def test_construct_kernels(tmp_path_factory):
matplotlib = pytest.importorskip("matplotlib")
matplotlib.use("agg")
plt = pytest.importorskip("matplotlib.pyplot")
plt.figure()
WIDTH = 5
OVERSAMP = 101
ll = kernels.uspace(WIDTH, OVERSAMP)
sel = ll <= (WIDTH + 2) // 2
plt.axvline(0.5, 0, 1, ls="--", c="k")
plt.axvline(-0.5, 0, 1, ls="--", c="k")
plt.plot(ll[sel] * OVERSAMP / 2 / np.pi,
10 * np.log10(
np.abs(
np.fft.fftshift(
np.fft.fft(
kernels.kbsinc(
WIDTH, oversample=OVERSAMP, order=0)[sel])))),
label="kbsinc order 0")
plt.plot(
ll[sel] * OVERSAMP / 2 / np.pi,
10 * np.log10(
np.abs(
np.fft.fftshift(
np.fft.fft(
kernels.kbsinc(WIDTH, oversample=OVERSAMP,
order=15)[sel])))),
label="kbsinc order 15")
plt.plot(ll[sel] * OVERSAMP / 2 / np.pi,
10 * np.log10(
np.abs(
np.fft.fftshift(
np.fft.fft(
kernels.hanningsinc(WIDTH,
oversample=OVERSAMP)[sel])))),
label="hanning sinc")
plt.plot(ll[sel] * OVERSAMP / 2 / np.pi,
10 * np.log10(
np.abs(
np.fft.fftshift(
np.fft.fft(
kernels.sinc(WIDTH, oversample=OVERSAMP)[sel])))),
label="sinc")
plt.xlim(-10, 10)
plt.legend()
plt.ylabel("Response [dB]")
plt.xlabel("FoV")
plt.grid(True)
plt.savefig(tmp_path_factory.mktemp("plots") / "aakernels.png")
def test_detaper(tmp_path_factory):
W = 5
OS = 3
K1D = kernels.kbsinc(W, oversample=OS)
K2D = np.outer(K1D, K1D)
detaper = kernels.compute_detaper(128, K2D, W, OS)
detaperdft = kernels.compute_detaper_dft(128, K2D, W, OS)
detaperdftsep = kernels.compute_detaper_dft_seperable(128, K1D, W, OS)
try:
import matplotlib
except ImportError:
pass
else:
matplotlib.use("agg")
from matplotlib import pyplot as plt
plt.figure()
plt.subplot(131)
plt.title("FFT detaper")
plt.imshow(detaper)
plt.colorbar()
plt.subplot(132)
plt.title("DFT detaper")
plt.imshow(detaperdft)
plt.colorbar()
plt.subplot(133)
plt.title("ABS error")
plt.imshow(np.abs(detaper - detaperdft))
plt.colorbar()
plt.savefig(tmp_path_factory.mktemp("detaper") / "detaper.png")
assert (np.percentile(np.abs(detaper - detaperdft), 99.0) < 1.0e-14)
assert (np.max(np.abs(detaperdft - detaperdftsep)) < 1.0e-14)
def test_degrid_dft_packed_dask_dft_check():
da = pytest.importorskip("dask.array")
# construct kernel
W = 5
OS = 3
kern = kernels.pack_kernel(kernels.kbsinc(W, oversample=OS),
W,
oversample=OS)
nrow = 100
nrow_chunk = nrow // 8
uvw = np.column_stack(
(5000.0 * np.cos(np.linspace(0, 2 * np.pi, nrow)),
5000.0 * np.sin(np.linspace(0, 2 * np.pi, nrow)), np.zeros(nrow)))
pxacrossbeam = 10
nchan = 16
frequency = np.linspace(1.0e9, 1.4e9, nchan)
wavelength = lightspeed / frequency
cell = np.rad2deg(
wavelength[0] /
(2 * max(np.max(np.abs(uvw[:, 0])), np.max(np.abs(uvw[:, 1]))) *
pxacrossbeam))
npix = 512
mod = np.zeros((1, npix, npix), dtype=np.complex64)
mod[0, npix // 2 - 5, npix // 2 - 5] = 1.0
ftmod = np.fft.ifftshift(np.fft.fft2(np.fft.fftshift(
