Merge pull request #20 from jorshi/fix/warnings

Fix/warnings
jorshi · Jul 1, 2024 · 2c776ec · 2c776ec
2 parents 34e0058 + df2aa03
commit 2c776ec
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Showing 18 changed files with 91 additions and 72 deletions.
diff --git a/.vscode/settings.json b/.vscode/settings.json
@@ -1,4 +1,12 @@
 {
     "cmake.configureOnOpen": true,
-    "cmake.cmakePath": "/opt/homebrew/bin/cmake"
+    "cmake.cmakePath": "/opt/homebrew/bin/cmake",
+    "cmake.configureArgs": [
+        "-DCMAKE_PREFIX_PATH=/Users/jordanm/anaconda3/envs/torchdrum/lib/python3.10/site-packages/torch/share/cmake",
+        "-DBUILD_TORCHDRUM_LIB=ON"
+    ],
+    "files.associations": {
+        "*.m": "matlab",
+        "vector": "cpp"
+    }
 }
diff --git a/.vscode/tasks.json b/.vscode/tasks.json
@@ -24,5 +24,4 @@
             "command": "cmake -Bbuild -DCMAKE_BUILD_TYPE:STRING=Release -DCMAKE_PREFIX_PATH=/Users/jordanm/anaconda3/envs/torchdrum/lib/python3.10/site-packages/torch/share/cmake -DCOPY_PLUGIN_AFTER_BUILD=0 && cmake --build build --config Release -j12"
         }
     ]
-
-}
+}
diff --git a/source/.clang-format b/source/.clang-format
@@ -24,7 +24,7 @@ BreakBeforeBraces: Allman
 BreakBeforeTernaryOperators: true
 BreakConstructorInitializersBeforeComma: false
 BreakStringLiterals: false
-ColumnLimit: 0
+ColumnLimit: 88
 ConstructorInitializerAllOnOneLineOrOnePerLine: true
 ConstructorInitializerIndentWidth: 4
 ContinuationIndentWidth: 4

diff --git a/source/Biquad.cpp b/source/Biquad.cpp
@@ -26,8 +26,9 @@ template <typename T>
 void BiquadCoeffT<T>::calc()
 {
     sample_t norm;
-    sample_t V = pow(10, fabs(peakGain) / 20.0);
-    sample_t K = tan(M_PI * Fc);
+    sample_t V = (sample_t) pow(10, fabs(peakGain) / 20.0);
+    sample_t K = (sample_t) tan(M_PI * Fc);
+    sample_t sqrt2 = (sample_t) sqrt(2.0);
     switch (this->type)
     {
         case lowpass:
@@ -85,39 +86,39 @@ void BiquadCoeffT<T>::calc()
         case lowshelf:
             if (peakGain >= 0)
             { // boost
-                norm = 1 / (1 + sqrt(2) * K + K * K);
+                norm = 1 / (1 + sqrt2 * K + K * K);
                 a0 = (1 + sqrt(2 * V) * K + V * K * K) * norm;
                 a1 = 2 * (V * K * K - 1) * norm;
                 a2 = (1 - sqrt(2 * V) * K + V * K * K) * norm;
                 b1 = 2 * (K * K - 1) * norm;
-                b2 = (1 - sqrt(2) * K + K * K) * norm;
+                b2 = (1 - sqrt2 * K + K * K) * norm;
             }
             else
             { // cut
                 norm = 1 / (1 + sqrt(2 * V) * K + V * K * K);
-                a0 = (1 + sqrt(2) * K + K * K) * norm;
+                a0 = (1 + sqrt2 * K + K * K) * norm;
                 a1 = 2 * (K * K - 1) * norm;
-                a2 = (1 - sqrt(2) * K + K * K) * norm;
+                a2 = (1 - sqrt2 * K + K * K) * norm;
                 b1 = 2 * (V * K * K - 1) * norm;
                 b2 = (1 - sqrt(2 * V) * K + V * K * K) * norm;
             }
             break;
         case highshelf:
             if (peakGain >= 0)
             { // boost
-                norm = 1 / (1 + sqrt(2) * K + K * K);
+                norm = 1 / (1 + sqrt2 * K + K * K);
                 a0 = (V + sqrt(2 * V) * K + K * K) * norm;
                 a1 = 2 * (K * K - V) * norm;
                 a2 = (V - sqrt(2 * V) * K + K * K) * norm;
                 b1 = 2 * (K * K - 1) * norm;
-                b2 = (1 - sqrt(2) * K + K * K) * norm;
+                b2 = (1 - sqrt2 * K + K * K) * norm;
             }
             else
             { // cut
                 norm = 1 / (V + sqrt(2 * V) * K + K * K);
-                a0 = (1 + sqrt(2) * K + K * K) * norm;
+                a0 = (1 + sqrt2 * K + K * K) * norm;
                 a1 = 2 * (K * K - 1) * norm;
-                a2 = (1 - sqrt(2) * K + K * K) * norm;
+                a2 = (1 - sqrt2 * K + K * K) * norm;
                 b1 = 2 * (K * K - V) * norm;
                 b2 = (V - sqrt(2 * V) * K + K * K) * norm;
             }

