diff --git a/input_images/skeleton_neom.png b/input_images/skeleton_neom.png
new file mode 100644
index 0000000..3d9efa9
Binary files /dev/null and b/input_images/skeleton_neom.png differ
diff --git a/input_images/skeleton_pringle.png b/input_images/skeleton_pringle.png
new file mode 100644
index 0000000..5a65b97
Binary files /dev/null and b/input_images/skeleton_pringle.png differ
diff --git a/map_server/map.png b/map_server/map.png
new file mode 100644
index 0000000..fbd876d
Binary files /dev/null and b/map_server/map.png differ
diff --git a/map_server/map.yaml b/map_server/map.yaml
new file mode 100644
index 0000000..2e52554
--- /dev/null
+++ b/map_server/map.yaml
@@ -0,0 +1,8 @@
+image: neom.png
+resolution: 0.050000
+origin: [-10.000000, -10.000000, 0.000000]
+negate: 0
+occupied_thresh: 0.65
+free_thresh: 0.196
+mode: scale
+
diff --git a/map_server/map_pringle.png b/map_server/map_pringle.png
new file mode 100644
index 0000000..21607ef
Binary files /dev/null and b/map_server/map_pringle.png differ
diff --git a/map_server/map_pringle_dilate.png b/map_server/map_pringle_dilate.png
new file mode 100644
index 0000000..b27ddd1
Binary files /dev/null and b/map_server/map_pringle_dilate.png differ
diff --git a/map_server/neom.png b/map_server/neom.png
new file mode 100644
index 0000000..ebea5de
Binary files /dev/null and b/map_server/neom.png differ
diff --git a/output_yaml/connected_graph__edited.yaml b/output_yaml/connected_graph__edited.yaml
new file mode 100644
index 0000000..7302475
--- /dev/null
+++ b/output_yaml/connected_graph__edited.yaml
@@ -0,0 +1,3207 @@
+0:
+  node_pos:
+  - 394.8
+  - 456.1
+  outward_edges:
+    13: 41.99974738359452
+    40: 33.31837655305863
+    66: 33.65979790687561
+    85: 42.60832602977753
+    228: 10.310660153627396
+    231: 10.28137083053589
+    237: 12.293502861261368
+    266: 10.443502861261369
+1:
+  node_pos:
+  - 262.8
+  - 444.3
+  outward_edges:
+    28: 33.69619399905205
+    32: 42.049747383594514
+    77: 36.09619399905205
+    86: 42.86543279886246
+    248: 10.372792184352875
+    251: 10.393502861261368
+    258: 14.809188276529312
+    286: 10.452081507444383
+2:
+  node_pos:
+  - 368.90000000000003
+  - 366.5
+  outward_edges:
+    14: 46.85330076813698
+    15: 33.692640614509585
+    52: 32.1512192606926
+    297: 10.331370830535889
+    300: 10.372792184352875
+    306: 10.922792184352875
+    330: 17.429898953437807
+3:
+  node_pos:
+  - 407.40000000000003
+  - 628.1500000000001
+  outward_edges:
+    3: 6.501219260692597
+    123: 15.331980460882187
+4:
+  node_pos:
+  - 340.05
+  - 622.0
+  outward_edges:
+    7: 55.46248904466629
+    42: 237.84589756131174
+    93: 24.224011445045473
+    100: 12.709188276529312
+    142: 13.4506096303463
+5:
+  node_pos:
+  - 241.5
+  - 586.1
+  outward_edges:
+    5: 2.3727921843528748
+    42: 6.91923879981041
+    54: 8.156244522333145
+6:
+  node_pos:
+  - 218.0
+  - 576.9
+  outward_edges:
+    6: 16.56482316851616
+    21: 17.271320307254793
+    65: 168.98473217487336
+    133: 11.74827550649643
+7:
+  node_pos:
+  - 345.3
+  - 568.1
+  outward_edges:
+    4: 55.46248904466629
+    34: 13.924873691797258
+    74: 38.91352979838848
+    139: 10.289949476718903
+    150: 17.626524075865746
+8:
+  node_pos:
+  - 363.20000000000005
+  - 530.65
+  outward_edges:
+    9: 16.95538227558136
+    24: 3.5399494767189026
+9:
+  node_pos:
+  - 350.55
+  - 525.8000000000001
+  outward_edges:
+    8: 16.95538227558136
+    84: 7.502691137790681
+    97: 13.035533845424652
+10:
+  node_pos:
+  - 347.75
+  - 500.90000000000003
+  outward_edges:
+    38: 8.716295045614244
+    76: 3.847056245803833
+11:
+  node_pos:
+  - 328.85
+  - 450.6
+  outward_edges:
+    26: 42.48259009122849
+    28: 34.11187941431999
+    30: 42.06543279886246
+    40: 33.95477264523506
+    238: 10.352081507444382
+    241: 10.372792184352875
+    247: 12.659188276529314
+    276: 10.322792184352876
+12:
+  node_pos:
+  - 431.1
+  - 417.6
+  outward_edges:
+    13: 33.37695519924164
+    66: 41.99619399905205
+    259: 10.331370830535889
+    262: 10.343502861261369
+    268: 12.172792184352875
+    325: 10.622792184352875
+13:
+  node_pos:
+  - 398.20000000000005
+  - 415.0
+  outward_edges:
+    0: 41.99974738359452
+    12: 33.37695519924164
+    14: 33.842640614509584
+    15: 46.453300768136984
+    264: 10.28137083053589
+    267: 10.352081507444382
+    273: 12.576345568895341
+    296: 14.87634556889534
+14:
+  node_pos:
+  - 365.1
+  - 412.35
+  outward_edges:
+    2: 46.85330076813698
+    13: 33.842640614509584
+    30: 32.90979790687561
+    40: 42.079036706686026
+    269: 10.310660153627396
+    272: 10.393502861261368
+    278: 11.643502861261368
+    299: 15.297056245803834
+15:
+  node_pos:
+  - 401.95000000000005
+  - 369.5
+  outward_edges:
+    2: 33.692640614509585
+    13: 46.453300768136984
+    294: 10.352081507444382
+    301: 12.405634891986848
+    321: 16.159188276529314
+    328: 7.548528122901917
+16:
+  node_pos:
+  - 304.15000000000003
+  - 360.5
+  outward_edges:
+    17: 29.859797906875613
+    31: 46.9518288910389
+    52: 34.17903670668602
+    88: 33.86690467596054
+    307: 10.393502861261368
+    310: 10.434924215078354
+    316: 12.538477599620819
+    334: 8.489949476718904
+17:
+  node_pos:
+  - 306.1
+  - 331.3
+  outward_edges:
+    16: 29.859797906875613
+    17: 2.114213538169861
+    18: 33.816904675960544
+    333: 10.455634891986847
+    338: 12.37634556889534
+18:
+  node_pos:
+  - 273.15000000000003
+  - 328.0
+  outward_edges:
+    17: 33.816904675960544
+    29: 39.92192993760109
+    78: 31.139087229967117
+    88: 29.735533845424655
+    335: 10.310660153627396
+    337: 10.434924215078354
+    340: 9.893502861261368
+    343: 8.439949476718903
+19:
+  node_pos:
+  - 278.75
+  - 249.40000000000003
+  outward_edges:
+    20: 39.80269113779068
+    29: 39.86482316851616
+    89: 30.352691137790682
+    358: 10.26923879981041
+    361: 10.160660153627397
+    368: 9.098528122901916
+    375: 8.515685415267944
+20:
+  node_pos:
+  - 281.15000000000003
+  - 210.05
+  outward_edges:
+    19: 39.80269113779068
+    41: 39.599137753248215
+    49: 32.98700572252274
+    79: 23.279898953437808
+    373: 10.177817445993425
+    376: 9.648528122901917
+    381: 12.510660153627397
+    410: 8.344974738359452
+21:
+  node_pos:
+  - 235.15
+  - 578.5
+  outward_edges:
+    6: 17.271320307254793
+    37: 50.37878409028053
+    54: 2.332842707633972
+    158: 7.455634891986847
+22:
+  node_pos:
+  - 428.3
+  - 545.8000000000001
+  outward_edges:
+    35: 7.464823168516159
+    58: 5.199137753248215
+    73: 4.9642135381698616
+    94: 33.6728965818882
+23:
+  node_pos:
+  - 441.0
+  - 538.15
+  outward_edges:
+    50: 5.736396092176438
+    53: 2.7899494767189026
+24:
+  node_pos:
+  - 367.0
+  - 531.5500000000001
+  outward_edges:
+    8: 3.5399494767189026
+    50: 79.77436845898629
+    80: 51.231118214130404
+    159: 10.393502861261368
+25:
+  node_pos:
+  - 243.55
+  - 531.15
+  outward_edges:
+    37: 7.7142135381698616
+    96: 20.56984843015671
+    163: 10.497056245803833
+    211: 13.38847759962082
+26:
+  node_pos:
+  - 325.1
+  - 492.05
+  outward_edges:
+    11: 42.48259009122849
+    38: 40.43883461356163
+    39: 34.166904675960545
+    201: 10.538477599620819
+    213: 12.714213538169862
+    240: 10.884924215078355
+27:
+  node_pos:
+  - 347.40000000000003
+  - 212.5
+  outward_edges:
+    49: 33.81629504561425
+    90: 33.28345233798027
+    91: 38.26629504561424
+    369: 10.198528122901918
+    372: 12.810660153627396
+    396: 7.0949747383594515
+28:
+  node_pos:
+  - 295.75
+  - 447.45000000000005
+  outward_edges:
+    1: 33.69619399905205
+    11: 34.11187941431999
+    31: 42.40685415267944
+    39: 42.64472212195397
+    243: 10.372792184352875
+    246: 10.497056245803833
+    252: 12.347056245803834
+    281: 10.643502861261368
+29:
+  node_pos:
+  - 276.2
+  - 288.8
+  outward_edges:
+    18: 39.92192993760109
+    19: 39.86482316851616
+    99: 35.82903670668602
+    341: 10.289949476718903
+    344: 10.260660153627397
+    357: 14.426345568895341
+    360: 8.536396092176437
+30:
+  node_pos:
+  - 332.75
+  - 409.55
+  outward_edges:
+    11: 42.06543279886246
+    14: 32.90979790687561
+    31: 33.71690467596054
+    52: 47.23467159867287
+    274: 10.393502861261368
+    277: 10.372792184352875
+    283: 12.367766922712327
+    304: 15.471320307254793
+31:
+  node_pos:
+  - 299.90000000000003
+  - 406.20000000000005
+  outward_edges:
+    16: 46.9518288910389
+    28: 42.40685415267944
+    30: 33.71690467596054
+    32: 34.782590091228485
+    279: 10.434924215078354
+    282: 10.41421353816986
+    288: 13.371320307254791
+    309: 15.209188276529312
+32:
+  node_pos:
+  - 266.2
+  - 403.15000000000003
+  outward_edges:
+    1: 42.049747383594514
+    31: 34.782590091228485
+    87: 36.33614347577095
+    88: 47.31396092176438
+    284: 10.352081507444382
+    287: 10.426345568895341
+    293: 14.72634556889534
+    314: 15.447056245803834
+33:
+  node_pos:
+  - 416.0
+  - 593.35
+  outward_edges:
+    33: 2.5914213538169864
+34:
+  node_pos:
+  - 359.0
+  - 570.1
+  outward_edges:
+    7: 13.924873691797258
+    34: 1.5328427076339723
+    137: 9.91421353816986
+35:
+  node_pos:
+  - 429.8
+  - 540.35
+  outward_edges:
+    22: 7.464823168516159
+    68: 2.81923879981041
+    73: 2.2485281229019165
+36:
+  node_pos:
+  - 418.45000000000005
+  - 539.7
+  outward_edges:
+    80: 13.21984843015671
+37:
+  node_pos:
+  - 235.8
+  - 532.1
+  outward_edges:
+    21: 50.37878409028053
+    25: 7.7142135381698616
+    155: 11.15979790687561
+    204: 24.60391039848328
+38:
+  node_pos:
+  - 356.15000000000003
+  - 498.95000000000005
+  outward_edges:
+    10: 8.716295045614244
+    26: 40.43883461356163
+    75: 183.0484843015671
+    201: 29.358935660123826
+    225: 48.380255967378616
+39:
+  node_pos:
+  - 291.85
+  - 489.0
+  outward_edges:
+    26: 34.166904675960545
+    28: 42.64472212195397
+    86: 33.92903670668602
+    212: 10.48847759962082
+    215: 12.405634891986848
+    245: 10.943502861261369
+40:
+  node_pos:
+  - 362.0938415527344
+  - 453.5181579589844
+  outward_edges:
+    0: 33.31837655305863
+    11: 33.95477264523506
+    14: 42.079036706686026
+    72: 43.12045806050301
+    233: 10.331370830535889
+    236: 10.352081507444382
+    242: 12.417766922712326
+    271: 10.49350286126137
+41:
+  node_pos:
+  - 283.0
+  - 170.75
+  outward_edges:
+    20: 39.599137753248215
+    67: 33.099137753248215
+    69: 22.71984843015671
+    71: 10.532842707633973
+    408: 10.198528122901918
+    411: 10.227817445993423
+    416: 11.56923879981041
+42:
+  node_pos:
+  - 240.65
+  - 593.3000000000001
+  outward_edges:
+    4: 237.84589756131174
+    5: 6.91923879981041
+    64: 21.9911687374115
+    105: 15.737005722522737
+43:
+  node_pos:
+  - 361.20000000000005
+  - 533.0500000000001
+  outward_edges:
+    74: 10.70710676908493
+    83: 14.740559107065202
+    94: 52.82056245803833
+    151: 13.355129659175873
+44:
+  node_pos:
+  - 285.8
+  - 507.80000000000007
+  outward_edges:
+    48: 14.466295045614244
+    59: 5.210660153627396
+    96: 73.36726168990135
+    183: 10.41421353816986
+45:
+  node_pos:
+  - 444.25
+  - 576.9
+  outward_edges:
+    45: 2.4363960921764374
+    55: 7.11923879981041
+    62: 5.857106769084931
+46:
+  node_pos:
+  - 405.95000000000005
+  - 573.4
+  outward_edges:
+    56: 17.981980460882188
+    57: 17.903731891512873
+    94: 27.294112491607667
+    147: 16.4006096303463
+47:
+  node_pos:
+  - 448.05
+  - 549.45
+  outward_edges:
+    47: 0.8707106769084931
+    53: 17.38987536728382
+48:
+  node_pos:
+  - 276.85
+  - 501.45000000000005
+  outward_edges:
+    44: 14.466295045614244
+    59: 10.288477599620819
+    196: 10.179898953437807
+49:
+  node_pos:
+  - 313.85
+  - 211.0
+  outward_edges:
+    20: 32.98700572252274
+    27: 33.81629504561425
+    67: 38.366295045614244
+    371: 10.21923879981041
+    377: 12.610660153627396
+    406: 7.224264061450959
+50:
+  node_pos:
+  - 434.95000000000005
+  - 537.45
+  outward_edges:
+    23: 5.736396092176438
+    24: 79.77436845898629
+    68: 3.853553384542465
+51:
+  node_pos:
+  - 341.20000000000005
+  - 173.5
+  outward_edges:
+    67: 25.46776692271233
+    71: 68.2439642727375
+    407: 15.06923879981041
+52:
+  node_pos:
+  - 337.40000000000003
+  - 363.65000000000003
+  outward_edges:
+    2: 32.1512192606926
+    16: 34.17903670668602
+    30: 47.23467159867287
+    302: 10.372792184352875
+    305: 10.293502861261368
+    311: 12.809188276529312
+    332: 17.13345233798027
+53:
+  node_pos:
+  - 442.35
+  - 535.35
+  outward_edges:
+    23: 2.7899494767189026
+    47: 17.38987536728382
+    75: 18.699494767189027
+54:
+  node_pos:
+  - 237.9
+  - 579.0500000000001
+  outward_edges:
+    5: 8.156244522333145
+    21: 2.332842707633972
+    54: 6.220458060503006
+55:
+  node_pos:
+  - 436.95000000000005
+  - 577.3000000000001
+  outward_edges:
+    45: 7.11923879981041
+    55: 1.2414213538169863
+    56: 13.866295045614244
+    62: 11.322792184352876
+56:
+  node_pos:
+  - 423.45000000000005
+  - 576.1
+  outward_edges:
+    46: 17.981980460882188
+    55: 13.866295045614244
+    56: 2.2414213538169863
+57:
+  node_pos:
+  - 391.3
+  - 573.1
+  outward_edges:
+    46: 17.903731891512873
+    57: 1.3621320307254792
+    138: 7.834924215078354
+58:
+  node_pos:
+  - 432.75
+  - 548.65
+  outward_edges:
+    22: 5.199137753248215
+    58: 2.353553384542465
+    62: 36.89472212195397
+    146: 22.16482316851616
+59:
+  node_pos:
+  - 287.05
+  - 502.45000000000005
+  outward_edges:
+    44: 5.210660153627396
+    48: 10.288477599620819
+    63: 55.75954529047013
+    190: 9.981370830535889
+60:
+  node_pos:
+  - 246.8
+  - 498.55
+  outward_edges:
+    65: 17.182337474822997
+    96: 64.93944424390793
+    195: 9.943502861261369
+    209: 18.561269783973696
+61:
+  node_pos:
+  - 343.75
+  - 173.10000000000002
+  outward_edges:
+    61: 2.2035533845424653
+    91: 5.493502861261368
+    420: 14.061879414319993
+62:
+  node_pos:
+  - 444.15000000000003
+  - 570.75
+  outward_edges:
+    45: 5.857106769084931
+    55: 11.322792184352876
+    58: 36.89472212195397
+    136: 10.802081507444383
+    146: 14.18847759962082
+63:
+  node_pos:
+  - 334.90000000000003
+  - 527.1
+  outward_edges:
+    59: 55.75954529047013
+    63: 4.860660153627396
+    92: 41.61248904466629
+    97: 6.239949476718903
+64:
+  node_pos:
+  - 253.3
+  - 602.25
+  outward_edges:
+    42: 21.9911687374115
+    93: 131.55519023537636
+    104: 9.434924215078354
+    125: 12.887362736463547
+    130: 7.728427076339722
+65:
+  node_pos:
+  - 232.55
+  - 490.6
+  outward_edges:
+    6: 168.98473217487336
+    60: 17.182337474822997
+    86: 28.749494767189027
+    216: 11.37462107539177
+    256: 12.161626797914506
+66:
+  node_pos:
+  - 427.90000000000003
+  - 458.8
+  outward_edges:
+    0: 33.65979790687561
+    12: 41.99619399905205
+    217: 10.393502861261368
+    226: 10.393502861261368
+    232: 12.455634891986847
+    261: 10.481370830535889
+67:
+  node_pos:
+  - 315.75
+  - 172.85000000000002
+  outward_edges:
+    41: 33.099137753248215
+    49: 38.366295045614244
+    51: 25.46776692271233
+    404: 10.20710676908493
+    407: 9.827817445993425
+    412: 12.122792184352875
+68:
+  node_pos:
