def frequency(self, f):
"""
Find the most significant frequency of a (complex) time series, :math:`f(t)`,
by Fourier transforming the function convolved with a Hanning filter and
picking the most significant peak. This assumes the time series, `f`,
is aligned with / given at the times specified when constructing this
object. An internal function.
Parameters
----------
f : array_like
Complex time-series, :math:`q(t) + i p(t)`.
Returns
-------
freq : numeric
The strongest frequency in the specified complex time series, ``f``.
"""
if len(f) != self.n:
logger.warning(
"Truncating time series to match shape of time array ({0}) ({1})"
.format(len(f), self.n))
f = f[:self.n]
# take Fourier transform of input (complex) function f
# if HAS_PYFFTW:
# _f = pyfftw.n_byte_align_empty(f.size, 16, 'complex128')
# _f[:] = f
# fft_obj = pyfftw.builders.fft(f, overwrite_input=True,
# planner_effort='FFTW_ESTIMATE')
# fff = fft_obj() / np.sqrt(self.n)
# else:
t1 = time.time()
fff = fft(f) / np.sqrt(self.n)
logger.log(0, "Took {} seconds to FFT.".format(time.time() - t1))
# frequencies
omegas = 2 * np.pi * fftfreq(f.size, self.dt)
# wmax is just an initial guess for optimization
xyf = np.abs(fff)
wmax = xyf.argmax()
if np.allclose(xyf[wmax], 0):
# return early -- "this may be an axial or planar orbit"
logger.log(0, "Returning early - may be an axial or planar orbit?")
return 0.
# real and complex part of input time series
Re_f = f.real.copy()
Im_f = f.imag.copy()
# frequency associated with the peak index
omega0 = omegas[wmax]
freq = naff_frequency(omega0, self.tz, self.chi, Re_f, Im_f, self.T)
return freq
def frequency(self, f):
"""
Find the most significant frequency of a (complex) time series, :math:`f(t)`,
by Fourier transforming the function convolved with a Hanning filter and
picking the most significant peak. This assumes the time series, `f`,
is aligned with / given at the times specified when constructing this
object. An internal function.
Parameters
----------
f : array_like
Complex time-series, :math:`q(t) + i p(t)`.
Returns
-------
freq : numeric
The strongest frequency in the specified complex time series, ``f``.
"""
if len(f) != self.n:
logger.warning("Truncating time series to match shape of time array ({0}) ({1})"
.format(len(f), self.n))
f = f[:self.n]
# take Fourier transform of input (complex) function f
# if HAS_PYFFTW:
# _f = pyfftw.n_byte_align_empty(f.size, 16, 'complex128')
# _f[:] = f
# fft_obj = pyfftw.builders.fft(f, overwrite_input=True,
# planner_effort='FFTW_ESTIMATE')
# fff = fft_obj() / np.sqrt(self.n)
# else:
t1 = time.time()
fff = fft(f) / np.sqrt(self.n)
logger.log(0, "Took {} seconds to FFT.".format(time.time()-t1))
# frequencies
omegas = 2*np.pi*fftfreq(f.size, self.dt)
# wmax is just an initial guess for optimization
xyf = np.abs(fff)
wmax = xyf.argmax()
if np.allclose(xyf[wmax], 0):
# return early -- "this may be an axial or planar orbit"
logger.log(0, "Returning early - may be an axial or planar orbit?")
return 0.
# real and complex part of input time series
Re_f = f.real.copy()
Im_f = f.imag.copy()
# frequency associated with the peak index
omega0 = omegas[wmax]
freq = naff_frequency(omega0, self.tz, self.chi, Re_f, Im_f, self.T)
return freq
def n_modelfunc(self, pars=None, debug=False, **kwargs):
"""
Simple wrapper to deal with N independent peaks for a given spectral model
"""
if pars is None:
pars = self.parinfo
elif not isinstance(pars, ParinfoList):
try:
partemp = copy.copy(self.parinfo)
partemp._from_Parameters(pars)
pars = partemp
except AttributeError:
log.log(5, "Reading pars {0} as LMPar failed.".format(pars))
if debug > 1:
import pdb
pdb.set_trace()
if hasattr(pars, 'values'):
# important to treat as Dictionary, since lmfit params & parinfo both have .items
parnames, parvals = list(zip(*list(pars.items())))
parnames = [p.lower() for p in parnames]
parvals = [p.value for p in parvals]
else:
parvals = list(pars)
if np.any(np.isnan(parvals)):
raise ValueError("A parameter is NaN. Unless you gave a NaN "
"value directly, this is a bug and should be "
"reported. If you specified a NaN parameter, "
"don't do that.")
