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#!/usr/bin/env python3
#
# Copyright (c) 2017 Weitian LI <weitian@aaronly.me>
# MIT license
#
"""
Calculate the 2D cylindrical-averaged power spectrum from the
3D image spectral cube.
"""
import os
import sys
import argparse
import logging
import numpy as np
from scipy import fftpack
from scipy.signal import windows
from astropy.io import fits
from astropy.wcs import WCS
from astropy.cosmology import FlatLambdaCDM
import astropy.constants as ac
logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(os.path.basename(sys.argv[0]))
# present Hubble parameter
H0 = 71.0 # [km/s/Mpc]
# present density parameter of matter
OmegaM0 = 0.27
# HI line frequency
freq21cm = 1420.405751 # [MHz]
def freq2z(freq):
z = freq21cm / freq - 1.0
return z
def get_frequencies(wcs, nfreq):
pix = np.zeros(shape=(nfreq, 3), dtype=np.int)
pix[:, -1] = np.arange(nfreq)
world = wcs.wcs_pix2world(pix, 0)
freqMHz = world[:, -1] / 1e6
return freqMHz
class PS2D:
"""
2D cylindrical-averaged power spectrum
cube dimensions: [nfreq, height, width] / [Z, Y, X]
"""
def __init__(self, cube, pixelsize, frequencies,
window="nuttall", width="extended"):
logger.info("Initializing PS2D instance ...")
self.cube = cube
self.pixelsize = pixelsize # [arcmin]
logger.info("Image pixel size: %.2f [arcmin]" % pixelsize)
self.frequencies = np.array(frequencies) # [MHz]
self.nfreq = len(self.frequencies)
# Central frequency and redshift
self.freqc = self.frequencies.mean()
self.zc = freq2z(self.freqc)
logger.info("Central frequency %.2f [MHz] <-> redshift %.4f" %
(self.freqc, self.zc))
self.cosmo = FlatLambdaCDM(H0=H0, Om0=OmegaM0)
# Transverse comoving distance at zc; unit: [Mpc]
self.DMz = self.cosmo.comoving_transverse_distance(self.zc).value
self.set_window(name=window, width=width)
def set_window(self, name, width="extended"):
self.window = {
"name": name,
"func": getattr(windows, name),
"width": width
}
filter = self.window["func"](self.window_width, sym=False)
if len(filter) > self.nfreq:
# cut the filter
midx = int(len(filter) / 2) # index of the peak element
nleft = int(self.nfreq / 2) # number of element on the left
nright = int((self.nfreq-1) / 2) # number of element on the right
filter = filter[(midx-nleft):(midx+nright+1)]
self.window["filter"] = filter
logger.info("Set window: %s (%s)" % (name, width))
@property
def window_width(self):
if self.window["width"] == "extended":
w = self.window["func"](self.nfreq, sym=False)
ex = 1.0 / (w.sum() / self.nfreq)
return int(ex * self.nfreq)
else:
return self.nfreq
def pad_cube(self):
# Pad the image cube to be square in spatial dimensions.
# TODO
__, ny, nz = self.cube.shape
if ny != nz:
logger.info("Padding image to be square ...")
raise RuntimeError("image must be square!")
def calc_ps3d(self):
"""
Calculate the 3D power spectrum of the image cube.
"""
logger.info("Applying window to frequency axis ...")
w = self.window["filter"]
cube2 = self.cube * w[:, np.newaxis, np.newaxis]
logger.info("Calculating 3D FFT and PS ...")
cubefft = fftpack.fftshift(fftpack.fftn(cube2))
self.ps3d = np.abs(cubefft) ** 2
return self.ps3d
def calc_ps2d(self):
"""
Calculate the 2D power spectrum by cylindrically binning
the above 3D power spectrum.
"""
nz, ny, nx = self.cube.shape
k_x, k_y = self.k_xy
k_z = self.k_z
dkx = np.abs(k_x[0] - k_x[1])
dkz = np.abs(k_z[0] - k_z[1])
vcell = dkx**2 * dkz # volume of each cell [Mpc^-3]
eps = 1e-8
ic_x = (np.abs(k_x) < eps).nonzero()[0][0]
ic_z = (np.abs(k_z) < eps).nonzero()[0][0]
p_x = np.arange(nx) - ic_x
p_z = np.abs(np.arange(ny) - ic_z)
mx, my = np.meshgrid(p_x, p_x)
rho, phi = self.cart2pol(mx, my)
rho = np.around(rho).astype(np.int)
n_k_perp = (nx+1) // 2
n_k_los = (nz+1) // 2
ps2d = np.zeros(shape=(n_k_los, n_k_perp)) # (k_los, k_perp)
logger.info("Calculating 2D PS by binning 3D PS ...")
for r in range(n_k_perp):
ix, iy = (rho == r).nonzero()
for s in range(n_k_los):
iz = (p_z == s).nonzero()[0]
cells = np.concatenate([self.ps3d[z, iy, ix] for z in iz])
volume = cells.size * vcell
ps2d[s, r] = cells.sum() / volume
self.ps2d = ps2d
return ps2d
def save(self, outfile, clobber=False):
"""
Save the calculated 2D power spectrum as a FITS image.
