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hera_NicCST_instrument_setup.py
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hera_NicCST_instrument_setup.py
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import numpy as np, healpy as hp
import os
from scipy import interpolate
import ionRIME_funcs as irf
import numba_funcs as irnf
class Parameters:
def __init__(self, param_dict):
for key in param_dict:
setattr(self, key, param_dict[key])
def txtname(n):
# dpath = '/data4/paper/zionos/polskysim/IonRIME/InstrumentSimData/NicCST_Old/'
# fname = 'Directivity ' + str(n) + ' MHz.txt'
if os.path.exists('/data4/paper'):
dpath = '/data4/paper/zionos/polskysim/IonRIME/InstrumentSimData/NicCST/'
else:
dpath = '/lustre/aoc/projects/hera/zmartino/zionos/polskysim/IonRIME/InstrumentSimData/NicCST/'
fname = 'HERA - E-pattern - ' + str(n) + 'MHz.txt'
return dpath + fname
def linear2Dbi(E): return 2. * 10. * np.log10(E)
def Dbi2linear(Dbi): return np.power(10., Dbi/20.)
def AzimuthalRotation(hmap):
"""
Azimuthal clockwise(?) rotation of a healpix map by pi/2 about the z-axis
"""
npix = len(hmap)
nside= hp.npix2nside(npix)
hpxidx = np.arange(npix)
t2,p2 = hp.pix2ang(nside, hpxidx)
p = p2 - np.pi/2
p[p < 0] += 2. * np.pi
t = t2
idx = hp.ang2pix(nside, t, p)
hout = hmap[idx]
return hout
def udgrade(x,nside_out):
return hp.alm2map(hp.map2alm(x),nside_out, verbose=False)
def udgrade_jones(jones, nside_out):
jones2 = np.zeros((hp.nside2npix(nside_out),2,2), dtype=np.complex128)
parts = [np.real,np.imag]
comp = [1., 1.j]
for i in range(2):
for j in range(2):
for k in range(2):
z = udgrade(parts[k](jones[:,i,j]),nside_out)
jones2[:,i,j] += z*comp[k]
return jones2
def make_jones(freq):
# if freq not in range(50,250):
# raise Exception('The input must be an integer in the range [50,250]')
data1 = np.loadtxt(txtname(freq),skiprows=2)
th_data = np.radians(data1[:,0])
phi_data = np.radians(data1[:,1])
Et = data1[:,3] * np.exp(-1j * np.radians(data1[:,4]))
Ep = data1[:,5] * np.exp(-1j * np.radians(data1[:,6]))
cosp = np.cos(phi_data)
sinp = np.sin(phi_data)
rEt = cosp * Et - sinp * Ep
rEp = sinp * Et + cosp * Ep
th_f,phi_f = np.abs(th_data), np.where(th_data < 0, phi_data + np.pi, phi_data)
# th_f, phi_f = np.abs(thM), np.where(thM < 0, phiM + np.pi, phiM)
hpxiz = lambda m: irf.healpixellize(m,th_f,phi_f,32,fancy=False)
nside = 512
npix = hp.nside2npix(nside)
hpxidx = np.arange(npix)
th,phi = hp.pix2ang(nside, hpxidx)
phi = np.where(phi >= np.pi, phi - np.amax(phi), phi)
EXt, EXp = [udgrade(hpxiz(X.real),nside) + 1j * udgrade(hpxiz(X.imag),nside) for X in [rEt,rEp]]
cosP = np.cos(phi)
sinP = np.sin(phi)
nEXt = cosP * EXt + sinP * EXp
nEXp = -sinP * EXt + cosP * EXp
nEYt = AzimuthalRotation(nEXt)
nEYp = AzimuthalRotation(nEXp)
jones_out = np.array([[nEXt,nEXp],[nEYt,nEYp]]).transpose(2,0,1)
# joens_out = np.ascontiguousarray(jones_out) # it looks like this line is unc
return jones_out
def transform_basis(nside, jones, z0_cza, R_z0):
npix = hp.nside2npix(nside)
hpxidx = np.arange(npix)
cza, ra = hp.pix2ang(nside, hpxidx)
fR = R_z0
tb, pb = irf.rotate_sphr_coords(fR, cza, ra)
cza_v = irf.t_hat_cart(cza, ra)
ra_v = irf.p_hat_cart(cza, ra)
tb_v = irf.t_hat_cart(tb, pb)
fRcza_v = np.einsum('ab...,b...->a...', fR, cza_v)
fRra_v = np.einsum('ab...,b...->a...', fR, ra_v)
cosX = np.einsum('a...,a...', fRcza_v, tb_v)
sinX = np.einsum('a...,a...', fRra_v, tb_v)
basis_rot = np.array([[cosX, -sinX],[sinX, cosX]])
basis_rot = np.transpose(basis_rot,(2,0,1))
# return np.einsum('...ab,...bc->...ac', jones, basis_rot)
return irnf.M(jones, basis_rot)
def jones2celestial_basis(jones, z0_cza=None):
if z0_cza is None:
z0_cza = np.radians(120.7215)
npix = jones.shape[0]
nside = hp.npix2nside(npix)
hpxidx = np.arange(npix)
cza, ra = hp.pix2ang(nside, hpxidx)
z0 = irf.r_hat_cart(z0_cza, 0.)
RotAxis = np.cross(z0, np.array([0,0,1.]))
RotAxis /= np.sqrt(np.dot(RotAxis,RotAxis))
RotAngle = np.arccos(np.dot(z0, [0,0,1.]))
