def avg_dump_dir(dirpath,
rmin,
rmax,
zmin,
zmax,
fix_ghosts=False,
N2CPU=2,
N3CPU=11,
nproc=None):
"Average dump data in directory. Save 2d files to same directory."
print("Mapping dumps in {} from 3d to 2d...".format(dirpath))
fnams = io.get_dumps_full(dirpath)
hdr = io.load_hdr(fnams[0])
geom = io.load_geom(hdr)
inputs = [(fnam,rmin,rmax,zmin,zmax,fix_ghosts,N2CPU,N3CPU,geom) \
for fnam in fnams]
p = Pool(processes=nproc)
p.map(_avg_dump_file_worker, inputs)
if MODES[n] == 3: # FAST
dvar[0] = 0.476395427447
dvar[1] = 0.635193903263
dvar[2] = -0.102965815319
dvar[3] = -0.316873207561
dvar[5] = 0.359559114174
dvar[6] = -0.359559114174
dvar *= amp
# RUN PROBLEM FOR EACH RESOLUTION AND ANALYZE RESULT
for m in xrange(len(RES)):
print ['./bhlight_' + str(RES[m]), '-p', 'param_template.dat']
call(['./bhlight_' + str(RES[m]), '-p', 'param_template.dat'])
dfiles = np.sort(glob.glob('dumps/dump*.h5'))
hdr = io.load_hdr(dfiles[-1])
geom = io.load_geom(hdr, recalc=True)
dump = io.load_dump(dfiles[-1],geom)
X1 = geom['x'][:,:,0]
X2 = geom['y'][:,:,0]
dvar_code = []
dvar_code.append(dump['RHO'][:,:,0] - var0[0])
dvar_code.append(dump['UU'][:,:,0] - var0[1])
dvar_code.append(dump['U1'][:,:,0] - var0[2])
dvar_code.append(dump['U2'][:,:,0] - var0[3])
dvar_code.append(dump['U3'][:,:,0] - var0[4])
dvar_code.append(dump['B1'][:,:,0] - var0[5])
dvar_code.append(dump['B2'][:,:,0] - var0[6])
dvar_code.append(dump['B3'][:,:,0] - var0[7])
#dvar_sol = []
num_cpus = multiprocessing.cpu_count()
os.environ['OMP_NUM_THREADS'] = str(int(np.max([2, num_cpus / num_mpi])))
# RUN EXECUTABLE
os.chdir(TMP_DIR)
args = ['./bhlight', '-p', 'param_template.dat']
if MPI:
bcall(args, str(num_mpi))
else:
bcall(args)
os.chdir('../')
# READ SIMULATION OUTPUT
dfiles = np.sort(glob.glob(os.path.join(TMP_DIR, '') + '/dumps/dump*.h5'))
Nd = len(dfiles)
hdr = io.load_hdr(dfiles[0])
geom = io.load_geom(hdr)
dump = io.load_dump(dfiles[-1], geom)
nuLnu = dump['nuLnu']
if np.any(np.abs(nuLnu[1:, :, :, :]) >= 1e-15):
nuLnu = np.sum(nuLnu, axis=0)
else:
nuLnu = nuLnu[0]
def make_1d(tensor, axis):
assert axis in [0, 1, 2]
assert len(tensor.shape) == 3
if axis == 0:
return np.sum(np.sum(tensor, axis=-1), axis=-1)
import hdf5_to_dict as io
import sys
preferred_keys = [
'N1', 'N2', 'N3', 'a', 'M_unit', 'B_unit', 'L_unit', 'Ne_unit'
]
if len(sys.argv) != 2:
print('ERROR format is')
print(' python hdr.py [filename]')
sys.exit()
fnam = sys.argv[1]
hdr = io.load_hdr(fnam)
used_keys = []
def print_val(vnam):
if vnam in hdr.keys() and vnam not in used_keys:
format_string = '%e' if type(hdr[vnam]) is float else '%s'
print(vnam, '=', format_string % hdr[vnam])
used_keys.append(vnam)
for k in preferred_keys:
print_val(k)
for k in hdr.keys():
print_val(k)
help=('Number of parallel processe to use. ' +
'If not set, defaults to all available cores.'))
args = parser.parse_args()
dfold = util.sanitize_path(args.dumpfolder)
if not os.path.exists(dfold):
print('ERROR Folder ' + dfnam + ' does not exist!')
