def demoBk():
'''
'''
kmax = 0.5
kf = 2.*np.pi/2600.
# read in Bk
bisp = pickle.load(open(os.path.join(UT.dat_dir(), 'egBk.p'), 'rb'))
i_k, j_k, l_k, bk = bisp['i_k1'], bisp['i_k2'], bisp['i_k3'], bisp['b123']
klim = ((i_k*kf <= kmax) & (j_k*kf <= kmax) & (l_k*kf <= kmax))
i_k, j_k, l_k = i_k[klim], j_k[klim], l_k[klim]
ijl = UT.ijl_order(i_k, j_k, l_k, typ='GM') # order of triangles
for itri in range(1500):
fig = plt.figure(figsize=(15,4.8))
sub = fig.add_subplot(111)
sub.plot(range(1500), bk[klim][ijl][:1500], c='k', lw=0.5)
sub.scatter(range(1500), bk[klim][ijl][:1500], c='k', s=2)
sub.scatter(itri, bk[klim][ijl][itri], c='C1', s=30, zorder=10)
itri_i, itri_j, itri_l = i_k[ijl][itri], j_k[ijl][itri], l_k[ijl][itri]
trixy = np.zeros((3,2))
trixy[0,:] = np.array([1400, 2e10])
trixy[1,:] = np.array([1400 - 3.33*itri_i, 2e10])
theta23 = np.arccos(-0.5*(itri_l**2 - itri_i**2 - itri_j**2)/itri_i/itri_j)[0]
trixy[2,:] = np.array([1400-3.33*itri_j[0]*np.cos(theta23),
10**(10.301 - 0.022*itri_j[0]*np.sin(theta23))])
tri = plt.Polygon(trixy, fill=None, edgecolor='k')
fig.gca().add_patch(tri)
sub.text(0.5*(trixy[0,0]+trixy[1,0]), 0.5*(trixy[0,1]+trixy[1,1]), '$k_3$',
fontsize=8, ha='center', va='bottom')
sub.text(0.5*(trixy[0,0]+trixy[2,0]), 0.5*(trixy[0,1]+trixy[2,1]), '$k_2$',
fontsize=8, ha='left', va='top')
sub.text(0.5*(trixy[1,0]+trixy[2,0]), 0.5*(trixy[1,1]+trixy[2,1]), '$k_1$',
fontsize=8, ha='right', va='top')
sub.set_xlabel('triangle configurations', fontsize=25)
sub.set_xlim([0, 1500])
sub.set_ylabel(r'$B(k_1, k_2, k_3)$', fontsize=25)
sub.set_yscale('log')
sub.set_ylim([1e7, 3e10])
fig.savefig(os.path.join(UT.dat_dir(), 'demo', 'demoBk%i.png' % itri), bbox_inches='tight')
plt.close()
return None
def AEM_rzspace():
''' comparison between real and redshift space
'''
f_b123 = lambda sim, rsd: os.path.join(
UT.dat_dir(), sim,
'pySpec.B123.halo.mlim1e13.Ngrid360.Nmax40.Ncut3.step3.pyfftw%s.dat' %
['', '.rsd'][rsd])
Lbox_aem = 1050.
