In [5]:
import numpy as np
import networkx as nx
import matplotlib.pyplot as plt
import os
from IPython.display import SVG
from IPython.display import HTML
In [8]:
pwd()
Out[8]:
'C:\\Users\\chaithcock\\Documents\\repos\\RushHour\\RushHourPy'
In [7]:
# if needed, set the working directory
os.chdir('../../')
In [9]:
pwd()
Out[9]:
'C:\\Users\\chaithcock\\Documents\\repos\\RushHour\\RushHourPy'
In [10]:
%run constants.py
In [ ]:
In [14]:
%run numpy_neighbors.py
%run numpy_display.py
%run numpy_distance_partition.py
v1 = np.array([blank]*36).reshape(6,6)
v1[2,3:5] = hcar
v1[4,1:3] = hcar
#v1[2:4,0] = vcar
#v1[3:,5] = vtruck
v1
nbrs = state_nbrs(board_to_int(v1),4)
svg = svg_neighborhood(board_to_int(v1),4)
HTML(svg)
Out[14]:
In [ ]:
In [7]:
[i for i in range(5)]
Out[7]:
[0, 1, 2, 3, 4]
In [15]:
%run numpy_neighbors.py
In [16]:
%run numpy_generate_states.py
In [17]:
%run numpy_display.py
In [18]:
%run numpy_generate_states.py
In [19]:
%run numpy_components.py
In [ ]:
In [20]:
%run numpy_display.py
%run numpy_neighbors.py
#v1 = np.array([blank]*36).reshape(6,6)
#v1[2,3:5] = hcar
#v1[4,1:3] = hcar
#v1[2:4,0] = vcar
#v1[3:,5] = vtruck
#v1
svg = svg_neighborhood(board_to_int(v1),1)
HTML(svg)
Out[20]:
Testing State Generation
In [21]:
states_2_2 = generate_states(2,2)
In [22]:
states_2_2[0], len(states_2_2)
Out[22]:
((278879418257689031394712044437504, 1), 116650)
In [23]:
counts = np.array( [np.count_nonzero(int_to_board(x[0])) for x in states_2_2])
counts
Out[23]:
array([10, 10, 10, ..., 10, 10, 10])
In [24]:
np.unique(counts)
Out[24]:
array([10])
In [25]:
%run numpy_components.py
In [26]:
comps = components(states_2_2)
In [57]:
In [27]:
sum([len(g.nodes()) for g in comps])
Out[27]:
116650
In [28]:
len(states_2_2)
Out[28]:
116650
In [29]:
import sys
sys.getsizeof(states_2_2)/(2**20)
Out[29]:
0.9952163696289062
In [263]:
g1 = comps[3]
len(g1.nodes())
Out[263]:
136
In [266]:
g1.node[0]
Out[266]:
{'board_int': 273812529653282047465268057211200,
'is_soln_state': False,
'red_col': 1}
In [118]:
#set([x for x in g1.nodes() if g1.node[x]['is_soln_state']])
In [267]:
sum([len(g.nodes()) for g in comps])
Out[267]:
116650
In [268]:
sum([1 for g in comps if len(g.nodes()) == 1])
Out[268]:
18
In [ ]:
In [269]:
%run numpy_distance_partition.py
distance_partition(g1)
In [270]:
g1.graph['distance_partition'].keys()
Out[270]:
dict_keys([0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10])
In [289]:
import json as json
#json.dumps(g1.__dict__)
g = g1
json_graph = {}
graph = {}
graph['distance_partition'] = {}
for k in g.__dict__['graph']['distance_partition']:
graph['distance_partition'][k] = list(g.__dict__['graph']['distance_partition'][k])
json_graph['graph'] = graph
json_graph['nodes'] = {}
for node in g.__dict__['_node']:
json_graph['nodes'][int(node)] = g.__dict__['_node'][node]
for node in json_graph['nodes']:
json_graph['nodes'][node]['is_soln_state'] = str.lower(str(json_graph['nodes'][node]['is_soln_state']))
json_graph['nodes'][node]['board_int'] = str(json_graph['nodes'][node]['board_int'])
json_graph['nodes'][node]['red_col'] = int( json_graph['nodes'][node]['red_col'] )
if 'inner_nbrs' in json_graph['nodes'][node]:
json_graph['nodes'][node]['inner_nbrs'] = list(json_graph['nodes'][node]['inner_nbrs'])
if 'outer_nbrs' in json_graph['nodes'][node]:
json_graph['nodes'][node]['outer_nbrs'] = list(json_graph['nodes'][node]['outer_nbrs'])
g.__dict__.keys() ,g.__dict__['graph'].keys()
links = []
for node in g._adj.keys():
for nbr in g._adj[node].keys():
if nbr > node:
edge = {}
edge['source'] = int(node)
edge['target'] = int(nbr)
links.append(edge)
json_graph['links'] = links
In [319]:
#for node in json_graph['nodes']:
# del( json_graph['nodes'][node]['red_col'])
#g1
#json_graph['nodes'][53]
with open('sample_dump_full_graph.json','a') as f:
f.write(json.dumps(json_graph))
#[type(k) for k in g1.__dict__['_node'][16]['red_col']]
In [317]:
#json_graph['graph']
str_json = json.dumps(json_graph['links'])
str_json
#json.dumps(json_graph)
#type(json_graph['nodes'][8]['outer_nbrs'][0])
#json.dumps(json_graph['nodes'])
#[type(x) for x in json_graph['nodes'].keys() ]
Out[317]:
'[{"source": 53, "target": 71}, {"source": 53, "target": 70}, {"source": 71, "target": 93}, {"source": 71, "target": 92}, {"source": 93, "target": 108}, {"source": 93, "target": 98}, {"source": 108, "target": 109}, {"source": 109, "target": 111}, {"source": 70, "target": 92}, {"source": 70, "target": 97}, {"source": 92, "target": 98}, {"source": 92, "target": 99}, {"source": 97, "target": 99}, {"source": 97, "target": 112}, {"source": 97, "target": 113}, {"source": 98, "target": 100}, {"source": 98, "target": 101}, {"source": 99, "target": 101}, {"source": 99, "target": 114}, {"source": 99, "target": 106}, {"source": 100, "target": 108}, {"source": 100, "target": 102}, {"source": 100, "target": 111}, {"source": 101, "target": 102}, {"source": 101, "target": 103}, {"source": 102, "target": 104}, {"source": 102, "target": 115}, {"source": 103, "target": 104}, {"source": 103, "target": 105}, {"source": 103, "target": 106}, {"source": 104, "target": 116}, {"source": 104, "target": 117}, {"source": 114, "target": 120}, {"source": 115, "target": 116}, {"source": 115, "target": 128}, {"source": 116, "target": 131}, {"source": 116, "target": 129}, {"source": 117, "target": 130}, {"source": 117, "target": 129}, {"source": 119, "target": 123}, {"source": 119, "target": 124}, {"source": 119, "target": 122}, {"source": 120, "target": 121}, {"source": 120, "target": 124}, {"source": 121, "target": 126}, {"source": 123, "target": 126}, {"source": 123, "target": 132}, {"source": 124, "target": 126}, {"source": 124, "target": 125}, {"source": 126, "target": 127}, {"source": 31, "target": 55}, {"source": 31, "target": 36}, {"source": 15, "target": 22}, {"source": 15, "target": 23}, {"source": 15, "target": 24}, {"source": 15, "target": 17}, {"source": 22, "target": 26}, {"source": 22, "target": 40}, {"source": 22, "target": 32}, {"source": 23, "target": 31}, {"source": 23, "target": 25}, {"source": 23, "target": 33}, {"source": 23, "target": 32}, {"source": 24, "target": 31}, {"source": 24, "target": 27}, {"source": 30, "target": 31}, {"source": 30, "target": 64}, {"source": 47, "target": 49}, {"source": 60, "target": 62}, {"source": 60, "target": 65}, {"source": 60, "target": 72}, {"source": 60, "target": 76}, {"source": 62, "target": 63}, {"source": 62, "target": 83}, {"source": 63, "target": 72}, {"source": 63, "target": 64}, {"source": 63, "target": 89}, {"source": 65, "target": 73}, {"source": 65, "target": 81}, {"source": 72, "target": 91}, {"source": 73, "target": 74}, {"source": 73, "target": 94}, {"source": 73, "target": 86}, {"source": 74, "target": 75}, {"source": 74, "target": 95}, {"source": 74, "target": 87}, {"source": 75, "target": 96}, {"source": 75, "target": 90}, {"source": 49, "target": 67}, {"source": 76, "target": 