merge

test.py

+from itertools import product
+
 import nifty_gridder as ng
 import numpy as np
 import pytest
@@ -387,3 +389,38 @@ def test_wgridder_against_wdft(nxdirty, nydirty, nchan, nrow, fov, epsilon):
     res0 = ng.vis2dirty_wstack(bl, conf, idx, vis)
     res1 = _dft(uvw, vis, conf, True)
     assert_(_l2error(res0, res1) < epsilon)
+
+
+@pmp('nxdirty', (32, 16))
+@pmp('nydirty', (32, 64))
+@pmp("nrow", (100, 1000))
+@pmp("nchan", (1, 5))
+@pmp('epsilon', (1e-3, 1e-6))
+def test_holo_from_correlations(nxdirty, nydirty, nchan, nrow, epsilon):
+    np.random.seed(42)
+    bl, conf, idx = _init_gridder(nxdirty, nydirty, epsilon, nchan, nrow)
+    nx, ny = 2*nxdirty, 2*nydirty
+    grid = np.random.randn(nx, ny) + 1.0j*np.random.randn(nx, ny)
+    W = conf.Supp()
+    res0 = np.zeros_like(grid)
+
+    # Precompute 2*W**2-2*W+1 images (naive: 4*W**2-4*W+1)
+    d0, d1 = [], []
+    for du, dv in product(range(-W + 1, W), range(1, W)):
+        d0.append(ng.get_correlations(bl, conf, idx, du, dv))
+    for du in range(1, W):
+        d1.append(ng.get_correlations(bl, conf, idx, du, 0))
+    d2 = ng.get_correlations(bl, conf, idx, 0, 0)
+
+    # Apply
+    for ii, (du, dv) in enumerate(product(range(-W + 1, W), range(1, W))):
+        tmp = np.roll(grid, -du, axis=0)
+        res0 += d0[ii]*np.roll(tmp, -dv, axis=1)
+        res0 += np.roll(d0[ii]*tmp, dv, axis=1)
+    for ii, du in enumerate(range(1, W)):
+        res0 += d1[ii]*np.roll(grid, -du, axis=0)
+        res0 += np.roll(d1[ii]*grid, du, axis=0)
+    res0 += d2*grid
+    res1 = ng.apply_holo(bl, conf, idx, grid)
+    assert_allclose(res0, res1, rtol=1e-13)
+