def write_alm(filename, alms, out_dtype=None, lmax=-1, mmax=-1, mmax_in=-1):
"""
Write alms to a fits file. In the fits file the alms are written
with explicit index scheme, index = l*l + l + m +1, possibly out of order.
By default write_alm makes a table with the same precision as the alms.
If specified, the lmax and mmax parameters truncate the input data to
include only alms for which l <= lmax and m <= mmax.
Input:
- filename: the filename of the output fits file
- alms: a complex array holding the alms.
Parameters:
- lmax: maximum l in the output file
- mmax: maximum m in the output file
- out_dtype: data type in the output file (must be a numpy dtype)
- mmax_in: maximum m in the input array
"""
l2max = Alm.getlmax(len(alms), mmax=mmax_in)
if lmax != -1 and lmax > l2max:
raise ValueError("Too big lmax in parameter")
elif lmax == -1:
lmax = l2max
if mmax_in == -1:
mmax_in = l2max
if mmax == -1:
mmax = lmax
if mmax > mmax_in:
mmax = mmax_in
if out_dtype == None:
out_dtype = alms.real.dtype
l, m = Alm.getlm(lmax)
idx = npy.where((l <= lmax) * (m <= mmax))
l = l[idx]
m = m[idx]
idx_in_original = Alm.getidx(l2max, l=l, m=m)
index = l ** 2 + l + m + 1
out_data = npy.empty(len(index), dtype=[("index", "i"), ("real", out_dtype), ("imag", out_dtype)])
out_data["index"] = index
out_data["real"] = alms.real[idx_in_original]
out_data["imag"] = alms.imag[idx_in_original]
cindex = pyf.Column(name="index", format=getformat(npy.int32), unit="l*l+l+m+1", array=out_data["index"])
creal = pyf.Column(name="real", format=getformat(out_dtype), unit="unknown", array=out_data["real"])
cimag = pyf.Column(name="imag", format=getformat(out_dtype), unit="unknown", array=out_data["imag"])
coldefs = pyf.ColDefs([cindex, creal, cimag])
tbhdu = pyf.new_table(coldefs)
tbhdu.writeto(filename, clobber=True)
def read_alm(filename, hdu=1, return_mmax=False):
"""Read alm from a fits file. In the fits file, the alm are written
with explicit index scheme, index = l**2+l+m+1, while healpix cxx
uses index = m*(2*lmax+1-m)/2+l. The conversion is done in this
function.
Input:
- filename: the name of the fits file to read
Parameters:
- hdu: the header to read. Start at 0. Default: hdu=1
- return_mmax: If true, both the alms and mmax is returned in a tuple. Default: return_mmax=False
Return:
- alms: if return_mmax=False
- alms,mmax: if return_mmax=True
"""
idx, almr, almi = mrdfits(filename, hdu=hdu)
l = npy.floor(npy.sqrt(idx - 1)).astype(long)
m = idx - l ** 2 - l - 1
if (m < 0).any():
raise ValueError("Negative m value encountered !")
lmax = l.max()
mmax = m.max()
alm = almr * (0 + 0j)
i = Alm.getidx(lmax, l, m)
alm.real[i] = almr
alm.imag[i] = almi
if return_mmax:
return alm, mmax
else:
return alm
def read_alm(filename, hdu=1, return_mmax=False):
"""Read alm from a fits file. In the fits file, the alm are written
with explicit index scheme, index = l**2+l+m+1, while healpix cxx
uses index = m*(2*lmax+1-m)/2+l. The conversion is done in this
function.
Input:
- filename: the name of the fits file to read
Parameters:
- hdu: the header to read. Start at 0. Default: hdu=1
- return_mmax: If true, both the alms and mmax is returned in a tuple. Default: return_mmax=False
Return:
- alms: if return_mmax=False
- alms,mmax: if return_mmax=True
"""
idx, almr, almi = mrdfits(filename, hdu=hdu)
l = npy.floor(npy.sqrt(idx - 1)).astype(long)
m = idx - l**2 - l - 1
if (m < 0).any():
raise ValueError('Negative m value encountered !')
lmax = l.max()
mmax = m.max()
alm = almr * (0 + 0j)
i = Alm.getidx(lmax, l, m)
alm.real[i] = almr
alm.imag[i] = almi
if return_mmax:
return alm, mmax
else:
return alm
def read_alm(filename, hdu=1, return_mmax=False):
"""Read alm from a fits file. In the fits file, the alm are written
with explicit index scheme, index = l**2+l+m+1, while healpix cxx
uses index = m*(2*lmax+1-m)/2+l. The conversion is done in this
function.
