def test_fits_cosmo():
ds = load(etc)
fid = FITSProjection(ds, "z", ["density"])
assert fid.wcs.wcs.cunit[0] == "kpc"
assert fid.wcs.wcs.cunit[1] == "kpc"
assert ds.hubble_constant == fid.hubble_constant
assert ds.current_redshift == fid.current_redshift
assert fid["density"].header["HUBBLE"] == ds.hubble_constant
assert fid["density"].header["REDSHIFT"] == ds.current_redshift
fid.close()
(list(label.values())[0], ds.current_time.in_units('Myr'),
nu.v, nu.units),
'CRVAL3':
int(nu.in_units('Hz').v)
})
fits_image[field].header.update(header_dict)
fits_image[field].header.update(wcs_header)
fitsfname = synchrotron_fits_filename(ds, dir, ptype, proj_axis,
mock_observation)
fits_image.writeto(fitsfname, clobber=True)
# End of if mock_observation
# Use stock yt FITSProjection and FITSOffAxisProjection
if proj_axis in ['x', 'y', 'z']:
fits_image = FITSProjection(ds_sync,
proj_axis,
fields,
center=[0, 0, 0],
width=width,
image_res=res)
else:
fits_image = FITSOffAxisProjection(ds_sync,
proj_axis,
fields,
center=[0, 0, 0],
north_vector=[1, 0, 0],
width=width,
image_res=res)
fitsfname = synchrotron_fits_filename(ds, dir, ptype, proj_axis)
fits_image.writeto(fitsfname, clobber=True)
def test_fits_image():
curdir = os.getcwd()
tmpdir = tempfile.mkdtemp()
os.chdir(tmpdir)
fields = ("density", "temperature")
units = (
"g/cm**3",
"K",
)
ds = fake_random_ds(64, fields=fields, units=units, nprocs=16, length_unit=100.0)
prj = ds.proj("density", 2)
prj_frb = prj.to_frb((0.5, "unitary"), 128)
fid1 = prj_frb.to_fits_data(
fields=[("gas", "density"), ("gas", "temperature")], length_unit="cm"
)
fits_prj = FITSProjection(
ds,
"z",
[ds.fields.gas.density, "temperature"],
image_res=128,
width=(0.5, "unitary"),
)
assert_equal(fid1["density"].data, fits_prj["density"].data)
assert_equal(fid1["temperature"].data, fits_prj["temperature"].data)
fid1.writeto("fid1.fits", overwrite=True)
new_fid1 = FITSImageData.from_file("fid1.fits")
assert_equal(fid1["density"].data, new_fid1["density"].data)
assert_equal(fid1["temperature"].data, new_fid1["temperature"].data)
assert_equal(fid1.length_unit, new_fid1.length_unit)
assert_equal(fid1.time_unit, new_fid1.time_unit)
assert_equal(fid1.mass_unit, new_fid1.mass_unit)
assert_equal(fid1.velocity_unit, new_fid1.velocity_unit)
assert_equal(fid1.magnetic_unit, new_fid1.magnetic_unit)
assert_equal(fid1.current_time, new_fid1.current_time)
ds2 = load("fid1.fits")
ds2.index
assert ("fits", "density") in ds2.field_list
assert ("fits", "temperature") in ds2.field_list
dw_cm = ds2.domain_width.in_units("cm")
assert dw_cm[0].v == 50.0
assert dw_cm[1].v == 50.0
slc = ds.slice(2, 0.5)
slc_frb = slc.to_frb((0.5, "unitary"), 128)
fid2 = slc_frb.to_fits_data(
fields=[("gas", "density"), ("gas", "temperature")], length_unit="cm"
)
fits_slc = FITSSlice(
ds,
"z",
[("gas", "density"), ("gas", "temperature")],
image_res=128,
width=(0.5, "unitary"),
)
assert_equal(fid2["density"].data, fits_slc["density"].data)
assert_equal(fid2["temperature"].data, fits_slc["temperature"].data)
dens_img = fid2.pop("density")
temp_img = fid2.pop("temperature")
combined_fid = FITSImageData.from_images([dens_img, temp_img])
