def pylians3Bispectrum(delta, k1, k2, theta):
''' Get data from pylians3 Bispectrum measurements.
returns: array_like
k1/kF | k2/kF | k3/kF | P(k1) | P(k2) | P(k3) | B(k1,k2,k3) | Number of triangles
delta : array_like
input data, shape = (numfiles, gridsize, gridsize, gridsize)
k1,k2: fixed wavenumber in units of the fundamental frequency.
integer number.
theta: angle between k1 and k2.
'''
Bk = PKL.Bk(delta, BoxSize, k1 * kf, k2 * kf, theta, MAS, threads)
BSk_pyl = Bk.B #bispectrm
triangle_conf = Bk.triangles #triangle counts
k3_pyl = Bk.k[2:] #k-bins for power spectrum
Pk1_pyl = Bk.Pk[0] #power spectrum PS(k1)
Pk2_pyl = Bk.Pk[1] # ´´ PS(k2)
Pk3_pyl = Bk.Pk[2:] # ´´ PS(k3)
lenn = len(theta)
return np.vstack([
np.full(lenn, k1),
np.full(lenn, k2), k3_pyl / kf,
np.full(lenn, Pk1_pyl),
np.full(lenn, Pk2_pyl), Pk3_pyl, BSk_pyl, triangle_conf
])
def compute_matter_bispectrum(vols, cubedim=64, k1=0.1, k2=0.5):
thetas = np.linspace(0.0, 2.5, 10)
bks = []
for i in xrange(vols.shape[0]):
with HiddenPrints():
bis = PKL.Bk(vols[i] - np.mean(vols[i]), float(cubedim), k1, k2,
thetas)
bks.append(bis.B)
return bks, thetas
def compute_bispectrum(self, save=True): #{{{
# (1) triangle configurations k = 1, 3, varying angles
_k1 = 1.0
_k2 = 3.0
_theta = np.linspace(0.0, np.pi, num=20)
Bk1 = PKL.Bk(self.data, self.BoxSize, _k1, _k2, _theta, self.MAS,
ARGS.threads).Q
if ARGS.verbose:
print 'Computed Bk1 in Field(%s)' % self.mode
# (2) triangle configurations k = 0.1, 0.3, varying angles
_k1 = 0.2
_k2 = 0.3
_theta = np.linspace(0.0, np.pi, num=20)
Bk2 = PKL.Bk(self.data, self.BoxSize, _k1, _k2, _theta, self.MAS,
ARGS.threads).Q
if ARGS.verbose:
print 'Computed Bk2 in Field(%s)' % self.mode
# (3) equilateral triangle configurations
_k = 10.0**np.linspace(np.log10(0.2), np.log10(3.0), num=20)
_theta = np.array([np.pi / 3.0])
Bk3 = []
for k in _k:
Bk3.append(
PKL.Bk(self.data, self.BoxSize, k, k, _theta, self.MAS,
ARGS.threads).Q)
if ARGS.verbose:
print 'Computed Bk3 in Field(%s)' % self.mode
self.bispectrum = {
'Bk1': Bk1,
'Bk2': Bk2,
'Bk3': Bk3,
}
if save:
np.savez(self.summary_path + '%s.npz' % self.bispectrumname,
**self.bispectrum)
if ARGS.verbose:
print 'Computed bispectrum in Field(%s)' % self.mode
BoxSize = 31.82373046875 #Size of the density field in Mpc/h
axis = 0
k1 = 0.5 #h/Mpc
k2 = 0.6 #h/Mpc
MAS = 'CIC'
threads = 32
theta = np.linspace(0, np.pi, 25) #array with the angles between k1 and k2
# compute true bispectrum
Bk_target = PKL.Bk(test_cube, BoxSize, k1, k2, theta, MAS, threads)
Bk = Bk_target.B #bispectrum
Qk = Bk_target.Q #reduced bispectrum
k = Bk_target.k_all #k-bins for power spectrum
Pk = Bk_target.Pk #power spectrum
# save bispectrum and k
np.save('../dat/processed/'+'target_theta_values.npy',theta)
np.save('../dat/processed/'+'target_Bk_values.npy',Bk)
# compute dm2gak bispectrum
# compute bispectrum
Bk_pred = PKL.Bk(pred_cube, BoxSize, k1, k2, theta, MAS, threads)