Parameters
----------
filename : str
The name of the fits file to read
hdu : int, optional
The header to read. Start at 0. Default: hdu=1
return_mmax : bool, optional
If true, both the alms and mmax is returned in a tuple. Default: return_mmax=False
Returns
-------
alms[, mmax] : complex array or tuple of a complex array and an int
The alms read from the file and optionally mmax read from the file
"""
idx, almr, almi = mrdfits(filename, hdu=hdu)
l = npy.floor(npy.sqrt(idx - 1)).astype(long)
m = idx - l**2 - l - 1
if (m < 0).any():
raise ValueError('Negative m value encountered !')
lmax = l.max()
mmax = m.max()
alm = almr * (0 + 0j)
i = Alm.getidx(lmax, l, m)
alm.real[i] = almr
alm.imag[i] = almi
if return_mmax:
return alm, mmax
else:
return alm
def read_alm(filename,hdu=1,return_mmax=False):
"""Read alm from a fits file. In the fits file, the alm are written
with explicit index scheme, index = l**2+l+m+1, while healpix cxx
uses index = m*(2*lmax+1-m)/2+l. The conversion is done in this
function.
Parameters
----------
filename : str
The name of the fits file to read
hdu : int, optional
The header to read. Start at 0. Default: hdu=1
return_mmax : bool, optional
If true, both the alms and mmax is returned in a tuple. Default: return_mmax=False
Returns
-------
alms[, mmax] : complex array or tuple of a complex array and an int
The alms read from the file and optionally mmax read from the file
"""
idx, almr, almi = mrdfits(filename,hdu=hdu)
l = npy.floor(npy.sqrt(idx-1)).astype(long)
m = idx - l**2 - l - 1
if (m<0).any():
raise ValueError('Negative m value encountered !')
lmax = l.max()
mmax = m.max()
alm = almr*(0+0j)
i = Alm.getidx(lmax,l,m)
alm.real[i] = almr
alm.imag[i] = almi
if return_mmax:
return alm, mmax
else:
return alm
def read_alm(filename,hdu=1):
"""Read alm from a fits file. In the fits file, the alm are written
with explicit index scheme, index = l**2+l+m+1, while healpix cxx
uses index = m*(2*lmax+1-m)/2+l. The conversion is done in this
function.
"""
idx, almr, almi = mrdfits(filename,hdu=hdu)
l = npy.floor(npy.sqrt(idx-1)).astype(long)
m = idx - l**2 - l - 1
if (m<0).any():
raise ValueError('Negative m value encountered !')
lmax = l.max()
mmax = m.max()
alm = almr*(0+0j)
i = Alm.getidx(lmax,l,m)
alm.real[i] = almr
alm.imag[i] = almi
return alm
def write_alm(filename,alms,out_dtype=None,lmax=-1,mmax=-1,mmax_in=-1):
"""Write alms to a fits file.
In the fits file the alms are written
with explicit index scheme, index = l*l + l + m +1, possibly out of order.
By default write_alm makes a table with the same precision as the alms.
If specified, the lmax and mmax parameters truncate the input data to
include only alms for which l <= lmax and m <= mmax.
Parameters
----------
filename : str
The filename of the output fits file
alms : array, complex
A complex ndarray holding the alms.
lmax : int, optional
The maximum l in the output file
mmax : int, optional
The maximum m in the output file
out_dtype : data type, optional
data type in the output file (must be a numpy dtype). Default: *alms*.real.dtype
mmax_in : int, optional
maximum m in the input array
"""
l2max = Alm.getlmax(len(alms),mmax=mmax_in)
if (lmax != -1 and lmax > l2max):
raise ValueError("Too big lmax in parameter")
elif lmax == -1:
lmax = l2max
if mmax_in == -1:
mmax_in = l2max
if mmax == -1:
mmax = lmax
if mmax > mmax_in:
mmax = mmax_in
if (out_dtype == None):
out_dtype = alms.real.dtype
l,m = Alm.getlm(lmax)
idx = np.where((l <= lmax)*(m <= mmax))
l = l[idx]
m = m[idx]
idx_in_original = Alm.getidx(l2max, l=l, m=m)
index = l**2 + l + m + 1
out_data = np.empty(len(index),\
dtype=[('index','i'),\
('real',out_dtype),('imag',out_dtype)])
out_data['index'] = index
out_data['real'] = alms.real[idx_in_original]
out_data['imag'] = alms.imag[idx_in_original]
cindex = pf.Column(name="index", format=getformat(np.int32), unit="l*l+l+m+1", array=out_data['index'])
creal = pf.Column(name="real", format=getformat(out_dtype), unit="unknown", array=out_data['real'])
cimag = pf.Column(name="imag", format=getformat(out_dtype), unit="unknown", array=out_data['imag'])
tbhdu = pf.new_table([cindex,creal,cimag])
tbhdu.writeto(filename,clobber=True)
