Now working with the new structure of fluid_decompositon - commit ebad604

nix
Pierre Alexandre Tremblay 7 years ago
parent 8091851198
commit 3936a42b51

@ -96,8 +96,6 @@ ${PROJECT}
MODULE
${FILENAME}
"${FLUID_DECOMP_DIR}/3rdparty/HISSTools_FFT/HISSTools_FFT.cpp"
"fluid_client_nmf.cc"
"fluid_client_nmf.h"
)
if(SUPERNOVA)
add_library(${PROJECT}_supernova MODULE ${FILENAME})

@ -2,22 +2,17 @@
// A tool from the FluCoMa project, funded by the European Research Council (ERC) under the European Unions Horizon 2020 research and innovation programme (grant agreement No 725899)
#include "SC_PlugIn.h"
#include "STFT.hpp"
#include "FluidTensor.hpp"
#include "fluid_client_nmf.h"
#include "fluid_nmf_tilde_util.h"
#include "algorithms/STFT.hpp"
#include "data/FluidTensor.hpp"
#include "clients/nrt/NMFClient.hpp"
//Using statements for fluidtensor
using fluid::FluidTensor;
using fluid::FluidTensorView;
using fluid::nmf::error_strings;
using fluid::nmf::NMFClient;
static InterfaceTable *ft;
//namespace to gaffatape
namespace gaffatape {
void BufNMF(World *world, struct SndBuf *dstBuf, struct sc_msg_iter *msg)
{
size_t dstFrameCount = dstBuf->frames;
@ -83,4 +78,3 @@ PluginLoad(OfflineFluidDecompositionUGens) {
ft = inTable;
DefineBufGen("BufNMF", BufNMF);
}
}

@ -1,100 +0,0 @@
#include "fluid_client_nmf.h"
#include "STFT.hpp"
#include "RatioMask.hpp"
namespace fluid{
namespace nmf{
using fluid::nmf::NMF;
using fluid::stft::STFT;
using fluid::stft::ISTFT;
using fluid::stft::Spectrogram;
using fluid::FluidTensor;
NMFClient::NMFClient(size_t rank,size_t iterations, size_t fft_size, size_t window_size, size_t hop_size):
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)
{}
void NMFClient::process(const FluidTensor<double, 1> &data, bool resynthesise)
{
m_audio_buffers.resize(m_rank,data.extent(0));
m_has_processed = false;
m_has_resynthed = false;
STFT stft(m_window_size,m_fft_size,m_hop_size);
Spectrogram spec = stft.process(data);
FluidTensor<double, 2> mag = spec.getMagnitude();
NMF nmf(m_rank,m_iterations);
m_model = nmf.process(spec.getMagnitude());
m_has_processed = true;
if(resynthesise)
{
ratiomask::RatioMask mask(m_model.getMixEstimate(),1);
ISTFT istft(m_window_size, m_fft_size, m_hop_size);
for(int i = 0; i < m_rank; ++i)
{
RealMatrix estimate = m_model.getEstimate(i);
Spectrogram result(mask.process(spec.mData, estimate));
RealVector audio = istft.process(result);
m_audio_buffers.row(i) = audio;
}
m_has_resynthed = true;
}
}
size_t NMFClient::dictionary_size() const
{
return m_has_processed ? m_model.getW().extent(0) : 0 ;
}
size_t NMFClient::activations_length() const{
return m_has_processed ? m_model.getH().extent(1) : 0;
}
size_t NMFClient::num_sources() const
{
return m_has_resynthed ? m_audio_buffers.size() : 0;
}
const FluidTensorView<double, 1> NMFClient::dictionary(const size_t idx) const
{
assert(m_has_processed && idx < m_model.W.cols());
return m_model.getW().col(idx);
}
const FluidTensorView<double, 1> NMFClient::activation(const size_t idx) const
{
assert(m_has_processed && idx < m_model.H.rows());
return m_model.getH().row(idx);
}
const FluidTensor<double,2> NMFClient::dictionaries() const
{
return m_model.getW();
}
const FluidTensor<double,2> NMFClient::activations()const
{
return m_model.getH();
}
const FluidTensorView<double, 1> NMFClient::source(const size_t idx) const
{
assert(idx < m_audio_buffers.rows() && "Range Error");
return m_audio_buffers.row(idx);
}
// source_iterator NMFClient::sources_begin() const
// {
// return m_audio_buffers.cbegin();
// }
//
// source_iterator NMFClient::sources_end() const
// {
// return m_audio_buffers.cend();
// }
}//namespace nmf
}//namespace fluid

