def write_fits(self, filename, clobber=False, length_unit=None, sky_scale=None, sky_center=None): r""" Write the PPVCube to a FITS file. Parameters ---------- filename : string The name of the file to write to. clobber : boolean, optional Whether to overwrite a file with the same name that already exists. Default False. length_unit : string, optional The units to convert the coordinates to in the file. sky_scale : tuple, optional Conversion between an angle unit and a length unit, if sky coordinates are desired, e.g. (1.0, "arcsec/kpc") sky_center : tuple, optional The (RA, Dec) coordinate in degrees of the central pixel. Must be specified with *sky_scale*. Examples -------- >>> cube.write_fits("my_cube.fits", clobber=False, ... sky_scale=(1.0,"arcsec/kpc"), sky_center=(30.,45.)) """ vunit = fits_info[self.axis_type][0] vtype = fits_info[self.axis_type][1] v_center = 0.5 * (self.vbins[0] + self.vbins[-1]).in_units(vunit).value if length_unit is None: units = str(self.ds.get_smallest_appropriate_unit(self.width)) else: units = length_unit units = sanitize_fits_unit(units) dx = self.width.in_units(units).v / self.nx dy = self.width.in_units(units).v / self.ny dv = self.dv.in_units(vunit).v w = _astropy.pywcs.WCS(naxis=3) w.wcs.crpix = [ 0.5 * (self.nx + 1), 0.5 * (self.ny + 1), 0.5 * (self.nv + 1) ] w.wcs.cdelt = [dx, dy, dv] w.wcs.crval = [0.0, 0.0, v_center] w.wcs.cunit = [units, units, vunit] w.wcs.ctype = ["LINEAR", "LINEAR", vtype] fib = FITSImageData(self.data.transpose(), fields=self.field, wcs=w) fib.update_all_headers("bunit", re.sub('()', '', str(self.proj_units))) fib.update_all_headers("btype", self.field) if sky_scale is not None and sky_center is not None: fib.create_sky_wcs(sky_center, sky_scale) fib.writeto(filename, clobber=clobber)
def write_fits(self, filename, sky_scale=None, sky_center=None, overwrite=True, **kwargs): r""" Export images to a FITS file. Writes the SZ distortion in all specified frequencies as well as the mass-weighted temperature and the optical depth. Distance units are in kpc, unless *sky_center* and *scale* are specified. Parameters ---------- filename : string The name of the FITS file to be written. sky_scale : tuple Conversion between an angle unit and a length unit, if sky coordinates are desired, e.g. (1.0, "arcsec/kpc") sky_center : tuple, optional The (RA, Dec) coordinate in degrees of the central pixel. Must be specified with *sky_scale*. overwrite : boolean, optional If the file already exists, do we overwrite? Additional keyword arguments are passed to :meth:`~astropy.io.fits.HDUList.writeto`. Examples -------- >>> # This example just writes out a FITS file with kpc coords >>> szprj.write_fits("SZbullet.fits", overwrite=False) >>> # This example uses sky coords >>> sky_scale = (1., "arcsec/kpc") # One arcsec per kpc >>> sky_center = (30., 45., "deg") >>> szprj.write_fits("SZbullet.fits", sky_center=sky_center, sky_scale=sky_scale) """ from yt.visualization.fits_image import FITSImageData dx = self.dx.in_units("kpc") dy = dx w = _astropy.pywcs.WCS(naxis=2) w.wcs.crpix = [0.5 * (self.nx + 1)] * 2 w.wcs.cdelt = [dx.v, dy.v] w.wcs.crval = [0.0, 0.0] w.wcs.cunit = ["kpc"] * 2 w.wcs.ctype = ["LINEAR"] * 2 fib = FITSImageData(self.data, fields=self.data.keys(), wcs=w) if sky_scale is not None and sky_center is not None: fib.create_sky_wcs(sky_center, sky_scale) fib.writeto(filename, overwrite=overwrite, **kwargs)
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)