def test_write_valued_network_to_shp(self):
out = 'output_network.shp'
fields = ['WEIGHT1','WEIGHT2']
types = [('N',7,3),('N',7,3)]
values = {(1,1):1,(2,2):2,(3,3):3,(4,4):4,(5,5):5,(6,6):6,(7,7):7}
def doubleX(values, node):
return values[node]*2.0
pynet.write_valued_network_to_shp(out,fields,types,self.G2,values,doubleX)
graph = pynet.read_network(out)
self.assertEqual(len(graph), len(self.G2))
def test_list_network_to_shp(self):
out = 'output_network.shp'
fields = ['WEIGHT']
types = [('N',7,3)]
list_network = []
for node1 in self.G2:
for node2 in self.G2[node1]:
list_network.append(((node1, node2),random.random()))
pynet.write_list_network_to_shp(out,fields,types,list_network)
graph = pynet.read_network(out)
self.assertEqual(len(graph), len(self.G2))
def test_list_network_to_shp(self):
out = 'output_network.shp'
fields = ['WEIGHT']
types = [('N', 7, 3)]
list_network = []
for node1 in self.G2:
for node2 in self.G2[node1]:
list_network.append(((node1, node2), random.random()))
pynet.write_list_network_to_shp(out, fields, types, list_network)
graph = pynet.read_network(out)
self.assertEqual(len(graph), len(self.G2))
def setUp(self):
self.net = 'streets.shp'
self.G = pynet.read_network(self.net)
self.G2 = {(1,1): {(2,2): 0.125, (3,3): 0.75}, (2,2): {(1,1): 0.125, (4,4): 1.2},
(3,3): {(1,1): 0.75, (4,4): 0.375},
(4,4): {(2,2): 1.2, (3,3): 0.375, (5,5): 0.5},
(5,5): {(4,4): 0.5}, (6,6):{(7,7):1.0}, (7,7):{(6,6):1.0}}
self.GDirected = {(1,1): {(2,2): 0.125, (3,3): 0.75}, (2,2): {(1,1): 0.125},
(3,3): {(1,1): 0.75, (4,4): 0.375},
(4,4): {(2,2): 1.2, (3,3): 0.375, (5,5): 0.5},
(5,5): {(4,4): 0.5}, (6,6):{(7,7):1.0}, (7,7):{(6,6):1.0}}
self.points = [((4,4), (2,2), 0.51466686561013752, 0.68533313438986243),
((4,4), (3,3), 0.077286837052313151, 0.29771316294768685),
((6,6), (7,7), 0.82358887253344548, 0.17641112746655452)]
def setUp(self):
self.population = range(5)
self.weights = [0.1, 0.25, 0.1, 0.2, 0.35]
np.random.seed(10)
self.network_file = 'streets.shp'
self.G = pynet.read_network(self.network_file)
self.references = [[i, [n]] for i, n in enumerate(self.G.keys())]
self.scale_set = (0, 1500, 500)
self.network_distances_cache = {}
search_radius = self.scale_set[1]
for i, node in self.references:
n = node[0]
self.network_distances_cache[n] = pynet.dijkstras(self.G, n, search_radius)
self.snapper = pynet.Snapper(self.G)
self.events_file = 'crimes.shp'
points = self.get_points_from_shapefile(self.events_file)
self.events = []
for p in points:
self.events.append(self.snapper.snap(p[0]))
self.test_node = (724587.78057580709, 877802.4281426128)
def test_write_valued_network_to_shp(self):
out = 'output_network.shp'
fields = ['WEIGHT1', 'WEIGHT2']
types = [('N', 7, 3), ('N', 7, 3)]
values = {
(1, 1): 1,
(2, 2): 2,
(3, 3): 3,
(4, 4): 4,
(5, 5): 5,
(6, 6): 6,
(7, 7): 7
}
def doubleX(values, node):
return values[node] * 2.0
pynet.write_valued_network_to_shp(out, fields, types, self.G2, values,