+  - 430.70000000000005
+  - 537.3000000000001
+  outward_edges:
+    35: 2.81923879981041
+    50: 3.853553384542465
+    82: 2.912132030725479
+69:
+  node_pos:
+  - 260.65000000000003
+  - 169.20000000000002
+  outward_edges:
+    41: 22.71984843015671
+    71: 36.367261689901355
+    79: 40.36335129141808
+    413: 10.364213538169862
+    416: 10.579898953437805
+    421: 16.232590091228484
+70:
+  node_pos:
+  - 415.25
+  - 187.35000000000002
+  outward_edges:
+    91: 105.20315254926682
+    98: 36.11873356699944
+    382: 10.227817445993423
+    392: 9.957716399431229
+    403: 12.518376553058625
+71:
+  node_pos:
+  - 283.45
+  - 159.8
+  outward_edges:
+    41: 10.532842707633973
+    51: 68.2439642727375
+    69: 36.367261689901355
+    417: 10.028427076339723
+    422: 7.937005722522736
+72:
+  node_pos:
+  - 358.45000000000005
+  - 495.6
+  outward_edges:
+    40: 43.12045806050301
+    85: 33.80477264523506
+    199: 10.455634891986847
+    235: 11.514213538169862
+73:
+  node_pos:
+  - 427.3
+  - 540.75
+  outward_edges:
+    22: 4.9642135381698616
+    35: 2.2485281229019165
+    82: 2.8621320307254794
+74:
+  node_pos:
+  - 350.15000000000003
+  - 533.2
+  outward_edges:
+    7: 38.91352979838848
+    43: 10.70710676908493
+    83: 2.5071067690849307
+    149: 10.352081507444382
+75:
+  node_pos:
+  - 434.6
+  - 519.35
+  outward_edges:
+    38: 183.0484843015671
+    53: 18.699494767189027
+    84: 96.33832938075066
+    181: 11.22634556889534
+76:
+  node_pos:
+  - 345.05
+  - 498.20000000000005
+  outward_edges:
+    10: 3.847056245803833
+    84: 13.481549337506294
+    194: 15.854772645235062
+77:
+  node_pos:
+  - 227.5
+  - 441.15000000000003
+  outward_edges:
+    1: 36.09619399905205
+    87: 41.729036706686024
+    253: 10.434924215078354
+    257: 10.331370830535889
+    291: 10.089949476718903
+78:
+  node_pos:
+  - 242.60000000000002
+  - 325.3
+  outward_edges:
+    18: 31.139087229967117
+    78: 2.332842707633972
+    339: 10.331370830535889
+79:
+  node_pos:
+  - 257.90000000000003
+  - 208.75
+  outward_edges:
+    20: 23.279898953437808
+    69: 40.36335129141808
+    89: 41.60721116662026
+    378: 10.68345233798027
+    381: 10.198528122901918
+    415: 8.848528122901916
+80:
+  node_pos:
+  - 416.95000000000005
+  - 536.1
+  outward_edges:
+    24: 51.231118214130404
+    36: 13.21984843015671
+    95: 2.881370830535889
+    162: 9.239949476718904
+81:
+  node_pos:
+  - 342.35
+  - 567.25
+  outward_edges:
+    92: 11.334924215078354
+    166: 11.043250244855882
+82:
+  node_pos:
+  - 427.35
+  - 537.4
+  outward_edges:
+    68: 2.912132030725479
+    73: 2.8621320307254794
+83:
+  node_pos:
+  - 350.25
+  - 530.6
+  outward_edges:
+    43: 14.740559107065202
+    74: 2.5071067690849307
+84:
+  node_pos:
+  - 347.90000000000003
+  - 518.8000000000001
+  outward_edges:
+    9: 7.502691137790681
+    75: 96.33832938075066
+    76: 13.481549337506294
+    175: 10.524011445045472
+    194: 9.56482316851616
+85:
+  node_pos:
+  - 391.45000000000005
+  - 497.90000000000003
+  outward_edges:
+    0: 42.60832602977753
+    72: 33.80477264523506
+    200: 12.455634891986847
+    222: 14.271320307254792
+    230: 11.093502861261369
+86:
+  node_pos:
+  - 258.95
+  - 486.1
+  outward_edges:
+    1: 42.86543279886246
+    39: 33.92903670668602
+    65: 28.749494767189027
+    214: 10.538477599620819
+    216: 16.800609630346298
+    250: 11.22634556889534
+87:
+  node_pos:
+  - 230.9
+  - 400.35
+  outward_edges:
+    32: 36.33614347577095
+    77: 41.729036706686024
+    99: 123.26848095059395
+    289: 10.393502861261368
+    292: 10.75771639943123
+    355: 13.522792184352875
+88:
+  node_pos:
+  - 271.1
+  - 357.25
+  outward_edges:
+    16: 33.86690467596054
+    18: 29.735533845424655
+    32: 47.31396092176438
+    312: 10.621320307254791
+    315: 10.393502861261368
+    336: 8.552081507444383
+89:
+  node_pos:
+  - 248.75
+  - 247.10000000000002
+  outward_edges:
+    19: 30.352691137790682
+    79: 41.60721116662026
+    99: 41.830865597724916
+    364: 11.242640614509583
+    367: 10.405634891986848
+    380: 8.08345233798027
+90:
+  node_pos:
+  - 380.5
+  - 214.0
+  outward_edges:
+    27: 33.28345233798027
+    370: 12.277817445993424
+    386: 10.26923879981041
+    401: 15.789949476718903
+91:
+  node_pos:
+  - 349.35
+  - 174.45000000000002
+  outward_edges:
+    27: 38.26629504561424
+    61: 5.493502861261368
+    70: 105.20315254926682
+    394: 10.20710676908493
+    397: 10.209188276529312
+92:
+  node_pos:
+  - 330.90000000000003
+  - 567.0500000000001
+  outward_edges:
+    63: 41.61248904466629
+    81: 11.334924215078354
+    92: 5.205634891986847
+93:
+  node_pos:
+  - 316.95000000000005
+  - 618.75
+  outward_edges:
+    4: 24.224011445045473
+    64: 131.55519023537636
+    100: 10.973401814699173
+    102: 7.402081507444382
+    132: 10.656244522333147
+94:
+  node_pos:
+  - 408.45000000000005
+  - 546.5
+  outward_edges:
+    22: 33.6728965818882
+    43: 52.82056245803833
+    46: 27.294112491607667
+    147: 10.372792184352875
+    154: 7.764213538169861
+95:
+  node_pos:
+  - 416.0
+  - 539.15
+  outward_edges:
+    80: 2.881370830535889
+    95: 2.2899494767189026
+96:
+  node_pos:
+  - 263.7
+  - 533.15
+  outward_edges:
+    25: 20.56984843015671
+    44: 73.36726168990135
+    60: 64.93944424390793
+    163: 9.460660153627396
+    185: 16.854163014888766
+    198: 12.788477599620819
+97:
+  node_pos:
+  - 341.35
+  - 527.7
+  outward_edges:
+    9: 13.035533845424652
+    63: 6.239949476718903
+    164: 10.828427076339722
+98:
+  node_pos:
+  - 448.25
+  - 194.60000000000002
+  outward_edges:
+    70: 36.11873356699944
+    98: 1.3778174459934236
+    391: 7.494974738359452
+    393: 14.72903670668602
+99:
+  node_pos:
+  - 241.25
+  - 286.2
+  outward_edges:
+    29: 35.82903670668602
+    87: 123.26848095059395
+    89: 41.830865597724916
+    347: 10.517766922712326
+    356: 10.479898953437806
+    366: 8.460660153627396
+100:
+  node_pos:
+  - 327.40000000000003
+  - 621.5
+  outward_edges:
+    4: 12.709188276529312
+    93: 10.973401814699173
+101:
+  node_pos:
+  - 312.55
+  - 602.4
+  outward_edges:
+    102: 11.496803629398347
+102:
+  node_pos:
+  - 318.15000000000003
+  - 611.2
+  outward_edges:
+    93: 7.402081507444382
+    101: 11.496803629398347
+103:
+  node_pos:
+  - 446.05
+  - 595.9
+  outward_edges:
+    103: 2.2828427076339723
+104:
+  node_pos:
+  - 243.8
+  - 601.65
+  outward_edges:
+    64: 9.434924215078354
+    104: 12.014823168516159
+105:
+  node_pos:
+  - 234.05
+  - 602.45
+  outward_edges:
+    42: 15.737005722522737
+    106: 9.852081507444382
+106:
+  node_pos:
+  - 233.10000000000002
+  - 612.45
+  outward_edges:
+    105: 9.852081507444382
+    107: 10.369848430156708
+107:
+  node_pos:
+  - 237.45000000000002
+  - 619.3000000000001
+  outward_edges:
+    106: 10.369848430156708
+    108: 9.731370830535889
+108:
+  node_pos:
+  - 247.45
+  - 620.2
+  outward_edges:
+    107: 9.731370830535889
+    109: 9.852081507444382
+109:
+  node_pos:
+  - 257.45
+  - 621.1500000000001
+  outward_edges:
+    108: 9.852081507444382
+    110: 9.852081507444382
+110:
+  node_pos:
+  - 267.45
+  - 622.1
+  outward_edges:
+    109: 9.852081507444382
+    111: 9.852081507444382
+111:
+  node_pos:
+  - 277.45
+  - 623.0500000000001
+  outward_edges:
+    110: 9.852081507444382
+    112: 9.852081507444382
+112:
+  node_pos:
+  - 287.45
+  - 624.0
+  outward_edges:
+    111: 9.852081507444382
+    113: 9.997056245803833
+113:
+  node_pos:
+  - 292.25
+  - 629.9000000000001
+  outward_edges:
+    112: 9.997056245803833
+    114: 9.91421353816986
+114:
+  node_pos:
+  - 302.25
+  - 631.0
+  outward_edges:
+    113: 9.91421353816986
+    115: 9.893502861261368
+115:
+  node_pos:
+  - 312.25
+  - 632.0500000000001
+  outward_edges:
+    114: 9.893502861261368
+    116: 9.893502861261368
+116:
+  node_pos:
+  - 322.25
+  - 633.1
+  outward_edges:
+    115: 9.893502861261368
+    117: 9.872792184352875
+117:
+  node_pos:
+  - 332.25
+  - 634.1
+  outward_edges:
+    116: 9.872792184352875
+    118: 9.955634891986847
+118:
+  node_pos:
+  - 340.90000000000003
+  - 633.1500000000001
+  outward_edges:
+    117: 9.955634891986847
+    119: 22.2911687374115
+119:
+  node_pos:
+  - 351.6
+  - 622.4000000000001
+  outward_edges:
+    118: 22.2911687374115
+    120: 9.831370830535889
+120:
+  node_pos:
+  - 361.6
+  - 623.3000000000001
+  outward_edges:
+    119: 9.831370830535889
+    121: 24.59766587615013
+121:
+  node_pos:
+  - 368.1
+  - 627.85
+  outward_edges:
+    120: 24.59766587615013
+    121: 0.9707106769084931
+122:
+  node_pos:
+  - 382.5
+  - 624.8000000000001
+  outward_edges:
+    123: 9.810660153627396
+123:
+  node_pos:
+  - 392.5
+  - 625.6500000000001
+  outward_edges:
+    3: 15.331980460882187
+    122: 9.810660153627396
+124:
+  node_pos:
+  - 273.0
+  - 586.9
+  outward_edges:
+    125: 12.31309867501259
+    126: 9.689949476718903
+125:
+  node_pos:
+  - 263.0
+  - 594.1
+  outward_edges:
+    64: 12.887362736463547
+    124: 12.31309867501259
+126:
+  node_pos:
+  - 283.0
+  - 587.65
+  outward_edges:
+    124: 9.689949476718903
+    127: 10.411269783973694
+127:
+  node_pos:
+  - 285.90000000000003
+  - 597.25
+  outward_edges:
+    126: 10.411269783973694
+    128: 10.24558436870575
+128:
+  node_pos:
+  - 287.85
+  - 607.25
+  outward_edges:
+    127: 10.24558436870575
+129:
+  node_pos:
+  - 270.65000000000003
+  - 606.95
+  outward_edges:
+    130: 10.328427076339722
+    131: 31.149494767189026
+130:
+  node_pos:
+  - 260.65000000000003
+  - 604.7
+  outward_edges:
+    64: 7.728427076339722
+    129: 10.328427076339722
+131:
+  node_pos:
+  - 296.85
+  - 613.45
+  outward_edges:
+    129: 31.149494767189026
+    132: 10.618376553058624
+132:
+  node_pos:
+  - 306.85
+  - 616.45
+  outward_edges:
+    93: 10.656244522333147
+    131: 10.618376553058624
+133:
+  node_pos:
+  - 207.55
+  - 580.4
+  outward_edges:
+    6: 11.74827550649643
+    134: 9.872792184352875
+134:
+  node_pos:
+  - 197.55
+  - 579.4
+  outward_edges:
+    133: 9.872792184352875
+    135: 9.872792184352875
+135:
+  node_pos:
+  - 187.55
+  - 578.4
+  outward_edges:
+    134: 9.872792184352875
+    135: 2.582842707633972
+136:
+  node_pos:
+  - 433.25
+  - 569.6
+  outward_edges:
+    62: 10.802081507444383
+137:
+  node_pos:
+  - 368.95000000000005
+  - 570.4
+  outward_edges:
+    34: 9.91421353816986
+    137: 17.826955199241638
+138:
+  node_pos:
+  - 383.45000000000005
+  - 571.75
+  outward_edges:
+    57: 7.834924215078354
+139:
+  node_pos:
+  - 344.55
+  - 578.65
+  outward_edges:
+    7: 10.289949476718903
+    140: 9.852081507444382
+140:
+  node_pos:
+  - 343.6
+  - 588.65
+  outward_edges:
+    139: 9.852081507444382
+    141: 9.852081507444382
+141:
+  node_pos:
+  - 342.65000000000003
+  - 598.65
+  outward_edges:
+    140: 9.852081507444382
+    142: 9.852081507444382
+142:
+  node_pos:
+  - 341.70000000000005
+  - 608.6500000000001
+  outward_edges:
+    4: 13.4506096303463
+    141: 9.852081507444382
+143:
+  node_pos:
+  - 472.5
+  - 567.75
+  outward_edges:
+    143: 0.6000000000000001
+144:
+  node_pos:
+  - 473.70000000000005
+  - 553.2
+  outward_edges:
+    144: 0.6000000000000001
+145:
+  node_pos:
+  - 455.75
+  - 550.4
+  outward_edges:
+    145: 1.3
+146:
+  node_pos:
+  - 445.75
+  - 556.65
+  outward_edges:
+    58: 22.16482316851616
+    62: 14.18847759962082
+147:
+  node_pos:
+  - 407.45000000000005
+  - 557.0
+  outward_edges:
+    46: 16.4006096303463
+    94: 10.372792184352875
+148:
+  node_pos:
+  - 473.85
+  - 543.65
+  outward_edges:
+    148: 0.65
+149:
+  node_pos:
+  - 349.3
+  - 543.7
+  outward_edges:
+    74: 10.352081507444382
+    150: 9.852081507444382
+150:
+  node_pos:
+  - 348.35
+  - 553.7
+  outward_edges:
+    7: 17.626524075865746
+    149: 9.852081507444382
+151:
+  node_pos:
+  - 370.6
+  - 542.4
+  outward_edges:
+    43: 13.355129659175873
+    152: 9.852081507444382
+152:
+  node_pos:
+  - 380.6
+  - 543.35
+  outward_edges:
+    151: 9.852081507444382
+    153: 9.852081507444382
+153:
+  node_pos:
+  - 390.6
+  - 544.3000000000001
+  outward_edges:
+    152: 9.852081507444382
+    154: 9.831370830535889
+154:
+  node_pos:
+  - 400.6
+  - 545.2
+  outward_edges:
+    94: 7.764213538169861
+    153: 9.831370830535889
+155:
+  node_pos:
+  - 239.4
+  - 541.0
+  outward_edges:
+    37: 11.15979790687561
+    156: 9.872792184352875
+156:
+  node_pos:
+  - 238.4
+  - 551.0
+  outward_edges:
+    155: 9.872792184352875
+    157: 9.852081507444382
+157:
+  node_pos:
+  - 237.45000000000002
+  - 561.0
+  outward_edges:
+    156: 9.852081507444382
+    158: 9.872792184352875
+158:
+  node_pos:
+  - 236.45000000000002
+  - 571.0
+  outward_edges:
+    21: 7.455634891986847
+    157: 9.872792184352875
+159:
+  node_pos:
+  - 377.5
+  - 532.65
+  outward_edges:
+    24: 10.393502861261368
+    160: 9.810660153627396
+160:
+  node_pos:
+  - 387.5
+  - 533.5
+  outward_edges:
+    159: 9.810660153627396
+    161: 9.810660153627396
+161:
+  node_pos:
+  - 397.5
+  - 534.35
+  outward_edges:
+    160: 9.810660153627396
+    162: 9.810660153627396
+162:
+  node_pos:
+  - 407.5
+  - 535.2
+  outward_edges:
+    80: 9.239949476718904
+    161: 9.810660153627396
+163:
+  node_pos:
+  - 254.05
+  - 532.65
+  outward_edges:
+    25: 10.497056245803833
+    96: 9.460660153627396
+164:
+  node_pos:
+  - 338.6
+  - 537.6
+  outward_edges:
+    97: 10.828427076339722
+    165: 9.748528122901917
+165:
+  node_pos:
+  - 337.90000000000003
+  - 547.6
+  outward_edges:
+    164: 9.748528122901917
+    166: 9.81923879981041
+166:
+  node_pos:
+  - 337.55
+  - 557.6
+  outward_edges:
+    81: 11.043250244855882
+    165: 9.81923879981041
+167:
+  node_pos:
+  - 359.05
+  - 516.1
+  outward_edges:
+    168: 10.40771639943123
+    174: 73.47731221318246
+168:
+  node_pos:
+  - 366.65000000000003
+  - 519.45
+  outward_edges:
+    167: 10.40771639943123
+    169: 9.831370830535889
+169:
+  node_pos:
+  - 376.65000000000003
+  - 520.35
+  outward_edges:
+    168: 9.831370830535889
+    170: 9.831370830535889
+170:
+  node_pos:
+  - 386.65000000000003
+  - 521.25
+  outward_edges:
+    169: 9.831370830535889
+    171: 9.852081507444382
+171:
+  node_pos:
+  - 396.65000000000003
+  - 522.2
+  outward_edges:
+    170: 9.852081507444382
+    172: 9.831370830535889
+172:
+  node_pos:
+  - 406.65000000000003
+  - 523.1
+  outward_edges:
+    171: 9.831370830535889
+    173: 9.78137083053589
+173:
+  node_pos:
+  - 416.65000000000003
+  - 524.0
+  outward_edges:
+    172: 9.78137083053589
+    174: 9.872792184352875
+174:
+  node_pos:
+  - 426.65000000000003
+  - 524.7
+  outward_edges:
+    167: 73.47731221318246
+    173: 9.872792184352875
+175:
+  node_pos:
+  - 352.70000000000005
+  - 509.9
+  outward_edges:
+    84: 10.524011445045472
+    176: 12.167766922712326
+176:
+  node_pos:
+  - 364.90000000000003
+  - 511.20000000000005
+  outward_edges:
+    175: 12.167766922712326
+    177: 9.934924215078354
+177:
+  node_pos:
+  - 374.90000000000003
+  - 512.35
+  outward_edges:
+    176: 9.934924215078354
+    178: 9.934924215078354
+178:
+  node_pos:
+  - 384.90000000000003
+  - 513.5
+  outward_edges:
+    177: 9.934924215078354
+    179: 9.934924215078354
+179:
+  node_pos:
+  - 394.90000000000003
+  - 514.65
+  outward_edges:
+    178: 9.934924215078354
+    180: 9.91421353816986
+180:
+  node_pos:
+  - 404.90000000000003
+  - 515.8000000000001
+  outward_edges:
+    179: 9.91421353816986
+    182: 8.352081507444382
+181:
+  node_pos:
+  - 423.40000000000003
+  - 517.9
+  outward_edges:
+    75: 11.22634556889534
+    182: 9.934924215078354
+182:
+  node_pos:
+  - 413.40000000000003
+  - 516.75
+  outward_edges:
+    180: 8.352081507444382
+    181: 9.934924215078354
+183:
+  node_pos:
+  - 285.35
+  - 518.3000000000001
+  outward_edges:
+    44: 10.41421353816986
+    184: 9.831370830535889
+184:
+  node_pos:
+  - 284.45
+  - 528.3000000000001
+  outward_edges:
+    183: 9.831370830535889
+185:
+  node_pos:
+  - 280.35
+  - 535.15
+  outward_edges:
+    96: 16.854163014888766
+    186: 14.21984843015671
+186:
+  node_pos:
+  - 288.05
+  - 536.0
+  outward_edges:
+    185: 14.21984843015671
+    187: 9.810660153627396
+187:
+  node_pos:
+  - 298.05
+  - 536.85
+  outward_edges:
+    186: 9.810660153627396
+    187: 9.359188276529313
+188:
+  node_pos:
+  - 338.8
+  - 505.55000000000007
+  outward_edges:
+    189: 14.527564829587938
+189:
+  node_pos:
+  - 336.85
+  - 515.5
+  outward_edges:
+    188: 14.527564829587938
+190:
+  node_pos:
+  - 297.20000000000005
+  - 502.80000000000007
+  outward_edges:
+    59: 9.981370830535889
+    191: 9.852081507444382
+191:
+  node_pos:
+  - 307.20000000000005
+  - 503.75
+  outward_edges:
+    190: 9.852081507444382
+    191: 16.65269113779068
+192:
+  node_pos:
+  - 319.6
+  - 504.20000000000005
+  outward_edges:
+    193: 9.748528122901917
+193:
+  node_pos:
+  - 329.6
+  - 504.9
+  outward_edges:
+    192: 9.748528122901917
+    193: 7.288477599620819
+194:
+  node_pos:
+  - 343.85
+  - 511.6
+  outward_edges:
+    76: 15.854772645235062
+    84: 9.56482316851616
+195:
+  node_pos:
+  - 256.8
+  - 498.85
+  outward_edges:
+    60: 9.943502861261369
+    196: 10.067766922712327
+196:
+  node_pos:
+  - 266.8
+  - 500.40000000000003
+  outward_edges:
+    48: 10.179898953437807
+    195: 10.067766922712327
+    197: 9.843502861261369
+197:
+  node_pos:
+  - 265.85
+  - 510.35
+  outward_edges:
+    196: 9.843502861261369
+    198: 9.872792184352875
+198:
+  node_pos:
+  - 264.85
+  - 520.35
+  outward_edges:
+    96: 12.788477599620819
+    197: 9.872792184352875
+199:
+  node_pos:
+  - 368.95000000000005
+  - 496.55
+  outward_edges:
+    72: 10.455634891986847
+    200: 9.810660153627396
+200:
+  node_pos:
+  - 378.95000000000005
+  - 497.40000000000003
+  outward_edges:
+    85: 12.455634891986847
+    199: 9.810660153627396
+201:
+  node_pos:
+  - 335.6
+  - 493.65000000000003
+  outward_edges:
+    26: 10.538477599620819
+    38: 29.358935660123826
+202:
+  node_pos:
+  - 227.0
+  - 500.05
+  outward_edges:
+    203: 18.17523070573807
+    209: 22.432947105169298
+203:
+  node_pos:
+  - 222.4
+  - 510.9
+  outward_edges:
+    202: 18.17523070573807
+    204: 9.852081507444382
+204:
+  node_pos:
+  - 221.4
+  - 520.9
+  outward_edges:
+    37: 24.60391039848328
+    203: 9.852081507444382
+205:
+  node_pos:
+  - 221.20000000000002
+  - 530.9
+  outward_edges:
+    206: 10.100609630346298
+206:
+  node_pos:
+  - 219.45000000000002
+  - 540.9
+  outward_edges:
+    205: 10.100609630346298
+    207: 9.872792184352875
+207:
+  node_pos:
+  - 218.45000000000002
+  - 550.9
+  outward_edges:
+    206: 9.872792184352875
+    208: 9.852081507444382
+208:
+  node_pos:
+  - 217.5
+  - 560.9
+  outward_edges:
+    207: 9.852081507444382
+209:
+  node_pos:
+  - 236.0
+  - 506.15
+  outward_edges:
+    60: 18.561269783973696
+    202: 22.432947105169298
+210:
+  node_pos:
+  - 245.70000000000002
+  - 507.75
+  outward_edges:
+    211: 9.852081507444382
+211:
+  node_pos:
+  - 244.9
+  - 517.75
+  outward_edges:
+    25: 13.38847759962082
+    210: 9.852081507444382
+212:
+  node_pos:
+  - 302.3
+  - 490.6
+  outward_edges:
+    39: 10.48847759962082
+    213: 9.831370830535889
+213:
+  node_pos:
+  - 312.3
+  - 491.5
+  outward_edges:
+    26: 12.714213538169862
+    212: 9.831370830535889
+214:
+  node_pos:
+  - 269.45
+  - 487.70000000000005
+  outward_edges:
+    86: 10.538477599620819
+    215: 9.831370830535889
+215:
+  node_pos:
+  - 279.45
+  - 488.6
+  outward_edges:
+    39: 12.405634891986848
+    214: 9.831370830535889
+216:
+  node_pos:
+  - 242.25
+  - 485.15000000000003
+  outward_edges:
+    65: 11.37462107539177
+    86: 16.800609630346298
+217:
+  node_pos:
+  - 427.0
+  - 469.35
+  outward_edges:
+    66: 10.393502861261368
+    218: 9.789949476718903
+218:
+  node_pos:
+  - 426.20000000000005
+  - 479.35
+  outward_edges:
+    217: 9.789949476718903
+    219: 9.810660153627396
+219:
+  node_pos:
+  - 425.35
+  - 489.35
+  outward_edges:
+    218: 9.810660153627396
+    220: 9.802081507444383
+220:
+  node_pos:
+  - 424.55
+  - 499.35
+  outward_edges:
+    219: 9.802081507444383
+221:
+  node_pos:
+  - 415.6
+  - 500.5
+  outward_edges:
+    222: 9.760660153627397
+    223: 25.21040753722191
+222:
+  node_pos:
+  - 405.6
+  - 499.70000000000005
+  outward_edges:
+    85: 14.271320307254792
+    221: 9.760660153627397
+223:
+  node_pos:
+  - 436.85
+  - 504.75
+  outward_edges:
+    221: 25.21040753722191
+    224: 10.017766922712326
+224:
+  node_pos:
+  - 429.40000000000003
+  - 507.35
+  outward_edges:
+    223: 10.017766922712326
+    225: 30.58908722996712
+225:
+  node_pos:
+  - 399.40000000000003
+  - 504.5
+  outward_edges:
+    38: 48.380255967378616
+    224: 30.58908722996712
+226:
+  node_pos:
+  - 438.45000000000005
+  - 459.65000000000003
+  outward_edges:
+    66: 10.393502861261368
+    227: 9.860660153627396
+227:
+  node_pos:
+  - 448.45000000000005
+  - 460.20000000000005
+  outward_edges:
+    226: 9.860660153627396
+    227: 0.6414213538169862
+228:
+  node_pos:
+  - 394.0
+  - 466.65000000000003
+  outward_edges:
+    0: 10.310660153627396
+    229: 9.789949476718903
+229:
+  node_pos:
+  - 393.20000000000005
+  - 476.65000000000003
+  outward_edges:
+    228: 9.789949476718903
+    230: 9.739949476718904
+230:
+  node_pos:
+  - 392.40000000000003
+  - 486.65000000000003
+  outward_edges:
+    85: 11.093502861261369
+    229: 9.739949476718904
+231:
+  node_pos:
+  - 405.35
+  - 456.95000000000005
+  outward_edges:
+    0: 10.28137083053589
+    232: 9.789949476718903
+232:
+  node_pos:
+  - 415.35
+  - 457.75
+  outward_edges:
+    66: 12.455634891986847
+    231: 9.789949476718903
+233:
+  node_pos:
+  - 360.90000000000003
+  - 464.0
+  outward_edges:
+    40: 10.331370830535889
+    234: 9.760660153627397
+234:
+  node_pos:
+  - 360.1
+  - 474.0
+  outward_edges:
+    233: 9.760660153627397
+    235: 9.810660153627396
+235:
+  node_pos:
+  - 359.25
+  - 484.0
+  outward_edges:
+    72: 11.514213538169862
+    234: 9.810660153627396
+236:
+  node_pos:
+  - 372.35
+  - 454.3
+  outward_edges:
+    40: 10.352081507444382
+    237: 9.789949476718903
+237:
+  node_pos:
+  - 382.35
+  - 455.1
+  outward_edges:
+    0: 12.293502861261368
+    236: 9.789949476718903
+238:
+  node_pos:
+  - 327.90000000000003
+  - 461.1
+  outward_edges:
+    11: 10.352081507444382
+    239: 9.831370830535889
+239:
+  node_pos:
+  - 327.0
+  - 471.1
+  outward_edges:
+    238: 9.831370830535889
+    240: 9.731370830535889
+240:
+  node_pos:
+  - 326.20000000000005
+  - 481.1
+  outward_edges:
+    26: 10.884924215078355
+    239: 9.731370830535889
+241:
+  node_pos:
+  - 339.40000000000003
+  - 451.55
+  outward_edges:
+    11: 10.372792184352875
+    242: 9.760660153627397
+242:
+  node_pos:
+  - 349.40000000000003
+  - 452.40000000000003
+  outward_edges:
+    40: 12.417766922712326
+    241: 9.760660153627397
+243:
+  node_pos:
+  - 294.90000000000003
+  - 457.95000000000005
+  outward_edges:
+    28: 10.372792184352875
+    244: 9.852081507444382
+244:
+  node_pos:
+  - 293.95
+  - 467.95000000000005
+  outward_edges:
+    243: 9.852081507444382
+    245: 9.852081507444382
+245:
+  node_pos:
+  - 293.0
+  - 477.95000000000005
+  outward_edges:
+    39: 10.943502861261369
+    244: 9.852081507444382
+246:
+  node_pos:
+  - 306.25
+  - 448.45000000000005
+  outward_edges:
+    28: 10.497056245803833
+    247: 9.872792184352875
+247:
+  node_pos:
+  - 316.25
+  - 449.45000000000005
+  outward_edges:
+    11: 12.659188276529314
+    246: 9.872792184352875
+248:
+  node_pos:
+  - 261.85
+  - 454.85
+  outward_edges:
+    1: 10.372792184352875
+    249: 9.831370830535889
+249:
+  node_pos:
+  - 260.95
+  - 464.85
+  outward_edges:
+    248: 9.831370830535889
+    250: 9.810660153627396
+250:
+  node_pos:
+  - 260.1
+  - 474.85
+  outward_edges:
+    86: 11.22634556889534
+    249: 9.810660153627396
+251:
+  node_pos:
+  - 273.35
+  - 445.25
+  outward_edges:
+    1: 10.393502861261368
+    252: 9.872792184352875
+252:
+  node_pos:
+  - 283.35
+  - 446.25
+  outward_edges:
+    28: 12.347056245803834
+    251: 9.872792184352875
+253:
+  node_pos:
+  - 226.10000000000002
+  - 451.6
+  outward_edges:
+    77: 10.434924215078354
+    254: 9.831370830535889
+254:
+  node_pos:
+  - 225.20000000000002
+  - 461.6
+  outward_edges:
+    253: 9.831370830535889
+    255: 9.852081507444382
+255:
+  node_pos:
+  - 224.25
+  - 471.6
+  outward_edges:
+    254: 9.852081507444382
+    256: 9.831370830535889
+256:
+  node_pos:
+  - 224.20000000000002
+  - 481.6
+  outward_edges:
+    65: 12.161626797914506
+    255: 9.831370830535889
+257:
+  node_pos:
+  - 238.0
+  - 441.90000000000003
+  outward_edges:
+    77: 10.331370830535889
+    258: 9.872792184352875
+258:
+  node_pos:
+  - 248.0
+  - 442.90000000000003
+  outward_edges:
+    1: 14.809188276529312
+    257: 9.872792184352875
+259:
+  node_pos:
+  - 430.3
+  - 428.1
+  outward_edges:
+    12: 10.331370830535889
+    260: 9.689949476718903
+260:
+  node_pos:
+  - 429.55
+  - 438.1
+  outward_edges:
+    259: 9.689949476718903
+    261: 9.789949476718903
+261:
+  node_pos:
+  - 428.75
+  - 448.1
+  outward_edges:
+    66: 10.481370830535889
+    260: 9.789949476718903
+262:
+  node_pos:
+  - 441.55
+  - 418.5
+  outward_edges:
+    12: 10.343502861261369
+    263: 9.739949476718904
+263:
+  node_pos:
+  - 451.55
+  - 419.25
+  outward_edges:
+    262: 9.739949476718904
+    263: 1.2571067690849305
+264:
+  node_pos:
+  - 397.35
+  - 425.5
+  outward_edges:
+    13: 10.28137083053589
+    265: 9.810660153627396
+265:
+  node_pos:
+  - 396.5
+  - 435.5
+  outward_edges:
+    264: 9.810660153627396
+    266: 9.789949476718903
+266:
+  node_pos:
+  - 395.70000000000005
+  - 445.5
+  outward_edges:
+    0: 10.443502861261369
+    265: 9.789949476718903
+267:
+  node_pos:
+  - 408.75
+  - 415.90000000000003
+  outward_edges:
+    13: 10.352081507444382
+    268: 9.710660153627396
+268:
+  node_pos:
+  - 418.75
+  - 416.65000000000003
+  outward_edges:
+    12: 12.172792184352875
+    267: 9.710660153627396
+269:
+  node_pos:
+  - 364.3
+  - 422.90000000000003
+  outward_edges:
+    14: 10.310660153627396
+    270: 9.789949476718903
+270:
+  node_pos:
+  - 363.5
+  - 432.90000000000003
+  outward_edges:
+    269: 9.789949476718903
+    271: 9.810660153627396
+271:
+  node_pos:
+  - 362.65000000000003
+  - 442.90000000000003
+  outward_edges:
+    40: 10.49350286126137
+    270: 9.810660153627396
+272:
+  node_pos:
+  - 375.6
+  - 413.20000000000005
+  outward_edges:
+    14: 10.393502861261368
+    273: 9.760660153627397
+273:
+  node_pos:
+  - 385.6
+  - 414.0
+  outward_edges:
+    13: 12.576345568895341
+    272: 9.760660153627397
+274:
+  node_pos:
+  - 331.75
+  - 420.1
+  outward_edges:
+    30: 10.393502861261368
+    275: 9.852081507444382
+275:
+  node_pos:
+  - 330.8
+  - 430.1
+  outward_edges:
+    274: 9.852081507444382
+    276: 9.872792184352875
+276:
+  node_pos:
+  - 329.8
+  - 440.1
+  outward_edges:
+    11: 10.322792184352876
+    275: 9.872792184352875
+277:
+  node_pos:
+  - 343.3
+  - 410.5
+  outward_edges:
+    30: 10.372792184352875
+    278: 9.810660153627396
+278:
+  node_pos:
+  - 353.3
+  - 411.35
+  outward_edges:
+    14: 11.643502861261368
+    277: 9.810660153627396
+279:
+  node_pos:
+  - 298.75
+  - 416.70000000000005
+  outward_edges:
+    31: 10.434924215078354
+    280: 9.852081507444382
+280:
+  node_pos:
+  - 297.8
+  - 426.70000000000005
+  outward_edges:
+    279: 9.852081507444382
+    281: 9.852081507444382
+281:
+  node_pos:
+  - 296.85
+  - 436.70000000000005
+  outward_edges:
+    28: 10.643502861261368
+    280: 9.852081507444382
+282:
+  node_pos:
+  - 310.40000000000003
+  - 407.35
+  outward_edges:
+    31: 10.41421353816986
+    283: 9.852081507444382
+283:
+  node_pos:
+  - 320.40000000000003
+  - 408.3
+  outward_edges:
+    30: 12.367766922712327
+    282: 9.852081507444382
+284:
+  node_pos:
+  - 265.40000000000003
+  - 413.65000000000003
+  outward_edges:
+    32: 10.352081507444382
+    285: 9.810660153627396
+285:
+  node_pos:
+  - 264.55
+  - 423.65000000000003
+  outward_edges:
+    284: 9.810660153627396
+    286: 9.810660153627396
+286:
+  node_pos:
+  - 263.7
+  - 433.65000000000003
+  outward_edges:
+    1: 10.452081507444383
+    285: 9.810660153627396
+287:
+  node_pos:
+  - 276.65000000000003
+  - 404.05
+  outward_edges:
+    32: 10.426345568895341
+    288: 9.852081507444382
+288:
+  node_pos:
+  - 286.65000000000003
+  - 405.0
+  outward_edges:
+    31: 13.371320307254791
+    287: 9.852081507444382
+289:
+  node_pos:
+  - 229.65
+  - 410.85
+  outward_edges:
+    87: 10.393502861261368
+    290: 9.78137083053589
+290:
+  node_pos:
+  - 228.8
+  - 420.85
+  outward_edges:
+    289: 9.78137083053589
+    291: 9.810660153627396
+291:
+  node_pos:
+  - 227.95000000000002
+  - 430.85
+  outward_edges:
+    77: 10.089949476718903
+    290: 9.810660153627396
+292:
+  node_pos:
+  - 241.45000000000002
+  - 401.05
+  outward_edges:
+    87: 10.75771639943123
+    293: 9.789949476718903
+293:
+  node_pos:
+  - 251.45
+  - 401.85
+  outward_edges:
+    32: 14.72634556889534
+    292: 9.789949476718903
+294:
+  node_pos:
+  - 401.05
+  - 380.05
+  outward_edges:
+    15: 10.352081507444382
+    295: 9.789949476718903
+295:
+  node_pos:
+  - 400.25
+  - 390.05
+  outward_edges:
+    294: 9.789949476718903
+    296: 9.810660153627396
+296:
+  node_pos:
+  - 399.40000000000003
+  - 400.05
+  outward_edges:
+    13: 14.87634556889534
+    295: 9.810660153627396
+297:
+  node_pos:
+  - 368.05
+  - 377.05
+  outward_edges:
+    2: 10.331370830535889
+    298: 9.810660153627396
+298:
+  node_pos:
+  - 367.20000000000005
+  - 387.05
+  outward_edges:
+    297: 9.810660153627396
+    299: 9.739949476718904
+299:
+  node_pos:
+  - 366.40000000000003
+  - 397.05
+  outward_edges:
+    14: 15.297056245803834
+    298: 9.739949476718904
+300:
+  node_pos:
+  - 379.45000000000005
+  - 367.45000000000005
+  outward_edges:
+    2: 10.372792184352875
+    301: 9.831370830535889
+301:
+  node_pos:
+  - 389.45000000000005
+  - 368.35
+  outward_edges:
+    15: 12.405634891986848
+    300: 9.831370830535889
+302:
+  node_pos:
+  - 336.35
+  - 374.15000000000003
+  outward_edges:
+    52: 10.372792184352875
+    303: 9.872792184352875
+303:
+  node_pos:
+  - 335.3
+  - 384.15000000000003
+  outward_edges:
+    302: 9.872792184352875
+    304: 9.872792184352875
+304:
+  node_pos:
+  - 334.3
+  - 394.15000000000003
+  outward_edges:
+    30: 15.471320307254793
+    303: 9.872792184352875
+305:
+  node_pos:
+  - 347.8