"""
hdu = fits.PrimaryHDU(data=self.ps2d, header=self.header)
try:
hdu.writeto(outfile, overwrite=clobber)
except TypeError:
hdu.writeto(outfile, clobber=clobber)
logger.info("PS2D results saved to file: %s" % outfile)
@property
def k_xy(self):
__, ny, nx = self.cube.shape
dxy = self.DMz * np.deg2rad(self.pixelsize / 60.0) # [Mpc]
kx = 2*np.pi * fftpack.fftshift(fftpack.fftfreq(nx, dxy))
ky = 2*np.pi * fftpack.fftshift(fftpack.fftfreq(ny, dxy))
return (kx, ky) # [Mpc^-1]
@property
def k_z(self):
freq_step = 1e6 * (self.frequencies[1] - self.frequencies[0]) # [Hz]
eta = fftpack.fftshift(fftpack.fftfreq(self.nfreq, freq_step)) # [s]
c = ac.c.si.value # [m/s]
h = H0 * 1000.0 # [m/s/Mpc]
f21cm = freq21cm * 1e6 # [Hz]
denom = c * (1+self.zc)**2 / h / f21cm / self.cosmo.efunc(self.zc)
kz = 2*np.pi * eta / denom
return kz # [Mpc^-1]
@property
def k_perp(self):
"""
Comoving wavenumbers perpendicular to the LoS
NOTE: The Nyquist frequency just located at the first element
after fftshift when the length is even, and it is negative.
"""
k_x, k_y = self.k_xy
return k_x[k_x >= 0]
@property
def k_los(self):
"""
Comoving wavenumbers along the LoS
"""
k_z = self.k_z
return k_z[k_z >= 0]
@staticmethod
def cart2pol(x, y):
"""
Convert Cartesian coordinates to polar coordinates.
"""
rho = np.sqrt(x**2 + y**2)
phi = np.arctan2(y, x)
return (rho, phi)
@property
def header(self):
kx, __ = self.k_xy
kz = self.k_z
dkx = np.abs(kx[0] - kx[1])
dkz = np.abs(kz[0] - kz[1])
hdr = fits.Header()
hdr["HDUNAME"] = ("PS2D", "block name")
hdr["CONTENT"] = ("2D cylindrical-averaged power spectrum",
"data product")
hdr["BUNIT"] = ("K^2 Mpc^3", "data unit")
# Physical coordinates: IRAF LTM/LTV
# Li{Image} = LTMi_i * Pi{Physical} + LTVi
# Reference: ftp://iraf.noao.edu/iraf/web/projects/fitswcs/specwcs.html
hdr["LTV1"] = 0.0
hdr["LTM1_1"] = 1.0 / dkx
hdr["LTV2"] = 0.0
hdr["LTM2_2"] = 1.0 / dkz
# WCS physical coordinates
hdr["WCSTY1P"] = "PHYSICAL"
hdr["CTYPE1P"] = ("k_perp", "wavenumbers perpendicular to LoS")
hdr["CRPIX1P"] = (0.5, "reference pixel")
hdr["CRVAL1P"] = (0.0, "coordinate of the reference pixel")
hdr["CDELT1P"] = (dkx, "coordinate delta/step")
hdr["CUNIT1P"] = ("Mpc^-1", "coordinate unit")
hdr["WCSTY2P"] = "PHYSICAL"
hdr["CTYPE2P"] = ("k_los", "wavenumbers along LoS")
hdr["CRPIX2P"] = (0.5, "reference pixel")
hdr["CRVAL2P"] = (0.0, "coordinate of the reference pixel")
hdr["CDELT2P"] = (dkz, "coordinate delta/step")
hdr["CUNIT2P"] = ("Mpc^-1", "coordinate unit")
# Command history
hdr.add_history(" ".join(sys.argv))
return hdr
def main():
parser = argparse.ArgumentParser(
description="Calculate 2D PS from 3D image cube")
parser.add_argument("-C", "--clobber", dest="clobber",
action="store_true",
help="overwrite existing file")
parser.add_argument("-p", "--pixelsize", dest="pixelsize",
type=float, required=True,
help="image cube pixel size; unit: [arcmin]")
parser.add_argument("-i", "--infile", dest="infile", required=True,
help="input FITS image cube")
parser.add_argument("-o", "--outfile", dest="outfile", required=True,
help="output 2D power spectrum FITS file")
args = parser.parse_args()
with fits.open(args.infile) as f:
cube = f[0].data
wcs = WCS(f[0].header)
nfreq = cube.shape[0]
frequencies = get_frequencies(wcs, nfreq)
logger.info("%d frequencies [MHz]:" % nfreq)
for f in frequencies:
logger.info("* %.2f" % f)
ps2d = PS2D(cube=cube, pixelsize=args.pixelsize, frequencies=frequencies)
ps2d.calc_ps3d()
ps2d.calc_ps2d()
ps2d.save(outfile=args.outfile, clobber=args.clobber)
if __name__ == "__main__":
main()
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