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flake8
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@mcara
mcara committed Oct 11, 2024
1 parent a6ffe26 commit bcead21
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Showing 3 changed files with 47 additions and 35 deletions.
10 changes: 8 additions & 2 deletions src/stcal/resample/__init__.py
View file
Original file line number Diff line number Diff line change
@@ -1,9 +1,15 @@
from .resample import *
from .resample import (
LibModelAccessBase,
OutputTooLargeError,
Resample,
resampled_wcs_from_models,
UnsupportedWCSError,
)

__all__ = [
"LibModelAccessBase",
"OutputTooLargeError",
"Resample",
"resampled_wcs_from_models",
"UnsupportedWCSError",
]
]
70 changes: 38 additions & 32 deletions src/stcal/resample/resample.py
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Original file line number Diff line number Diff line change
Expand Up @@ -91,7 +91,7 @@ class LibModelAccessBase(abc.ABC):
"elapsed_exposure_time",

"pixelarea_steradians",
# "pixelarea_arcsecsq",
# "pixelarea_arcsecsq",

"level", # sky level
"subtracted",
Expand Down Expand Up @@ -266,7 +266,6 @@ class Resample:
"""
resample_suffix = 'i2d'
resample_file_ext = '.fits'
n_arrays_per_output = 2 # #flt-point arrays in the output (data, weight, var, err, etc.)

# supported output arrays (subclasses can add more):
output_array_types = {
Expand Down Expand Up @@ -310,8 +309,8 @@ def __init__(self, input_models, pixfrac=1.0, kernel="square",
self._accumulate = accumulate

# these are attributes that are used only for information purpose
# and are added to created the output_model only if they are not already
# present there:
# and are added to created the output_model only if they are
# not already present there:
self._pixel_scale_ratio = None
self._output_pixel_scale = None

Expand Down Expand Up @@ -394,7 +393,8 @@ def __init__(self, input_models, pixfrac=1.0, kernel="square",
npix = np.prod(self._output_array_shape)
if not npix:
raise ValueError(
f"Invalid output frame shape: {tuple(self._output_array_shape)}"
"Invalid output frame shape: "
f"{tuple(self._output_array_shape)}"
)

# set up output model (arrays, etc.)
Expand Down Expand Up @@ -617,7 +617,8 @@ def check_memory_requirements(self, arrays, allowed_memory):
that there is enough memory to hold the output.
"""
if allowed_memory is None and "DMODEL_ALLOWED_MEMORY" not in os.environ:
if (allowed_memory is None and
"DMODEL_ALLOWED_MEMORY" not in os.environ):
return

allowed_memory = float(allowed_memory)
Expand Down Expand Up @@ -695,7 +696,7 @@ def build_driz_weight(self, model_info, weight_type=None, good_bits=None):
# apply a median filter to smooth the weight at saturated
# (or high read-out noise) single pixels. keep kernel size
# small to still give lower weight to extended CRs, etc.
ksz = weight_type[8 if selective_median else 7 :]
ksz = weight_type[8 if selective_median else 7:]
if ksz:
kernel_size = int(ksz)
if not (kernel_size % 2):
Expand Down Expand Up @@ -805,7 +806,7 @@ def finalize_time_info(self):
"start_time": min(self._exptime_start),
"end_time": max(self._exptime_end),
# Update other exposure time keywords:
# XPOSURE (identical to the total effective exposure time, EFFEXPTM)
# XPOSURE (identical to the total effective exposure time,EFFEXPTM)
"effective_exposure_time": self._total_exposure_time,
# DURATION (identical to TELAPSE, elapsed time)
"duration": self._duration,
Expand Down Expand Up @@ -1034,7 +1035,8 @@ def resample_variance_data(self, data_model, add_image_kwargs):
weight[weight_mask] = np.reciprocal(var[weight_mask])
weight_mask &= (weight > 0.0)
# Add the inverse of the resampled variance to a running sum.
# Update only pixels (in the running sum) with valid new values:
# Update only pixels (in the running sum) with
# valid new values:
self._var_rnoise_sum[weight_mask] = np.nansum(
[
self._var_rnoise_sum[weight_mask],
Expand Down Expand Up @@ -1100,18 +1102,21 @@ def finalize_variance_processing(self):
# Zero weight and missing values are NaN in the output.
with warnings.catch_warnings():
warnings.filterwarnings("ignore", "invalid value*", RuntimeWarning)
warnings.filterwarnings("ignore", "divide by zero*", RuntimeWarning)
warnings.filterwarnings(
"ignore",
"divide by zero*",
RuntimeWarning,
)