diff --git a/source/Biquad.h b/source/Biquad.h
@@ -54,32 +54,32 @@ class BiquadCoeffT : public BiquadCoeff
     int setup(const Settings& settings)
     {
         type = settings.type;
-        Fs = settings.fs;
-        Fc = settings.cutoff / Fs;
-        Q = settings.q;
-        peakGain = settings.peakGainDb;
+        Fs = (sample_t) settings.fs;
+        Fc = (sample_t) settings.cutoff / Fs;
+        Q = (sample_t) settings.q;
+        peakGain = (sample_t) settings.peakGainDb;
         calc();
         return 0;
     }
 
-    void setType(Type type)
+    void setType(Type newValue)
     {
-        this->type = type;
+        this->type = newValue;
         calc();
     }
-    void setQ(sample_t Q)
+    void setQ(sample_t newValue)
     {
-        this->Q = Q;
+        this->Q = newValue;
         calc();
     }
-    void setFc(sample_t Fc)
+    void setFc(sample_t newValue)
     {
-        this->Fc = Fc / this->Fs;
+        this->Fc = newValue / this->Fs;
         calc();
     }
-    void setPeakGain(sample_t peakGainDB)
+    void setPeakGain(sample_t newValue)
     {
-        this->peakGain = peakGainDB;
+        this->peakGain = newValue;
         calc();
     }
 
@@ -105,7 +105,7 @@ class BiquadCoeffT : public BiquadCoeff
 class Biquad : public BiquadCoeffT<double>
 {
 public:
-    Biquad() {};
+    Biquad() {}
     Biquad(const Settings& s) { setup(s); }
     /**
    * Process one input sample and return one output sample.

diff --git a/source/FeatureExtraction/FeatureExtraction.cpp b/source/FeatureExtraction/FeatureExtraction.cpp
@@ -22,7 +22,7 @@ void FeatureExtraction::process(const juce::AudioBuffer<float>& buffer, FeatureE
     jassert(buffer.getNumChannels() == 1 && buffer.getNumSamples() == frameSize);
 
     // Calculate RMS
-    double rms = 0.0;
+    float rms = 0.0;
     auto* audio = buffer.getReadPointer(0);
     for (int i = 0; i < buffer.getNumSamples(); ++i)
     {
@@ -35,7 +35,7 @@ void FeatureExtraction::process(const juce::AudioBuffer<float>& buffer, FeatureE
 
     // Convert to dB with epsilon to avoid log(0) and floor at -80 dB
     rms = 20.0f * std::log10(rms + 1e-8f);
-    rms = std::max(rms, -80.0);
+    rms = std::max(rms, -80.0f);
 
     // Update the results
     results.rmsMean.set(rms, true);

diff --git a/source/FeatureExtraction/FeatureValue.h b/source/FeatureExtraction/FeatureValue.h
@@ -43,8 +43,12 @@ class FeatureValue
     // Get the normalized value
     T getNormalized() const
     {
-        if (minValue == maxValue || minValue == std::numeric_limits<T>::max())
+        // If the minimum / maximum values have yet to be set (or not different)
+        if (juce::approximatelyEqual(minValue, maxValue)
+            || juce::approximatelyEqual(minValue, std::numeric_limits<T>::max()))
+        {
             return 0.5;
+        }
 
         T normalized = (value - minValue) / (maxValue - minValue);
         return juce::jlimit(static_cast<T>(0.0), static_cast<T>(1.0), normalized);

diff --git a/source/FeatureExtraction/SpectralExtractor.h b/source/FeatureExtraction/SpectralExtractor.h
@@ -24,15 +24,15 @@ class SpectralExtractor
         fftSize = size;
 
         // Initialize FFT
-        int fftOrder = std::log2(fftSize);
+        int fftOrder = (int) std::log2(fftSize);
         fft = std::make_unique<juce::dsp::FFT>(fftOrder);
-        fftBuffer.resize(fftSize * 2);
-        fftWindow.resize(fftSize);
+        fftBuffer.resize((size_t) fftSize * 2);
+        fftWindow.resize((size_t) fftSize);
 