91}, {"source": 76, "target": 81}, {"source": 76, "target": 83}, {"source": 28, "target": 30}, {"source": 28, "target": 63}, {"source": 28, "target": 36}, {"source": 34, "target": 65}, {"source": 34, "target": 37}, {"source": 35, "target": 40}, {"source": 35, "target": 37}, {"source": 35, "target": 38}, {"source": 35, "target": 39}, {"source": 16, "target": 62}, {"source": 16, "target": 28}, {"source": 16, "target": 25}, {"source": 16, "target": 19}, {"source": 18, "target": 28}, {"source": 18, "target": 27}, {"source": 18, "target": 20}, {"source": 17, "target": 25}, {"source": 17, "target": 26}, {"source": 17, "target": 27}, {"source": 0, "target": 1}, {"source": 0, "target": 3}, {"source": 0, "target": 2}, {"source": 1, "target": 13}, {"source": 1, "target": 4}, {"source": 1, "target": 10}, {"source": 13, "target": 41}, {"source": 13, "target": 29}, {"source": 13, "target": 14}, {"source": 41, "target": 47}, {"source": 41, "target": 67}, {"source": 41, "target": 46}, {"source": 7, "target": 53}, {"source": 7, "target": 52}, {"source": 8, "target": 52}, {"source": 8, "target": 54}, {"source": 6, "target": 7}, {"source": 6, "target": 8}, {"source": 52, "target": 71}, {"source": 52, "target": 84}, {"source": 54, "target": 66}, {"source": 54, "target": 84}, {"source": 66, "target": 68}, {"source": 66, "target": 85}, {"source": 68, "target": 88}, {"source": 84, "target": 93}, {"source": 84, "target": 85}, {"source": 85, "target": 108}, {"source": 85, "target": 88}, {"source": 25, "target": 60}, {"source": 25, "target": 34}, {"source": 25, "target": 36}, {"source": 26, "target": 34}, {"source": 26, "target": 35}, {"source": 27, "target": 36}, {"source": 3, "target": 9}, {"source": 3, "target": 5}, {"source": 3, "target": 10}, {"source": 33, "target": 60}, {"source": 33, "target": 55}, {"source": 33, "target": 57}, {"source": 33, "target": 58}, {"source": 33, "target": 59}, {"source": 55, "target": 72}, {"source": 55, "target": 64}, {"source": 55, "target": 77}, {"source": 57, "target": 65}, {"source": 57, "target": 78}, {"source": 57, "target": 86}, {"source": 58, "target": 62}, {"source": 58, "target": 64}, {"source": 58, "target": 79}, {"source": 64, "target": 82}, {"source": 50, "target": 69}, {"source": 40, "target": 47}, {"source": 40, "target": 56}, {"source": 40, "target": 44}, {"source": 59, "target": 76}, {"source": 59, "target": 77}, {"source": 59, "target": 78}, {"source": 59, "target": 79}, {"source": 77, "target": 82}, {"source": 77, "target": 91}, {"source": 78, "target": 80}, {"source": 78, "target": 81}, {"source": 128, "target": 131}, {"source": 131, "target": 134}, {"source": 46, "target": 66}, {"source": 46, "target": 48}, {"source": 48, "target": 67}, {"source": 48, "target": 68}, {"source": 12, "target": 17}, {"source": 12, "target": 21}, {"source": 2, "target": 6}, {"source": 2, "target": 4}, {"source": 2, "target": 5}, {"source": 4, "target": 8}, {"source": 4, "target": 12}, {"source": 4, "target": 29}, {"source": 29, "target": 54}, {"source": 29, "target": 46}, {"source": 19, "target": 23}, {"source": 19, "target": 30}, {"source": 19, "target": 58}, {"source": 20, "target": 24}, {"source": 20, "target": 30}, {"source": 9, "target": 15}, {"source": 9, "target": 19}, {"source": 9, "target": 20}, {"source": 9, "target": 11}, {"source": 32, "target": 34}, {"source": 32, "target": 57}, {"source": 32, "target": 56}, {"source": 56, "target": 61}, {"source": 56, "target": 86}, {"source": 61, "target": 69}, {"source": 61, "target": 87}, {"source": 69, "target": 90}, {"source": 44, "target": 49}, {"source": 44, "target": 50}, {"source": 44, "target": 61}, {"source": 118, "target": 122}, {"source": 118, "target": 130}, {"source": 122, "target": 125}, {"source": 122, "target": 132}, {"source": 125, "target": 127}, {"source": 127, "target": 132}, {"source": 130, "target": 133}, {"source": 133, "target": 135}, {"source": 79, "target": 82}, {"source": 79, "target": 83}, {"source": 80, "target": 107}, {"source": 80, "target": 94}, {"source": 80, "target": 86}, {"source": 82, "target": 89}, {"source": 107, "target": 110}, {"source": 105, "target": 117}, {"source": 105, "target": 119}, {"source": 105, "target": 118}, {"source": 106, "target": 119}, {"source": 106, "target": 120}, {"source": 106, "target": 112}, {"source": 89, "target": 91}, {"source": 94, "target": 95}, {"source": 95, "target": 107}, {"source": 95, "target": 96}, {"source": 96, "target": 110}, {"source": 111, "target": 115}, {"source": 112, "target": 121}, {"source": 112, "target": 123}, {"source": 113, "target": 114}, {"source": 113, "target": 121}, {"source": 45, "target": 50}, {"source": 45, "target": 51}, {"source": 81, "target": 94}, {"source": 83, "target": 89}, {"source": 42, "target": 74}, {"source": 42, "target": 61}, {"source": 42, "target": 51}, {"source": 51, "target": 75}, {"source": 51, "target": 69}, {"source": 36, "target": 72}, {"source": 37, "target": 73}, {"source": 37, "target": 56}, {"source": 37, "target": 42}, {"source": 38, "target": 44}, {"source": 38, "target": 45}, {"source": 38, "target": 42}, {"source": 38, "target": 43}, {"source": 5, "target": 12}, {"source": 5, "target": 11}, {"source": 11, "target": 16}, {"source": 11, "target": 18}, {"source": 11, "target": 17}, {"source": 21, "target": 26}, {"source": 21, "target": 29}, {"source": 21, "target": 39}, {"source": 43, "target": 49}, {"source": 43, "target": 48}, {"source": 39, "target": 47}, {"source": 39, "target": 46}, {"source": 39, "target": 43}, {"source": 88, "target": 109}, {"source": 129, "target": 133}, {"source": 129, "target": 134}, {"source": 134, "target": 135}, {"source": 10, "target": 15}, {"source": 10, "target": 12}, {"source": 10, "target": 14}, {"source": 14, "target": 22}, {"source": 14, "target": 47}, {"source": 14, "target": 21}, {"source": 86, "target": 87}, {"source": 87, "target": 107}, {"source": 87, "target": 90}, {"source": 90, "target": 110}]'
In [138]:
type(g.__dict__['graph']['distance_partition'][0])
Out[138]:
set
In [131]:
%run numpy_display.py
#graph_json = nx.readwrite.json_graph.node_link_data(g1)
g1_json = json.dumps(json_graph)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-131-2fc7711717a5> in <module>()
1 get_ipython().magic('run numpy_display.py')
2 #graph_json = nx.readwrite.json_graph.node_link_data(g1)
----> 3 g1_json = json.dumps(json_graph)
4
~\AppData\Local\Continuum\anaconda3\lib\json\__init__.py in dumps(obj, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
229 cls is None and indent is None and separators is None and
230 default is None and not sort_keys and not kw):
--> 231 return _default_encoder.encode(obj)
232 if cls is None:
233 cls = JSONEncoder
~\AppData\Local\Continuum\anaconda3\lib\json\encoder.py in encode(self, o)
197 # exceptions aren't as detailed. The list call should be roughly
198 # equivalent to the PySequence_Fast that ''.join() would do.
