TEL4, and fix some strange bugs in the code and datasets

.gitignore

@@ -9,4 +9,6 @@ analysis/gis
 analysis/graphs
 !bus/reader_timed.py
 !bus/graph_in*
-.ipynb_checkpoints
+.ipynb_checkpoints
+downloader/
+!downloader/downloader.py

analysis/dijkstra.py

@@ -6,60 +6,15 @@
 import numpy as np
 import networkx as nx
 
+#cross platform interchanges - they share the same node
 interchange_codes = {
     "EW24": "NS1",
     "EW13": "NS25",
     "EW14": "NS26",
-    "DT15": "CC4",
-    "CC1": "NS24",
-    "NE6": "NS24",
-    "BP1": "NS4",
-    "CC15": "NS17",
-    "CE2": "NS27",
-    "CC9": "EW8",
-    "DT14": "EW12",
-    "NE3": "EW16",
-    "CC22": "EW21",
-    "DT35": "CG1",
-    "CC29": "NE1",
-    "DT19": "NE4",
-    "DT12": "NE7",
-    "CC13": "NE12",
-    "STC": "NE16",
-    "PTC": "NE17",
-    "DT26": "CC10",
-    "DT9": "CC19",
-    "DT16": "CE1",
-    "TE2": "NS9",
-    "TE9": "CC17",
-    "TE11": "DT10",
-    "TE14": "NS22",
-    "TE17": "EW16",
-    "TE20": "NS27",
-    "TE31": "DT37",
-    "FL1": "CC32",
-    "JS1": "NS4",
-    "JS8": "EW27",
-    "JE5": "NS1",
-    "CR5": "EW1",
-    "CR8": "NE14",
-    "CR11": "NS16",
-    "CR13": "TE7",
-	  "CP4": "NE17",
-    "CR15": "DT6",
-    "CR17": "EW23",
-    #as leaked in online exhibit
-    "CR21": "JS12",
-    "CR24": "EW30",
-    #unpaid links
-    # hack: represent unpaid links with a distance cost of 99 so only entries/exits use it
-    #"BP6": "DT1",
-    #"DT32": "EW2",
-    #"DT11": "NS21",
-    "CP3": "PE4"
+    "DT16": "CE1"
     }
 
-unpaid_links = ["BP6/DT1", "EW2/DT32", "NS21/DT11"]
+interchange_nodes = []
 
 # we'll use infinity as a default distance to nodes.
 inf = float('inf')
@@ -76,14 +31,23 @@ def pairwise(iterable):
 print("Running pathfinder AND route walker!")
 
 graph = nx.Graph()
-df = pd.read_csv("nodes_unpaidhack.csv")
+df = pd.read_csv("nodes.csv")
 df = df.replace({'n1': interchange_codes, 'n2': interchange_codes})
 df1 = pd.read_csv("stations.csv")
 df1 = df1.replace({'stn_code': interchange_codes})
 df1 = df1.drop_duplicates()
 df2 = pd.DataFrame()
 for index, row in df.iterrows():
     graph.add_edge(row['n1'], row['n2'], weight=row['time'])
+
+# interchange station handling - weight 99 to the joint code so that only entries/exits use it
+for index, row in df1.iterrows():
+  code = row["stn_code"]
+  break_code = code.split('/')
+  if len(break_code) > 1:
+    interchange_nodes.append(code)
+    for subcode in break_code:
+      graph.add_edge(code, subcode, weight=99)
 
 for index1, row1 in tqdm(df1['stn_code'].items(), total = df1.size):
 #row1 = "BP10"
@@ -95,15 +59,14 @@ def pairwise(iterable):
       if row2 not in results[row1]:
         results[row1][row2] = []
 
-      # code here to select routes b
       results[row1][row2] = list(nx.dijkstra_path(graph, row1, row2))
 
 with open ("train_routes_nx_tel3.json", "w") as outfile:
     json.dump(results, outfile, sort_keys=True, indent=4, ensure_ascii=False)
 
 # remove our hack nodes
-#for u in unpaid_links:
-#   graph.remove_node(u)
+for u in interchange_nodes:
+   graph.remove_node(u)
 
 import matplotlib.pyplot as plt
 pos = nx.kamada_kawai_layout(graph, scale=10)  # positions for all nodes