+  - 364.6
+  outward_edges:
+    52: 10.293502861261368
+    306: 9.852081507444382
+306:
+  node_pos:
+  - 357.8
+  - 365.55
+  outward_edges:
+    2: 10.922792184352875
+    305: 9.852081507444382
+307:
+  node_pos:
+  - 303.15000000000003
+  - 371.05
+  outward_edges:
+    16: 10.393502861261368
+    308: 9.872792184352875
+308:
+  node_pos:
+  - 302.15000000000003
+  - 381.05
+  outward_edges:
+    307: 9.872792184352875
+    309: 9.852081507444382
+309:
+  node_pos:
+  - 301.20000000000005
+  - 391.05
+  outward_edges:
+    31: 15.209188276529312
+    308: 9.852081507444382
+310:
+  node_pos:
+  - 314.65000000000003
+  - 361.55
+  outward_edges:
+    16: 10.434924215078354
+    311: 9.852081507444382
+311:
+  node_pos:
+  - 324.65000000000003
+  - 362.5
+  outward_edges:
+    52: 12.809188276529312
+    310: 9.852081507444382
+312:
+  node_pos:
+  - 269.25
+  - 367.70000000000005
+  outward_edges:
+    88: 10.621320307254791
+    313: 9.760660153627397
+313:
+  node_pos:
+  - 268.40000000000003
+  - 377.70000000000005
+  outward_edges:
+    312: 9.760660153627397
+    314: 9.810660153627396
+314:
+  node_pos:
+  - 267.55
+  - 387.70000000000005
+  outward_edges:
+    32: 15.447056245803834
+    313: 9.810660153627396
+315:
+  node_pos:
+  - 281.6
+  - 358.45000000000005
+  outward_edges:
+    88: 10.393502861261368
+    316: 9.852081507444382
+316:
+  node_pos:
+  - 291.6
+  - 359.40000000000003
+  outward_edges:
+    16: 12.538477599620819
+    315: 9.852081507444382
+317:
+  node_pos:
+  - 434.3
+  - 345.05
+  outward_edges:
+    318: 9.852081507444382
+318:
+  node_pos:
+  - 433.35
+  - 355.05
+  outward_edges:
+    317: 9.852081507444382
+    319: 9.852081507444382
+319:
+  node_pos:
+  - 432.40000000000003
+  - 365.05
+  outward_edges:
+    318: 9.852081507444382
+    322: 15.99827550649643
+320:
+  node_pos:
+  - 428.05
+  - 371.70000000000005
+  outward_edges:
+    321: 9.810660153627396
+321:
+  node_pos:
+  - 418.05
+  - 370.85
+  outward_edges:
+    15: 16.159188276529314
+    320: 9.810660153627396
+322:
+  node_pos:
+  - 434.40000000000003
+  - 376.8
+  outward_edges:
+    319: 15.99827550649643
+    323: 9.739949476718904
+323:
+  node_pos:
+  - 433.65000000000003
+  - 386.8
+  outward_edges:
+    322: 9.739949476718904
+    324: 9.739949476718904
+324:
+  node_pos:
+  - 432.85
+  - 396.8
+  outward_edges:
+    323: 9.739949476718904
+    325: 9.760660153627397
+325:
+  node_pos:
+  - 432.05
+  - 406.8
+  outward_edges:
+    12: 10.622792184352875
+    324: 9.760660153627397
+326:
+  node_pos:
+  - 405.15000000000003
+  - 341.85
+  outward_edges:
+    327: 10.055634891986848
+327:
+  node_pos:
+  - 403.5
+  - 351.70000000000005
+  outward_edges:
+    326: 10.055634891986848
+    328: 9.810660153627396
+328:
+  node_pos:
+  - 402.65000000000003
+  - 361.70000000000005
+  outward_edges:
+    15: 7.548528122901917
+    327: 9.810660153627396
+329:
+  node_pos:
+  - 371.95000000000005
+  - 339.15000000000003
+  outward_edges:
+    330: 10.034924215078355
+330:
+  node_pos:
+  - 370.35
+  - 349.05
+  outward_edges:
+    2: 17.429898953437807
+    329: 10.034924215078355
+331:
+  node_pos:
+  - 340.5
+  - 336.75
+  outward_edges:
+    332: 10.014213538169862
+332:
+  node_pos:
+  - 339.0
+  - 346.70000000000005
+  outward_edges:
+    52: 17.13345233798027
+    331: 10.014213538169862
+333:
+  node_pos:
+  - 305.85
+  - 341.8
+  outward_edges:
+    17: 10.455634891986847
+    334: 9.78137083053589
+334:
+  node_pos:
+  - 304.95000000000005
+  - 351.8
+  outward_edges:
+    16: 8.489949476718904
+    333: 9.78137083053589
+335:
+  node_pos:
+  - 272.35
+  - 338.55
+  outward_edges:
+    18: 10.310660153627396
+    336: 9.789949476718903
+336:
+  node_pos:
+  - 271.55
+  - 348.55
+  outward_edges:
+    88: 8.552081507444383
+    335: 9.789949476718903
+337:
+  node_pos:
+  - 283.65000000000003
+  - 328.90000000000003
+  outward_edges:
+    18: 10.434924215078354
+    338: 9.872792184352875
+338:
+  node_pos:
+  - 293.65000000000003
+  - 329.90000000000003
+  outward_edges:
+    17: 12.37634556889534
+    337: 9.872792184352875
+339:
+  node_pos:
+  - 253.10000000000002
+  - 326.05
+  outward_edges:
+    78: 10.331370830535889
+    340: 9.831370830535889
+340:
+  node_pos:
+  - 263.1
+  - 326.95000000000005
+  outward_edges:
+    18: 9.893502861261368
+    339: 9.831370830535889
+341:
+  node_pos:
+  - 275.55
+  - 299.3
+  outward_edges:
+    29: 10.289949476718903
+    342: 9.76923879981041
+342:
+  node_pos:
+  - 274.8
+  - 309.3
+  outward_edges:
+    341: 9.76923879981041
+    343: 9.76923879981041
+343:
+  node_pos:
+  - 274.05
+  - 319.3
+  outward_edges:
+    18: 8.439949476718903
+    342: 9.76923879981041
+344:
+  node_pos:
+  - 286.7
+  - 289.3
+  outward_edges:
+    29: 10.260660153627397
+    345: 9.657106769084931
+345:
+  node_pos:
+  - 296.7
+  - 289.85
+  outward_edges:
+    344: 9.657106769084931
+    346: 9.70710676908493
+346:
+  node_pos:
+  - 306.70000000000005
+  - 290.45
+  outward_edges:
+    345: 9.70710676908493
+    346: 6.131370830535889
+347:
+  node_pos:
+  - 239.70000000000002
+  - 296.65000000000003
+  outward_edges:
+    99: 10.517766922712326
+    348: 9.91421353816986
+348:
+  node_pos:
+  - 238.60000000000002
+  - 306.65000000000003
+  outward_edges:
+    347: 9.91421353816986
+    349: 9.91421353816986
+349:
+  node_pos:
+  - 237.5
+  - 316.65000000000003
+  outward_edges:
+    348: 9.91421353816986
+    350: 25.547665876150134
+350:
+  node_pos:
+  - 235.60000000000002
+  - 336.65000000000003
+  outward_edges:
+    349: 25.547665876150134
+    351: 9.760660153627397
+351:
+  node_pos:
+  - 234.8
+  - 346.65000000000003
+  outward_edges:
+    350: 9.760660153627397
+    352: 9.760660153627397
+352:
+  node_pos:
+  - 233.95000000000002
+  - 356.65000000000003
+  outward_edges:
+    351: 9.760660153627397
+    353: 9.76923879981041
+353:
+  node_pos:
+  - 233.20000000000002
+  - 366.65000000000003
+  outward_edges:
+    352: 9.76923879981041
+    354: 9.789949476718903
+354:
+  node_pos:
+  - 232.4
+  - 376.65000000000003
+  outward_edges:
+    353: 9.789949476718903
+    355: 9.789949476718903
+355:
+  node_pos:
+  - 231.60000000000002
+  - 386.65000000000003
+  outward_edges:
+    87: 13.522792184352875
+    354: 9.789949476718903
+356:
+  node_pos:
+  - 251.7
+  - 286.90000000000003
+  outward_edges:
+    99: 10.479898953437806
+    357: 9.76923879981041
+357:
+  node_pos:
+  - 261.7
+  - 287.65000000000003
+  outward_edges:
+    29: 14.426345568895341
+    356: 9.76923879981041
+358:
+  node_pos:
+  - 278.05
+  - 259.95
+  outward_edges:
+    19: 10.26923879981041
+    359: 9.677817445993425
+359:
+  node_pos:
+  - 277.45
+  - 269.95
+  outward_edges:
+    358: 9.677817445993425
+    360: 9.698528122901918
+360:
+  node_pos:
+  - 276.8
+  - 279.95
+  outward_edges:
+    29: 8.536396092176437
+    359: 9.698528122901918
+361:
+  node_pos:
+  - 289.15000000000003
+  - 249.90000000000003
+  outward_edges:
+    19: 10.160660153627397
+    362: 9.70710676908493
+362:
+  node_pos:
+  - 299.15000000000003
+  - 250.5
+  outward_edges:
+    361: 9.70710676908493
+    363: 9.627817445993424
+363:
+  node_pos:
+  - 309.15000000000003
+  - 251.05
+  outward_edges:
+    362: 9.627817445993424
+    363: 7.659188276529313
+364:
+  node_pos:
+  - 245.4
+  - 257.55
+  outward_edges:
+    89: 11.242640614509583
+    365: 10.411269783973694
+365:
+  node_pos:
+  - 242.95000000000002
+  - 267.55
+  outward_edges:
+    364: 10.411269783973694
+    366: 10.059188276529312
+366:
+  node_pos:
+  - 241.45000000000002
+  - 277.55
+  outward_edges:
+    99: 8.460660153627396
+    365: 10.059188276529312
+367:
+  node_pos:
+  - 259.3
+  - 248.2
+  outward_edges:
+    89: 10.405634891986848
+    368: 9.70710676908493
+368:
+  node_pos:
+  - 269.3
+  - 248.8
+  outward_edges:
+    19: 9.098528122901916
+    367: 9.70710676908493
+369:
+  node_pos:
+  - 357.90000000000003
+  - 213.4
+  outward_edges:
+    27: 10.198528122901918
+    370: 9.615685415267945
+370:
+  node_pos:
+  - 367.90000000000003
+  - 213.85000000000002
+  outward_edges:
+    90: 12.277817445993424
+    369: 9.615685415267945
+371:
+  node_pos:
+  - 324.35
+  - 211.9
+  outward_edges:
+    49: 10.21923879981041
+    372: 9.594974738359452
+372:
+  node_pos:
+  - 334.35
+  - 212.35000000000002
+  outward_edges:
+    27: 12.810660153627396
+    371: 9.594974738359452
+373:
+  node_pos:
+  - 280.7
+  - 220.55
+  outward_edges:
+    20: 10.177817445993425
+    374: 9.727817445993423
+374:
+  node_pos:
+  - 280.05
+  - 230.55
+  outward_edges:
+    373: 9.727817445993423
+    375: 9.677817445993425
+375:
+  node_pos:
+  - 279.40000000000003
+  - 240.55
+  outward_edges:
+    19: 8.515685415267944
+    374: 9.677817445993425
+376:
+  node_pos:
+  - 291.05
+  - 210.35000000000002
+  outward_edges:
+    20: 9.648528122901917
+    377: 9.586396092176438
+377:
+  node_pos:
+  - 301.05
+  - 210.8
+  outward_edges:
+    49: 12.610660153627396
+    376: 9.586396092176438
+378:
+  node_pos:
+  - 255.8
+  - 219.20000000000002
+  outward_edges:
+    79: 10.68345233798027
+    379: 10.473401814699173
+379:
+  node_pos:
+  - 253.2
+  - 229.20000000000002
+  outward_edges:
+    378: 10.473401814699173
+    380: 10.535533845424652
+380:
+  node_pos:
+  - 250.45
+  - 239.20000000000002
+  outward_edges:
+    89: 8.08345233798027
+    379: 10.535533845424652
+381:
+  node_pos:
+  - 268.40000000000003
+  - 209.25
+  outward_edges:
+    20: 12.510660153627397
+    79: 10.198528122901918
+382:
+  node_pos:
+  - 414.6
+  - 197.9
+  outward_edges:
+    70: 10.227817445993423
+    383: 9.627817445993424
+383:
+  node_pos:
+  - 414.05
+  - 207.9
+  outward_edges:
+    382: 9.627817445993424
+    387: 16.942030984163285
+384:
+  node_pos:
+  - 411.05
+  - 215.70000000000002
+  outward_edges:
+    385: 9.594974738359452
+385:
+  node_pos:
+  - 401.05
+  - 215.3
+  outward_edges:
+    384: 9.594974738359452
+    386: 9.644974738359451
+386:
+  node_pos:
+  - 391.05
+  - 214.85000000000002
+  outward_edges:
+    90: 10.26923879981041
+    385: 9.644974738359451
+387:
+  node_pos:
+  - 420.95000000000005
+  - 216.10000000000002
+  outward_edges:
+    383: 16.942030984163285
+    388: 9.594974738359452
+388:
+  node_pos:
+  - 430.95000000000005
+  - 216.5
+  outward_edges:
+    387: 9.594974738359452
+    389: 9.615685415267945
+389:
+  node_pos:
+  - 440.95000000000005
+  - 216.95000000000002
+  outward_edges:
+    388: 9.615685415267945
+390:
+  node_pos:
+  - 447.35
+  - 212.5
+  outward_edges:
+    390: 9.897056245803833
+    391: 9.636396092176438
+391:
+  node_pos:
+  - 447.85
+  - 202.5
+  outward_edges:
+    98: 7.494974738359452
+    390: 9.636396092176438
+392:
+  node_pos:
+  - 424.8
+  - 188.35000000000002
+  outward_edges:
+    70: 9.957716399431229
+    393: 10.266295045614243
+393:
+  node_pos:
+  - 434.8
+  - 190.4
+  outward_edges:
+    98: 14.72903670668602
+    392: 10.266295045614243
+394:
+  node_pos:
+  - 348.70000000000005
+  - 184.95000000000002
+  outward_edges:
+    91: 10.20710676908493
+    395: 9.586396092176438
+395:
+  node_pos:
+  - 348.25
+  - 194.95000000000002
+  outward_edges:
+    394: 9.586396092176438
+    396: 9.665685415267944
+396:
+  node_pos:
+  - 347.75
+  - 204.95000000000002
+  outward_edges:
+    27: 7.0949747383594515
+    395: 9.665685415267944
+397:
+  node_pos:
+  - 359.5
+  - 175.3
+  outward_edges:
+    91: 10.209188276529312
+    398: 10.121320307254791
+398:
+  node_pos:
+  - 369.5
+  - 177.0
+  outward_edges:
+    397: 10.121320307254791
+    399: 10.266295045614243
+399:
+  node_pos:
+  - 379.5
+  - 179.05
+  outward_edges:
+    398: 10.266295045614243
+    402: 22.31040753722191
+400:
+  node_pos:
+  - 381.70000000000005
+  - 187.9
+  outward_edges:
+    401: 9.665685415267944
+401:
+  node_pos:
+  - 381.20000000000005
+  - 197.9
+  outward_edges:
+    90: 15.789949476718903
+    400: 9.665685415267944
+402:
+  node_pos:
+  - 393.6
+  - 181.95000000000002
+  outward_edges:
+    399: 22.31040753722191
+    403: 10.24558436870575
+403:
+  node_pos:
+  - 403.6
+  - 184.0
+  outward_edges:
+    70: 12.518376553058625
+    402: 10.24558436870575
+404:
+  node_pos:
+  - 315.15000000000003
+  - 183.35000000000002
+  outward_edges:
+    67: 10.20710676908493
+    405: 9.586396092176438
+405:
+  node_pos:
+  - 314.70000000000005
+  - 193.35000000000002
+  outward_edges:
+    404: 9.586396092176438
+    406: 9.636396092176438
+406:
+  node_pos:
+  - 314.20000000000005
+  - 203.35000000000002
+  outward_edges:
+    49: 7.224264061450959
+    405: 9.636396092176438
+407:
+  node_pos:
+  - 325.90000000000003
+  - 172.85000000000002
+  outward_edges:
+    51: 15.06923879981041
+    67: 9.827817445993425
+408:
+  node_pos:
+  - 282.6
+  - 181.25
+  outward_edges:
+    41: 10.198528122901918
+    409: 9.657106769084931
+409:
+  node_pos:
+  - 282.05
+  - 191.25
+  outward_edges:
+    408: 9.657106769084931
+    410: 9.686396092176437
+410:
+  node_pos:
+  - 281.5
+  - 201.25
+  outward_edges:
+    20: 8.344974738359452
+    409: 9.686396092176437
+411:
+  node_pos:
+  - 293.5
+  - 171.15
+  outward_edges:
+    41: 10.227817445993423
+    412: 9.586396092176438
+412:
+  node_pos:
+  - 303.5
+  - 171.65
+  outward_edges:
+    67: 12.122792184352875
+    411: 9.586396092176438
+413:
+  node_pos:
+  - 259.3
+  - 179.65
+  outward_edges:
+    69: 10.364213538169862
+    414: 9.748528122901917
+414:
+  node_pos:
+  - 258.6
+  - 189.65
+  outward_edges:
+    413: 9.748528122901917
+    415: 9.66923879981041
+415:
+  node_pos:
+  - 257.95
+  - 199.65
+  outward_edges:
+    79: 8.848528122901916
+    414: 9.66923879981041
+416:
+  node_pos:
+  - 271.15000000000003
+  - 170.0
+  outward_edges:
+    41: 11.56923879981041
+    69: 10.579898953437805
+417:
+  node_pos:
+  - 293.1
+  - 160.85000000000002
+  outward_edges:
+    71: 10.028427076339723
+    418: 10.287005722522736
+418:
+  node_pos:
+  - 303.1
+  - 163.0
+  outward_edges:
+    417: 10.287005722522736
+    419: 10.287005722522736
+419:
+  node_pos:
+  - 313.1
+  - 165.10000000000002
+  outward_edges:
+    418: 10.287005722522736
+    420: 21.156854152679443
+420:
+  node_pos:
+  - 333.1
+  - 169.3
+  outward_edges:
+    61: 14.061879414319993
+    419: 21.156854152679443
+421:
+  node_pos:
+  - 265.45
+  - 155.05
+  outward_edges:
+    69: 16.232590091228484
+    422: 10.928427076339723
+422:
+  node_pos:
+  - 276.05
+  - 157.20000000000002
+  outward_edges:
+    71: 7.937005722522736
+    421: 10.928427076339723
diff --git a/output_yaml/connected_graph_high_level.yaml b/output_yaml/connected_graph_high_level.yaml
new file mode 100644
index 0000000..f08a9e5
--- /dev/null
+++ b/output_yaml/connected_graph_high_level.yaml
@@ -0,0 +1,3223 @@
+0:
+  node_pos:
+  - 394.8
+  - 456.1
+  outward_edges:
+    13: 41.99974738359452
+    40: 33.51837655305862
+    66: 33.65979790687561
+    85: 42.60832602977753
+    228: 10.310660153627396
+    231: 10.28137083053589
+    237: 12.293502861261368
+    266: 10.443502861261369
+1:
+  node_pos:
+  - 262.8
+  - 444.3
+  outward_edges:
+    28: 33.69619399905205
+    32: 42.049747383594514
+    77: 36.09619399905205
+    86: 42.86543279886246
+    248: 10.372792184352875
+    251: 10.393502861261368
+    258: 14.809188276529312
+    286: 10.452081507444383
+2:
+  node_pos:
+  - 368.90000000000003
+  - 366.5
+  outward_edges:
