nifty_gridder.cc 30.4 KB
Newer Older
Martin Reinecke's avatar
Martin Reinecke committed
1
2
3
4
5
6
7
8
9
10
11
12
13
14
/*
 *  This file is part of nifty_gridder.
 *
 *  nifty_gridder is free software; you can redistribute it and/or modify
 *  it under the terms of the GNU General Public License as published by
 *  the Free Software Foundation; either version 2 of the License, or
 *  (at your option) any later version.
 *
 *  nifty_gridder is distributed in the hope that it will be useful,
 *  but WITHOUT ANY WARRANTY; without even the implied warranty of
 *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 *  GNU General Public License for more details.
 *
 *  You should have received a copy of the GNU General Public License
Martin Reinecke's avatar
Martin Reinecke committed
15
 *  along with nifty_gridder; if not, write to the Free Software
Martin Reinecke's avatar
Martin Reinecke committed
16
17
18
 *  Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA  02110-1301  USA
 */

Martin Reinecke's avatar
Martin Reinecke committed
19
20
21
/* Copyright (C) 2019 Max-Planck-Society
   Author: Martin Reinecke */

Martin Reinecke's avatar
import  
Martin Reinecke committed
22
23
#include <pybind11/pybind11.h>
#include <pybind11/numpy.h>
Martin Reinecke's avatar
Martin Reinecke committed
24

Martin Reinecke's avatar
Martin Reinecke committed
25
#include "gridder_cxx.h"
Martin Reinecke's avatar
import  
Martin Reinecke committed
26
27

using namespace std;
Martin Reinecke's avatar
Martin Reinecke committed
28
using namespace gridder;
Martin Reinecke's avatar
import  
Martin Reinecke committed
29
30
31
32
33

namespace py = pybind11;

namespace {

Martin Reinecke's avatar
Martin Reinecke committed
34
35
auto None = py::none();

36
template<typename T>
Martin Reinecke's avatar
updates    
Martin Reinecke committed
37
  using pyarr = py::array_t<T, 0>;
Martin Reinecke's avatar
import  
Martin Reinecke committed
38

Martin Reinecke's avatar
Martin Reinecke committed
39
40
template<typename T> pyarr<T> makeArray(const vector<size_t> &shape)
  { return pyarr<T>(shape); }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
41

Martin Reinecke's avatar
merge    
Martin Reinecke committed
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
void checkArray(const py::array &arr, const char *aname,
  const vector<size_t> &shape)
  {
  if (size_t(arr.ndim())!=shape.size())
    {
    cerr << "Array '" << aname << "' has " << arr.ndim() << " dimensions; "
            "expected " << shape.size() << endl;
    throw runtime_error("bad dimensionality");
    }
  for (size_t i=0; i<shape.size(); ++i)
    if ((shape[i]!=0) && (size_t(arr.shape(i))!=shape[i]))
      {
      cerr << "Dimension " << i << " of array '" << aname << "' has size "
           << arr.shape(i) << "; expected " << shape[i] << endl;
      throw runtime_error("bad array size");
      }
  }

Martin Reinecke's avatar
Martin Reinecke committed
60
template<typename T> pyarr<T> provideArray(const py::object &in,
Martin Reinecke's avatar
merge    
Martin Reinecke committed
61
62
  const vector<size_t> &shape)
  {
63
  if (in.is_none())
Martin Reinecke's avatar
merge    
Martin Reinecke committed
64
65
66
67
68
69
70
71
    {
    auto tmp_ = makeArray<T>(shape);
    size_t sz = size_t(tmp_.size());
    auto tmp = tmp_.mutable_data();
    for (size_t i=0; i<sz; ++i)
      tmp[i] = T(0);
    return tmp_;
    }
72
  auto tmp_ = in.cast<pyarr<T>>();
Martin Reinecke's avatar
merge    
Martin Reinecke committed
73
74
75
76
  checkArray(tmp_, "temporary", shape);
  return tmp_;
  }

Martin Reinecke's avatar
Martin Reinecke committed
77
78
79
80
81
82
83
84
85
86
template<typename T> pyarr<T> providePotentialArray(const py::object &in,
  const vector<size_t> &shape)
  {
  if (in.is_none())
    return makeArray<T>(vector<size_t>(shape.size(), 0));
  auto tmp_ = in.cast<pyarr<T>>();
  checkArray(tmp_, "temporary", shape);
  return tmp_;
  }

Martin Reinecke's avatar
Martin Reinecke committed
87
template<typename T> pyarr<T> provideCArray(py::object &in,
Martin Reinecke's avatar
merge    
Martin Reinecke committed
88
89
  const vector<size_t> &shape)
  {
90
  if (in.is_none())
Martin Reinecke's avatar
merge    
Martin Reinecke committed
91
92
93
94
95
96
97
98
    {
    auto tmp_ = makeArray<T>(shape);
    size_t sz = size_t(tmp_.size());
    auto tmp = tmp_.mutable_data();
    for (size_t i=0; i<sz; ++i)
      tmp[i] = T(0);
    return tmp_;
    }
Martin Reinecke's avatar
Martin Reinecke committed
99
  auto tmp_ = in.cast<pyarr<T>>();
Martin Reinecke's avatar
merge    
Martin Reinecke committed
100
101
102
103
  checkArray(tmp_, "temporary", shape);
  return tmp_;
  }

Martin Reinecke's avatar
Martin Reinecke committed
104
template<size_t ndim, typename T> mav<T,ndim> make_mav(pyarr<T> &in)
Martin Reinecke's avatar
Martin Reinecke committed
105
  {
Martin Reinecke's avatar
Martin Reinecke committed
106
107
108
109
  myassert(ndim==in.ndim(), "dimension mismatch");
  array<size_t,ndim> dims;
  array<ptrdiff_t,ndim> str;
  for (size_t i=0; i<ndim; ++i)
Martin Reinecke's avatar
Martin Reinecke committed
110
    {
Martin Reinecke's avatar
Martin Reinecke committed
111
112
113
    dims[i]=in.shape(i);
    str[i]=in.strides(i)/sizeof(T);
    myassert(str[i]*ptrdiff_t(sizeof(T))==in.strides(i), "weird strides");
Martin Reinecke's avatar
Martin Reinecke committed
114
    }
Martin Reinecke's avatar
Martin Reinecke committed
115
  return mav<T, ndim>(in.mutable_data(),dims,str);
Martin Reinecke's avatar
Martin Reinecke committed
116
  }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
117
template<size_t ndim, typename T> const_mav<T,ndim> make_const_mav(const pyarr<T> &in)
Martin Reinecke's avatar
Martin Reinecke committed
118
119
120
121
122
123
124
125
126
127
  {
  myassert(ndim==in.ndim(), "dimension mismatch");
  array<size_t,ndim> dims;
  array<ptrdiff_t,ndim> str;
  for (size_t i=0; i<ndim; ++i)
    {
    dims[i]=in.shape(i);
    str[i]=in.strides(i)/sizeof(T);
    myassert(str[i]*ptrdiff_t(sizeof(T))==in.strides(i), "weird strides");
    }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
128
  return const_mav<T, ndim>(in.data(),dims,str);
Martin Reinecke's avatar
Martin Reinecke committed
129
  }
Martin Reinecke's avatar
Martin Reinecke committed
130

Martin Reinecke's avatar
Martin Reinecke committed
131
constexpr auto PyBaselines_DS = R"""(
132
133
134
135
136
137
138
139
140
Class storing UVW coordinates and channel information.