--> 199 chunks = self.iterencode(o, _one_shot=True)
200 if not isinstance(chunks, (list, tuple)):
201 chunks = list(chunks)
~\AppData\Local\Continuum\anaconda3\lib\json\encoder.py in iterencode(self, o, _one_shot)
255 self.key_separator, self.item_separator, self.sort_keys,
256 self.skipkeys, _one_shot)
--> 257 return _iterencode(o, 0)
258
259 def _make_iterencode(markers, _default, _encoder, _indent, _floatstr,
~\AppData\Local\Continuum\anaconda3\lib\json\encoder.py in default(self, o)
178 """
179 raise TypeError("Object of type '%s' is not JSON serializable" %
--> 180 o.__class__.__name__)
181
182 def encode(self, o):
TypeError: Object of type 'set' is not JSON serializable
In [105]:
g1.__dict__.keys(),
g1.__dict__['_adj']
Out[105]:
{0: {1: {}, 2: {}},
1: {0: {}, 3: {}, 4: {}, 5: {}},
2: {0: {}, 5: {}, 8: {}},
3: {1: {}, 7: {}, 9: {}, 11: {}},
4: {1: {}, 6: {}, 7: {}},
5: {1: {}, 2: {}, 9: {}, 10: {}},
6: {4: {}, 31: {}, 32: {}},
7: {3: {}, 4: {}, 27: {}, 31: {}},
8: {2: {}, 10: {}, 17: {}, 18: {}},
9: {3: {}, 5: {}, 12: {}, 13: {}},
10: {5: {}, 8: {}, 13: {}, 19: {}, 20: {}},
11: {3: {}, 12: {}, 27: {}},
12: {9: {}, 11: {}, 14: {}},
13: {9: {}, 10: {}, 14: {}, 15: {}, 16: {}},
14: {12: {}, 13: {}, 21: {}, 22: {}},
15: {13: {}, 19: {}, 22: {}, 23: {}, 24: {}},
16: {13: {}, 20: {}, 21: {}, 24: {}},
17: {8: {}, 20: {}, 25: {}},
18: {8: {}, 19: {}, 25: {}, 26: {}},
19: {10: {}, 15: {}, 18: {}, 30: {}, 34: {}},
20: {10: {}, 16: {}, 17: {}, 30: {}},
21: {14: {}, 16: {}, 28: {}},
22: {14: {}, 15: {}, 28: {}, 35: {}, 36: {}},
23: {15: {}, 29: {}, 34: {}, 36: {}, 37: {}},
24: {15: {}, 16: {}, 28: {}, 29: {}, 30: {}},
25: {17: {}, 18: {}, 30: {}, 38: {}},
26: {18: {}, 34: {}, 38: {}, 39: {}},
27: {7: {}, 11: {}, 33: {}},
28: {21: {}, 22: {}, 24: {}, 40: {}, 41: {}},
29: {23: {}, 24: {}, 41: {}, 42: {}, 43: {}},
30: {19: {}, 20: {}, 24: {}, 25: {}, 43: {}},
31: {6: {}, 7: {}, 33: {}, 45: {}},
32: {6: {}, 44: {}, 45: {}},
33: {27: {}, 31: {}, 49: {}},
34: {19: {}, 23: {}, 26: {}, 43: {}, 51: {}},
35: {22: {}, 40: {}, 52: {}, 53: {}, 54: {}},
36: {22: {}, 23: {}, 41: {}, 52: {}, 55: {}},
37: {23: {}, 42: {}, 51: {}, 55: {}},
38: {25: {}, 26: {}, 43: {}, 50: {}},
39: {26: {}, 50: {}, 51: {}},
40: {28: {}, 35: {}, 56: {}, 57: {}, 58: {}},
41: {28: {}, 29: {}, 36: {}, 56: {}, 59: {}},
42: {29: {}, 37: {}, 48: {}, 59: {}},
43: {29: {}, 30: {}, 34: {}, 38: {}, 48: {}},
44: {32: {}, 46: {}, 47: {}},
45: {31: {}, 32: {}, 47: {}, 49: {}},
46: {44: {}, 61: {}, 62: {}, 63: {}},
47: {44: {}, 45: {}, 60: {}, 61: {}},
48: {42: {}, 43: {}, 50: {}, 51: {}},
49: {33: {}, 45: {}, 60: {}},
50: {38: {}, 39: {}, 48: {}},
51: {34: {}, 37: {}, 39: {}, 48: {}},
52: {35: {}, 36: {}, 56: {}, 67: {}, 68: {}, 69: {}},
53: {35: {}, 57: {}, 68: {}, 70: {}},
54: {35: {}, 58: {}, 69: {}, 70: {}},
55: {36: {}, 37: {}, 59: {}, 67: {}},
56: {40: {}, 41: {}, 52: {}, 74: {}, 76: {}, 77: {}},
57: {40: {}, 53: {}, 73: {}, 77: {}},
58: {40: {}, 54: {}, 73: {}, 74: {}},
59: {41: {}, 42: {}, 55: {}, 76: {}},
60: {47: {}, 49: {}, 64: {}},
61: {46: {}, 47: {}, 64: {}, 66: {}, 80: {}},
62: {46: {}, 65: {}, 80: {}, 81: {}},
63: {46: {}, 65: {}, 66: {}},
64: {60: {}, 61: {}, 72: {}, 82: {}},
65: {62: {}, 63: {}, 71: {}, 83: {}},
66: {61: {}, 63: {}, 71: {}, 72: {}},
67: {52: {}, 55: {}, 76: {}, 78: {}, 79: {}},
68: {52: {}, 53: {}, 75: {}, 77: {}, 78: {}},
69: {52: {}, 54: {}, 74: {}, 75: {}, 79: {}},
70: {53: {}, 54: {}, 73: {}, 75: {}},
71: {65: {}, 66: {}, 80: {}, 84: {}, 85: {}},
72: {64: {}, 66: {}, 84: {}},
73: {57: {}, 58: {}, 70: {}, 97: {}},
74: {56: {}, 58: {}, 69: {}, 97: {}, 98: {}},
75: {68: {}, 69: {}, 70: {}, 97: {}, 99: {}},
76: {56: {}, 59: {}, 67: {}, 98: {}, 100: {}},
77: {56: {}, 57: {}, 68: {}, 97: {}, 100: {}},
78: {67: {}, 68: {}, 99: {}, 100: {}},
79: {67: {}, 69: {}, 98: {}, 99: {}},
80: {61: {}, 62: {}, 71: {}, 82: {}, 87: {}},
81: {62: {}, 83: {}, 87: {}, 92: {}},
82: {64: {}, 80: {}, 84: {}, 95: {}, 106: {}},
83: {65: {}, 81: {}, 85: {}, 90: {}},
84: {71: {}, 72: {}, 82: {}, 86: {}, 107: {}},
85: {71: {}, 83: {}, 86: {}, 87: {}, 88: {}},
86: {84: {}, 85: {}, 91: {}, 95: {}, 108: {}},
87: {80: {}, 81: {}, 85: {}, 89: {}, 95: {}},
88: {85: {}, 89: {}, 90: {}, 91: {}},
89: {87: {}, 88: {}, 92: {}, 94: {}},
90: {83: {}, 88: {}, 92: {}},
91: {86: {}, 88: {}, 93: {}, 94: {}},
92: {81: {}, 89: {}, 90: {}},
93: {91: {}, 96: {}, 105: {}, 108: {}},
94: {89: {}, 91: {}, 95: {}, 96: {}},
95: {82: {}, 86: {}, 87: {}, 94: {}, 102: {}},
96: {93: {}, 94: {}, 102: {}, 103: {}},
97: {73: {}, 74: {}, 75: {}, 77: {}, 101: {}},
98: {74: {}, 76: {}, 79: {}, 101: {}},
99: {75: {}, 78: {}, 79: {}, 101: {}},
100: {76: {}, 77: {}, 78: {}, 101: {}},
101: {97: {}, 98: {}, 99: {}, 100: {}},
102: {95: {}, 96: {}, 104: {}, 106: {}, 108: {}},
103: {96: {}, 104: {}, 105: {}},
104: {102: {}, 103: {}, 109: {}, 110: {}},
105: {93: {}, 103: {}, 110: {}},
106: {82: {}, 102: {}, 107: {}, 109: {}},
107: {84: {}, 106: {}, 108: {}, 111: {}},
108: {86: {}, 93: {}, 102: {}, 107: {}, 110: {}},
109: {104: {}, 106: {}, 111: {}},
110: {104: {}, 105: {}, 108: {}, 111: {}},
111: {107: {}, 109: {}, 110: {}}}
In [93]:
g1.__dict__.keys(),{'nodes':list(g1.__dict__['nodes'])}
Out[93]:
(dict_keys(['node_dict_factory', 'adjlist_outer_dict_factory', 'adjlist_inner_dict_factory', 'edge_attr_dict_factory', 'graph', '_node', '_adj', 'nodes']),
{'nodes': [32,
45,
49,
44,
46,
47,
60,
61,
62,
63,
64,
65,
81,
107,
108,
18,
8,
58,
73,
43,
37,
42,
52,
55,
56,
59,
69,
74,
48,
40,
19,
20,
0,
66,
71,
72,
80,
82,
84,
85,
86,
87,
88,
29,
36,
41,
9,
12,
13,
16,
15,
21,
22,
95,
6,
7,
4,
27,
31,
33,
2,
75,
79,
70,
54,
25,
26,
38,
39,
50,
17,
1,
3,
11,
78,
100,
23,
24,
28,
14,
99,
101,
98,
83,
90,
92,
93,
96,
102,
103,
104,
105,
106,
51,
67,
76,
53,
57,
5,
10,
30,
34,
35,
109,
110,
111,
89,
91,
94,
97,
68,
77]})
In [94]:
g1.__dict__.keys() ,g1.__dict__['graph'].keys()
Out[94]:
(dict_keys(['node_dict_factory', 'adjlist_outer_dict_factory', 'adjlist_inner_dict_factory', 'edge_attr_dict_factory', 'graph', '_node', '_adj', 'nodes']),
dict_keys(['distance_partition']))
In [95]:
g1.__dict__.keys(),g1.__dict__['_node']
Out[95]:
(dict_keys(['node_dict_factory', 'adjlist_outer_dict_factory', 'adjlist_inner_dict_factory', 'edge_attr_dict_factory', 'graph', '_node', '_adj', 'nodes']),
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'red_col': 5,
'soln_distance': 0},
109: {'board_int': 1511164011925362180227072,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
110: {'board_int': 396142323735333591332165910528,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
111: {'board_int': 396142323735333591339667423232,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0}})
In [104]:
g1.__dict__.keys(),
g1.__dict__['_adj']
Out[104]:
{0: {1: {}, 2: {}},
1: {0: {}, 3: {}, 4: {}, 5: {}},
2: {0: {}, 5: {}, 8: {}},
3: {1: {}, 7: {}, 9: {}, 11: {}},
4: {1: {}, 6: {}, 7: {}},
5: {1: {}, 2: {}, 9: {}, 10: {}},
