Merge remote-tracking branch 'origin/master' into more_weights

nifty_gridder.cc

@@ -423,7 +423,7 @@ template<typename T> class Baselines
         The visibility data for the index array
     )""";
 
-    pyarr_c<T> ind2effectiveuvw(const pyarr_c<uint32_t> &idx_) const
+    pyarr_c<T> effectiveuvw(const pyarr_c<uint32_t> &idx_) const
     {
       checkArray(idx_, "idx", {0});
       size_t nvis = size_t(idx_.shape(0));
@@ -1477,7 +1477,7 @@ PYBIND11_MODULE(nifty_gridder, m)
     .def ("Nchannels",&Baselines<double>::Nchannels)
     .def ("ms2vis",&Baselines<double>::ms2vis<complex<double>>,
       Baselines<double>::ms2vis_DS, "ms"_a, "idx"_a)
-    .def ("ind2effectiveuvw",&Baselines<double>::ind2effectiveuvw, "idx"_a)
+    .def ("effectiveuvw",&Baselines<double>::effectiveuvw, "idx"_a)
     .def ("vis2ms",&Baselines<double>::vis2ms<complex<double>>,
       Baselines<double>::vis2ms_DS, "vis"_a, "idx"_a, "ms_in"_a=None);
   py::class_<GridderConfig<double>> (m, "GridderConfig", GridderConfig_DS)

profile.py

-import nifty_gridder as ng
-from time import time
-import numpy as np
-
-
-def _wscreen(npix, dst, w):
-    dc = (np.linspace(start=-npix/2, stop=npix/2 - 1, num=npix)*dst)**2
-    ls = np.broadcast_to(dc, (dc.shape[0],)*2)
-    theta = np.sqrt(ls + ls.T)
-    n = np.cos(theta)
-    wscreen = np.exp(2*np.pi*1j*w*(n - 1))/n
-    return wscreen
-
-
-def time_op(func, x, ntries=5):
-    t0 = time()
-    for ii in range(ntries):
-        print(ii)
-        func(x)
-    return (time() - t0)/ntries
-
-
-if __name__ == '__main__':
-    ng.set_nthreads(4)
-    ntries = 20
-    nx = 2048
-    dx = 12
-    w = 1000.2
-    ny, dy = nx, dx
-    conf = ng.GridderConfig(nx, ny, 1e-7, dx, dy)
-    x, y = conf.Nxdirty(), conf.Nydirty()
-
-    fld = np.random.randn(x, y) + 1j*np.random.randn(x, y)
-    func0 = lambda x: _wscreen(nx, dy, w).conjugate()*x
-    func1 = lambda x: conf.apply_wscreen(x, w, True)
-    print(time_op(func0, fld), time_op(func1, fld))
-
-    fld = np.random.randn(nx, ny)
-    func0 = lambda x: _wscreen(nx, dx, w)*x.real
-    func1 = lambda x: conf.apply_wscreen(x, w, False)
-    print(time_op(func0, fld), time_op(func1, fld))