algorithm implemented

routeplanner/maps.py

+
+import networkx as nx
+import pickle
+from chart_studio import plotly as py
+#import plotly.plotly as py
+import random
+from plotly.graph_objs import *
+from plotly.offline import init_notebook_mode, plot, iplot
+init_notebook_mode(connected=True)
+
+
+map_10_dict = {
+	0: {'pos': (0.7798606835438107, 0.6922727646627362), 'connections': [7, 6, 5]}, 
+	1: {'pos': (0.7647837074641568, 0.3252670836724646), 'connections': [4, 3, 2]}, 
+	2: {'pos': (0.7155217893995438, 0.20026498027300055), 'connections': [4, 3, 1]}, 
+	3: {'pos': (0.7076566826610747, 0.3278339270610988), 'connections': [5, 4, 1, 2]}, 
+	4: {'pos': (0.8325506249953353, 0.02310946309985762), 'connections': [1, 2, 3]}, 
+	5: {'pos': (0.49016747075266875, 0.5464878695400415), 'connections': [7, 0, 3]}, 
+	6: {'pos': (0.8820353070895344, 0.6791919587749445), 'connections': [0]}, 
+	7: {'pos': (0.46247219371675075, 0.6258061621642713), 'connections': [0, 5]}, 
+	8: {'pos': (0.11622158839385677, 0.11236327488812581), 'connections': [9]}, 
+	9: {'pos': (0.1285377678230034, 0.3285840695698353), 'connections': [8]}
+}
+
+
+class Map:
+	def __init__(self, G):
+		self._graph = G
+		self.intersections = nx.get_node_attributes(G, "pos")
+		self.roads = [list(G[node]) for node in G.nodes()]
+
+	def save(self, filename):
+		with open(filename, 'wb') as f:
+			pickle.dump(self._graph, f)
+
+def load_map_graph(map_dict):
+	G = nx.Graph()
+	for node in map_dict.keys():
+		G.add_node(node, pos=map_dict[node]['pos'])
+	for node in map_dict.keys():
+		for con_node in map_dict[node]['connections']:
+			G.add_edge(node, con_node)
+	return G
+
+def load_map_10():
+	G = load_map_graph(map_10_dict)
+	return Map(G)
+
+def load_map_40():
+	G = load_map_graph(map_40_dict)
+	return Map(G)
+
+def show_map(M, start=None, goal=None, path=None):
+    G = M._graph
+    pos = nx.get_node_attributes(G, 'pos')
+    edge_trace = Scatter(
+    x=[],
+    y=[],
+    line=Line(width=0.5,color='#888'),
+    hoverinfo='none',
+    mode='lines')
+
+    for edge in G.edges():
+        x0, y0 = G.node[edge[0]]['pos']
+        x1, y1 = G.node[edge[1]]['pos']
+        edge_trace['x'] += [x0, x1, None]
+        edge_trace['y'] += [y0, y1, None]
+
+    node_trace = Scatter(
+        x=[],
+        y=[],
+        text=[],
+        mode='markers',
+        hoverinfo='text',
+        marker=Marker(
+            showscale=False,
+            # colorscale options
+            # 'Greys' | 'Greens' | 'Bluered' | 'Hot' | 'Picnic' | 'Portland' |
+            # Jet' | 'RdBu' | 'Blackbody' | 'Earth' | 'Electric' | 'YIOrRd' | 'YIGnBu'
+            colorscale='Hot',
+            reversescale=True,
+            color=[],
+            size=10,
+            colorbar=dict(
+                thickness=15,
+                title='Node Connections',
+                xanchor='left',
+                titleside='right'
+            ),
+            line=dict(width=2)))
+    for node in G.nodes():
+        x, y = G.node[node]['pos']
+        node_trace['x'].append(x)
+        node_trace['y'].append(y)
+
+    for node, adjacencies in enumerate(G.adjacency_list()):
+        color = 0
+        if path and node in path:
+            color = 2
+        if node == start:
+            color = 3
+        elif node == goal:
+            color = 1
+        # node_trace['marker']['color'].append(len(adjacencies))
+        node_trace['marker']['color'].append(color)
+        node_info = "Intersection " + str(node)
+        node_trace['text'].append(node_info)
+
+    fig = Figure(data=Data([edge_trace, node_trace]),
+                 layout=Layout(
+                    title='<br>Network graph made with Python',
+                    titlefont=dict(size=16),
+                    showlegend=False,
+                    hovermode='closest',
+                    margin=dict(b=20,l=5,r=5,t=40),
+                   
+                    xaxis=XAxis(showgrid=False, zeroline=False, showticklabels=False),
+                    yaxis=YAxis(showgrid=False, zeroline=False, showticklabels=False)))
+
+    iplot(fig)