6: {4: {}, 31: {}, 32: {}},
7: {3: {}, 4: {}, 27: {}, 31: {}},
8: {2: {}, 10: {}, 17: {}, 18: {}},
9: {3: {}, 5: {}, 12: {}, 13: {}},
10: {5: {}, 8: {}, 13: {}, 19: {}, 20: {}},
11: {3: {}, 12: {}, 27: {}},
12: {9: {}, 11: {}, 14: {}},
13: {9: {}, 10: {}, 14: {}, 15: {}, 16: {}},
14: {12: {}, 13: {}, 21: {}, 22: {}},
15: {13: {}, 19: {}, 22: {}, 23: {}, 24: {}},
16: {13: {}, 20: {}, 21: {}, 24: {}},
17: {8: {}, 20: {}, 25: {}},
18: {8: {}, 19: {}, 25: {}, 26: {}},
19: {10: {}, 15: {}, 18: {}, 30: {}, 34: {}},
20: {10: {}, 16: {}, 17: {}, 30: {}},
21: {14: {}, 16: {}, 28: {}},
22: {14: {}, 15: {}, 28: {}, 35: {}, 36: {}},
23: {15: {}, 29: {}, 34: {}, 36: {}, 37: {}},
24: {15: {}, 16: {}, 28: {}, 29: {}, 30: {}},
25: {17: {}, 18: {}, 30: {}, 38: {}},
26: {18: {}, 34: {}, 38: {}, 39: {}},
27: {7: {}, 11: {}, 33: {}},
28: {21: {}, 22: {}, 24: {}, 40: {}, 41: {}},
29: {23: {}, 24: {}, 41: {}, 42: {}, 43: {}},
30: {19: {}, 20: {}, 24: {}, 25: {}, 43: {}},
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35: {22: {}, 40: {}, 52: {}, 53: {}, 54: {}},
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43: {29: {}, 30: {}, 34: {}, 38: {}, 48: {}},
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45: {31: {}, 32: {}, 47: {}, 49: {}},
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47: {44: {}, 45: {}, 60: {}, 61: {}},
48: {42: {}, 43: {}, 50: {}, 51: {}},
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62: {46: {}, 65: {}, 80: {}, 81: {}},
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65: {62: {}, 63: {}, 71: {}, 83: {}},
66: {61: {}, 63: {}, 71: {}, 72: {}},
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68: {52: {}, 53: {}, 75: {}, 77: {}, 78: {}},
69: {52: {}, 54: {}, 74: {}, 75: {}, 79: {}},
70: {53: {}, 54: {}, 73: {}, 75: {}},
71: {65: {}, 66: {}, 80: {}, 84: {}, 85: {}},
72: {64: {}, 66: {}, 84: {}},
73: {57: {}, 58: {}, 70: {}, 97: {}},
74: {56: {}, 58: {}, 69: {}, 97: {}, 98: {}},
75: {68: {}, 69: {}, 70: {}, 97: {}, 99: {}},
76: {56: {}, 59: {}, 67: {}, 98: {}, 100: {}},
77: {56: {}, 57: {}, 68: {}, 97: {}, 100: {}},
78: {67: {}, 68: {}, 99: {}, 100: {}},
79: {67: {}, 69: {}, 98: {}, 99: {}},
80: {61: {}, 62: {}, 71: {}, 82: {}, 87: {}},
81: {62: {}, 83: {}, 87: {}, 92: {}},
82: {64: {}, 80: {}, 84: {}, 95: {}, 106: {}},
83: {65: {}, 81: {}, 85: {}, 90: {}},
84: {71: {}, 72: {}, 82: {}, 86: {}, 107: {}},
85: {71: {}, 83: {}, 86: {}, 87: {}, 88: {}},
86: {84: {}, 85: {}, 91: {}, 95: {}, 108: {}},
87: {80: {}, 81: {}, 85: {}, 89: {}, 95: {}},
88: {85: {}, 89: {}, 90: {}, 91: {}},
89: {87: {}, 88: {}, 92: {}, 94: {}},
90: {83: {}, 88: {}, 92: {}},
91: {86: {}, 88: {}, 93: {}, 94: {}},
92: {81: {}, 89: {}, 90: {}},
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95: {82: {}, 86: {}, 87: {}, 94: {}, 102: {}},
96: {93: {}, 94: {}, 102: {}, 103: {}},
97: {73: {}, 74: {}, 75: {}, 77: {}, 101: {}},
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99: {75: {}, 78: {}, 79: {}, 101: {}},
100: {76: {}, 77: {}, 78: {}, 101: {}},
101: {97: {}, 98: {}, 99: {}, 100: {}},
102: {95: {}, 96: {}, 104: {}, 106: {}, 108: {}},
103: {96: {}, 104: {}, 105: {}},
104: {102: {}, 103: {}, 109: {}, 110: {}},
105: {93: {}, 103: {}, 110: {}},
106: {82: {}, 102: {}, 107: {}, 109: {}},
107: {84: {}, 106: {}, 108: {}, 111: {}},
108: {86: {}, 93: {}, 102: {}, 107: {}, 110: {}},
109: {104: {}, 106: {}, 111: {}},
110: {104: {}, 105: {}, 108: {}, 111: {}},
111: {107: {}, 109: {}, 110: {}}}
In [102]:
g1.__dict__.keys(),g1.__dict__['node_dict_factory']
Out[102]:
(dict_keys(['node_dict_factory', 'adjlist_outer_dict_factory', 'adjlist_inner_dict_factory', 'edge_attr_dict_factory', 'graph', '_node', '_adj', 'nodes']),
dict)
In [70]:
%run numpy_display.py
#graph_json = nx.readwrite.json_graph.node_link_data(g1)
g1_json = graph_json(g1)
Out[70]:
{'directed': False,
'graph': {},
'links': [{'source': 32, 'target': 45},
{'source': 32, 'target': 44},
{'source': 32, 'target': 6},
{'source': 45, 'target': 49},
{'source': 45, 'target': 47},
{'source': 45, 'target': 31},
{'source': 49, 'target': 60},
{'source': 49, 'target': 33},
{'source': 44, 'target': 46},
{'source': 44, 'target': 47},
{'source': 46, 'target': 61},
{'source': 46, 'target': 62},
{'source': 46, 'target': 63},
{'source': 47, 'target': 60},
{'source': 47, 'target': 61},
{'source': 60, 'target': 64},
{'source': 61, 'target': 64},
{'source': 61, 'target': 66},
{'source': 61, 'target': 80},
{'source': 62, 'target': 65},
{'source': 62, 'target': 81},
{'source': 62, 'target': 80},
{'source': 63, 'target': 65},
{'source': 63, 'target': 66},
{'source': 64, 'target': 72},
{'source': 64, 'target': 82},
{'source': 65, 'target': 71},
{'source': 65, 'target': 83},
{'source': 81, 'target': 87},
{'source': 81, 'target': 83},
{'source': 81, 'target': 92},
{'source': 107, 'target': 108},
{'source': 107, 'target': 84},
{'source': 107, 'target': 106},
{'source': 107, 'target': 111},
{'source': 108, 'target': 86},
{'source': 108, 'target': 93},
{'source': 108, 'target': 102},
{'source': 108, 'target': 110},
{'source': 18, 'target': 8},
{'source': 18, 'target': 19},
{'source': 18, 'target': 25},
{'source': 18, 'target': 26},
{'source': 8, 'target': 2},
{'source': 8, 'target': 17},
{'source': 8, 'target': 10},
{'source': 58, 'target': 73},
{'source': 58, 'target': 74},
{'source': 58, 'target': 40},
{'source': 58, 'target': 54},
{'source': 73, 'target': 70},
{'source': 73, 'target': 57},
{'source': 73, 'target': 97},
{'source': 43, 'target': 48},
{'source': 43, 'target': 29},
{'source': 43, 'target': 38},
{'source': 43, 'target': 30},
{'source': 43, 'target': 34},
{'source': 37, 'target': 42},
{'source': 37, 'target': 55},
{'source': 37, 'target': 23},
{'source': 37, 'target': 51},
{'source': 42, 'target': 59},
{'source': 42, 'target': 48},
{'source': 42, 'target': 29},
{'source': 52, 'target': 56},
{'source': 52, 'target': 69},
{'source': 52, 'target': 36},
{'source': 52, 'target': 67},
{'source': 52, 'target': 35},
{'source': 52, 'target': 68},
{'source': 55, 'target': 59},
{'source': 55, 'target': 36},
{'source': 55, 'target': 67},
{'source': 56, 'target': 74},
{'source': 56, 'target': 40},
{'source': 56, 'target': 41},
{'source': 56, 'target': 76},
{'source': 56, 'target': 77},
{'source': 59, 'target': 41},
{'source': 59, 'target': 76},
{'source': 69, 'target': 74},
{'source': 69, 'target': 75},
{'source': 69, 'target': 79},
{'source': 69, 'target': 54},
{'source': 74, 'target': 98},
{'source': 74, 'target': 97},
{'source': 48, 'target': 50},
{'source': 48, 'target': 51},
{'source': 40, 'target': 28},
{'source': 40, 'target': 57},
{'source': 40, 'target': 35},
{'source': 19, 'target': 15},
{'source': 19, 'target': 10},
{'source': 19, 'target': 30},
{'source': 19, 'target': 34},
{'source': 20, 'target': 16},
{'source': 20, 'target': 17},
{'source': 20, 'target': 10},
{'source': 20, 'target': 30},
{'source': 0, 'target': 2},
{'source': 0, 'target': 1},
{'source': 66, 'target': 71},
