowerDelayPaths[2] = { lowerDelay, delay };
                          size_t upperDelayPaths[2] = { upperDelay, delay };
                          lowerDelay = lowerDelayPaths[upperReach];
                          upperDelay = upperDelayPaths[lowerReach];
                          // Use explicit bitwise AND for modulo (bufferLen = 65536)
                          lowerReadPtr = static_cast<uint16_t>(writePtr - lowerDelay) & 0xFFFF;
                          upperReadPtr = static_cast<uint16_t>(writePtr - upperDelay) & 0xFFFF;
                          writePtr++;
                          interpolation = std::max(0.0f, std::min(1.0f, interpolation + increment));
                          yLeft[n] = interpolation * (bufferLeft[upperReadPtr] - bufferLeft[lowerReadPtr]) + bufferLeft[lowerReadPtr];
                          yRight[n] = interpolation * (bufferRight[upperReadPtr] - bufferRight[lowerReadPtr]) + bufferRight[lowerReadPtr];
                      }
                  }
                  DelaySmooth() {
                      bufferLeft.resize(bufferLen);
                      bufferRight.resize(bufferLen);
                  }
                  DelaySmooth(size_t _delay, size_t _interpTime) {
                      bufferLeft.resize(bufferLen);
                      bufferRight.resize(bufferLen);
                      delay = _delay;
                      interpolationTime = std::max<size_t>(1, _interpTime);
                      interpolationStep = 1.0f / float(interpolationTime);
                  }
              };
      
              //------------------------------------------------------------------------------
              // ExpSmootherCascade: Cascaded one-pole exponential smoothers (4 stages)
              // with separate attack and release coefficients.
              class ExpSmootherCascade {
              private:
                  static constexpr size_t stages = 4;
                  const float coeffCorrection = 1.0f / std::sqrt(std::pow(2.0f, 1.0f / float(stages)) - 1.0f);
                  const float epsilon = std::numeric_limits<float>::epsilon();
                  float SR = 48000.0f;
                  float T = 1.0f / SR;
                  const float twoPiC = 2.0f * static_cast<float>(M_PI) * coeffCorrection;
                  float twoPiCT = twoPiC * T;
                  float attTime = 0.001f;
                  float relTime = 0.01f;
                  float attCoeff = std::exp(-twoPiCT / attTime);
                  float relCoeff = std::exp(-twoPiCT / relTime);
                  float coeff[2] = { relCoeff, attCoeff };
                  float output[stages] = { 0.0f, 0.0f, 0.0f, 0.0f };
              public:
                  void SetSR(float _SR) {
                      SR = std::max(_SR, 1.0f);
                      T = 1.0f / SR;
                      twoPiCT = twoPiC * T;
                  }
                  void SetAttTime(float _attTime) {
                      attTime = std::max(epsilon, _attTime);
                      attCoeff = std::exp(-twoPiCT / attTime);
                      coeff[1] = attCoeff;
                  }
                  void SetRelTime(float _relTime) {
                      relTime = std::max(epsilon, _relTime);
                      relCoeff = std::exp(-twoPiCT / relTime);
                      coeff[0] = relCoeff;
                  }
                  void Reset() { std::memset(output, 0, sizeof(output)); }
                  void Process(float* xVec, float* yVec, size_t vecLen) {
                      for (size_t n = 0; n < vecLen; n++) {
                          float input = xVec[n];
                          // Unrolled stage 0
                          bool isAttackPhase = (input > output[0]);
                          float coeffVal = isAttackPhase ? attCoeff : relCoeff;
                          output[0] = input + coeffVal * (output[0] - input);
                          input = output[0];
                          // Unrolled stage 1
                          isAttackPhase = (input > output[1]);
                          coeffVal = isAttackPhase ? attCoeff : relCoeff;
                          output[1] = input + coeffVal * (output[1] - input);
                          input = output[1];
                          // Unrolled stage 2
                          isAttackPhase = (input > output[2]);
                          coeffVal = isAttackPhase ? attCoeff : relCoeff;
                          output[2] = input + coeffVal * (output[2] - input);
                          input = output[2];
                          // Unrolled stage 3
                          isAttackPhase = (input > output[3]);
                          coeffVal = isAttackPhase ? attCoeff : relCoeff;
                          output[3] = input + coeffVal * (output[3] - input);
                          yVec[n] = output[3];
                      }
                  }
                  ExpSmootherCascade() {}
                  ExpSmootherCascade(float _SR, float _attTime, float _relTime) {
                      SR = std::max(_SR, 1.0f);
                      T = 1.0f / SR;
                      twoPiCT = twoPiC * T;
                      attTime = std::max(epsilon, _attTime);
                      relTime = std::max(epsilon, _relTime);
                      attCoeff = std::exp(-twoPiCT / attTime);
                      relCoeff = std::exp(-twoPiCT / relTime);
                      coeff[0] = relCoeff;
                      coeff[1] = attCoeff;
                  }
              };
      
