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Merged
Jammy2211 merged 5 commits into from
Mar 14, 2025
Merged

feature/aggregate_hdu #220

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5e8dcac
updated all save_fits inputs
Jammy2211 Mar 13, 2025
e57f637
fix test -using new fits rather than hdu
rhayes777 Mar 14, 2025
d0ffcc5
fix more tesdts
rhayes777 Mar 14, 2025
c47f0bb
fixed remaining tests
rhayes777 Mar 14, 2025
7fdff77
bump actions/cache version
rhayes777 Mar 14, 2025
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2 changes: 1 addition & 1 deletion .github/workflows/main.yml
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Expand Up @@ -32,7 +32,7 @@ jobs:
uses: actions/setup-python@v2
with:
python-version: ${{ matrix.python-version }}
- uses: actions/cache@v2
- uses: actions/cache@v3
id: cache-pip
with:
path: ~/.cache/pip
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2 changes: 1 addition & 1 deletion autogalaxy/aggregator/__init__.py
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Expand Up @@ -7,4 +7,4 @@
from autogalaxy.aggregator.ellipse.multipoles import MultipolesAgg
from autogalaxy.aggregator.ellipse.fit_ellipse import FitEllipseAgg
from autogalaxy.aggregator.subplot import SubplotDataset as subplot_dataset
from autogalaxy.aggregator.subplot import SubplotFit as subplot_fit
from autogalaxy.aggregator.subplot import SubplotFit as subplot_fit
8 changes: 4 additions & 4 deletions autogalaxy/aggregator/agg_util.py
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Expand Up @@ -38,11 +38,11 @@ def adapt_images_from(
for fit in fit_list:
try:
mask = aa.Mask2D.from_primary_hdu(
primary_hdu=fit.value(name="dataset.mask")
primary_hdu=fit.value(name="dataset.mask")[0]
)
except AttributeError:
except TypeError:
mask = aa.Mask2D.from_primary_hdu(
primary_hdu=fit.value(name="dataset.real_space_mask")
primary_hdu=fit.value(name="dataset.real_space_mask")[0]
)

galaxy_name_image_dict = {}
Expand All @@ -51,7 +51,7 @@ def adapt_images_from(

for name in adapt_image_name_list:
adapt_image = aa.Array2D.from_primary_hdu(
primary_hdu=fit.value(name=f"adapt_images.{name}")
primary_hdu=fit.value(name=f"adapt_images.{name}")[0]
)
adapt_image = adapt_image.apply_mask(mask=mask)
galaxy_name_image_dict[name] = adapt_image
Expand Down
20 changes: 11 additions & 9 deletions autogalaxy/aggregator/imaging/imaging.py
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Expand Up @@ -39,15 +39,17 @@ def _imaging_from(
dataset_list = []

for fit in fit_list:
data = aa.Array2D.from_primary_hdu(primary_hdu=fit.value(name="dataset.data"))
data = aa.Array2D.from_primary_hdu(
primary_hdu=fit.value(name="dataset.data")[0]
)
noise_map = aa.Array2D.from_primary_hdu(
primary_hdu=fit.value(name="dataset.noise_map")
primary_hdu=fit.value(name="dataset.noise_map")[0]
)
try:
psf = aa.Kernel2D.from_primary_hdu(
primary_hdu=fit.value(name="dataset.psf")
primary_hdu=fit.value(name="dataset.psf")[0]
)
except AttributeError:
except TypeError:
psf = None

dataset = aa.Imaging(
Expand All @@ -57,26 +59,26 @@ def _imaging_from(
check_noise_map=False,
)

mask = aa.Mask2D.from_primary_hdu(primary_hdu=fit.value(name="dataset.mask"))
mask = aa.Mask2D.from_primary_hdu(primary_hdu=fit.value(name="dataset.mask")[0])

dataset = dataset.apply_mask(mask=mask)