doubleX)
graph = pynet.read_network(out)
self.assertEqual(len(graph), len(self.G2))
def setUp(self):
self.base = np.array([100, 80, 50, 120, 90])
self.events = np.array([20, 20, 5, 10, 25])
np.random.seed(10)
self.observed = np.array([0.1,0.15,0.2])
self.simulated = np.array([[0.05,0.10,0.25],[0.12,0.11,0.3],[0.11,0.09,0.27]])
self.network_file = 'streets.shp'
self.G = pynet.read_network(self.network_file)
self.test_link = ((724432.38723173144, 877800.08747069736),
(724587.78057580709, 877802.4281426128))
self.G2 = copy.deepcopy(self.G)
done = set()
for n1 in self.G2:
for n2 in self.G2[n1]:
if (n1, n2) in done:
continue
dist = self.G2[n1][n2]
base = int(random.random()*1000)
event = int(random.random()*base)
self.G2[n1][n2] = [dist, base, event]
self.G2[n2][n1] = [dist, base, event]
done.add((n1,n2))
done.add((n2,n1))
def setUp(self):
self.base = np.array([100, 80, 50, 120, 90])
self.events = np.array([20, 20, 5, 10, 25])
np.random.seed(10)
self.observed = np.array([0.1, 0.15, 0.2])
self.simulated = np.array([[0.05, 0.10, 0.25], [0.12, 0.11, 0.3],
[0.11, 0.09, 0.27]])
self.network_file = 'streets.shp'
self.G = pynet.read_network(self.network_file)
self.test_link = ((724432.38723173144, 877800.08747069736),
(724587.78057580709, 877802.4281426128))
self.G2 = copy.deepcopy(self.G)
done = set()
for n1 in self.G2:
for n2 in self.G2[n1]:
if (n1, n2) in done:
continue
dist = self.G2[n1][n2]
base = int(random.random() * 1000)
event = int(random.random() * base)
self.G2[n1][n2] = [dist, base, event]
self.G2[n2][n1] = [dist, base, event]
done.add((n1, n2))
done.add((n2, n1))
def test_write_network_to_pysalshp(self):
out = 'output_network.shp'
pynet.write_network_to_pysalshp(self.G, out)
graph = pynet.read_network(out)
self.assertEqual(graph, self.G)
def test_read_network(self):
graph = pynet.read_network(self.net)
self.assertEqual(graph, self.G)
def setUp(self):
self.net = 'streets.shp'
self.G = pynet.read_network(self.net)
self.G2 = {
(1, 1): {
(2, 2): 0.125,
(3, 3): 0.75
},
(2, 2): {
(1, 1): 0.125,
(4, 4): 1.2
},
(3, 3): {
(1, 1): 0.75,
(4, 4): 0.375
},
(4, 4): {
(2, 2): 1.2,
(3, 3): 0.375,
(5, 5): 0.5
},
(5, 5): {
(4, 4): 0.5
},
(6, 6): {
(7, 7): 1.0
},
(7, 7): {
(6, 6): 1.0
}
}
self.GDirected = {
(1, 1): {
(2, 2): 0.125,
(3, 3): 0.75
},
(2, 2): {
(1, 1): 0.125
},
(3, 3): {
(1, 1): 0.75,
(4, 4): 0.375
},
(4, 4): {
(2, 2): 1.2,
(3, 3): 0.375,
(5, 5): 0.5
},
(5, 5): {
(4, 4): 0.5
},
(6, 6): {
(7, 7): 1.0
},
(7, 7): {
(6, 6): 1.0
}
}
self.points = [
((4, 4), (2, 2), 0.51466686561013752, 0.68533313438986243),
((4, 4), (3, 3), 0.077286837052313151, 0.29771316294768685),
((6, 6), (7, 7), 0.82358887253344548, 0.17641112746655452)
]
def test_write_network_to_pysalshp(self):
out = 'output_network.shp'
pynet.write_network_to_pysalshp(self.G, out)
graph = pynet.read_network(out)
self.assertEqual(graph, self.G)
def test_read_network(self):
graph = pynet.read_network(self.net)
self.assertEqual(graph, self.G)