              //------------------------------------------------------------------------------
              // PeakHoldCascade: Cascaded peak-holders (8 stages fixed) to approximate a max filter.
              // The cascade splits the hold time to detect secondary peaks.
              class PeakHoldCascade {
              private:
                  static constexpr size_t stages = 8;
                  float SR = 48000.0f;
                  float holdTime = 0.001f;
                  const float oneOverStages = 1.0f / float(stages);
                  size_t holdTimeSamples = std::rint(holdTime * oneOverStages * SR);
                  size_t timer[stages];
                  float output[stages];
              public:
                  void SetSR(float _SR) {
                      SR = std::max(_SR, 1.0f);
                      holdTimeSamples = std::rint(holdTime * oneOverStages * SR);
                  }
                  void SetHoldTime(float _holdTime) {
                      holdTime = std::max(0.0f, _holdTime);
                      holdTimeSamples = std::rint(holdTime * oneOverStages * SR);
                  }
                  void Reset() {
                      std::memset(timer, 0, sizeof(timer));
                      std::memset(output, 0, sizeof(output));
                  }
                  void Process(float* xVec, float* yVec, size_t vecLen) {
                      for (size_t n = 0; n < vecLen; n++) {
                          float input = std::fabs(xVec[n]);
                          bool release;
                          // Unrolled stage 0
                          release = (input >= output[0]) || (timer[0] >= holdTimeSamples);
                          timer[0] = release ? 0 : (timer[0] + 1);
                          output[0] = release ? input : output[0];
                          input = output[0];
                          // Unrolled stage 1
                          release = (input >= output[1]) || (timer[1] >= holdTimeSamples);
                          timer[1] = release ? 0 : (timer[1] + 1);
                          output[1] = release ? input : output[1];
                          input = output[1];
                          // Unrolled stage 2
                          release = (input >= output[2]) || (timer[2] >= holdTimeSamples);
                          timer[2] = release ? 0 : (timer[2] + 1);
                          output[2] = release ? input : output[2];
                          input = output[2];
                          // Unrolled stage 3
                          release = (input >= output[3]) || (timer[3] >= holdTimeSamples);
                          timer[3] = release ? 0 : (timer[3] + 1);
                          output[3] = release ? input : output[3];
                          input = output[3];
                          // Unrolled stage 4
                          release = (input >= output[4]) || (timer[4] >= holdTimeSamples);
                          timer[4] = release ? 0 : (timer[4] + 1);
                          output[4] = release ? input : output[4];
                          input = output[4];
                          // Unrolled stage 5
                          release = (input >= output[5]) || (timer[5] >= holdTimeSamples);
                          timer[5] = release ? 0 : (timer[5] + 1);
                          output[5] = release ? input : output[5];
                          input = output[5];
                          // Unrolled stage 6
                          release = (input >= output[6]) || (timer[6] >= holdTimeSamples);
                          timer[6] = release ? 0 : (timer[6] + 1);
                          output[6] = release ? input : output[6];
                          input = output[6];
                          // Unrolled stage 7
                          release = (input >= output[7]) || (timer[7] >= holdTimeSamples);
                          timer[7] = release ? 0 : (timer[7] + 1);
                          output[7] = release ? input : output[7];
                          yVec[n] = output[7];
                      }
                  }
                  PeakHoldCascade() { Reset(); }
                  PeakHoldCascade(float _SR, float _holdTime) {
                      SR = std::max(_SR, 1.0f);
                      holdTime = _holdTime;
                      holdTimeSamples = std::rint(holdTime * oneOverStages * SR);
                      Reset();
                  }
              };
      
              //------------------------------------------------------------------------------
              // Limiter: Lookahead peak-limiter combining DelaySmooth, PeakHoldCascade, and
              // ExpSmootherCascade. Computes a stereo envelope and applies a gain to keep
              // signal peaks below a given threshold.
              template<typename real>
              class Limiter {
              private:
                  float SR = 48000.0f;
                  float T = 1.0f / SR;
                  const float twoPi = 2.0f * static_cast<float>(M_PI);
                  const float epsilon = std::numeric_limits<float>::epsilon();
                  const float smoothParamCutoff = 20.0f;
                  float attack = 0.01f;
                  float hold = 0.0f;
                  float release = 0.05f;
                  float dBThreshold = -6.0f;
                  float linThreshold = std::pow(10.0f, dBThreshold * 0.05f);
                  float dBPreGain = 0.0f;
                  float linPreGain = 1.0f;
                  float smoothPreGain = 0.0f;
                  float smoothThreshold = 0.0f;
                  float smoothParamCoeff = std::exp(-twoPi * smoothParamCutoff * T);
                  size_t lookaheadDelay = 0;
                  DelaySmooth delay;
                  static constexpr size_t numberOfPeakHoldSections = 8;
                  static constexpr size_t numberOfSmoothSections = 4;
                  const float oneOverPeakSections = 1.0f / float(numberOfPeakHoldSections);
                  PeakHoldCascade peakHolder;
                  ExpSmootherCascade expSmoother;
              public:
                  void SetSR(float _SR) {
                      SR = std::max(_SR, 1.0f);
                      T = 1.0f / SR;
                      smoothParamCoeff = std::exp(-twoPi * smoothParamCutoff * T);
                      peakHolder.SetSR(SR);
                      expSmoother.SetSR(SR);
                  }
                  void SetAttTime(float _attack) {
                      attack = std::max(epsilon, _attack);
                      lookaheadDelay = std::rint(attack * oneOverPeakSections * SR) * numberOfPeakHoldSections;
                      delay.SetDelay(lookaheadDelay);
                      delay.SetInterpolationTime(lookaheadDelay);
                      expSmoother.SetAttTime(attack);
                      peakHolder.SetHoldTime(attack + hold);
                  }
                  void SetHoldTime(float _hold) {
                      hold = std::max(0.0f, _hold);
                      peakHolder.SetHoldTime(attack + hold);
                  }
                  void SetRelTime(float _release) {
                      release = std::max(epsilon, _release);
                      expSmoother.SetRelTime(release);
                  }
                  void SetThreshold(float _threshold) {
                      dBThreshold = std::max(-120.0f, _threshold);
                      linThreshold = std::pow(10.0f, dBThreshold * 0.05f);
                  }
                  void SetPreGain(float _preGain) {
                      dBPreGain = _preGain;
                      linPreGain = std::pow(10.0f, dBPreGain * 0.05f);
                  }
                  void Reset() {
                      delay.Reset();
                      peakHolder.Reset();
                      expSmoother.Reset();
                  }
                  // Process takes separate input and output stereo buffers.
                  // The design uses an in-place delay so the input buffer is overwritten.
                  void Process(float** xVec, float** yVec, size_t vecLen) {
                      // Get channel pointers once outside loops.
                      float* xLeft = xVec[0];
                      float* xRight = xVec[1];
                      float* yLeft = yVec[0];
                      float* yRight = yVec[1];
                      // Merge pre-gain smoothing and envelope computation.
                      for (size_t n = 0; n < vecLen; n++) {
                          smoothPreGain = linPreGain + smoothParamCoeff * (smoothPreGain - linPreGain);
                          xLeft[n] *= smoothPreGain;
                          xRight[n] *= smoothPreGain;
                          yLeft[n] = std::max(std::fabs(xLeft[n]), std::fabs(xRight[n]));
                      }
                      // Process envelope with peak-hold cascade.
                      peakHolder.Process(yLeft, yLeft, vecLen);
                      // Smooth and clip envelope to threshold.
                      for (size_t n = 0; n < vecLen; n++) {
                          smoothThreshold = linThreshold + smoothParamCoeff * (smoothThreshold - linThreshold);
                          yLeft[n] = std::max(yLeft[n], smoothThreshold);
                          yRight[n] = smoothThreshold;
                      }
                      // Smooth envelope with exponential cascade.
                      expSmoother.Process(yLeft, yLeft, vecLen);
                      // Apply lookahead delay (in-place).
                      delay.Process(xVec, xVec, vecLen);
                      // Compute attenuation gain and apply to delayed signal in one loop.
                      for (size_t n = 0; n < vecLen; n++) {
                          float gain = yRight[n] / yLeft[n];
                          yLeft[n] = gain * xLeft[n];
                          yRight[n] = gain * xRight[n];
                      }
                  }
                  Limiter() {}
                  Limiter(float _SR, float _dBPreGain, float _attack, float _hold, float _release, float _dBThreshold) {
                      SR = std::max(_SR, 1.0f);
                      dBPreGain = _dBPreGain;
                      attack = std::max(epsilon, _attack);
                      hold = std::max(0.0f, _hold);
                      release = std::max(epsilon, _release);
                      dBThreshold = std::max(-120.0f, _dBThreshold);
                  }
              };
      
