From e4c75707c7894f21440baee64e67e716ee9e055c Mon Sep 17 00:00:00 2001
From: FZill <florian.zill@ufz.de>
Date: Mon, 12 Feb 2024 11:31:31 +0100
Subject: [PATCH] updated observation point example
---
.../plot_observation_points.py | 24 +++++++++++--------
1 file changed, 14 insertions(+), 10 deletions(-)
diff --git a/docs/examples/howto_meshplotlib/plot_observation_points.py b/docs/examples/howto_meshplotlib/plot_observation_points.py
index 473f72b3d..70b6331cd 100644
--- a/docs/examples/howto_meshplotlib/plot_observation_points.py
+++ b/docs/examples/howto_meshplotlib/plot_observation_points.py
@@ -8,7 +8,7 @@ In this example we plot the data values on observation points over all
timesteps. Since requested observation points don't necessarily coincide with
actual nodes of the mesh different interpolation options are available. See
:py:mod:`ogstools.meshlib.mesh_series.MeshSeries.probe` for more details.
-Here again, we use a component transport example from the ogs benchmark gallery
+Here we use a component transport example from the ogs benchmark gallery
(https://www.opengeosys.org/docs/benchmarks/hydro-component/elder/).
"""
@@ -17,6 +17,7 @@ Here again, we use a component transport example from the ogs benchmark gallery
# sphinx_gallery_start_ignore
# sphinx_gallery_thumbnail_number = 2
+# fmt:off
# sphinx_gallery_end_ignore
@@ -25,6 +26,7 @@ import numpy as np
from ogstools import meshplotlib
from ogstools.meshplotlib.examples import meshseries_CT_2D as mesh_series
+from ogstools.meshplotlib.utils import justified_labels
from ogstools.propertylib import Scalar
meshplotlib.setup.reset()
@@ -39,7 +41,10 @@ si = Scalar(
# Let's define 4 observation points and plot them on the mesh.
# %%
-points = np.asarray([[x, 0, 60] for x in [0, 40, 80, 120]])
+points = np.asarray(
+ [[x, 0, 60] for x in [0, 40, 80, 120]]
+ + [[x, 0, 40] for x in [0, 40, 80, 120]]
+)
fig = meshplotlib.plot(mesh_series.read(0), si)
fig.axes[0].scatter(points[:, 0], points[:, 2], s=50, fc="none", ec="r", lw=3)
for i, point in enumerate(points):
@@ -50,10 +55,11 @@ plt.rcdefaults()
# And now probe the points and the values over time:
# %%
+labels = [f"{i}: {label}" for i, label in enumerate(justified_labels(points))]
fig = meshplotlib.plot_probe(
- mesh_series=mesh_series, points=points, mesh_property=si, time_unit="a"
+ mesh_series=mesh_series, points=points[:4], mesh_property=si,
+ time_unit="a", labels=labels[:4]
)
-
# %% [markdown]
# You can also pass create your own matplotlib figure and pass the axes object.
# Additionally, you can pass any keyword arguments which are known by
@@ -64,11 +70,9 @@ fig = meshplotlib.plot_probe(
# %%
fig, axs = plt.subplots(nrows=2, figsize=[10, 5])
meshplotlib.plot_probe(
- mesh_series, points, si, time_unit="a", ax=axs[0], colors=["k", "b"],
- marker="." # fmt: skip
-)
-points_2 = np.asarray([[50, 0, z] for z in [60, 50, 40, 30]])
+ mesh_series, points[:4], si, time_unit="a", ax=axs[0], colors=["k"],
+ labels=labels[:4], marker=".")
meshplotlib.plot_probe(
- mesh_series, points_2, si, time_unit="a", ax=axs[1], linestyles=["-"],
- linewidth=1 # fmt: skip
+ mesh_series, points[4:], si, time_unit="a", ax=axs[1], linestyles=["-"],
+ labels=labels[4:], linewidth=1,
)
--
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