         // Initialize window function
         juce::dsp::WindowingFunction<float>::fillWindowingTables(
             fftWindow.data(),
-            fftSize,
+            (size_t) fftSize,
             juce::dsp::WindowingFunction<float>::hann,
             false);
 
@@ -49,8 +49,8 @@ class SpectralExtractor
             return;
 
         // Apply window function and copy to FFT buffer
-        for (int i = 0; i < fftSize; ++i)
-            fftBuffer[i] = buffer.getSample(0, i) * fftWindow[i];
+        for (size_t i = 0; i < (size_t) fftSize; ++i)
+            fftBuffer[i] = buffer.getSample(0, (int) i) * fftWindow[i];
 
         // Perform FFT
         fft->performFrequencyOnlyForwardTransform(fftBuffer.data(), true);
@@ -66,8 +66,8 @@ class SpectralExtractor
         // Calculate spectral centroid based on current frequency magnitude buffer
         float weightedSum = 0.0;
         float norm = 0.0;
-        int realSize = (fftSize / 2) + 1;
-        for (int n = 0; n < realSize; n++)
+        size_t realSize = (size_t) (fftSize / 2) + 1;
+        for (size_t n = 0; n < realSize; n++)
         {
             jassert(fftBuffer[n] >= 0.0f);
             weightedSum += n * fftBuffer[n];
@@ -80,7 +80,7 @@ class SpectralExtractor
         float centroid = weightedSum / norm;
 
         // Convert to Hz
-        centroid = centroid * sampleRate / (float) fftSize;
+        centroid = centroid * (float) sampleRate / fftSize;
 
         // Convert to semitones
         centroid = 12.0f * std::log2(centroid / 440.0f) + 69.0f;
@@ -92,8 +92,8 @@ class SpectralExtractor
     {
         float geometricMean = 0.0;
         float arithmeticMean = 0.0;
-        int realSize = (fftSize / 2) + 1;
-        for (int n = 0; n < realSize; n++)
+        size_t realSize = (size_t) (fftSize / 2) + 1;
+        for (size_t n = 0; n < realSize; n++)
         {
             float power = std::max(fftBuffer[n] * fftBuffer[n], 1e-10f);
             geometricMean += std::log(power);
@@ -106,7 +106,7 @@ class SpectralExtractor
         arithmeticMean /= (float) realSize;
 
         float flatness = geometricMean / arithmeticMean;
-        flatness = 20.0 * std::log10(flatness);
+        flatness = 20.0f * std::log10(flatness);
         return flatness;
     }
 

diff --git a/source/NeuralNetwork.cpp b/source/NeuralNetwork.cpp
@@ -29,18 +29,18 @@ void NeuralNetwork::process(const std::vector<double>& input, std::vector<double
 
     // Run prediction with model
     auto& inputTensor = inputs[0].toTensor();
-    for (int i = 0; i < input.size(); ++i)
+    for (size_t i = 0; i < input.size(); ++i)
     {
-        inputTensor[0][i] = input[i];
+        inputTensor[0][(int64_t) i] = input[i];
     }
 
     auto outputTensor = model.forward(inputs).toTensor();
     jassert(outputTensor.sizes().size() == 2);
-    jassert(outputTensor.sizes()[1] == output.size());
+    jassert(outputTensor.sizes()[1] == (int64_t) output.size());
 
-    for (int i = 0; i < output.size(); ++i)
+    for (size_t i = 0; i < output.size(); ++i)
     {
-        output[i] = outputTensor[0][i].item<double>();
+        output[i] = outputTensor[0][(int64_t) i].item<double>();
     }
 }
 
@@ -54,9 +54,9 @@ void NeuralNetwork::getCurrentPatch(std::vector<juce::RangedAudioParameter*> par
     }
 
     jassert(currentPatch.size() == parameters.size());
-    for (int i = 0; i < parameters.size(); ++i)
+    for (size_t i = 0; i < parameters.size(); ++i)
     {
-        parameters[i]->setValueNotifyingHost(currentPatch[i]);
+        parameters[i]->setValueNotifyingHost((float) currentPatch[i]);
     }
 }
 
@@ -95,10 +95,10 @@ void NeuralNetwork::_testModel()
 
         // Update the current patch from network output
         currentPatch.clear();
-        currentPatch.resize(outputFeatures);
-        for (int i = 0; i < outputFeatures; ++i)
+        currentPatch.resize((size_t) outputFeatures);
+        for (size_t i = 0; i < (size_t) outputFeatures; ++i)
         {
-            currentPatch[i] = output[1][i].item<double>();
+            currentPatch[i] = output[1][(int64_t) i].item<double>();
         }
     }
     catch (const c10::Error& e)

diff --git a/source/PluginEditor.cpp b/source/PluginEditor.cpp
@@ -2,7 +2,7 @@
 #include "PluginProcessor.h"
 