analysis/ints.csv

@@ -0,0 +1,8 @@
+EW24,NS1
+CC1,NS24
+NE6,NS24
+EW13,NS25
+EW14,NS26
+DT15,CC4
+STC,NE16
+PTC,NE17

analysis/nodes.csv

@@ -3,10 +3,12 @@ NS1,NS2,T,3,3
 NS2,NS3,T,2,3
 NS3,NS4,T,4,3
 NS4,NS5,T,3,
+NS4,BP1,T,1,
 NS5,NS7,T,5,
 NS7,NS8,T,3,3
 NS8,NS9,T,2,3
 NS9,NS10,T,3,3
+NS9,TE2,T,3,
 NS10,NS11,T,3,3
 NS11,NS12,T,3,3
 NS12,NS13,T,3,3
@@ -15,16 +17,22 @@ NS14,NS15,T,6,5
 NS15,NS16,T,2,2
 NS16,NS17,T,4,2
 NS17,NS18,T,2,2
+NS17,CC15,T,2,
 NS18,NS19,T,2,2
 NS19,NS20,T,3,2
 NS20,NS21,T,2,2
 NS21,NS22,T,3,2
 NS22,NS23,T,2,2
+NS22,TE14,T,2,
 NS23,NS24,T,2,1
 NS24,NS25,T,3,2
+NS24,NE6,T,3,
+NS24,CC1,T,1,
 NS25,NS26,T,2,2
 NS26,NS27,T,2,2
 NS27,NS28,T,3,1
+NS27,CE2,T,2,
+NS27,TE20,T,4,
 EW1,EW2,T,3,
 EW2,EW3,T,3,
 EW3,EW4,T,3,
@@ -33,19 +41,24 @@ EW5,EW6,T,3,
 EW6,EW7,T,3,
 EW7,EW8,T,2,
 EW8,EW9,T,2,
+EW8,CC9,T,2,
 EW9,EW10,T,3,
 EW10,EW11,T,2,
 EW11,EW12,T,2,
 EW12,EW13,T,3,
+EW12,DT14,T,3,
 EW13,EW14,T,2,
 EW14,EW15,T,3,
 EW15,EW16,T,2,
 EW16,EW17,T,3,
+EW16,NE3,T,2,
+EW16,TE17,T,1,
 EW17,EW18,T,2,
 EW18,EW19,T,3,
 EW19,EW20,T,2,
 EW20,EW21,T,2,
 EW21,EW22,T,3,
+EW21,CC22,T,2,
 EW22,EW23,T,3,
 EW23,EW24,T,4,
 EW24,EW25,T,3,
@@ -59,39 +72,51 @@ EW31,EW32,T,2,
 EW32,EW33,T,2,
 EW4,CG1,T,3,
 CG1,CG2,T,4,
+CG1,DT35,T,3,
 NE1,NE3,T,4,
+NE1,CC29,T,2,
 NE3,NE4,T,1,
+NE3,TE17,T,2,
 NE4,NE5,T,2,
+NE4,DT19,T,1,
 NE5,NE6,T,4,
 NE6,NE7,T,1,
 NE7,NE8,T,1,
+NE7,DT12,T,3,
 NE8,NE9,T,2,
 NE9,NE10,T,3,
 NE10,NE11,T,1,
 NE11,NE12,T,2,
 NE12,NE13,T,3,
+NE12,CC13,T,2,
 NE13,NE14,T,2,
 NE14,NE15,T,2,
 NE15,NE16,T,2,
+NE16,STC,T,2,
 NE16,NE17,T,3,
+NE17,PTC,T,2,
 CC1,CC2,T,2,
 CC2,CC3,T,2,
 CC3,CC4,T,2,
 CC4,CC5,T,2,
+CC4,DT15,T,1,
 CC5,CC6,T,2,
 CC6,CC7,T,2,
 CC7,CC8,T,2,
 CC8,CC9,T,2,
 CC9,CC10,T,2,
 CC10,CC11,T,2,
+CC10,DT26,T,1,
 CC11,CC12,T,2,
 CC12,CC13,T,3,
 CC13,CC14,T,2,
 CC14,CC15,T,2,
 CC15,CC16,T,3,
 CC16,CC17,T,2,
 CC17,CC19,T,5,
+CC17,TE9,T,3,
 CC19,CC20,T,2,
+CC19,DT9,T,2,
 CC20,CC21,T,3,
 CC21,CC22,T,2,
 CC22,CC23,T,2,
@@ -112,6 +137,7 @@ DT7,DT8,T,2,
 DT8,DT9,T,2,
 DT9,DT10,T,2,
 DT10,DT11,T,2,
+DT10,TE11,T,2,
 DT11,DT12,T,3,
 DT12,DT13,T,1,
 DT13,DT14,T,2,
@@ -172,7 +198,8 @@ PE5,PE6,T,1,
 PE6,PE7,T,1,
 PE7,PTC,T,2,
 PTC,PE1,T,3,
-PW1,PW3,T,2,
+PW1,PW2,T,1,
+PW2,PW3,T,1,
 PW3,PW4,T,1,
 PW4,PW5,T,1,
 PW5,PW6,T,1,
@@ -181,20 +208,28 @@ PW7,PTC,T,3,
 PTC,PW1,T,2,
 TE1,TE2,T,2,
 TE2,TE3,T,3,
-TE3,TE4,T,5,
+TE3,TE4,T,4,
 TE4,TE5,T,3,
 TE5,TE6,T,2,
 TE6,TE7,T,2,
-TE7,TE8,T,3,
+TE7,TE8,T,2,
 TE8,TE9,T,3,
 TE9,TE11,T,4,
-TE11,TE12,T,3,
+TE11,TE12,T,2,
 TE12,TE13,T,2,
 TE13,TE14,T,2,
-TE14,TE15,T,3,
-TE15,TE16,T,1,
+TE14,TE15,T,2,
+TE15,TE16,T,2,
 TE16,TE17,T,2,
 TE17,TE18,T,2,
-TE18,TE19,T,2,
+TE18,TE19,T,1,
 TE19,TE20,T,2,
 TE20,TE22,T,3,
+TE20,CE2,T,3,
+TE22,TE23,T,4,
+TE23,TE24,T,2,
+TE24,TE25,T,2,
+TE25,TE26,T,2,
+TE26,TE27,T,2,
+TE27,TE28,T,2,
+TE28,TE29,T,3,