def test_emulator():
#Unpickle the emulator
emulator = Emulator.load("analysis.p")
emulator.train()
#Set the model
emulator.set_to_model(np.array([ 0.26,-2.66,1.31,0.96]))
ell = emulator.feature_label
Pell = emulator._current_predicted_feature
#Select the new multipoles
l = np.arange(900.0,3000.0,200.0)
#Emulate the power spectrum
Pl = emulator.emulate(l)
#Plot
fig,ax = plt.subplots()
ax.plot(ell,ell*(ell+1)*Pell/(2*np.pi),label="Fully emulated")
ax.plot(l,l*(l+1)*Pl/(2.0*np.pi),label="New multipoles",color="yellow")
ax.set_xlabel(r"$l$")
ax.set_ylabel(r"$l(l+1)P_l/2\pi$")
ax.set_yscale("log")
ax.legend(loc="upper left")
fig.savefig("emulated_power.png")
def test_emulator():
#Unpickle the emulator
emulator = Emulator.load("analysis.p")
emulator.train()
#Set the model
emulator.set_to_model(np.array([0.26, -2.66, 1.31, 0.96]))
ell = emulator.feature_label
Pell = emulator._current_predicted_feature
#Select the new multipoles
l = np.arange(900.0, 3000.0, 200.0)
#Emulate the power spectrum
Pl = emulator.emulate(l)
#Plot
fig, ax = plt.subplots()
ax.plot(ell, ell * (ell + 1) * Pell / (2 * np.pi), label="Fully emulated")
ax.plot(l,
l * (l + 1) * Pl / (2.0 * np.pi),
label="New multipoles",
color="yellow")
ax.set_xlabel(r"$l$")
ax.set_ylabel(r"$l(l+1)P_l/2\pi$")
ax.set_yscale("log")
ax.legend(loc="upper left")
fig.savefig("emulated_power.png")
def test_reparametrize():
#Unpickle the emulator
emulator = Emulator.load("analysis.p")
#Get the old parametrizations
Om = emulator.parameter_set[:,0]
w = emulator.parameter_set[:,1]
si8 = emulator.parameter_set[:,2]
#Define the reparametrizer ( (Om,si8) -> (si8 x Om^0.5))
def formatter(data,n):
print("Omega_m exponent={0:.1f}".format(n))
return np.array([data[:,1],data[:,2]*(data[:,0]**n)]).transpose()
#Reparametrize the parameter space
emulator.reparametrize(formatter,0.5)
#Check that everything worked
assert (emulator.parameter_set[:,0]==w).all()
assert (emulator.parameter_set[:,1]==(si8*(Om**0.5))).all()
def test_reparametrize():
#Unpickle the emulator
emulator = Emulator.load("analysis.p")
#Get the old parametrizations
Om = emulator.parameter_set[:, 0]
w = emulator.parameter_set[:, 1]
si8 = emulator.parameter_set[:, 2]
#Define the reparametrizer ( (Om,si8) -> (si8 x Om^0.5))
def formatter(data, n):
print("Omega_m exponent={0:.1f}".format(n))
return np.array([data[:, 1], data[:, 2] * (data[:, 0]**n)]).transpose()
#Reparametrize the parameter space
emulator.reparametrize(formatter, 0.5)
#Check that everything worked
assert (emulator.parameter_set[:, 0] == w).all()
assert (emulator.parameter_set[:, 1] == (si8 * (Om**0.5))).all()
