now working with the tensors and the share client code
Pierre Alexandre Tremblay
7 years ago
parent
4132670a7f
commit
a783c4af61
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#include "fluid_client_nmf.h"
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#include "STFT.hpp"
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#include "RatioMask.hpp"
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namespace fluid{
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namespace nmf{
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using fluid::nmf::NMF;
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using fluid::stft::STFT;
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using fluid::stft::ISTFT;
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using fluid::stft::Spectrogram;
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using fluid::FluidTensor;
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NMFClient::NMFClient(size_t rank,size_t iterations, size_t fft_size, size_t window_size, size_t hop_size):
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m_rank(rank),m_iterations(iterations), m_fft_size(fft_size), m_window_size(window_size), m_hop_size(hop_size), m_has_processed(false), m_has_resynthed(false)
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{}
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void NMFClient::process(const FluidTensor<double, 1> &data, bool resynthesise)
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{
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m_audio_buffers.resize(m_rank,data.extent(0));
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m_has_processed = false;
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m_has_resynthed = false;
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STFT stft(m_window_size,m_fft_size,m_hop_size);
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Spectrogram spec = stft.process(data);
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FluidTensor<double, 2> mag = spec.getMagnitude();
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NMF nmf(m_rank,m_iterations);
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m_model = nmf.process(spec.getMagnitude());
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m_has_processed = true;
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if(resynthesise)
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{
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ratiomask::RatioMask mask(m_model.getMixEstimate(),1);
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ISTFT istft(m_window_size, m_fft_size, m_hop_size);
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for(int i = 0; i < m_rank; ++i)
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{
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RealMatrix estimate = m_model.getEstimate(i);
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Spectrogram result(mask.process(spec.mData, estimate));
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RealVector audio = istft.process(result);
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m_audio_buffers.row(i) = audio;
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}
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m_has_resynthed = true;
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}
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}
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size_t NMFClient::dictionary_size() const
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{
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return m_has_processed ? m_model.getW().extent(0) : 0 ;
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}
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size_t NMFClient::activations_length() const{
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return m_has_processed ? m_model.getH().extent(1) : 0;
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}
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size_t NMFClient::num_sources() const
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{
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return m_has_resynthed ? m_audio_buffers.size() : 0;
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}
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const FluidTensorView<double, 1> NMFClient::dictionary(const size_t idx) const
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{
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assert(m_has_processed && idx < m_model.W.cols());
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return m_model.getW().col(idx);
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}
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const FluidTensorView<double, 1> NMFClient::activation(const size_t idx) const
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{
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assert(m_has_processed && idx < m_model.H.rows());
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return m_model.getH().row(idx);
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}
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const FluidTensor<double,2> NMFClient::dictionaries() const
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{
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return m_model.getW();
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}
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const FluidTensor<double,2> NMFClient::activations()const
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{
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return m_model.getH();
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}
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const FluidTensorView<double, 1> NMFClient::source(const size_t idx) const
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{
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assert(idx < m_audio_buffers.rows() && "Range Error");
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return m_audio_buffers.row(idx);
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}
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// source_iterator NMFClient::sources_begin() const
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// {
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// return m_audio_buffers.cbegin();
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// }
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//
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// source_iterator NMFClient::sources_end() const
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// {
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// return m_audio_buffers.cend();
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// }
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}//namespace nmf
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}//namespace fluid
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@ -0,0 +1,96 @@
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#pragma once
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#include "FluidTensor.hpp"
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#include "NMF.hpp"
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#include <vector>
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#include <iterator>
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using fluid::FluidTensor;
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namespace fluid {
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namespace nmf{
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/**
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Integration class for doing NMF filtering and resynthesis
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**/
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class NMFClient
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{
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// using vec_iterator = std::vector<double>::const_iterator;
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// using source_iterator = std::vector<std::vector<double>>::const_iterator;
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public:
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//No, you may not construct an empty instance, or copy this, or move this
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NMFClient() = delete;
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NMFClient(NMFClient&)=delete;
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NMFClient(NMFClient&&)=delete;
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NMFClient operator=(NMFClient&)=delete;
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NMFClient operator=(NMFClient&&)=delete;
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/**
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You may constrct one by supplying some senisble numbers here
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rank: NMF rank
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iterations: max nmf iterations
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fft_size: power 2 pls
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**/
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NMFClient(size_t rank, size_t iterations, size_t fft_size, size_t window_size, size_t hop_size);
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~NMFClient()= default;
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//Not implemented
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//void reset();
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//bool isReady() const;
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/***
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Take some data, NMF it
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***/
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void process(const FluidTensor<double,1> &data, bool resynthesise);
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/***
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Report the size of a dictionary, in bins (= fft_size/2)
