Updated post_process scripts

post_process/animate/__main__.py

@@ -14,5 +14,5 @@ parser.add_argument('-l', '--log-level', default='INFO', type=str,
 args = parser.parse_args()
 
 if args.var == 'alpha.water':
-    import alpha_water
+    from . import alpha_water
     alpha_water.animate(args.config, args.log_level)

post_process/config.anim.ini

@@ -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

post_process/post_process/__main__.py

@@ -44,18 +44,28 @@ if config.getboolean('main', 'loaddata', fallback=False):
             with ThreadPool(
                         config.getint('main', 'nthreads', fallback=1)
                     ) as pool:
-                sensor = dict(zip(timesteps, pool.map(
-                    lambda t:np.apply_along_axis(
-                        lambda x:np.sqrt((x**2).sum()),
-                        0,
-                        fluidfoam.readvector(
+                if config.getboolean('sensor', 'vector', fallback=False):
+                    sensor = dict(zip(timesteps, pool.map(
+                        lambda t:np.apply_along_axis(
+                            lambda x:np.sqrt((x**2).sum()),
+                            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),
                             t,
                             config.get('sensor', 'value')
                         ),
-                    ),
-                    timesteps.index
-                )))
+                        timesteps.index
+                    )))
         
                 hdf.put(case, pd.DataFrame(sensor))
                 del sensor
@@ -75,7 +85,7 @@ with pd.HDFStore(
     mesh = data.get('mesh')
     rawxs = config.get('sensor', 'x').split(',')
     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):
         x0 = float(rawx)
         y0 = rubble_line.iloc[np.abs(x0-rubble_line.index).argmin()]
@@ -107,7 +117,7 @@ with pd.HDFStore(
         axi.grid()
         axi.set(
             xlabel='t (s)',
-            ylabel='U (m/s)',
+            ylabel=config.get('figure', 'ylabel', fallback=''),
             xlim=(0,timesteps.max()),
             ylim=(0,figmax),
         )