{'source': 66, 'target': 72},
{'source': 71, 'target': 80},
{'source': 71, 'target': 84},
{'source': 71, 'target': 85},
{'source': 72, 'target': 84},
{'source': 80, 'target': 82},
{'source': 80, 'target': 87},
{'source': 82, 'target': 84},
{'source': 82, 'target': 95},
{'source': 82, 'target': 106},
{'source': 84, 'target': 86},
{'source': 85, 'target': 86},
{'source': 85, 'target': 87},
{'source': 85, 'target': 88},
{'source': 85, 'target': 83},
{'source': 86, 'target': 95},
{'source': 86, 'target': 91},
{'source': 87, 'target': 95},
{'source': 87, 'target': 89},
{'source': 88, 'target': 90},
{'source': 88, 'target': 89},
{'source': 88, 'target': 91},
{'source': 29, 'target': 41},
{'source': 29, 'target': 23},
{'source': 29, 'target': 24},
{'source': 36, 'target': 41},
{'source': 36, 'target': 22},
{'source': 36, 'target': 23},
{'source': 41, 'target': 28},
{'source': 9, 'target': 12},
{'source': 9, 'target': 13},
{'source': 9, 'target': 3},
{'source': 9, 'target': 5},
{'source': 12, 'target': 11},
{'source': 12, 'target': 14},
{'source': 13, 'target': 16},
{'source': 13, 'target': 15},
{'source': 13, 'target': 14},
{'source': 13, 'target': 10},
{'source': 16, 'target': 21},
{'source': 16, 'target': 24},
{'source': 15, 'target': 22},
{'source': 15, 'target': 23},
{'source': 15, 'target': 24},
{'source': 21, 'target': 28},
{'source': 21, 'target': 14},
{'source': 22, 'target': 28},
{'source': 22, 'target': 14},
{'source': 22, 'target': 35},
{'source': 95, 'target': 102},
{'source': 95, 'target': 94},
{'source': 6, 'target': 4},
{'source': 6, 'target': 31},
{'source': 7, 'target': 4},
{'source': 7, 'target': 27},
{'source': 7, 'target': 31},
{'source': 7, 'target': 3},
{'source': 4, 'target': 1},
{'source': 27, 'target': 33},
{'source': 27, 'target': 11},
{'source': 31, 'target': 33},
{'source': 2, 'target': 5},
{'source': 75, 'target': 70},
{'source': 75, 'target': 99},
{'source': 75, 'target': 97},
{'source': 75, 'target': 68},
{'source': 79, 'target': 99},
{'source': 79, 'target': 98},
{'source': 79, 'target': 67},
{'source': 70, 'target': 54},
{'source': 70, 'target': 53},
{'source': 54, 'target': 35},
{'source': 25, 'target': 38},
{'source': 25, 'target': 17},
{'source': 25, 'target': 30},
{'source': 26, 'target': 38},
{'source': 26, 'target': 39},
{'source': 26, 'target': 34},
{'source': 38, 'target': 50},
{'source': 39, 'target': 50},
{'source': 39, 'target': 51},
{'source': 1, 'target': 3},
{'source': 1, 'target': 5},
{'source': 3, 'target': 11},
{'source': 78, 'target': 100},
{'source': 78, 'target': 99},
{'source': 78, 'target': 67},
{'source': 78, 'target': 68},
{'source': 100, 'target': 101},
{'source': 100, 'target': 76},
{'source': 100, 'target': 77},
{'source': 23, 'target': 34},
{'source': 24, 'target': 28},
{'source': 24, 'target': 30},
{'source': 99, 'target': 101},
{'source': 101, 'target': 98},
{'source': 101, 'target': 97},
{'source': 98, 'target': 76},
{'source': 83, 'target': 90},
{'source': 90, 'target': 92},
{'source': 92, 'target': 89},
{'source': 93, 'target': 96},
{'source': 93, 'target': 105},
{'source': 93, 'target': 91},
{'source': 96, 'target': 102},
{'source': 96, 'target': 103},
{'source': 96, 'target': 94},
{'source': 102, 'target': 104},
{'source': 102, 'target': 106},
{'source': 103, 'target': 104},
{'source': 103, 'target': 105},
{'source': 104, 'target': 109},
{'source': 104, 'target': 110},
{'source': 105, 'target': 110},
{'source': 106, 'target': 109},
{'source': 51, 'target': 34},
{'source': 67, 'target': 76},
{'source': 53, 'target': 57},
{'source': 53, 'target': 35},
{'source': 53, 'target': 68},
{'source': 57, 'target': 77},
{'source': 5, 'target': 10},
{'source': 109, 'target': 111},
{'source': 110, 'target': 111},
{'source': 89, 'target': 94},
{'source': 91, 'target': 94},
{'source': 97, 'target': 77},
{'source': 68, 'target': 77}],
'multigraph': False,
'nodes': [{'id': 32, 'outer_nbrs': [6], 'soln_dist': 0},
{'id': 45, 'outer_nbrs': [31], 'soln_dist': 0},
{'id': 49, 'outer_nbrs': [33], 'soln_dist': 0},
{'id': 44, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 46, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 47, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 60, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 61, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 62, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 63, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 64, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 65, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 81, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 107, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 108, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 18, 'inner_nbrs': [8, 19], 'outer_nbrs': [25, 26], 'soln_dist': 7},
{'id': 8, 'inner_nbrs': [2, 10], 'outer_nbrs': [17, 18], 'soln_dist': 6},
{'id': 58, 'inner_nbrs': [40, 54], 'outer_nbrs': [73, 74], 'soln_dist': 9},
{'id': 73, 'inner_nbrs': [57, 58, 70], 'outer_nbrs': [97], 'soln_dist': 10},
{'id': 43, 'inner_nbrs': [34, 30], 'outer_nbrs': [48, 38], 'soln_dist': 8},
{'id': 37, 'inner_nbrs': [23], 'outer_nbrs': [42], 'soln_dist': 8},
{'id': 42, 'inner_nbrs': [37, 29], 'outer_nbrs': [], 'soln_dist': 9},
{'id': 52,
'inner_nbrs': [35, 36],
'outer_nbrs': [56, 67, 68, 69],
'soln_dist': 8},
{'id': 55, 'inner_nbrs': [36], 'outer_nbrs': [59, 67], 'soln_dist': 8},
{'id': 56,
'inner_nbrs': [40, 41, 52],
'outer_nbrs': [74, 76, 77],
'soln_dist': 9},
{'id': 59, 'inner_nbrs': [41, 55], 'outer_nbrs': [76], 'soln_dist': 9},
{'id': 69,
'inner_nbrs': [52, 54],
'outer_nbrs': [74, 75, 79],
'soln_dist': 9},
{'id': 74,
'inner_nbrs': [56, 58, 69],
'outer_nbrs': [97, 98],
'soln_dist': 10},
{'id': 48, 'inner_nbrs': [43, 51], 'outer_nbrs': [50], 'soln_dist': 9},
{'id': 40,
'inner_nbrs': [35, 28],
'outer_nbrs': [56, 57, 58],
'soln_dist': 8},
{'id': 19, 'inner_nbrs': [10], 'outer_nbrs': [34, 18, 30], 'soln_dist': 6},
{'id': 20, 'inner_nbrs': [10], 'outer_nbrs': [17, 30], 'soln_dist': 6},
{'id': 0, 'inner_nbrs': [1], 'outer_nbrs': [2], 'soln_dist': 4},
{'id': 66, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 71, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 72, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 80, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 82, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 84, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 85, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 86, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 87, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 88, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 29, 'inner_nbrs': [24, 23], 'outer_nbrs': [42], 'soln_dist': 8},
{'id': 36, 'inner_nbrs': [22], 'outer_nbrs': [41, 52, 55], 'soln_dist': 7},
{'id': 41, 'inner_nbrs': [36, 28], 'outer_nbrs': [56, 59], 'soln_dist': 8},
{'id': 9, 'inner_nbrs': [3], 'outer_nbrs': [13], 'soln_dist': 4},
