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#ifndef WSCLEAN_WGRIDDER_H_
#define WSCLEAN_WGRIDDER_H_
#include <complex>
#include <cstddef>
#include <vector>
#include <aocommon/banddata.h>
#include "ducc0/wgridder/wgridder.h"
#include "../gridding/gainmode.h"
#include "../gridding/msgridder.h"
namespace wsclean {
class MsGridder;
struct VisibilityCallbackData {
size_t n_channels;
const aocommon::BandData &selected_band;
size_t data_desc_id;
const std::pair<size_t, size_t> *antennas;
const std::complex<float> *visibilities;
const double *uvws;
const size_t *time_offsets;
MsGridder *gridder;
size_t n_antennas;
const std::complex<float> *parm_response;
const BeamResponseCacheChunk &beam_response;
};
class WGridderBase {
public:
virtual ~WGridderBase() = default;
virtual size_t ConstantMemoryUsage() const = 0;
virtual size_t PerVisibilityMemoryUsage() const = 0;
virtual void InitializeInversion() = 0;
virtual void AddInversionData(size_t n_rows, size_t n_chan, const double *uvw,
const double *freq,
const std::complex<float> *vis) = 0;
virtual void AddInversionDataWithCorrectionCallback(
GainMode mode, size_t n_polarizations, size_t n_rows, const double *uvws,
const double *frequencies, VisibilityCallbackData &data) = 0;
virtual void FinalizeImage(double multiplication_factor) = 0;
virtual std::vector<float> RealImage() = 0;
virtual void InitializePrediction(const float *image_data) = 0;
virtual void PredictVisibilities(size_t n_rows, size_t n_channels,
const double *uvws,
const double *frequencies,
std::complex<float> *visibilities) const = 0;
};
/**
* VisibilityCallbackBuffer implements a virtual buffer replacement to the
* `cmav` that would ordinarily be used to pass visibility data into DUCC.
*
* Ordinarily the `cmav` that DUCC takes would contain visibilities with facet
* solutions pre-applied.
* With VisibilityCallbackBuffer we instead hold in memory a buffer that does
* not have facet solutions applied.
* When DUCC requests from the buffer a specific visibility for a specific facet
* the facet solution is applied "on the fly" and the required value returned.
* Some internal caching is applied at the row level to help a bit with
* efficiency.
*/
template <typename TVisibility, typename TInfo = ducc0::detail_mav::mav_info<2>>
class VisibilityCallbackBuffer : public TInfo {
public:
VisibilityCallbackBuffer(
size_t n_rows, VisibilityCallbackData &data,
std::function<std::complex<float>(
size_t, size_t, size_t, MsGridder *, const std::complex<float> *,
const double *uvws, const aocommon::BandData &selected_band,
size_t data_desc_id, const std::complex<float> *,
const BeamResponseCacheChunk &, const size_t *,
const std::pair<size_t, size_t> *)>
visibility_callback)
: TInfo({n_rows, data.n_channels}),
n_antennas_(data.n_antennas),
n_channels_(data.n_channels),
selected_band_(data.selected_band),
data_desc_id_(data.data_desc_id),
antennas_(data.antennas),
visibilities_(data.visibilities),
uvws_(data.uvws),
time_offsets_(data.time_offsets),
gridder_(data.gridder),
parm_response_(data.parm_response),
beam_response_(data.beam_response),
visibility_callback_(std::move(visibility_callback)) {}
template <typename Index>
const TVisibility raw(Index index) const {
return visibility_callback_(index, n_channels_, n_antennas_, gridder_,
visibilities_, uvws_, selected_band_,
data_desc_id_, parm_response_, beam_response_,
time_offsets_, antennas_);
}
template <typename... Params>
const TVisibility operator()(Params... params) const {
return raw(TInfo::idx(params...));
}
// Turn all prefetch operations inside DUCC into null ops
// As we return by value and are not a persistent buffer prefetching doesn't
// make sense in this context
template <typename Index>
void prefetch_r(Index) const {}
template <typename Index>
void prefetch_w(Index) const {}
template <typename... Params>
void prefetch_r(Params...) const {}
private:
size_t n_antennas_;
// Number of channels per row of visibilities
size_t n_channels_;
const aocommon::BandData &selected_band_;
size_t data_desc_id_;
const std::pair<size_t, size_t> *antennas_;
const std::complex<float> *visibilities_;
const double *uvws_;
/**
* When applying corrections sequentially a time_offset is calculated by @ref
* CacheParmResponse() for each row, used for applying the corrections, and
* then the time_offset for the next row calculated on top of it.
