fpar.write("task='%s'\n" % task)
fpar.write("set ylabel '%s'\n" % label)
fpar.write("file='%s_set'\n" % task)
fpar.write('xr=%f\n' % (maxtime))
f.close()
fpar.close()
ftasks1d.close()
ftasks2d.close()
return
if __name__ == "__main__":
import pathlib
from docopt import docopt
from dedalus.tools import logging
from dedalus.tools import post
from dedalus.tools.parallel import Sync
args = docopt(__doc__)
output_path = pathlib.Path(args['--output']).absolute()
# Create output directory if needed
with Sync() as sync:
if sync.comm.rank == 0:
if not output_path.exists():
output_path.mkdir()
post.visit_writes(args['<files>'], main, output=output_path)
def read_data(files):
start_time = time.time()
def accumulate_files(filename, start, count, file_list):
if start == 0:
file_list.append(filename)
file_list = []
post.visit_writes(files, accumulate_files, file_list=file_list)
logger.debug(file_list)
data = {}
times = None
r = None
theta = None
color = int(len(file_list) > 0)
comm = MPI.COMM_WORLD.Split(color=color)
rank = comm.rank
size = comm.size
if color:
for file in file_list:
logger.debug("opening file: {}".format(file))
f = h5py.File(file, 'r')
data_slices = (slice(None), 0, slice(None), slice(None))
for task in f['tasks']:
if task[0] == '<' and task[
-1] == '>': #azavgs denoted with '<q>'
logger.info("task: {}".format(task))
if task in data:
data[task] = np.append(data[task],
f['tasks'][task][data_slices],
axis=0)
else:
data[task] = np.array(f['tasks'][task][data_slices])
if r is None or theta is None:
theta = f['tasks'][task].dims[2][0][:]
r = f['tasks'][task].dims[3][0][:]
if times is None:
times = f['scales/sim_time'][:]
else:
times = np.append(times, f['scales/sim_time'][:])
f.close()
else:
data = {'zero': np.zeros((1, 1, 1))}
times = np.zeros(1)
comm.Barrier()
n_global_time = np.array(0)
n_global_data = np.array(0)
data_set = data
global_data_set = {}
comm.Reduce([np.array(times.size), MPI.INT], [n_global_time, MPI.INT],
op=MPI.SUM,
root=0)
if rank == 0:
n_times_each = np.empty([size], dtype=np.int)
global_time = np.empty([n_global_time], dtype=np.float64)
else:
n_times_each = None
global_time = None
comm.Gather(np.array(times.size), n_times_each, root=0)
if rank == 0:
send_counts = tuple(n_times_each)
displacements = tuple(
np.append(np.zeros(1, dtype=np.int),
np.cumsum(n_times_each))[0:-1])
else:
send_counts = None
displacements = None
comm.Gatherv(times.astype(np.float64),
[global_time, send_counts, displacements, MPI.DOUBLE],
root=0)
for task in data_set:
data = data_set[task]
comm.Reduce([np.array(data.size), MPI.INT], [n_global_data, MPI.INT],
op=MPI.SUM,
root=0)
if rank == 0:
logger.info("{}: n_time = {}, n_data = {}".format(
task, n_global_time, n_global_data))
n_data_each = np.empty([size], dtype=np.int)
global_data = np.empty([
n_global_time,
] + list(data[0, :, :].shape),
dtype=np.float64)
logger.debug("{}, {}, {}".format(data.shape, global_time.shape,
global_data.shape))
else:
n_data_each = None
global_data = None
comm.Gather(np.array(data.size), n_data_each, root=0)
if rank == 0:
displacements = tuple(
np.append(np.zeros(1, dtype=np.int),
np.cumsum(n_data_each))[0:-1])
send_counts = tuple(n_data_each)
comm.Gatherv(data.astype(np.float64),
[global_data, send_counts, displacements, MPI.DOUBLE],
root=0)
global_data_set[task] = global_data
end_time = time.time()
logger.info("time to build dataset {:g}sec".format(end_time - start_time))
return global_data_set, global_time, theta, r
# Create output directory if needed
with Sync() as sync:
if sync.comm.rank == 0:
if not output_path.exists():
output_path.mkdir()
logger.info("output to {}".format(output_path))
fields = args['--fields'].split(',')
def accumulate_files(filename, start, count, file_list):
print(filename, start, count)
if start == 0:
file_list.append(filename)
file_list = []
post.visit_writes(args['<files>'], accumulate_files, file_list=file_list)
logger.info(file_list)
if len(file_list) > 0:
for file in file_list:
f = h5py.File(file, 'r')
r = np.array(f['scales/r/1.5'])
theta = np.array(f['scales/theta/1.5'])
phi = np.array(f['scales/phi/1.5'])
t = np.array(f['scales/sim_time'])
pcm_list = []
fig_list = []
for field in fields:
if field == 's_fluc':
cmap = 'RdYlBu_r'
else:
cmap = None
plot_tools.plot_bot(dset,(1,2),(slice(None),slice(None)))
# Add time title
title = title_func(file['scales/sim_time'][index])
title_height = 1 - 0.5 * mfig.margin.top / mfig.fig.y
fig.suptitle(title, x=0.48, y=title_height, ha='left')
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
fig.clear()
plt.close(fig)
if __name__ == "__main__":
import pathlib
from docopt import docopt
from dedalus.tools import logging
from dedalus.tools import post
from dedalus.tools.parallel import Sync
args = docopt(__doc__)
output_path = pathlib.Path(args['--output']).absolute()
# Create output directory if needed
with Sync() as sync:
if sync.comm.rank == 0:
if not output_path.exists():
output_path.mkdir()
post.visit_writes(args['<files>'], main, output=output_path)
try:
slicer = float(args['--slice'])
except:
slicer = 7.5
pass
x_axis = str(args['--x_axis'])
y_axis = str(args['--y_axis'])
plot_axes = []
for s in [x_axis, y_axis]:
if s == 'z':
plot_axes.append(1)
elif s == 'theta':
plot_axes.append(2)
elif s == 'r':
plot_axes.append(3)
else:
print(
'Bad axis basis specified. Options are z, theta, r. Exiting...'