mod[0, :, :]))).reshape((1, 1, npix, npix))
chanmap = np.zeros(nchan, dtype=np.int64)
dec, ra = np.meshgrid(
np.arange(-npix // 2, npix // 2) * np.deg2rad(cell),
np.arange(-npix // 2, npix // 2) * np.deg2rad(cell))
radec = np.column_stack((ra.flatten(), dec.flatten()))
vis_dft = im_to_vis(mod[0, :, :].reshape(1, 1, npix * npix).T.copy(), uvw,
radec, frequency)
vis_degrid = dwrap.degridder(
da.from_array(uvw, chunks=(nrow_chunk, 3)),
da.from_array(ftmod, chunks=(1, 1, npix, npix)),
da.from_array(wavelength, chunks=(nchan, )),
da.from_array(chanmap, chunks=(nchan, )),
cell * 3600.0,
da.from_array(np.array([[0, np.pi / 4.0]]), chunks=(1, 2)),
(0, np.pi / 4.0),
kern,
W,
OS,
"None", # no faceting
"None", # no faceting
"XXYY_FROM_I",
"conv_1d_axisymmetric_packed_gather")
vis_degrid = vis_degrid.compute()
assert np.percentile(
np.abs(vis_dft[:, 0, 0].real - vis_degrid[:, 0, 0].real), 99.0) < 0.05
assert np.percentile(
np.abs(vis_dft[:, 0, 0].imag - vis_degrid[:, 0, 0].imag), 99.0) < 0.05
def test_degrid_dft_packed_dask():
da = pytest.importorskip("dask.array")
# construct kernel
W = 5
OS = 3
kern = kernels.pack_kernel(kernels.kbsinc(W, oversample=OS),
W,
oversample=OS)
nrow = int(5e4)
nrow_chunk = nrow // 32
uvw = np.column_stack(
(5000.0 * np.cos(np.linspace(0, 2 * np.pi, nrow)),
5000.0 * np.sin(np.linspace(0, 2 * np.pi, nrow)), np.zeros(nrow)))
pxacrossbeam = 10
nchan = 1024
frequency = np.linspace(1.0e9, 1.4e9, nchan)
wavelength = lightspeed / frequency
cell = np.rad2deg(
wavelength[0] /
(2 * max(np.max(np.abs(uvw[:, 0])), np.max(np.abs(uvw[:, 1]))) *
pxacrossbeam))
npix = 512
mod = np.zeros((1, npix, npix), dtype=np.complex64)
mod[0, npix // 2 - 5, npix // 2 - 5] = 1.0
ftmod = np.fft.ifftshift(np.fft.fft2(np.fft.fftshift(
mod[0, :, :]))).reshape((1, 1, npix, npix))
chanmap = np.zeros(nchan, dtype=np.int64)
with clock("DASK degridding") as tictoc:
vis_degrid = dwrap.degridder(
da.from_array(uvw, chunks=(nrow_chunk, 3)),
da.from_array(ftmod, chunks=(1, 1, npix, npix)),
da.from_array(wavelength, chunks=(nchan, )),
da.from_array(chanmap, chunks=(nchan, )),
cell * 3600.0,
da.from_array(np.array([[0, np.pi / 4.0]]), chunks=(1, 2)),
(0, np.pi / 4.0),
kern,
W,
OS,
"None", # no faceting
"None", # no faceting
"XXYY_FROM_I",
"conv_1d_axisymmetric_packed_gather")
vis_degrid = vis_degrid.compute()
print(tictoc)
def test_facetcodepath():
# construct kernel
W = 5
OS = 3
kern = kernels.pack_kernel(kernels.kbsinc(W, oversample=OS),
W,
oversample=OS)
# offset 0
uvw = np.array([[0, 0, 0]])
vis = np.array([[[1.0 + 0j, 1.0 + 0j]]])
gridder.gridder(uvw, vis, np.array([1.0]), np.array([0]), 64, 30, (0, 0),
(0, 0), kern, W, OS, "rotate", "phase_rotate",
"I_FROM_XXYY", "conv_1d_axisymmetric_packed_scatter")
def test_degrid_dft_packed_nondask():
# construct kernel
W = 5
OS = 3
kern = kernels.pack_kernel(kernels.kbsinc(W, oversample=OS),
