import pylab as plt
rkey, ikey = amrex.get_particle_keys()
t = []
fee = []
fexR = []
fexI = []
fxx = []
pupt = []
files = sorted(glob.glob("plt[0-9][0-9][0-9][0-9][0-9]"))
print(files[0], files[-1])
nfiles = len(files)
idata, rdata = amrex.read_particle_data(files[0], ptype="neutrinos")
nparticles = len(rdata)
print("Detected " + str(nparticles) + " particles.")
t = np.zeros(nfiles)
fee = np.zeros((nparticles, nfiles))
fexR = np.zeros((nparticles, nfiles))
fexI = np.zeros((nparticles, nfiles))
fxx = np.zeros((nparticles, nfiles))
feebar = np.zeros((nparticles, nfiles))
fexRbar = np.zeros((nparticles, nfiles))
fexIbar = np.zeros((nparticles, nfiles))
fxxbar = np.zeros((nparticles, nfiles))
pupt = np.zeros((nparticles, nfiles))
for (fi, f) in zip(range(nfiles), files):
dx = 64. / 1024.
#ix = 500
basedir = "/global/project/projectdirs/m3018/Emu/PAPER/1D/converge_direction/1D_dir128"
directory = basedir + "/plt00300" #[basedir+"/plt00000",basedir+"/plt00300",basedir+"/plt04800"]
ds = yt.load(directory)
print(ds.current_time)
ad = ds.all_data()
f01 = ad['boxlib', "Fx01_Re"]
ix = np.argmin(f01)
print("ix=", ix, np.min(f01))
rkey, ikey = amrex.get_3flavor_particle_keys()
idata, rdata = amrex.read_particle_data(directory, ptype="neutrinos")
zvals = rdata[:, rkey["z"]]
locs = np.where((zvals < (ix + 1) * dx) & (zvals > ix * dx))
zvals = zvals[locs]
#fee = np.arctan2(rdata[:,rkey["f01_Im"]][locs],rdata[:,rkey["f01_Re"]][locs])
fee = rdata[:, rkey["f01_Re"]][locs]
pupx = rdata[:, rkey["pupx"]][locs]
pupy = rdata[:, rkey["pupy"]][locs]
pupz = rdata[:, rkey["pupz"]][locs]
pupt = rdata[:, rkey["pupt"]][locs]
xhat = pupx / pupt
yhat = pupy / pupt
zhat = pupz / pupt
latitude = np.arccos(zhat) - np.pi / 2.
longitude = np.arctan2(yhat, xhat)
print(np.min(fee), np.max(fee))
import numpy as np
import argparse
import amrex_plot_tools as amrex
parser = argparse.ArgumentParser()
parser.add_argument("plotfile", type=str, help="Name of plotfile to process.")
args = parser.parse_args()
if __name__ == "__main__":
import pylab as plt
x0 = []
y0 = []
idata, rdata = amrex.read_particle_data(args.plotfile, ptype="neutrinos")
for p in rdata:
x0.append(p[0])
y0.append(p[1])
fig = plt.gcf()
fig.set_size_inches(8, 8)
plt.plot(x0, y0, 'b.')
plt.axis((0., 1., 0., 1.))
ax = plt.gca()
ax.set_xlabel(r'$x$')
ax.set_ylabel(r'$y$')
plt.savefig('{}_neutrinos.png'.format(args.plotfile))
ad = ds.all_data()
grid_data = GridData(ad)
nlevels = len(header.grids)
assert nlevels==1
level = 0
ngrids = len(header.grids[level])
# average the angular power spectrum over many cells
# loop over all cells within each grid
spectrum = np.zeros((nl,2,6))
total_ncells = 0
for gridID in range(ngrids):
print(" grid",gridID+1,"/",ngrids)
# read particle data on a single grid
idata, rdata = amrex.read_particle_data(directory, ptype="neutrinos", level_gridID=(level,gridID))
# get list of cell ids
idlist = grid_data.get_particle_cell_ids(rdata)
# sort rdata based on id list
sorted_indices = idlist.argsort()
rdata = rdata[sorted_indices]
idlist = idlist[sorted_indices]
# split up the data into cell chunks
ncells = np.max(idlist)+1
nppc = len(idlist) // ncells
rdata = [ rdata[icell*nppc:(icell+1)*nppc,:] for icell in range(ncells)]
idlist = [idlist[icell*nppc:(icell+1)*nppc ] for icell in range(ncells)]
icell_list = [icell for icell in range(ncells)]