Skip to content

Commit

Permalink
improvements; fix unit tests; reviewer comments
Browse files Browse the repository at this point in the history
  • Loading branch information
@mcara
mcara committed Dec 10, 2024
1 parent 8690bee commit bef3e11
Show file tree
Hide file tree
Showing 4 changed files with 151 additions and 78 deletions.
1 change: 1 addition & 0 deletions .coveragerc
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@ source = drizzle

omit =
drizzle/__init__*
drizzle/util.py
drizzle/**/conftest.py
drizzle/**/setup*
drizzle/**/tests/*
Expand Down
114 changes: 83 additions & 31 deletions drizzle/resample.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -315,17 +315,6 @@ def __init__(self, kernel="square", fillval=None, fillval2=None,
out_img = np.asarray(out_img, dtype=np.float32)
shapes.add(out_img.shape)

if out_img2 is not None:
if isinstance(out_img2, np.ndarray):
out_img2 = np.asarray(out_img2, dtype=np.float32)
shapes.add(out_img2.shape)
else:
out_img2 = [
np.asarray(img, dtype=np.float32) for img in out_img2
]
for img in out_img2:
shapes.add(img.shape)

if out_wht is not None:
out_wht = np.asarray(out_wht, dtype=np.float32)
shapes.add(out_wht.shape)
Expand All @@ -350,7 +339,6 @@ def __init__(self, kernel="square", fillval=None, fillval2=None,
out_wht=out_wht,
out_ctx=out_ctx,
)
self._alloc_output_arrays2_init(out_img2=out_img2)

elif len(shapes) > 1:
raise ValueError(
Expand All @@ -363,39 +351,64 @@ def __init__(self, kernel="square", fillval=None, fillval2=None,
self._out_wht = None
self._out_ctx = None

if out_img2 is not None:
if self._out_shape is not None:
shapes.add(self._out_shape)
if isinstance(out_img2, np.ndarray):
out_img2 = np.asarray(out_img2, dtype=np.float32)
shapes.add(out_img2.shape)
else:
for img in out_img2:
if img is not None:
shapes.add(np.shape(img))
if len(shapes) > 1:
raise ValueError(
"Inconsistent data shapes specified: 'out_shape' "
"and/or out_img, out_img2, out_wht, out_ctx have "
"different shapes."
)
self._output_shapes = shapes
self._alloc_output_arrays2_init(out_img2=out_img2)

@property
def fillval(self):
"""Fill value for output pixels without contributions from input images."""
""" Fill value for output pixels without contributions from input images. """
return self._fillval

@property
def fillval2(self):
""" Fill value for output pixels in ``out_img2`` without contributions
from input images. """
return self._fillval2

@property
def kernel(self):
"""Resampling kernel."""
return self._kernel

@property
def ctx_id(self):
"""Context image "ID" (0-based ) of the next image to be resampled."""
""" Context image "ID" (0-based ) of the next image to be resampled. """
return self._ctx_id

@property
def out_img(self):
"""Output resampled image."""
""" Output resampled image. """
return self._out_img

@property
def out_wht(self):
"""Output weight image."""
""" Output weight image. """
return self._out_wht

@property
def out_ctx(self):
"""Output "context" image."""
""" Output "context" image. """
return self._out_ctx

@property
def out_img2(self):
"""Output resampled image(s) obtained with squared weights.
""" Output resampled image(s) obtained with squared weights.
It is always a list of one or more 2D arrays.
"""
Expand Down Expand Up @@ -458,14 +471,35 @@ def _alloc_output_arrays2_init(self, out_img2=None):
out_img2 = [out_img2]

self._out_img2 = []

if (isinstance(self._fillval2, str) and
self._fillval2.strip().upper() == "INDEF"):
fv = np.nan
else:
fv = np.float32(self._fillval2)

for i2 in out_img2:
if i2 is None:
arr = np.zeros(self._out_shape, dtype=np.float32)
if self._out_shape is None:
if len(self._output_shapes) == 1:
shape = list(self._output_shapes)[0]
else:
self._out_img2.append(None)
continue
else:
shape = self._out_shape
arr = np.full(shape, fill_value=fv, dtype=np.float32)
else:
arr = np.asarray(i2, dtype=np.float32)
self._out_img2.append(arr)
del arr

def _alloc_output_arrays2_add(self, ninputs2=None):
if (isinstance(self._fillval2, str) and
self._fillval2.strip().upper() == "INDEF"):
fv = np.nan
else:
fv = np.float32(self._fillval2)
if self._out_img2 is None:
if ninputs2 is None or ninputs2 < 1:
# nothing to do
Expand All @@ -476,13 +510,22 @@ def _alloc_output_arrays2_add(self, ninputs2=None):
"and the number of inputs."
)
self._out_img2 = [
np.zeros(self._out_shape, dtype=np.float32)
np.full(self._out_shape, fill_value=fv, dtype=np.float32)
for _ in range(ninputs2)
]

else:
nimg2 = len(self._out_img2)