W,
oversample=OS)
nrow = int(5e4)
uvw = np.column_stack(
(5000.0 * np.cos(np.linspace(0, 2 * np.pi, nrow)),
5000.0 * np.sin(np.linspace(0, 2 * np.pi, nrow)), np.zeros(nrow)))
pxacrossbeam = 10
nchan = 1024
frequency = np.linspace(1.0e9, 1.4e9, nchan)
wavelength = lightspeed / frequency
cell = np.rad2deg(
wavelength[0] /
(2 * max(np.max(np.abs(uvw[:, 0])), np.max(np.abs(uvw[:, 1]))) *
pxacrossbeam))
npix = 512
mod = np.zeros((1, npix, npix), dtype=np.complex64)
mod[0, npix // 2 - 5, npix // 2 - 5] = 1.0
ftmod = np.fft.ifftshift(np.fft.fft2(np.fft.fftshift(
mod[0, :, :]))).reshape((1, npix, npix))
chanmap = np.zeros(nchan, dtype=np.int64)
with clock("Non-DASK degridding") as tictoc:
degridder.degridder(
uvw,
ftmod,
wavelength,
chanmap,
cell * 3600.0,
(0, np.pi / 4.0),
(0, np.pi / 4.0),
kern,
W,
OS,
"None", # no faceting
"None", # no faceting
"XXYY_FROM_I",
"conv_1d_axisymmetric_packed_gather")
print(tictoc)
def test_wcorrection_faceting_forward(tmp_path_factory):
# construct kernel
W = 5
OS = 9
kern = kernels.pack_kernel(kernels.kbsinc(W, oversample=OS), W, OS)
nrow = 5000
np.random.seed(0)
# simulate some ficticious baselines rotated by an hour angle
uvw = np.zeros((nrow, 3), dtype=np.float64)
blpos = np.random.uniform(26, 10000, size=(25, 3))
ntime = int(nrow / 25.0)
d0 = np.pi / 4.0
for n in range(25):
for ih0, h0 in enumerate(
np.linspace(np.deg2rad(-20), np.deg2rad(20), ntime)):
s = np.sin
c = np.cos
R = np.array([[s(h0), c(h0), 0],
[-s(d0) * c(h0),
s(d0) * s(h0), c(d0)],
[c(d0) * c(h0), -c(d0) * s(h0),
s(d0)]])
uvw[n * ntime + ih0, :] = np.dot(R, blpos[n, :].T)
pxacrossbeam = 5
frequency = np.array([1.4e9])
wavelength = lightspeed / frequency
cell = np.rad2deg(
wavelength[0] /
(max(np.max(np.abs(uvw[:, 0])), np.max(np.abs(uvw[:, 1]))) *
pxacrossbeam))
npixfacet = 100
mod = np.ones((1, 1, 1), dtype=np.complex64)
deltaradec = np.array([[20 * np.deg2rad(cell), 20 * np.deg2rad(cell)]])
lm = radec_to_lmn(deltaradec + np.array([[0, d0]]),
phase_centre=np.array([0, d0]))
vis_dft = im_to_vis(mod, uvw, lm[:, 0:2],
frequency).repeat(2).reshape(nrow, 1, 2)
chanmap = np.array([0])
ftmod = np.ones((1, npixfacet, npixfacet),
dtype=np.complex64) # point source at centre of facet
vis_degrid = degridder.degridder(
uvw,
ftmod,
wavelength,
chanmap,
cell * 3600.0,
(deltaradec + np.array([[0, d0]]))[0, :],
(0, d0),
kern,
W,
OS,
"rotate", # no faceting
"phase_rotate", # no faceting
"XXYY_FROM_I",
"conv_1d_axisymmetric_packed_gather")
try:
import matplotlib
except ImportError:
pass
else:
matplotlib.use("agg")
from matplotlib import pyplot as plt
plot_dir = tmp_path_factory.mktemp("wcorrection_forward")
plt.figure()
plt.plot(vis_degrid[:, 0, 0].real,
label=r"$\Re(\mathtt{degrid facet})$")
plt.plot(vis_dft[:, 0, 0].real, label=r"$\Re(\mathtt{dft})$")