kf_aem = 2. * np.pi / Lbox_aem
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, _ = np.loadtxt(
f_b123('aemulus', False), skiprows=1, unpack=True, usecols=range(10))
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123_s, q123_s, counts, _ = np.loadtxt(
f_b123('aemulus', True), skiprows=1, unpack=True, usecols=range(10))
klim = ((i_k * kf_aem <= 0.3) & (j_k * kf_aem <= 0.3) &
(l_k * kf_aem <= 0.3))
ijl = UT.ijl_order(i_k[klim], j_k[klim], l_k[klim],
typ='GM') # order of triangles
sub.scatter(range(np.sum(klim)),
b123[klim][ijl],
c='k',
s=5,
label='real-space')
sub.plot(range(np.sum(klim)), b123[klim][ijl], c='k')
sub.scatter(range(np.sum(klim)),
b123_s[klim][ijl],
c='C1',
s=5,
label='z-space')
sub.plot(range(np.sum(klim)), b123_s[klim][ijl], c='C1')
print(b123_s[klim][ijl] / b123[klim][ijl]).flatten()
sub.legend(loc='upper right', markerscale=4, handletextpad=0., fontsize=20)
sub.set_ylabel('$B(k_1, k_2, k_3)$', fontsize=25)
sub.set_yscale('log')
sub.set_xlabel(r'$k_1 \le k_2 \le k_3$ triangle indices', fontsize=25)
sub.set_xlim([0, np.sum(klim)])
fig.savefig(''.join([UT.dat_dir(), 'qpm/B123_aemulus_rzspace.png']),
bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
sub.scatter(range(np.sum(klim)),
q123[klim][ijl],
c='k',
s=2,
label='real-space')
sub.plot(range(np.sum(klim)), q123[klim][ijl], c='k', lw=1)
sub.scatter(range(np.sum(klim)),
q123_s[klim][ijl],
c='C1',
s=2,
label='redshift-space')
sub.plot(range(np.sum(klim)), q123_s[klim][ijl], c='C1', lw=1)
sub.legend(loc='lower right',
handletextpad=0.2,
markerscale=10,
fontsize=20)
sub.set_ylabel('$Q(k_1, k_2, k_3)$', fontsize=25)
sub.set_xlabel('$k_1 > k_2 > k_3$ triangle indices', fontsize=25)
sub.set_xlim([0, np.sum(klim)])
sub.set_ylim([0., 1.])
fig.savefig(''.join([UT.dat_dir(), 'qpm/Q123_aemulus_rzspace.png']),
bbox_inches='tight')
return None
def QPM_AEM(rsd=False):
str_rsd = ''
if rsd: str_rsd = '.rsd'
f_pell = lambda sim: ''.join([
UT.dat_dir(), sim, '/pySpec.Plk.halo.mlim1e13.Ngrid360', str_rsd,
'.dat'
])
f_pnkt = lambda sim: ''.join([
UT.dat_dir(), sim, '/pySpec.Plk.halo.mlim1e13.Ngrid360.nbodykit',
str_rsd, '.dat'
])
f_b123 = lambda sim: ''.join([
UT.dat_dir(), sim,
'/pySpec.B123.halo.mlim1e13.Ngrid360.Nmax40.Ncut3.step3.pyfftw',
str_rsd, '.dat'
])
Lbox_qpm = 1050.
Lbox_aem = 1050.
kf_qpm = 2. * np.pi / Lbox_qpm
kf_aem = 2. * np.pi / Lbox_aem
fig = plt.figure(figsize=(5, 5))
sub = fig.add_subplot(111)
k, p0k = np.loadtxt(f_pell('aemulus'),
unpack=True,
skiprows=1,
usecols=[0, 1])
klim = (k < 0.3)
sub.plot(k[klim], p0k[klim], c='k', lw=1, label='Aemulus')
k, p0k = np.loadtxt(f_pnkt('aemulus'),
unpack=True,
skiprows=1,
usecols=[0, 1])
klim = (k < 0.3)
sub.plot(k[klim], p0k[klim], c='k', ls='--', lw=1)
k, p0k = np.loadtxt(f_pell('qpm'), unpack=True, skiprows=1, usecols=[0, 1])
klim = (k < 0.3)
sub.plot(k[klim], p0k[klim], c='C1', lw=1, label='QPM')
k, p0k = np.loadtxt(f_pnkt('qpm'), unpack=True, skiprows=1, usecols=[0, 1])
klim = (k < 0.3)
sub.plot(k[klim], p0k[klim], c='C1', ls='--', lw=1)
sub.legend(loc='upper right', fontsize=20)
sub.set_ylabel('$P_0(k)$', fontsize=25)
sub.set_yscale('log')
sub.set_xlabel('$k$', fontsize=25)
sub.set_xlim([8e-3, 0.5])
sub.set_xscale('log')
fig.savefig(''.join([UT.dat_dir(), 'qpm/p0k_qpm_aemulus', str_rsd,
'.png']),
bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, b123_sn = np.loadtxt(
f_b123('aemulus'), skiprows=1, unpack=True, usecols=range(10))