log.debug("pars to n_modelfunc: {0}, parvals:{1}".format(
pars, parvals))
def L(x):
v = np.zeros(len(x))
if self.vheight:
v += parvals[0]
# use len(pars) instead of self.npeaks because we want this to work
# independent of the current best fit
for jj in range(int((len(parvals) - self.vheight) / self.npars)):
lower_parind = jj * self.npars + self.vheight
upper_parind = (jj + 1) * self.npars + self.vheight
v += self.modelfunc(x, *parvals[lower_parind:upper_parind],
**kwargs)
return v
return L
def n_modelfunc(self, pars=None, debug=False, **kwargs):
"""
Simple wrapper to deal with N independent peaks for a given spectral model
"""
if pars is None:
pars = self.parinfo
elif not isinstance(pars, ParinfoList):
try:
partemp = copy.copy(self.parinfo)
partemp._from_Parameters(pars)
pars = partemp
except AttributeError:
log.log(5, "Reading pars {0} as LMPar failed.".format(pars))
if debug > 1:
import pdb; pdb.set_trace()
if hasattr(pars,'values'):
# important to treat as Dictionary, since lmfit params & parinfo both have .items
parnames,parvals = list(zip(*list(pars.items())))
parnames = [p.lower() for p in parnames]
parvals = [p.value for p in parvals]
else:
parvals = list(pars)
if np.any(np.isnan(parvals)):
raise ValueError("A parameter is NaN. Unless you gave a NaN "
"value directly, this is a bug and should be "
"reported. If you specified a NaN parameter, "
"don't do that.")
log.debug("pars to n_modelfunc: {0}, parvals:{1}".format(pars, parvals))
def L(x):
v = np.zeros(len(x))
if self.vheight:
v += parvals[0]
# use len(pars) instead of self.npeaks because we want this to work
# independent of the current best fit
for jj in range(int((len(parvals)-self.vheight)/self.npars)):
lower_parind = jj*self.npars+self.vheight
upper_parind = (jj+1)*self.npars+self.vheight
v += self.modelfunc(x, *parvals[lower_parind:upper_parind], **kwargs)
return v
return L
def _parse_staging_request_page(self, data_list_page):
"""
Parse pages like this one:
https://almascience.eso.org/rh/requests/anonymous/786572566
that include links to data sets that have been requested and staged
Parameters
----------
data_list_page : requests.Response object
"""
root = BeautifulSoup(data_list_page.content, 'html5lib')
# for link in root.findAll('a'):
# if 'script.sh' in link.text:
# download_script_url = urljoin(self.dataarchive_url,
# link['href'])
# if 'download_script_url' not in locals():
# raise RemoteServiceError("No download links were found.")
# download_script = self._request('GET', download_script_url,
# cache=False)
# download_script_target_urls = []
# for line in download_script.text.split('\n'):
# if line and line.split() and line.split()[0] == 'wget':
# download_script_target_urls.append(line.split()[1].strip('"'))
# if len(download_script_target_urls) == 0:
# raise RemoteServiceError("There was an error parsing the download"
# " script; it is empty. "
# "You can access the download script "
# "directly from this URL: "
# "{0}".format(download_script_url))
data_table = root.findAll('table', class_='list', id='report')[0]
columns = {'uid': [], 'URL': [], 'size': []}
for tr in data_table.findAll('tr'):
tds = tr.findAll('td')
# Cannot check class if it is not defined
cl = 'class' in tr.attrs
if (len(tds) > 1 and 'uid' in tds[0].text and
(cl and 'Level' in tr['class'][0])):
# New Style
text = tds[0].text.strip().split()
if text[0] in ('Asdm', 'Member'):
uid = text[-1]
elif len(tds) > 1 and 'uid' in tds[1].text:
# Old Style
uid = tds[1].text.strip()
elif cl and tr['class'] == 'Level_1':
raise ValueError("Heading was found when parsing the download "
"page but it was not parsed correctly")
if len(tds) > 3 and (cl and tr['class'][0] == 'fileRow'):
# New Style
size, unit = re.search('(-|[0-9\.]*)([A-Za-z]*)',
tds[2].text).groups()
href = tds[1].find('a')
if size == '':
# this is a header row
continue
authorized = ('access_authorized.png' in
tds[3].findChild('img')['src'])
if authorized:
columns['uid'].append(uid)
if href and 'href' in href.attrs:
columns['URL'].append(href.attrs['href'])
else:
columns['URL'].append('None_Found')
unit = (u.Unit(unit) if unit in ('GB', 'MB')
else u.Unit('kB') if 'kb' in unit.lower()
else 1)
try:
columns['size'].append(float(size) * u.Unit(unit))
except ValueError:
# size is probably a string?
columns['size'].append(-1 * u.byte)
log.log(level=5, msg="Found a new-style entry. "
"size={0} uid={1} url={2}"
.format(size, uid, columns['URL'][-1]))
else:
log.warn("Access to {0} is not authorized.".format(uid))
elif len(tds) > 3 and tds[2].find('a'):
# Old Style
href = tds[2].find('a')
size, unit = re.search('([0-9\.]*)([A-Za-z]*)',
tds[3].text).groups()
columns['uid'].append(uid)
columns['URL'].append(href.attrs['href'])
unit = (u.Unit(unit) if unit in ('GB', 'MB')
else u.Unit('kB') if 'kb' in unit.lower()
else 1)
columns['size'].append(float(size) * u.Unit(unit))
log.log(level=5, msg="Found an old-style entry. "
"size={0} uid={1} url={2}".format(size, uid,
columns['URL'][-1]))
columns['size'] = u.Quantity(columns['size'], u.Gbyte)
if len(columns['uid']) == 0:
raise RemoteServiceError(
"No valid UIDs were found in the staged data table. "
"Please include {0} in a bug report."
.format(self._staging_log['data_list_url']))
# if len(download_script_target_urls) != len(columns['URL']):
# log.warn("There was an error parsing the data staging page. "
# "The results from the page and the download script "
# "differ. You can access the download script directly "
# "from this URL: {0}".format(download_script_url))
# else:
# bad_urls = []
# for (rurl,url) in (zip(columns['URL'],
# download_script_target_urls)):
# if rurl == 'None_Found':
# url_uid = os.path.split(url)[-1]
# ind = np.where(np.array(columns['uid']) == url_uid)[0][0]
# columns['URL'][ind] = url
# elif rurl != url:
# bad_urls.append((rurl, url))
# if bad_urls:
# log.warn("There were mismatches between the parsed URLs "
# "from the staging page ({0}) and the download "
# "script ({1})."
# .format(self._staging_log['data_list_url'],
# download_script_url))
tbl = Table([Column(name=k, data=v) for k, v in iteritems(columns)])
return tbl
def _parse_staging_request_page(self, data_list_page):
"""
Parse pages like this one:
https://almascience.eso.org/rh/requests/anonymous/786572566
that include links to data sets that have been requested and staged
Parameters
----------
data_list_page : requests.Response object
"""
root = BeautifulSoup(data_list_page.content, 'html5lib')
data_table = root.findAll('table', class_='list', id='report')[0]
columns = {'uid': [], 'URL': [], 'size': []}
for tr in data_table.findAll('tr'):
tds = tr.findAll('td')
# Cannot check class if it is not defined
cl = 'class' in tr.attrs
if (len(tds) > 1 and 'uid' in tds[0].text
and (cl and 'Level' in tr['class'][0])):
# New Style
text = tds[0].text.strip().split()
if text[0] in ('Asdm', 'Member'):
uid = text[-1]
elif len(tds) > 1 and 'uid' in tds[1].text:
# Old Style
uid = tds[1].text.strip()
elif cl and tr['class'] == 'Level_1':
raise ValueError("Heading was found when parsing the download "
"page but it was not parsed correctly")
if len(tds) > 3 and (cl and tr['class'][0] == 'fileRow'):
# New Style
size, unit = re.search(r'(-|[0-9\.]*)([A-Za-z]*)',
tds[2].text).groups()
href = tds[1].find('a')
if size == '':
# this is a header row
continue
authorized = ('access_authorized.png'
in tds[3].findChild('img')['src'])
if authorized:
columns['uid'].append(uid)
if href and 'href' in href.attrs:
columns['URL'].append(href.attrs['href'])
else:
columns['URL'].append('None_Found')
unit = (u.Unit(unit) if unit in ('GB', 'MB') else
u.Unit('kB') if 'kb' in unit.lower() else 1)
try:
columns['size'].append(float(size) * u.Unit(unit))
except ValueError:
# size is probably a string?
columns['size'].append(-1 * u.byte)
log.log(level=5,
msg="Found a new-style entry. "
"size={0} uid={1} url={2}".format(
size, uid, columns['URL'][-1]))
else:
log.warning("Access to {0} is not authorized.".format(uid))
elif len(tds) > 3 and tds[2].find('a'):
# Old Style
href = tds[2].find('a')
size, unit = re.search(r'([0-9\.]*)([A-Za-z]*)',
tds[3].text).groups()
columns['uid'].append(uid)
columns['URL'].append(href.attrs['href'])
unit = (u.Unit(unit) if unit in ('GB', 'MB') else
u.Unit('kB') if 'kb' in unit.lower() else 1)
columns['size'].append(float(size) * u.Unit(unit))
log.log(level=5,
msg="Found an old-style entry. "
"size={0} uid={1} url={2}".format(
size, uid, columns['URL'][-1]))
columns['size'] = u.Quantity(columns['size'], u.Gbyte)
if len(columns['uid']) == 0:
raise RemoteServiceError(
"No valid UIDs were found in the staged data table. "
"Please include {0} in a bug report.".format(
self._staging_log['data_list_url']))
tbl = Table([Column(name=k, data=v) for k, v in iteritems(columns)])
return tbl
def _parse_staging_request_page(self, data_list_page):
"""
Parse pages like this one:
https://almascience.eso.org/rh/requests/anonymous/786572566
that include links to data sets that have been requested and staged
Parameters
----------
data_list_page : requests.Response object
"""
root = BeautifulSoup(data_list_page.content, 'html5lib')
data_table = root.findAll('table', class_='list', id='report')[0]
columns = {'uid': [], 'URL': [], 'size': []}
for tr in data_table.findAll('tr'):
tds = tr.findAll('td')
# Cannot check class if it is not defined
cl = 'class' in tr.attrs
if (len(tds) > 1 and 'uid' in tds[0].text and
(cl and 'Level' in tr['class'][0])):
# New Style
text = tds[0].text.strip().split()
if text[0] in ('Asdm', 'Member'):
uid = text[-1]
elif len(tds) > 1 and 'uid' in tds[1].text:
# Old Style
uid = tds[1].text.strip()
elif cl and tr['class'] == 'Level_1':
raise ValueError("Heading was found when parsing the download "
"page but it was not parsed correctly")
if len(tds) > 3 and (cl and tr['class'][0] == 'fileRow'):
# New Style
size, unit = re.search('(-|[0-9\.]*)([A-Za-z]*)',
tds[2].text).groups()
href = tds[1].find('a')
if size == '':
# this is a header row
continue
authorized = ('access_authorized.png' in
tds[3].findChild('img')['src'])
if authorized:
columns['uid'].append(uid)
if href and 'href' in href.attrs:
columns['URL'].append(href.attrs['href'])
else:
columns['URL'].append('None_Found')
unit = (u.Unit(unit) if unit in ('GB', 'MB')
else u.Unit('kB') if 'kb' in unit.lower()
else 1)
try:
columns['size'].append(float(size) * u.Unit(unit))
except ValueError:
# size is probably a string?
columns['size'].append(-1 * u.byte)
log.log(level=5, msg="Found a new-style entry. "
"size={0} uid={1} url={2}"
.format(size, uid, columns['URL'][-1]))
else:
log.warning("Access to {0} is not authorized.".format(uid))
elif len(tds) > 3 and tds[2].find('a'):
# Old Style
href = tds[2].find('a')
size, unit = re.search('([0-9\.]*)([A-Za-z]*)',
tds[3].text).groups()
columns['uid'].append(uid)
columns['URL'].append(href.attrs['href'])
unit = (u.Unit(unit) if unit in ('GB', 'MB')
else u.Unit('kB') if 'kb' in unit.lower()
else 1)
columns['size'].append(float(size) * u.Unit(unit))
log.log(level=5, msg="Found an old-style entry. "
"size={0} uid={1} url={2}".format(size, uid,
columns['URL'][-1]))
columns['size'] = u.Quantity(columns['size'], u.Gbyte)
if len(columns['uid']) == 0:
raise RemoteServiceError(
"No valid UIDs were found in the staged data table. "
"Please include {0} in a bug report."