plt.plot(np.abs(vis_dft[:, 0, 0].real - vis_degrid[:, 0, 0].real),
label="Error")
plt.legend()
plt.xlabel("sample")
plt.ylabel("Real of predicted")
plt.savefig(plot_dir / "facet_degrid_vs_dft_re_packed.png")
plt.figure()
plt.plot(vis_degrid[:, 0, 0].imag,
label=r"$\Im(\mathtt{degrid facet})$")
plt.plot(vis_dft[:, 0, 0].imag, label=r"$\Im(\mathtt{dft})$")
plt.plot(np.abs(vis_dft[:, 0, 0].imag - vis_degrid[:, 0, 0].imag),
label="Error")
plt.legend()
plt.xlabel("sample")
plt.ylabel("Imag of predicted")
plt.savefig(plot_dir / "facet_degrid_vs_dft_im_packed.png")
assert np.percentile(
np.abs(vis_dft[:, 0, 0].real - vis_degrid[:, 0, 0].real), 99.0) < 0.05
assert np.percentile(
np.abs(vis_dft[:, 0, 0].imag - vis_degrid[:, 0, 0].imag), 99.0) < 0.05
def test_wcorrection_faceting_backward(tmp_path_factory):
# construct kernel
W = 5
OS = 9
kern = kernels.pack_kernel(kernels.kbsinc(W, oversample=OS), W, OS)
nrow = 5000
np.random.seed(0)
# simulate some ficticious baselines rotated by an hour angle
uvw = np.zeros((nrow, 3), dtype=np.float64)
blpos = np.random.uniform(26, 10000, size=(25, 3))
ntime = int(nrow / 25.0)
d0 = np.pi / 4.0
for n in range(25):
for ih0, h0 in enumerate(
np.linspace(np.deg2rad(-20), np.deg2rad(20), ntime)):
s = np.sin
c = np.cos
R = np.array([[s(h0), c(h0), 0],
[-s(d0) * c(h0),
s(d0) * s(h0), c(d0)],
[c(d0) * c(h0), -c(d0) * s(h0),
s(d0)]])
uvw[n * ntime + ih0, :] = np.dot(R, blpos[n, :].T)
pxacrossbeam = 5
frequency = np.array([1.4e9])
wavelength = lightspeed / frequency
cell = np.rad2deg(
wavelength[0] /
(max(np.max(np.abs(uvw[:, 0])), np.max(np.abs(uvw[:, 1]))) *
pxacrossbeam))
npix = 2048
npixfacet = 100
fftpad = 1.1
mod = np.ones((1, 1, 1), dtype=np.complex64)
deltaradec = np.array([[600 * np.deg2rad(cell), 600 * np.deg2rad(cell)]])
lm = radec_to_lmn(deltaradec + np.array([[0, d0]]),
phase_centre=np.array([0, d0]))
vis_dft = im_to_vis(mod, uvw, lm[:, 0:2],
frequency).repeat(2).reshape(nrow, 1, 2)
chanmap = np.array([0])
detaper = kernels.compute_detaper_dft_seperable(
int(npix * fftpad), kernels.unpack_kernel(kern, W, OS), W, OS)
vis_grid_nofacet = gridder.gridder(
uvw,
vis_dft,
wavelength,
chanmap,
int(npix * fftpad),
cell * 3600.0,
(0, d0),
(0, d0),
kern,
W,
OS,
"None", # no faceting
"None", # no faceting
"I_FROM_XXYY",
"conv_1d_axisymmetric_packed_scatter",
do_normalize=True)
ftvis = (np.fft.fftshift(
np.fft.ifft2(np.fft.ifftshift(vis_grid_nofacet[0, :, :]))).reshape(
(1, int(npix * fftpad), int(npix * fftpad)))).real / detaper * int(
npix * fftpad)**2
ftvis = ftvis[:,
int(npix * fftpad) // 2 - npix // 2:int(npix * fftpad) // 2 -
npix // 2 + npix,
int(npix * fftpad) // 2 - npix // 2:int(npix * fftpad) // 2 -
npix // 2 + npix]
detaper_facet = kernels.compute_detaper_dft_seperable(
int(npixfacet * fftpad), kernels.unpack_kernel(kern, W, OS), W, OS)
vis_grid_facet = gridder.gridder(uvw,
