From b441a1afeca68efadf6fc210606515c876cdb52d Mon Sep 17 00:00:00 2001
From: FZill <florian.zill@ufz.de>
Date: Thu, 21 Mar 2024 12:45:26 +0100
Subject: [PATCH] [meshlib] added aggregate function to MeshSeries
---
ogstools/meshlib/mesh_series.py | 67 +++++++++++++++++++++++++++++++++
1 file changed, 67 insertions(+)
diff --git a/ogstools/meshlib/mesh_series.py b/ogstools/meshlib/mesh_series.py
index d43f39654..4420b6739 100644
--- a/ogstools/meshlib/mesh_series.py
+++ b/ogstools/meshlib/mesh_series.py
@@ -10,6 +10,9 @@ import vtuIO
from scipy.interpolate import LinearNDInterpolator, NearestNDInterpolator
from tqdm.auto import tqdm
+from ogstools.propertylib import Property, presets
+from ogstools.propertylib.tensor_math import identity
+
from .xdmf_reader import XDMFReader
@@ -164,6 +167,70 @@ class MeshSeries:
)
return mesh[data_name]
+ def aggregate(
+ self,
+ mesh_property: Union[Property, str],
+ func: Literal["min", "max", "mean", "median", "sum", "std", "var"],
+ ) -> tuple[pv.DataSet, Property]:
+ """Aggregate data over all timesteps using a specified function.
+
+ :param mesh_property:
+ The mesh property to be aggregated. If given as type `Property`, the
+ :meth:`~ogstools.propertylib.property.Property.transform` function
+ will be applied on each timestep and aggregation afterwards.
+ :param func:
+ The aggregation function to apply. It must be one of "min", "max",
+ "mean", "median", "sum", "std", "var". The equally named numpy
+ function will be used to aggregate over all timesteps.
+ :returns: A mesh with aggregated data according to the given function
+ and a Property corresponding to this data.
+
+ """
+ np_func = {
+ "min": np.min,
+ "max": np.max,
+ "mean": np.mean,
+ "median": np.median,
+ "sum": np.sum,
+ "std": np.std,
+ "var": np.var,
+ }[func]
+ mesh = self.read(0).copy(deep=True)
+ mesh.clear_data()
+ if isinstance(mesh_property, Property):
+ if mesh_property.mesh_dependent:
+ vals = np.asarray(
+ [
+ mesh_property.transform(self.read(t))
+ for t in tqdm(self.timesteps)
+ ]
+ )
+ else:
+ vals = mesh_property.transform(
+ self.values(mesh_property.data_name)
+ )
+ else:
+ vals = self.values(mesh_property)
+ output_name = (
+ f"{mesh_property.output_name}_{func}"
+ if isinstance(mesh_property, Property)
+ else f"{mesh_property}_{func}"
+ )
+ mesh[output_name] = np.empty(vals.shape[1:])
+ np_func(vals, out=mesh[output_name], axis=0)
+ if isinstance(mesh_property, Property):
+ agg_property = mesh_property.replace(
+ data_name=output_name,
+ data_unit=mesh_property.output_unit,
+ output_unit=mesh_property.output_unit,
+ output_name=output_name,
+ func=identity,
+ mesh_dependent=False,
+ )
+ else:
+ agg_property = presets.get_preset(output_name, mesh)
+ return mesh, agg_property
+
def _probe_pvd(
self,
points: np.ndarray,
--
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