          } // end namespace FunctionsClasses
      
          //------------------------------------------------------------------------------
          // SNEX Node - Stereo Limiter Node Implementation
          //------------------------------------------------------------------------------
          template <int NV>
          struct Griffin_Limiter : public data::base
          {
              SNEX_NODE(Griffin_Limiter);
      
              struct MetadataClass
              {
                  SN_NODE_ID("Griffin_Limiter");
              };
      
              // Node Properties 
              static constexpr bool isModNode() { return false; }
              static constexpr bool isPolyphonic() { return NV > 1; }
              static constexpr bool hasTail() { return false; }
              static constexpr bool isSuspendedOnSilence() { return false; }
              static constexpr int getFixChannelAmount() { return 2; }
      
              static constexpr int NumTables = 0;
              static constexpr int NumSliderPacks = 0;
              static constexpr int NumAudioFiles = 0;
              static constexpr int NumFilters = 0;
              static constexpr int NumDisplayBuffers = 0;
      
              // Create an instance of our DSP Limiter 
              FunctionsClasses::Limiter<float> limiter;
      
              // Scratch buffers to avoid per-block allocation.
          private:
              std::vector<float> scratchInLeft, scratchInRight;
              std::vector<float> scratchOutLeft, scratchOutRight;
          public:
              //--------------------------------------------------------------------------
              // Main Processing Functions
              //--------------------------------------------------------------------------
              void prepare(PrepareSpecs specs)
              {
                  float sampleRate = specs.sampleRate;
                  limiter.SetSR(sampleRate);
                  limiter.Reset();
                  // Preallocate scratch buffers (use maximum BlockSize if available, otherwise default to 512).
                  int blockSize = (specs.blockSize > 0) ? specs.blockSize : 512;
                  scratchInLeft.resize(blockSize);
                  scratchInRight.resize(blockSize);
                  scratchOutLeft.resize(blockSize);
                  scratchOutRight.resize(blockSize);
              }
      
              void reset() {}
      
              template <typename ProcessDataType>
              inline void process(ProcessDataType& data)
              {
                  auto& fixData = data.template as<ProcessData<getFixChannelAmount()>>();
                  auto audioBlock = fixData.toAudioBlock();
                  float* leftChannelData = audioBlock.getChannelPointer(0);
                  float* rightChannelData = audioBlock.getChannelPointer(1);
                  int numSamples = data.getNumSamples();
      
                  juce::FloatVectorOperations::copy(scratchInLeft.data(), leftChannelData, numSamples);
                  juce::FloatVectorOperations::copy(scratchInRight.data(), rightChannelData, numSamples);
      
                  float* inBuffers[2] = { scratchInLeft.data(), scratchInRight.data() };
                  float* outBuffers[2] = { scratchOutLeft.data(), scratchOutRight.data() };
      
                  limiter.Process(inBuffers, outBuffers, numSamples);
      
                  juce::FloatVectorOperations::copy(leftChannelData, scratchOutLeft.data(), numSamples);
                  juce::FloatVectorOperations::copy(rightChannelData, scratchOutRight.data(), numSamples);
              }
      
              //--------------------------------------------------------------------------
              // Parameter Handling
              //--------------------------------------------------------------------------
              template <int P>
              void setParameter(double v)
              {
                  if (P == 0) {
                      limiter.SetPreGain(static_cast<float>(v));
                  }
                  else if (P == 1) {
                      // Convert from ms to seconds.
                      limiter.SetAttTime(static_cast<float>(v * 0.001));
                  }
                  else if (P == 2) {
                      limiter.SetHoldTime(static_cast<float>(v * 0.001));
                  }
                  else if (P == 3) {
                      limiter.SetRelTime(static_cast<float>(v * 0.001));
                  }
                  else if (P == 4) {
                      limiter.SetThreshold(static_cast<float>(v));
                  }
              }
      
              void createParameters(ParameterDataList& data)
              {
                  {
                      parameter::data p("PreGain (dB)", { -24.0, 24.0, 0.1 });
                      registerCallback<0>(p);
                      p.setDefaultValue(0.0);
                      data.add(std::move(p));
                  }
                  {
                      parameter::data p("Attack (ms)", { 1.0, 500.0, 1.0 });
                      registerCallback<1>(p);
                      p.setDefaultValue(10.0);
                      p.setSkewForCentre(80.0f);
                      data.add(std::move(p));
                  }
                  {
                      parameter::data p("Hold (ms)", { 0.0, 100.0, 1.0 });
                      registerCallback<2>(p);
                      p.setDefaultValue(5.0);
                      p.setSkewForCentre(30.0f);
                      data.add(std::move(p));
                  }
                  {
                      parameter::data p("Release (ms)", { 1.0, 2500.0, 1.0 });
                      registerCallback<3>(p);
                      p.setDefaultValue(80.0);
                      p.setSkewForCentre(800.0f);
                      data.add(std::move(p));
                  }
                  {
                      parameter::data p("Ceiling (dB)", { -60.0, 0.0, 0.1 });
                      registerCallback<4>(p);
                      p.setDefaultValue(-6.0);
                      data.add(std::move(p));
                  }
              }
      
              void setExternalData(const ExternalData& ed, int index)
              {
                  // Not needed.
              }
      
              void handleHiseEvent(HiseEvent& e)
              {
                  // Not needed.
              }
      
              template <typename FrameDataType>
              void processFrame(FrameDataType& data)
              {
                  // Not needed.
              }
          };
      
      } // end namespace project
      
      posted in C++ Development
      griffinboyG
      griffinboy
    • RE: What is the process for writing my own module (not scriptnode)

      @Christoph-Hart

      Thanks, I'm already making use of the new Global Cable feature!
      It works great.