vis_dft,
wavelength,
chanmap,
int(npixfacet * fftpad),
cell * 3600.0,
(deltaradec + np.array([[0, d0]]))[0, :],
(0, d0),
kern,
W,
OS,
"rotate",
"phase_rotate",
"I_FROM_XXYY",
"conv_1d_axisymmetric_packed_scatter",
do_normalize=True)
ftvisfacet = (np.fft.fftshift(
np.fft.ifft2(np.fft.ifftshift(vis_grid_facet[0, :, :]))).reshape(
(1, int(npixfacet * fftpad), int(
npixfacet * fftpad)))).real / detaper_facet * int(
npixfacet * fftpad)**2
ftvisfacet = ftvisfacet[:,
int(npixfacet * fftpad) // 2 -
npixfacet // 2:int(npixfacet * fftpad) // 2 -
npixfacet // 2 + npixfacet,
int(npixfacet * fftpad) // 2 -
npixfacet // 2:int(npixfacet * fftpad) // 2 -
npixfacet // 2 + npixfacet]
try:
import matplotlib
except ImportError:
pass
else:
matplotlib.use("agg")
from matplotlib import pyplot as plt
plot_dir = tmp_path_factory.mktemp("wcorrection_backward")
plt.figure()
plt.subplot(121)
plt.imshow(ftvis[0, 1624 - 50:1624 + 50, 1447 - 50:1447 + 50])
plt.colorbar()
plt.title("Offset FFT (peak={0:.1f})".format(np.max(ftvis)))
plt.subplot(122)
plt.imshow(ftvisfacet[0, :, :])
plt.colorbar()
plt.title("Faceted FFT (peak={0:.1f})".format(np.max(ftvisfacet)))
plt.savefig(plot_dir / "facet_imaging.png")
assert (np.abs(np.max(ftvisfacet[0, :, :]) - 1.0) < 1.0e-6)
def test_grid_dft_packed(tmp_path_factory):
# construct kernel
W = 7
OS = 1009
kern = kernels.pack_kernel(kernels.kbsinc(W, oversample=OS), W, OS)
nrow = 5000
np.random.seed(0)
uvw = np.random.normal(scale=6000, size=(nrow, 3))
uvw[:, 2] = 0.0 # ignore widefield effects for now
pxacrossbeam = 10
frequency = np.array([30.0e9])
wavelength = lightspeed / frequency
cell = np.rad2deg(
wavelength[0] /
(2 * max(np.max(np.abs(uvw[:, 0])), np.max(np.abs(uvw[:, 1]))) *
pxacrossbeam))
npix = 256
fftpad = 1.25
mod = np.zeros((1, npix, npix), dtype=np.complex64)
for n in [int(n) for n in np.linspace(npix // 8, 2 * npix // 5, 5)]:
mod[0, npix // 2 + n, npix // 2 + n] = 1.0
mod[0, npix // 2 + n, npix // 2 - n] = 1.0
mod[0, npix // 2 - n, npix // 2 - n] = 1.0
mod[0, npix // 2 - n, npix // 2 + n] = 1.0
mod[0, npix // 2, npix // 2 + n] = 1.0
mod[0, npix // 2, npix // 2 - n] = 1.0
mod[0, npix // 2 - n, npix // 2] = 1.0
mod[0, npix // 2 + n, npix // 2] = 1.0
dec, ra = np.meshgrid(
np.arange(-npix // 2, npix // 2) * np.deg2rad(cell),
np.arange(-npix // 2, npix // 2) * np.deg2rad(cell))
radec = np.column_stack((ra.flatten(), dec.flatten()))
vis_dft = im_to_vis(mod[0, :, :].reshape(1, 1, npix * npix).T.copy(), uvw,
radec, frequency).repeat(2).reshape(nrow, 1, 2)
chanmap = np.array([0])
detaper = kernels.compute_detaper_dft_seperable(
int(npix * fftpad), kernels.unpack_kernel(kern, W, OS), W, OS)
vis_grid = gridder.gridder(
uvw,
vis_dft,
wavelength,
chanmap,
int(npix * fftpad),
cell * 3600.0,
(0, np.pi / 4.0),
(0, np.pi / 4.0),
kern,
W,
OS,
"None", # no faceting
