def setUp(self) -> None:
'''
Load two networks. The first one is a simple test network, and the second one is the London subway
stations network(Victoria).
'''
# load data (simple network)
self.network1 = ot.TemporalDiGraph(
'test_network', data=ot.CsvInput('../overtime/data/network.csv'))
# load data (London subway stations - Victoria)
tfl_data = ot.CsvInput(
'../overtime/data/victoria_central_bakerloo_piccadilly-inbound_outbound.csv'
)
self.network2 = ot.TemporalDiGraph('TflNetwork', data=tfl_data)
self.network2.nodes.add_data(
'../overtime/data/victoria_central_bakerloo_piccadilly-stations.csv'
)
import overtime as ot
# load data (simple network)
network1 = ot.TemporalDiGraph(
'test_network', data=ot.CsvInput('../../overtime/data/network.csv'))
# load data (London subway stations - Victoria)
tfl_data = ot.CsvInput(
'../../overtime/data/victoria_central_bakerloo_piccadilly-inbound_outbound.csv'
)
network2 = ot.TemporalDiGraph('TflNetwork', data=tfl_data)
network2.nodes.add_data(
'../../overtime/data/victoria_central_bakerloo_piccadilly-stations.csv')
# timeline - circular layout
# simple network
ot.echarts_Timeline(network1,
3,
path='../html/network_circular_layout_timeline1.html',
title='circular layout timeline',
subtitle='simple network',
layout='circular')
# timeline - force layout
# simple network
ot.echarts_Timeline(network1,
3,
path='../html/network_force_layout_timeline2.html',
title='force layout timeline',
subtitle='simple network',
layout='force')
import overtime as ot
network = ot.TemporalDiGraph('SampleNetwork', data=ot.CsvInput('./data/network.csv'))
subgraph = network.get_temporal_subgraph(intervals=((0,3),(8,10)), nodes=('a', 'c', 'd'))
subgraph.details()
subgraph.print()
print(subgraph.edges.timespan())
plotter = ot.Plotter()
plotter.single(ot.Circle, network.get_snapshot(7))
plotter.single(ot.Slice, network)
snapshots = []
for t in network.edges.timespan():
snapshots.append(network.get_snapshot(t))
plotter.multi(ot.Circle, snapshots)
a_tree = ot.calculate_foremost_tree(network, 'a')
print(ot.calculate_reachability(network, 'a'))
plotter.single(ot.Circle, a_tree)
input("Press enter key to exit...")
import overtime as ot
####################
### Introduction ###
####################
### import central line data & create graph.
central = ot.TemporalDiGraph('CentralLine',
data=ot.CsvInput('./data/central-inbound.csv'))
central.nodes # nodes object
central.edges # edges object
# nodes
central.nodes.aslist()[0:4]
central.nodes.count()
central.nodes.labels()
# node
lstreet = central.nodes.get('Liverpool Street')
lstreet.sourceof()
lstreet.sourceof().labels()
lstreet.sinkof().labels()
lstreet.sinkof().start_times()
lstreet.sinkof().end_times()
lstreet.nodeof().labels()
lstreet.neighbours()
# edges
central.edges.aslist()
central.edges.count()
central.edges.labels()
import overtime as ot
import pandas as pd
tube = ot.TemporalDiGraph('TubeNetwork', data=ot.CsvInput('./bakerloo-inbound.csv'))
tube.details()
ot.Circle(tube)
plotter = ot.Plotter()
plotter.single(ot.Circle, tube)
ot.Slice(tube)
for node in tube.nodes.set:
node.data['reachability'] = ot.calculate_reachability(tube, node.label)
ot.NodeScatter(tube, bubble_metric='reachability')
station_df = pd.read_csv("bakerloo-stations.csv")
tube.nodes.add_data(station_df)
ot.NodeScatter(tube, x='lon', y='lat', bubble_metric='reachability')
foremost_oxcirc = ot.calculate_foremost_tree(tube, 'Oxford Circus')
foremost_oxcirc.nodes.add_data(station_df)
ot.NodeScatter(foremost_oxcirc, x='lon', y='lat', bubble_metric='foremost_time')
input("Press enter key to exit...")
def parse_graph_to_json(self):
pass
class Temporal_DiGraph_Network_Parser(Graph_Network_Parser):
def __init__(self, graph):
super().__init__(graph)
self.start_time = graph.edges.start_times()
self.end_time = graph.edges.end_times()
def parse_graph_to_json(self):
json_dataset = {}
json_dataset['nodes'] = self.node_labels
json_dataset['edges'] = []
for i in range(len(self.edge_labels)):
edge = {}
source_and_target = self.edge_labels[i].split("-")
edge['source'] = source_and_target[0]
edge['target'] = source_and_target[1]
edge['start'] = self.start_time[i]
edge['end'] = self.end_time[i]
json_dataset['edges'].append(edge)
return json.dumps(json_dataset)
underground = ot.TemporalDiGraph(
'UndergroundLine', data=ot.CsvInput('./data/mini_underground_all.csv'))
visual = Temporal_DiGraph_Network_Parser(underground)
result = visual.parse_graph_to_json()
print(result)
import math
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import overtime as ot
tube = ot.TemporalDiGraph('TubeNetwork',
data=ot.CsvInput('./bakerloo-inbound_outbound.csv'))
tube.details()
station_df = pd.read_csv("bakerloo-stations.csv")
tube.nodes.add_data(station_df)
R = []
for node in tube.nodes.set:
R.append(ot.calculate_reachability(tube, node.label))
X = [node.data['lon'] for node in tube.nodes.set]
Y = [node.data['lat'] for node in tube.nodes.set]
figure, axis = plt.subplots(1)
plt.subplots_adjust(left=0.05,
bottom=0.05,
right=0.95,
top=0.95,
wspace=0,
hspace=0)
axis.set_aspect('equal')
plt.scatter(X, Y, s=[(r + 2) * 30 for r in R], c=Y, alpha=0.5)
#axis.set_xticks(range(0, tube.nodes.count()))
def dataset(): # This is hardcode example of dataset, in the future the user can select their own file
underground = ot.TemporalDiGraph('UndergroundLine', data=ot.CsvInput('./data/mini_jubilee.csv'))
visual = Temporal_DiGraph_Network_Parser(underground)
res = visual.parse_graph_to_json()
return res