.format(self._staging_log['data_list_url']))
tbl = Table([Column(name=k, data=v) for k, v in iteritems(columns)])
return tbl
def _parse_staging_request_page(self, data_list_page):
"""
Parse pages like this one:
https://almascience.eso.org/rh/requests/anonymous/786572566
that include links to data sets that have been requested and staged
Parameters
----------
data_list_page : requests.Response object
"""
root = BeautifulSoup(data_list_page.content, 'html5lib')
#for link in root.findAll('a'):
# if 'script.sh' in link.text:
# download_script_url = urljoin(self.dataarchive_url,
# link['href'])
#if 'download_script_url' not in locals():
# raise RemoteServiceError("No download links were found.")
#download_script = self._request('GET', download_script_url,
# cache=False)
#download_script_target_urls = []
#for line in download_script.text.split('\n'):
# if line and line.split() and line.split()[0] == 'wget':
# download_script_target_urls.append(line.split()[1].strip('"'))
#if len(download_script_target_urls) == 0:
# raise RemoteServiceError("There was an error parsing the download "
# "script; it is empty. "
# "You can access the download script "
# "directly from this URL: "
# "{0}".format(download_script_url))
data_table = root.findAll('table', class_='list', id='report')[0]
columns = {'uid':[], 'URL':[], 'size':[]}
for tr in data_table.findAll('tr'):
tds = tr.findAll('td')
# Cannot check class if it is not defined
cl = 'class' in tr.attrs
if len(tds) > 1 and 'uid' in tds[0].text and (cl and
'Level' in tr['class'][0]):
# New Style
text = tds[0].text.strip().split()
if text[0] in ('Asdm', 'Member'):
uid = text[-1]
elif len(tds) > 1 and 'uid' in tds[1].text:
# Old Style
uid = tds[1].text.strip()
elif cl and tr['class'] == 'Level_1':
raise ValueError("A heading was found when parsing the download page but "
"it was not parsed correctly")
if len(tds) > 3 and (cl and tr['class'][0] == 'fileRow'):
# New Style
size,unit = re.search('(-|[0-9\.]*)([A-Za-z]*)', tds[2].text).groups()
href = tds[1].find('a')
if size == '':
# this is a header row
continue
authorized = ('access_authorized.png' in tds[3].findChild('img')['src'])
if authorized:
columns['uid'].append(uid)
if href and 'href' in href.attrs:
columns['URL'].append(href.attrs['href'])
else:
columns['URL'].append('None_Found')
unit = (u.Unit(unit) if unit in ('GB','MB')
else u.Unit('kB') if 'kb' in unit.lower()
else 1)
try:
columns['size'].append(float(size)*u.Unit(unit))
except ValueError:
# size is probably a string?
columns['size'].append(-1*u.byte)
log.log(level=5, msg="Found a new-style entry. "
"size={0} uid={1} url={2}".format(size, uid,
columns['URL'][-1]))
else:
log.warn("Access to {0} is not authorized.".format(uid))
elif len(tds) > 3 and tds[2].find('a'):
# Old Style
href = tds[2].find('a')
size,unit = re.search('([0-9\.]*)([A-Za-z]*)', tds[3].text).groups()
columns['uid'].append(uid)
columns['URL'].append(href.attrs['href'])
unit = (u.Unit(unit) if unit in ('GB','MB')
else u.Unit('kB') if 'kb' in unit.lower()
else 1)
columns['size'].append(float(size)*u.Unit(unit))
log.log(level=5, msg="Found an old-style entry. "
"size={0} uid={1} url={2}".format(size, uid,
columns['URL'][-1]))
columns['size'] = u.Quantity(columns['size'], u.Gbyte)
if len(columns['uid']) == 0:
raise RemoteServiceError("No valid UIDs were found in the staged "
"data table. Please include {0} "
"in a bug report."
.format(self._staging_log['data_list_url']))
#if len(download_script_target_urls) != len(columns['URL']):
# log.warn("There was an error parsing the data staging page. "
# "The results from the page and the download script "
# "differ. You can access the download script directly "
# "from this URL: {0}".format(download_script_url))
#else:
# bad_urls = []
# for (rurl,url) in (zip(columns['URL'],
# download_script_target_urls)):
# if rurl == 'None_Found':
# url_uid = os.path.split(url)[-1]
# ind = np.where(np.array(columns['uid']) == url_uid)[0][0]
# columns['URL'][ind] = url
# elif rurl != url:
# bad_urls.append((rurl, url))
# if bad_urls:
# log.warn("There were mismatches between the parsed URLs "
# "from the staging page ({0}) and the download "
# "script ({1})."
# .format(self._staging_log['data_list_url'],
# download_script_url))
tbl = Table([Column(name=k, data=v) for k,v in iteritems(columns)])
return tbl
def _hducut(img_hdu, center_coord, cutout_size, correct_wcs=False, verbose=False):
"""
Takes an ImageHDU (image and associated metatdata in the fits format), as well as a center
coordinate and size and make a cutout of that image, which is returned as another ImageHDU,
including updated WCS information.