)
run_slices = []
for i in range(3):
if i + 1 in plot_axes:
run_slices.append(slice(None))
else:
run_slices.append(slicer)
post.visit_writes(args['<prefix>'],
main,
output=output_path,
args['<tasks>'])
axes.axis('off')
# Timestamp title
if title:
axes.set_title('%.2f' % file['scales']['sim_time'][index],
fontsize='large')
# Save frame
if save:
savename = 'graph_%06i.png' % file['scales/write_number'][index]
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
axes.cla()
if __name__ == "__main__":
import pathlib
from docopt import docopt
from dedalus.tools import logging
from dedalus.tools import post
from dedalus.tools.parallel import Sync
args = docopt(__doc__)
output_path = pathlib.Path(args['--output']).absolute()
# Create output directory if needed
with Sync() as sync:
if sync.comm.rank == 0:
if not output_path.exists():
output_path.mkdir()
post.visit_writes(args['<files>'], plot_writes, output=output_path)
except ValueError:
# suffix_num not in PLOT_IDXS, continue
continue
fig.savefig(str(savepath) + '_labeled', dpi=dpi)
fig.clear()
plt.close(fig)
if __name__ == "__main__":
import pathlib
from docopt import docopt
from dedalus.tools import logging
from dedalus.tools import post
from dedalus.tools.parallel import Sync
args = docopt(__doc__)
output_path = pathlib.Path(args['--output']).absolute()
write_start = int(args['--write'])
# Create output directory if needed
with Sync() as sync:
if sync.comm.rank == 0:
if not output_path.exists():
output_path.mkdir()
post.visit_writes(args['<files>'],
main,
output=output_path,
write_start=write_start)
# Save figure
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
axes.clear()
plt.close(fig)
if __name__ == "__main__":
from docopt import docopt
from dedalus.tools import logging
from dedalus.tools import post
from dedalus.tools.parallel import Sync
args = docopt(__doc__)
output_path = pathlib.Path(args['--output']).absolute()
slice_type = args['--slice-type']
# Create output directory if needed
with Sync() as sync:
if sync.comm.rank == 0:
if not output_path.exists():
output_path.mkdir()
print("slice_type = {}".format(slice_type))
post.visit_writes(args['<files>'],
main,
output=output_path,
slice_type=slice_type)
if args['--output'] is not None:
output_path = pathlib.Path(args['--output']).absolute()
else:
data_dir = case + '/'
output_path = pathlib.Path(data_dir).absolute()
fields = ['s(z)', 'F_h(z)', 'F_κ(z)', 'F_KE(z)', 'F_PE(z)', 'Q_source(z)']
def accumulate_files(filename, start, count, file_list):
if start == 0:
file_list.append(filename)
file_list = []
post.visit_writes(files, accumulate_files, file_list=file_list)
logger.debug(file_list)
data = {}
z = None
times = None
for file in file_list:
logger.debug("opening file: {}".format(file))
f = h5py.File(file, 'r')
#data_slices = (slice(None), 0, 0, slice(None))
data_slices = (slice(None), 0, slice(None))
for task in f['tasks']:
if '(z)' in task: # fluxes denoted with 'f(z)'
logger.info("task: {}".format(task))
if task in data:
data[task] = np.append(data[task],
climits = args['--climits']
xlimits = args['--xlimits']
ylimits = args['--ylimits']
dns_tidx = int(args['--dns_tidx'])
ce2_tidx = int(args['--ce2_tidx'])
field = args['--field']
climits = tuple([int(i) for i in climits.split(',')])
xlimits = tuple([int(i) for i in xlimits.split(',')])
ylimits = tuple([int(i) for i in ylimits.split(',')])
with Sync() as sync:
if sync.comm.rank == 0:
# Create output directory if needed
output_path = pathlib.Path(args['--output']).absolute()
if not output_path.exists():
output_path.mkdir()
post.visit_writes(args['<ce2_file_path>'],
plot_power_spectra,
field=field,
climits=climits,
xlimits=xlimits,
ylimits=ylimits,
dns_tidx=-1,
ce2_tidx=-1,
label=label,
dns_filename=args['<dns_file_path>'],
output=args['--output'])
temp = file['tasks/Temperature(y=+1)'][index,:,:,0]
c_temp = np.fft.rfft(temp,axis=1)
power = (c_temp * c_temp.conj()).real
log_power = np.log10(power)
vmin = np.nanmin(log_power)
vmax = np.nanmax(log_power)
if vmin == -np.inf:
vmin = vmax-16
print("vmin, vmax = {},{}".format(vmin,vmax))
img.set_data(log_power)
cbar.mappable.set_clim(vmin=vmin,vmax=vmax)
cbar.set_ticks([vmin,vmax])
cax.xaxis.tick_top()
cax.xaxis.set_label_position('top')
savename = savename_func(file['scales/write_number'][index])
savepath = output.joinpath(savename)
fig.savefig(str(savepath), dpi=dpi)
plt.close(fig)
args = docopt(__doc__)
output_path = pathlib.Path(args['--output']).absolute()
# Create output directory if needed
with Sync() as sync:
if sync.comm.rank == 0:
if not output_path.exists():
output_path.mkdir()
post.visit_writes(args['<files>'], calc_front, output=output_path)
