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Updated post_process scripts

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This commit is contained in:
Edgar P. Burkhart 2022-02-01 01:21:42 +01:00
parent 028b9db8b7
commit 14bd508058
Signed by: edpibu
GPG key ID: 9833D3C5A25BD227
4 changed files with 29 additions and 11 deletions
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2
post_process/animate/__main__.py
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@ -14,5 +14,5 @@ parser.add_argument('-l', '--log-level', default='INFO', type=str,
args = parser.parse_args() args = parser.parse_args()
if args.var == 'alpha.water': if args.var == 'alpha.water':
import alpha_water from . import alpha_water
alpha_water.animate(args.config, args.log_level) alpha_water.animate(args.config, args.log_level)

8
post_process/config.anim.ini Normal file
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@ -0,0 +1,8 @@
[main]
root = ~/OpenFOAM/work/artha_4_04/
out = out/anim.mp4
#log_file = openfoam.log
[data]
path = ../bathymetry/3_pd/data.hdf
blocs = bloc0,bloc1

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post_process/local.p.hdf Normal file
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30
post_process/post_process/__main__.py
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@ -44,18 +44,28 @@ if config.getboolean('main', 'loaddata', fallback=False):
with ThreadPool( with ThreadPool(
config.getint('main', 'nthreads', fallback=1) config.getint('main', 'nthreads', fallback=1)
) as pool: ) as pool:
sensor = dict(zip(timesteps, pool.map( if config.getboolean('sensor', 'vector', fallback=False):
lambda t:np.apply_along_axis( sensor = dict(zip(timesteps, pool.map(
lambda x:np.sqrt((x**2).sum()), lambda t:np.apply_along_axis(
0, lambda x:np.sqrt((x**2).sum()),
fluidfoam.readvector( 0,
fluidfoam.readvector(
root.joinpath(case),
t,
config.get('sensor', 'value')
),
),
timesteps.index
)))
else:
sensor = dict(zip(timesteps, pool.map(
lambda t:fluidfoam.readscalar(
root.joinpath(case), root.joinpath(case),
t, t,
config.get('sensor', 'value') config.get('sensor', 'value')
), ),
), timesteps.index
timesteps.index )))
)))
hdf.put(case, pd.DataFrame(sensor)) hdf.put(case, pd.DataFrame(sensor))
del sensor del sensor
@ -75,7 +85,7 @@ with pd.HDFStore(
mesh = data.get('mesh') mesh = data.get('mesh')
rawxs = config.get('sensor', 'x').split(',') rawxs = config.get('sensor', 'x').split(',')
fig, ax = plt.subplots(len(rawxs)) fig, ax = plt.subplots(len(rawxs))
figmax = config.getfloat('figure', 'max') figmax = config.getfloat('figure', 'max', fallback=None)
for axi, rawx in zip(ax, rawxs): for axi, rawx in zip(ax, rawxs):
x0 = float(rawx) x0 = float(rawx)
y0 = rubble_line.iloc[np.abs(x0-rubble_line.index).argmin()] y0 = rubble_line.iloc[np.abs(x0-rubble_line.index).argmin()]
@ -107,7 +117,7 @@ with pd.HDFStore(
axi.grid() axi.grid()
axi.set( axi.set(
xlabel='t (s)', xlabel='t (s)',
ylabel='U (m/s)', ylabel=config.get('figure', 'ylabel', fallback=''),
xlim=(0,timesteps.max()), xlim=(0,timesteps.max()),
ylim=(0,figmax), ylim=(0,figmax),
) )