def __init__(self, shapefile=Path("assets/wrs/WRS2_descending.shp")):
speedups.disable()
self.shapefile = ogr.Open(str(shapefile))
self.layer = self.shapefile.GetLayer(0)
self.polygons = []
for i in range(self.layer.GetFeatureCount()):
feature = self.layer.GetFeature(i)
path = feature['PATH']
row = feature['ROW']
geom = feature.GetGeometryRef()
shape = shapely.wkt.loads(geom.ExportToWkt())
self.polygons.append((shape, path, row))
# Here I apply a global model on bus OD data in Singapore. The bus OD data is a small subset of bus trip data available via LTA Data Mall: https://datamall.lta.gov.sg/content/datamall/en.html. Preprocessing has been performed by matching O/D to bus stop locations, and line features connecting each pair of OD are created. Weight column carries the expected volume of passengers on the pair of OD nodes. # # %% [markdown] # ## Global Model # %% import geopandas as gpd import networkx as nx import pandas as pd import numpy as np import matplotlib.pyplot as plt import os, sys # %% from shapely import speedups speedups.disable() # %% # import line shapefile (representing OD flows between each pair of bus stops) orig_flow = gpd.read_file(r"data\SampleODFlow.shp") orig_flow.head() # %% orig_flow.info() # %% orig_flow.plot(linewidth=0.5, alpha=0.01) # %% [markdown] # Some of the nodes are in erroneous locations (X/Y of 0,0). We will remove these OD links from the dataset.
def tearDown(self):
self.assertTrue(speedups._orig)
speedups.disable()
self.assertFalse(speedups._orig)
def tearDown(self):
self.assertTrue(speedups._orig)
speedups.disable()
self.assertFalse(speedups._orig)