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***/
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size_t dictionary_size() const;
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/***
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Report the length of an activation, in frames
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***/
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size_t activations_length() const;
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/***
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Report the number of sources (i.e. the rank
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***/
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size_t num_sources() const;
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// size_t rank() const;
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/***
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Retreive the dictionary at the given index
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***/
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const FluidTensorView<double, 1> dictionary(const size_t idx) const;
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/***
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Retreive the activation at the given index
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***/
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const FluidTensorView<double, 1> activation(const size_t idx) const;
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/***
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Retreive the resynthesized source at the given index (so long as resyntheiss has happened, mind
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***/
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const FluidTensorView<double, 1> source(const size_t idx) const;
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// source_iterator sources_begin() const ;
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// source_iterator sources_end()const;
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/***
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Get the whole of dictionaries / activations as a 2D structure
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***/
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const FluidTensor<double,2> dictionaries() const;
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const FluidTensor<double,2> activations() const;
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private:
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size_t m_rank;
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size_t m_iterations;
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size_t m_fft_size;
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size_t m_window_size;
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size_t m_hop_size;
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bool m_has_processed;
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bool m_has_resynthed;
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fluid::nmf::NMFModel m_model;
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FluidTensor<double,2> m_audio_buffers;
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};
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} //namespace max
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} //namesapce fluid
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@ -0,0 +1,89 @@
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//
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// fluid_nmf_tilde_util.h
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// fluid.nmf~
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//
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// Created by Owen Green on 02/07/2018.
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//
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#ifndef fluid_nmf_tilde_util_h
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#define fluid_nmf_tilde_util_h
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#include "FluidTensor.hpp"
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#include <string>
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#include <vector>
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namespace fluid{
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namespace nmf{
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using real_matrix = fluid::FluidTensor<double,2>;
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struct error_strings
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{
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static constexpr const char* rank_below_one = "Rank < 1 makes no sense";
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static constexpr const char* no_input_buffer_symbol = "Could not extract symbol from input buffer name";
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static constexpr const char* no_out_polybuf_symbol = "Could not extract symbol from output polybuffer name";
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static constexpr const char* sources_args = "At least three arguments required: NMF rank, input buffer, and output polybuffer.";
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static constexpr const char* filters_args = "At least four arguments required: NMF rank, input buffer, output dictionary polybuffer, and output activations polybuffer.";
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static constexpr const char* no_filter_polybuf_symbol = "Could not extract symbol from filters polybuffer name";
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static constexpr const char* no_env_polybuf_symbol = "Could not extract symbol from envelopes polybuffer name";
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static constexpr const char* get_buffer_fail = "Could not get buffer for name %s";
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private:
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error_strings(){}
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};
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// /*****************
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// A template function to reduce duplication in copying back to Max buffers
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// My hope is to render this either obsolete or much simpler once algo code
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// is refactored.
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// At present it needs to be fed a vector of vectors (ugh) and a function that
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// does the copying (see under)
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// *******************/
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// template<typename F>
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// void copy_to_buffer(t_object* obj, int rank, t_symbol* polybuf_name,real_matrix &mtrx,F&& copy_fn, double scale=1.)
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// {
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// for(int i = 0; i < rank; i++)
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// {
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// std::ostringstream ss;
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// ss << polybuf_name->s_name << "." << i+1;
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// const char* buffername = ss.str().c_str();
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//
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// t_buffer_ref* ref = buffer_ref_new(obj, gensym(buffername));
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// t_buffer_obj* this_buffer = buffer_ref_getobject(ref);
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//
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// if(this_buffer)
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// {
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// float* samps = buffer_locksamples(this_buffer);
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// if(samps)
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// {
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// copy_fn(samps,mtrx,i,scale);
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// buffer_unlocksamples(this_buffer);
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// }
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// }
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//
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// if(ref)
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// object_free(ref);
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//
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// }
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// }
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//
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// void from_cols(float* dst, real_matrix &m, long i,double scale)
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// {
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// for(long j = 0; j< m[0].size(); j++)
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// dst[j] = m[i][j] * scale;
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// }
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//
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// void from_rows(float* dst,real_matrix &m, long i,double scale)
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// {
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// for(long j = 0; j < m.size(); j++)
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// dst[j] = m[j][i] * scale;
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// }
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}
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}
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#endif /* fluid_nmf_tilde_util_h */
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