{'id': 12, 'inner_nbrs': [11], 'outer_nbrs': [14], 'soln_dist': 4},
{'id': 13, 'inner_nbrs': [9], 'outer_nbrs': [16, 15], 'soln_dist': 5},
{'id': 16, 'inner_nbrs': [13], 'outer_nbrs': [24], 'soln_dist': 6},
{'id': 15, 'inner_nbrs': [13], 'outer_nbrs': [24, 23], 'soln_dist': 6},
{'id': 21, 'inner_nbrs': [14], 'outer_nbrs': [28], 'soln_dist': 6},
{'id': 22, 'inner_nbrs': [14], 'outer_nbrs': [35, 36, 28], 'soln_dist': 6},
{'id': 95, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 6, 'inner_nbrs': [32], 'outer_nbrs': [4], 'soln_dist': 1},
{'id': 7, 'inner_nbrs': [31], 'outer_nbrs': [3], 'soln_dist': 2},
{'id': 4, 'inner_nbrs': [6], 'outer_nbrs': [1], 'soln_dist': 2},
{'id': 27, 'inner_nbrs': [33], 'outer_nbrs': [11], 'soln_dist': 2},
{'id': 31, 'inner_nbrs': [45], 'outer_nbrs': [7], 'soln_dist': 1},
{'id': 33, 'inner_nbrs': [49], 'outer_nbrs': [27], 'soln_dist': 1},
{'id': 2, 'inner_nbrs': [0, 5], 'outer_nbrs': [8], 'soln_dist': 5},
{'id': 75,
'inner_nbrs': [68, 69, 70],
'outer_nbrs': [97, 99],
'soln_dist': 10},
{'id': 79, 'inner_nbrs': [67, 69], 'outer_nbrs': [98, 99], 'soln_dist': 10},
{'id': 70, 'inner_nbrs': [53, 54], 'outer_nbrs': [73, 75], 'soln_dist': 9},
{'id': 54, 'inner_nbrs': [35], 'outer_nbrs': [58, 69, 70], 'soln_dist': 8},
{'id': 25, 'inner_nbrs': [17, 18, 30], 'outer_nbrs': [38], 'soln_dist': 8},
{'id': 26, 'inner_nbrs': [18, 34], 'outer_nbrs': [38, 39], 'soln_dist': 8},
{'id': 38, 'inner_nbrs': [25, 26, 43], 'outer_nbrs': [50], 'soln_dist': 9},
{'id': 39, 'inner_nbrs': [26, 51], 'outer_nbrs': [50], 'soln_dist': 9},
{'id': 50, 'inner_nbrs': [48, 38, 39], 'outer_nbrs': [], 'soln_dist': 10},
{'id': 17, 'inner_nbrs': [8, 20], 'outer_nbrs': [25], 'soln_dist': 7},
{'id': 1, 'inner_nbrs': [4], 'outer_nbrs': [0, 5], 'soln_dist': 3},
{'id': 3, 'inner_nbrs': [7], 'outer_nbrs': [9], 'soln_dist': 3},
{'id': 11, 'inner_nbrs': [27], 'outer_nbrs': [12], 'soln_dist': 3},
{'id': 78, 'inner_nbrs': [67, 68], 'outer_nbrs': [99, 100], 'soln_dist': 10},
{'id': 100,
'inner_nbrs': [76, 77, 78],
'outer_nbrs': [101],
'soln_dist': 11},
{'id': 23, 'inner_nbrs': [15], 'outer_nbrs': [29, 37], 'soln_dist': 7},
{'id': 24, 'inner_nbrs': [16, 15], 'outer_nbrs': [29], 'soln_dist': 7},
{'id': 28, 'inner_nbrs': [21, 22], 'outer_nbrs': [40, 41], 'soln_dist': 7},
{'id': 14, 'inner_nbrs': [12], 'outer_nbrs': [21, 22], 'soln_dist': 5},
{'id': 99, 'inner_nbrs': [75, 78, 79], 'outer_nbrs': [101], 'soln_dist': 11},
{'id': 101, 'inner_nbrs': [97, 98, 99, 100], 'soln_dist': 12},
{'id': 98, 'inner_nbrs': [74, 76, 79], 'outer_nbrs': [101], 'soln_dist': 11},
{'id': 83, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 90, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 92, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 93, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 96, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 102, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 103, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 104, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 105, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 106, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 51, 'inner_nbrs': [34], 'outer_nbrs': [48, 39], 'soln_dist': 8},
{'id': 67,
'inner_nbrs': [52, 55],
'outer_nbrs': [76, 78, 79],
'soln_dist': 9},
{'id': 76,
'inner_nbrs': [56, 59, 67],
'outer_nbrs': [98, 100],
'soln_dist': 10},
{'id': 53, 'inner_nbrs': [35], 'outer_nbrs': [57, 68, 70], 'soln_dist': 8},
{'id': 57, 'inner_nbrs': [40, 53], 'outer_nbrs': [73, 77], 'soln_dist': 9},
{'id': 5, 'inner_nbrs': [1], 'outer_nbrs': [2, 10], 'soln_dist': 4},
{'id': 10, 'inner_nbrs': [5], 'outer_nbrs': [8, 19, 20], 'soln_dist': 5},
{'id': 30, 'inner_nbrs': [19, 20], 'outer_nbrs': [25, 43], 'soln_dist': 7},
{'id': 34, 'inner_nbrs': [19], 'outer_nbrs': [51, 26, 43], 'soln_dist': 7},
{'id': 35,
'inner_nbrs': [22],
'outer_nbrs': [40, 52, 53, 54],
'soln_dist': 7},
{'id': 109, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 110, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 111, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 89, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 91, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 94, 'outer_nbrs': [], 'soln_dist': 0},
{'id': 97,
'inner_nbrs': [73, 74, 75, 77],
'outer_nbrs': [101],
'soln_dist': 11},
{'id': 68,
'inner_nbrs': [52, 53],
'outer_nbrs': [75, 77, 78],
'soln_dist': 9},
{'id': 77,
'inner_nbrs': [56, 57, 68],
'outer_nbrs': [97, 100],
'soln_dist': 10}]}
In [69]:
g1.edges()
Out[69]:
EdgeView([(32, 45), (32, 44), (32, 6), (45, 49), (45, 47), (45, 31), (49, 60), (49, 33), (44, 46), (44, 47), (46, 61), (46, 62), (46, 63), (47, 60), (47, 61), (60, 64), (61, 64), (61, 66), (61, 80), (62, 65), (62, 81), (62, 80), (63, 65), (63, 66), (64, 72), (64, 82), (65, 71), (65, 83), (81, 87), (81, 83), (81, 92), (107, 108), (107, 84), (107, 106), (107, 111), (108, 86), (108, 93), (108, 102), (108, 110), (18, 8), (18, 19), (18, 25), (18, 26), (8, 2), (8, 17), (8, 10), (58, 73), (58, 74), (58, 40), (58, 54), (73, 70), (73, 57), (73, 97), (43, 48), (43, 29), (43, 38), (43, 30), (43, 34), (37, 42), (37, 55), (37, 23), (37, 51), (42, 59), (42, 48), (42, 29), (52, 56), (52, 69), (52, 36), (52, 67), (52, 35), (52, 68), (55, 59), (55, 36), (55, 67), (56, 74), (56, 40), (56, 41), (56, 76), (56, 77), (59, 41), (59, 76), (69, 74), (69, 75), (69, 79), (69, 54), (74, 98), (74, 97), (48, 50), (48, 51), (40, 28), (40, 57), (40, 35), (19, 15), (19, 10), (19, 30), (19, 34), (20, 16), (20, 17), (20, 10), (20, 30), (0, 2), (0, 1), (66, 71), (66, 72), (71, 80), (71, 84), (71, 85), (72, 84), (80, 82), (80, 87), (82, 84), (82, 95), (82, 106), (84, 86), (85, 86), (85, 87), (85, 88), (85, 83), (86, 95), (86, 91), (87, 95), (87, 89), (88, 90), (88, 89), (88, 91), (29, 41), (29, 23), (29, 24), (36, 41), (36, 22), (36, 23), (41, 28), (9, 12), (9, 13), (9, 3), (9, 5), (12, 11), (12, 14), (13, 16), (13, 15), (13, 14), (13, 10), (16, 21), (16, 24), (15, 22), (15, 23), (15, 24), (21, 28), (21, 14), (22, 28), (22, 14), (22, 35), (95, 102), (95, 94), (6, 4), (6, 31), (7, 4), (7, 27), (7, 31), (7, 3), (4, 1), (27, 33), (27, 11), (31, 33), (2, 5), (75, 70), (75, 99), (75, 97), (75, 68), (79, 99), (79, 98), (79, 67), (70, 54), (70, 53), (54, 35), (25, 38), (25, 17), (25, 30), (26, 38), (26, 39), (26, 34), (38, 50), (39, 50), (39, 51), (1, 3), (1, 5), (3, 11), (78, 100), (78, 99), (78, 67), (78, 68), (100, 101), (100, 76), (100, 77), (23, 34), (24, 28), (24, 30), (99, 101), (101, 98), (101, 97), (98, 76), (83, 90), (90, 92), (92, 89), (93, 96), (93, 105), (93, 91), (96, 102), (96, 103), (96, 94), (102, 104), (102, 106), (103, 104), (103, 105), (104, 109), (104, 110), (105, 110), (106, 109), (51, 34), (67, 76), (53, 57), (53, 35), (53, 68), (57, 77), (5, 10), (109, 111), (110, 111), (89, 94), (91, 94), (97, 77), (68, 77)])
In [163]:
type(graph_json['graph']['distance_partition'][0])
Out[163]:
set
In [177]:
graph_json?
