#include <iostream>

#include "../wstackinggridder.h"

#include <aocommon/image.h>
#include <aocommon/system.h>

int main(int argc, char* argv[]) {
  const size_t width = 4000, height = 4000;
  const double pixelScale =
      1.0 / 60.0 * (M_PI / 180.0);  // one arcmin in radians
  const size_t threadCount =
      aocommon::system::ProcessorCount();  // number of CPUs in system

  // Get available memory
  const long memSize = aocommon::system::TotalMemory();

  // Initialize an image with all zero except one pixel
  aocommon::Image image(width, height, 0.0);
  const size_t sourceX = width / 2 - width / 17,
               sourceY = height / 2 - height / 21;
  image[sourceX + sourceY * width] = 100.0;

  // Initialize the gridder
  // Here, larger and more accurate values are used for the kernel size (here:
  // 15) and oversampling factor (here: 201). Often, the default values are good
  // enough and provide a better compromise between accuracy and performance. To
  // get the default values, the last two parameters can be left out.
  wsclean::WStackingGridder<float> gridder(width, height, pixelScale,
                                           pixelScale, threadCount, 15, 1023);

  // Prepare the w-layers. This example disables w-term correction by setting
  // the number of w-layers to 1, and therefore this call becomes quite simple.
  // For w-term correction, actually proper w-extremes should have been given.
  // Specifying a memsize will allow the gridder to warn when not enough memory
  // would be available. Alternatively, a very large number can be given to
  // avoid this.
  gridder.PrepareWLayers(1, memSize, -1.0, 1.0);

  // To keep things simple, we do not handle situations in which multiple passes
  // would have been required. Since only one w-layer is requested, this test is
  // not necessary, but here for good style.
  if (gridder.NPasses() != 1) {
    std::cerr << "Error; w-layers do not all fit in memory at once.\n";
    return -1;
  }

  // Now we supply the image.
  gridder.InitializePrediction(std::move(image));

  // Start the first (and only) pass. This will perform the FFTs for this pass.
  // Since there is only one w-layer, only one FFT will be performed.
  gridder.StartPredictionPass(0);

  // We can now start to sample visibilities
  // We calculate some random uvw's that are likely within the
  // gridded area. These are in units of number of wavelengths.
  double u = 100.0;
  double v = 10.0;
  double w = 10.0;

  for (size_t i = 0; i != 20; ++i, u /= 2.0, v /= 2.0, w /= 2.0) {
    std::complex<float> value;
    gridder.SampleDataSample(value, u, v, w);
    std::cout << "uvw = (" << u << ", " << v << ", " << w
              << "), visibility = " << value << '\n';
  }
}
