def create_fitsheader(naxis=None,
dtype=None,
fromdata=None,
extname=None,
crval=(0., 0.),
crpix=None,
ctype=('RA---TAN', 'DEC--TAN'),
cunit='deg',
cd=None,
cdelt=None,
pa=None,
equinox=2000.):
"""
Helper to create a FITS header.
Parameters
----------
naxis : array, optional
(NAXIS1,NAXIS2,...) tuple, which specifies the data dimensions.
dtype : data-type, optional
Desired data type for the data stored in the FITS file
fromdata : array_like, optional
An array from which the dimensions and typewill be extracted. Note
that following the FITS convention, the dimension along X is the
second value of the array shape and that the dimension along the
Y axis is the first one.
extname : None or string
if a string is specified ('' can be used), the returned header
type will be an Image HDU (otherwise a Primary HDU).
crval : 2 element array, optional
Reference pixel values (FITS convention).
crpix : 2 element array, optional
Reference pixel (FITS convention).
ctype : 2 element string array, optional
Projection types.
cunit : string or 2 element string array
Units of the CD matrix (default is degrees/pixel).
cd : 2 x 2 array
FITS parameters
CD1_1 CD1_2
CD2_1 CD2_2
cdelt : float or 2 element array
Physical increment at the reference pixel.
pa : float
Position angle of the Y=AXIS2 axis (=-CROTA2).
equinox : float
Reference equinox
Examples
--------
>>> map = Map.ones((10,100), unit='Jy/pixel')
>>> map.header = create_fitsheader(naxis=(100,10), cd=[[-1,0],[0,1]])
>>> map.header = create_fitsheader(fromdata=map)
"""
if fromdata is None:
if naxis is None:
raise ValueError("Keywords 'naxis' or 'fromdata' must be specifie" \
'd.')
if isinstance(naxis, np.ndarray) and naxis.size > 8:
raise ValueError('First argument is naxis=(NAXIS1,NAXIS2,...)')
if dtype is not None:
typename = dtype.name
else:
typename = 'float64'
else:
array = fromdata
if not isinstance(array, np.ndarray):
raise TypeError('The input is not an ndarray.')
if naxis is None:
naxis = tuple(reversed(array.shape))
if dtype is not None:
array = arrays.astype(dtype)
if array.dtype.itemsize == 1:
typename = 'uint8'
elif array.dtype.names is not None:
typename = None
else:
typename = array.dtype.name
if type(naxis) not in (list, tuple):
naxis = (naxis, )
numaxis = len(naxis)
if extname is None:
card = pyfits.createCard('simple', True)
else:
card = pyfits.createCard('xtension', 'IMAGE', 'Image extension')
header = pyfits.Header([card])
if typename is not None:
header.update('bitpix', pyfits.PrimaryHDU.ImgCode[typename],
'array data type')
header.update('naxis', numaxis, 'number of array dimensions')
for dim in range(numaxis):
header.update('naxis' + str(dim + 1), naxis[dim])
if extname is None:
header.update('extend', True)
else:
header.update('pcount', 0, 'number of parameters')
header.update('gcount', 1, 'number of groups')
header.update('extname', extname)
if cd is not None:
cd = np.asarray(cd, dtype=np.float64)
if cd.shape != (2, 2):
raise ValueError('The CD matrix is not a 2x2 matrix.')
else:
if cdelt is None:
return header
if _my_isscalar(cdelt):
cdelt = (-cdelt, cdelt)
if pa is None:
pa = 0.
theta = np.deg2rad(-pa)
cd = np.diag(cdelt).dot(
np.array([[np.cos(theta), np.sin(theta)],
[-np.sin(theta), np.cos(theta)]]))
crval = np.asarray(crval, dtype=np.float64)
if crval.size != 2:
raise ValueError('CRVAL does not have two elements.')
if crpix is None:
crpix = (np.array(naxis) + 1) / 2.
