#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Dec 4 11:06:35 2018 @author: engels """ import wabbit_tools import sys time, x0, dx, box, data, treecode = wabbit_tools.read_wabbit_hdf5(sys.argv[1]) data = wabbit_tools.overwrite_block_data_with_level(treecode, data) wabbit_tools.write_wabbit_hdf5(sys.argv[2], time, x0, dx, box, data, treecode)
def write_mat_file_wabbit(args,
outfile,
times,
timestamps,
prefixes,
scalars,
vectors,
directory,
mpicommand="mpirun -np 2 ",
level=None):
print('-------------------------')
print('- WABBIT module matlab -')
print('-------------------------')
# use any file to get blocksize and dimensionality
file = directory + prefixes[0] + '_' + timestamps[0] + '.h5'
# open h5 file
f = h5py.File(file)
# get the dataset handle
dset_id = f.get('blocks')
res = dset_id.shape
dim = len(res) - 1
densedir = directory + "/densedir%d/" % len(timestamps)
if not os.path.exists(densedir):
os.makedirs(densedir)
# loop over time steps
all_data = []
data_list = {
"names": prefixes,
"data": [],
"time": times,
"domain_size": np.zeros(dim)
}
for prefix in prefixes:
data_tmp = []
for i in range(len(timestamps)):
#use any of our files at the same timestamp to determine number of blocks
file = directory + prefix + '_' + timestamps[i] + '.h5'
file_dense = densedir + prefix + '_' + timestamps[i] + '.h5'
if not level:
command = mpicommand + " " + \
"wabbit-post --sparse-to-dense "+file + " "+file_dense+ " "
else:
command = mpicommand + " " + \
"wabbit-post --sparse-to-dense "+file + " "+file_dense+ " " \
+ level + " 4" #+ order
command = command + " >> " + densedir + "wabbit-post.log"
print("\n", command, "\n")
ierr = os.system(command)
if (ierr > 0):
warn(
"Need wabbit for sparse-to-dense! Please export wabbit in PATH. export PATH=$PATH:/path/to/wabbit/"
)
return 0
time, x0, dx, box, data, treecode = read_wabbit_hdf5(file_dense)
data_dense, box_dense = dense_matrix(x0, dx, data, treecode, dim)
data_tmp.append(data_dense)
if os.path.isfile(file_dense):
os.remove(file_dense)
else: ## Show an error ##
print("Error: %s file not found" % file_dense)
data_list["domain_size"] = box_dense
data_list["dx"] = dx
data_list["data"].append(np.asarray(data_tmp))
# save everything in one file
savemat(directory + "/" + outfile, data_list)
# remove temporal directory
try:
shutil.rmtree(densedir)
except OSError as e:
print("Error: %s : %s" % (densedir, e.strerror))
mode_lists = [
"mode1_list.txt", "mode2_list.txt", "mode3_list.txt", "mode4_list.txt"
]
reconstructed_iteration = 7
# read data
files = sorted(glob.glob(data["folder"] + "Jmax" + str(jmax) + "/u*.h5"))[275:]
p_list = []
t_list = []
for fname_in in files:
path, fname = os.path.split(fname_in)
folder = data['folder'] + "/Jmax" + str(jmax - 1) + "/"
fname_out = folder + fname.split("_")[0]
time, x0, dx, box, datafield, treecode = wt.read_wabbit_hdf5(fname_in)
field, box = wt.dense_matrix(x0, dx, datafield, treecode)
p_list.append(field[786, 2048])
t_list.append(time)
field = np.squeeze(field)
Bs = wt.field_shape_to_bs(field.shape, jmax)
box = box[::-1]
fname = wt.dense_to_wabbit_hdf5(field, fname_out, Bs, box, time)
# plt.figure(55)
# plt.pcolormesh(field)
# plt.axis("image")
# plt.xticks([])
# plt.yticks([])
# plt.savefig(fname.replace("h5","png"))
jmin, jmax = wabbit_tools.get_max_min_level(treecode)
# note zero-based indexing
level = np.zeros([jmax])
for i in range(N):
J = wabbit_tools.treecode_level(treecode[i, :]) - 1 # zero-based
level[J] += 1
for J in np.arange(start=jmin, stop=jmax):
print("J=%2i Nb=%7i " % (J + 1, level[J]))
else:
time, x0, dx, box, data, treecode = wabbit_tools.read_wabbit_hdf5(file)
if args.mpirank:
fid = h5py.File(file, 'r')
# read procs array from file
b = fid['procs'][:]
procs = np.array(b, dtype=float)
fid.close()
if len(data.shape) == 4:
N = treecode.shape[0]
for i in range(N):
data[i, :, :, :] = float(procs[i])
elif len(data.shape) == 3:
print("\n", dense_command, "\n\n")
success = os.system(dense_command) # execute command
#wt.plot_wabbit_file(file_dense,savepng=True)
if success != 0:
print("command did not execute successfully")
return
# delete reference file
os.system("rm " + file_coarse)
return file_dense
file = wabbit_adapt(dirs, params, wabbit_setup)
# Grab some test data.
time, x0, dx, box, field, treecode = wt.read_wabbit_hdf5(file)
field, box = wt.dense_matrix(x0, dx, field, treecode)
# %%
plt.close("all")
fig1 = plt.figure()
ax1 = fig1.gca(projection='3d')
Nxy = field.shape
Z = field[Nxy[0] // 3:-Nxy[0] // 3:40, Nxy[1] // 3:-Nxy[1] // 3:40]
x = np.linspace(0, params.domain.L[0], Z.shape[0])
y = np.linspace(0, params.domain.L[1], Z.shape[1])
[X, Y] = np.meshgrid(x, y)
# Plot a basic wireframe.
#RHO =ONES*data[:,1]
#V = ONES*data[:,2]
#U = np.zeros([256, 256])
#plt.plot(data[:,2])
#Bs = np.asarray([33,33])
#box_size = np.asarray([1,1.7])
#
#wtools.dense_to_wabbit_hdf5(P.T, 'p' , Bs, box_size, 0, 0)
#wtools.dense_to_wabbit_hdf5(U.T, 'Ux' , Bs, box_size, 0, 0)
#wtools.dense_to_wabbit_hdf5(RHO.T, 'rho' , Bs, box_size, 0, 0)
#wtools.dense_to_wabbit_hdf5(V.T, 'Uy' , Bs, box_size, 0, 0)
#wtools.plot_wabbit_file('rho_000000000000.h5')
#%%
k = wtools.read_wabbit_hdf5('rho_000000000000.h5')
rho_feld = wtools.dense_matrix(k[1], k[2], k[4], k[5], dim=2)[0]
plt.plot(rho_feld[:, 0])
#%%
#wtools.plot_wabbit_file('/home/sparr/devel/Guderley_valid/wabbit_sim/free_timestep/rho_fil/rho_000000500000.h5')
#Bs = np.asarray([33,33])
#box_size = np.asarray([1.7,1])
k1 = wtools.read_wabbit_hdf5(
'/home/sparr/devel/rot_valid/pressure_ring/p_000000400000.h5')
k2 = wtools.read_wabbit_hdf5(
'/home/sparr/devel/rot_valid/new_presswave/p_fil/p_000000400000.h5')