Parameters
==========
coord: np.array((nrows, 3), dtype=np.float)
    u, v and w coordinates for each row
freq: np.array((nchannels,), dtype=np.float)
    frequency for each individual channel (in Hz)
)""";
Martin Reinecke's avatar
Martin Reinecke committed
141
template<typename T> class PyBaselines: public Baselines<T>
Martin Reinecke's avatar
Martin Reinecke committed
142
  {
Martin Reinecke's avatar
Martin Reinecke committed
143
144
145
146
147
  protected:
    using Baselines<T>::coord;
    using Baselines<T>::f_over_c;
    using Baselines<T>::nrows;
    using Baselines<T>::nchan;
Martin Reinecke's avatar
Martin Reinecke committed
148
149

  public:
Martin Reinecke's avatar
Martin Reinecke committed
150
151
    using Baselines<T>::Baselines;
    PyBaselines(const pyarr<T> &coord, const pyarr<T> &freq)
Martin Reinecke's avatar
Martin Reinecke committed
152
      : Baselines<T>(make_const_mav<2>(coord), make_const_mav<1>(freq))
Martin Reinecke's avatar
Martin Reinecke committed
153
      {}
Martin Reinecke's avatar
Martin Reinecke committed
154

Martin Reinecke's avatar
Martin Reinecke committed
155
156
157
    using Baselines<T>::effectiveCoord;
    using Baselines<T>::Nrows;
    using Baselines<T>::Nchannels;
Martin Reinecke's avatar
updates    
Martin Reinecke committed
158

159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
    static constexpr auto ms2vis_DS = R"""(
    Extracts visibility data from a measurement for the provided indices.

    Parameters
    ==========
    ms: np.array((nrows, nchannels), dtype=np.complex)
        the measurement set's visibility data
    idx: np.array((nvis,), dtype=np.uint32)
        the indices to be extracted

    Returns
    =======
    np.array((nvis,), dtype=np.complex)
        The visibility data for the index array
    )""";
174

Martin Reinecke's avatar
Martin Reinecke committed
175
   // using Baselines<T>::effectiveUVW;
Martin Reinecke's avatar
Martin Reinecke committed
176
    pyarr<T> effectiveuvw(const pyarr<uint32_t> &idx_) const
Martin Reinecke's avatar
Martin Reinecke committed
177
      {
178
      size_t nvis = size_t(idx_.shape(0));
Martin Reinecke's avatar
Martin Reinecke committed
179
      auto idx=make_const_mav<1>(idx_);
180
      auto res_=makeArray<T>({nvis, 3});
Martin Reinecke's avatar
Martin Reinecke committed
181
      auto res=make_mav<2>(res_);
Martin Reinecke's avatar
Martin Reinecke committed
182
183
184
185
      {
      py::gil_scoped_release release;
      Baselines<T>::effectiveUVW(idx,res);
      }
186
      return res_;
Martin Reinecke's avatar
Martin Reinecke committed
187
      }
188

Martin Reinecke's avatar
Martin Reinecke committed
189
    template<typename T2> pyarr<T2> ms2vis(const pyarr<T2> &ms_,
Martin Reinecke's avatar
Martin Reinecke committed
190
      const pyarr<uint32_t> &idx_, size_t nthreads) const
Martin Reinecke's avatar
updates    
Martin Reinecke committed
191
      {
Martin Reinecke's avatar
Martin Reinecke committed
192
      auto idx=make_const_mav<1>(idx_);
Martin Reinecke's avatar
Martin Reinecke committed
193
      size_t nvis = size_t(idx.shape(0));
Martin Reinecke's avatar
Martin Reinecke committed
194
      auto ms = make_const_mav<2>(ms_);
Martin Reinecke's avatar
merge    
Martin Reinecke committed
195
      auto res=makeArray<T2>({nvis});
Martin Reinecke's avatar
Martin Reinecke committed
196
      auto vis = make_mav<1>(res);
Martin Reinecke's avatar
Martin Reinecke committed
197
198
      {
      py::gil_scoped_release release;
Martin Reinecke's avatar
Martin Reinecke committed
199
      Baselines<T>::ms2vis(ms, idx, vis, nthreads);
Martin Reinecke's avatar
Martin Reinecke committed
200
      }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
201
202
203
      return res;
      }

204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
    static constexpr auto vis2ms_DS = R"""(
    Produces a new MS with the provided visibilities set.

    Parameters
    ==========
    vis: np.array((nvis,), dtype=np.complex)
        The visibility data for the index array
    idx: np.array((nvis,), dtype=np.uint32)
        the indices to be inserted
    ms_in: np.array((nrows, nchannels), dtype=np.complex), optional
        input measurement set to which the visibilities are added.

    Returns
    =======
    np.array((nrows, nchannels), dtype=np.complex)
        the measurement set's visibility data (0 where not covered by idx)
    )""";
Martin Reinecke's avatar
Martin Reinecke committed
221
    template<typename T2> pyarr<T2> vis2ms(const pyarr<T2> &vis_,
Martin Reinecke's avatar
Martin Reinecke committed
222
      const pyarr<uint32_t> &idx_, py::object &ms_in, size_t nthreads) const
Martin Reinecke's avatar
updates    
Martin Reinecke committed
223
      {
Martin Reinecke's avatar
Martin Reinecke committed
224
225
      auto vis=make_const_mav<1>(vis_);
      auto idx=make_const_mav<1>(idx_);
Martin Reinecke's avatar
merge    
Martin Reinecke committed
226
      auto res = provideArray<T2>(ms_in, {nrows, nchan});
Martin Reinecke's avatar
Martin Reinecke committed
227
      auto ms = make_mav<2>(res);
Martin Reinecke's avatar
Martin Reinecke committed
228
229
      {
      py::gil_scoped_release release;
Martin Reinecke's avatar
Martin Reinecke committed
230
      Baselines<T>::vis2ms(vis, idx, ms, nthreads);
Martin Reinecke's avatar
Martin Reinecke committed
231
      }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
232
233
      return res;
      }
Martin Reinecke's avatar
Martin Reinecke committed
234
235
  };

236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
constexpr auto grid2dirty_DS = R"""(
Converts from UV grid to dirty image (FFT, cropping, correction)

Parameters
==========
grid: np.array((nu, nv), dtype=np.float64)
    gridded UV data

Returns
=======
nd.array((nxdirty, nydirty), dtype=np.float64)
    the dirty image
)""";

constexpr auto dirty2grid_DS = R"""(
Converts from a dirty image to a UV grid (correction, padding, FFT)

Parameters
==========
dirty: nd.array((nxdirty, nydirty), dtype=np.float64)
    the dirty image

Returns
=======
np.array((nu, nv), dtype=np.float64)
    gridded UV data
)""";

Martin Reinecke's avatar
Martin Reinecke committed
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
constexpr auto apply_taper_DS = R"""(
Applies the taper (or its inverse) to an image

Parameters
==========
img: nd.array((nxdirty, nydirty), dtype=np.float64)
    the image
divide: bool
    if True, the routine dividex by the taper, otherwise it multiplies by it

Returns
=======
np.array((nxdirty, nydirty), dtype=np.float64)
    the image with the taper applied
)""";

Martin Reinecke's avatar
Martin Reinecke committed
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
constexpr auto apply_wscreen_DS = R"""(
Applies the w screen to an image

Parameters
==========
dirty: nd.array((nxdirty, nydirty), dtype=np.complex128)
    the image
w : float
    the w value to use
adjoint: bool
    if True, apply the complex conjugate of the w screen

Returns
=======
np.array((nxdirty, nydirty), dtype=np.complex128)
    the image with the w screen applied
)""";

298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
constexpr auto GridderConfig_DS = R"""(
Class storing information related to the gridding/degridding process.

