def make_data_cube(
detectid=None,
coords=None,
shotid=None,
pixscale=0.25 * u.arcsec,
imsize=30.0 * u.arcsec,
wave_range=[3470, 5540],
dwave=2.0,
dcont=50.0,
convolve_image=True,
ffsky=True,
subcont=False,
):
"""
Function to make a datacube from either a detectid or from a
coordinate/shotid combination.
Paramaters
----------
detectid: int
detectid from the continuum or lines catalog. Default is
None. Provide a coords/shotid combo if this isn't given
coords: SkyCoords object
coordinates to define the centre of the data cube
pixscale: astropy angle quantity
plate scale
imsize: astropy angle quantity
spatial length of cube (equal dims is only option)
wave_range: list
start and stop value for the wavelength range in Angstrom
dwave
step in wavelength range in Angstrom
convolve_image: bool
option to convolve image with shotid seeing
ffsky: bool
option to use full frame calibrated fibers. Default is
True.
subcont: bool
option to subtract continuum. Default is False. This
will measure the continuum 50AA below and above the
input wave_range
dcont
width in angstrom to measure the continuum. Default is to
measure 50 AA wide regions on either side of the line
Returns
-------
hdu: PrimaryHDU object
the data cube 3D array and associated 3d header
Units are '10^-17 erg cm-2 s-1 per spaxel'
Examples
--------
Can either pass in a detectid:
>>> detectid_obj=2101602788
>>> hdu = make_data_cube( detectid=detectid_obj)
>>> hdu.writeto( str(detectid_obj) + '.fits', overwrite=True)
or can put in an SkyCoord object:
>>> star_coords = SkyCoord(9.625181, -0.043587, unit='deg')
>>> hdu = make_data_cube( coords=star_coords[0], shotid=20171016108, dwave=2.0)
>>> hdu.writeto( 'star.fits', overwrite=True)
"""
global config, detecth5, surveyh5
if detectid is not None:
detectid_obj = detectid
det_info = detecth5.root.Detections.read_where(
'detectid == detectid_obj')[0]
shotid = det_info["shotid"]
coords = SkyCoord(det_info["ra"], det_info["dec"], unit="deg")
if coords is None or shotid is None:
print("Provide a detectid or both a coords and shotid")
E = Extract()
E.load_shot(shotid, fibers=False)
# get spatial dims:
ndim = int(imsize / pixscale)
center = int(ndim / 2)
# get wave dims:
nwave = int((wave_range[1] - wave_range[0]) / dwave + 1)
w = wcs.WCS(naxis=3)
w.wcs.crval = [coords.ra.deg, coords.dec.deg, wave_range[0]]
w.wcs.crpix = [center, center, 1]
w.wcs.ctype = ["RA---TAN", "DEC--TAN", "WAVE"]
w.wcs.cdelt = [-pixscale.to(u.deg).value, pixscale.to(u.deg).value, dwave]
rad = imsize.to(u.arcsec).value
info_result = E.get_fiberinfo_for_coord(coords, radius=rad, ffsky=False)
ifux, ifuy, xc, yc, ra, dec, data, error, mask = info_result
# get ifu center:
ifux_cen, ifuy_cen = E.convert_radec_to_ifux_ifuy(ifux, ifuy, ra, dec,
coords.ra.deg,
coords.dec.deg)
# get FWHM and PA
surveyh5 = tb.open_file(config.surveyh5, "r")
shotid_obj = shotid
pa = surveyh5.root.Survey.read_where("shotid == shotid_obj")["pa"][0]
if convolve_image:
fwhm = surveyh5.root.Survey.read_where(
"shotid == shotid_obj")["fwhm_virus"][0]
else:
fwhm = 1.8 # just a dummy variable as convolve_image=False
surveyh5.close()
# add in rotation
sys_rot = 1.55