# replace None values with arrays of _out_shape:
for k, img in enumerate(self._out_img2):
if img is None:
self._out_img2[k] = np.full(
self._out_shape,
fill_value=fv,
dtype=np.float32
)

if ((ninputs2 is not None and ninputs2 != nimg2) or
(ninputs2 is None and nimg2 > 0)):
raise ValueError(
Expand Down Expand Up @@ -627,17 +670,26 @@ def add_image(self, data, exptime, pixmap, data2=None, scale=1.0,
# set output image shape based on output coordinates from the pixmap.
#
if self._out_shape is None:
pmap_xmin = int(np.floor(np.nanmin(pixmap[:, :, 0])))
pmap_xmax = int(np.ceil(np.nanmax(pixmap[:, :, 0])))
pmap_ymin = int(np.floor(np.nanmin(pixmap[:, :, 1])))
pmap_ymax = int(np.ceil(np.nanmax(pixmap[:, :, 1])))
pixmap = pixmap.copy()
pixmap[:, :, 0] -= pmap_xmin
pixmap[:, :, 1] -= pmap_ymin
self._out_shape = (
pmap_xmax - pmap_xmin + 1,
pmap_ymax - pmap_ymin + 1
)
nshapes = len(self._output_shapes)
if nshapes == 0:
pmap_xmin = int(np.floor(np.nanmin(pixmap[:, :, 0])))
pmap_xmax = int(np.ceil(np.nanmax(pixmap[:, :, 0])))
pmap_ymin = int(np.floor(np.nanmin(pixmap[:, :, 1])))
pmap_ymax = int(np.ceil(np.nanmax(pixmap[:, :, 1])))
pixmap = pixmap.copy()
pixmap[:, :, 0] -= pmap_xmin
pixmap[:, :, 1] -= pmap_ymin
self._out_shape = (
pmap_xmax - pmap_xmin + 1,
pmap_ymax - pmap_ymin + 1
)
elif nshapes == 1:
self._out_shape = list(self._output_shapes)[0]
else:
raise ValueError(
"Inconsistent data shapes: 'out_shape' and/or "
"out_img, out_img2, out_wht, out_ctx have different shapes."
) # pragma: no cover

self._alloc_output_arrays(
out_shape=self._out_shape,
Expand Down
35 changes: 28 additions & 7 deletions drizzle/tests/test_resample.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -1477,8 +1477,6 @@ def test_drizzle_weights_squared(kernel, fc):

out_shape = (int(y.max()) + 1, int(x.max()) + 1)

assert np.min(x) > -0.5 and np.min(y) > -0.5

if fc:
# create a Drizzle object using all default parameters
# (except for 'kernel', 'out_shape')
Expand Down Expand Up @@ -1512,15 +1510,14 @@ def test_drizzle_weights_squared(kernel, fc):
assert len(driz.out_img2) == 1

else:
# create a Drizzle object using all default parameters
# (except for 'kernel')
# create a Drizzle object using mostly default parameters
driz = resample.Drizzle(
kernel=kernel,
out_img2=[None],
fillval2=-99.0,
)

assert driz.out_img is None
assert driz.out_img2 is None
assert driz.total_exptime == 0.0

with pytest.warns(Warning):
Expand Down Expand Up @@ -1553,6 +1550,7 @@ def test_drizzle_weights_squared(kernel, fc):
rtol=1.0e-6,
atol=0.0
)
assert abs(float(driz.fillval2) + 99.0) < 1e-7


def test_drizzle_weights_squared_bad_inputs():
Expand Down Expand Up @@ -1695,6 +1693,7 @@ def test_drizzle_weights_squared_array_shape_mismatch():
y, x = np.indices(in_shape, dtype=np.float64)

in_sci1 = np.zeros(in_shape, dtype=np.float32)
in_sci1[n // 2, n // 2] = 2.222222222222
in_sci1_sq = np.zeros(in_shape, dtype=np.float32)

in_wht2 = np.zeros(in_shape1, dtype=np.float32)
Expand All @@ -1719,15 +1718,16 @@ def test_drizzle_weights_squared_array_shape_mismatch():

driz = resample.Drizzle(
kernel=kernel,
out_img2=[out_img2, out_img2],
out_img=out_img2.copy(),
out_img2=[out_img2, out_img2, None],
)
with pytest.raises(ValueError) as err_info:
driz.add_image(
data=in_sci1,
exptime=1.0,
pixmap=pixmap,
weight_map=in_wht2,
data2=[in_sci1_sq, in_sci2_sq],
data2=[in_sci1_sq, in_sci2_sq, None],
)
assert str(err_info.value).startswith(
"'data2' shape(s) is not consistent with 'data' shape."
Expand Down Expand Up @@ -1772,3 +1772,24 @@ def test_drizzle_weights_squared_array_shape_mismatch():
assert str(err_info.value).startswith(
"'weight_map' shape is not consistent with 'data' shape."
)

# zero-sized variance array
driz = resample.Drizzle(
kernel=kernel,
out_img2=[out_img2, out_img2.copy(), out_img2.copy(), None]
)
driz.add_image(
data=in_sci1,
exptime=1.0,
pixmap=pixmap,
data2=[in_sci1, in_sci1, np.array([]), None]
)
driz.add_image(
data=in_sci1,
exptime=1.0,
pixmap=pixmap,
data2=[in_sci1, None, in_sci1, None]
)
assert np.allclose(np.nansum(driz.out_img2[0]), 2.0 * np.nansum(driz.out_img2[1]))
assert np.allclose(np.nansum(driz.out_img2[0]), 2.0 * np.nansum(driz.out_img2[2]))
assert np.allclose(0.0, np.nansum(driz.out_img2[3]))
Loading

0 comments on commit bef3e11

Please sign in to comment.