R_z0 = irf.rotation_matrix(RotAxis, RotAngle)
jones_b = transform_basis(nside, jones, z0_cza, R_z0.T)
rot = [0., -z0_cza, 0.]
jones_out = irf.unitary_rotate_jones(jones_b, rot, multiway=True)
return jones_out
def neighbors_of_neighbors(nside, th, phi):
"""
Finds the pixel numbers of the 8 neighbors of the the point (th,phi),
then find the 8 neighbors of each of those points. The are the 64 pixel
indices of the "neighbors of neighbors" of the point (th,phi).
"""
neighbors = hp.get_all_neighbours(nside, th, phi=phi)
tn, pn = hp.pix2ang(nside, neighbors)
nn = hp.get_all_neighbours(nside, tn, phi=pn)
return nn.flatten()
def jones_f(nu_node, nside):
return udgrade_jones(jones2celestial_basis(make_jones(nu_node)), nside)
def horizon_mask(jones, z0_cza):
npix = jones.shape[0]
nside = hp.npix2nside(npix)
hpxidx = np.arange(npix)
cza, ra = hp.pix2ang(nside, hpxidx)
if z0_cza == 0.:
tb, pb = cza, ra
else:
z0 = irf.r_hat_cart(z0_cza, 0.)
RotAxis = np.cross(z0, np.array([0,0,1.]))
RotAxis /= np.sqrt(np.dot(RotAxis,RotAxis))
RotAngle = np.arccos(np.dot(z0, [0,0,1.]))
R_z0 = irf.rotation_matrix(RotAxis, RotAngle)
tb, pb = irf.rotate_sphr_coords(R_z0, cza, ra)
hm = np.zeros((npix,2,2))
hm[np.where(tb < np.pi/2.)] = 1.
return hm
def make_ijones_spectrum(parameters_dict, verbose=False):
p = Parameters(parameters_dict)
"""
nu_axis: frequency in Hz
"""
fmax = int(p.nu_axis[-1]/1e6)
fmin = int(p.nu_axis[0]/1e6)
# fmax = 250
# fmin = 80
nfreq = len(p.nu_axis)
nnodes = fmax - fmin + 1
nu_nodes = np.array([fmin + x for x in range(nnodes)])
# nu_nodes = np.array(range(80,260,10))
# nnodes = len(nu_nodes)
lmax = 3 * p.nside -1
nlm = hp.Alm.getsize(lmax)
joneslm = np.zeros((nnodes, nlm, 2,2,2), dtype=np.complex128)
sht = lambda x: hp.map2alm(x, lmax=lmax)
comp = [np.real, np.imag]
u = [1,1j]
if verbose == True:
print "Freq. min/max:", fmin, fmax
print "nnodes: ", nnodes
print "len(nu_nodes): ", len(nu_nodes)
# synthesize maps at the nside to be used in the simulation for each frequency node
# This is necessary because the basis transformation is done at nside 1024 to minimize
# the topological error at the center of the beam. But for the frequency interpolation
# this resolution would probably use too much memory.
# note that the output of jones_f() is a beam with zenith at -31 deg latitude
for n in range(nnodes):
if verbose == True:
print "Loading jones node ", n, ", freq", nu_nodes[n]
jones_node = jones_f(nu_nodes[n], p.nside)
for i in range(2):
for j in range(2):
for k in range(2):
joneslm[n,:,i,j,k] = sht(comp[k](jones_node[:,i,j]))
joneslm_re = joneslm.real
joneslm_im = joneslm.imag
if verbose == True:
print joneslm_re.shape
print joneslm_im.shape
print nu_nodes.shape
interpolant_re = interpolate.interp1d(nu_nodes,joneslm_re,kind='cubic',axis=0)
interpolant_im = interpolate.interp1d(nu_nodes,joneslm_im,kind='cubic',axis=0)
freqs_out = p.nu_axis/1e6
joneslm_re_int = interpolant_re(freqs_out)
joneslm_im_int = interpolant_im(freqs_out)
joneslm_int = joneslm_re_int + 1j*joneslm_im_int
# now we just need to resynthesize at each frequency and we're done
isht = lambda x: hp.alm2map(np.ascontiguousarray(x), p.nside,verbose=False)
z0_cza = np.radians(120.7215)
solid_angle_spectrum = []
peak_norm_spectrum = []
ijones = np.zeros((p.nfreq,p.npix,2,2), dtype=np.complex128)
for n in range(p.nfreq):
for i in range(2):
for j in range(2):
ijones[n,:,i,j] = isht(joneslm_int[n,:,i,j,0]) + 1j*isht(joneslm_int[n,:,i,j,1])
ijones[n] *= horizon_mask(ijones[n].squeeze(), z0_cza)
If = abs(ijones[n,:,0,0])**2. + abs(ijones[n,:,0,1])**2. + abs(ijones[n,:,0,1])**2. + abs(ijones[n,:,1,0])**2
peak_norm = np.amax(If)
solid_angle = (4. * np.pi / p.npix) * np.sum(If/peak_norm)
peak_norm_spectrum.append(peak_norm)
solid_angle_spectrum.append(solid_angle)
ijones[n] /= np.sqrt(peak_norm)
# ijones[n] /= np.sqrt(solid_angle)
if verbose == True:
print "norm is:", np.sqrt(peak_norm)
solid_angle_spectrum = np.array(solid_angle_spectrum)
peak_norm_spectrum = np.array(peak_norm_spectrum)
return ijones, solid_angle_spectrum, peak_norm_spectrum