.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "_auto_examples/creating_models/plot_create_zoning.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr__auto_examples_creating_models_plot_create_zoning.py: .. _create_zones: Creating a zone system based on Hex Bins ======================================== In this example, we show how to create hex bin zones covering an arbitrary area. We use the Nauru example to create roughly 100 zones covering the whole modeling area as delimited by the entire network You are obviously welcome to create whatever zone system you would like, as long as you have the geometries for them. In that case, you can just skip the hex bin computation part of this notebook. We also add centroid connectors to our network to make it a pretty complete example .. GENERATED FROM PYTHON SOURCE LINES 21-22 Imports .. GENERATED FROM PYTHON SOURCE LINES 22-30 .. code-block:: Python from uuid import uuid4 from tempfile import gettempdir from os.path import join from math import sqrt from shapely.geometry import Point import shapely.wkb from aequilibrae.utils.create_example import create_example, list_examples .. GENERATED FROM PYTHON SOURCE LINES 32-33 We create an empty project on an arbitrary folder .. GENERATED FROM PYTHON SOURCE LINES 33-41 .. code-block:: Python fldr = join(gettempdir(), uuid4().hex) # We can print the list of examples that ship with AequilibraE print(list_examples()) # Let's use the Nauru example project for display project = create_example(fldr, "nauru") .. rst-class:: sphx-glr-script-out .. code-block:: none ['coquimbo', 'sioux_falls', 'nauru'] .. GENERATED FROM PYTHON SOURCE LINES 42-43 We said we wanted 100 zones .. GENERATED FROM PYTHON SOURCE LINES 43-45 .. code-block:: Python zones = 100 .. GENERATED FROM PYTHON SOURCE LINES 46-48 Hex Bins using Spatialite ------------------------- .. GENERATED FROM PYTHON SOURCE LINES 50-52 Spatialite requires a few things to compute hex bins. One of them is the area you want to cover. .. GENERATED FROM PYTHON SOURCE LINES 52-57 .. code-block:: Python network = project.network # So we use the convenient network method ``convex_hull()`` (it may take some time for very large networks) geo = network.convex_hull() .. GENERATED FROM PYTHON SOURCE LINES 58-60 The second thing is the side of the hex bin, which we can compute from its area. The approximate area of the desired hex bin is .. GENERATED FROM PYTHON SOURCE LINES 60-65 .. code-block:: Python zone_area = geo.area / zones # Since the area of the hexagon is **3 * sqrt(3) * side^2 / 2** # is side is equal to **sqrt(2 * sqrt(3) * A/9)** zone_side = sqrt(2 * sqrt(3) * zone_area / 9) .. GENERATED FROM PYTHON SOURCE LINES 66-70 Now we can run an SQL query to compute the hexagonal grid. There are many ways to create hex bins (including with a GUI on QGIS), but we find that using SpatiaLite is a pretty neat solution. For which we will use the entire network bounding box to make sure we cover everything .. GENERATED FROM PYTHON SOURCE LINES 70-81 .. code-block:: Python extent = network.extent() curr = project.conn.cursor() b = extent.bounds curr.execute( "select st_asbinary(HexagonalGrid(GeomFromWKB(?), ?, 0, GeomFromWKB(?)))", [extent.wkb, zone_side, Point(b[2], b[3]).wkb], ) grid = curr.fetchone()[0] grid = shapely.wkb.loads(grid) .. GENERATED FROM PYTHON SOURCE LINES 82-84 Since we used the bounding box, we have WAY more zones than we wanted, so we clean them by only keeping those that intersect the network convex hull. .. GENERATED FROM PYTHON SOURCE LINES 84-93 .. code-block:: Python grid = [p for p in grid.geoms if p.intersects(geo)] # Let's re-number all nodes with IDs smaller than 300 to something bigger as to free space to our centroids to go from 1 # to N nodes = network.nodes for i in range(1, 301): nd = nodes.get(i) nd.renumber(i + 1300) .. GENERATED FROM PYTHON SOURCE LINES 94-96 Now we can add them to the model And add centroids to them while we are at it .. GENERATED FROM PYTHON SOURCE LINES 96-106 .. code-block:: Python zoning = project.zoning for i, zone_geo in enumerate(grid): zone = zoning.new(i + 1) zone.geometry = zone_geo zone.save() # None means that the centroid will be added in the geometric point of the zone # But we could provide a Shapely point as an alternative zone.add_centroid(None) .. GENERATED FROM PYTHON SOURCE LINES 107-109 Centroid connectors ------------------- .. GENERATED FROM PYTHON SOURCE LINES 111-123 .. code-block:: Python for zone_id, zone in zoning.all_zones().items(): # We will connect for walk, with 1 connector per zone zone.connect_mode(mode_id="w", connectors=1) # And for cars, for cars with 2 connectors per zone # We also specify the link types we accept to connect to (can be used to avoid connection to ramps or freeways) zone.connect_mode(mode_id="c", link_types="ytrusP", connectors=2) # This takes a few minutes to compute, so we will break after processing the first 10 zones if zone_id >= 10: break .. GENERATED FROM PYTHON SOURCE LINES 124-126 Let's add special generator zones We also add a centroid at the airport terminal .. GENERATED FROM PYTHON SOURCE LINES 126-138 .. code-block:: Python nodes = project.network.nodes # Let's use some silly number for its ID, like 10,000, just so we can easily differentiate it airport = nodes.new_centroid(10000) airport.geometry = Point(166.91749582, -0.54472590) airport.save() # When connecting a centroid not associated with a zone, we need to tell AequilibraE what is the initial area around # the centroid that needs to be considered when looking for candidate nodes. # Distance here is in degrees, so 0.01 is equivalent to roughly 1.1km airport.connect_mode(airport.geometry.buffer(0.01), mode_id="c", link_types="ytrusP", connectors=1) .. GENERATED FROM PYTHON SOURCE LINES 139-140 .. code-block:: Python project.close() .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 4.368 seconds) .. _sphx_glr_download__auto_examples_creating_models_plot_create_zoning.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_create_zoning.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_create_zoning.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_