.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "_auto_examples/other_applications/plot_find_disconnected.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_other_applications_plot_find_disconnected.py: .. _find_disconnected_links: Finding disconnected links ========================== In this example, we show how to find disconnected links in an AequilibraE network We use the Nauru example to find disconnected links .. GENERATED FROM PYTHON SOURCE LINES 12-13 Imports .. GENERATED FROM PYTHON SOURCE LINES 13-22 .. code-block:: Python from uuid import uuid4 from tempfile import gettempdir from os.path import join from datetime import datetime import pandas as pd import numpy as np from aequilibrae.utils.create_example import create_example from aequilibrae.paths.results import PathResults .. GENERATED FROM PYTHON SOURCE LINES 24-25 We create an empty project on an arbitrary folder .. GENERATED FROM PYTHON SOURCE LINES 25-33 .. code-block:: Python fldr = join(gettempdir(), uuid4().hex) # Let's use the Nauru example project for display project = create_example(fldr, "nauru") # Let's analyze the mode car or 'c' in our model mode = "c" .. GENERATED FROM PYTHON SOURCE LINES 34-35 We need to create the graph, but before that, we need to have at least one centroid in our network .. GENERATED FROM PYTHON SOURCE LINES 35-57 .. code-block:: Python # We get an arbitrary node to set as centroid and allow for the construction of graphs centroid_count = project.conn.execute("select count(*) from nodes where is_centroid=1").fetchone()[0] if centroid_count == 0: arbitrary_node = project.conn.execute("select node_id from nodes limit 1").fetchone()[0] nodes = project.network.nodes nd = nodes.get(arbitrary_node) nd.is_centroid = 1 nd.save() network = project.network network.build_graphs(modes=[mode]) graph = network.graphs[mode] graph.set_blocked_centroid_flows(False) if centroid_count == 0: # Let's revert to setting up that node as centroid in case we had to do it nd.is_centroid = 0 nd.save() .. rst-class:: sphx-glr-script-out .. code-block:: none /opt/hostedtoolcache/Python/3.9.18/x64/lib/python3.9/site-packages/aequilibrae/project/network/network.py:342: FutureWarning: Downcasting object dtype arrays on .fillna, .ffill, .bfill is deprecated and will change in a future version. Call result.infer_objects(copy=False) instead. To opt-in to the future behavior, set `pd.set_option('future.no_silent_downcasting', True)` df = pd.read_sql(sql, conn).fillna(value=np.nan) .. GENERATED FROM PYTHON SOURCE LINES 58-59 We set the graph for computation .. GENERATED FROM PYTHON SOURCE LINES 59-73 .. code-block:: Python graph.set_graph("distance") graph.set_skimming("distance") # Get the nodes that are part of the car network missing_nodes = [ x[0] for x in project.conn.execute(f"Select node_id from nodes where instr(modes, '{mode}')").fetchall() ] missing_nodes = np.array(missing_nodes) # And prepare the path computation structure res = PathResults() res.prepare(graph) .. GENERATED FROM PYTHON SOURCE LINES 74-75 Now we can compute all the path islands we have .. GENERATED FROM PYTHON SOURCE LINES 75-93 .. code-block:: Python islands = [] idx_islands = 0 # while missing_nodes.shape[0] >= 2: print(datetime.now().strftime("%H:%M:%S"), f" - Computing island: {idx_islands}") res.reset() res.compute_path(missing_nodes[0], missing_nodes[1]) res.predecessors[graph.nodes_to_indices[missing_nodes[0]]] = 0 connected = graph.all_nodes[np.where(res.predecessors >= 0)] connected = np.intersect1d(missing_nodes, connected) missing_nodes = np.setdiff1d(missing_nodes, connected) print(f" Nodes to find: {missing_nodes.shape[0]:,}") df = pd.DataFrame({"node_id": connected, "island": idx_islands}) islands.append(df) idx_islands += 1 print(f"\nWe found {idx_islands} islands") .. rst-class:: sphx-glr-script-out .. code-block:: none 08:40:12 - Computing island: 0 Nodes to find: 2 08:40:12 - Computing island: 1 Nodes to find: 0 We found 2 islands .. GENERATED FROM PYTHON SOURCE LINES 94-95 consolidate everything into a single DataFrame .. GENERATED FROM PYTHON SOURCE LINES 95-100 .. code-block:: Python islands = pd.concat(islands) # And save to disk alongside our model islands.to_csv(join(fldr, "island_outputs_complete.csv"), index=False) .. GENERATED FROM PYTHON SOURCE LINES 101-103 If you join the node_id field in the csv file generated above with the a_node or b_node fields in the links table, you will have the corresponding links in each disjoint island found .. GENERATED FROM PYTHON SOURCE LINES 105-106 .. code-block:: Python project.close() .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.177 seconds) .. _sphx_glr_download__auto_examples_other_applications_plot_find_disconnected.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_find_disconnected.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_find_disconnected.py ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_