sys.exit()
tmpdir = 'FRAMES'
util.safe_remove(tmpdir)
os.mkdir(tmpdir)
dfnams = io.get_dumps_full(dfold)
hdr = io.load_hdr(dfnams[0])
geom = io.load_geom(hdr)
num_files = len(dfnams)
def make_frame(pair):
i, d = pair
gc.collect()
print("frame %d/%d" % (i, num_files))
make_snap(d,
args.variable,
args.coords,
args.size,
args.cmap,
args.log,
os.path.join(tmpdir, 'frame_%08d.png' % i),
os.chdir(TMP_DIR)
run_args = ['./bhlight', '-p', 'param_template.dat']
if MPI:
NPROC = 4
import psutil
NCORE = psutil.cpu_count(logical=False)
NTHREADS = (max(NCORE / NPROC, 1))
os.environ['OMP_NUM_THREADS'] = '%d' % NTHREADS
bcall(run_args, int(NPROC), stdin=DEVNULL)
else:
bcall(run_args)
os.chdir('../')
# load simulation output
dumps = sorted(glob.glob(os.path.join(TMP_DIR, '') + '/dumps/dump*.h5'))
hdr = io.load_hdr(dumps[0])
geom = io.load_geom(hdr)
N1, N2, N3 = [hdr[i] for i in ['N1', 'N2', 'N3']]
times = np.empty(len(dumps))
Yes = np.empty((len(dumps), N1, N2))
dump = io.load_dump(dumps[0])
x, y = geom['xf'][:, :, 0], geom['yf'][:, :, 0]
#STOPPED EDITING HERE
for i, d in enumerate(dumps):
dump = io.load_dump(d)
times[i] = dump['t']
Yes[i] = dump['Ye'].reshape(N1, N2)
times *= hdr['T_unit']
dvar[2] = -0.0832240462505
dvar[3] = -0.224080007379
dvar[4] = -0.224080007379
dvar[5] = 0.406380545676
dvar[6] = -0.203190272838
dvar[7] = -0.203190272838
dvar *= amp
# USE DUMPS IN FOLDERS OF GIVEN FORMAT
for m in xrange(len(RES)):
print '../dumps_' + str(RES[m]) + '_' + str(MODES[n])
os.chdir('../dumps_' + str(RES[m]) + '_' + str(MODES[n]))
dfile = np.sort(glob.glob('dump*.h5'))[-1]
hdr = io.load_hdr(dfile)
geom = io.load_geom(hdr, dfile)
dump = io.load_dump(hdr, geom, dfile)
X1 = dump['x']
X2 = dump['y']
X3 = dump['z']
dvar_code = []
dvar_code.append(dump['RHO'] - var0[0])
dvar_code.append(dump['UU'] - var0[1])
dvar_code.append(dump['U1'] - var0[2])
dvar_code.append(dump['U2'] - var0[3])
dvar_code.append(dump['U3'] - var0[4])
dvar_code.append(dump['B1'] - var0[5])
dvar_code.append(dump['B2'] - var0[6])
import util
import os
import matplotlib
import matplotlib.pyplot as plt
SADW = True
if len(sys.argv) < 3:
print('ERROR Format is')
print(' savg.py [/path/to/dumpfile] [variable] [SADW=True]')
sys.exit()
path = sys.argv[1]
vnam = sys.argv[2]
hdr = io.load_hdr(path)
geom = io.load_geom(hdr)
dump = io.load_dump(path, geom)
N1 = hdr['N1']
N2 = hdr['N2']
N3 = hdr['N3']
dx1 = hdr['dx'][1]
dx2 = hdr['dx'][2]
dx3 = hdr['dx'][3]
savg = np.zeros(N1)
for i in range(N1):
vol = 0
vol = (dump['RHO'][i, :, :] * dx2 * dx3 *
geom['gdet'][i, :, :]).sum(axis=-1).sum(axis=-1)
def make_snap(dfnam,
vnam,
coords,
size,
cmap,
logplot,
savefig,
label,
vmin,
vmax,
index=None,
geom=None):
if not os.path.exists(dfnam):
print('ERROR File ' + dfnam + ' does not exist!')
sys.exit()
import matplotlib
if savefig is not None and savefig:
matplotlib.use('Agg')
import matplotlib.pyplot as plt
import plot as bplt
import hdf5_to_dict as io
import numpy as np
font = {'size': 16}
matplotlib.rc('font', **font)
hdr = io.load_hdr(dfnam)
if geom is None:
geom = io.load_geom(hdr)
dump = io.load_dump(dfnam, geom=geom)
if not vnam in dump.keys():
print('ERROR Variable ' + vnam + ' is not contained in dump file!')
