switch to better_params branch

Dockerfile

@@ -13,7 +13,7 @@ RUN apt-get update && apt-get install -y \
     python3-mpi4py python3-matplotlib \
   # more optional NIFTy dependencies
   && pip3 install git+https://gitlab.mpcdf.mpg.de/ift/pyHealpix.git \
-  && pip3 install git+https://gitlab.mpcdf.mpg.de/ift/nifty_gridder.git@powergrid \
+  && pip3 install git+https://gitlab.mpcdf.mpg.de/ift/nifty_gridder.git@better_params \
   && pip3 install git+https://gitlab.mpcdf.mpg.de/mtr/pypocketfft.git \
   && pip3 install jupyter \
   && rm -rf /var/lib/apt/lists/*

demos/bench_gridder.py

@@ -10,13 +10,15 @@ np.random.seed(40)
 N0s, a0s, b0s, c0s = [], [], [], []
 
 for ii in range(10, 26):
+    fovx = 0.0001
+    fovy = 0.0002
     nu = 1024
     nv = 1024
     N = int(2**ii)
     print('N = {}'.format(N))
     nchan=16
     nrow=N//nchan
-    fct = 1.+0.00001*np.arange(nchan)
+    freq = 1e9+1e6*np.arange(nchan)
     uvw = np.random.rand(nrow, 3) - 0.5
     vis = (np.random.randn(N) + 1j*np.random.randn(N)).reshape((nrow,nchan))
 
@@ -30,7 +32,7 @@ for ii in range(10, 26):
 
     t0 = time()
     GM = ift.GridderMaker(uvspace, eps=1e-7, uvw=uvw,
-                          channel_fact=fct,
+                          freq=freq, fovx=fovx, fovy=fovy,
                           flags=np.zeros((N//nchan, nchan), dtype=np.bool))
     vis = ift.from_global_data(visspace, vis)
     op = GM.getFull().adjoint

nifty5/library/gridder.py

@@ -24,17 +24,17 @@ import numpy as np
 
 
 class GridderMaker(object):
-    def __init__(self, dirty_domain, uvw, channel_fact, flags, eps=2e-13):
+    def __init__(self, dirty_domain, uvw, freq, fovx, fovy, flags, eps=2e-13):
         import nifty_gridder
         dirty_domain = makeDomain(dirty_domain)
         if (len(dirty_domain) != 1 or not isinstance(dirty_domain[0], RGSpace)
                 or not len(dirty_domain.shape) == 2):
             raise ValueError("need dirty_domain with exactly one 2D RGSpace")
-        if channel_fact.ndim != 1:
-            raise ValueError("channel_fact must be a 1D array")
-        bl = nifty_gridder.Baselines(uvw, channel_fact)
+        if freq.ndim != 1:
+            raise ValueError("freq must be a 1D array")
+        bl = nifty_gridder.Baselines(uvw, freq)
         nxdirty, nydirty = dirty_domain.shape
-        gconf = nifty_gridder.GridderConfig(nxdirty, nydirty, eps, 1., 1.)
+        gconf = nifty_gridder.GridderConfig(nxdirty, nydirty, eps, fovx, fovy)
         nu = gconf.Nu()
         nv = gconf.Nv()
         self._idx = nifty_gridder.getIndices(bl, gconf, flags)

test/test_operators/test_nft.py

@@ -29,19 +29,24 @@ pmp = pytest.mark.parametrize
 def _l2error(a, b):
     return np.sqrt(np.sum(np.abs(a-b)**2)/np.sum(np.abs(a)**2))
 
+speedOfLight = 299792458.
 
 @pmp('eps', [1e-2, 1e-4, 1e-7, 1e-10, 1e-11, 1e-12, 2e-13])
 @pmp('nu', [12, 128])
 @pmp('nv', [4, 12, 128])
 @pmp('N', [1, 10, 100])
-@pmp('channel_fact', [1, 1.2])
-def test_gridding(nu, nv, N, eps, channel_fact):
-    uvw = np.random.rand(N, 3) - 0.5
+@pmp('freq', [1e9])
+def test_gridding(nu, nv, N, eps, freq):
+    fovx = 0.0001
+    fovy = 0.0002
+    uvw = (np.random.rand(N, 3) - 0.5)
+    uvw[:,0] /= fovx*freq/speedOfLight
+    uvw[:,1] /= fovy*freq/speedOfLight
     vis = (np.random.randn(N) + 1j*np.random.randn(N)).reshape((-1,1))
 
     # Nifty
     GM = ift.GridderMaker(ift.RGSpace((nu, nv)), uvw=uvw,
-                          channel_fact=np.array([channel_fact]), eps=eps,
+                          freq=np.array([freq]), eps=eps, fovx=fovx, fovy=fovy,
                           flags=np.zeros((N, 1), dtype=np.bool))
     vis2 = ift.from_global_data(ift.UnstructuredDomain(vis.shape), vis)
 
@@ -50,9 +55,11 @@ def test_gridding(nu, nv, N, eps, channel_fact):
     # DFT
     x, y = np.meshgrid(
         *[-ss/2 + np.arange(ss) for ss in [nu, nv]], indexing='ij')
+    x *= fovx*freq/speedOfLight
+    y *= fovy*freq/speedOfLight
     dft = pynu*0.
     for i in range(N):
-        dft += (vis[i]*np.exp(2j*np.pi*(x*uvw[i, 0] + y*uvw[i, 1])*channel_fact)).real
+        dft += (vis[i]*np.exp(2j*np.pi*(x*uvw[i, 0] + y*uvw[i, 1]))).real
     assert_(_l2error(dft, pynu) < eps)
 
 
@@ -60,14 +67,15 @@ def test_gridding(nu, nv, N, eps, channel_fact):
 @pmp('nu', [12, 128])
 @pmp('nv', [4, 12, 128])
 @pmp('N', [1, 10, 100])
-@pmp('cfact', [np.array([1.]), np.array([0.3, 0.5, 2.3])])
-def test_build(nu, nv, N, eps, cfact):
+@pmp('freq', [np.array([1e9]), np.array([1e9, 2e9, 2.5e9])])
+def test_build(nu, nv, N, eps, freq):
     dom = ift.RGSpace([nu, nv])
+    fov = np.pi/180/60
     uvw = np.random.rand(N, 3) - 0.5
-    flags=np.zeros((N, cfact.shape[0]), dtype=np.bool)
+    flags=np.zeros((N, freq.shape[0]), dtype=np.bool)
     flags[0,0]=True
-    GM = ift.GridderMaker(dom, uvw=uvw, channel_fact=cfact, eps=eps,
-                          flags=flags)
+    GM = ift.GridderMaker(dom, uvw=uvw, freq=freq, eps=eps,
+                          flags=flags, fovx=fov, fovy=fov)
     R0 = GM.getGridder()
     R1 = GM.getRest()
     R = R1@R0