assert_equal(combined_fid.length_unit, dens_img.length_unit)
assert_equal(combined_fid.time_unit, dens_img.time_unit)
assert_equal(combined_fid.mass_unit, dens_img.mass_unit)
assert_equal(combined_fid.velocity_unit, dens_img.velocity_unit)
assert_equal(combined_fid.magnetic_unit, dens_img.magnetic_unit)
assert_equal(combined_fid.current_time, dens_img.current_time)
cut = ds.cutting([0.1, 0.2, -0.9], [0.5, 0.42, 0.6])
cut_frb = cut.to_frb((0.5, "unitary"), 128)
fid3 = cut_frb.to_fits_data(
fields=[("gas", "density"), ds.fields.gas.temperature], length_unit="cm"
)
fits_cut = FITSOffAxisSlice(
ds,
[0.1, 0.2, -0.9],
["density", "temperature"],
image_res=128,
center=[0.5, 0.42, 0.6],
width=(0.5, "unitary"),
)
assert_equal(fid3["density"].data, fits_cut["density"].data)
assert_equal(fid3["temperature"].data, fits_cut["temperature"].data)
fid3.create_sky_wcs([30.0, 45.0], (1.0, "arcsec/kpc"))
fid3.writeto("fid3.fits", overwrite=True)
new_fid3 = FITSImageData.from_file("fid3.fits")
assert_same_wcs(fid3.wcs, new_fid3.wcs)
assert new_fid3.wcs.wcs.cunit[0] == "deg"
assert new_fid3.wcs.wcs.cunit[1] == "deg"
assert new_fid3.wcs.wcs.ctype[0] == "RA---TAN"
assert new_fid3.wcs.wcs.ctype[1] == "DEC--TAN"
buf = off_axis_projection(
ds, ds.domain_center, [0.1, 0.2, -0.9], 0.5, 128, "density"
).swapaxes(0, 1)
fid4 = FITSImageData(buf, fields="density", width=100.0)
fits_oap = FITSOffAxisProjection(
ds,
[0.1, 0.2, -0.9],
"density",
width=(0.5, "unitary"),
image_res=128,
depth=(0.5, "unitary"),
)
assert_equal(fid4["density"].data, fits_oap["density"].data)
fid4.create_sky_wcs([30.0, 45.0], (1.0, "arcsec/kpc"), replace_old_wcs=False)
assert fid4.wcs.wcs.cunit[0] == "cm"
assert fid4.wcs.wcs.cunit[1] == "cm"
assert fid4.wcs.wcs.ctype[0] == "linear"
assert fid4.wcs.wcs.ctype[1] == "linear"
assert fid4.wcsa.wcs.cunit[0] == "deg"
assert fid4.wcsa.wcs.cunit[1] == "deg"
assert fid4.wcsa.wcs.ctype[0] == "RA---TAN"
assert fid4.wcsa.wcs.ctype[1] == "DEC--TAN"
cvg = ds.covering_grid(
ds.index.max_level,
[0.25, 0.25, 0.25],
[32, 32, 32],
fields=["density", "temperature"],
)
fid5 = cvg.to_fits_data(fields=["density", "temperature"])
assert fid5.dimensionality == 3
fid5.update_header("density", "time", 0.1)
fid5.update_header("all", "units", "cgs")
assert fid5["density"].header["time"] == 0.1
assert fid5["temperature"].header["units"] == "cgs"
assert fid5["density"].header["units"] == "cgs"
fid6 = FITSImageData.from_images(fid5)
fid5.change_image_name("density", "mass_per_volume")
assert fid5["mass_per_volume"].name == "mass_per_volume"
assert fid5["mass_per_volume"].header["BTYPE"] == "mass_per_volume"
assert "mass_per_volume" in fid5.fields
assert "mass_per_volume" in fid5.field_units
assert "density" not in fid5.fields
assert "density" not in fid5.field_units
assert "density" in fid6.fields
assert_equal(fid6["density"].data, fid5["mass_per_volume"].data)
fid7 = FITSImageData.from_images(fid4)
fid7.convolve("density", (3.0, "cm"))
sigma = 3.0 / fid7.wcs.wcs.cdelt[0]
kernel = _astropy.conv.Gaussian2DKernel(x_stddev=sigma)
data_conv = _astropy.conv.convolve(fid4["density"].data.d, kernel)
assert_allclose(data_conv, fid7["density"].data.d)