      Here we are sending the drawing straight from Hise into a c++ node for playback!

      posted in C++ Development
      griffinboyG
      griffinboy
    • RE: About C++ Nodes

      @spider

      Okay I solved it.
      I think I'll make a whole video about this process later for any noobs like myself.

      posted in ScriptNode
      griffinboyG
      griffinboy
    • [Free Dsp] Unfinished Self Oscillating Filter

      A work in progress analog filter.

      • Requires oversampling or the high frequencies will alias. You can hear this in the video when the cutoff goes really high.

      • This node uses a lot of CPU (2%-13%) and has an inaccurate cutoff frequency.

      I'm releasing it now because I probably won't give out the code when it's finished.
      However I thought it may be fun for someone to mess with or expand upon.

      Although it's a flawed design, you can replace the nonlinearity with any distortion element. You can also tap out audio from any of the stages. Here we tap out of the final stage, but you may take audio from anywhere in the circuit matrix... So there are at least a few things to play with in the design.



      Griffin_Growl_Stereo.h

      #pragma once
      #include <JuceHeader.h>
      #include <cmath>
      #include <array>
      #include <algorithm>
      
      #ifndef M_PI
      #define M_PI 3.14159265358979323846
      #endif
      
      #ifndef NOISE_FEEDBACK_VOLUME
      #define NOISE_FEEDBACK_VOLUME 0.008f
      #endif
      
      #ifndef INPUT_SIGNAL_THRESHOLD
      #define INPUT_SIGNAL_THRESHOLD 1e-6f
      #endif
      
      // Fast tanh approximation
      struct TanhHelper {
          static inline float tanh(float x) {
              float x2 = x * x;
              float sh = x * (1.f + x2 * (1.f / 6.f + x2 * (1.f / 120.f)));
              return sh / std::sqrt(1.f + sh * sh);
          }
      };
      
      // Transistor nonlinearity lookup table for (2/M_PI)*atan(7.5*x)
      namespace transistorHelpers {
          inline float lookupAdvancedTransistorNonlinearity(float x) {
              static const int TABLE_SIZE = 4096;
              static const float maxInput = 2.0f;
              static const float invStep = (TABLE_SIZE - 1) / (2.0f * maxInput);
              static float lookupTable[TABLE_SIZE];
              static bool tableInitialized = false;
              if (!tableInitialized) {
                  const float step = 2.0f * maxInput / (TABLE_SIZE - 1);
                  for (int i = 0; i < TABLE_SIZE; i++) {
                      float xi = -maxInput + i * step;
                      lookupTable[i] = (2.0f / M_PI) * std::atan(7.5f * xi);
                  }
                  tableInitialized = true;
              }
              float clampedX = std::clamp(x, -maxInput, maxInput);
              float index = (clampedX + maxInput) * invStep;
              int indexInt = static_cast<int>(index);
              float frac = index - indexInt;
              return lookupTable[indexInt] * (1.f - frac) + lookupTable[indexInt + 1] * frac;
          }
          inline float advancedTransistorNonlinearity(float x, float /*drive*/) {
              return lookupAdvancedTransistorNonlinearity(x);
          }
      }
      
      namespace project {
          using namespace juce;
          using namespace hise;
          using namespace scriptnode;
      