+    14: 46.85330076813698
+    15: 33.692640614509585
+    52: 32.1512192606926
+    297: 10.331370830535889
+    300: 10.372792184352875
+    306: 10.922792184352875
+    330: 17.429898953437807
+3:
+  node_pos:
+  - 407.40000000000003
+  - 628.1500000000001
+  outward_edges:
+    3: 6.501219260692597
+    123: 15.331980460882187
+4:
+  node_pos:
+  - 340.05
+  - 622.0
+  outward_edges:
+    7: 55.46248904466629
+    42: 237.84589756131174
+    93: 24.224011445045473
+    100: 12.709188276529312
+    142: 13.4506096303463
+5:
+  node_pos:
+  - 241.5
+  - 586.1
+  outward_edges:
+    5: 2.3727921843528748
+    42: 6.91923879981041
+    54: 8.156244522333145
+6:
+  node_pos:
+  - 218.0
+  - 576.9
+  outward_edges:
+    6: 16.56482316851616
+    21: 17.271320307254793
+    65: 169.10544285178185
+    133: 11.74827550649643
+7:
+  node_pos:
+  - 345.3
+  - 568.1
+  outward_edges:
+    4: 55.46248904466629
+    34: 13.924873691797258
+    74: 38.91352979838848
+    139: 10.289949476718903
+    150: 17.626524075865746
+8:
+  node_pos:
+  - 363.20000000000005
+  - 530.65
+  outward_edges:
+    9: 16.95538227558136
+    24: 3.5399494767189026
+9:
+  node_pos:
+  - 350.55
+  - 525.8000000000001
+  outward_edges:
+    8: 16.95538227558136
+    84: 7.502691137790681
+    97: 13.035533845424652
+10:
+  node_pos:
+  - 347.75
+  - 500.90000000000003
+  outward_edges:
+    38: 8.716295045614244
+    76: 3.847056245803833
+11:
+  node_pos:
+  - 328.85
+  - 450.6
+  outward_edges:
+    26: 42.48259009122849
+    28: 34.11187941431999
+    30: 42.06543279886246
+    40: 33.71335129141808
+    238: 10.352081507444382
+    241: 10.372792184352875
+    247: 12.659188276529314
+    276: 10.322792184352876
+12:
+  node_pos:
+  - 431.1
+  - 417.6
+  outward_edges:
+    13: 33.37695519924164
+    66: 41.99619399905205
+    259: 10.331370830535889
+    262: 10.343502861261369
+    268: 12.172792184352875
+    325: 10.622792184352875
+13:
+  node_pos:
+  - 398.20000000000005
+  - 415.0
+  outward_edges:
+    0: 41.99974738359452
+    12: 33.37695519924164
+    14: 33.842640614509584
+    15: 46.453300768136984
+    264: 10.28137083053589
+    267: 10.352081507444382
+    273: 12.576345568895341
+    296: 14.87634556889534
+14:
+  node_pos:
+  - 365.1
+  - 412.35
+  outward_edges:
+    2: 46.85330076813698
+    13: 33.842640614509584
+    30: 32.90979790687561
+    40: 42.02903670668602
+    269: 10.310660153627396
+    272: 10.393502861261368
+    278: 11.643502861261368
+    299: 15.297056245803834
+15:
+  node_pos:
+  - 401.95000000000005
+  - 369.5
+  outward_edges:
+    2: 33.692640614509585
+    13: 46.453300768136984
+    294: 10.352081507444382
+    301: 12.405634891986848
+    321: 16.159188276529314
+    328: 7.548528122901917
+16:
+  node_pos:
+  - 304.15000000000003
+  - 360.5
+  outward_edges:
+    17: 29.859797906875613
+    31: 46.9518288910389
+    52: 34.17903670668602
+    88: 33.86690467596054
+    307: 10.393502861261368
+    310: 10.434924215078354
+    316: 12.538477599620819
+    334: 8.489949476718904
+17:
+  node_pos:
+  - 306.1
+  - 331.3
+  outward_edges:
+    16: 29.859797906875613
+    17: 2.114213538169861
+    18: 33.816904675960544
+    333: 10.455634891986847
+    338: 12.37634556889534
+18:
+  node_pos:
+  - 273.15000000000003
+  - 328.0
+  outward_edges:
+    17: 33.816904675960544
+    29: 39.92192993760109
+    78: 31.139087229967117
+    88: 29.735533845424655
+    335: 10.310660153627396
+    337: 10.434924215078354
+    340: 9.893502861261368
+    343: 8.439949476718903
+19:
+  node_pos:
+  - 278.75
+  - 249.40000000000003
+  outward_edges:
+    20: 39.80269113779068
+    29: 39.86482316851616
+    89: 30.352691137790682
+    358: 10.26923879981041
+    361: 10.160660153627397
+    368: 9.098528122901916
+    375: 8.515685415267944
+20:
+  node_pos:
+  - 281.15000000000003
+  - 210.05
+  outward_edges:
+    19: 39.80269113779068
+    41: 39.599137753248215
+    49: 32.98700572252274
+    79: 23.279898953437808
+    373: 10.177817445993425
+    376: 9.648528122901917
+    381: 12.510660153627397
+    410: 8.344974738359452
+21:
+  node_pos:
+  - 235.15
+  - 578.5
+  outward_edges:
+    6: 17.271320307254793
+    37: 50.37878409028053
+    54: 2.332842707633972
+    158: 7.455634891986847
+22:
+  node_pos:
+  - 428.3
+  - 545.8000000000001
+  outward_edges:
+    35: 7.464823168516159
+    58: 5.199137753248215
+    73: 4.9642135381698616
+    94: 33.6728965818882
+23:
+  node_pos:
+  - 441.0
+  - 538.15
+  outward_edges:
+    50: 5.736396092176438
+    53: 2.7899494767189026
+24:
+  node_pos:
+  - 367.0
+  - 531.5500000000001
+  outward_edges:
+    8: 3.5399494767189026
+    50: 79.77436845898629
+    80: 51.231118214130404
+    159: 10.393502861261368
+25:
+  node_pos:
+  - 243.55
+  - 531.15
+  outward_edges:
+    37: 7.7142135381698616
+    96: 20.56984843015671
+    163: 10.497056245803833
+    211: 13.38847759962082
+26:
+  node_pos:
+  - 325.1
+  - 492.05
+  outward_edges:
+    11: 42.48259009122849
+    38: 40.43883461356163
+    39: 34.166904675960545
+    201: 10.538477599620819
+    213: 12.714213538169862
+    240: 10.884924215078355
+27:
+  node_pos:
+  - 347.40000000000003
+  - 212.5
+  outward_edges:
+    49: 33.81629504561425
+    90: 33.28345233798027
+    91: 38.26629504561424
+    369: 10.198528122901918
+    372: 12.810660153627396
+    396: 7.0949747383594515
+28:
+  node_pos:
+  - 295.75
+  - 447.45000000000005
+  outward_edges:
+    1: 33.69619399905205
+    11: 34.11187941431999
+    31: 42.40685415267944
+    39: 42.64472212195397
+    243: 10.372792184352875
+    246: 10.497056245803833
+    252: 12.347056245803834
+    281: 10.643502861261368
+29:
+  node_pos:
+  - 276.2
+  - 288.8
+  outward_edges:
+    18: 39.92192993760109
+    19: 39.86482316851616
+    99: 35.82903670668602
+    341: 10.289949476718903
+    344: 10.260660153627397
+    357: 14.426345568895341
+    360: 8.536396092176437
+30:
+  node_pos:
+  - 332.75
+  - 409.55
+  outward_edges:
+    11: 42.06543279886246
+    14: 32.90979790687561
+    31: 33.71690467596054
+    52: 47.23467159867287
+    274: 10.393502861261368
+    277: 10.372792184352875
+    283: 12.367766922712327
+    304: 15.471320307254793
+31:
+  node_pos:
+  - 299.90000000000003
+  - 406.20000000000005
+  outward_edges:
+    16: 46.9518288910389
+    28: 42.40685415267944
+    30: 33.71690467596054
+    32: 34.782590091228485
+    279: 10.434924215078354
+    282: 10.41421353816986
+    288: 13.371320307254791
+    309: 15.209188276529312
+32:
+  node_pos:
+  - 266.2
+  - 403.15000000000003
+  outward_edges:
+    1: 42.049747383594514
+    31: 34.782590091228485
+    87: 36.33614347577095
+    88: 47.31396092176438
+    284: 10.352081507444382
+    287: 10.426345568895341
+    293: 14.72634556889534
+    314: 15.447056245803834
+33:
+  node_pos:
+  - 416.0
+  - 593.35
+  outward_edges:
+    33: 2.5914213538169864
+34:
+  node_pos:
+  - 359.0
+  - 570.1
+  outward_edges:
+    7: 13.924873691797258
+    34: 1.5328427076339723
+    137: 9.91421353816986
+35:
+  node_pos:
+  - 429.8
+  - 540.35
+  outward_edges:
+    22: 7.464823168516159
+    68: 2.81923879981041
+    73: 2.2485281229019165
+36:
+  node_pos:
+  - 418.45000000000005
+  - 539.7
+  outward_edges:
+    80: 13.21984843015671
+37:
+  node_pos:
+  - 235.8
+  - 532.1
+  outward_edges:
+    21: 50.37878409028053
+    25: 7.7142135381698616
+    155: 11.15979790687561
+    204: 24.60391039848328
+38:
+  node_pos:
+  - 356.15000000000003
+  - 498.95000000000005
+  outward_edges:
+    10: 8.716295045614244
+    26: 40.43883461356163
+    75: 183.0484843015671
+    201: 29.358935660123826
+    225: 48.380255967378616
+39:
+  node_pos:
+  - 291.85
+  - 489.0
+  outward_edges:
+    26: 34.166904675960545
+    28: 42.64472212195397
+    86: 33.92903670668602
+    212: 10.48847759962082
+    215: 12.405634891986848
+    245: 10.943502861261369
+40:
+  node_pos:
+  - 361.85
+  - 453.5
+  outward_edges:
+    0: 33.51837655305862
+    11: 33.71335129141808
+    14: 42.02903670668602
+    72: 43.07045806050301
+    233: 10.331370830535889
+    236: 10.352081507444382
+    242: 12.417766922712326
+    271: 10.49350286126137
+41:
+  node_pos:
+  - 283.0
+  - 170.75
+  outward_edges:
+    20: 39.599137753248215
+    67: 33.099137753248215
+    69: 22.71984843015671
+    71: 10.532842707633973
+    408: 10.198528122901918
+    411: 10.227817445993423
+    416: 11.56923879981041
+42:
+  node_pos:
+  - 240.65
+  - 593.3000000000001
+  outward_edges:
+    4: 237.84589756131174
+    5: 6.91923879981041
+    64: 21.9911687374115
+    105: 15.737005722522737
+43:
+  node_pos:
+  - 361.20000000000005
+  - 533.0500000000001
+  outward_edges:
+    74: 10.70710676908493
+    83: 14.740559107065202
+    94: 52.82056245803833
+    151: 13.355129659175873
+44:
+  node_pos:
+  - 285.8
+  - 507.80000000000007
+  outward_edges:
+    48: 14.466295045614244
+    59: 5.210660153627396
+    96: 73.36726168990135
+    183: 10.41421353816986
+45:
+  node_pos:
+  - 444.25
+  - 576.9
+  outward_edges:
+    45: 2.4363960921764374
+    55: 7.11923879981041
+    62: 5.857106769084931
+46:
+  node_pos:
+  - 405.95000000000005
+  - 573.4
+  outward_edges:
+    56: 17.981980460882188
+    57: 17.903731891512873
+    94: 27.294112491607667
+    147: 16.4006096303463
+47:
+  node_pos:
+  - 448.05
+  - 549.45
+  outward_edges:
+    47: 0.8707106769084931
+    53: 17.38987536728382
+48:
+  node_pos:
+  - 276.85
+  - 501.45000000000005
+  outward_edges:
+    44: 14.466295045614244
+    59: 10.288477599620819
+    196: 10.179898953437807
+49:
+  node_pos:
+  - 313.85
+  - 211.0
+  outward_edges:
+    20: 32.98700572252274
+    27: 33.81629504561425
+    67: 38.366295045614244
+    371: 10.21923879981041
+    377: 12.610660153627396
+    406: 7.224264061450959
+50:
+  node_pos:
+  - 434.95000000000005
+  - 537.45
+  outward_edges:
+    23: 5.736396092176438
+    24: 79.77436845898629
+    68: 3.853553384542465
+51:
+  node_pos:
+  - 341.20000000000005
+  - 173.5
+  outward_edges:
+    67: 25.46776692271233
+    71: 68.2439642727375
+    407: 15.06923879981041
+52:
+  node_pos:
+  - 337.40000000000003
+  - 363.65000000000003
+  outward_edges:
+    2: 32.1512192606926
+    16: 34.17903670668602
+    30: 47.23467159867287
+    302: 10.372792184352875
+    305: 10.293502861261368
+    311: 12.809188276529312
+    332: 17.13345233798027
+53:
+  node_pos:
+  - 442.35
+  - 535.35
+  outward_edges:
+    23: 2.7899494767189026
+    47: 17.38987536728382
+    75: 18.699494767189027
+54:
+  node_pos:
+  - 237.9
+  - 579.0500000000001
+  outward_edges:
+    5: 8.156244522333145
+    21: 2.332842707633972
+    54: 6.220458060503006
+55:
+  node_pos:
+  - 436.95000000000005
+  - 577.3000000000001
+  outward_edges:
+    45: 7.11923879981041
+    55: 1.2414213538169863
+    56: 13.866295045614244
+    62: 11.322792184352876
+56:
+  node_pos:
+  - 423.45000000000005
+  - 576.1
+  outward_edges:
+    46: 17.981980460882188
+    55: 13.866295045614244
+    56: 2.2414213538169863
+57:
+  node_pos:
+  - 391.3
+  - 573.1
+  outward_edges:
+    46: 17.903731891512873
+    57: 1.3621320307254792
+    138: 7.834924215078354
+58:
+  node_pos:
+  - 432.75
+  - 548.65
+  outward_edges:
+    22: 5.199137753248215
+    58: 2.353553384542465
+    62: 36.89472212195397
+    146: 22.16482316851616
+59:
+  node_pos:
+  - 287.05
+  - 502.45000000000005
+  outward_edges:
+    44: 5.210660153627396
+    48: 10.288477599620819
+    63: 55.75954529047013
+    190: 9.981370830535889
+60:
+  node_pos:
+  - 246.8
+  - 498.55
+  outward_edges:
+    65: 17.182337474822997
+    96: 64.93944424390793
+    195: 9.943502861261369
+    209: 18.561269783973696
+61:
+  node_pos:
+  - 343.75
+  - 173.10000000000002
+  outward_edges:
+    61: 2.2035533845424653
+    91: 5.493502861261368
+    420: 14.061879414319993
+62:
+  node_pos:
+  - 444.15000000000003
+  - 570.75
+  outward_edges:
+    45: 5.857106769084931
+    55: 11.322792184352876
+    58: 36.89472212195397
+    136: 10.802081507444383
+    146: 14.18847759962082
+63:
+  node_pos:
+  - 334.90000000000003
+  - 527.1
+  outward_edges:
+    59: 55.75954529047013
+    63: 4.860660153627396
+    92: 41.61248904466629
+    97: 6.239949476718903
+64:
+  node_pos:
+  - 253.3
+  - 602.25
+  outward_edges:
+    42: 21.9911687374115
+    93: 131.55519023537636
+    104: 9.434924215078354
+    125: 12.887362736463547
+    130: 7.728427076339722
+65:
+  node_pos:
+  - 232.50047302246094
+  - 490.51361083984375
+  outward_edges:
+    6: 169.10544285178185
+    60: 17.182337474822997
+    86: 28.799494767189028
+    216: 11.37462107539177
+    256: 12.161626797914506
+66:
+  node_pos:
+  - 427.90000000000003
+  - 458.8
+  outward_edges:
+    0: 33.65979790687561
+    12: 41.99619399905205
+    217: 10.393502861261368
+    226: 10.393502861261368
+    232: 12.455634891986847
+    261: 10.481370830535889
+67:
+  node_pos:
+  - 315.75
+  - 172.85000000000002
+  outward_edges:
+    41: 33.099137753248215
+    49: 38.366295045614244
+    51: 25.46776692271233
+    404: 10.20710676908493
+    407: 9.827817445993425
+    412: 12.122792184352875
+68:
+  node_pos:
+  - 430.70000000000005
+  - 537.3000000000001
+  outward_edges:
+    35: 2.81923879981041
+    50: 3.853553384542465
+    82: 2.912132030725479
+69:
+  node_pos:
+  - 260.65000000000003
+  - 169.20000000000002
+  outward_edges:
+    41: 22.71984843015671
+    71: 36.367261689901355
+    79: 40.36335129141808
+    413: 10.364213538169862
+    416: 10.579898953437805
+    421: 16.232590091228484
+70:
+  node_pos:
+  - 415.25
+  - 187.35000000000002
+  outward_edges:
+    91: 105.20315254926682
+    98: 36.11873356699944
+    382: 10.227817445993423
+    392: 9.957716399431229
+    403: 12.518376553058625
+71:
+  node_pos:
+  - 283.45
+  - 159.8
+  outward_edges:
+    41: 10.532842707633973
+    51: 68.2439642727375
+    69: 36.367261689901355
+    417: 10.028427076339723
+    422: 7.937005722522736
+72:
+  node_pos:
+  - 358.45000000000005
+  - 495.6
+  outward_edges:
+    40: 43.07045806050301
+    85: 33.80477264523506
+    199: 10.455634891986847
+    235: 11.514213538169862
+73:
+  node_pos:
+  - 427.3
+  - 540.75
+  outward_edges:
+    22: 4.9642135381698616
+    35: 2.2485281229019165
+    82: 2.8621320307254794
+74:
+  node_pos:
+  - 350.15000000000003
+  - 533.2
+  outward_edges:
+    7: 38.91352979838848
+    43: 10.70710676908493
+    83: 2.5071067690849307
+    149: 10.352081507444382
+75:
+  node_pos:
+  - 434.6
+  - 519.35
+  outward_edges:
+    38: 183.0484843015671
+    53: 18.699494767189027
+    84: 96.33832938075066
+    181: 11.22634556889534
+76:
+  node_pos:
+  - 345.05
+  - 498.20000000000005
+  outward_edges:
+    10: 3.847056245803833
+    84: 13.481549337506294
+    194: 15.854772645235062
+77:
+  node_pos:
+  - 227.5
+  - 441.15000000000003
+  outward_edges:
+    1: 36.09619399905205
+    87: 41.729036706686024
+    253: 10.434924215078354
+    257: 10.331370830535889
+    291: 10.089949476718903
+78:
+  node_pos:
+  - 242.60000000000002
+  - 325.3
+  outward_edges:
+    18: 31.139087229967117
+    78: 2.332842707633972
+    339: 10.331370830535889
+79:
+  node_pos:
+  - 257.90000000000003
+  - 208.75
+  outward_edges:
+    20: 23.279898953437808
+    69: 40.36335129141808
+    89: 41.60721116662026
+    378: 10.68345233798027
+    381: 10.198528122901918
+    415: 8.848528122901916