rot = 360. - (90. + pa + sys_rot)
w.wcs.crota = [0, rot, 0]
# rrot = np.deg2rad(rot)
# w.wcs.pc = [[np.cos(rrot),
# np.sin(rrot),0],
# [-1.0*np.sin(rrot),
# np.cos(rrot),0], [0,0,0]]
im_cube = np.zeros((nwave, ndim, ndim))
wave_i = wave_range[0]
i = 0
while wave_i <= wave_range[1]:
try:
im_src = E.make_narrowband_image(
ifux_cen,
ifuy_cen,
ifux,
ifuy,
data,
mask,
scale=pixscale.to(u.arcsec).value,
wrange=[wave_i, wave_i + dwave],
nchunks=1,
seeing_fac=fwhm,
convolve_image=convolve_image,
boxsize=imsize.to(u.arcsec).value,
)
im_slice = im_src[0]
if subcont:
zarray_blue = E.make_narrowband_image(
ifux_cen,
ifuy_cen,
ifux,
ifuy,
data,
mask,
seeing_fac=fwhm,
scale=pixscale.to(u.arcsec).value,
boxsize=imsize.to(u.arcsec).value,
nchunks=2,
wrange=[wave_i - dcont, wave_i],
convolve_image=convolve_image,
)
zarray_red = E.make_narrowband_image(
ifux_cen,
ifuy_cen,
ifux,
ifuy,
data,
mask,
seeing_fac=fwhm,
nchunks=2,
scale=pixscale.to(u.arcsec).value,
boxsize=imsize.to(u.arcsec).value,
wrange=[wave_i + dwave, wave_i + dwave + dcont],
convolve_image=convolve_image,
)
im_cont = (zarray_blue[0] + zarray_red[0]) / (2 * dcont)
im_slice = im_src[0] - dwave * im_cont
im_cube[i, :, :] = im_slice
except Exception:
im_cube[i, :, :] = np.zeros((ndim, ndim))
wave_i += dwave
i += 1
hdu = fits.PrimaryHDU(im_cube, header=w.to_header())
E.close()
return hdu
def make_narrowband_image(
detectid=None,
coords=None,
shotid=None,
pixscale=0.25 * u.arcsec,
imsize=30.0 * u.arcsec,
wave_range=None,
convolve_image=True,
ffsky=True,
subcont=False,
dcont=50.,
include_error=False,
):
"""
Function to make narrowband image from either a detectid or from a
coordinate/shotid combination.
Paramaters
----------
detectid: int
detectid from the continuum or lines catalog. Default is
None. Provide a coords/shotid combo if this isn't given
coords: SkyCoords object
coordinates to define the centre of the data cube
pixscale: astropy angle quantity
plate scale
imsize: astropy angle quantity
image size
wave_range: list or None
start and stop value for the wavelength range in Angstrom.
If not given, the detectid linewidth is used
convolve_image: bool
option to convolve image with shotid seeing
ffsky: bool
option to use full frame calibrated fibers. Default is
True.
subcont: bool
option to subtract continuum. Default is False. This
will measure the continuum 50AA below and above the
input wave_range
dcont
width in angstrom to measure the continuum. Default is to
measure 50 AA wide regions on either side of the line
include_error bool
option to include error array
Returns
-------
hdu: PrimaryHDU object
the 2D summed data array and associated 2d header
Units are '10^-17 erg cm-2 s-1'
If include_error=True will include addiional hdu
Examples
--------
For a specific detectid:
>>> hdu = make_narrowband_image(detectid=2101046271)
For a SkyCoords object. You must provide shotid and
wavelength range
>>> coords = SkyCoord(188.79312, 50.855747, unit='deg')
>>> wave_obj = 4235.84 #in Angstrom
>>> hdu = make_narrowband_image(coords=coords,
shotid=20190524021,
wave_range=[wave_obj-10, wave_obj+10])
"""
global config, detecth5, surveyh5
if detectid is not None:
detectid_obj = detectid
det_info = detecth5.root.Detections.read_where(
'detectid == detectid_obj')[0]
shotid_obj = det_info["shotid"]
wave_obj = det_info["wave"]
linewidth = det_info["linewidth"]
wave_range = [wave_obj - 2.0 * linewidth, wave_obj + 2.0 * linewidth]
coords = SkyCoord(det_info["ra"], det_info["dec"], unit="deg")
elif coords is not None:
if shotid is not None:
shotid_obj = shotid
else:
print("Provide a shotid")
if wave_range is None:
print("Provide a wavelength range to collapse. \
Example wave_range=[4500,4540]")
else:
print("Provide a detectid or both a coords and shotid")
fwhm = surveyh5.root.Survey.read_where(
"shotid == shotid_obj")["fwhm_virus"][0]
pa = surveyh5.root.Survey.read_where("shotid == shotid_obj")["pa"][0]
E = Extract()
E.load_shot(shotid_obj, fibers=False)
# get spatial dims:
ndim = int(imsize / pixscale)
center = int(ndim / 2)
rad = imsize.to(u.arcsec).value # convert to arcsec value, not quantity
info_result = E.get_fiberinfo_for_coord(coords, radius=rad, ffsky=ffsky)
ifux, ifuy, xc, yc, ra, dec, data, error, mask = info_result
# get ifu center:
ifux_cen, ifuy_cen = E.convert_radec_to_ifux_ifuy(ifux, ifuy, ra, dec,
coords.ra.deg,
coords.dec.deg)
if include_error:
zarray = E.make_narrowband_image(
ifux_cen,
ifuy_cen,
ifux,
ifuy,
data,
mask,
error=error,
seeing_fac=fwhm,
scale=pixscale.to(u.arcsec).value,
boxsize=imsize.to(u.arcsec).value,
wrange=wave_range,
convolve_image=convolve_image,
)
imslice = zarray[0]
imerror = zarray[1]
else:
zarray = E.make_narrowband_image(
ifux_cen,
ifuy_cen,
ifux,
ifuy,
data,
mask,
seeing_fac=fwhm,
scale=pixscale.to(u.arcsec).value,
boxsize=imsize.to(u.arcsec).value,
wrange=wave_range,
convolve_image=convolve_image,
)
imslice = zarray[0]
if subcont:
zarray_blue = E.make_narrowband_image(
ifux_cen,
ifuy_cen,
ifux,
ifuy,
data,
mask,
seeing_fac=fwhm,
scale=pixscale.to(u.arcsec).value,
boxsize=imsize.to(u.arcsec).value,
wrange=[wave_range[0] - dcont - 10, wave_range[0] - 10],
convolve_image=convolve_image,
)
zarray_red = E.make_narrowband_image(
ifux_cen,
ifuy_cen,
ifux,
ifuy,
data,
mask,
seeing_fac=fwhm,
scale=pixscale.to(u.arcsec).value,
boxsize=imsize.to(u.arcsec).value,
wrange=[wave_range[1] + 10, wave_range[1] + dcont + 10],
convolve_image=convolve_image,
)
dwave = wave_range[1] - wave_range[0]
im_cont = (zarray_blue[0] + zarray_red[0]) / (2 * dcont)
imslice = zarray[0] - dwave * im_cont
w = wcs.WCS(naxis=2)
imsize = imsize.to(u.arcsec).value
w.wcs.crval = [coords.ra.deg, coords.dec.deg]
w.wcs.crpix = [center, center]
w.wcs.ctype = ["RA---TAN", "DEC--TAN"]
w.wcs.cdelt = [-pixscale.to(u.deg).value, pixscale.to(u.deg).value]
# get rotation:
sys_rot = 1.55
rot = 360. - (90. + pa + sys_rot)
rrot = np.deg2rad(rot)
# w.wcs.crota = [ 0, rot]
w.wcs.pc = [[np.cos(rrot), np.sin(rrot)],
[-1.0 * np.sin(rrot), np.cos(rrot)]]
hdu = fits.PrimaryHDU(imslice, header=w.to_header())
E.close()
if include_error:
hdu_error = fits.ImageHDU(imerror, header=w.to_header())
hdu_x = fits.ImageHDU(zarray[2], header=w.to_header())
hdu_y = fits.ImageHDU(zarray[3], header=w.to_header())
return fits.HDUList([hdu, hdu_error, hdu_x, hdu_y])
else:
return hdu