print('Available variables are:')
for key in dump.keys():
if type(dump[key]) is np.ndarray:
if (len(dump[key].shape) == 3
and dump[key].shape[0] == hdr['N1']
and dump[key].shape[1] == hdr['N2']
and dump[key].shape[2] == hdr['N3']):
print(key, end=' ')
print('')
sys.exit()
IS_3D = hdr['N3'] > 1
var = dump[vnam]
if index is not None:
var = var[..., index]
if logplot:
var = np.log10(var)
if label is None:
label = vnam
if index is not None:
label += '[{}]'.format(index)
if IS_3D:
if coords == 'mks':
fig, (a0, a1) = plt.subplots(1,
2,
gridspec_kw={'width_ratios': [1, 1]},
figsize=(12, 6))
elif coords == 'cart':
fig, (a0, a1) = plt.subplots(1,
2,
gridspec_kw={'width_ratios': [1, 1]},
figsize=(13, 7))
ax = a0
if coords == 'mks':
bplt.plot_X1X2(ax,
geom,
var,
dump,
cmap=cmap,
vmin=vmin,
vmax=vmax,
cbar=False,
label=label,
ticks=None,
shading='gouraud')
elif coords == 'cart':
bplt.plot_xz(ax,
geom,
var,
dump,
cmap=cmap,
vmin=vmin,
vmax=vmax,
cbar=False,
label=label,
ticks=None,
shading='gouraud')
ax.set_xlim([-size, size])
ax.set_ylim([-size, size])
ax = a1
if coords == 'mks':
bplt.plot_X1X3(ax,
geom,
var,
dump,
cmap=cmap,
vmin=vmin,
vmax=vmax,
cbar=True,
label=label,
ticks=None,
shading='gouraud')
elif coords == 'cart':
bplt.plot_xy(ax,
geom,
var,
dump,
cmap=cmap,
vmin=vmin,
vmax=vmax,
cbar=True,
label=label,
ticks=None,
shading='gouraud')
ax.set_xlim([-size, size])
ax.set_ylim([-size, size])
else:
if coords == 'mks':
fig, ax = plt.subplots(1, 1, figsize=(10, 10))
bplt.plot_X1X2(ax,
geom,
var,
dump,
cmap=cmap,
vmin=vmin,
vmax=vmax,
cbar=True,
label=label,
ticks=None,
shading='gouraud')
elif coords == 'cart':
fig, ax = plt.subplots(1, 1, figsize=(7, 10))
bplt.plot_xz(ax,
geom,
var,
dump,
cmap=cmap,
vmin=vmin,
vmax=vmax,
cbar=True,
label=label,
ticks=None,
shading='gouraud')
ax.set_xlim([0, size])
ax.set_ylim([-size, size])
if savefig == False:
plt.show()
else:
plt.savefig(savefig, bbox_inches='tight')
plt.cla()
plt.clf()
plt.close()
tstart = float(sys.argv[4])
if len(sys.argv) > 5:
tend = float(sys.argv[5])
# LOAD FILES
files1 = io.get_dumps_list(path1)
files2 = io.get_dumps_list(path2)
if len(files1) == 0 or len(files2) == 0:
util.warn("INVALID PATH TO DUMP FOLDER")
sys.exit(1)
frame_dir = "frames_compare_"+movie_type
util.make_dir(frame_dir)
hdr1 = io.load_hdr(files1[0])
hdr2 = io.load_hdr(files2[0])
geom1 = io.load_geom(hdr1, path1)
geom2 = io.load_geom(hdr2, path2)
# TODO diags from post?
# Load diagnostics from HARM itself
diag1 = io.load_log(path1)
diag2 = io.load_log(path2)
nthreads = util.calc_nthreads(hdr1)
if debug:
for i in range(len(files1)):
plot(i)
else:
util.run_parallel(plot, len(files1), nthreads)
dumpfile = sys.argv[1]
if len(sys.argv) > 3:
gridfile = sys.argv[2]
var = sys.argv[3]
elif len(sys.argv) > 2:
gridfile = None
var = sys.argv[2]
# Optionally take extra name
name = sys.argv[-1]
if UNITS and var not in ['Tp']:
M_unit = float(sys.argv[-1])
if gridfile is not None:
hdr = io.load_hdr(dumpfile)
geom = io.load_geom(hdr, gridfile)
dump = io.load_dump(dumpfile, hdr, geom)
else:
# Assumes gridfile in same directory
hdr, geom, dump = io.load_all(dumpfile)
# If we're plotting a derived variable, calculate + add it
if var in ['jcov', 'jsq']:
dump['jcov'] = np.einsum("...i,...ij->...j", dump['jcon'],
geom['gcov'][:, :, None, :, n])
dump['jsq'] = np.sum(dump['jcon'] * dump['jcov'], axis=-1)
elif var in ['divE2D']:
JE1g, JE2g = T_mixed(dump, 1, 0).mean(axis=-1) * geom['gdet'], T_mixed(
dump, 2, 0).mean(axis=-1) * geom['gdet']
face_JE1 = 0.5 * (JE1g[:-1, :] + JE1g[1:, :])