          // Stereo filter using Newton-Raphson iteration.
          // Caches the filter coefficient (cachedBaseG) and maintains separate states for left/right channels.
          class JunoFilterStereo {
          public:
              JunoFilterStereo()
                  : cutoff(1000.f), resonance(1.f), drive(7.5f), sr(44100.0),
                  errorThresh(0.000001f), cachedBaseG(std::tan(1000.f * M_PI / 44100.0))
              {
                  for (int i = 0; i < 4; ++i) {
                      yL[i] = 0.f;
                      yR[i] = 0.f;
                  }
                  sL[0] = sL[1] = sL[2] = sL[3] = 0.f;
                  sR[0] = sR[1] = sR[2] = sR[3] = 0.f;
              }
              inline void setCutoff(float c) {
                  if (cutoff != c) {
                      cutoff = c;
                      cachedBaseG = std::tan(cutoff * M_PI / sr);
                  }
              }
              inline void setResonance(float r) { resonance = r; }
              inline void setDrive(float) { drive = 7.5f; }
              inline void prepare(double sr_) {
                  sr = sr_;
                  cachedBaseG = std::tan(cutoff * M_PI / sr);
              }
              inline void reset() {
                  for (int i = 0; i < 4; ++i) {
                      yL[i] = 0.f;
                      yR[i] = 0.f;
                  }
                  sL[0] = sL[1] = sL[2] = sL[3] = 0.f;
                  sR[0] = sR[1] = sR[2] = sR[3] = 0.f;
              }
              // Process one stereo sample; returns {left, right}.
              inline std::pair<float, float> processSample(float inL, float inR) {
                  const float g = cachedBaseG;
                  // Left channel
                  const float noiseL = (NOISE_FEEDBACK_VOLUME > 0.f && std::abs(inL) > INPUT_SIGNAL_THRESHOLD) ?
                      NOISE_FEEDBACK_VOLUME * (randGen.nextFloat() * 2.f - 1.f) : 0.f;
                  for (int iter = 0; iter < 20; ++iter) {
                      const float prev_yL3 = yL[3];
                      float nl0 = transistorHelpers::advancedTransistorNonlinearity(inL - yL[0] - resonance * yL[3] + noiseL, drive);
                      float nl1 = transistorHelpers::advancedTransistorNonlinearity(yL[0] - yL[1], drive);
                      float nl2 = transistorHelpers::advancedTransistorNonlinearity(yL[1] - yL[2], drive);
                      float nl3 = transistorHelpers::advancedTransistorNonlinearity(yL[2] - yL[3], drive);
                      float f0 = g * nl0 + sL[0] - yL[0];
                      float f1 = g * nl1 + sL[1] - yL[1];
                      float f2 = g * nl2 + sL[2] - yL[2];
                      float f3 = g * nl3 + sL[3] - yL[3];
                      float h0 = 1.f - nl0 * nl0;
                      float h1 = 1.f - nl1 * nl1;
                      float h2 = 1.f - nl2 * nl2;
                      float h3 = 1.f - nl3 * nl3;
                      float j00 = -g * h0 - 1.f;
                      float j03 = -g * resonance * h0;
                      float j10 = g * h1;
                      float j11 = -g * h1 - 1.f;
                      float j21 = g * h2;
                      float j22 = -g * h2 - 1.f;
                      float j32 = g * h3;
                      float j33 = -g * h3 - 1.f;
                      float den = j00 * j11 * j22 * j33 - j03 * j10 * j21 * j32;
                      yL[0] += (f1 * j03 * j21 * j32 - f0 * j11 * j22 * j33 - f2 * j03 * j11 * j32 + f3 * j03 * j11 * j22) / den;
                      yL[1] += (f0 * j10 * j22 * j33 - f1 * j00 * j22 * j33 + f2 * j03 * j10 * j32 - f3 * j03 * j10 * j22) / den;
                      yL[2] += (f1 * j00 * j21 * j33 - f0 * j10 * j21 * j33 - f2 * j00 * j11 * j33 + f3 * j03 * j10 * j21) / den;
                      yL[3] += (f0 * j10 * j21 * j32 - f1 * j00 * j21 * j32 + f2 * j00 * j11 * j32 - f3 * j00 * j11 * j22) / den;
                      if (std::abs(yL[3] - prev_yL3) <= errorThresh)
                          break;
                  }
                  sL[0] = 2.f * yL[0] - sL[0];
                  sL[1] = 2.f * yL[1] - sL[1];
                  sL[2] = 2.f * yL[2] - sL[2];
                  sL[3] = 2.f * yL[3] - sL[3];
                  // Right channel
                  const float noiseR = (NOISE_FEEDBACK_VOLUME > 0.f && std::abs(inR) > INPUT_SIGNAL_THRESHOLD) ?
                      NOISE_FEEDBACK_VOLUME * (randGen.nextFloat() * 2.f - 1.f) : 0.f;
                  for (int iter = 0; iter < 20; ++iter) {
                      const float prev_yR3 = yR[3];
                      float nl0 = transistorHelpers::advancedTransistorNonlinearity(inR - yR[0] - resonance * yR[3] + noiseR, drive);
                      float nl1 = transistorHelpers::advancedTransistorNonlinearity(yR[0] - yR[1], drive);
                      float nl2 = transistorHelpers::advancedTransistorNonlinearity(yR[1] - yR[2], drive);
                      float nl3 = transistorHelpers::advancedTransistorNonlinearity(yR[2] - yR[3], drive);
                      float f0 = g * nl0 + sR[0] - yR[0];
                      float f1 = g * nl1 + sR[1] - yR[1];
                      float f2 = g * nl2 + sR[2] - yR[2];
                      float f3 = g * nl3 + sR[3] - yR[3];
                      float h0 = 1.f - nl0 * nl0;
                      float h1 = 1.f - nl1 * nl1;
                      float h2 = 1.f - nl2 * nl2;
                      float h3 = 1.f - nl3 * nl3;
                      float j00 = -g * h0 - 1.f;
                      float j03 = -g * resonance * h0;
                      float j10 = g * h1;
                      float j11 = -g * h1 - 1.f;
                      float j21 = g * h2;
                      float j22 = -g * h2 - 1.f;
                      float j32 = g * h3;
                      float j33 = -g * h3 - 1.f;
                      float den = j00 * j11 * j22 * j33 - j03 * j10 * j21 * j32;
                      yR[0] += (f1 * j03 * j21 * j32 - f0 * j11 * j22 * j33 - f2 * j03 * j11 * j32 + f3 * j03 * j11 * j22) / den;
                      yR[1] += (f0 * j10 * j22 * j33 - f1 * j00 * j22 * j33 + f2 * j03 * j10 * j32 - f3 * j03 * j10 * j22) / den;
                      yR[2] += (f1 * j00 * j21 * j33 - f0 * j10 * j21 * j33 - f2 * j00 * j11 * j33 + f3 * j03 * j10 * j21) / den;
                      yR[3] += (f0 * j10 * j21 * j32 - f1 * j00 * j21 * j32 + f2 * j00 * j11 * j32 - f3 * j00 * j11 * j22) / den;
                      if (std::abs(yR[3] - prev_yR3) <= errorThresh)
                          break;
                  }
                  sR[0] = 2.f * yR[0] - sR[0];
                  sR[1] = 2.f * yR[1] - sR[1];
                  sR[2] = 2.f * yR[2] - sR[2];
                  sR[3] = 2.f * yR[3] - sR[3];
                  return { yL[3], yR[3] };
              }
          private:
              double sr;
              float cutoff, resonance, drive, errorThresh;
              float cachedBaseG;
              float yL[4], sL[4];
              float yR[4], sR[4];
              juce::Random randGen;
          };
      
          // Polyphonic stereo node.
          template <int NV>
          struct Griffin_Growl_Stereo : public data::base {
              SNEX_NODE(Griffin_Growl_Stereo);
              struct MetadataClass { SN_NODE_ID("Griffin_Growl_Stereo"); };
              static constexpr bool isModNode() { return false; }
              static constexpr bool isPolyphonic() { return NV > 1; }
              static constexpr bool hasTail() { return false; }
              static constexpr bool isSuspendedOnSilence() { return false; }
              static constexpr int getFixChannelAmount() { return 2; }
              static constexpr int NumTables = 0, NumSliderPacks = 0, NumAudioFiles = 0, NumFilters = 0, NumDisplayBuffers = 0;
      
              float cutoffFrequency = 1000.f, resonance = 1.f;
              PolyData<JunoFilterStereo, NV> filters;
      
              inline void prepare(PrepareSpecs specs) {
                  double sr = specs.sampleRate;
                  filters.prepare(specs);
                  for (auto& voice : filters) {
                      voice.prepare(sr);
                      voice.setDrive(7.5f);
                  }
              }
              inline void reset() { for (auto& voice : filters) voice.reset(); }
      