In [40]:
for x in g1.nodes:
print(x)
32
45
49
44
46
47
60
61
62
63
64
65
81
107
108
18
8
58
73
43
37
42
52
55
56
59
69
74
48
40
19
20
0
66
71
72
80
82
84
85
86
87
88
29
36
41
9
12
13
16
15
21
22
95
6
7
4
27
31
33
2
75
79
70
54
25
26
38
39
50
17
1
3
11
78
100
23
24
28
14
99
101
98
83
90
92
93
96
102
103
104
105
106
51
67
76
53
57
5
10
30
34
35
109
110
111
89
91
94
97
68
77
In [176]:
import json
with open("graph.json",'w') as outfile:
json.dump(graph_json,outfile)
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-176-eb3f5729b548> in <module>()
1 import json
2 with open("graph.json",'w') as outfile:
----> 3 json.dump(graph_json,outfile)
~\AppData\Local\Continuum\anaconda3\lib\json\__init__.py in dump(obj, fp, skipkeys, ensure_ascii, check_circular, allow_nan, cls, indent, separators, default, sort_keys, **kw)
177 # could accelerate with writelines in some versions of Python, at
178 # a debuggability cost
--> 179 for chunk in iterable:
180 fp.write(chunk)
181
~\AppData\Local\Continuum\anaconda3\lib\json\encoder.py in _iterencode(o, _current_indent_level)
428 yield from _iterencode_list(o, _current_indent_level)
429 elif isinstance(o, dict):
--> 430 yield from _iterencode_dict(o, _current_indent_level)
431 else:
432 if markers is not None:
~\AppData\Local\Continuum\anaconda3\lib\json\encoder.py in _iterencode_dict(dct, _current_indent_level)
402 else:
403 chunks = _iterencode(value, _current_indent_level)
--> 404 yield from chunks
405 if newline_indent is not None:
406 _current_indent_level -= 1
~\AppData\Local\Continuum\anaconda3\lib\json\encoder.py in _iterencode_list(lst, _current_indent_level)
323 else:
324 chunks = _iterencode(value, _current_indent_level)
--> 325 yield from chunks
326 if newline_indent is not None:
327 _current_indent_level -= 1
~\AppData\Local\Continuum\anaconda3\lib\json\encoder.py in _iterencode_dict(dct, _current_indent_level)
402 else:
403 chunks = _iterencode(value, _current_indent_level)
--> 404 yield from chunks
405 if newline_indent is not None:
406 _current_indent_level -= 1
~\AppData\Local\Continuum\anaconda3\lib\json\encoder.py in _iterencode(o, _current_indent_level)
435 raise ValueError("Circular reference detected")
436 markers[markerid] = o
--> 437 o = _default(o)
438 yield from _iterencode(o, _current_indent_level)
439 if markers is not None:
~\AppData\Local\Continuum\anaconda3\lib\json\encoder.py in default(self, o)
178 """
179 raise TypeError("Object of type '%s' is not JSON serializable" %
--> 180 o.__class__.__name__)
181
182 def encode(self, o):
TypeError: Object of type 'bool_' is not JSON serializable
In [146]:
graph_json
Out[146]:
{'directed': False,
'graph': {'distance_partition': {0: {32,
44,
45,
46,
47,
49,
60,
61,
62,
63,
64,
65,
66,
71,
72,
80,
81,
82,
83,
84,
85,
86,
87,
88,
89,
90,
91,
92,
93,
94,
95,
96,
102,
103,
104,
105,
106,
107,
108,
109,
110,
111},
1: {6, 31, 33},
2: {4, 7, 27},
3: {1, 3, 11},
4: {0, 5, 9, 12},
5: {2, 10, 13, 14},
6: {8, 15, 16, 19, 20, 21, 22},
7: {17, 18, 23, 24, 28, 30, 34, 35, 36},
8: {25, 26, 29, 37, 40, 41, 43, 51, 52, 53, 54, 55},
9: {38, 39, 42, 48, 56, 57, 58, 59, 67, 68, 69, 70},
10: {50, 73, 74, 75, 76, 77, 78, 79},
11: {97, 98, 99, 100},
12: {101}}},
'links': [{'foo': 3, 'source': 32, 'target': 45},
{'source': 32, 'target': 44},
{'source': 32, 'target': 6},
{'source': 45, 'target': 49},
{'source': 45, 'target': 47},
{'source': 45, 'target': 31},
{'source': 49, 'target': 60},
{'source': 49, 'target': 33},
{'source': 44, 'target': 46},
{'source': 44, 'target': 47},
{'source': 46, 'target': 61},
{'source': 46, 'target': 62},
{'source': 46, 'target': 63},
{'source': 47, 'target': 60},
{'source': 47, 'target': 61},
{'source': 60, 'target': 64},
{'source': 61, 'target': 64},
{'source': 61, 'target': 66},
{'source': 61, 'target': 80},
{'source': 62, 'target': 65},
{'source': 62, 'target': 81},
{'source': 62, 'target': 80},
{'source': 63, 'target': 65},
{'source': 63, 'target': 66},
{'source': 64, 'target': 72},
{'source': 64, 'target': 82},
{'source': 65, 'target': 71},
{'source': 65, 'target': 83},
{'source': 81, 'target': 87},
{'source': 81, 'target': 83},
{'source': 81, 'target': 92},
{'source': 107, 'target': 108},
{'source': 107, 'target': 84},
{'source': 107, 'target': 106},
{'source': 107, 'target': 111},
{'source': 108, 'target': 86},
{'source': 108, 'target': 93},
{'source': 108, 'target': 102},
{'source': 108, 'target': 110},
{'source': 18, 'target': 8},
{'source': 18, 'target': 19},
{'source': 18, 'target': 25},
{'source': 18, 'target': 26},
{'source': 8, 'target': 2},
{'source': 8, 'target': 17},
{'source': 8, 'target': 10},
{'source': 58, 'target': 73},
{'source': 58, 'target': 74},
{'source': 58, 'target': 40},
{'source': 58, 'target': 54},
{'source': 73, 'target': 70},
{'source': 73, 'target': 57},
{'source': 73, 'target': 97},
{'source': 43, 'target': 48},
{'source': 43, 'target': 29},
{'source': 43, 'target': 38},
{'source': 43, 'target': 30},
{'source': 43, 'target': 34},
{'source': 37, 'target': 42},
{'source': 37, 'target': 55},
{'source': 37, 'target': 23},
{'source': 37, 'target': 51},
{'source': 42, 'target': 59},
{'source': 42, 'target': 48},
{'source': 42, 'target': 29},
{'source': 52, 'target': 56},
{'source': 52, 'target': 69},
{'source': 52, 'target': 36},
{'source': 52, 'target': 67},
{'source': 52, 'target': 35},
{'source': 52, 'target': 68},
{'source': 55, 'target': 59},
{'source': 55, 'target': 36},
{'source': 55, 'target': 67},
{'source': 56, 'target': 74},
{'source': 56, 'target': 40},
{'source': 56, 'target': 41},
{'source': 56, 'target': 76},
{'source': 56, 'target': 77},
{'source': 59, 'target': 41},
{'source': 59, 'target': 76},
{'source': 69, 'target': 74},
{'source': 69, 'target': 75},
{'source': 69, 'target': 79},
{'source': 69, 'target': 54},
{'source': 74, 'target': 98},
{'source': 74, 'target': 97},
{'source': 48, 'target': 50},
{'source': 48, 'target': 51},
{'source': 40, 'target': 28},
{'source': 40, 'target': 57},
{'source': 40, 'target': 35},
{'source': 19, 'target': 15},
{'source': 19, 'target': 10},
{'source': 19, 'target': 30},
{'source': 19, 'target': 34},
{'source': 20, 'target': 16},
{'source': 20, 'target': 17},
{'source': 20, 'target': 10},
{'source': 20, 'target': 30},
{'source': 0, 'target': 2},
{'source': 0, 'target': 1},
{'source': 66, 'target': 71},
{'source': 66, 'target': 72},
{'source': 71, 'target': 80},
{'source': 71, 'target': 84},
{'source': 71, 'target': 85},
{'source': 72, 'target': 84},
{'source': 80, 'target': 82},
{'source': 80, 'target': 87},
{'source': 82, 'target': 84},
{'source': 82, 'target': 95},
{'source': 82, 'target': 106},
{'source': 84, 'target': 86},
{'source': 85, 'target': 86},
{'source': 85, 'target': 87},
{'source': 85, 'target': 88},
{'source': 85, 'target': 83},
{'source': 86, 'target': 95},
{'source': 86, 'target': 91},
{'source': 87, 'target': 95},
{'source': 87, 'target': 89},
{'source': 88, 'target': 90},
{'source': 88, 'target': 89},
{'source': 88, 'target': 91},
{'source': 29, 'target': 41},
{'source': 29, 'target': 23},
{'source': 29, 'target': 24},
{'source': 36, 'target': 41},
{'source': 36, 'target': 22},
{'source': 36, 'target': 23},
{'source': 41, 'target': 28},
{'source': 9, 'target': 12},
{'source': 9, 'target': 13},
{'source': 9, 'target': 3},
{'source': 9, 'target': 5},
{'source': 12, 'target': 11},
{'source': 12, 'target': 14},
{'source': 13, 'target': 16},
{'source': 13, 'target': 15},
{'source': 13, 'target': 14},
{'source': 13, 'target': 10},
{'source': 16, 'target': 21},
{'source': 16, 'target': 24},
{'source': 15, 'target': 22},
{'source': 15, 'target': 23},
{'source': 15, 'target': 24},
{'source': 21, 'target': 28},
{'source': 21, 'target': 14},
{'source': 22, 'target': 28},
{'source': 22, 'target': 14},
{'source': 22, 'target': 35},
{'source': 95, 'target': 102},
{'source': 95, 'target': 94},
{'source': 6, 'target': 4},
{'source': 6, 'target': 31},
{'source': 7, 'target': 4},
{'source': 7, 'target': 27},
{'source': 7, 'target': 31},
{'source': 7, 'target': 3},
{'source': 4, 'target': 1},
{'source': 27, 'target': 33},
{'source': 27, 'target': 11},
{'source': 31, 'target': 33},
{'source': 2, 'target': 5},
{'source': 75, 'target': 70},
{'source': 75, 'target': 99},
{'source': 75, 'target': 97},
{'source': 75, 'target': 68},
{'source': 79, 'target': 99},
{'source': 79, 'target': 98},
{'source': 79, 'target': 67},
{'source': 70, 'target': 54},
{'source': 70, 'target': 53},
{'source': 54, 'target': 35},