+80:
+  node_pos:
+  - 416.95000000000005
+  - 536.1
+  outward_edges:
+    24: 51.231118214130404
+    36: 13.21984843015671
+    95: 2.881370830535889
+    162: 9.239949476718904
+81:
+  node_pos:
+  - 342.35
+  - 567.25
+  outward_edges:
+    92: 11.334924215078354
+    166: 11.043250244855882
+82:
+  node_pos:
+  - 427.35
+  - 537.4
+  outward_edges:
+    68: 2.912132030725479
+    73: 2.8621320307254794
+83:
+  node_pos:
+  - 350.25
+  - 530.6
+  outward_edges:
+    43: 14.740559107065202
+    74: 2.5071067690849307
+84:
+  node_pos:
+  - 347.90000000000003
+  - 518.8000000000001
+  outward_edges:
+    9: 7.502691137790681
+    75: 96.33832938075066
+    76: 13.481549337506294
+    175: 10.524011445045472
+    194: 9.56482316851616
+85:
+  node_pos:
+  - 391.45000000000005
+  - 497.90000000000003
+  outward_edges:
+    0: 42.60832602977753
+    72: 33.80477264523506
+    200: 12.455634891986847
+    222: 14.271320307254792
+    230: 11.093502861261369
+86:
+  node_pos:
+  - 258.95
+  - 486.1
+  outward_edges:
+    1: 42.86543279886246
+    39: 33.92903670668602
+    65: 28.799494767189028
+    214: 10.538477599620819
+    216: 16.800609630346298
+    250: 11.22634556889534
+87:
+  node_pos:
+  - 230.9
+  - 400.35
+  outward_edges:
+    32: 36.33614347577095
+    77: 41.729036706686024
+    99: 123.26848095059395
+    289: 10.393502861261368
+    292: 10.75771639943123
+    355: 13.522792184352875
+88:
+  node_pos:
+  - 271.1
+  - 357.25
+  outward_edges:
+    16: 33.86690467596054
+    18: 29.735533845424655
+    32: 47.31396092176438
+    312: 10.621320307254791
+    315: 10.393502861261368
+    336: 8.552081507444383
+89:
+  node_pos:
+  - 248.75
+  - 247.10000000000002
+  outward_edges:
+    19: 30.352691137790682
+    79: 41.60721116662026
+    99: 41.830865597724916
+    364: 11.242640614509583
+    367: 10.405634891986848
+    380: 8.08345233798027
+90:
+  node_pos:
+  - 380.5
+  - 214.0
+  outward_edges:
+    27: 33.28345233798027
+    370: 12.277817445993424
+    386: 10.26923879981041
+    401: 15.789949476718903
+91:
+  node_pos:
+  - 349.35
+  - 174.45000000000002
+  outward_edges:
+    27: 38.26629504561424
+    61: 5.493502861261368
+    70: 105.20315254926682
+    394: 10.20710676908493
+    397: 10.209188276529312
+92:
+  node_pos:
+  - 330.90000000000003
+  - 567.0500000000001
+  outward_edges:
+    63: 41.61248904466629
+    81: 11.334924215078354
+    92: 5.205634891986847
+93:
+  node_pos:
+  - 316.95000000000005
+  - 618.75
+  outward_edges:
+    4: 24.224011445045473
+    64: 131.55519023537636
+    100: 10.973401814699173
+    102: 7.402081507444382
+    132: 10.656244522333147
+94:
+  node_pos:
+  - 408.45000000000005
+  - 546.5
+  outward_edges:
+    22: 33.6728965818882
+    43: 52.82056245803833
+    46: 27.294112491607667
+    147: 10.372792184352875
+    154: 7.764213538169861
+95:
+  node_pos:
+  - 416.0
+  - 539.15
+  outward_edges:
+    80: 2.881370830535889
+    95: 2.2899494767189026
+96:
+  node_pos:
+  - 263.7
+  - 533.15
+  outward_edges:
+    25: 20.56984843015671
+    44: 73.36726168990135
+    60: 64.93944424390793
+    163: 9.460660153627396
+    185: 16.854163014888766
+    198: 12.788477599620819
+97:
+  node_pos:
+  - 341.35
+  - 527.7
+  outward_edges:
+    9: 13.035533845424652
+    63: 6.239949476718903
+    164: 10.828427076339722
+98:
+  node_pos:
+  - 448.25
+  - 194.60000000000002
+  outward_edges:
+    70: 36.11873356699944
+    98: 1.3778174459934236
+    391: 7.494974738359452
+    393: 14.72903670668602
+99:
+  node_pos:
+  - 241.25
+  - 286.2
+  outward_edges:
+    29: 35.82903670668602
+    87: 123.26848095059395
+    89: 41.830865597724916
+    347: 10.517766922712326
+    356: 10.479898953437806
+    366: 8.460660153627396
+100:
+  node_pos:
+  - 327.40000000000003
+  - 621.5
+  outward_edges:
+    4: 12.709188276529312
+    93: 10.973401814699173
+101:
+  node_pos:
+  - 312.55
+  - 602.4
+  outward_edges:
+    102: 11.496803629398347
+102:
+  node_pos:
+  - 318.15000000000003
+  - 611.2
+  outward_edges:
+    93: 7.402081507444382
+    101: 11.496803629398347
+103:
+  node_pos:
+  - 446.05
+  - 595.9
+  outward_edges:
+    103: 2.2828427076339723
+104:
+  node_pos:
+  - 243.8
+  - 601.65
+  outward_edges:
+    64: 9.434924215078354
+    104: 12.014823168516159
+105:
+  node_pos:
+  - 234.05
+  - 602.45
+  outward_edges:
+    42: 15.737005722522737
+    106: 9.852081507444382
+106:
+  node_pos:
+  - 233.10000000000002
+  - 612.45
+  outward_edges:
+    105: 9.852081507444382
+    107: 10.369848430156708
+107:
+  node_pos:
+  - 237.45000000000002
+  - 619.3000000000001
+  outward_edges:
+    106: 10.369848430156708
+    108: 9.731370830535889
+108:
+  node_pos:
+  - 247.45
+  - 620.2
+  outward_edges:
+    107: 9.731370830535889
+    109: 9.852081507444382
+109:
+  node_pos:
+  - 257.45
+  - 621.1500000000001
+  outward_edges:
+    108: 9.852081507444382
+    110: 9.852081507444382
+110:
+  node_pos:
+  - 267.45
+  - 622.1
+  outward_edges:
+    109: 9.852081507444382
+    111: 9.852081507444382
+111:
+  node_pos:
+  - 277.45
+  - 623.0500000000001
+  outward_edges:
+    110: 9.852081507444382
+    112: 9.852081507444382
+112:
+  node_pos:
+  - 287.45
+  - 624.0
+  outward_edges:
+    111: 9.852081507444382
+    113: 9.997056245803833
+113:
+  node_pos:
+  - 292.25
+  - 629.9000000000001
+  outward_edges:
+    112: 9.997056245803833
+    114: 9.91421353816986
+114:
+  node_pos:
+  - 302.25
+  - 631.0
+  outward_edges:
+    113: 9.91421353816986
+    115: 9.893502861261368
+115:
+  node_pos:
+  - 312.25
+  - 632.0500000000001
+  outward_edges:
+    114: 9.893502861261368
+    116: 9.893502861261368
+116:
+  node_pos:
+  - 322.25
+  - 633.1
+  outward_edges:
+    115: 9.893502861261368
+    117: 9.872792184352875
+117:
+  node_pos:
+  - 332.25
+  - 634.1
+  outward_edges:
+    116: 9.872792184352875
+    118: 9.955634891986847
+118:
+  node_pos:
+  - 340.90000000000003
+  - 633.1500000000001
+  outward_edges:
+    117: 9.955634891986847
+    119: 22.2911687374115
+119:
+  node_pos:
+  - 351.6
+  - 622.4000000000001
+  outward_edges:
+    118: 22.2911687374115
+    120: 9.831370830535889
+120:
+  node_pos:
+  - 361.6
+  - 623.3000000000001
+  outward_edges:
+    119: 9.831370830535889
+    121: 24.59766587615013
+121:
+  node_pos:
+  - 368.1
+  - 627.85
+  outward_edges:
+    120: 24.59766587615013
+    121: 0.9707106769084931
+122:
+  node_pos:
+  - 382.5
+  - 624.8000000000001
+  outward_edges:
+    123: 9.810660153627396
+123:
+  node_pos:
+  - 392.5
+  - 625.6500000000001
+  outward_edges:
+    3: 15.331980460882187
+    122: 9.810660153627396
+124:
+  node_pos:
+  - 273.0
+  - 586.9
+  outward_edges:
+    125: 12.31309867501259
+    126: 9.689949476718903
+125:
+  node_pos:
+  - 263.0
+  - 594.1
+  outward_edges:
+    64: 12.887362736463547
+    124: 12.31309867501259
+126:
+  node_pos:
+  - 283.0
+  - 587.65
+  outward_edges:
+    124: 9.689949476718903
+    127: 10.411269783973694
+127:
+  node_pos:
+  - 285.90000000000003
+  - 597.25
+  outward_edges:
+    126: 10.411269783973694
+    128: 10.24558436870575
+128:
+  node_pos:
+  - 287.85
+  - 607.25
+  outward_edges:
+    127: 10.24558436870575
+129:
+  node_pos:
+  - 270.65000000000003
+  - 606.95
+  outward_edges:
+    130: 10.328427076339722
+    131: 31.149494767189026
+130:
+  node_pos:
+  - 260.65000000000003
+  - 604.7
+  outward_edges:
+    64: 7.728427076339722
+    129: 10.328427076339722
+131:
+  node_pos:
+  - 296.85
+  - 613.45
+  outward_edges:
+    129: 31.149494767189026
+    132: 10.618376553058624
+132:
+  node_pos:
+  - 306.85
+  - 616.45
+  outward_edges:
+    93: 10.656244522333147
+    131: 10.618376553058624
+133:
+  node_pos:
+  - 207.55
+  - 580.4
+  outward_edges:
+    6: 11.74827550649643
+    134: 9.872792184352875
+134:
+  node_pos:
+  - 197.55
+  - 579.4
+  outward_edges:
+    133: 9.872792184352875
+    135: 9.872792184352875
+135:
+  node_pos:
+  - 187.55
+  - 578.4
+  outward_edges:
+    134: 9.872792184352875
+    135: 2.582842707633972
+136:
+  node_pos:
+  - 433.25
+  - 569.6
+  outward_edges:
+    62: 10.802081507444383
+137:
+  node_pos:
+  - 368.95000000000005
+  - 570.4
+  outward_edges:
+    34: 9.91421353816986
+    137: 17.826955199241638
+138:
+  node_pos:
+  - 383.45000000000005
+  - 571.75
+  outward_edges:
+    57: 7.834924215078354
+139:
+  node_pos:
+  - 344.55
+  - 578.65
+  outward_edges:
+    7: 10.289949476718903
+    140: 9.852081507444382
+140:
+  node_pos:
+  - 343.6
+  - 588.65
+  outward_edges:
+    139: 9.852081507444382
+    141: 9.852081507444382
+141:
+  node_pos:
+  - 342.65000000000003
+  - 598.65
+  outward_edges:
+    140: 9.852081507444382
+    142: 9.852081507444382
+142:
+  node_pos:
+  - 341.70000000000005
+  - 608.6500000000001
+  outward_edges:
+    4: 13.4506096303463
+    141: 9.852081507444382
+143:
+  node_pos:
+  - 472.5
+  - 567.75
+  outward_edges:
+    143: 0.6000000000000001
+144:
+  node_pos:
+  - 473.70000000000005
+  - 553.2
+  outward_edges:
+    144: 0.6000000000000001
+145:
+  node_pos:
+  - 455.75
+  - 550.4
+  outward_edges:
+    145: 1.3
+146:
+  node_pos:
+  - 445.75
+  - 556.65
+  outward_edges:
+    58: 22.16482316851616
+    62: 14.18847759962082
+147:
+  node_pos:
+  - 407.45000000000005
+  - 557.0
+  outward_edges:
+    46: 16.4006096303463
+    94: 10.372792184352875
+148:
+  node_pos:
+  - 473.85
+  - 543.65
+  outward_edges:
+    148: 0.65
+149:
+  node_pos:
+  - 349.3
+  - 543.7
+  outward_edges:
+    74: 10.352081507444382
+    150: 9.852081507444382
+150:
+  node_pos:
+  - 348.35
+  - 553.7
+  outward_edges:
+    7: 17.626524075865746
+    149: 9.852081507444382
+151:
+  node_pos:
+  - 370.6
+  - 542.4
+  outward_edges:
+    43: 13.355129659175873
+    152: 9.852081507444382
+152:
+  node_pos:
+  - 380.6
+  - 543.35
+  outward_edges:
+    151: 9.852081507444382
+    153: 9.852081507444382
+153:
+  node_pos:
+  - 390.6
+  - 544.3000000000001
+  outward_edges:
+    152: 9.852081507444382
+    154: 9.831370830535889
+154:
+  node_pos:
+  - 400.6
+  - 545.2
+  outward_edges:
+    94: 7.764213538169861
+    153: 9.831370830535889
+155:
+  node_pos:
+  - 239.4
+  - 541.0
+  outward_edges:
+    37: 11.15979790687561
+    156: 9.872792184352875
+156:
+  node_pos:
+  - 238.4
+  - 551.0
+  outward_edges:
+    155: 9.872792184352875
+    157: 9.852081507444382
+157:
+  node_pos:
+  - 237.45000000000002
+  - 561.0
+  outward_edges:
+    156: 9.852081507444382
+    158: 9.872792184352875
+158:
+  node_pos:
+  - 236.45000000000002
+  - 571.0
+  outward_edges:
+    21: 7.455634891986847
+    157: 9.872792184352875
+159:
+  node_pos:
+  - 377.5
+  - 532.65
+  outward_edges:
+    24: 10.393502861261368
+    160: 9.810660153627396
+160:
+  node_pos:
+  - 387.5
+  - 533.5
+  outward_edges:
+    159: 9.810660153627396
+    161: 9.810660153627396
+161:
+  node_pos:
+  - 397.5
+  - 534.35
+  outward_edges:
+    160: 9.810660153627396
+    162: 9.810660153627396
+162:
+  node_pos:
+  - 407.5
+  - 535.2
+  outward_edges:
+    80: 9.239949476718904
+    161: 9.810660153627396
+163:
+  node_pos:
+  - 254.05
+  - 532.65
+  outward_edges:
+    25: 10.497056245803833
+    96: 9.460660153627396
+164:
+  node_pos:
+  - 338.6
+  - 537.6
+  outward_edges:
+    97: 10.828427076339722
+    165: 9.748528122901917
+165:
+  node_pos:
+  - 337.90000000000003
+  - 547.6
+  outward_edges:
+    164: 9.748528122901917
+    166: 9.81923879981041
+166:
+  node_pos:
+  - 337.55
+  - 557.6
+  outward_edges:
+    81: 11.043250244855882
+    165: 9.81923879981041
+167:
+  node_pos:
+  - 359.05
+  - 516.1
+  outward_edges:
+    168: 10.40771639943123
+    174: 73.47731221318246
+168:
+  node_pos:
+  - 366.65000000000003
+  - 519.45
+  outward_edges:
+    167: 10.40771639943123
+    169: 9.831370830535889
+169:
+  node_pos:
+  - 376.65000000000003
+  - 520.35
+  outward_edges:
+    168: 9.831370830535889
+    170: 9.831370830535889
+170:
+  node_pos:
+  - 386.65000000000003
+  - 521.25
+  outward_edges:
+    169: 9.831370830535889
+    171: 9.852081507444382
+171:
+  node_pos:
+  - 396.65000000000003
+  - 522.2
+  outward_edges:
+    170: 9.852081507444382
+    172: 9.831370830535889
+172:
+  node_pos:
+  - 406.65000000000003
+  - 523.1
+  outward_edges:
+    171: 9.831370830535889
+    173: 9.78137083053589
+173:
+  node_pos:
+  - 416.65000000000003
+  - 524.0
+  outward_edges:
+    172: 9.78137083053589
+    174: 9.872792184352875
+174:
+  node_pos:
+  - 426.65000000000003
+  - 524.7
+  outward_edges:
+    167: 73.47731221318246
+    173: 9.872792184352875
+175:
+  node_pos:
+  - 352.70000000000005
+  - 509.9
+  outward_edges:
+    84: 10.524011445045472
+    176: 12.167766922712326
+176:
+  node_pos:
+  - 364.90000000000003
+  - 511.20000000000005
+  outward_edges:
+    175: 12.167766922712326
+    177: 9.934924215078354
+177:
+  node_pos:
+  - 374.90000000000003
+  - 512.35
+  outward_edges:
+    176: 9.934924215078354
+    178: 9.934924215078354
+178:
+  node_pos:
+  - 384.90000000000003
+  - 513.5
+  outward_edges:
+    177: 9.934924215078354
+    179: 9.934924215078354
+179:
+  node_pos:
+  - 394.90000000000003
+  - 514.65
+  outward_edges:
+    178: 9.934924215078354
+    180: 9.91421353816986
+180:
+  node_pos:
+  - 404.90000000000003
+  - 515.8000000000001
+  outward_edges:
+    179: 9.91421353816986
+    182: 8.352081507444382
+181:
+  node_pos:
+  - 423.40000000000003
+  - 517.9
+  outward_edges:
+    75: 11.22634556889534
+    182: 9.934924215078354
+182:
+  node_pos:
+  - 413.40000000000003
+  - 516.75
+  outward_edges:
+    180: 8.352081507444382
+    181: 9.934924215078354
+183:
+  node_pos:
+  - 285.35
+  - 518.3000000000001
+  outward_edges:
+    44: 10.41421353816986
+    184: 9.831370830535889
+184:
+  node_pos:
+  - 284.45
+  - 528.3000000000001
+  outward_edges:
+    183: 9.831370830535889
+185:
+  node_pos:
+  - 280.35
+  - 535.15
+  outward_edges:
+    96: 16.854163014888766
+    186: 14.21984843015671
+186:
+  node_pos:
+  - 288.05
+  - 536.0
+  outward_edges:
+    185: 14.21984843015671
+    187: 9.810660153627396
+187:
+  node_pos:
+  - 298.05
+  - 536.85
+  outward_edges:
+    186: 9.810660153627396
+    187: 9.359188276529313
+188:
+  node_pos:
+  - 338.8
+  - 505.55000000000007
+  outward_edges:
+    189: 14.527564829587938
+189:
+  node_pos:
+  - 336.85
+  - 515.5
+  outward_edges:
+    188: 14.527564829587938
+190:
+  node_pos:
+  - 297.20000000000005
+  - 502.80000000000007
+  outward_edges:
+    59: 9.981370830535889
+    191: 9.852081507444382
+191:
+  node_pos:
+  - 307.20000000000005
+  - 503.75
+  outward_edges:
+    190: 9.852081507444382
+    191: 16.65269113779068
+192:
+  node_pos:
+  - 319.6
+  - 504.20000000000005
+  outward_edges:
+    193: 9.748528122901917
+193:
+  node_pos:
+  - 329.6
+  - 504.9
+  outward_edges:
+    192: 9.748528122901917
+    193: 7.288477599620819
+194:
+  node_pos:
+  - 343.85
+  - 511.6
+  outward_edges:
+    76: 15.854772645235062
+    84: 9.56482316851616
+195:
+  node_pos:
+  - 256.8
+  - 498.85
+  outward_edges:
+    60: 9.943502861261369
+    196: 10.067766922712327
+196:
+  node_pos:
+  - 266.8
+  - 500.40000000000003
+  outward_edges:
+    48: 10.179898953437807
+    195: 10.067766922712327
+    197: 9.843502861261369
+197:
+  node_pos:
+  - 265.85
+  - 510.35
+  outward_edges:
+    196: 9.843502861261369
+    198: 9.872792184352875
+198:
+  node_pos:
+  - 264.85
