def write_covariance():
"""
Write out a P(k,mu) or multipoles covariance matrix
"""
from pyRSD.rsdfit.data import PkmuCovarianceMatrix, PoleCovarianceMatrix
parser = argparse.ArgumentParser()
parser.formatter_class = argparse.RawTextHelpFormatter
# required arguments
h = 'the mode, either `pkmu` or `poles`'
parser.add_argument('mode', choices=['pkmu', 'poles'], help=h)
h = parse_tools.PowerSpectraParser.format_help()
parser.add_argument('data', type=parse_tools.PowerSpectraParser.data, help=h)
h = parse_tools.PowerSpectraCallable.format_help()
parser.add_argument('callable', type=parse_tools.PowerSpectraCallable.data, help=h)
h = 'the data format to use, either `pickle` or `plaintext`'
parser.add_argument('--format', choices=['pickle', 'plaintext'], default='plaintext', help=h)
h = 'the output file name'
parser.add_argument('-o', '--output', required=True, type=str, help=h)
h = 'the multipole numbers to compute'
parser.add_argument('--ells', nargs='*', type=int, help=h)
# options
h = "the minimum wavenumber to use"
parser.add_argument('--kmin', nargs='+', type=float, default=[-np.inf], help=h)
h = "the maximum wavenumber to use"
parser.add_argument('--kmax', nargs='+', type=float, default=[np.inf], help=h)
h = "set off-diagonal elements to zero"
parser.add_argument('--force_diagonal', action='store_true', help=h)
# parse
args = parser.parse_args()
if len(args.kmin) == 1: args.kmin = args.kmin[0]
if len(args.kmax) == 1: args.kmax = args.kmax[0]
# get the data from the parent data and function
data = getattr(args.data, args.callable['name'])(**args.callable['kwargs'])
# compute the covariance matrix
kwargs = {}
kwargs['kmin'] = args.kmin
kwargs['kmax'] = args.kmax
kwargs['force_diagonal'] = args.force_diagonal
if args.mode == 'pkmu':
C = PkmuCovarianceMatrix.from_spectra_set(data, **kwargs)
elif args.mode == 'poles':
if args.ells is not None: kwargs['ells'] = args.ells
C = PoleCovarianceMatrix.from_spectra_set(data, **kwargs)
# now output
if args.format == 'pickle':
C.to_pickle(args.output)
else:
C.to_plaintext(args.output)
def write_data_gaussian_covariance():
"""
Write out the gaussian covariance matrix from data measurements,
for either P(k,mu) or multipoles
"""
from pyRSD.rsdfit.data import PkmuCovarianceMatrix, PoleCovarianceMatrix
parser = argparse.ArgumentParser()
parser.formatter_class = argparse.RawTextHelpFormatter
subparsers = parser.add_subparsers(dest='subparser_name')
# pkmu parser
pkmu_parser = subparsers.add_parser('pkmu')
h = parse_tools.PowerSpectraParser.format_help()
pkmu_parser.add_argument('data', type=parse_tools.PowerSpectraParser.data, help=h)
h = parse_tools.PowerSpectraCallable.format_help()
pkmu_parser.add_argument('callable', type=parse_tools.PowerSpectraCallable.data, help=h)
h = 'a list of (lower, upper) specifying the mu bin bounds'
pkmu_parser.add_argument('mu_bounds', type=str, help=h)
h = "the data keys to slice the data on; specified as `a = '0.6452'`"
pkmu_parser.add_argument('key', type=str, nargs='+', action=parse_tools.StoreDataKeys, help=h)
# poles parser
pole_parser = subparsers.add_parser('poles')
h = parse_tools.PowerSpectraParser.format_help()
pole_parser.add_argument('data', type=parse_tools.PowerSpectraParser.data, help=h)
h = parse_tools.PowerSpectraCallable.format_help()
pole_parser.add_argument('callable', type=parse_tools.PowerSpectraCallable.data, help=h)
h = 'the multipole numbers'
pole_parser.add_argument('ells', type=str, help=h)
h = "the data keys to slice the data on; specified as `a = '0.6452'`"
pole_parser.add_argument('key', type=str, nargs='+', action=parse_tools.StoreDataKeys, help=h)
# options
for p in [pkmu_parser, pole_parser]:
h = 'the data format to use, either `pickle` or `plaintext`'
p.add_argument('--format', choices=['pickle', 'plaintext'], default='plaintext', help=h)
h = 'the output file name'
p.add_argument('-o', '--output', required=True, type=str, help=h)
h = "the minimum wavenumber to use"
p.add_argument('--kmin', nargs='+', type=float, default=[-np.inf], help=h)
h = "the maximum wavenumber to use"
p.add_argument('--kmax', nargs='+', type=float, default=[np.inf], help=h)
# parse
args = parser.parse_args()
if len(args.kmin) == 1: args.kmin = args.kmin[0]
if len(args.kmax) == 1: args.kmax = args.kmax[0]
# get the data from the parent data and function
data = getattr(args.data, args.callable['name'])(**args.callable['kwargs'])
coords = data.coords
for c in coords:
if c in args.key:
dt = data.coords[c].dtype.type
args.key[c] = [dt(x) for x in args.key[c]]
# now slice
for k in args.key:
if len(args.key[k]) != 1:
raise ValueError("must specify exactly one key for each dimension")
args.key[k] = args.key[k][0]
try:
data = data.sel(**args.key)
if data.size == 1: data = data.get()
except Exception as e:
raise RuntimeError("error slicing data with key %s: %s" %(str(args.key), str(e)))
# compute the covariance matrix
if args.subparser_name == 'pkmu':
mu_bounds = eval(args.mu_bounds)
C, coords = covariance.data_pkmu_gausscov(data, mu_bounds, kmin=args.kmin, kmax=args.kmax)
C = PkmuCovarianceMatrix(C, coords[0], coords[1])
else:
ells = np.array(eval(args.ells), dtype=float)
C, coords = covariance.data_pole_gausscov(data, ells, kmin=args.kmin, kmax=args.kmax)
C = PoleCovarianceMatrix(C, coords[0], coords[1])
# now output
if args.format == 'pickle':
C.to_pickle(args.output)
else:
C.to_plaintext(args.output)