else:
crpix = np.asarray(crpix, dtype=np.float64)
if crpix.size != 2:
raise ValueError('CRPIX does not have two elements.')
ctype = np.asarray(ctype, dtype=np.string_)
if ctype.size != 2:
raise ValueError('CTYPE does not have two elements.')
if _my_isscalar(cunit):
cunit = (cunit, cunit)
cunit = np.asarray(cunit, dtype=np.string_)
if cunit.size != 2:
raise ValueError('CUNIT does not have two elements.')
header.update('crval1', crval[0])
header.update('crval2', crval[1])
header.update('crpix1', crpix[0])
header.update('crpix2', crpix[1])
header.update('cd1_1', cd[0, 0])
header.update('cd2_1', cd[1, 0])
header.update('cd1_2', cd[0, 1])
header.update('cd2_2', cd[1, 1])
header.update('ctype1', ctype[0])
header.update('ctype2', ctype[1])
header.update('cunit1', cunit[0])
header.update('cunit2', cunit[1])
header.update('equinox', 2000.)
return header
#!/usr/bin/env python
import time
import pyfits
from AllSky340 import AllSky340
cam = AllSky340(port="/dev/tty.usbserial-A700dzlT", baudrate=460800, timeout=1)
cam.log_info("Testing camera communication.")
p = cam.ping()
if p:
exp = 0.1
cam.log_info("Taking %f sec test image." % exp)
imag = cam.getImage(exp, light=True)
now = time.localtime()
date = time.strftime("%Y/%m/%d")
sast = time.strftime("%H:%M:%S")
# set up and create the FITS file
cards = []
cards.append(pyfits.createCard("DATEOBS", date, "Date of observation"))
cards.append(
pyfits.createCard("TIMEOBS", sast, "Time of observation (SAST)"))
cards.append(pyfits.createCard("EXPTIME", exp, "Exposure time (s)"))
header = pyfits.Header(cards=cards)
pyfits.writeto("test.fits", imag, header=header, clobber=True)
#!/usr/bin/env python
import time
import pyfits
from AllSky340 import AllSky340
cam = AllSky340(port="/dev/tty.usbserial-A700dzlT", baudrate=460800, timeout=1)
cam.log_info("Testing camera communication.")
p = cam.ping()
if p:
exp = 0.1
cam.log_info("Taking %f sec test image." % exp)
imag = cam.getImage(exp, light=True)
now = time.localtime()
date = time.strftime("%Y/%m/%d")
sast = time.strftime("%H:%M:%S")
# set up and create the FITS file
cards = []
cards.append(pyfits.createCard("DATEOBS", date, "Date of observation"))
cards.append(pyfits.createCard("TIMEOBS", sast, "Time of observation (SAST)"))
cards.append(pyfits.createCard("EXPTIME", exp, "Exposure time (s)"))
header = pyfits.Header(cards=cards)
pyfits.writeto("test.fits", imag, header=header, clobber=True)
def create_fitsheader(naxis=None, dtype=None, fromdata=None, extname=None,
crval=(0.,0.), crpix=None, ctype=('RA---TAN','DEC--TAN'),
cunit='deg', cd=None, cdelt=None, pa=None, equinox=2000.):
"""
Helper to create a FITS header.
Parameters
----------
naxis : array, optional
(NAXIS1,NAXIS2,...) tuple, which specifies the data dimensions.
dtype : data-type, optional
Desired data type for the data stored in the FITS file
fromdata : array_like, optional
An array from which the dimensions and typewill be extracted. Note
that following the FITS convention, the dimension along X is the
second value of the array shape and that the dimension along the
Y axis is the first one.
extname : None or string
if a string is specified ('' can be used), the returned header
type will be an Image HDU (otherwise a Primary HDU).
crval : 2 element array, optional
Reference pixel values (FITS convention).
crpix : 2 element array, optional
Reference pixel (FITS convention).
ctype : 2 element string array, optional
Projection types.