"None", # no faceting
"I_FROM_XXYY",
"conv_1d_axisymmetric_packed_scatter",
do_normalize=True)
ftvis = (np.fft.fftshift(np.fft.ifft2(np.fft.ifftshift(
vis_grid[0, :, :]))).reshape((1, int(npix * fftpad), int(
npix * fftpad)))).real / detaper * int(npix * fftpad)**2
ftvis = ftvis[:,
int(npix * fftpad) // 2 - npix // 2:int(npix * fftpad) // 2 -
npix // 2 + npix,
int(npix * fftpad) // 2 - npix // 2:int(npix * fftpad) // 2 -
npix // 2 + npix]
dftvis = vis_to_im(vis_dft, uvw, radec, frequency,
np.zeros(vis_dft.shape,
dtype=np.bool)).T.copy().reshape(
2, 1, npix, npix) / nrow
try:
import matplotlib
except ImportError:
pass
else:
matplotlib.use("agg")
from matplotlib import pyplot as plt
plt.figure()
plt.subplot(131)
plt.title("FFT")
plt.imshow(ftvis[0, :, :])
plt.colorbar()
plt.subplot(132)
plt.title("DFT")
plt.imshow(dftvis[0, 0, :, :])
plt.colorbar()
plt.subplot(133)
plt.title("ABS diff")
plt.imshow(np.abs(ftvis[0, :, :] - dftvis[0, 0, :, :]))
plt.colorbar()
plt.savefig(
tmp_path_factory.mktemp("grid_dft_packed") /
"grid_diff_dft_packed.png")
assert (np.percentile(np.abs(ftvis[0, :, :] - dftvis[0, 0, :, :]), 95.0) <
0.15)
def test_degrid_dft_packed(tmp_path_factory):
# construct kernel
W = 5
OS = 3
kern = kernels.pack_kernel(kernels.kbsinc(W, oversample=OS),
W,
oversample=OS)
uvw = np.column_stack(
(5000.0 * np.cos(np.linspace(0, 2 * np.pi, 1000)),
5000.0 * np.sin(np.linspace(0, 2 * np.pi, 1000)), np.zeros(1000)))
pxacrossbeam = 10
frequency = np.array([1.4e9])
wavelength = lightspeed / frequency
cell = np.rad2deg(
wavelength[0] /
(2 * max(np.max(np.abs(uvw[:, 0])), np.max(np.abs(uvw[:, 1]))) *
pxacrossbeam))
npix = 512
mod = np.zeros((1, npix, npix), dtype=np.complex64)
mod[0, npix // 2 - 5, npix // 2 - 5] = 1.0
ftmod = np.fft.ifftshift(np.fft.fft2(np.fft.fftshift(
mod[0, :, :]))).reshape((1, npix, npix))
chanmap = np.array([0])
vis_degrid = degridder.degridder(
uvw,
ftmod,
wavelength,
chanmap,
cell * 3600.0,
(0, np.pi / 4.0),
(0, np.pi / 4.0),
kern,
W,
OS,
"None", # no faceting
"None", # no faceting
"XXYY_FROM_I",
"conv_1d_axisymmetric_packed_gather")
dec, ra = np.meshgrid(
np.arange(-npix // 2, npix // 2) * np.deg2rad(cell),
np.arange(-npix // 2, npix // 2) * np.deg2rad(cell))
radec = np.column_stack((ra.flatten(), dec.flatten()))
vis_dft = im_to_vis(mod[0, :, :].reshape(1, 1, npix * npix).T.copy(), uvw,
radec, frequency)
try:
import matplotlib
except ImportError:
pass
else:
matplotlib.use("agg")
from matplotlib import pyplot as plt
plt.figure()
plt.plot(vis_degrid[:, 0, 0].real, label=r"$\Re(\mathtt{degrid})$")
plt.plot(vis_dft[:, 0, 0].real, label=r"$\Re(\mathtt{dft})$")
plt.plot(np.abs(vis_dft[:, 0, 0].real - vis_degrid[:, 0, 0].real),
label="Error")
plt.legend()
plt.xlabel("sample")
plt.ylabel("Real of predicted")
plt.savefig(
os.path.join(os.environ.get("TMPDIR", "/tmp"),