@ -1,96 +0,0 @@
#pragma once
#include "FluidTensor.hpp"
#include "NMF.hpp"
#include <vector>
#include <iterator>
using fluid::FluidTensor;
namespace fluid {
namespace nmf{
/**
Integration class for doing NMF filtering and resynthesis
**/
class NMFClient
{
// using vec_iterator = std::vector<double>::const_iterator;
// using source_iterator = std::vector<std::vector<double>>::const_iterator;
public:
//No, you may not construct an empty instance, or copy this, or move this
NMFClient() = delete;
NMFClient(NMFClient&)=delete;
NMFClient(NMFClient&&)=delete;
NMFClient operator=(NMFClient&)=delete;
NMFClient operator=(NMFClient&&)=delete;
/**
You may constrct one by supplying some senisble numbers here
rank: NMF rank
iterations: max nmf iterations
fft_size: power 2 pls
**/
NMFClient(size_t rank, size_t iterations, size_t fft_size, size_t window_size, size_t hop_size);
~NMFClient()= default;
//Not implemented
//void reset();
//bool isReady() const;
/***
Take some data, NMF it
***/
void process(const FluidTensor<double,1> &data, bool resynthesise);
/***
Report the size of a dictionary, in bins (= fft_size/2)
***/
size_t dictionary_size() const;
/***
Report the length of an activation, in frames
***/
size_t activations_length() const;
/***
Report the number of sources (i.e. the rank
***/
size_t num_sources() const;
// size_t rank() const;
/***
Retreive the dictionary at the given index
***/
const FluidTensorView<double, 1> dictionary(const size_t idx) const;
/***
Retreive the activation at the given index
***/
const FluidTensorView<double, 1> activation(const size_t idx) const;
/***
Retreive the resynthesized source at the given index (so long as resyntheiss has happened, mind
***/
const FluidTensorView<double, 1> source(const size_t idx) const;
// source_iterator sources_begin() const ;
// source_iterator sources_end()const;
/***
Get the whole of dictionaries / activations as a 2D structure
***/
const FluidTensor<double,2> dictionaries() const;
const FluidTensor<double,2> activations() const;
private:
size_t m_rank;
size_t m_iterations;
size_t m_fft_size;
size_t m_window_size;
size_t m_hop_size;
bool m_has_processed;
bool m_has_resynthed;
fluid::nmf::NMFModel m_model;
FluidTensor<double,2> m_audio_buffers;
};
} //namespace max
} //namesapce fluid

@ -1,89 +0,0 @@
//
// fluid_nmf_tilde_util.h
// fluid.nmf~
//
// Created by Owen Green on 02/07/2018.
//
#ifndef fluid_nmf_tilde_util_h
#define fluid_nmf_tilde_util_h
#include "FluidTensor.hpp"
#include <string>
#include <vector>
namespace fluid{
namespace nmf{
using real_matrix = fluid::FluidTensor<double,2>;
struct error_strings
{
static constexpr const char* rank_below_one = "Rank < 1 makes no sense";
static constexpr const char* no_input_buffer_symbol = "Could not extract symbol from input buffer name";
static constexpr const char* no_out_polybuf_symbol = "Could not extract symbol from output polybuffer name";
static constexpr const char* sources_args = "At least three arguments required: NMF rank, input buffer, and output polybuffer.";
static constexpr const char* filters_args = "At least four arguments required: NMF rank, input buffer, output dictionary polybuffer, and output activations polybuffer.";
static constexpr const char* no_filter_polybuf_symbol = "Could not extract symbol from filters polybuffer name";
static constexpr const char* no_env_polybuf_symbol = "Could not extract symbol from envelopes polybuffer name";
static constexpr const char* get_buffer_fail = "Could not get buffer for name %s";
private:
error_strings(){}
};
// /*****************
// A template function to reduce duplication in copying back to Max buffers
// My hope is to render this either obsolete or much simpler once algo code
// is refactored.
// At present it needs to be fed a vector of vectors (ugh) and a function that
// does the copying (see under)
// *******************/
// template<typename F>
// void copy_to_buffer(t_object* obj, int rank, t_symbol* polybuf_name,real_matrix &mtrx,F&& copy_fn, double scale=1.)
// {
// for(int i = 0; i < rank; i++)
// {
// std::ostringstream ss;
// ss << polybuf_name->s_name << "." << i+1;
// const char* buffername = ss.str().c_str();
//
// t_buffer_ref* ref = buffer_ref_new(obj, gensym(buffername));
// t_buffer_obj* this_buffer = buffer_ref_getobject(ref);
//
// if(this_buffer)
// {
// float* samps = buffer_locksamples(this_buffer);
// if(samps)
// {
// copy_fn(samps,mtrx,i,scale);
// buffer_unlocksamples(this_buffer);
// }
// }
//
// if(ref)
// object_free(ref);
//
// }
// }
//
// void from_cols(float* dst, real_matrix &m, long i,double scale)
// {
// for(long j = 0; j< m[0].size(); j++)
// dst[j] = m[i][j] * scale;
// }
//
// void from_rows(float* dst,real_matrix &m, long i,double scale)
// {
// for(long j = 0; j < m.size(); j++)
// dst[j] = m[j][i] * scale;
// }
}
}
#endif /* fluid_nmf_tilde_util_h */
Loading…
Cancel
Save