klim = ((i_k * kf_aem <= 0.22) & (i_k * kf_aem >= 0.03) &
(j_k * kf_aem <= 0.22) & (j_k * kf_aem >= 0.03) &
(l_k * kf_aem <= 0.22) & (l_k * kf_aem >= 0.03))
i_k, j_k, l_k = i_k[klim], j_k[klim], l_k[klim]
ijl = UT.ijl_order(i_k, j_k, l_k, typ='GM') # order of triangles
sub.scatter(range(np.sum(klim)),
b123[klim][ijl],
c='k',
s=5,
label='Aemulus')
sub.plot(range(np.sum(klim)), b123[klim][ijl], c='k')
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, b123_sn = np.loadtxt(
f_b123('qpm'), skiprows=1, unpack=True, usecols=range(10))
klim = ((i_k * kf_qpm <= 0.22) & (i_k * kf_qpm >= 0.03) &
(j_k * kf_qpm <= 0.22) & (j_k * kf_qpm >= 0.03) &
(l_k * kf_qpm <= 0.22) & (l_k * kf_qpm >= 0.03))
i_k, j_k, l_k, = i_k[klim], j_k[klim], l_k[klim]
ijl = UT.ijl_order(i_k, j_k, l_k, typ='GM') # order of triangles
sub.scatter(range(np.sum(klim)), b123[klim][ijl], c='C1', s=5, label='QPM')
sub.plot(range(np.sum(klim)), b123[klim][ijl], c='C1')
sub.legend(loc='upper right', markerscale=4, handletextpad=0., fontsize=20)
sub.set_ylabel('$B(k_1, k_2, k_3)$', fontsize=25)
sub.set_yscale('log')
sub.set_ylim([1e8, 6e9])
sub.set_xlabel(r'$k_1 \le k_2 \le k_3$ triangle indices', fontsize=25)
sub.set_xlim([0, np.sum(klim)])
fig.savefig(''.join(
[UT.dat_dir(), 'qpm/B123_qpm_aemulus', str_rsd, '.png']),
bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, b123_sn = np.loadtxt(
f_b123('aemulus'), skiprows=1, unpack=True, usecols=range(10))
sub.scatter(range(len(q123)), q123, c='k', s=2, label='Aemulus')
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, b123_sn = np.loadtxt(
f_b123('qpm'), skiprows=1, unpack=True, usecols=range(10))
sub.scatter(range(len(q123)), q123, c='C1', s=2, label='QPM')
sub.legend(loc='upper right', fontsize=20)
sub.set_ylabel('$Q(k_1, k_2, k_3)$', fontsize=25)
sub.set_xlabel('$k_1 > k_2 > k_3$ triangle indices', fontsize=25)
sub.set_xlim([0, len(q123)])
sub.set_ylim([0., 1.])
fig.savefig(''.join(
[UT.dat_dir(), 'qpm/Q123_qpm_aemulus', str_rsd, '.png']),
bbox_inches='tight')
return None
def fastpm_v_tng(z,
str_flag='',
mh_lim=15.,
Lbox=205.,
Nmax=40,
Ncut=3,
step=3):
''' make plots that compare the powerspectrum and bispectrum of
fastpm and illustris tng
'''
dir_fpm = os.path.join(UT.dat_dir(), 'fastpm')
f_fpm = ('halocat_FastPM_40step_N250_IC500_B2_z%.2f%s.mlim%.fe10' %
(z, str_flag, mh_lim))
f_tng = ('halocat_TNG300Dark_z%.2f.mlim%.fe10' % (z, mh_lim))
print('FastPM file: %s' % f_fpm)
print('Illustris TNG file: %s' % f_tng)
f_pell = lambda f_halo: ('%s/pySpec.Plk.%s.Lbox%.f.Ngrid360.dat' %
(dir_fpm, f_halo, Lbox))
f_pnkt = lambda f_halo: ('%s/pySpec.Plk.%s.Lbox%.f.Ngrid360.nbodykit.dat' %
(dir_fpm, f_halo, Lbox))
f_b123 = lambda f_halo: (
'%s/pySpec.Bk.%s.Lbox%.f.Ngrid360.step%i.Ncut%i.Nmax%i.dat' %
(dir_fpm, f_halo, Lbox, step, Ncut, Nmax))
kf = 2. * np.pi / Lbox
# P(k) comparison
fig = plt.figure(figsize=(5, 5))
sub = fig.add_subplot(111)
k, p0k = np.loadtxt(f_pell(f_fpm), unpack=True, skiprows=1, usecols=[0, 1])
sub.plot(k, p0k, c='k', lw=1, label='FastPM')
k, p0k_fpm = np.loadtxt(f_pnkt(f_fpm),
unpack=True,
skiprows=1,
usecols=[0, 1])
sub.plot(k, p0k_fpm, c='k', ls='--', lw=1)
k, p0k = np.loadtxt(f_pell(f_tng), unpack=True, skiprows=1, usecols=[0, 1])
sub.plot(k, p0k, c='C1', lw=1, label='Illustris TNG')
k, p0k_tng = np.loadtxt(f_pnkt(f_tng),
unpack=True,
skiprows=1,
usecols=[0, 1])
sub.plot(k, p0k_tng, c='C1', ls='--', lw=1)
print(p0k_fpm / p0k_tng)[k < 0.2] - 1.