Parameters
----------
img_hdu : `~astropy.io.fits.hdu.image.ImageHDU`
The image and assciated metadata that is being cut out.
center_coord : `~astropy.coordinates.sky_coordinate.SkyCoord`
The coordinate to cut out around.
cutout_size : array
The size of the cutout as [nx,ny], where nx/ny can be integers (assumed to be pixels)
or `~astropy.Quantity` values, either pixels or angular quantities.
correct_wcs : bool
Default False. If true a new WCS will be created for the cutout that is tangent projected
and does not include distortions.
verbose : bool
Default False. If true intermediate information is printed.
Returns
-------
response : `~astropy.io.fits.hdu.image.ImageHDU`
The cutout image and associated metadata.
"""
hdu_header = fits.Header(img_hdu.header, copy=True)
# We are going to reroute the logging to a string stream temporarily so we can
# intercept any message from astropy, chiefly the "Inconsistent SIP distortion information"
# INFO message which will indicate that we need to remove existing SIP keywords
# from a WCS whose CTYPE does not include SIP. In this we are taking the CTYPE to be
# correct and adjusting the header keywords to match.
hdlrs = log.handlers
log.handlers = []
with log.log_to_list() as log_list:
img_wcs = wcs.WCS(hdu_header, relax=True)
for hd in hdlrs:
log.addHandler(hd)
no_sip = False
if (len(log_list) > 0):
if ("Inconsistent SIP distortion information" in log_list[0].msg):
# Remove sip coefficients
img_wcs.sip = None
no_sip = True
else: # Message(s) we didn't prepare for we want to go ahead and display
for log_rec in log_list:
log.log(log_rec.levelno, log_rec.msg, extra={"origin": log_rec.name})
img_data = img_hdu.data
if verbose:
print("Original image shape: {}".format(img_data.shape))
# Get cutout limits
cutout_lims = get_cutout_limits(img_wcs, center_coord, cutout_size)
if verbose:
print("xmin,xmax: {}".format(cutout_lims[0]))
print("ymin,ymax: {}".format(cutout_lims[1]))
# These limits are not guarenteed to be within the image footprint
xmin, xmax = cutout_lims[0]
ymin, ymax = cutout_lims[1]
ymax_img, xmax_img = img_data.shape
# Check the cutout is on the image
if (xmax <= 0) or (xmin >= xmax_img) or (ymax <= 0) or (ymin >= ymax_img):
raise InvalidQueryError("Cutout location is not in image footprint!")
# Adjust limits and figuring out the` padding
padding = np.zeros((2, 2), dtype=int)
if xmin < 0:
padding[1, 0] = -xmin
xmin = 0
if ymin < 0:
padding[0, 0] = -ymin
ymin = 0
if xmax > xmax_img:
padding[1, 1] = xmax - xmax_img
xmax = xmax_img
if ymax > ymax_img:
padding[0, 1] = ymax - ymax_img
ymax = ymax_img
img_cutout = img_hdu.data[ymin:ymax, xmin:xmax]
# Adding padding to the cutout so that it's the expected size
if padding.any(): # only do if we need to pad
img_cutout = np.pad(img_cutout, padding, 'constant', constant_values=np.nan)
if verbose:
print("Image cutout shape: {}".format(img_cutout.shape))
# Getting the cutout wcs
cutout_wcs = get_cutout_wcs(img_wcs, cutout_lims)
# Updating the header with the new wcs info
if no_sip:
hdu_header.update(cutout_wcs.to_header(relax=False))
else:
hdu_header.update(cutout_wcs.to_header(relax=True)) # relax arg is for sip distortions if they exist
# Naming the extension and preserving the original name
hdu_header["O_EXT_NM"] = (hdu_header.get("EXTNAME"), "Original extension name.")
hdu_header["EXTNAME"] = "CUTOUT"
# Moving the filename, if present, into the ORIG_FLE keyword
hdu_header["ORIG_FLE"] = (hdu_header.get("FILENAME"), "Original image filename.")
hdu_header.remove("FILENAME", ignore_missing=True)
hdu = fits.ImageHDU(header=hdu_header, data=img_cutout)
return hdu