Parameters
==========
nxdirty: int
    x resolution of the dirty image; must be even
nydirty: int
    y resolution of the dirty image; must be even
epsilon: float
    required accuracy for the gridding/degridding step
    Must be >= 2e-13.
pixsize_x: float
    Pixel size in x direction (radians)
pixsize_y: float
    Pixel size in y direction (radians)
)""";
Martin Reinecke's avatar
Martin Reinecke committed
315
template<typename T> class PyGridderConfig: public GridderConfig<T>
Martin Reinecke's avatar
Martin Reinecke committed
316
  {
Martin Reinecke's avatar
Martin Reinecke committed
317
318
319
320
321
  protected:
    using GridderConfig<T>::nx_dirty;
    using GridderConfig<T>::ny_dirty;
    using GridderConfig<T>::nu;
    using GridderConfig<T>::nv;
Martin Reinecke's avatar
Martin Reinecke committed
322

Martin Reinecke's avatar
Martin Reinecke committed
323
  public:
Martin Reinecke's avatar
Martin Reinecke committed
324
325
    using GridderConfig<T>::GridderConfig;
    PyGridderConfig(size_t nxdirty, size_t nydirty, double epsilon,
Martin Reinecke's avatar
Martin Reinecke committed
326
327
      double pixsize_x, double pixsize_y, size_t nthreads)
      : GridderConfig<T>(nxdirty, nydirty, epsilon, pixsize_x, pixsize_y, nthreads) {}
Martin Reinecke's avatar
Martin Reinecke committed
328
329
330
331
332
333
334
335
336
    using GridderConfig<T>::Nxdirty;
    using GridderConfig<T>::Nydirty;
    using GridderConfig<T>::Epsilon;
    using GridderConfig<T>::Pixsize_x;
    using GridderConfig<T>::Pixsize_y;
    using GridderConfig<T>::Nu;
    using GridderConfig<T>::Nv;
    using GridderConfig<T>::Supp;
    using GridderConfig<T>::Nsafe;
337

Martin Reinecke's avatar
Martin Reinecke committed
338
    pyarr<T> apply_taper(const pyarr<T> &img, bool divide) const
Martin Reinecke's avatar
Martin Reinecke committed
339
      {
Martin Reinecke's avatar
merge    
Martin Reinecke committed
340
      auto res = makeArray<T>({nx_dirty, ny_dirty});
Martin Reinecke's avatar
Martin Reinecke committed
341
342
      auto img2 = make_const_mav<2>(img);
      auto res2 = make_mav<2>(res);
Martin Reinecke's avatar
Martin Reinecke committed
343
344
      {
      py::gil_scoped_release release;
Martin Reinecke's avatar
Martin Reinecke committed
345
      GridderConfig<T>::apply_taper(img2, res2, divide);
Martin Reinecke's avatar
Martin Reinecke committed
346
      }
Martin Reinecke's avatar
Martin Reinecke committed
347
348
      return res;
      }
349
350
351
352
353
354
355
356
357
358
359
    pyarr<T> grid2dirty(const pyarr<T> &grid) const
      {
      auto res = makeArray<T>({nx_dirty, ny_dirty});
      auto grid2=make_const_mav<2>(grid);
      auto res2=make_mav<2>(res);
      {
      py::gil_scoped_release release;
      GridderConfig<T>::grid2dirty(grid2,res2);
      }
      return res;
      }
Martin Reinecke's avatar
Martin Reinecke committed
360
    pyarr<complex<T>> grid2dirty_c(const pyarr<complex<T>> &grid) const
Martin Reinecke's avatar
Martin Reinecke committed
361
      {
Martin Reinecke's avatar
merge    
Martin Reinecke committed
362
      auto res = makeArray<complex<T>>({nx_dirty, ny_dirty});
Martin Reinecke's avatar
Martin Reinecke committed
363
364
      auto grid2=make_const_mav<2>(grid);
      auto res2=make_mav<2>(res);
Martin Reinecke's avatar
Martin Reinecke committed
365
366
      {
      py::gil_scoped_release release;
Martin Reinecke's avatar
Martin Reinecke committed
367
      GridderConfig<T>::grid2dirty_c(grid2,res2);
Martin Reinecke's avatar
Martin Reinecke committed
368
      }
369
370
      return res;
      }
371

372
373
374
375
376
377
378
379
380
381
382
    pyarr<T> dirty2grid(const pyarr<T> &dirty) const
      {
      auto dirty2 = make_const_mav<2>(dirty);
      auto grid = makeArray<T>({nu, nv});
      auto grid2=make_mav<2>(grid);
      {
      py::gil_scoped_release release;
      GridderConfig<T>::dirty2grid(dirty2, grid2);
      }
      return grid;
      }
Martin Reinecke's avatar
Martin Reinecke committed
383
    pyarr<complex<T>> dirty2grid_c(const pyarr<complex<T>> &dirty) const
384
      {
Martin Reinecke's avatar
updates    
Martin Reinecke committed
385
386
387
      auto dirty2 = make_const_mav<2>(dirty);
      auto grid = makeArray<complex<T>>({nu, nv});
      auto grid2=make_mav<2>(grid);
Martin Reinecke's avatar
Martin Reinecke committed
388
389
      {
      py::gil_scoped_release release;
Martin Reinecke's avatar
updates    
Martin Reinecke committed
390
      GridderConfig<T>::dirty2grid_c(dirty2, grid2);
Martin Reinecke's avatar
Martin Reinecke committed
391
      }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
392
      return grid;
393
      }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
394
    pyarr<complex<T>> apply_wscreen(const pyarr<complex<T>> &dirty, double w, bool adjoint) const
Martin Reinecke's avatar
test1    
Martin Reinecke committed
395
      {
Martin Reinecke's avatar
updates    
Martin Reinecke committed
396
397
398
      auto dirty2 = make_const_mav<2>(dirty);
      auto res = makeArray<complex<T>>({nx_dirty, ny_dirty});
      auto res2 = make_mav<2>(res);
Martin Reinecke's avatar
test1    
Martin Reinecke committed
399
400
      {
      py::gil_scoped_release release;
Martin Reinecke's avatar
updates    
Martin Reinecke committed
401
      GridderConfig<T>::apply_wscreen(dirty2, res2, w, adjoint);
402
      }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
403
      return res;
404
      }
Martin Reinecke's avatar
Martin Reinecke committed
405
406
  };