* As the time_offset is needed when we apply the corrections, and we can't
* compute it again here without sequentially going through every single row,
* we have to store all of them in a buffer to be used when we apply the
* corrections.
*/
const size_t *time_offsets_;
MsGridder *gridder_;
const std::complex<float> *parm_response_;
const BeamResponseCacheChunk &beam_response_;
std::function<std::complex<float>(
size_t, size_t, size_t, MsGridder *, const std::complex<float> *,
const double *uvws, const aocommon::BandData &selected_band,
size_t data_desc_id, const std::complex<float> *,
const BeamResponseCacheChunk &, const size_t *,
const std::pair<size_t, size_t> *)>
visibility_callback_;
};
namespace internal {
/**
* VisibilityCallback implements the logic required by @ref
* VisibilityCallbackBuffer::raw This is delibritely isolated into a standalone
* function that can be passed into @ref VisibilityCallbackBuffer as a
* std::function in order to break coupling with DUCC.
* @ref VisibilityCallbackBuffer is passed into DUCC as a template paramater and
* therefore for each different instance/type of @ref VisibilityCallbackBuffer a
* new/different instantiation of DUCC is created. This leads to longer compile
* times and larger binaries, which is especially problematic for builds with
* debug symbols. By breaking the coupling we avoid these multiple
* instantiations. Removing this decoupling would theoretically remove some
* "function call" overhead which potentially might improve performance, however
* testing at the time of this writing code showed that doing so actually harmed
* performance and that the decoupled code outperformed the coupled code by
* about 5%
*/
template <GainMode Mode, size_t NPolarizations, size_t NParms, bool ApplyBeam,
bool ApplyForward, bool HasH5Parm, bool ApplyRotation>
const std::complex<float> VisibilityCallback(
size_t index, size_t n_channels, size_t n_antennas, MsGridder *gridder,
const std::complex<float> *visibilities, const double *uvws,
const aocommon::BandData &selected_band, size_t data_desc_id,
const std::complex<float> *parm_response,
const BeamResponseCacheChunk &beam_response, const size_t *time_offsets,
const std::pair<size_t, size_t> *antennas) {
// Calculate offsets
const size_t row = index / n_channels;
size_t channel = index % n_channels;
// Retrieve value for offsets
const std::pair<size_t, size_t> &antenna_pair = antennas[row];
const size_t &time_offset = time_offsets[row];
std::complex<float> visibilities_temp[NPolarizations];
std::copy_n(&visibilities[(row * n_channels * NPolarizations) +
(channel * NPolarizations)],
NPolarizations, visibilities_temp);
// Apply rotation for direction dependent PSF
if constexpr (ApplyRotation) {
double dl = gridder->LShift();
double dm = gridder->MShift();
gridder->RotateSingleVisibilityToPhaseCenter<NPolarizations>(
dl, dm, channel, selected_band, uvws + (row * 3),
&visibilities_temp[0]);
}
// Apply correction
const aocommon::VectorMap<std::vector<aocommon::MC2x2F>> empty_beam_response;
const aocommon::VectorMap<std::vector<aocommon::MC2x2F>>
&cached_beam_response =
ApplyBeam ? beam_response.GetCachedBeamResponseForRow(row)
: empty_beam_response;
gridder->ApplySingleCorrection<Mode, NParms, ModifierBehaviour::kApply,
ApplyBeam, ApplyForward, HasH5Parm>(
parm_response, channel, n_channels, data_desc_id, n_antennas,
visibilities_temp, nullptr, antenna_pair.first, antenna_pair.second,
time_offset, nullptr, cached_beam_response);
internal::CollapseData<NPolarizations>(1, visibilities_temp,
gridder->Polarization());
return visibilities_temp[0];
}
} // namespace internal
/* Memory usage of this gridder is:
between calls:
width*height*4 between calls (dirty image buffer)
during gridding/degridding calls:
width*height*(
4 + (dirty image buffer)
8*2*2 + (padded complex uv grid)
8*2*2 ) (second uv grid used during FFT, not really necessary)
+ nvis_unflagged*8 (index arrays, rough guess)
*/
template <typename NumT>
class WGridder final : public WGridderBase {
private:
static constexpr double sigma_min = 1.1;
static constexpr double sigma_max = 2.0;
size_t width_;
size_t height_;
size_t trimmed_width_;
size_t trimmed_height_;
size_t n_threads_;
double pixel_size_x_;
double pixel_size_y_;
double l_shift_;
double m_shift_;
double epsilon_;
std::vector<NumT> image_;
size_t verbosity_;
bool tuning_;
public:
/** Construct a new gridder with given settings.