# readout noise
np.reciprocal(self._var_rnoise_sum, out=self._var_rnoise_sum)
v = self._var_rnoise_sum.astype(
dtype=self.output_array_types["var_rnoise"]
)
if self._accumulate and self._output_model["var_rnoise"]:
self._output_model["var_rnoise"] += self._var_rnoise_sum.astype(
dtype=self.output_array_types["var_rnoise"]
)
self._output_model["var_rnoise"] += v
else:
self._output_model["var_rnoise"] = self._var_rnoise_sum.astype(
dtype=self.output_array_types["var_rnoise"]
)
self._output_model["var_rnoise"] = v

# Poisson noise
for _ in range(2):
Expand All @@ -1121,14 +1126,13 @@ def finalize_variance_processing(self):
out=self._var_poisson_sum
)

v = self._var_rnoise_sum.astype(
dtype=self.output_array_types["var_poisson"]
)
if self._accumulate and self._output_model["var_poisson"]:
self._output_model["var_poisson"] += self._var_rnoise_sum.astype(
dtype=self.output_array_types["var_poisson"]
)
self._output_model["var_poisson"] += v
else:
self._output_model["var_poisson"] = self._var_rnoise_sum.astype(
dtype=self.output_array_types["var_poisson"]
)
self._output_model["var_poisson"] = v

# flat's noise
for _ in range(2):
Expand All @@ -1138,14 +1142,13 @@ def finalize_variance_processing(self):
out=self._var_flat_sum
)

v = self._var_rnoise_sum.astype(
dtype=self.output_array_types["var_flat"]
)
if self._accumulate and self._output_model["var_flat"]:
self._output_model["var_flat"] += self._var_rnoise_sum.astype(
dtype=self.output_array_types["var_flat"]
)
self._output_model["var_flat"] += v
else:
self._output_model["var_flat"] = self._var_rnoise_sum.astype(
dtype=self.output_array_types["var_flat"]
)
self._output_model["var_flat"] = v

# free arrays:
del self._var_rnoise_sum
Expand Down Expand Up @@ -1175,7 +1178,8 @@ def compute_errors(self):
self._output_model["err"] = err


def _get_boundary_points(xmin, xmax, ymin, ymax, dx=None, dy=None, shrink=0):
def _get_boundary_points(xmin, xmax, ymin, ymax, dx=None, dy=None,
shrink=0): # noqa: E741
"""
xmin, xmax, ymin, ymax - integer coordinates of pixel boundaries
step - distance between points along an edge
Expand Down Expand Up @@ -1209,7 +1213,7 @@ def _get_boundary_points(xmin, xmax, ymin, ymax, dx=None, dy=None, shrink=0):
b = np.s_[0:sx] # bottom edge
r = np.s_[sx:sx + sy] # right edge
t = np.s_[sx + sy:2 * sx + sy] # top edge
l = np.s_[2 * sx + sy:2 * sx + 2 * sy] # left
l = np.s_[2 * sx + sy:2 * sx + 2 * sy] # noqa: E741 left edge

x[b] = np.linspace(xmin, xmax, sx, False)
y[b] = ymin
Expand All @@ -1233,7 +1237,9 @@ def _compute_image_pixel_area(wcs):
raise ValueError("WCS must have array_shape attribute set.")

valid_polygon = False
spatial_idx = np.where(np.array(wcs.output_frame.axes_type) == 'SPATIAL')[0]
spatial_idx = np.where(
np.array(wcs.output_frame.axes_type) == 'SPATIAL'
)[0]

ny, nx = wcs.array_shape

Expand All @@ -1253,7 +1259,7 @@ def _compute_image_pixel_area(wcs):

while xmin < xmax and ymin < ymax:
try:
x, y, image_area, center, b, r, t, l = _get_boundary_points(
(x, y, image_area, center, b, r, t, l) = _get_boundary_points(
xmin=xmin,
xmax=xmax,
ymin=ymin,
Expand Down
2 changes: 1 addition & 1 deletion src/stcal/resample/utils.py
View file
Original file line number Diff line number Diff line change
Expand Up @@ -122,4 +122,4 @@ def bytes2human(n):
if n >= prefix[s]:
value = float(n) / prefix[s]
return '%.1f%s' % (value, s)
return "%sB" % n
return "%sB" % n

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