try:
over_sample_size_lp = aa.Array2D.from_primary_hdu(
primary_hdu=fit.value(name="dataset.over_sample_size_lp")
primary_hdu=fit.value(name="dataset.over_sample_size_lp")[0]
).native
over_sample_size_lp = over_sample_size_lp.apply_mask(mask=mask)
except AttributeError:
except TypeError:
over_sample_size_lp = 1

try:
over_sample_size_pixelization = aa.Array2D.from_primary_hdu(
primary_hdu=fit.value(name="dataset.over_sample_size_pixelization")
primary_hdu=fit.value(name="dataset.over_sample_size_pixelization")[0]
).native
over_sample_size_pixelization = over_sample_size_pixelization.apply_mask(
mask=mask
)
except AttributeError:
except TypeError:
over_sample_size_pixelization = 1

dataset = dataset.apply_over_sampling(
Expand Down
8 changes: 4 additions & 4 deletions autogalaxy/aggregator/interferometer/interferometer.py
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Expand Up @@ -41,18 +41,18 @@ def _interferometer_from(

for fit in fit_list:
data = aa.Visibilities(
visibilities=fit.value(name="dataset.data").data.astype("float")
visibilities=fit.value(name="dataset.data")[0].data.astype("float")
)
noise_map = aa.VisibilitiesNoiseMap(
fit.value(name="dataset.noise_map").data.astype("float")
fit.value(name="dataset.noise_map")[0].data.astype("float")
)
uv_wavelengths = fit.value(name="dataset.uv_wavelengths").data
uv_wavelengths = fit.value(name="dataset.uv_wavelengths")[0].data

real_space_mask = (
real_space_mask
if real_space_mask is not None
else aa.Mask2D.from_primary_hdu(
primary_hdu=fit.value(name="dataset.real_space_mask")
primary_hdu=fit.value(name="dataset.real_space_mask")[0]
)
)

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4 changes: 3 additions & 1 deletion autogalaxy/aggregator/subplot.py
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@@ -1,5 +1,6 @@
from enum import Enum


class SubplotDataset(Enum):
"""
The subplots that can be extracted from the subplot_fit image.
Expand All @@ -16,6 +17,7 @@ class SubplotDataset(Enum):
over_sample_size_lp = (0, 2)
over_sample_Size_pixelization = (1, 2)


class SubplotFit(Enum):
"""
The subplots that can be extracted from the subplot_fit image.
Expand All @@ -28,4 +30,4 @@ class SubplotFit(Enum):
model_image = (2, 0)
normalized_residual_map = (0, 1)
normalized_residual_map_one_sigma = (1, 1)
chi_squared_map = (2, 1)
chi_squared_map = (2, 1)
10 changes: 5 additions & 5 deletions autogalaxy/analysis/analysis/dataset.py
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Expand Up @@ -170,22 +170,22 @@ def save_attributes(self, paths: af.DirectoryPaths):
"""
paths.save_fits(
name="data",
hdu=self.dataset.data.hdu_for_output,
fits=self.dataset.data.hdu_for_output,
prefix="dataset",
)
paths.save_fits(
name="noise_map",
hdu=self.dataset.noise_map.hdu_for_output,
fits=self.dataset.noise_map.hdu_for_output,
prefix="dataset",
)
paths.save_fits(
name="over_sample_size_lp",
hdu=self.dataset.grids.lp.over_sample_size.native.hdu_for_output,
fits=self.dataset.grids.lp.over_sample_size.native.hdu_for_output,
prefix="dataset",
)
paths.save_fits(
name="over_sample_size_pixelization",
hdu=self.dataset.grids.pixelization.over_sample_size.native.hdu_for_output,
fits=self.dataset.grids.pixelization.over_sample_size.native.hdu_for_output,
prefix="dataset",
)
paths.save_json(
Expand All @@ -209,7 +209,7 @@ def save_attributes(self, paths: af.DirectoryPaths):
for name in self.adapt_images.galaxy_name_image_dict.keys():
paths.save_fits(
name=name,
hdu=self.adapt_images.galaxy_name_image_dict[name].hdu_for_output,
fits=self.adapt_images.galaxy_name_image_dict[name].hdu_for_output,
prefix="adapt_images",
)