sub.legend(loc='lower left', fontsize=20)
sub.set_ylabel('$P_0(k)$', fontsize=25)
sub.set_yscale('log')
sub.set_ylim([1e0, 1e4])
sub.set_xlabel('$k$', fontsize=25)
sub.set_xscale('log')
sub.set_xlim([1e-2, 10.])
fig.savefig(os.path.join(dir_fpm,
'p0k_fpm_tng_z%.2f%s.png' % (z, str_flag)),
bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
for fh, lbl, c in zip([f_fpm, f_tng], ['FastPM', 'Illustris TNG'],
['k', 'C1']):
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, b123_sn = np.loadtxt(
f_b123(fh), skiprows=1, unpack=True, usecols=range(10))
klim = ((i_k * kf <= 1.) & (i_k * kf >= 0.01) & (j_k * kf <= 1.) &
(j_k * kf >= 0.01) & (l_k * kf <= 1.) & (l_k * kf >= 0.01))
i_k, j_k, l_k = i_k[klim], j_k[klim], l_k[klim]
ijl = UT.ijl_order(i_k, j_k, l_k, typ='GM') # order of triangles
sub.scatter(range(np.sum(klim)), b123[klim][ijl], c=c, s=5, label=lbl)
sub.plot(range(np.sum(klim)), b123[klim][ijl], c=c)
sub.legend(loc='upper right', markerscale=4, handletextpad=0., fontsize=20)
sub.set_ylabel('$B(k_1, k_2, k_3)$', fontsize=25)
sub.set_yscale('log')
sub.set_ylim([1e3, 5e6])
sub.set_xlabel(r'$k_1 \le k_2 \le k_3$ triangle indices', fontsize=25)
sub.set_xlim([0, np.sum(klim)])
fig.savefig(os.path.join(dir_fpm,
'bk_fpm_tng_z%.2f%s.png' % (z, str_flag)),
bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
for fh, lbl, c in zip([f_fpm, f_tng], ['FastPM', 'Illustris TNG'],
['k', 'C1']):
i_k, j_k, l_k, p0k1, p0k2, p0k3, b123, q123, counts, b123_sn = np.loadtxt(
f_b123(fh), skiprows=1, unpack=True, usecols=range(10))
klim = ((i_k * kf >= 0.01) & (j_k * kf >= 0.01) & (l_k * kf >= 0.01))
i_k, j_k, l_k = i_k[klim], j_k[klim], l_k[klim]
ijl = UT.ijl_order(i_k, j_k, l_k, typ='GM') # order of triangles
sub.scatter(range(np.sum(klim)), q123[klim][ijl], c=c, s=5, label=lbl)
sub.plot(range(np.sum(klim)), q123[klim][ijl], c=c)
sub.legend(loc='upper right', markerscale=4, handletextpad=0., fontsize=20)
sub.set_ylabel('$Q(k_1, k_2, k_3)$', fontsize=25)
sub.set_ylim([0., 1.])