"degrid_vs_dft_re_packed.png"))
plt.figure()
plt.plot(vis_degrid[:, 0, 0].imag, label=r"$\Im(\mathtt{degrid})$")
plt.plot(vis_dft[:, 0, 0].imag, label=r"$\Im(\mathtt{dft})$")
plt.plot(np.abs(vis_dft[:, 0, 0].imag - vis_degrid[:, 0, 0].imag),
label="Error")
plt.legend()
plt.xlabel("sample")
plt.ylabel("Imag of predicted")
plt.savefig(
tmp_path_factory.mktemp("degrid_dft_packed") /
"degrid_vs_dft_im_packed.png")
assert np.percentile(
np.abs(vis_dft[:, 0, 0].real - vis_degrid[:, 0, 0].real), 99.0) < 0.05
assert np.percentile(
np.abs(vis_dft[:, 0, 0].imag - vis_degrid[:, 0, 0].imag), 99.0) < 0.05
def test_gridder_dask():
da = pytest.importorskip("dask.array")
with clock("DASK gridding") as tictoc:
# construct kernel
W = 5
OS = 9
kern = kernels.pack_kernel(kernels.kbsinc(W, oversample=OS), W, OS)
nrow = int(1e6)
np.random.seed(0)
# simulate some ficticious baselines rotated by an hour angle
row_chunks = nrow // 10
uvw = np.zeros((nrow, 3), dtype=np.float64)
blpos = np.random.uniform(26, 10000, size=(25, 3))
ntime = int(nrow / 25.0)
d0 = np.pi / 4.0
for n in range(25):
for ih0, h0 in enumerate(
np.linspace(np.deg2rad(-20), np.deg2rad(20), ntime)):
s = np.sin
c = np.cos
R = np.array([[s(h0), c(h0), 0],
[-s(d0) * c(h0),
s(d0) * s(h0),
c(d0)], [c(d0) * c(h0), -c(d0) * s(h0),
s(d0)]])
uvw[n * ntime + ih0, :] = np.dot(R, blpos[n, :].T)
uvw = da.from_array(uvw, chunks=(row_chunks, 3))
pxacrossbeam = 5
nchan = 128
frequency = da.from_array(np.linspace(1.0e9, 1.4e9, nchan),
chunks=(nchan, ))
wavelength = lightspeed / frequency
cell = da.rad2deg(wavelength[0] / (max(da.max(da.absolute(
uvw[:, 0])), da.max(da.absolute(uvw[:, 1]))) * pxacrossbeam))
npixfacet = 100
fftpad = 1.1
image_centres = da.from_array(np.array([[0, d0]]), chunks=(1, 2))
chanmap = da.from_array(np.zeros(nchan, dtype=np.int64),
chunks=(nchan, ))
detaper_facet = kernels.compute_detaper_dft_seperable(
int(npixfacet * fftpad), kernels.unpack_kernel(kern, W, OS), W, OS)
vis_dft = da.ones(shape=(nrow, nchan, 2),
chunks=(row_chunks, nchan, 2),
dtype=np.complex64)
vis_grid_facet = dwrap.gridder(uvw,
vis_dft,
wavelength,
chanmap,
int(npixfacet * fftpad),
cell * 3600.0,
image_centres, (0, d0),
kern,
W,
OS,
"None",
"None",
"I_FROM_XXYY",
"conv_1d_axisymmetric_packed_scatter",
do_normalize=True)
vis_grid_facet = vis_grid_facet.compute()
ftvisfacet = (np.fft.fftshift(
np.fft.ifft2(np.fft.ifftshift(vis_grid_facet[0, :, :]))).reshape(
(1, int(npixfacet * fftpad), int(
npixfacet * fftpad)))).real / detaper_facet * int(
npixfacet * fftpad)**2
ftvisfacet = ftvisfacet[:,
int(npixfacet * fftpad) // 2 -
npixfacet // 2:int(npixfacet * fftpad) // 2 -
npixfacet // 2 + npixfacet,
int(npixfacet * fftpad) // 2 -
npixfacet // 2:int(npixfacet * fftpad) // 2 -
npixfacet // 2 + npixfacet]
print(tictoc)
assert (np.abs(np.max(ftvisfacet[0, :, :]) - 1.0) < 1.0e-6)