{'source': 25, 'target': 38},
{'source': 25, 'target': 17},
{'source': 25, 'target': 30},
{'source': 26, 'target': 38},
{'source': 26, 'target': 39},
{'source': 26, 'target': 34},
{'source': 38, 'target': 50},
{'source': 39, 'target': 50},
{'source': 39, 'target': 51},
{'source': 1, 'target': 3},
{'source': 1, 'target': 5},
{'source': 3, 'target': 11},
{'source': 78, 'target': 100},
{'source': 78, 'target': 99},
{'source': 78, 'target': 67},
{'source': 78, 'target': 68},
{'source': 100, 'target': 101},
{'source': 100, 'target': 76},
{'source': 100, 'target': 77},
{'source': 23, 'target': 34},
{'source': 24, 'target': 28},
{'source': 24, 'target': 30},
{'source': 99, 'target': 101},
{'source': 101, 'target': 98},
{'source': 101, 'target': 97},
{'source': 98, 'target': 76},
{'source': 83, 'target': 90},
{'source': 90, 'target': 92},
{'source': 92, 'target': 89},
{'source': 93, 'target': 96},
{'source': 93, 'target': 105},
{'source': 93, 'target': 91},
{'source': 96, 'target': 102},
{'source': 96, 'target': 103},
{'source': 96, 'target': 94},
{'source': 102, 'target': 104},
{'source': 102, 'target': 106},
{'source': 103, 'target': 104},
{'source': 103, 'target': 105},
{'source': 104, 'target': 109},
{'source': 104, 'target': 110},
{'source': 105, 'target': 110},
{'source': 106, 'target': 109},
{'source': 51, 'target': 34},
{'source': 67, 'target': 76},
{'source': 53, 'target': 57},
{'source': 53, 'target': 35},
{'source': 53, 'target': 68},
{'source': 57, 'target': 77},
{'source': 5, 'target': 10},
{'source': 109, 'target': 111},
{'source': 110, 'target': 111},
{'source': 89, 'target': 94},
{'source': 91, 'target': 94},
{'source': 97, 'target': 77},
{'source': 68, 'target': 77}],
'multigraph': False,
'nodes': [{'board_int': 162259895799233978881293873578304,
'id': 32,
'is_soln_state': True,
'outer_nbrs': {6},
'red_col': 5,
'soln_distance': 0},
{'board_int': 618972381798731150685897024,
'id': 45,
'is_soln_state': True,
'outer_nbrs': {31},
'red_col': 5,
'soln_distance': 0},
{'board_int': 2362165048212491075904,
'id': 49,
'is_soln_state': True,
'outer_nbrs': {33},
'red_col': 5,
'soln_distance': 0},
{'board_int': 162259895799239743488816907812864,
'id': 44,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 162259897310397018007103292309504,
'id': 46,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 618972387563338673720131584,
'id': 47,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 2367929655735525310464,
'id': 60,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 620483544837856960104628224,
'id': 61,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 162259897310397018007043280207872,
'id': 62,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 162656038122968339673080779505664,
'id': 63,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 1513525204174021909807104,
'id': 64,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 162656038122968339673020767404032,
'id': 65,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 162259897310397018007035778695168,
'id': 81,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 396142323735342598538922033152,
'id': 107,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 396142323735342598531420520448,
'id': 108,
'is_soln_state': True,
'outer_nbrs': set(),
'red_col': 5,
'soln_distance': 0},
{'board_int': 162259897314380541949445031329792,
'id': 18,
'inner_nbrs': {8, 19},
'is_soln_state': False,
'outer_nbrs': {25, 26},
'red_col': 1,
'soln_distance': 7},
{'board_int': 162259897314380541949505043431424,
'id': 8,
'inner_nbrs': {2, 10},
'is_soln_state': False,
'outer_nbrs': {17, 18},
'red_col': 1,
'soln_distance': 6},
{'board_int': 396142327718866540940673155072,
'id': 58,
'inner_nbrs': {40, 54},
'is_soln_state': False,
'outer_nbrs': {73, 74},
'red_col': 1,
'soln_distance': 9},
{'board_int': 396142327718857533741418545152,
'id': 73,
'inner_nbrs': {57, 58, 70},
'is_soln_state': False,
'outer_nbrs': {97},
'red_col': 1,
'soln_distance': 10},
{'board_int': 162656038123465428985483911757824,
'id': 43,
'inner_nbrs': {30, 34},
'is_soln_state': False,
'outer_nbrs': {38, 48},
'red_col': 2,
'soln_distance': 8},
{'board_int': 620484041927169362299191296,
'id': 37,
'inner_nbrs': {23},
'is_soln_state': False,
'outer_nbrs': {42},
'red_col': 2,
'soln_distance': 8},
{'board_int': 396761296613248835339786387456,
'id': 42,
'inner_nbrs': {29, 37},
'is_soln_state': False,
'outer_nbrs': set(),
'red_col': 2,
'soln_distance': 9},
{'board_int': 1511661110245024579190784,
'id': 52,
'inner_nbrs': {35, 36},
'is_soln_state': False,
'outer_nbrs': {56, 67, 68, 69},
'red_col': 2,
'soln_distance': 8},
{'board_int': 1514022293486424104370176,
'id': 55,
'inner_nbrs': {36},
'is_soln_state': False,
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In [34]:
json = nx.readwrite.json_graph.node_link_data(g2)
In [35]:
json
Out[35]:
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In [ ]:
partition = {}
partition[0] = set([x for x in g.nodes() if 5 in x[1] ])
remaining_nodes = set(g.nodes())
remaining_nodes.difference_update(partition[0])
i = 1
In [ ]:
partition[i] = set()
tmp = set(partition[0])
In [ ]:
x = tmp.pop()
x
In [ ]:
nbrs = set(g.neighbors(x) )
remaining_nodes.difference_update(nbrs)
In [ ]:
nbrs
In [ ]:
nbrs.difference_update(partition[i-1])
nbrs
In [ ]:
partition[i].update(nbrs)
In [ ]:
partition[1]
In [ ]:
x = np.zeros((6,6),dtype=int)
x[2,1:3] = hcar
x[0:3,0] = vtruck
x[0,1:3] = hcar
x[0:3,3] = vtruck
x[3:5,2] = vcar
x[3,3:6] = htruck
x[5,2:5] = htruck
x[4:6,5] = vcar
x
In [ ]:
HTML(svg_from_state(x,(int(1),int(2))).tostring())
In [ ]:
comps = components( [(board_to_int(x),(int(1),int(2)))] )
comps
In [ ]:
g = comps[0]
len(g.nodes()), g.size()
In [ ]:
g.graph['dist_partition'] = distance_partition(g)
In [ ]:
g.graph['dist_partition'].keys()
In [ ]:
data = np.array([len(g.graph['dist_partition'][i]) for i in range(len(g.graph['dist_partition'].keys()))])
data
In [ ]:
H = nx.blockmodel(g,list(g.graph['dist_partition'].values()))
In [ ]:
len(H.nodes())
In [ ]:
nx.draw_networkx(H)
plt.show()
In [ ]:
%run numpy_generate_states.py
In [ ]:
states = generate_states(2,2)
len(states)
In [ ]:
comps = components( states )
len(comps)
In [ ]:
sizes_2_2 = np.array([ [i,len(comps[i].nodes())] for i in range(len(comps)) ])
In [ ]:
np.histogram(sizes_2_2)
In [ ]:
np.sum(sizes_2_2)
In [ ]:
comp_states = set()
gen_states = set(states)
for g in comps:
comp_states.update(set(g.nodes()))
gen_states.difference_update(comp_states)
len(gen_states)
In [ ]:
gen_states
In [ ]:
s = set(comp_states.pop())
In [ ]:
t = set(gen_states.pop())
In [ ]:
t,s
In [ ]:
t.difference_update(s)
t
In [ ]:
plt.hist(sizes_2_2, bins='auto')
plt.show()
In [ ]:
len(np.unique(sizes_2_2))
In [ ]:
plt.scatter(sizes_2_2[:,0],sizes_2_2[:,1])
plt.show()
In [ ]:
#[ [f1(comps[i]),f2(comps[i]),f3(comps[i])] for i in range(len(comps))]
In [ ]:
#nodes, #issolvable,
In [ ]:
np.array([x[1][1] for x in g.nodes()])
In [ ]:
solvable = [g for g in comps if g.graph['solvable']]
unsolvable = [g for g in comps if not g.graph['solvable']]
In [ ]:
len(solvable),len(unsolvable)
In [ ]:
g = unsolvable[0]
len(g.nodes())
In [ ]:
g.nodes()
In [ ]:
HTML(svg_from_state(int_to_board(63230561102196900165),(int(1),int(2))).tostring())
In [ ]:
[x for x in range(1,6)]
In [26]:
keys = ['a','b','c']
new_keys = range(len(keys))
keys,list(new_keys)
Out[26]:
(['a', 'b', 'c'], [0, 1, 2])
In [28]:
list(zip(keys,new_keys))
Out[28]:
[('a', 0), ('b', 1), ('c', 2)]
In [29]:
{x[0]:x[1] for x in zip(keys,new_keys)}
Out[29]:
{'a': 0, 'b': 1, 'c': 2}
In [30]:
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-30-f5302386464f> in <module>()
----> 1 g
NameError: name 'g' is not defined
In [31]:
Out[31]:
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In [118]:
g1
Out[118]:
<networkx.classes.graph.Graph at 0x247f1e1f978>
In [122]:
list(g1.edges())[:3]
Out[122]:
[(32, 45), (32, 44), (32, 6)]
In [124]:
g1[32], g1[45]
Out[124]:
(AtlasView({45: {}, 44: {}, 6: {}}),
AtlasView({32: {}, 49: {}, 47: {}, 31: {}}))
In [128]:
g1.node[47]['soln_distance']
Out[128]:
0
In [137]:
g1.edges[(32,45)].intra_partition
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-137-095ebeb43cc9> in <module>()
----> 1 g1.edges[(32,45)].delete('foo')
AttributeError: 'dict' object has no attribute 'delete'
In [132]:
g1.edges[(32,45)]
Out[132]:
{'foo': 3}
In [ ]:
Content source: crhaithcock/RushHour
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