Martin Reinecke's avatar
import  
Martin Reinecke committed
407

408
409
410
411
412
413
414
415
416
417
418
419
420
421
422
423
constexpr auto vis2grid_c_DS = R"""(
Grids visibilities onto a UV grid

Parameters
==========
baselines: Baselines
    the Baselines object
gconf: GridderConf
    the GridderConf object to be used
    (used to optimize the ordering of the indices)
idx: np.array((nvis,), dtype=np.uint32)
    the indices for the entries to be gridded
vis: np.array((nvis,), dtype=np.complex)
    The visibility data for the index array
grid_in: np.array((nu,nv), dtype=np.complex128), optional
    If present, the result is added to this array.
Martin Reinecke's avatar
Martin Reinecke committed
424
425
wgt: np.array((nvis,), dtype=np.float64), optional
    If present, visibilities are multiplied by the corresponding entries.
426
427
428
429
430
431

Returns
=======
np.array((nu,nv), dtype=np.complex128):
    the gridded visibilities
)""";
Martin Reinecke's avatar
updates    
Martin Reinecke committed
432
template<typename T> pyarr<complex<T>> Pyvis2grid_c(
Martin Reinecke's avatar
Martin Reinecke committed
433
  const PyBaselines<T> &baselines, const PyGridderConfig<T> &gconf,
Martin Reinecke's avatar
Martin Reinecke committed
434
  const pyarr<uint32_t> &idx_, const pyarr<complex<T>> &vis_,
Martin Reinecke's avatar
Martin Reinecke committed
435
  py::object &grid_in, const py::object &wgt_)
436
  {
Martin Reinecke's avatar
updates    
Martin Reinecke committed
437
438
439
440
441
442
443
  auto vis2 = make_const_mav<1>(vis_);
  size_t nvis = vis2.shape(0);
  auto idx2 = make_const_mav<1>(idx_);
  pyarr<T> wgt = providePotentialArray<T>(wgt_, {nvis});
  auto wgt2 = make_const_mav<1>(wgt);
  auto res = provideCArray<complex<T>>(grid_in, {gconf.Nu(), gconf.Nv()});
  auto grid = make_mav<2>(res);
Martin Reinecke's avatar
Martin Reinecke committed
444
445
  {
  py::gil_scoped_release release;
Martin Reinecke's avatar
updates    
Martin Reinecke committed
446
  vis2grid_c<T>(baselines, gconf, idx2, vis2, grid, wgt2);
Martin Reinecke's avatar
Martin Reinecke committed
447
  }
448
449
450
  return res;
  }

451
452
453
454
455
456
457
458
459
460
461
462
463
464
constexpr auto vis2grid_DS = R"""(
Grids visibilities onto a UV grid

Parameters
==========
baselines: Baselines
    the Baselines object
gconf: GridderConf
    the GridderConf object to be used
    (used to optimize the ordering of the indices)
idx: np.array((nvis,), dtype=np.uint32)
    the indices for the entries to be gridded
vis: np.array((nvis,), dtype=np.complex)
    The visibility data for the index array
Martin Reinecke's avatar
Martin Reinecke committed
465
466
grid_in: np.array((nu,nv), dtype=np.float64), optional
    If present, the result is added to this array.
Martin Reinecke's avatar
Martin Reinecke committed
467
468
wgt: np.array((nvis,), dtype=np.float64), optional
    If present, visibilities are multiplied by the corresponding entries.
469
470
471
472
473
474

Returns
=======
np.array((nu,nv), dtype=np.float64):
    the gridded visibilities (made real by making use of Hermitian symmetry)
)""";
475
476
477
478
479
480
481
482
483
template<typename T> pyarr<T> Pyvis2grid(const PyBaselines<T> &baselines,
  const PyGridderConfig<T> &gconf, const pyarr<uint32_t> &idx_,
  const pyarr<complex<T>> &vis_, py::object &grid_in, const py::object &wgt_)
  {
  auto tmp=Pyvis2grid_c(baselines, gconf, idx_, vis_, None, wgt_);
  auto grd=provideCArray<T>(grid_in,{gconf.Nu(), gconf.Nv()});
  gridder::detail::complex2hartley(make_const_mav<2>(tmp), make_mav<2>(grd), gconf.Nthreads());
  return grd;
  }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
484

485
486
487
488
489
490
491
492
493
494
495
496
497
498
499
500
constexpr auto ms2grid_c_DS = R"""(
Grids measurement set data onto a UV grid

Parameters
==========
baselines: Baselines
    the Baselines object
gconf: GridderConf
    the GridderConf object to be used
    (used to optimize the ordering of the indices)
idx: np.array((nvis,), dtype=np.uint32)
    the indices for the entries to be gridded
ms: np.array((nrows, nchannels), dtype=np.complex128)
    the measurement set.
grid_in: np.array((nu,nv), dtype=np.complex128), optional
    If present, the result is added to this array.
Martin Reinecke's avatar
Martin Reinecke committed
501
502
wgt: np.array((nrows, nchannels), dtype=np.float64), optional
    If present, visibilities are multiplied by the corresponding entries.
503
504
505
506
507
508

Returns
=======
np.array((nu,nv), dtype=np.complex128):
    the gridded visibilities
)""";
Martin Reinecke's avatar
updates    
Martin Reinecke committed
509
template<typename T> pyarr<complex<T>> Pyms2grid_c(
Martin Reinecke's avatar
Martin Reinecke committed
510
  const PyBaselines<T> &baselines, const PyGridderConfig<T> &gconf,
Martin Reinecke's avatar
Martin Reinecke committed
511
  const pyarr<uint32_t> &idx_, const pyarr<complex<T>> &ms_,
Martin Reinecke's avatar
Martin Reinecke committed
512
  py::object &grid_in, const py::object &wgt_)
Martin Reinecke's avatar
merge    
Martin Reinecke committed
513
514
515
  {
  auto nrows = baselines.Nrows();
  auto nchan = baselines.Nchannels();
Martin Reinecke's avatar
updates    
Martin Reinecke committed
516
517
518
519
520
521
  auto ms2 = make_const_mav<2>(ms_);
  auto idx2 = make_const_mav<1>(idx_);
  pyarr<T> wgt = providePotentialArray<T>(wgt_, {nrows, nchan});
  auto wgt2 = make_const_mav<2>(wgt);
  auto res = provideCArray<complex<T>>(grid_in, {gconf.Nu(), gconf.Nv()});
  auto grid = make_mav<2>(res);
Martin Reinecke's avatar
Martin Reinecke committed
522
523
  {
  py::gil_scoped_release release;
Martin Reinecke's avatar
updates    
Martin Reinecke committed
524
  ms2grid_c<T>(baselines, gconf, idx2, ms2, grid, wgt2);
Martin Reinecke's avatar
Martin Reinecke committed
525
  }
Martin Reinecke's avatar
merge    
Martin Reinecke committed
526
527
528
  return res;
  }