+  - 520.35
+  outward_edges:
+    96: 12.788477599620819
+    197: 9.872792184352875
+199:
+  node_pos:
+  - 368.95000000000005
+  - 496.55
+  outward_edges:
+    72: 10.455634891986847
+    200: 9.810660153627396
+200:
+  node_pos:
+  - 378.95000000000005
+  - 497.40000000000003
+  outward_edges:
+    85: 12.455634891986847
+    199: 9.810660153627396
+201:
+  node_pos:
+  - 335.6
+  - 493.65000000000003
+  outward_edges:
+    26: 10.538477599620819
+    38: 29.358935660123826
+202:
+  node_pos:
+  - 227.0
+  - 500.05
+  outward_edges:
+    203: 18.17523070573807
+    209: 22.432947105169298
+203:
+  node_pos:
+  - 222.4
+  - 510.9
+  outward_edges:
+    202: 18.17523070573807
+    204: 9.852081507444382
+204:
+  node_pos:
+  - 221.4
+  - 520.9
+  outward_edges:
+    37: 24.60391039848328
+    203: 9.852081507444382
+205:
+  node_pos:
+  - 221.20000000000002
+  - 530.9
+  outward_edges:
+    206: 10.100609630346298
+206:
+  node_pos:
+  - 219.45000000000002
+  - 540.9
+  outward_edges:
+    205: 10.100609630346298
+    207: 9.872792184352875
+207:
+  node_pos:
+  - 218.45000000000002
+  - 550.9
+  outward_edges:
+    206: 9.872792184352875
+    208: 9.852081507444382
+208:
+  node_pos:
+  - 217.5
+  - 560.9
+  outward_edges:
+    207: 9.852081507444382
+209:
+  node_pos:
+  - 236.0
+  - 506.15
+  outward_edges:
+    60: 18.561269783973696
+    202: 22.432947105169298
+210:
+  node_pos:
+  - 245.70000000000002
+  - 507.75
+  outward_edges:
+    211: 9.852081507444382
+211:
+  node_pos:
+  - 244.9
+  - 517.75
+  outward_edges:
+    25: 13.38847759962082
+    210: 9.852081507444382
+212:
+  node_pos:
+  - 302.3
+  - 490.6
+  outward_edges:
+    39: 10.48847759962082
+    213: 9.831370830535889
+    247: 42.87607148724392
+213:
+  node_pos:
+  - 312.3
+  - 491.5
+  outward_edges:
+    26: 12.714213538169862
+    212: 9.831370830535889
+214:
+  node_pos:
+  - 269.45
+  - 487.70000000000005
+  outward_edges:
+    86: 10.538477599620819
+    215: 9.831370830535889
+215:
+  node_pos:
+  - 279.45
+  - 488.6
+  outward_edges:
+    39: 12.405634891986848
+    214: 9.831370830535889
+216:
+  node_pos:
+  - 242.25
+  - 485.15000000000003
+  outward_edges:
+    65: 11.37462107539177
+    86: 16.800609630346298
+217:
+  node_pos:
+  - 427.0
+  - 469.35
+  outward_edges:
+    66: 10.393502861261368
+    218: 9.789949476718903
+218:
+  node_pos:
+  - 426.20000000000005
+  - 479.35
+  outward_edges:
+    217: 9.789949476718903
+    219: 9.810660153627396
+219:
+  node_pos:
+  - 425.35
+  - 489.35
+  outward_edges:
+    218: 9.810660153627396
+    220: 9.802081507444383
+220:
+  node_pos:
+  - 424.55
+  - 499.35
+  outward_edges:
+    219: 9.802081507444383
+221:
+  node_pos:
+  - 415.6
+  - 500.5
+  outward_edges:
+    222: 9.760660153627397
+    223: 25.21040753722191
+222:
+  node_pos:
+  - 405.6
+  - 499.70000000000005
+  outward_edges:
+    85: 14.271320307254792
+    221: 9.760660153627397
+223:
+  node_pos:
+  - 436.85
+  - 504.75
+  outward_edges:
+    221: 25.21040753722191
+    224: 10.017766922712326
+224:
+  node_pos:
+  - 429.40000000000003
+  - 507.35
+  outward_edges:
+    223: 10.017766922712326
+    225: 30.58908722996712
+225:
+  node_pos:
+  - 399.40000000000003
+  - 504.5
+  outward_edges:
+    38: 48.380255967378616
+    224: 30.58908722996712
+226:
+  node_pos:
+  - 438.45000000000005
+  - 459.65000000000003
+  outward_edges:
+    66: 10.393502861261368
+    227: 9.860660153627396
+227:
+  node_pos:
+  - 448.45000000000005
+  - 460.20000000000005
+  outward_edges:
+    226: 9.860660153627396
+    227: 0.6414213538169862
+228:
+  node_pos:
+  - 394.0
+  - 466.65000000000003
+  outward_edges:
+    0: 10.310660153627396
+    229: 9.789949476718903
+229:
+  node_pos:
+  - 393.20000000000005
+  - 476.65000000000003
+  outward_edges:
+    228: 9.789949476718903
+    230: 9.739949476718904
+230:
+  node_pos:
+  - 392.40000000000003
+  - 486.65000000000003
+  outward_edges:
+    85: 11.093502861261369
+    229: 9.739949476718904
+231:
+  node_pos:
+  - 405.35
+  - 456.95000000000005
+  outward_edges:
+    0: 10.28137083053589
+    232: 9.789949476718903
+232:
+  node_pos:
+  - 415.35
+  - 457.75
+  outward_edges:
+    66: 12.455634891986847
+    231: 9.789949476718903
+233:
+  node_pos:
+  - 360.90000000000003
+  - 464.0
+  outward_edges:
+    40: 10.331370830535889
+    234: 9.760660153627397
+234:
+  node_pos:
+  - 360.1
+  - 474.0
+  outward_edges:
+    233: 9.760660153627397
+    235: 9.810660153627396
+235:
+  node_pos:
+  - 359.25
+  - 484.0
+  outward_edges:
+    72: 11.514213538169862
+    234: 9.810660153627396
+236:
+  node_pos:
+  - 372.35
+  - 454.3
+  outward_edges:
+    40: 10.352081507444382
+    237: 9.789949476718903
+237:
+  node_pos:
+  - 382.35
+  - 455.1
+  outward_edges:
+    0: 12.293502861261368
+    236: 9.789949476718903
+238:
+  node_pos:
+  - 327.90000000000003
+  - 461.1
+  outward_edges:
+    11: 10.352081507444382
+    239: 9.831370830535889
+239:
+  node_pos:
+  - 327.0
+  - 471.1
+  outward_edges:
+    238: 9.831370830535889
+    240: 9.731370830535889
+    423: 13.6274443044847
+240:
+  node_pos:
+  - 326.20000000000005
+  - 481.1
+  outward_edges:
+    26: 10.884924215078355
+    239: 9.731370830535889
+    246: 38.30874999858687
+241:
+  node_pos:
+  - 339.40000000000003
+  - 451.55
+  outward_edges:
+    11: 10.372792184352875
+    242: 9.760660153627397
+242:
+  node_pos:
+  - 349.40000000000003
+  - 452.40000000000003
+  outward_edges:
+    40: 12.417766922712326
+    241: 9.760660153627397
+243:
+  node_pos:
+  - 294.90000000000003
+  - 457.95000000000005
+  outward_edges:
+    28: 10.372792184352875
+    244: 9.852081507444382
+244:
+  node_pos:
+  - 293.95
+  - 467.95000000000005
+  outward_edges:
+    243: 9.852081507444382
+    245: 9.852081507444382
+245:
+  node_pos:
+  - 293.0
+  - 477.95000000000005
+  outward_edges:
+    39: 10.943502861261369
+    244: 9.852081507444382
+246:
+  node_pos:
+  - 306.25
+  - 448.45000000000005
+  outward_edges:
+    28: 10.497056245803833
+    240: 38.30874999858687
+247:
+  node_pos:
+  - 316.25
+  - 449.45000000000005
+  outward_edges:
+    11: 12.659188276529314
+    212: 42.87607148724392
+248:
+  node_pos:
+  - 261.85
+  - 454.85
+  outward_edges:
+    1: 10.372792184352875
+    249: 9.831370830535889
+249:
+  node_pos:
+  - 260.95
+  - 464.85
+  outward_edges:
+    248: 9.831370830535889
+    250: 9.810660153627396
+250:
+  node_pos:
+  - 260.1
+  - 474.85
+  outward_edges:
+    86: 11.22634556889534
+    249: 9.810660153627396
+251:
+  node_pos:
+  - 273.35
+  - 445.25
+  outward_edges:
+    1: 10.393502861261368
+    252: 9.872792184352875
+252:
+  node_pos:
+  - 283.35
+  - 446.25
+  outward_edges:
+    28: 12.347056245803834
+    251: 9.872792184352875
+253:
+  node_pos:
+  - 226.10000000000002
+  - 451.6
+  outward_edges:
+    77: 10.434924215078354
+    254: 9.831370830535889
+254:
+  node_pos:
+  - 225.20000000000002
+  - 461.6
+  outward_edges:
+    253: 9.831370830535889
+    255: 9.852081507444382
+255:
+  node_pos:
+  - 224.25
+  - 471.6
+  outward_edges:
+    254: 9.852081507444382
+    256: 9.831370830535889
+256:
+  node_pos:
+  - 224.20000000000002
+  - 481.6
+  outward_edges:
+    65: 12.161626797914506
+    255: 9.831370830535889
+257:
+  node_pos:
+  - 238.0
+  - 441.90000000000003
+  outward_edges:
+    77: 10.331370830535889
+    258: 9.872792184352875
+258:
+  node_pos:
+  - 248.0
+  - 442.90000000000003
+  outward_edges:
+    1: 14.809188276529312
+    257: 9.872792184352875
+259:
+  node_pos:
+  - 430.3
+  - 428.1
+  outward_edges:
+    12: 10.331370830535889
+    260: 9.689949476718903
+260:
+  node_pos:
+  - 429.55
+  - 438.1
+  outward_edges:
+    259: 9.689949476718903
+    261: 9.789949476718903
+261:
+  node_pos:
+  - 428.75
+  - 448.1
+  outward_edges:
+    66: 10.481370830535889
+    260: 9.789949476718903
+262:
+  node_pos:
+  - 441.55
+  - 418.5
+  outward_edges:
+    12: 10.343502861261369
+    263: 9.739949476718904
+263:
+  node_pos:
+  - 451.55
+  - 419.25
+  outward_edges:
+    262: 9.739949476718904
+    263: 1.2571067690849305
+264:
+  node_pos:
+  - 397.35
+  - 425.5
+  outward_edges:
+    13: 10.28137083053589
+    265: 9.810660153627396
+265:
+  node_pos:
+  - 396.5
+  - 435.5
+  outward_edges:
+    264: 9.810660153627396
+    266: 9.789949476718903
+266:
+  node_pos:
+  - 395.70000000000005
+  - 445.5
+  outward_edges:
+    0: 10.443502861261369
+    265: 9.789949476718903
+267:
+  node_pos:
+  - 408.75
+  - 415.90000000000003
+  outward_edges:
+    13: 10.352081507444382
+    268: 9.710660153627396
+268:
+  node_pos:
+  - 418.75
+  - 416.65000000000003
+  outward_edges:
+    12: 12.172792184352875
+    267: 9.710660153627396
+269:
+  node_pos:
+  - 364.3
+  - 422.90000000000003
+  outward_edges:
+    14: 10.310660153627396
+    270: 9.789949476718903
+270:
+  node_pos:
+  - 363.5
+  - 432.90000000000003
+  outward_edges:
+    269: 9.789949476718903
+    271: 9.810660153627396
+271:
+  node_pos:
+  - 362.65000000000003
+  - 442.90000000000003
+  outward_edges:
+    40: 10.49350286126137
+    270: 9.810660153627396
+272:
+  node_pos:
+  - 375.6
+  - 413.20000000000005
+  outward_edges:
+    14: 10.393502861261368
+    273: 9.760660153627397
+273:
+  node_pos:
+  - 385.6
+  - 414.0
+  outward_edges:
+    13: 12.576345568895341
+    272: 9.760660153627397
+274:
+  node_pos:
+  - 331.75
+  - 420.1
+  outward_edges:
+    30: 10.393502861261368
+    275: 9.852081507444382
+275:
+  node_pos:
+  - 330.8
+  - 430.1
+  outward_edges:
+    274: 9.852081507444382
+    276: 9.872792184352875
+276:
+  node_pos:
+  - 329.8
+  - 440.1
+  outward_edges:
+    11: 10.322792184352876
+    275: 9.872792184352875
+277:
+  node_pos:
+  - 343.3
+  - 410.5
+  outward_edges:
+    30: 10.372792184352875
+    278: 9.810660153627396
+278:
+  node_pos:
+  - 353.3
+  - 411.35
+  outward_edges:
+    14: 11.643502861261368
+    277: 9.810660153627396
+279:
+  node_pos:
+  - 298.75
+  - 416.70000000000005
+  outward_edges:
+    31: 10.434924215078354
+    280: 9.852081507444382
+280:
+  node_pos:
+  - 297.8
+  - 426.70000000000005
+  outward_edges:
+    279: 9.852081507444382
+    281: 9.852081507444382
+281:
+  node_pos:
+  - 296.85
+  - 436.70000000000005
+  outward_edges:
+    28: 10.643502861261368
+    280: 9.852081507444382
+282:
+  node_pos:
+  - 310.40000000000003
+  - 407.35
+  outward_edges:
+    31: 10.41421353816986
+    283: 9.852081507444382
+283:
+  node_pos:
+  - 320.40000000000003
+  - 408.3
+  outward_edges:
+    30: 12.367766922712327
+    282: 9.852081507444382
+284:
+  node_pos:
+  - 265.40000000000003
+  - 413.65000000000003
+  outward_edges:
+    32: 10.352081507444382
+    285: 9.810660153627396
+285:
+  node_pos:
+  - 264.55
+  - 423.65000000000003
+  outward_edges:
+    284: 9.810660153627396
+    286: 9.810660153627396
+286:
+  node_pos:
+  - 263.7
+  - 433.65000000000003
+  outward_edges:
+    1: 10.452081507444383
+    285: 9.810660153627396
+287:
+  node_pos:
+  - 276.65000000000003
+  - 404.05
+  outward_edges:
+    32: 10.426345568895341
+    288: 9.852081507444382
+288:
+  node_pos:
+  - 286.65000000000003
+  - 405.0
+  outward_edges:
+    31: 13.371320307254791
+    287: 9.852081507444382
+289:
+  node_pos:
+  - 229.65
+  - 410.85
+  outward_edges:
+    87: 10.393502861261368
+    290: 9.78137083053589
+290:
+  node_pos:
+  - 228.8
+  - 420.85
+  outward_edges:
+    289: 9.78137083053589
+    291: 9.810660153627396
+291:
+  node_pos:
+  - 227.95000000000002
+  - 430.85
+  outward_edges:
+    77: 10.089949476718903
+    290: 9.810660153627396
+292:
+  node_pos:
+  - 241.45000000000002
+  - 401.05
+  outward_edges:
+    87: 10.75771639943123
+    293: 9.789949476718903
+293:
+  node_pos:
+  - 251.45
+  - 401.85
+  outward_edges:
+    32: 14.72634556889534
+    292: 9.789949476718903
+294:
+  node_pos:
+  - 401.05
+  - 380.05
+  outward_edges:
+    15: 10.352081507444382
+    295: 9.789949476718903
+295:
+  node_pos:
+  - 400.25
+  - 390.05
+  outward_edges:
+    294: 9.789949476718903
+    296: 9.810660153627396
+296:
+  node_pos:
+  - 399.40000000000003
+  - 400.05
+  outward_edges:
+    13: 14.87634556889534
+    295: 9.810660153627396
+297:
+  node_pos:
+  - 368.05
+  - 377.05
+  outward_edges:
+    2: 10.331370830535889
+    298: 9.810660153627396
+298:
+  node_pos:
+  - 367.20000000000005
+  - 387.05
+  outward_edges:
+    297: 9.810660153627396
+    299: 9.739949476718904
+299:
+  node_pos:
+  - 366.40000000000003
+  - 397.05
+  outward_edges:
+    14: 15.297056245803834
+    298: 9.739949476718904
+300:
+  node_pos:
+  - 379.45000000000005
+  - 367.45000000000005
+  outward_edges:
+    2: 10.372792184352875
+    301: 9.831370830535889
+301:
+  node_pos:
+  - 389.45000000000005
+  - 368.35
+  outward_edges:
+    15: 12.405634891986848
+    300: 9.831370830535889
+302:
+  node_pos:
+  - 336.35
+  - 374.15000000000003
+  outward_edges:
+    52: 10.372792184352875
+    303: 9.872792184352875
+303:
+  node_pos:
+  - 335.3
+  - 384.15000000000003
+  outward_edges:
+    302: 9.872792184352875
+    304: 9.872792184352875
+304:
+  node_pos:
+  - 334.3
+  - 394.15000000000003
+  outward_edges:
+    30: 15.471320307254793
+    303: 9.872792184352875
+305:
+  node_pos:
+  - 347.8
+  - 364.6
+  outward_edges:
+    52: 10.293502861261368
+    306: 9.852081507444382
+306:
+  node_pos:
+  - 357.8
+  - 365.55
+  outward_edges:
+    2: 10.922792184352875
+    305: 9.852081507444382
+307:
+  node_pos:
+  - 303.15000000000003
+  - 371.05
+  outward_edges:
+    16: 10.393502861261368
+    308: 9.872792184352875
+308:
+  node_pos:
+  - 302.15000000000003
+  - 381.05
+  outward_edges:
+    307: 9.872792184352875
+    309: 9.852081507444382
+309:
+  node_pos:
+  - 301.20000000000005
+  - 391.05
+  outward_edges:
+    31: 15.209188276529312
+    308: 9.852081507444382
+310:
+  node_pos:
+  - 314.65000000000003
+  - 361.55
+  outward_edges:
+    16: 10.434924215078354
+    311: 9.852081507444382
+311:
+  node_pos:
+  - 324.65000000000003
+  - 362.5
+  outward_edges:
+    52: 12.809188276529312
+    310: 9.852081507444382
+312:
+  node_pos:
+  - 269.25
+  - 367.70000000000005
+  outward_edges:
+    88: 10.621320307254791
+    313: 9.760660153627397
+313:
+  node_pos:
+  - 268.40000000000003
+  - 377.70000000000005
+  outward_edges:
+    312: 9.760660153627397
+    314: 9.810660153627396
+314:
+  node_pos:
+  - 267.55
+  - 387.70000000000005
+  outward_edges:
+    32: 15.447056245803834
+    313: 9.810660153627396
+315:
+  node_pos:
+  - 281.6
+  - 358.45000000000005
+  outward_edges:
+    88: 10.393502861261368
+    316: 9.852081507444382
+316:
+  node_pos:
+  - 291.6
+  - 359.40000000000003
+  outward_edges:
+    16: 12.538477599620819
+    315: 9.852081507444382
+317:
+  node_pos:
+  - 434.3
+  - 345.05
+  outward_edges:
+    318: 9.852081507444382
+318:
+  node_pos:
+  - 433.35
+  - 355.05
+  outward_edges:
+    317: 9.852081507444382
+    319: 9.852081507444382
+319:
+  node_pos:
+  - 432.40000000000003
+  - 365.05
+  outward_edges:
+    318: 9.852081507444382
+    322: 15.99827550649643
+320:
+  node_pos:
+  - 428.05
+  - 371.70000000000005
+  outward_edges:
+    321: 9.810660153627396
+321:
+  node_pos:
+  - 418.05
+  - 370.85
+  outward_edges:
+    15: 16.159188276529314
+    320: 9.810660153627396
+322:
+  node_pos:
+  - 434.40000000000003
+  - 376.8
+  outward_edges:
+    319: 15.99827550649643