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6 changes: 3 additions & 3 deletions autogalaxy/ellipse/model/analysis.py
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Expand Up @@ -186,17 +186,17 @@ def save_attributes(self, paths: af.DirectoryPaths):
"""
paths.save_fits(
name="data",
hdu=self.dataset.data.hdu_for_output,
fits=self.dataset.data.hdu_for_output,
prefix="dataset",
)
paths.save_fits(
name="noise_map",
hdu=self.dataset.noise_map.hdu_for_output,
fits=self.dataset.noise_map.hdu_for_output,
prefix="dataset",
)
paths.save_fits(
name="mask",
hdu=self.dataset.mask.hdu_for_output,
fits=self.dataset.mask.hdu_for_output,
prefix="dataset",
)

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4 changes: 2 additions & 2 deletions autogalaxy/imaging/model/analysis.py
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Expand Up @@ -232,12 +232,12 @@ def save_attributes(self, paths: af.DirectoryPaths):

paths.save_fits(
name="psf",
hdu=self.dataset.psf.hdu_for_output,
fits=self.dataset.psf.hdu_for_output,
prefix="dataset",
)
paths.save_fits(
name="mask",
hdu=self.dataset.mask.hdu_for_output,
fits=self.dataset.mask.hdu_for_output,
prefix="dataset",
)

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1 change: 0 additions & 1 deletion autogalaxy/imaging/model/plotter_interface.py
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Expand Up @@ -60,7 +60,6 @@ def fits_to_fits(
)

if should_plot("fits_model_galaxy_images"):

multi_plotter = aplt.MultiFigurePlotter(
plotter_list=[
aplt.Array2DPlotter(array=image, mat_plot_2d=mat_plot_2d)
Expand Down
4 changes: 2 additions & 2 deletions autogalaxy/interferometer/model/analysis.py
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Expand Up @@ -237,10 +237,10 @@ def save_attributes(self, paths: af.DirectoryPaths):
hdu = aa.util.array_2d.hdu_for_output_from(
array_2d=self.dataset.uv_wavelengths,
)
paths.save_fits(name="uv_wavelengths", hdu=hdu, prefix="dataset")
paths.save_fits(name="uv_wavelengths", fits=hdu, prefix="dataset")
paths.save_fits(
name="real_space_mask",
hdu=self.dataset.real_space_mask.hdu_for_output,
fits=self.dataset.real_space_mask.hdu_for_output,
prefix="dataset",
)
paths.save_json(
Expand Down
10 changes: 8 additions & 2 deletions autogalaxy/profiles/mass/dark/gnfw_virial_mass_gnfw_conc.py
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Expand Up @@ -11,7 +11,13 @@


def kappa_s_and_scale_radius(
cosmology, virial_mass, concentration, overdens, redshift_object, redshift_source, inner_slope
cosmology,
virial_mass,
concentration,
overdens,
redshift_object,
redshift_source,
inner_slope,
):
# gNFW concentration imported

Expand Down Expand Up @@ -129,4 +135,4 @@ def __init__(
kappa_s=kappa_s,
inner_slope=inner_slope,
scale_radius=scale_radius,
)
)
6 changes: 3 additions & 3 deletions autogalaxy/quantity/model/analysis.py
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Expand Up @@ -152,17 +152,17 @@ def save_attributes(self, paths: af.DirectoryPaths):
"""
paths.save_fits(
name="data",
hdu=self.dataset.data.hdu_for_output,
fits=self.dataset.data.hdu_for_output,
prefix="dataset",
)
paths.save_fits(
name="noise_map",
hdu=self.dataset.noise_map.hdu_for_output,
fits=self.dataset.noise_map.hdu_for_output,
prefix="dataset",
)
paths.save_fits(
name="mask",
hdu=self.dataset.mask.hdu_for_output,
fits=self.dataset.mask.hdu_for_output,
prefix="dataset",
)
paths.save_json(
Expand Down
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