529
530
531
532
533
534
535
536
537
538
539
540
template<typename T> pyarr<T> Pyms2grid(
  const PyBaselines<T> &baselines, const PyGridderConfig<T> &gconf,
  const pyarr<uint32_t> &idx_, const pyarr<complex<T>> &ms_,
  py::object &grid_in, const py::object &wgt_)
  {
  auto tmp = Pyms2grid_c(baselines, gconf, idx_, ms_, None, wgt_);
  auto res_ = provideCArray<T>(grid_in, {gconf.Nu(), gconf.Nv()});
  auto res = make_mav<2>(res_);
  gridder::detail::complex2hartley(make_const_mav<2>(tmp), res, gconf.Nthreads());
  return res_;
  }

Martin Reinecke's avatar
updates    
Martin Reinecke committed
541
template<typename T> pyarr<complex<T>> Pygrid2vis_c(
Martin Reinecke's avatar
Martin Reinecke committed
542
  const PyBaselines<T> &baselines, const PyGridderConfig<T> &gconf,
Martin Reinecke's avatar
Martin Reinecke committed
543
  const pyarr<uint32_t> &idx_, const pyarr<complex<T>> &grid_,
Martin Reinecke's avatar
Martin Reinecke committed
544
  const py::object &wgt_)
545
  {
Martin Reinecke's avatar
updates    
Martin Reinecke committed
546
547
548
549
550
  auto grid2 = make_const_mav<2>(grid_);
  auto idx2 = make_const_mav<1>(idx_);
  size_t nvis = idx2.shape(0);
  pyarr<T> wgt = providePotentialArray<T>(wgt_, {nvis});
  auto wgt2 = make_const_mav<1>(wgt);
Martin Reinecke's avatar
merge    
Martin Reinecke committed
551
  auto res = makeArray<complex<T>>({nvis});
Martin Reinecke's avatar
updates    
Martin Reinecke committed
552
  auto vis = make_mav<1>(res);
Martin Reinecke's avatar
Martin Reinecke committed
553
554
  {
  py::gil_scoped_release release;
Martin Reinecke's avatar
updates    
Martin Reinecke committed
555
  grid2vis_c<T>(baselines, gconf, idx2, grid2, vis, wgt2);
Martin Reinecke's avatar
Martin Reinecke committed
556
  }
557
558
559
  return res;
  }

560
561
562
563
564
565
566
567
568
569
570
571
572
573
constexpr auto grid2vis_DS = R"""(
Degrids visibilities from a UV grid

Parameters
==========
baselines: Baselines
    the Baselines object
gconf: GridderConf
    the GridderConf object to be used
    (used to optimize the ordering of the indices)
idx: np.array((nvis,), dtype=np.uint32)
    the indices for the entries to be degridded
grid: np.array((nu,nv), dtype=np.float64):
    the gridded visibilities (made real by making use of Hermitian symmetry)
Martin Reinecke's avatar
Martin Reinecke committed
574
575
wgt: np.array((nvis,), dtype=np.float64), optional
    If present, visibilities are multiplied by the corresponding entries.
576
577
578
579
580
581

Returns
=======
np.array((nvis,), dtype=np.complex)
    The degridded visibility data
)""";
582
583
584
585
586
587
588
589
590
template<typename T> pyarr<complex<T>> Pygrid2vis(const PyBaselines<T> &baselines,
  const PyGridderConfig<T> &gconf, const pyarr<uint32_t> &idx_,
  const pyarr<T> &grid_, const py::object &wgt_)
  {
  auto tmp=makeArray<complex<T>>({gconf.Nu(), gconf.Nv()});
  gridder::detail::hartley2complex(make_const_mav<2>(grid_),make_mav<2>(tmp), gconf.Nthreads());
  return Pygrid2vis_c(baselines, gconf, idx_, tmp, wgt_);
  }

Martin Reinecke's avatar
updates    
Martin Reinecke committed
591
592
593
594
595
596
597
598
599
600
601
602
603
604
605
606
607
608
609
template<typename T> pyarr<complex<T>> Pygrid2ms_c(
  const PyBaselines<T> &baselines, const PyGridderConfig<T> &gconf,
  const pyarr<uint32_t> &idx_, const pyarr<complex<T>> &grid_,
  py::object &ms_in, const py::object &wgt_)
  {
  auto nrows = baselines.Nrows();
  auto nchan = baselines.Nchannels();
  auto grid2 = make_const_mav<2>(grid_);
  auto idx2 = make_const_mav<1>(idx_);
  pyarr<T> wgt = providePotentialArray<T>(wgt_, {nrows, nchan});
  auto wgt2 = make_const_mav<2>(wgt);
  auto res = provideCArray<complex<T>>(ms_in, {nrows, nchan});
  auto ms = make_mav<2>(res);
  {
  py::gil_scoped_release release;
  grid2ms_c<T>(baselines, gconf, idx2, grid2, ms, wgt2);
  }
  return res;
  }
Martin Reinecke's avatar
merge    
Martin Reinecke committed
610

611
612
613
614
615
616
617
618
619
620
template<typename T> pyarr<complex<T>> Pygrid2ms(const PyBaselines<T> &baselines,
  const PyGridderConfig<T> &gconf, const pyarr<uint32_t> &idx_,
  const pyarr<T> &grid_, py::object &ms_in, const py::object &wgt_)
  {
  auto grid2_ = makeArray<complex<T>>({gconf.Nu(), gconf.Nv()});
  auto grid2 = make_mav<2>(grid2_);
  gridder::detail::hartley2complex(make_const_mav<2>(grid_), grid2, gconf.Nthreads());
  return Pygrid2ms_c(baselines, gconf, idx_, grid2_, ms_in, wgt_);
  }

Martin Reinecke's avatar
Martin Reinecke committed
621
template<typename T> pyarr<complex<T>> Pyapply_holo(
Martin Reinecke's avatar
Martin Reinecke committed
622
  const PyBaselines<T> &baselines, const PyGridderConfig<T> &gconf,
Martin Reinecke's avatar
Martin Reinecke committed
623
  const pyarr<uint32_t> &idx_, const pyarr<complex<T>> &grid_,
Martin Reinecke's avatar
Martin Reinecke committed
624
  const py::object &wgt_)
625
  {
Martin Reinecke's avatar
Martin Reinecke committed
626
627
628
629
630
631
632
  auto idx = make_const_mav<1>(idx_);
  auto grid = make_const_mav<2>(grid_);
  pyarr<T> wgt2 = providePotentialArray<T>(wgt_, {idx.shape(0)});
  auto wgt=make_const_mav<1>(wgt2);

  auto res = makeArray<complex<T>>({grid.shape(0),grid.shape(1)});
  auto ogrid = make_mav<2>(res);
633
634
  {
  py::gil_scoped_release release;
Martin Reinecke's avatar
Martin Reinecke committed
635
  apply_holo(baselines, gconf, idx, grid, ogrid, wgt);
636
637
638
  }
  return res;
  }
639

Martin Reinecke's avatar
Martin Reinecke committed
640
template<typename T> pyarr<T> Pyget_correlations(
Martin Reinecke's avatar
Martin Reinecke committed
641
  const PyBaselines<T> &baselines, const PyGridderConfig<T> &gconf,
642
  const pyarr<uint32_t> &idx_, int du, int dv, const py::object &wgt_)
643
  {
Martin Reinecke's avatar
Martin Reinecke committed
644
645
646
647
648
649
  auto idx = make_const_mav<1>(idx_);
  pyarr<T> wgt2 = providePotentialArray<T>(wgt_, {idx.shape(0)});
  auto wgt=make_const_mav<1>(wgt2);

  auto res = makeArray<T>({gconf.Nu(),gconf.Nv()});
  auto ogrid = make_mav<2>(res);
650
651
  {
  py::gil_scoped_release release;
Martin Reinecke's avatar
Martin Reinecke committed
652
  get_correlations(baselines, gconf, idx, du, dv, ogrid, wgt);
653
654
655
656
  }
  return res;
  }

657
658
659
660
661
662
663
664
665
666
667
668
669
670
671
672
673
674
675
676
677
678
679
680
681
682
683
constexpr auto getIndices_DS = R"""(
Selects a subset of entries from a `Baselines` object.