* @param epsilon The requested accuracy of the gridding process.
* Affects the support of the employed kernel. Useful values
* range between 1e-2 and 1e-6 (for single-precision visibilities).
* @param verbosity The amount of diagnostic output printed
* 0: no output
* 1: print short overview for every inversion/prediction
* 2: print information for every processed w-plane
*/
WGridder(size_t width, size_t height, size_t trimmed_width,
size_t trimmed_height, double pixel_size_x, double pixel_size_y,
double l_shift, double m_shift, size_t n_threads,
double epsilon = 1e-4, size_t verbosity = 0, bool tuning_ = false);
WGridder(const WGridder &) = delete;
WGridder &operator=(const WGridder &) = delete;
/**
* @return The constant base memory usage of the object in bytes
*/
size_t ConstantMemoryUsage() const final;
/**
* @return Additional memory required per gridded visibility in bytes.
*/
size_t PerVisibilityMemoryUsage() const final;
/**
* Initialize a new inversion gridding pass. This just
* intializes the accumulated dirty image with zero.
*/
void InitializeInversion() final;
/** Add more data to the current inversion operation.
* The visibilities will be gridded, and the dirty image
* will be updated accordingly.
* visibilities with value 0 will be skipped entirely.
* @param uvws pointer to n_rows*3 doubles containing UVW in m.
* U(row) := uvws[3*row ]
* V(row) := uvws[3*row+1]
* W(row) := uvws[3*row+2]
* @param visibilities pointer to nrow*n_channels complex<float> containing
* weighted and corrected visibilities: visibility(row, chan) :=
* vis[row*n_channels + chan]
*/
void AddInversionData(size_t n_rows, size_t n_channels, const double *uvws,
const double *frequencies,
const std::complex<float> *visibilities) final;
/** Equivalent to @ref AddInversionData() but without facet solutions
* pre-applied and with additional paramaters to allow the creation of a
* callback that can apply solutions "on the fly" as required
*
* It is expected that corrections have already been summed via @ref
* ApplyCorrections<ModifierBehaviour::kSum>()
*
* @param n_polarizations The number of polarizations per visibility in @ref
* visibilities
* @param antennas Pointer to n_rows `std::pair<size_t, size_t>` containing
* the antenna pair for each row of visibilities.
* @param uvws Pointer to n_rows*3 doubles containing UVW in meters.
* U(row) := uvws[3*row ]
* V(row) := uvws[3*row+1]
* W(row) := uvws[3*row+2]
* @param frequencies Pointer to n_channels doubles containing channel
* frequencies
* @param visibilities Pointer to n_rows*n_channels*n_polarizations
* `complex<float>` containing weighted but uncorrected and not yet collapsed
* visibilities: visibility(row, chan) := vis[row*n_chan + chan]
* @param time_offsets Pointer to n_rows `size_t` containing the time offset
* as calculated by @ref CacheParmResponse() for the corresponding visibility
* row when applying @ref ApplyCorrections<ModifierBehaviour::kSum>()
* on it For further explanation see @ref
* VisibilityCallbackBuffer::time_offsets_
* @param gridder Pointer to a gridder that can be called back into in order
* to apply solutions
*/
void AddInversionDataWithCorrectionCallback(
GainMode mode, size_t n_polarizations, size_t n_rows, const double *uvws,
const double *frequencies, VisibilityCallbackData &data) final;
/**
* Finalize inversion once all passes are performed.