sub.set_xlabel(r'$k_1 \le k_2 \le k_3$ triangle indices', fontsize=25)
sub.set_xlim([0, np.sum(klim)])
fig.savefig(os.path.join(dir_fpm,
'qk_fpm_tng_z%.2f%s.png' % (z, str_flag)),
bbox_inches='tight')
return None
def QPM_AEM(rsd=False):
str_rsd = ''
str_rsd_pdf = ''
if rsd:
str_rsd = '.rsd'
str_rsd_pdf = '_rsd'
f_pell = lambda sim: os.path.join(
dir_dat, sim, 'pySpec.Plk.halo.mlim1e13.Lbox1050.Ngrid360%s.dat' %
str_rsd)
f_pnkt = lambda sim: os.path.join(
dir_dat, sim,
'pySpec.Plk.halo.mlim1e13.Lbox1050.Ngrid360.nbodykit%s.dat' % str_rsd)
f_b123 = lambda sim: os.path.join(
dir_dat, sim,
'pySpec.B123.halo.mlim1e13.Lbox1050.Ngrid360.Nmax40.Ncut3.step3.pyfftw%s.dat'
% str_rsd)
Lbox = 1050.
kf = 2. * np.pi / 1050
fig = plt.figure(figsize=(5, 5))
sub = fig.add_subplot(111)
k, p0k = np.loadtxt(f_pell('aemulus'),
unpack=True,
skiprows=1,
usecols=[0, 1])
klim = (k < 0.3)
sub.plot(k[klim], p0k[klim], c='k', lw=1, label='Aemulus')
k, p0k = np.loadtxt(f_pnkt('aemulus'),
unpack=True,
skiprows=1,
usecols=[0, 1])
klim = (k < 0.3)
sub.plot(k[klim], p0k[klim], c='k', ls='--', lw=1)
k, p0k = np.loadtxt(f_pell('qpm'), unpack=True, skiprows=1, usecols=[0, 1])
klim = (k < 0.3)
sub.plot(k[klim], p0k[klim], c='C1', lw=1, label='QPM')
k, p0k = np.loadtxt(f_pnkt('qpm'), unpack=True, skiprows=1, usecols=[0, 1])
klim = (k < 0.3)
sub.plot(k[klim], p0k[klim], c='C1', ls='--', lw=1)
sub.legend(loc='upper right', fontsize=20)
sub.set_ylabel('$P_0(k)$', fontsize=25)
sub.set_yscale('log')
sub.set_xlabel('$k$', fontsize=25)
sub.set_xlim([8e-3, 0.5])
sub.set_xscale('log')
fig.savefig(os.path.join(dir_dat, 'qpm',
'p0k_qpm_aemulus%s.png' % str_rsd),
bbox_inches='tight')
i_k, j_k, l_k, _, _, _, b123_aem, q123_aem, counts_aem, _ = \
np.loadtxt(f_b123('aemulus'), skiprows=1, unpack=True,
usecols=range(10))
i_k, j_k, l_k, _, _, _, b123_qpm, q123_qpm, counts_qpm, _ = \
np.loadtxt(f_b123('qpm'), skiprows=1, unpack=True,
usecols=range(10))
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
#klim = ((i_k*kf <= 0.22) & (i_k*kf >= 0.03) &
# (j_k*kf <= 0.22) & (j_k*kf >= 0.03) &
# (l_k*kf <= 0.22) & (l_k*kf >= 0.03))
klim = ((i_k * kf <= 0.22) & (j_k * kf <= 0.22) & (l_k * kf <= 0.22))
print('%i triangle configurations' % np.sum(klim))
i_k, j_k, l_k = i_k[klim], j_k[klim], l_k[klim]
b123_aem = b123_aem[klim]
q123_aem = q123_aem[klim]
b123_qpm = b123_qpm[klim]
q123_qpm = q123_qpm[klim]
counts_aem = counts_aem[klim]
counts_qpm = counts_qpm[klim]
ijl = UT.ijl_order(i_k, j_k, l_k, typ='GM') # order of triangles
sub.scatter(range(np.sum(klim)),
b123_aem[ijl],
c='k',
s=5,
label='Aemulus')
sub.plot(range(np.sum(klim)), b123_aem[ijl], c='k')
sub.scatter(range(np.sum(klim)), b123_qpm[ijl], c='C1', s=5, label='QPM')
sub.plot(range(np.sum(klim)), b123_qpm[ijl], c='C1')