Parameters
==========
baselines: Baselines
    the Baselines object
gconf: GridderConf
    the GridderConf object to be used with the returned indices.
    (used to optimize the ordering of the indices)
flags: np.array((nrows, nchannels), dtype=np.bool)
    "True" indicates that the value should not be used
chbegin: int
    first channel to use (-1: start with the first available channel)
chend: int
    one-past last channel to use (-1: one past the last available channel)
wmin: float
    only select entries with w>=wmin
wmax: float
    only select entries with w<wmax

Returns
=======
np.array((nvis,), dtype=np.uint32)
    the compressed indices for all entries which match the selected criteria
    and are not flagged.
)""";
Martin Reinecke's avatar
Martin Reinecke committed
684
template<typename T> pyarr<uint32_t> PygetIndices(const PyBaselines<T> &baselines,
Martin Reinecke's avatar
Martin Reinecke committed
685
  const PyGridderConfig<T> &gconf, const pyarr<bool> &flags_, int chbegin,
686
  int chend, T wmin, T wmax)
Martin Reinecke's avatar
updates    
Martin Reinecke committed
687
  {
688
689
  size_t nidx;
  auto flags = make_const_mav<2>(flags_);
Martin Reinecke's avatar
Martin Reinecke committed
690
691
  {
  py::gil_scoped_release release;
692
  nidx = getIdxSize(baselines, flags, chbegin, chend, wmin, wmax, gconf.Nthreads());
Martin Reinecke's avatar
Martin Reinecke committed
693
  }
694
695
  auto res = makeArray<uint32_t>({nidx});
  auto res2 = make_mav<1>(res);
Martin Reinecke's avatar
Martin Reinecke committed
696
697
  {
  py::gil_scoped_release release;
698
  fillIdx(baselines, gconf, flags, chbegin, chend, wmin, wmax, res2);
Martin Reinecke's avatar
Martin Reinecke committed
699
  }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
700
701
702
  return res;
  }

703
template<typename T> pyarr<T> Pyvis2dirty_wstack(const PyBaselines<T> &baselines,
Martin Reinecke's avatar
Martin Reinecke committed
704
  const PyGridderConfig<T> &gconf, const pyarr<uint32_t> &idx_,
Martin Reinecke's avatar
Martin Reinecke committed
705
706
  const pyarr<complex<T>> &vis_)
  {
Martin Reinecke's avatar
Martin Reinecke committed
707
708
  auto nx_dirty=gconf.Nxdirty();
  auto ny_dirty=gconf.Nydirty();
Martin Reinecke's avatar
updates    
Martin Reinecke committed
709
710
  auto idx2=make_const_mav<1>(idx_);
  auto vis2=make_const_mav<1>(vis_);
711
  auto dirty = makeArray<T>({nx_dirty, ny_dirty});
Martin Reinecke's avatar
updates    
Martin Reinecke committed
712
  auto dirty2=make_mav<2>(dirty);
Martin Reinecke's avatar
Martin Reinecke committed
713
714
  {
  py::gil_scoped_release release;
Martin Reinecke's avatar
updates    
Martin Reinecke committed
715
  vis2dirty_wstack<T>(baselines, gconf, idx2, vis2, dirty2);
Martin Reinecke's avatar
Martin Reinecke committed
716
  }
Martin Reinecke's avatar
updates    
Martin Reinecke committed
717
  return dirty;
Martin Reinecke's avatar
Martin Reinecke committed
718
719
  }

720
721
template<typename T> pyarr<complex<T>> Pydirty2vis_wstack(const PyBaselines<T> &baselines,
  const PyGridderConfig<T> &gconf, const pyarr<uint32_t> &idx_,
722
  const pyarr<T> &dirty_)
723
724
725
726
727
728
729
730
  {
  auto idx2=make_const_mav<1>(idx_);
  auto nvis = idx2.shape(0);
  auto vis = makeArray<complex<T>>({nvis});
  auto vis2=make_mav<1>(vis);
  auto dirty2=make_const_mav<2>(dirty_);
  {
  py::gil_scoped_release release;
Martin Reinecke's avatar
Martin Reinecke committed
731
  vis2.fill(0);
732
733
734
735
736
  dirty2vis_wstack<T>(baselines, gconf, idx2, dirty2, vis2);
  }
  return vis;
  }

737
738
739
740
741
742
743
744
745
746
747
748
749
750
751
752
753
754
755
756
757
758
759
760
761
762
763
764
765
766
767
template<typename T> pyarr<T> Pygridding(const pyarr<T> &uvw,
  const pyarr<T> &freq, const pyarr<complex<T>> &ms, const py::object &wgt_,
  size_t npix_x, size_t npix_y, T pixsize_x, T pixsize_y, double epsilon,
  size_t nthreads, size_t verbosity)
  {
  auto uvw2 = make_const_mav<2>(uvw);
  auto freq2 = make_const_mav<1>(freq);
  auto ms2 = make_const_mav<2>(ms);
  auto wgt=providePotentialArray<T>(wgt_,{ms2.shape(0),ms2.shape(1)});
  auto wgt2 = make_const_mav<2>(wgt);
  auto dirty=makeArray<T>({npix_x,npix_y});
  auto dirty2 =make_mav<2>(dirty);
  gridding(uvw2,freq2,ms2,wgt2,pixsize_x,pixsize_y,epsilon,nthreads,dirty2,verbosity);
  return dirty;
  }

template<typename T> pyarr<complex<T>> Pydegridding(const pyarr<T> &uvw,
  const pyarr<T> &freq, const pyarr<T> &dirty, const py::object &wgt_,
  T pixsize_x, T pixsize_y, double epsilon, size_t nthreads, size_t verbosity)
  {
  auto uvw2 = make_const_mav<2>(uvw);
  auto freq2 = make_const_mav<1>(freq);
  auto dirty2 = make_const_mav<2>(dirty);
  auto wgt=providePotentialArray<T>(wgt_,{uvw2.shape(0),freq2.shape(0)});
  auto wgt2 = make_const_mav<2>(wgt);
  auto ms=makeArray<complex<T>>({uvw2.shape(0),freq2.shape(0)});
  auto ms2 =make_mav<2>(ms);
  degridding(uvw2,freq2,dirty2,wgt2,pixsize_x,pixsize_y,epsilon,nthreads,ms2,verbosity);
  return ms;
  }