* @param multiplication_factor Apply this factor to all pixels. This can be
* used to normalize the image for the weighting scheme.
*/
void FinalizeImage(double multiplication_factor) final;
/**
* Get the untrimmed image result of inversion. This is an array of size width
* x height, and can be indexed with [x + y*width]. It is allowed to change
* this image, e.g. set the horizon to zero before saving to fits. This call
* is only valid once @ref FinalizeImage() has been called.
*/
std::vector<float> RealImage() final;
/**
* Initialize gridder for prediction and specify image to predict for.
* @param image The (untrimmed) model image that is to be predicted for. This
* is an array of width * height size, index by (x + width*y).
*/
void InitializePrediction(const float *image_data) final;
/** Predicts visibilities from the current dirty image.
* FIXME: how do we indicate flagged visibilities that do not
* need to be computed? Some special value on input?
* @param uvws pointer to n_rows*3 doubles containing UVW in m.
* U(row) := uvws[3*row ]
* V(row) := uvws[3*row+1]
* W(row) := uvws[3*row+2]
* @param visibilities pointer to nrow*n_channels complex<float> containing
* weighted visibilities visibility(row, chan) := vis[row*n_channels + chan]
*/
void PredictVisibilities(size_t n_rows, size_t n_channels, const double *uvws,
const double *frequencies,
std::complex<float> *visibilities) const final;
private:
/** Internal helper to handle the processing of
* AddInversionData/AddInversionDataWithCorrectionCallback
* @tparam TMs Container type for visibilities, must be derived from or
* compatible with cmav interface
* @param freq Buffer via which all frequencies for this inversion can be
* accessed, indexing must be in ascending order
* @param ms Virtual or actual buffer via which all visibilities for this
* inversion can be accessed, indexing must be in ascending order
*/
template <typename Tms>
void AddInversionMs(size_t n_rows, const double *uvw,
const ducc0::cmav<double, 1> &freq, Tms &ms);
template <typename Tms>
void AddInversionMsImplementation(size_t n_rows, const double *uvw,
const ducc0::cmav<double, 1> &freq,
Tms &ms) {
ducc0::cmav<double, 2> uvw2(uvw, {n_rows, 3});
ducc0::vmav<NumT, 2> tdirty({trimmed_width_, trimmed_height_});
ducc0::cmav<float, 2> twgt(nullptr, {0, 0});
ducc0::cmav<std::uint8_t, 2> tmask(nullptr, {0, 0});
if (!tuning_)
ducc0::ms2dirty<NumT, NumT>(uvw2, freq, ms, twgt, tmask, pixel_size_x_,
pixel_size_y_, epsilon_, true, n_threads_,
tdirty, verbosity_, true, false, sigma_min,
sigma_max, -l_shift_, -m_shift_);
else
ducc0::ms2dirty_tuning<NumT, NumT>(
uvw2, freq, ms, twgt, tmask, pixel_size_x_, pixel_size_y_, epsilon_,
true, n_threads_, tdirty, verbosity_, true, false, sigma_min,
sigma_max, -l_shift_, -m_shift_);
for (size_t i = 0; i < trimmed_width_ * trimmed_height_; ++i)
image_[i] += tdirty.raw(i);
}
// Each of the following versions of CreateAndAddInversionMs converts the
// first parameter into a template argument and then passes the rest of the
// parameters on to the next call.
// We add multiple template parameters in a chain to avoid an exponential
// explosion of boilerplate code.
