.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/spatial_indexing_1d_network.py"
.. LINE NUMBERS ARE GIVEN BELOW.
.. only:: html
.. note::
:class: sphx-glr-download-link-note
:ref:`Go to the end <sphx_glr_download_examples_spatial_indexing_1d_network.py>`
to download the full example code.
.. rst-class:: sphx-glr-example-title
.. _sphx_glr_examples_spatial_indexing_1d_network.py:
Spatial indexing of 1D networks and linear geometry
===================================================
This example demonstrates how to use the ``numba_celltree`` package to index 1D
grids. The package provides a :class:`EdgeCellTree` class that constructs a
cell tree for 1D networks and linear geometries. The package currently supports
the following operations:
* Locating points
* Locating line segments
This example provides an introduction to searching a cell tree for each of
these.
We'll start by importing the required packages with matplotlib for plotting.
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.. code-block:: Python
import os
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.collections import LineCollection
os.environ["NUMBA_DISABLE_JIT"] = "1" # small examples, avoid JIT overhead
from numba_celltree import EdgeCellTree2d, demo # noqa E402
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Let's start with a simple 1D network.
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.. code-block:: Python
vertices, edges = demo.example_1d_network()
node_x = vertices.T[0]
node_y = vertices.T[1]
fig, ax = plt.subplots()
demo.plot_edges(node_x, node_y, edges, ax, color="black")
.. image-sg:: /examples/images/sphx_glr_spatial_indexing_1d_network_001.png
:alt: spatial indexing 1d network
:srcset: /examples/images/sphx_glr_spatial_indexing_1d_network_001.png
:class: sphx-glr-single-img
.. GENERATED FROM PYTHON SOURCE LINES 40-44
Locating points
---------------
We'll build a cell tree first, then look for some points.
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.. code-block:: Python
tree = EdgeCellTree2d(vertices, edges)
points = np.array(
[
[0.25, 1.5],
[0.75, 1.5],
[2.0, 1.5], # This one is outside the grid
]
)
i = tree.locate_points(points)
i
.. rst-class:: sphx-glr-script-out
.. code-block:: none
array([ 7, 1, -1])
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This returns the indices of the edges that contain each point, with -1
indicating points outside the network. We'll have to filter those out first.
Let's plot them:
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.. code-block:: Python
ii = i[i != -1]
fig, ax = plt.subplots()
ax.scatter(*points.transpose())
demo.plot_edges(node_x, node_y, edges, ax, color="black")
demo.plot_edges(node_x, node_y, edges[ii], ax, color="blue", linewidth=3)
.. image-sg:: /examples/images/sphx_glr_spatial_indexing_1d_network_002.png
:alt: spatial indexing 1d network
:srcset: /examples/images/sphx_glr_spatial_indexing_1d_network_002.png
:class: sphx-glr-single-img
.. GENERATED FROM PYTHON SOURCE LINES 70-75
Locating line segments
-----------------------
Let's locate some line segments on the grid. We'll start off with creating
some line segments.
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.. code-block:: Python
segments = np.array(
[
[[0.0, 1.25], [1.5, 1.5]],
[[1.5, 1.5], [2.25, 3.5]],
]
)
fig, ax = plt.subplots()
demo.plot_edges(node_x, node_y, edges, ax, color="black")
ax.add_collection(LineCollection(segments, color="gray", linewidth=3))
.. image-sg:: /examples/images/sphx_glr_spatial_indexing_1d_network_003.png
:alt: spatial indexing 1d network
:srcset: /examples/images/sphx_glr_spatial_indexing_1d_network_003.png
:class: sphx-glr-single-img
.. rst-class:: sphx-glr-script-out
.. code-block:: none
<matplotlib.collections.LineCollection object at 0x7fd8c03bacf0>
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Let's now intersect these line segments with the edges in the network.
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.. code-block:: Python
segment_index, tree_edge_index, xy_intersection = tree.intersect_edges(segments)
xy_intersection
.. rst-class:: sphx-glr-script-out
.. code-block:: none
array([[0.6 , 1.35 ],
[0.25 , 1.29166667],
[2.02173913, 2.89130435],
[1.875 , 2.5 ]])
.. GENERATED FROM PYTHON SOURCE LINES 93-98
The ``intersect_edges`` method returns three arrays: which input segments
intersect with the network, which network edges they intersect with, and the
coordinates of each intersection point.
Let's plot the results:
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.. code-block:: Python
fig, ax = plt.subplots()
demo.plot_edges(node_x, node_y, edges, ax, color="black")
demo.plot_edges(node_x, node_y, edges[tree_edge_index], ax, color="blue", linewidth=3)
ax.add_collection(LineCollection(segments, color="gray", linewidth=3))
ax.scatter(*xy_intersection.transpose(), s=60, color="darkgreen", zorder=2.5)
.. image-sg:: /examples/images/sphx_glr_spatial_indexing_1d_network_004.png
:alt: spatial indexing 1d network
:srcset: /examples/images/sphx_glr_spatial_indexing_1d_network_004.png
:class: sphx-glr-single-img
.. rst-class:: sphx-glr-script-out
.. code-block:: none
<matplotlib.collections.PathCollection object at 0x7fd8c02806e0>
.. rst-class:: sphx-glr-timing
**Total running time of the script:** (0 minutes 0.266 seconds)
.. _sphx_glr_download_examples_spatial_indexing_1d_network.py:
.. only:: html
.. container:: sphx-glr-footer sphx-glr-footer-example
.. container:: sphx-glr-download sphx-glr-download-jupyter
:download:`Download Jupyter notebook: spatial_indexing_1d_network.ipynb <spatial_indexing_1d_network.ipynb>`
.. container:: sphx-glr-download sphx-glr-download-python
:download:`Download Python source code: spatial_indexing_1d_network.py <spatial_indexing_1d_network.py>`
.. container:: sphx-glr-download sphx-glr-download-zip
:download:`Download zipped: spatial_indexing_1d_network.zip <spatial_indexing_1d_network.zip>`
.. only:: html
.. rst-class:: sphx-glr-signature
`Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_