sub.legend(loc='upper right', markerscale=4, handletextpad=0., fontsize=20)
sub.set_ylabel('$B(k_1, k_2, k_3)$', fontsize=25)
sub.set_yscale('log')
sub.set_ylim([1e8, 1e10])
sub.set_xlabel(r'$k_1 \le k_2 \le k_3$ triangle indices', fontsize=25)
sub.set_xlim([0, np.sum(klim)])
fig.savefig(os.path.join(dir_dat, 'qpm',
'B123_qpm_aemulus%s.png' % str_rsd),
bbox_inches='tight')
fig.savefig(os.path.join(dir_dat, 'qpm',
'B123_qpm_aemulus%s.pdf' % str_rsd_pdf),
bbox_inches='tight')
fig = plt.figure(figsize=(10, 5))
sub = fig.add_subplot(111)
sub.scatter(range(np.sum(klim)),
q123_aem[ijl],
c='k',
s=2,
label='Aemulus')
sub.plot(range(np.sum(klim)), q123_aem[ijl], c='k')
sub.scatter(range(np.sum(klim)), q123_qpm[ijl], c='C1', s=2, label='QPM')
sub.plot(range(np.sum(klim)), q123_qpm[ijl], c='C1')
sub.legend(loc='lower left', handletextpad=0., markerscale=4, fontsize=25)
sub.set_ylabel('$Q(k_1, k_2, k_3)$', fontsize=25)
sub.set_xlabel(r'$k_1 \le k_2 \le k_3$ triangle indices', fontsize=25)
#sub.set_xlabel('$k_1 > k_2 > k_3$ triangle indices', fontsize=25)
sub.set_xlim([0, np.sum(klim)])
sub.set_ylim([0., 1.])
fig.savefig(os.path.join(dir_dat, 'qpm',
'Q123_qpm_aemulus%s.png' % str_rsd),
bbox_inches='tight')
fig.savefig(os.path.join(dir_dat, 'qpm',
'Q123_qpm_aemulus%s.pdf' % str_rsd_pdf),
bbox_inches='tight')
# plot Q shape triangle plot
nbin = 13
x_bins = np.linspace(0., 1., nbin + 1)
y_bins = np.linspace(0.5, 1., (nbin // 2) + 1)
print(y_bins)
fig = plt.figure(figsize=(12, 4))
sub = fig.add_subplot(121)
Bgrid = Plots._BorQgrid(
l_k.astype(float) / i_k.astype(float),
j_k.astype(float) / i_k.astype(float), q123_qpm, counts_qpm, x_bins,
y_bins)
bplot = plt.pcolormesh(x_bins,
y_bins,
Bgrid.T,
vmin=0,
vmax=1,
cmap='RdBu')
sub.text(0.95,
0.05,
'QPM',
ha='right',
va='bottom',
transform=sub.transAxes,
fontsize=25)
sub.set_ylabel('$k_2/k_1$', fontsize=25)
sub = fig.add_subplot(122)
Bgrid = Plots._BorQgrid(
l_k.astype(float) / i_k.astype(float),
j_k.astype(float) / i_k.astype(float), q123_aem, counts_aem, x_bins,
y_bins)
bplot = plt.pcolormesh(x_bins,
y_bins,
Bgrid.T,
vmin=0,
vmax=1,
cmap='RdBu')
sub.text(0.95,
0.05,
'Aemulus',
ha='right',
va='bottom',
transform=sub.transAxes,
fontsize=25)
bkgd = fig.add_subplot(111, frameon=False)
bkgd.tick_params(labelcolor='none',
top=False,
bottom=False,
left=False,
right=False)
bkgd.set_xlabel(r'$k_3/k_1$', labelpad=10, fontsize=25)
cbar_ax = fig.add_axes([0.925, 0.15, 0.01, 0.7])
cbar = fig.colorbar(bplot, cax=cbar_ax)
cbar.set_label('$Q(k_1, k_2, k_3)$', labelpad=10, rotation=90, fontsize=20)
fig.subplots_adjust(wspace=0.15)
fig.savefig(os.path.join(dir_dat, 'qpm',
'Q123_shape_qpm_aemulus%s.png' % str_rsd),
bbox_inches='tight')
fig.savefig(os.path.join(dir_dat, 'qpm',
'Q123_shape_qpm_aemulus%s.pdf' % str_rsd_pdf),
bbox_inches='tight')
return None