# We need to manually close all the file descriptors so
# that windows can delete the folder that contains them.
ds2.close()
for fid in (fid1, fid2, fid3, fid4, fid5, fid6, fid7, new_fid1, new_fid3):
fid.close()
os.chdir(curdir)
shutil.rmtree(tmpdir)
def test_fits_image():
tmpdir = tempfile.mkdtemp()
curdir = os.getcwd()
os.chdir(tmpdir)
fields = ("density", "temperature")
units = (
'g/cm**3',
'K',
)
ds = fake_random_ds(64,
fields=fields,
units=units,
nprocs=16,
length_unit=100.0)
prj = ds.proj("density", 2)
prj_frb = prj.to_frb((0.5, "unitary"), 128)
fid1 = FITSImageData(prj_frb,
fields=["density", "temperature"],
units="cm")
fits_prj = FITSProjection(ds,
"z", ["density", "temperature"],
image_res=128,
width=(0.5, "unitary"))
assert_equal(fid1.get_data("density"), fits_prj.get_data("density"))
assert_equal(fid1.get_data("temperature"),
fits_prj.get_data("temperature"))
fid1.writeto("fid1.fits", clobber=True)
new_fid1 = FITSImageData.from_file("fid1.fits")
assert_equal(fid1.get_data("density"), new_fid1.get_data("density"))
assert_equal(fid1.get_data("temperature"),
new_fid1.get_data("temperature"))
ds2 = load("fid1.fits")
ds2.index
assert ("fits", "density") in ds2.field_list
assert ("fits", "temperature") in ds2.field_list
dw_cm = ds2.domain_width.in_units("cm")
assert dw_cm[0].v == 50.
assert dw_cm[1].v == 50.
slc = ds.slice(2, 0.5)
slc_frb = slc.to_frb((0.5, "unitary"), 128)
fid2 = FITSImageData(slc_frb,
fields=["density", "temperature"],
units="cm")
fits_slc = FITSSlice(ds,
"z", ["density", "temperature"],
image_res=128,
width=(0.5, "unitary"))
assert_equal(fid2.get_data("density"), fits_slc.get_data("density"))
assert_equal(fid2.get_data("temperature"),
fits_slc.get_data("temperature"))
dens_img = fid2.pop("density")
temp_img = fid2.pop("temperature")
# This already has some assertions in it, so we don't need to do anything
# with it other than just make one
FITSImageData.from_images([dens_img, temp_img])
cut = ds.cutting([0.1, 0.2, -0.9], [0.5, 0.42, 0.6])
cut_frb = cut.to_frb((0.5, "unitary"), 128)
fid3 = FITSImageData(cut_frb,
fields=["density", "temperature"],
units="cm")
fits_cut = FITSOffAxisSlice(ds, [0.1, 0.2, -0.9],
["density", "temperature"],
image_res=128,
center=[0.5, 0.42, 0.6],
width=(0.5, "unitary"))
assert_equal(fid3.get_data("density"), fits_cut.get_data("density"))
assert_equal(fid3.get_data("temperature"),
fits_cut.get_data("temperature"))
fid3.create_sky_wcs([30., 45.], (1.0, "arcsec/kpc"))
fid3.writeto("fid3.fits", clobber=True)
new_fid3 = FITSImageData.from_file("fid3.fits")
assert_same_wcs(fid3.wcs, new_fid3.wcs)
assert new_fid3.wcs.wcs.cunit[0] == "deg"
assert new_fid3.wcs.wcs.cunit[1] == "deg"
assert new_fid3.wcs.wcs.ctype[0] == "RA---TAN"
assert new_fid3.wcs.wcs.ctype[1] == "DEC--TAN"
buf = off_axis_projection(ds, ds.domain_center, [0.1, 0.2, -0.9], 0.5, 128,
"density").swapaxes(0, 1)
fid4 = FITSImageData(buf, fields="density", width=100.0)
fits_oap = FITSOffAxisProjection(ds, [0.1, 0.2, -0.9],
"density",
width=(0.5, "unitary"),
image_res=128,
depth_res=128,
depth=(0.5, "unitary"))
assert_equal(fid4.get_data("density"), fits_oap.get_data("density"))
fid4.create_sky_wcs([30., 45.], (1.0, "arcsec/kpc"), replace_old_wcs=False)
assert fid4.wcs.wcs.cunit[0] == "cm"
assert fid4.wcs.wcs.cunit[1] == "cm"
assert fid4.wcs.wcs.ctype[0] == "linear"
assert fid4.wcs.wcs.ctype[1] == "linear"
assert fid4.wcsa.wcs.cunit[0] == "deg"
assert fid4.wcsa.wcs.cunit[1] == "deg"
assert fid4.wcsa.wcs.ctype[0] == "RA---TAN"
assert fid4.wcsa.wcs.ctype[1] == "DEC--TAN"
cvg = ds.covering_grid(ds.index.max_level, [0.25, 0.25, 0.25],
[32, 32, 32],
fields=["density", "temperature"])
fid5 = FITSImageData(cvg, fields=["density", "temperature"])
assert fid5.dimensionality == 3
fid5.update_header("density", "time", 0.1)
fid5.update_header("all", "units", "cgs")
assert fid5["density"].header["time"] == 0.1
assert fid5["temperature"].header["units"] == "cgs"
assert fid5["density"].header["units"] == "cgs"
os.chdir(curdir)
shutil.rmtree(tmpdir)