cunit : string or 2 element string array
Units of the CD matrix (default is degrees/pixel).
cd : 2 x 2 array
FITS parameters
CD1_1 CD1_2
CD2_1 CD2_2
cdelt : float or 2 element array
Physical increment at the reference pixel.
pa : float
Position angle of the Y=AXIS2 axis (=-CROTA2).
equinox : float
Reference equinox
Examples
--------
>>> map = Map.ones((10,100), unit='Jy/pixel')
>>> map.header = create_fitsheader(naxis=(100,10), cd=[[-1,0],[0,1]])
>>> map.header = create_fitsheader(fromdata=map)
"""
if fromdata is None:
if naxis is None:
raise ValueError("Keywords 'naxis' or 'fromdata' must be specifie" \
'd.')
if isinstance(naxis, np.ndarray) and naxis.size > 8:
raise ValueError('First argument is naxis=(NAXIS1,NAXIS2,...)')
if dtype is not None:
typename = dtype.name
else:
typename = 'float64'
else:
array = fromdata
if not isinstance(array, np.ndarray):
raise TypeError('The input is not an ndarray.')
if naxis is None:
naxis = tuple(reversed(array.shape))
if dtype is not None:
array = arrays.astype(dtype)
if array.dtype.itemsize == 1:
typename = 'uint8'
elif array.dtype.names is not None:
typename = None
else:
typename = array.dtype.name
if type(naxis) not in (list, tuple):
naxis = (naxis,)
numaxis = len(naxis)
if extname is None:
card = pyfits.createCard('simple', True)
else:
card = pyfits.createCard('xtension', 'IMAGE', 'Image extension')
header = pyfits.Header([card])
if typename is not None:
header.update('bitpix', pyfits.PrimaryHDU.ImgCode[typename],
'array data type')
header.update('naxis', numaxis, 'number of array dimensions')
for dim in range(numaxis):
header.update('naxis'+str(dim+1), naxis[dim])
if extname is None:
header.update('extend', True)
else:
header.update('pcount', 0, 'number of parameters')
header.update('gcount', 1, 'number of groups')
header.update('extname', extname)
if cd is not None:
cd = np.asarray(cd, dtype=np.float64)
if cd.shape != (2,2):
raise ValueError('The CD matrix is not a 2x2 matrix.')
else:
if cdelt is None:
return header
if _my_isscalar(cdelt):
cdelt = (-cdelt, cdelt)
if pa is None:
pa = 0.
theta=np.deg2rad(-pa)
cd = np.diag(cdelt).dot(np.array([[ np.cos(theta), np.sin(theta)],
[-np.sin(theta), np.cos(theta)]]))
crval = np.asarray(crval, dtype=np.float64)
if crval.size != 2:
raise ValueError('CRVAL does not have two elements.')
if crpix is None:
crpix = (np.array(naxis) + 1) / 2.
else:
crpix = np.asarray(crpix, dtype=np.float64)
if crpix.size != 2:
raise ValueError('CRPIX does not have two elements.')
ctype = np.asarray(ctype, dtype=np.string_)
if ctype.size != 2:
raise ValueError('CTYPE does not have two elements.')
if _my_isscalar(cunit):
cunit = (cunit, cunit)
cunit = np.asarray(cunit, dtype=np.string_)
if cunit.size != 2:
raise ValueError('CUNIT does not have two elements.')
header.update('crval1', crval[0])
header.update('crval2', crval[1])
header.update('crpix1', crpix[0])
header.update('crpix2', crpix[1])
header.update('cd1_1' , cd[0,0])
header.update('cd2_1' , cd[1,0])
header.update('cd1_2' , cd[0,1])
header.update('cd2_2' , cd[1,1])
header.update('ctype1', ctype[0])
header.update('ctype2', ctype[1])
header.update('cunit1', cunit[0])
header.update('cunit2', cunit[1])
header.update('equinox', 2000.)
return header