// Sorted and numbered in the order that they will be called.
void CreateAndAddInversionMs(GainMode mode, size_t n_polarizations,
size_t n_parms, bool apply_beam,
bool apply_forward, bool has_h5_parm,
size_t n_rows, const double *uvws,
const ducc0::cmav<double, 1> &frequencies,
VisibilityCallbackData &data);
template <GainMode Mode>
void CreateAndAddInversionMs2(size_t n_polarizations, size_t n_parms,
bool apply_beam, bool apply_forward,
bool has_h5_parm, size_t n_rows,
const double *uvws,
const ducc0::cmav<double, 1> &frequencies,
VisibilityCallbackData &data);
template <GainMode Mode, size_t NPolarizations>
void CreateAndAddInversionMs3(size_t n_parms, bool apply_beam,
bool apply_forward, bool has_h5_parm,
size_t n_rows, const double *uvws,
const ducc0::cmav<double, 1> &frequencies,
VisibilityCallbackData &data);
template <GainMode Mode, size_t NPolarizations, size_t NParms>
void CreateAndAddInversionMs4(bool apply_beam, bool apply_forward,
bool has_h5_parm, size_t n_rows,
const double *uvws,
const ducc0::cmav<double, 1> &frequencies,
VisibilityCallbackData &data);
template <GainMode Mode, size_t NPolarizations, size_t NParms, bool ApplyBeam>
void CreateAndAddInversionMs5(bool apply_forward, bool has_h5_parm,
size_t n_rows, const double *uvws,
const ducc0::cmav<double, 1> &frequencies,
VisibilityCallbackData &data);
template <GainMode Mode, size_t NPolarizations, size_t NParms, bool ApplyBeam,
bool ApplyForward>
void CreateAndAddInversionMs6(bool has_h5_parm, size_t n_rows,
const double *uvws,
const ducc0::cmav<double, 1> &frequencies,
VisibilityCallbackData &data);
template <GainMode Mode, size_t NPolarizations, size_t NParms, bool ApplyBeam,
bool ApplyForward, bool HasH5Parm>
void CreateAndAddInversionMs7(size_t n_rows, const double *uvws,
const ducc0::cmav<double, 1> &frequencies,
VisibilityCallbackData &data);
// Construct a VisibilityCallbackBuffer object using the remaining paramaters
// and templatized based on all the paramaters that previous calls in the
// template chain have parsed.
// Call AddInversionMs with the constructed callback object.
template <GainMode Mode, size_t NPolarizations, size_t NParms, bool ApplyBeam,
bool ApplyForward, bool HasH5Parm, bool ApplyRotation>
void CreateAndAddInversionMs8(size_t n_rows, const double *uvws,
const ducc0::cmav<double, 1> &frequencies,
VisibilityCallbackData &data);
};
// Prevent implicit instantiation of these templates as they are costly.
// Explicit instantiation is done instead, see:
// wgridder_double.cpp
// wgridder_float.cpp
extern template class WGridder<float>;
extern template class WGridder<double>;
extern template void
WGridder<float>::AddInversionMs<VisibilityCallbackBuffer<std::complex<float>>>(
size_t n_rows, const double *uvw, const ducc0::cmav<double, 1> &freq,
VisibilityCallbackBuffer<std::complex<float>> &ms);
extern template void
WGridder<double>::AddInversionMs<VisibilityCallbackBuffer<std::complex<float>>>(
size_t n_rows, const double *uvw, const ducc0::cmav<double, 1> &freq,
VisibilityCallbackBuffer<std::complex<float>> &ms);
} // namespace wsclean
#endif // WSCLEAN_WGRIDDER_H_
/*
Usage scenario:
WGridder gridder(width, height, pixel_size_x, pixel_size_y,
n_threads, 1e-5);
// determine number of visibilities that can be gridded in one go, using
// gridder.memUsage() and information about available memory.
// Making the chunks as large as posssible will improve perfrmance.
// Making chunks compact in w will also help a lot.
gridder.InitializeInversion();
for (auto &chunk: chunks)
gridder.AddInversionData(...)
auto res = gridder.RealImage();
*/
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