def test_shift4():
a = np.array([[0.,0,0],[0,1,0],[0,0,0]])
b = np.empty_like(a)
shift(a, b, 1, axis=1)
assert_all_eq(b, np.roll(a,1,axis=1))
shift(b, b, -2, axis=1)
assert_all_eq(b, np.roll(a,-1,axis=1))
def test_shift4():
a = np.array([[0., 0, 0], [0, 1, 0], [0, 0, 0]])
b = np.empty_like(a)
shift(a, b, 1, axis=1)
assert_all_eq(b, np.roll(a, 1, axis=1))
shift(b, b, -2, axis=1)
assert_all_eq(b, np.roll(a, -1, axis=1))
def test_write():
filename2 = 'test-' + id + '.fits'
lmap.save(filename2)
ref2 = Map(filename2, comm=MPI.COMM_SELF)
lmap2 = Map(filename2, comm=MPI.COMM_WORLD)
lmap2.save('test' + str(rank) + 'fits', comm=MPI.COMM_SELF)
assert_all_eq(lmap, lmap2)
assert_all_eq(ref, ref2)
def test_write():
filename2 = 'test-' + id + '.fits'
lmap.save(filename2)
ref2 = Map(filename2, comm=MPI.COMM_SELF)
lmap2 = Map(filename2, comm=MPI.COMM_WORLD)
lmap2.save('test'+str(rank)+'fits', comm=MPI.COMM_SELF)
assert_all_eq(lmap, lmap2)
assert_all_eq(ref, ref2)
def test_read():
shape_global = ref.shape
shape_local = distribute_shape(shape_global)
assert_equal(shape_local, lmap.shape)
lmaps = MPI.COMM_WORLD.allgather(lmap)
gmap = np.concatenate(lmaps, axis=0).magnitude
assert_all_eq(ref, gmap)
def func(naxis, axis):
shape = [i + 8 for i in range(naxis)]
a = np.random.random_integers(1, 10, size=shape).astype(float)
ref = -np.diff(a, axis=axis)
diff(a, a, axis=axis)
s = tuple([slice(0, s) for s in ref.shape])
print s, a.shape, ref.shape
a[s] -= ref
assert_all_eq(a, 0)
def func(naxis, axis):
shape = [i+8 for i in range(naxis)]
a=np.random.random_integers(1, 10, size=shape).astype(float)
ref = -np.diff(a, axis=axis)
diff(a, a, axis=axis)
s = tuple([slice(0,s) for s in ref.shape])
print s, a.shape, ref.shape
a[s] -= ref
assert_all_eq(a, 0)
def test_read():
shape_global = ref.shape
shape_local = distribute_shape(shape_global)
assert_equal(shape_local, lmap.shape)
lmaps = MPI.COMM_WORLD.allgather(lmap)
gmap = np.concatenate(lmaps, axis=0).magnitude
assert_all_eq(ref, gmap)
def test1():
comm_map = MPI.COMM_SELF
for obs, tod in ((obs1, tod1), (obs2, tod2)):
proj = obs.get_projection_operator(downsampling=True,
npixels_per_sample=6, header=map_ref_global.header,
commin=comm_map)
proj.apply_mask(tod.mask)
m = mapper_naive(tod, proj)
yield check_map_global, m
assert_all_eq(proj.get_mask(), mask_ref_global)
def test1():
comm_map = MPI.COMM_SELF
for obs, tod in ((obs1, tod1), (obs2, tod2)):
proj = obs.get_projection_operator(
downsampling=True, npixels_per_sample=6, header=map_ref_global.header, commin=comm_map
)
proj.apply_mask(tod.mask)
m = mapper_naive(tod, proj)
yield check_map_global, m
assert_all_eq(proj.get_mask(), mask_ref_global)
def func(x):
y = filter_nonfinite(x)
y_expected = np.asanyarray(x).copy()
y_expected[~np.isfinite(x)] = 0
if hasattr(x, 'mask') and x.mask is not None:
y_expected.mask = x.mask.copy()
y_expected.mask[~np.isfinite(x)] = True
assert_all_eq(y, y_expected)
x = np.asanyarray(x)
filter_nonfinite(x, out=x)
assert_all_eq(x, y_expected)
def func(x):
y = filter_nonfinite(x)
y_expected = np.asanyarray(x).copy()
y_expected[~np.isfinite(x)] = 0
if hasattr(x, 'mask') and x.mask is not None:
y_expected.mask = x.mask.copy()
y_expected.mask[~np.isfinite(x)] = True
assert_all_eq(y, y_expected)
x = np.asanyarray(x)
filter_nonfinite(x, out=x)
assert_all_eq(x, y_expected)
def func(a, s):
b = np.empty_like(a)
shift(b, b, s, axis=-1)
assert_all_eq(b, 0)
def check_map_local(m):
assert_all_eq(m.magnitude, map_ref_local.magnitude, mtol)
assert_all_eq(m.coverage, cov_ref_local, mtol)
from pyoperators.utils.mpi import MPI
from pysimulators import FitsArray, Map, Tod
from tamasis.utils import assert_all_eq
raise SkipTest
tamasis.var.verbose = True
rank = MPI.COMM_WORLD.Get_rank()
size = MPI.COMM_WORLD.Get_size()
# test DistributedArray
shapes = [ (10,), (5,4), (3,4,2) ]
dtypes = (int, float, complex)
for shape in shapes:
for dtype in dtypes:
for order in ('c', 'f'):
a = np.random.random_sample(shape).astype(dtype)
a = MPI.COMM_WORLD.bcast(a)
objs = [
FitsArray(a, dtype=dtype, order=order),
Map(a, dtype=dtype, order=order, error=a, coverage=a),
Tod(a, dtype=dtype, order=order, mask=a.astype(np.bool))
]
for obj in objs:
if isinstance(obj, Tod) and obj.ndim == 1:
continue
local = obj.tolocal()
globa = local.toglobal()
assert_all_eq(obj, globa)
def check_map_local(m):
assert_all_eq(m.magnitude, map_ref_local.magnitude, 1e-10)
assert_all_eq(m.coverage, map_ref_local.coverage, 1e-10)
assert_all_eq(m.tounit('Jy/arcsec^2'), map_ref_local.tounit('Jy/arcsec^2'),
1e-10)
def check_map_local(m):
assert_all_eq(m.magnitude, map_ref_local.magnitude, 1e-10)
assert_all_eq(m.coverage, map_ref_local.coverage, 1e-10)
assert_all_eq(m.tounit("Jy/arcsec^2"), map_ref_local.tounit("Jy/arcsec^2"), 1e-10)
def test_shift2():
a = np.array([[1.,1.,1.,1.],[2.,2.,2.,2.]])
shift(a, a, [1,-1], axis=1)
assert_all_eq(a, [[0,1,1,1],[2,2,2,0]])
def test_shift2():
a = np.array([[1., 1., 1., 1.], [2., 2., 2., 2.]])
shift(a, a, [1, -1], axis=1)
assert_all_eq(a, [[0, 1, 1, 1], [2, 2, 2, 0]])
def func(a, s):
b = np.empty_like(a)
shift(b, b, s, axis=-1)
assert_all_eq(b, 0)