 TorchDrumEditor::TorchDrumEditor(TorchDrumProcessor& p)
-    : AudioProcessorEditor(&p), processor(p)
+    : AudioProcessorEditor(&p), drumProcessor(p)
 {
     fileChooser = std::make_unique<juce::FileChooser>(
         "File Browser",
@@ -28,33 +28,33 @@ TorchDrumEditor::TorchDrumEditor(TorchDrumProcessor& p)
     // Setup the reset normalizer button
     resetNormButton.onClick = [this]
     {
-        processor.getSynthController().resetFeatureNormalizers();
+        drumProcessor.getSynthController().resetFeatureNormalizers();
     };
 
     // Add the action listener to the SynthController
-    processor.getSynthController().getBroadcaster().addActionListener(this);
+    drumProcessor.getSynthController().getBroadcaster().addActionListener(this);
 
     setSize(400, 600);
 }
 
 TorchDrumEditor::~TorchDrumEditor()
 {
-    processor.getSynthController().getBroadcaster().removeActionListener(this);
+    drumProcessor.getSynthController().getBroadcaster().removeActionListener(this);
 }
 
 void TorchDrumEditor::chooserCallback(const juce::FileChooser& chooser)
 {
     auto result = chooser.getResult();
     auto resultPath = result.getFullPathName().toStdString();
-    processor.getSynthController().updateModel(resultPath);
+    drumProcessor.getSynthController().updateModel(resultPath);
 }
 
 void TorchDrumEditor::paint(juce::Graphics& g)
 {
     g.fillAll(
         getLookAndFeel().findColour(juce::ResizableWindow::backgroundColourId));
 
-    auto& results = processor.getSynthController().getFeatures();
+    auto& results = drumProcessor.getSynthController().getFeatures();
     float rms = results.rmsMean.getNormalized();
     float sc = results.spectralCentroidMean.getNormalized();
     float sf = results.spectralFlatnessMean.getNormalized();

diff --git a/source/PluginEditor.h b/source/PluginEditor.h
@@ -28,8 +28,8 @@ class TorchDrumEditor : public juce::AudioProcessorEditor, juce::ActionListener
 
     juce::File getPresetFolder();
 
-    TorchDrumProcessor& processor;
-    juce::GenericAudioProcessorEditor editor { processor };
+    TorchDrumProcessor& drumProcessor;
+    juce::GenericAudioProcessorEditor editor { drumProcessor };
     juce::TextButton loadModelButton { "Load Model" };
     juce::TextButton resetNormButton { "Reset Normalizer" };
     std::unique_ptr<juce::FileChooser> fileChooser;

diff --git a/source/Synth/Modules/Noise.h b/source/Synth/Modules/Noise.h
@@ -14,6 +14,6 @@ class WhiteNoise
 
     float process()
     {
-        return 2.0 * ((float) rand() / (float) RAND_MAX) - 1.0;
+        return (float) 2 * rand() / RAND_MAX - 1;
     }
 };
diff --git a/source/Synth/Modules/Tonal.h b/source/Synth/Modules/Tonal.h
@@ -20,7 +20,7 @@ class Tonal
     void setTuning(float newValue);
 
     // Destructor
-    ~Tonal() {};
+    ~Tonal() {}
 
 private:
     double sampleRate;

diff --git a/source/Synth/Snare808.cpp b/source/Synth/Snare808.cpp
@@ -84,7 +84,7 @@ float Snare808::process()
 
     // Noise Signal
     float n = noise.process();
-    n = noiseFilter.process(n);
+    n = (float) noiseFilter.process(n);
     n = n * noiseEnv.process();
     n = noiseGain.process(n);
 
@@ -109,7 +109,7 @@ void Snare808::trigger()
 // Update the filter frequency
 void Snare808::updateFilterFreq(float value)
 {
-    float nyquist = 0.5f * sampleRate;
+    float nyquist = 0.5f * (float) sampleRate;
     float freq = std::min(value, nyquist);
     noiseFilter.setFc(freq);
 }
-Original file line number
+Diff line change
@@ Expand Up / @@ -24,5 +24,4 @@ @@
                 "command": "cmake -Bbuild -DCMAKE_BUILD_TYPE:STRING=Release -DCMAKE_PREFIX_PATH=/Users/jordanm/anaconda3/envs/torchdrum/lib/python3.10/site-packages/torch/share/cmake -DCOPY_PLUGIN_AFTER_BUILD=0 && cmake --build build --config Release -j12"
             }
         ]
-    }
+    }