              // Process block: scale inputs using fast tanh, process with filter, output stereo.
              template <typename ProcessDataType>
              inline void process(ProcessDataType& data) {
                  auto& fixData = data.template as<ProcessData<getFixChannelAmount()>>();
                  auto audioBlock = fixData.toAudioBlock();
                  float* leftChannel = audioBlock.getChannelPointer(0);
                  float* rightChannel = audioBlock.getChannelPointer(1);
                  const int numSamples = static_cast<int>(data.getNumSamples());
                  const float tanhConst = TanhHelper::tanh(1.5f);
                  for (int i = 0; i < numSamples; ++i) {
                      float inL = TanhHelper::tanh(1.5f * leftChannel[i]) / tanhConst;
                      float inR = TanhHelper::tanh(1.5f * rightChannel[i]) / tanhConst;
                      float outL = 0.f, outR = 0.f;
                      for (auto& voice : filters) {
                          auto outs = voice.processSample(inL, inR);
                          outL += outs.first;
                          outR += outs.second;
                      }
                      outL /= NV;
                      outR /= NV;
                      leftChannel[i] = outL;
                      rightChannel[i] = outR;
                  }
              }
              template <typename FrameDataType>
              inline void processFrame(FrameDataType& data) {}
      
              // Parameter callback: update voices on change.
              template <int P>
              inline void setParameter(double v) {
                  if (P == 0) {
                      float newVal = static_cast<float>(v);
                      if (cutoffFrequency != newVal) {
                          cutoffFrequency = newVal;
                          for (auto& voice : filters)
                              voice.setCutoff(cutoffFrequency);
                      }
                  }
                  else if (P == 1) {
                      float newVal = static_cast<float>(v);
                      if (resonance != newVal) {
                          resonance = newVal;
                          for (auto& voice : filters)
                              voice.setResonance(resonance);
                      }
                  }
              }
              inline void createParameters(ParameterDataList& data) {
                  parameter::data p1("Cutoff", { 20.0, 4000.0, 0.00001 });
                  registerCallback<0>(p1);
                  p1.setDefaultValue(1000.0);
                  data.add(std::move(p1));
                  parameter::data p2("Resonance", { 0.1, 4.3, 0.00001 });
                  registerCallback<1>(p2);
                  p2.setDefaultValue(1.0);
                  data.add(std::move(p2));
              }
              inline void setExternalData(const ExternalData& ed, int index) {}
              inline void handleHiseEvent(HiseEvent& e) {}
          };
      }
      

      Griffin_Growl_Mono.h

      #pragma once
      #include <JuceHeader.h>
      #include <cmath>
      #include <array>
      #include <algorithm>
      
      #ifndef M_PI
      #define M_PI 3.14159265358979323846
      #endif
      
      #ifndef NOISE_FEEDBACK_VOLUME
      #define NOISE_FEEDBACK_VOLUME 0.008f
      #endif
      
      #ifndef INPUT_SIGNAL_THRESHOLD
      #define INPUT_SIGNAL_THRESHOLD 1e-6f
      #endif
      
      // Fast tanh approximation 
      struct TanhHelper {
          static inline float tanh(float x) {
              float x2 = x * x;
              float sh = x * (1.f + x2 * (1.f / 6.f + x2 * (1.f / 120.f)));
              return sh / std::sqrt(1.f + sh * sh);
          }
      };
      
      // Transistor nonlinearity lookup table for (2/M_PI)*atan(7.5*x)
      namespace transistorHelpers {
          inline float lookupAdvancedTransistorNonlinearity(float x) {
              static const int TABLE_SIZE = 4096;
              static const float maxInput = 2.0f;
              static const float invStep = (TABLE_SIZE - 1) / (2.0f * maxInput);
              static float lookupTable[TABLE_SIZE];
              static bool tableInitialized = false;
              if (!tableInitialized) {
                  const float step = 2.0f * maxInput / (TABLE_SIZE - 1);
                  for (int i = 0; i < TABLE_SIZE; i++) {
                      float xi = -maxInput + i * step;
                      lookupTable[i] = (2.0f / M_PI) * std::atan(7.5f * xi);
                  }
                  tableInitialized = true;
              }
              float clampedX = std::clamp(x, -maxInput, maxInput);
              float index = (clampedX + maxInput) * invStep;
              int indexInt = static_cast<int>(index);
              float frac = index - indexInt;
              return lookupTable[indexInt] * (1.f - frac) + lookupTable[indexInt + 1] * frac;
          }
          inline float advancedTransistorNonlinearity(float x, float /*drive*/) {
              return lookupAdvancedTransistorNonlinearity(x);
          }
      }
      
      namespace project {
          using namespace juce;
          using namespace hise;
          using namespace scriptnode;
      
          // Mono filter using Newton-Raphson iteration.
          // The filter coefficient is cached (cachedBaseG) and updated only when cutoff or sr change.
          class JunoFilterMono {
          public:
              JunoFilterMono()
                  : cutoff(1000.f), resonance(1.f), drive(7.5f), sr(44100.0),
                  errorThresh(0.000001f), cachedBaseG(std::tan(1000.f * M_PI / 44100.0))
              {
                  for (int i = 0; i < 4; ++i)
                      y[i] = 0.f;
                  s[0] = s[1] = s[2] = s[3] = 0.f;
              }
              inline void setCutoff(float c) {
                  if (cutoff != c) {
                      cutoff = c;
                      cachedBaseG = std::tan(cutoff * M_PI / sr);
                  }
              }
              inline void setResonance(float r) { resonance = r; }
              inline void setDrive(float) { drive = 7.5f; }
              inline void prepare(double sr_) {
                  sr = sr_;
                  cachedBaseG = std::tan(cutoff * M_PI / sr);
              }
              inline void reset() {
                  for (int i = 0; i < 4; ++i)
                      y[i] = 0.f;
                  s[0] = s[1] = s[2] = s[3] = 0.f;
              }
      