768
template<typename T> pyarr<T> Pyfull_gridding(const pyarr<T> &uvw,
Martin Reinecke's avatar
Martin Reinecke committed
769
  const pyarr<T> &freq, const pyarr<complex<T>> &ms, const py::object &wgt_,
Martin Reinecke's avatar
Martin Reinecke committed
770
771
  size_t npix_x, size_t npix_y, T pixsize_x, T pixsize_y, double epsilon,
  size_t nthreads, size_t verbosity)
Martin Reinecke's avatar
Martin Reinecke committed
772
773
774
775
776
777
  {
  auto uvw2 = make_const_mav<2>(uvw);
  auto freq2 = make_const_mav<1>(freq);
  auto ms2 = make_const_mav<2>(ms);
  auto wgt=providePotentialArray<T>(wgt_,{ms2.shape(0),ms2.shape(1)});
  auto wgt2 = make_const_mav<2>(wgt);
778
  auto dirty=makeArray<T>({npix_x,npix_y});
Martin Reinecke's avatar
Martin Reinecke committed
779
  auto dirty2 =make_mav<2>(dirty);
Martin Reinecke's avatar
Martin Reinecke committed
780
  full_gridding(uvw2,freq2,ms2,wgt2,pixsize_x,pixsize_y,epsilon,nthreads,dirty2,verbosity);
Martin Reinecke's avatar
Martin Reinecke committed
781
782
783
784
  return dirty;
  }

template<typename T> pyarr<complex<T>> Pyfull_degridding(const pyarr<T> &uvw,
785
  const pyarr<T> &freq, const pyarr<T> &dirty, const py::object &wgt_,
Martin Reinecke's avatar
Martin Reinecke committed
786
  T pixsize_x, T pixsize_y, double epsilon, size_t nthreads, size_t verbosity)
Martin Reinecke's avatar
Martin Reinecke committed
787
788
789
790
791
792
793
794
  {
  auto uvw2 = make_const_mav<2>(uvw);
  auto freq2 = make_const_mav<1>(freq);
  auto dirty2 = make_const_mav<2>(dirty);
  auto wgt=providePotentialArray<T>(wgt_,{uvw2.shape(0),freq2.shape(0)});
  auto wgt2 = make_const_mav<2>(wgt);
  auto ms=makeArray<complex<T>>({uvw2.shape(0),freq2.shape(0)});
  auto ms2 =make_mav<2>(ms);
Martin Reinecke's avatar
Martin Reinecke committed
795
  full_degridding(uvw2,freq2,dirty2,wgt2,pixsize_x,pixsize_y,epsilon,nthreads,ms2,verbosity);
Martin Reinecke's avatar
Martin Reinecke committed
796
797
798
  return ms;
  }

Martin Reinecke's avatar
import  
Martin Reinecke committed
799
800
801
802
} // unnamed namespace

PYBIND11_MODULE(nifty_gridder, m)
  {
803
804
  using namespace pybind11::literals;

Martin Reinecke's avatar
Martin Reinecke committed
805
  py::class_<PyBaselines<double>> (m, "Baselines", PyBaselines_DS)
Martin Reinecke's avatar
Martin Reinecke committed
806
    .def(py::init<const pyarr<double> &, const pyarr<double> &>(),
807
      "coord"_a, "freq"_a)
Martin Reinecke's avatar
Martin Reinecke committed
808
809
810
    .def ("Nrows",&PyBaselines<double>::Nrows)
    .def ("Nchannels",&PyBaselines<double>::Nchannels)
    .def ("ms2vis",&PyBaselines<double>::ms2vis<complex<double>>,
Martin Reinecke's avatar
Martin Reinecke committed
811
      PyBaselines<double>::ms2vis_DS, "ms"_a, "idx"_a, "nthreads"_a=1)
Martin Reinecke's avatar
Martin Reinecke committed
812
813
    .def ("effectiveuvw",&PyBaselines<double>::effectiveuvw, "idx"_a)
    .def ("vis2ms",&PyBaselines<double>::vis2ms<complex<double>>,
Martin Reinecke's avatar
Martin Reinecke committed
814
      PyBaselines<double>::vis2ms_DS, "vis"_a, "idx"_a, "ms_in"_a=None, "nthreads"_a=1);
Martin Reinecke's avatar
Martin Reinecke committed
815
  py::class_<PyGridderConfig<double>> (m, "GridderConfig", GridderConfig_DS)
Martin Reinecke's avatar
Martin Reinecke committed
816
817
    .def(py::init<size_t, size_t, double, double, double, size_t>(),"nxdirty"_a,
      "nydirty"_a, "epsilon"_a, "pixsize_x"_a, "pixsize_y"_a, "nthreads"_a=1)
Martin Reinecke's avatar
Martin Reinecke committed
818
819
820
821
822
823
824
825
826
    .def("Nxdirty", &PyGridderConfig<double>::Nxdirty)
    .def("Nydirty", &PyGridderConfig<double>::Nydirty)
    .def("Epsilon", &PyGridderConfig<double>::Epsilon)
    .def("Pixsize_x", &PyGridderConfig<double>::Pixsize_x)
    .def("Pixsize_y", &PyGridderConfig<double>::Pixsize_y)
    .def("Nu", &PyGridderConfig<double>::Nu)
    .def("Nv", &PyGridderConfig<double>::Nv)
    .def("Supp", &PyGridderConfig<double>::Supp)
    .def("apply_taper", &PyGridderConfig<double>::apply_taper, apply_taper_DS,
Martin Reinecke's avatar
Martin Reinecke committed
827
      "img"_a, "divide"_a=false)
828
829
     .def("grid2dirty", &PyGridderConfig<double>::grid2dirty,
        grid2dirty_DS, "grid"_a)
Martin Reinecke's avatar
Martin Reinecke committed
830
    .def("grid2dirty_c", &PyGridderConfig<double>::grid2dirty_c, "grid"_a)
831
832
    .def("dirty2grid", &PyGridderConfig<double>::dirty2grid,
       dirty2grid_DS, "dirty"_a)
Martin Reinecke's avatar
Martin Reinecke committed
833
834
    .def("dirty2grid_c", &PyGridderConfig<double>::dirty2grid_c, "dirty"_a)
    .def("apply_wscreen", &PyGridderConfig<double>::apply_wscreen,
Martin Reinecke's avatar
Martin Reinecke committed
835
      apply_wscreen_DS, "dirty"_a, "w"_a, "adjoint"_a)
836
837
838
839

    // pickle support
    .def(py::pickle(
        // __getstate__
Martin Reinecke's avatar
Martin Reinecke committed
840
        [](const PyGridderConfig<double> & gc) {
841
842
          // Encode object state in tuple
          return py::make_tuple(gc.Nxdirty(), gc.Nydirty(), gc.Epsilon(),
Martin Reinecke's avatar
Martin Reinecke committed
843
                                gc.Pixsize_x(), gc.Pixsize_y(), gc.Nthreads());
844
845
846
        },
        // __setstate__
        [](py::tuple t) {
Martin Reinecke's avatar
Martin Reinecke committed
847
          myassert(t.size()==6,"Invalid state");
848
849

