gadget_io.py

from lenstools.simulations import Gadget2SnapshotDE

import numpy as np
import matplotlib.pyplot as plt

from astropy.units import Mpc,m,s

########################Write#################################

#Create an empty gadget snapshot
snap = Gadget2SnapshotDE()

#Generate random positions and velocities
NumPart = 32**3
x = np.random.normal(loc=7.0,scale=5.0,size=(NumPart,3)) * Mpc
v = np.random.uniform(-1,1,size=(NumPart,3)) * m / s

#Put the particles in the snapshot
snap.setPositions(x)
snap.setVelocities(v)

#Generate minimal header
snap.setHeaderInfo()

#Write the snapshot
snap.write("gadget_ic")

######################Read and visualize#########################

#Open the snapshot
snap = Gadget2SnapshotDE.open("gadget_ic")

#Visualize the header
print(snap.header)

#Visualize the snapshot
snap.visualize(s=1)
snap.savefig("snapshot.png")
snap.close()

#################Actual Gadget snapshot##########################
###################Read and visualize############################

#Open the snapshot
snap = Gadget2SnapshotDE.open("../Test/Data/gadget/snapshot_001")

#Visualize the header
print(snap.header)

#Get positions and velocities
snap.getPositions()
snap.getVelocities()

#Visualize the snapshot
snap.visualize(s=1)
snap.savefig("snapshot_gadget.png")

#Measure the power spectrum
k_edges = np.arange(1.0,20.0,0.5) * (1/snap.Mpc_over_h)
k,Pk = snap.powerSpectrum(k_edges,resolution=64)

#Plot
fig,ax = plt.subplots() 

ax.plot(k,Pk)
ax.set_yscale("log")
ax.set_xscale("log")
ax.set_xlabel(r"$k(h\mathrm{Mpc}^{-1})$")
ax.set_ylabel(r"$P_k(h^{-3}\mathrm{Mpc}^3)$")
fig.savefig("snapshot_power_spectrum.png")

snap.close()