              // Process one sample using cached filter coefficient.
              inline float processSample(float in) {
                  // Use precomputed base coefficient (cachedBaseG) for all stages.
                  const float g = cachedBaseG;
                  // Generate noise only if input is nonzero.
                  const float noise = (NOISE_FEEDBACK_VOLUME > 0.f && std::abs(in) > INPUT_SIGNAL_THRESHOLD) ?
                      NOISE_FEEDBACK_VOLUME * (randGen.nextFloat() * 2.f - 1.f) : 0.f;
                  // Newton-Raphson iteration (max 20 iterations)
                  for (int iter = 0; iter < 20; ++iter) {
                      const float prev_y3 = y[3];
                      const float nl0 = transistorHelpers::advancedTransistorNonlinearity(in - y[0] - resonance * y[3] + noise, drive);
                      const float nl1 = transistorHelpers::advancedTransistorNonlinearity(y[0] - y[1], drive);
                      const float nl2 = transistorHelpers::advancedTransistorNonlinearity(y[1] - y[2], drive);
                      const float nl3 = transistorHelpers::advancedTransistorNonlinearity(y[2] - y[3], drive);
                      const float f0 = g * nl0 + s[0] - y[0];
                      const float f1 = g * nl1 + s[1] - y[1];
                      const float f2 = g * nl2 + s[2] - y[2];
                      const float f3 = g * nl3 + s[3] - y[3];
                      const float h0 = 1.f - nl0 * nl0;
                      const float h1 = 1.f - nl1 * nl1;
                      const float h2 = 1.f - nl2 * nl2;
                      const float h3 = 1.f - nl3 * nl3;
                      const float j00 = -g * h0 - 1.f;
                      const float j03 = -g * resonance * h0;
                      const float j10 = g * h1;
                      const float j11 = -g * h1 - 1.f;
                      const float j21 = g * h2;
                      const float j22 = -g * h2 - 1.f;
                      const float j32 = g * h3;
                      const float j33 = -g * h3 - 1.f;
                      const float den = j00 * j11 * j22 * j33 - j03 * j10 * j21 * j32;
                      y[0] += (f1 * j03 * j21 * j32 - f0 * j11 * j22 * j33 - f2 * j03 * j11 * j32 + f3 * j03 * j11 * j22) / den;
                      y[1] += (f0 * j10 * j22 * j33 - f1 * j00 * j22 * j33 + f2 * j03 * j10 * j32 - f3 * j03 * j10 * j22) / den;
                      y[2] += (f1 * j00 * j21 * j33 - f0 * j10 * j21 * j33 - f2 * j00 * j11 * j33 + f3 * j03 * j10 * j21) / den;
                      y[3] += (f0 * j10 * j21 * j32 - f1 * j00 * j21 * j32 + f2 * j00 * j11 * j32 - f3 * j00 * j11 * j22) / den;
                      if (std::abs(y[3] - prev_y3) <= errorThresh)
                          break;
                  }
                  s[0] = 2.f * y[0] - s[0];
                  s[1] = 2.f * y[1] - s[1];
                  s[2] = 2.f * y[2] - s[2];
                  s[3] = 2.f * y[3] - s[3];
                  return y[3];
              }
          private:
              double sr;
              float cutoff, resonance, drive, errorThresh;
              float cachedBaseG;
              float y[4], s[4];
              juce::Random randGen;
          };
      
          // Polyphonic mono node.
          template <int NV>
          struct Griffin_Growl_Mono : public data::base {
              SNEX_NODE(Griffin_Growl_Mono);
              struct MetadataClass { SN_NODE_ID("Griffin_Growl_Mono"); };
              static constexpr bool isModNode() { return false; }
              static constexpr bool isPolyphonic() { return NV > 1; }
              static constexpr bool hasTail() { return false; }
              static constexpr bool isSuspendedOnSilence() { return false; }
              static constexpr int getFixChannelAmount() { return 2; }
              static constexpr int NumTables = 0, NumSliderPacks = 0, NumAudioFiles = 0, NumFilters = 0, NumDisplayBuffers = 0;
      
              float cutoffFrequency = 1000.f, resonance = 1.f;
              PolyData<JunoFilterMono, NV> filters;
      
              // Prepare voices; update sample rate only.
              inline void prepare(PrepareSpecs specs) {
                  double sr = specs.sampleRate;
                  filters.prepare(specs);
                  for (auto& voice : filters) {
                      voice.prepare(sr);
                      voice.setDrive(7.5f);
                  }
              }
              inline void reset() { for (auto& voice : filters) voice.reset(); }
      
              // Process audio block: apply fast tanh scaling, sum voices, process with filter, copy mono output to both channels.
              template <typename ProcessDataType>
              inline void process(ProcessDataType& data) {
                  auto& fixData = data.template as<ProcessData<getFixChannelAmount()>>();
                  auto audioBlock = fixData.toAudioBlock();
                  float* leftChannel = audioBlock.getChannelPointer(0);
                  float* rightChannel = audioBlock.getChannelPointer(1);
                  const int numSamples = static_cast<int>(data.getNumSamples());
                  const float tanhConst = TanhHelper::tanh(1.5f);
                  for (int i = 0; i < numSamples; ++i) {
                      float in = TanhHelper::tanh(1.5f * leftChannel[i]) / tanhConst;
                      float out = 0.f;
                      for (auto& voice : filters)
                          out += voice.processSample(in);
                      out /= NV;
                      leftChannel[i] = out;
                      rightChannel[i] = out;
                  }
              }
              template <typename FrameDataType>
              inline void processFrame(FrameDataType& data) {}
      
              // Parameter callback: update voices on change.
              template <int P>
              inline void setParameter(double v) {
                  if (P == 0) {
                      float newVal = static_cast<float>(v);
                      if (cutoffFrequency != newVal) {
                          cutoffFrequency = newVal;
                          for (auto& voice : filters)
                              voice.setCutoff(cutoffFrequency);
                      }
                  }
                  else if (P == 1) {
                      float newVal = static_cast<float>(v);
                      if (resonance != newVal) {
                          resonance = newVal;
                          for (auto& voice : filters)
                              voice.setResonance(resonance);
                      }
                  }
              }
              inline void createParameters(ParameterDataList& data) {
                  parameter::data p1("Cutoff", { 20.0, 4000.0, 0.00001 });
                  registerCallback<0>(p1);
                  p1.setDefaultValue(1000.0);
                  data.add(std::move(p1));
                  parameter::data p2("Resonance", { 0.1, 4.3, 0.00001 });
                  registerCallback<1>(p2);
                  p2.setDefaultValue(0.8);
                  data.add(std::move(p2));
              }
              inline void setExternalData(const ExternalData& ed, int index) {}
              inline void handleHiseEvent(HiseEvent& e) {}
          };
      }
      
      posted in C++ Development
      griffinboyG
      griffinboy
    • RE: Help me understand Waveshaping

      @ccbl

      Clipping is waveshaping.

      Waveshaping is taking an input sample and mapping it to an output sample.

      Audio samples make up waveforms.
      Samples range from -1 to 1, and an audio file is an array of these numbers. A sine wave for example could start at 0, increase to 1 and then back to 0, then to -1 then to 0, and repeat.

      Waveshaping basically looks at the current sample, say this sample is 0.75, and it maps this to a different sample value and outputs that value instead.
      This is raw digital distortion of the wave. You basically take a wave shape, and transform each point in order to end up at a different wave.