          // Reconstruct from tuple
Martin Reinecke's avatar
Martin Reinecke committed
850
          return PyGridderConfig<double>(t[0].cast<size_t>(), t[1].cast<size_t>(),
851
                                       t[2].cast<double>(), t[3].cast<double>(),
Martin Reinecke's avatar
Martin Reinecke committed
852
                                       t[4].cast<double>(), t[5].cast<size_t>());
853
854

        }));
Martin Reinecke's avatar
Martin Reinecke committed
855
  m.def("getIndices", PygetIndices<double>, getIndices_DS, "baselines"_a,
Martin Reinecke's avatar
cleanup    
Martin Reinecke committed
856
    "gconf"_a, "flags"_a, "chbegin"_a=-1, "chend"_a=-1,
857
858
859
860
861
862
863
864
865
    "wmin"_a=-1e30, "wmax"_a=1e30);
   m.def("vis2grid",&Pyvis2grid<double>, vis2grid_DS, "baselines"_a, "gconf"_a,
     "idx"_a, "vis"_a, "grid_in"_a=None, "wgt"_a=None);
  m.def("ms2grid",&Pyms2grid<double>, "baselines"_a, "gconf"_a, "idx"_a, "ms"_a,
    "grid_in"_a=None, "wgt"_a=None);
  m.def("grid2vis",&Pygrid2vis<double>, grid2vis_DS, "baselines"_a, "gconf"_a,
    "idx"_a, "grid"_a, "wgt"_a=None);
  m.def("grid2ms",&Pygrid2ms<double>, "baselines"_a, "gconf"_a, "idx"_a,
    "grid"_a, "ms_in"_a=None, "wgt"_a=None);
Martin Reinecke's avatar
updates    
Martin Reinecke committed
866
  m.def("vis2grid_c",&Pyvis2grid_c<double>, vis2grid_c_DS, "baselines"_a,
Martin Reinecke's avatar
Martin Reinecke committed
867
    "gconf"_a, "idx"_a, "vis"_a, "grid_in"_a=None, "wgt"_a=None);
Martin Reinecke's avatar
updates    
Martin Reinecke committed
868
  m.def("ms2grid_c",&Pyms2grid_c<double>, ms2grid_c_DS, "baselines"_a, "gconf"_a,
Martin Reinecke's avatar
Martin Reinecke committed
869
    "idx"_a, "ms"_a, "grid_in"_a=None, "wgt"_a=None);
Martin Reinecke's avatar
updates    
Martin Reinecke committed
870
  m.def("grid2vis_c",&Pygrid2vis_c<double>, "baselines"_a, "gconf"_a, "idx"_a,
Martin Reinecke's avatar
Martin Reinecke committed
871
    "grid"_a, "wgt"_a=None);
Martin Reinecke's avatar
updates    
Martin Reinecke committed
872
  m.def("grid2ms_c",&Pygrid2ms_c<double>, "baselines"_a, "gconf"_a, "idx"_a,
Martin Reinecke's avatar
Martin Reinecke committed
873
    "grid"_a, "ms_in"_a=None, "wgt"_a=None);
Martin Reinecke's avatar
Martin Reinecke committed
874
  m.def("apply_holo",&Pyapply_holo<double>, "baselines"_a, "gconf"_a, "idx"_a,
Martin Reinecke's avatar
Martin Reinecke committed
875
    "grid"_a, "wgt"_a=None);
Martin Reinecke's avatar
Martin Reinecke committed
876
  m.def("get_correlations", &Pyget_correlations<double>, "baselines"_a, "gconf"_a,
Martin Reinecke's avatar
Martin Reinecke committed
877
    "idx"_a, "du"_a, "dv"_a, "wgt"_a=None);
Martin Reinecke's avatar
updates    
Martin Reinecke committed
878
  m.def("vis2dirty_wstack",&Pyvis2dirty_wstack<double>, "baselines"_a, "gconf"_a,
Martin Reinecke's avatar
Martin Reinecke committed
879
    "idx"_a, "vis"_a);
880
881
  m.def("dirty2vis_wstack",&Pydirty2vis_wstack<double>, "baselines"_a, "gconf"_a,
    "idx"_a, "dirty"_a);
Martin Reinecke's avatar
Martin Reinecke committed
882

883
  m.def("full_gridding",&Pyfull_gridding<double>,"uvw"_a,"freq"_a,"ms"_a,
884
    "wgt"_a=None,"npix_x"_a,"npix_y"_a,"pixsize_x"_a,"pixsize_y"_a,"epsilon"_a,
Martin Reinecke's avatar
Martin Reinecke committed
885
    "nthreads"_a=1, "verbosity"_a=0);
886
  m.def("full_gridding_f",&Pyfull_gridding<float>,"uvw"_a,"freq"_a,"ms"_a,
887
    "wgt"_a=None,"npix_x"_a,"npix_y"_a,"pixsize_x"_a,"pixsize_y"_a,"epsilon"_a,
Martin Reinecke's avatar
Martin Reinecke committed
888
    "nthreads"_a=1, "verbosity"_a=0);
Martin Reinecke's avatar
Martin Reinecke committed
889
  m.def("full_degridding",&Pyfull_degridding<double>,"uvw"_a,"freq"_a,"dirty"_a,
890
    "wgt"_a=None,"pixsize_x"_a,"pixsize_y"_a, "epsilon"_a,"nthreads"_a=1,
Martin Reinecke's avatar
Martin Reinecke committed
891
    "verbosity"_a=0);
892
  m.def("full_degridding_f",&Pyfull_degridding<float>,"uvw"_a,"freq"_a,"dirty"_a,
893
    "wgt"_a=None,"pixsize_x"_a,"pixsize_y"_a, "epsilon"_a, "nthreads"_a=1,
Martin Reinecke's avatar
Martin Reinecke committed
894
    "verbosity"_a=0);
895
  m.def("gridding",&Pygridding<double>,"uvw"_a,"freq"_a,"ms"_a,
896
    "wgt"_a=None,"npix_x"_a,"npix_y"_a,"pixsize_x"_a,"pixsize_y"_a,"epsilon"_a,
897
898
    "nthreads"_a=1, "verbosity"_a=0);
  m.def("gridding_f",&Pygridding<float>,"uvw"_a,"freq"_a,"ms"_a,
899
    "wgt"_a=None,"npix_x"_a,"npix_y"_a,"pixsize_x"_a,"pixsize_y"_a,"epsilon"_a,
900
901
    "nthreads"_a=1, "verbosity"_a=0);
  m.def("degridding",&Pydegridding<double>,"uvw"_a,"freq"_a,"dirty"_a,
902
    "wgt"_a=None,"pixsize_x"_a,"pixsize_y"_a, "epsilon"_a,"nthreads"_a=1,
903
904
    "verbosity"_a=0);
  m.def("degridding_f",&Pydegridding<float>,"uvw"_a,"freq"_a,"dirty"_a,
905
    "wgt"_a=None,"pixsize_x"_a,"pixsize_y"_a, "epsilon"_a, "nthreads"_a=1,
906
    "verbosity"_a=0);
Martin Reinecke's avatar
import  
Martin Reinecke committed
907
  }