      Often continuous functions are used.
      309ca949-50b6-45b0-89cd-88c5bba445e2-image.png
      So that you get a smooth transformation.
      Waveshaping is linear and memoryless.

      Waveshaping is static and will generally not sound like a guitar amp.
      Because analog amps are nonlinear and will have a different effect depending on past audio. Rather than just looking at the current sample and transforming it.

      posted in General Questions
      griffinboyG
      griffinboy
    • Add XSIMD to hi_tools by default?

      Can we have a better way to include XSIMD in a C++ node please?

      I find myself using XSIMD more and more lately in my c++ nodes (for Filters), and currently every developer I hand my code to, I have to get them to rebuild hise with the following edit to hi_tools:

      #include "hi_neural/RTNeural/modules/xsimd/xsimd.hpp"
      

      It would be really helpful if this could be included via an easier route! Either included in hi_tools by default, or via a flag, or via an include in the c++ nodes themselves.

      Would that be possible? It's a change that basically only I would ask for, but still 😆 I will ask

      posted in Feature Requests
      griffinboyG
      griffinboy

    Latest posts made by griffinboy

    • RE: Possible to feed Granulator audio from outputs of my plugin?

      @LozPetts

      Idk about the stock one, but It's something I've done using c++ in hise

      posted in General Questions
      griffinboyG
      griffinboy
    • RE: Remake stock Phaser Module in Scriptnode

      @Christoph-Hart

      Ah yeah yeah.
      That's fine then, it's not an issue in my designs I don't think. I end up creating systems for the sample accurate parameters which smooth and then update the internal variables of the dsp. And sometimes I create per sample paths for when modulation is happening.

      But that's very interesting, i never thought about it that way, you could process left and right in one iteration if frame processing. For sample accurate changes that indeed is more efficient. I never thought of that.

      Edit: oh that latency thing is interesting though I'll have to investigate. Although I've never used a routing node.

      posted in General Questions
      griffinboyG
      griffinboy
    • RE: Remake stock Phaser Module in Scriptnode

      @Christoph-Hart

      About frame processing, why do you recommend it here? I've yet to find many use cases for frame processing aside from cases where you need access to both channels simultaneously to process each sample... You said something to do with smoothing? I'm just curious

      The default c++ node has frame processing set up, same as the snex node. Yet I always end up just using process in 95% of my dsp because I can vectorize each channel and do things much more efficiently when not interleaving them.

      posted in General Questions
      griffinboyG
      griffinboy
    • Add XSIMD to hi_tools by default?

      Can we have a better way to include XSIMD in a C++ node please?

      I find myself using XSIMD more and more lately in my c++ nodes (for Filters), and currently every developer I hand my code to, I have to get them to rebuild hise with the following edit to hi_tools:

      #include "hi_neural/RTNeural/modules/xsimd/xsimd.hpp"
      

      It would be really helpful if this could be included via an easier route! Either included in hi_tools by default, or via a flag, or via an include in the c++ nodes themselves.

      Would that be possible? It's a change that basically only I would ask for, but still 😆 I will ask

      posted in Feature Requests
      griffinboyG
      griffinboy
    • RE: machine learning to capture analog tech

      @Morphoice

      AP mastering is not to be believed, in his tests he has bad luck and chooses many plugins that have been half assed and are not proper analog circuit models, wheras, there are many good analog model products out there. Either that, or he downplays the differences. From discussing with him, his stance is not that analog model products are a sham anyway, his stance is that he prefers digital tools which are predictable and don't cause distortion. He admitted to creating his videos in such a way to clickbait for the algorithm / be polarizing. That's where the whole 'scam' thing came from, although he is right that many analog modelling plugins are not very good and don't match the real devices very well.

      That out of the way, machine learning for analog simulation is mostly about creating digital models of individual circuit components, or small circuits. For example, you can train a neural network on the response of an EC66 triode tube and it will create an accurate digital model which runs much more efficiently than doing it mathematically by brute force, and may be more stable (so you may be able to eliminate recursive solvers by using Neural). This can be done for whole circuits too (but you run into aliasing issues). Then you can insert the AI model into your regular circuit simulation. The boon is more accuracy and less computational cost, all at once.

      The other thing you can do is to try and train an AI to predict an entire device. For example you have a gigantic dataset of gain reduction from an analog compressor, for all it's knob settings. The AI can then be trained to match this dataset and produce the correct curves, learning the nuances of the device.

      It's easier said than done. Many problems arise and getting the AI to be both correct and run efficiently are two huge challenges.

      There are research papers on the topic just search for the word 'differentiable' alongside analog modelling, or a type of device eg compressor.

      posted in General Questions
      griffinboyG
      griffinboy
    • RE: Wavetable Synth Hard Sync?

      @DanH
      @CyberGen

      Might be of interest to you, but I've been working on c++ WT engine for Hise. It works and includes all the mentioned features.
      The engine is not available yet to the public though, it's still being developed as a commission.

      posted in General Questions
      griffinboyG
      griffinboy
    • RE: Wavetable Synth Hard Sync?

      @CyberGen

      As long as the wavetable synth does upsampling after setting the playback position it should work I think. It depends a little on how the WT synth handles it's antialiasing.

      posted in General Questions
      griffinboyG
      griffinboy
    • RE: Multiple Global Data Cables - only the first one gets a runtime target

      @Orvillain

      Yep that'll be it.

      I actually wish it worked differently, but currently scriptnode c++ synth nodes only call process() per active voice. So if there are no voices it won't call process (or subsequently process frame).

      Additionally say there are 3 voices playing, that will mean your process script gets called 3 times as frequently... Each voice will run it's own process.

      You can check which voice the process() is currently running for, using polydata, which allows you to do different processing per voice

      posted in Bug Reports
      griffinboyG
      griffinboy
    • RE: Multiple Global Data Cables - only the first one gets a runtime target

      @Orvillain

      It should work fine. I think it works. I might be wrong though, I haven't used them in a synth recently.

      Process() only runs when voices are playing in a scriptnode synth. But that shouldn't affect the callbacks.

      posted in Bug Reports
      griffinboyG
      griffinboy
    • RE: Multiple Global Data Cables - only the first one gets a runtime target

      @Orvillain

      Oh yeah i made this mistake a while ago XD

      I use a template for my c++ nodes and it has a helper baked in with temp IDs for the cables. I forgot you have to generate the IDs from the project!

      posted in Bug Reports
      griffinboyG
      griffinboy