+    323: 9.739949476718904
+323:
+  node_pos:
+  - 433.65000000000003
+  - 386.8
+  outward_edges:
+    322: 9.739949476718904
+    324: 9.739949476718904
+324:
+  node_pos:
+  - 432.85
+  - 396.8
+  outward_edges:
+    323: 9.739949476718904
+    325: 9.760660153627397
+325:
+  node_pos:
+  - 432.05
+  - 406.8
+  outward_edges:
+    12: 10.622792184352875
+    324: 9.760660153627397
+326:
+  node_pos:
+  - 405.15000000000003
+  - 341.85
+  outward_edges:
+    327: 10.055634891986848
+327:
+  node_pos:
+  - 403.5
+  - 351.70000000000005
+  outward_edges:
+    326: 10.055634891986848
+    328: 9.810660153627396
+328:
+  node_pos:
+  - 402.65000000000003
+  - 361.70000000000005
+  outward_edges:
+    15: 7.548528122901917
+    327: 9.810660153627396
+329:
+  node_pos:
+  - 371.95000000000005
+  - 339.15000000000003
+  outward_edges:
+    330: 10.034924215078355
+330:
+  node_pos:
+  - 370.35
+  - 349.05
+  outward_edges:
+    2: 17.429898953437807
+    329: 10.034924215078355
+331:
+  node_pos:
+  - 340.5
+  - 336.75
+  outward_edges:
+    332: 10.014213538169862
+332:
+  node_pos:
+  - 339.0
+  - 346.70000000000005
+  outward_edges:
+    52: 17.13345233798027
+    331: 10.014213538169862
+333:
+  node_pos:
+  - 305.85
+  - 341.8
+  outward_edges:
+    17: 10.455634891986847
+    334: 9.78137083053589
+334:
+  node_pos:
+  - 304.95000000000005
+  - 351.8
+  outward_edges:
+    16: 8.489949476718904
+    333: 9.78137083053589
+335:
+  node_pos:
+  - 272.35
+  - 338.55
+  outward_edges:
+    18: 10.310660153627396
+    336: 9.789949476718903
+336:
+  node_pos:
+  - 271.55
+  - 348.55
+  outward_edges:
+    88: 8.552081507444383
+    335: 9.789949476718903
+337:
+  node_pos:
+  - 283.65000000000003
+  - 328.90000000000003
+  outward_edges:
+    18: 10.434924215078354
+    338: 9.872792184352875
+338:
+  node_pos:
+  - 293.65000000000003
+  - 329.90000000000003
+  outward_edges:
+    17: 12.37634556889534
+    337: 9.872792184352875
+339:
+  node_pos:
+  - 253.10000000000002
+  - 326.05
+  outward_edges:
+    78: 10.331370830535889
+    340: 9.831370830535889
+340:
+  node_pos:
+  - 263.1
+  - 326.95000000000005
+  outward_edges:
+    18: 9.893502861261368
+    339: 9.831370830535889
+341:
+  node_pos:
+  - 275.55
+  - 299.3
+  outward_edges:
+    29: 10.289949476718903
+    342: 9.76923879981041
+342:
+  node_pos:
+  - 274.8
+  - 309.3
+  outward_edges:
+    341: 9.76923879981041
+    343: 9.76923879981041
+343:
+  node_pos:
+  - 274.05
+  - 319.3
+  outward_edges:
+    18: 8.439949476718903
+    342: 9.76923879981041
+344:
+  node_pos:
+  - 286.7
+  - 289.3
+  outward_edges:
+    29: 10.260660153627397
+    345: 9.657106769084931
+345:
+  node_pos:
+  - 296.7
+  - 289.85
+  outward_edges:
+    344: 9.657106769084931
+    346: 9.70710676908493
+346:
+  node_pos:
+  - 306.70000000000005
+  - 290.45
+  outward_edges:
+    345: 9.70710676908493
+    346: 6.131370830535889
+347:
+  node_pos:
+  - 239.70000000000002
+  - 296.65000000000003
+  outward_edges:
+    99: 10.517766922712326
+    348: 9.91421353816986
+348:
+  node_pos:
+  - 238.60000000000002
+  - 306.65000000000003
+  outward_edges:
+    347: 9.91421353816986
+    349: 9.91421353816986
+349:
+  node_pos:
+  - 237.5
+  - 316.65000000000003
+  outward_edges:
+    348: 9.91421353816986
+    350: 25.547665876150134
+350:
+  node_pos:
+  - 235.60000000000002
+  - 336.65000000000003
+  outward_edges:
+    349: 25.547665876150134
+    351: 9.760660153627397
+351:
+  node_pos:
+  - 234.8
+  - 346.65000000000003
+  outward_edges:
+    350: 9.760660153627397
+    352: 9.760660153627397
+352:
+  node_pos:
+  - 233.95000000000002
+  - 356.65000000000003
+  outward_edges:
+    351: 9.760660153627397
+    353: 9.76923879981041
+353:
+  node_pos:
+  - 233.20000000000002
+  - 366.65000000000003
+  outward_edges:
+    352: 9.76923879981041
+    354: 9.789949476718903
+354:
+  node_pos:
+  - 232.4
+  - 376.65000000000003
+  outward_edges:
+    353: 9.789949476718903
+    355: 9.789949476718903
+355:
+  node_pos:
+  - 231.60000000000002
+  - 386.65000000000003
+  outward_edges:
+    87: 13.522792184352875
+    354: 9.789949476718903
+356:
+  node_pos:
+  - 251.7
+  - 286.90000000000003
+  outward_edges:
+    99: 10.479898953437806
+    357: 9.76923879981041
+357:
+  node_pos:
+  - 261.7
+  - 287.65000000000003
+  outward_edges:
+    29: 14.426345568895341
+    356: 9.76923879981041
+358:
+  node_pos:
+  - 278.05
+  - 259.95
+  outward_edges:
+    19: 10.26923879981041
+    359: 9.677817445993425
+359:
+  node_pos:
+  - 277.45
+  - 269.95
+  outward_edges:
+    358: 9.677817445993425
+    360: 9.698528122901918
+360:
+  node_pos:
+  - 276.8
+  - 279.95
+  outward_edges:
+    29: 8.536396092176437
+    359: 9.698528122901918
+361:
+  node_pos:
+  - 289.15000000000003
+  - 249.90000000000003
+  outward_edges:
+    19: 10.160660153627397
+    362: 9.70710676908493
+362:
+  node_pos:
+  - 299.15000000000003
+  - 250.5
+  outward_edges:
+    361: 9.70710676908493
+    363: 9.627817445993424
+363:
+  node_pos:
+  - 309.15000000000003
+  - 251.05
+  outward_edges:
+    362: 9.627817445993424
+    363: 7.659188276529313
+364:
+  node_pos:
+  - 245.4
+  - 257.55
+  outward_edges:
+    89: 11.242640614509583
+    365: 10.411269783973694
+365:
+  node_pos:
+  - 242.95000000000002
+  - 267.55
+  outward_edges:
+    364: 10.411269783973694
+    366: 10.059188276529312
+366:
+  node_pos:
+  - 241.45000000000002
+  - 277.55
+  outward_edges:
+    99: 8.460660153627396
+    365: 10.059188276529312
+367:
+  node_pos:
+  - 259.3
+  - 248.2
+  outward_edges:
+    89: 10.405634891986848
+    368: 9.70710676908493
+368:
+  node_pos:
+  - 269.3
+  - 248.8
+  outward_edges:
+    19: 9.098528122901916
+    367: 9.70710676908493
+369:
+  node_pos:
+  - 357.90000000000003
+  - 213.4
+  outward_edges:
+    27: 10.198528122901918
+    370: 9.615685415267945
+370:
+  node_pos:
+  - 367.90000000000003
+  - 213.85000000000002
+  outward_edges:
+    90: 12.277817445993424
+    369: 9.615685415267945
+371:
+  node_pos:
+  - 324.35
+  - 211.9
+  outward_edges:
+    49: 10.21923879981041
+    372: 9.594974738359452
+372:
+  node_pos:
+  - 334.35
+  - 212.35000000000002
+  outward_edges:
+    27: 12.810660153627396
+    371: 9.594974738359452
+373:
+  node_pos:
+  - 280.7
+  - 220.55
+  outward_edges:
+    20: 10.177817445993425
+    374: 9.727817445993423
+374:
+  node_pos:
+  - 280.05
+  - 230.55
+  outward_edges:
+    373: 9.727817445993423
+    375: 9.677817445993425
+375:
+  node_pos:
+  - 279.40000000000003
+  - 240.55
+  outward_edges:
+    19: 8.515685415267944
+    374: 9.677817445993425
+376:
+  node_pos:
+  - 291.05
+  - 210.35000000000002
+  outward_edges:
+    20: 9.648528122901917
+    377: 9.586396092176438
+377:
+  node_pos:
+  - 301.05
+  - 210.8
+  outward_edges:
+    49: 12.610660153627396
+    376: 9.586396092176438
+378:
+  node_pos:
+  - 255.8
+  - 219.20000000000002
+  outward_edges:
+    79: 10.68345233798027
+    379: 10.473401814699173
+379:
+  node_pos:
+  - 253.2
+  - 229.20000000000002
+  outward_edges:
+    378: 10.473401814699173
+    380: 10.535533845424652
+380:
+  node_pos:
+  - 250.45
+  - 239.20000000000002
+  outward_edges:
+    89: 8.08345233798027
+    379: 10.535533845424652
+381:
+  node_pos:
+  - 268.40000000000003
+  - 209.25
+  outward_edges:
+    20: 12.510660153627397
+    79: 10.198528122901918
+382:
+  node_pos:
+  - 414.6
+  - 197.9
+  outward_edges:
+    70: 10.227817445993423
+    383: 9.627817445993424
+383:
+  node_pos:
+  - 414.05
+  - 207.9
+  outward_edges:
+    382: 9.627817445993424
+    387: 16.942030984163285
+384:
+  node_pos:
+  - 411.05
+  - 215.70000000000002
+  outward_edges:
+    385: 9.594974738359452
+385:
+  node_pos:
+  - 401.05
+  - 215.3
+  outward_edges:
+    384: 9.594974738359452
+    386: 9.644974738359451
+386:
+  node_pos:
+  - 391.05
+  - 214.85000000000002
+  outward_edges:
+    90: 10.26923879981041
+    385: 9.644974738359451
+387:
+  node_pos:
+  - 420.95000000000005
+  - 216.10000000000002
+  outward_edges:
+    383: 16.942030984163285
+    388: 9.594974738359452
+388:
+  node_pos:
+  - 430.95000000000005
+  - 216.5
+  outward_edges:
+    387: 9.594974738359452
+    389: 9.615685415267945
+389:
+  node_pos:
+  - 440.95000000000005
+  - 216.95000000000002
+  outward_edges:
+    388: 9.615685415267945
+390:
+  node_pos:
+  - 447.35
+  - 212.5
+  outward_edges:
+    390: 9.897056245803833
+    391: 9.636396092176438
+391:
+  node_pos:
+  - 447.85
+  - 202.5
+  outward_edges:
+    98: 7.494974738359452
+    390: 9.636396092176438
+392:
+  node_pos:
+  - 424.8
+  - 188.35000000000002
+  outward_edges:
+    70: 9.957716399431229
+    393: 10.266295045614243
+393:
+  node_pos:
+  - 434.8
+  - 190.4
+  outward_edges:
+    98: 14.72903670668602
+    392: 10.266295045614243
+394:
+  node_pos:
+  - 348.70000000000005
+  - 184.95000000000002
+  outward_edges:
+    91: 10.20710676908493
+    395: 9.586396092176438
+395:
+  node_pos:
+  - 348.25
+  - 194.95000000000002
+  outward_edges:
+    394: 9.586396092176438
+    396: 9.665685415267944
+396:
+  node_pos:
+  - 347.75
+  - 204.95000000000002
+  outward_edges:
+    27: 7.0949747383594515
+    395: 9.665685415267944
+397:
+  node_pos:
+  - 359.5
+  - 175.3
+  outward_edges:
+    91: 10.209188276529312
+    398: 10.121320307254791
+398:
+  node_pos:
+  - 369.5
+  - 177.0
+  outward_edges:
+    397: 10.121320307254791
+    399: 10.266295045614243
+399:
+  node_pos:
+  - 379.5
+  - 179.05
+  outward_edges:
+    398: 10.266295045614243
+    402: 22.31040753722191
+400:
+  node_pos:
+  - 381.70000000000005
+  - 187.9
+  outward_edges:
+    401: 9.665685415267944
+401:
+  node_pos:
+  - 381.20000000000005
+  - 197.9
+  outward_edges:
+    90: 15.789949476718903
+    400: 9.665685415267944
+402:
+  node_pos:
+  - 393.6
+  - 181.95000000000002
+  outward_edges:
+    399: 22.31040753722191
+    403: 10.24558436870575
+403:
+  node_pos:
+  - 403.6
+  - 184.0
+  outward_edges:
+    70: 12.518376553058625
+    402: 10.24558436870575
+404:
+  node_pos:
+  - 315.15000000000003
+  - 183.35000000000002
+  outward_edges:
+    67: 10.20710676908493
+    405: 9.586396092176438
+405:
+  node_pos:
+  - 314.70000000000005
+  - 193.35000000000002
+  outward_edges:
+    404: 9.586396092176438
+    406: 9.636396092176438
+406:
+  node_pos:
+  - 314.20000000000005
+  - 203.35000000000002
+  outward_edges:
+    49: 7.224264061450959
+    405: 9.636396092176438
+407:
+  node_pos:
+  - 325.90000000000003
+  - 172.85000000000002
+  outward_edges:
+    51: 15.06923879981041
+    67: 9.827817445993425
+408:
+  node_pos:
+  - 282.6
+  - 181.25
+  outward_edges:
+    41: 10.198528122901918
+    409: 9.657106769084931
+409:
+  node_pos:
+  - 282.05
+  - 191.25
+  outward_edges:
+    408: 9.657106769084931
+    410: 9.686396092176437
+410:
+  node_pos:
+  - 281.5
+  - 201.25
+  outward_edges:
+    20: 8.344974738359452
+    409: 9.686396092176437
+411:
+  node_pos:
+  - 293.5
+  - 171.15
+  outward_edges:
+    41: 10.227817445993423
+    412: 9.586396092176438
+412:
+  node_pos:
+  - 303.5
+  - 171.65
+  outward_edges:
+    67: 12.122792184352875
+    411: 9.586396092176438
+413:
+  node_pos:
+  - 259.3
+  - 179.65
+  outward_edges:
+    69: 10.364213538169862
+    414: 9.748528122901917
+414:
+  node_pos:
+  - 258.6
+  - 189.65
+  outward_edges:
+    413: 9.748528122901917
+    415: 9.66923879981041
+415:
+  node_pos:
+  - 257.95
+  - 199.65
+  outward_edges:
+    79: 8.848528122901916
+    414: 9.66923879981041
+416:
+  node_pos:
+  - 271.15000000000003
+  - 170.0
+  outward_edges:
+    41: 11.56923879981041
+    69: 10.579898953437805
+417:
+  node_pos:
+  - 293.1
+  - 160.85000000000002
+  outward_edges:
+    71: 10.028427076339723
+    418: 10.287005722522736
+418:
+  node_pos:
+  - 303.1
+  - 163.0
+  outward_edges:
+    417: 10.287005722522736
+    419: 10.287005722522736
+419:
+  node_pos:
+  - 313.1
+  - 165.10000000000002
+  outward_edges:
+    418: 10.287005722522736
+    420: 21.156854152679443
+420:
+  node_pos:
+  - 333.1
+  - 169.3
+  outward_edges:
+    61: 14.061879414319993
+    419: 21.156854152679443
+421:
+  node_pos:
+  - 265.45
+  - 155.05
+  outward_edges:
+    69: 16.232590091228484
+    422: 10.928427076339723
+422:
+  node_pos:
+  - 276.05
+  - 157.20000000000002
+  outward_edges:
+    71: 7.937005722522736
+    421: 10.928427076339723
+423:
+  node_pos:
+  - 315.06268310546875
+  - 477.9519348144531
+  outward_edges:
+    239: 13.6274443044847
+    424: 7.761135935980155
+424:
+  node_pos:
+  - 312.3125
+  - 485.1031799316406
+  outward_edges:
+    423: 7.761135935980155
diff --git a/output_yaml/connected_graph_low_level.yaml b/output_yaml/connected_graph_low_level.yaml
new file mode 100644
index 0000000..b622123
--- /dev/null
+++ b/output_yaml/connected_graph_low_level.yaml
@@ -0,0 +1,710 @@
+0:
+  node_pos:
+  - 394.8
+  - 456.1
+  outward_edges:
+    13: 41.99974738359452
+    40: 33.51837655305862
+    66: 33.65979790687561
+    85: 42.60832602977753
+1:
+  node_pos:
+  - 262.8
+  - 444.3
+  outward_edges:
+    28: 33.69619399905205
+    32: 42.049747383594514
+    77: 36.09619399905205
+    86: 42.86543279886246
+2:
+  node_pos:
+  - 368.90000000000003
+  - 366.5
+  outward_edges:
+    14: 46.85330076813698
+    15: 33.692640614509585
+    52: 32.1512192606926
+3:
+  node_pos:
+  - 407.40000000000003
+  - 628.1500000000001
+  outward_edges: {}
+4:
+  node_pos:
+  - 340.05
+  - 622.0
+  outward_edges:
+    7: 55.46248904466629
+    42: 237.84589756131174
+    93: 24.224011445045473
+5:
+  node_pos:
+  - 241.5
+  - 586.1
+  outward_edges:
+    42: 6.91923879981041
+    54: 8.156244522333145
+6:
+  node_pos:
+  - 218.0
+  - 576.9
+  outward_edges:
+    21: 17.271320307254793
+    65: 168.98473217487336
+    69: 1308.6000000000001
+7:
+  node_pos:
+  - 345.3
+  - 568.1
+  outward_edges:
+    4: 55.46248904466629
+    34: 13.924873691797258
+    74: 38.91352979838848
+8:
+  node_pos:
+  - 363.20000000000005
+  - 530.65
+  outward_edges:
+    9: 16.90538227558136
+    24: 3.589949476718903
+9:
+  node_pos:
+  - 350.55
+  - 525.8000000000001
+  outward_edges:
+    8: 16.90538227558136
+    84: 7.502691137790681
+    97: 13.035533845424652
+10:
+  node_pos:
+  - 347.75
+  - 500.90000000000003
+  outward_edges:
+    38: 8.716295045614244
+    76: 3.847056245803833
+11:
+  node_pos:
+  - 328.98284912109375
+  - 449.8285217285156
+  outward_edges:
+    28: 32.211685752608886
+    30: 41.31543279886246
+    40: 32.211877859025
+12:
+  node_pos:
+  - 431.1
+  - 417.6
+  outward_edges:
+    13: 33.37695519924164
+    66: 41.99619399905205
+    103: 47.7721084445715
+13:
+  node_pos:
+  - 398.20000000000005
+  - 415.0
+  outward_edges:
+    0: 41.99974738359452
+    12: 33.37695519924164
+    14: 33.842640614509584
+    15: 46.453300768136984
+14:
+  node_pos:
+  - 365.1
+  - 412.35
+  outward_edges:
+    2: 46.85330076813698
+    13: 33.842640614509584
+    30: 32.90979790687561
+    40: 41.62903670668602
+15:
+  node_pos:
+  - 401.95000000000005
+  - 369.5
+  outward_edges:
+    2: 33.692640614509585
+    13: 46.453300768136984
+    103: 31.85832602977753
+16:
+  node_pos:
+  - 304.15000000000003
+  - 360.5
+  outward_edges:
+    17: 29.859797906875613
+    31: 46.9518288910389
+    52: 34.17903670668602
+    88: 33.86690467596054
+17:
+  node_pos:
+  - 306.1
+  - 331.3
+  outward_edges:
+    16: 29.859797906875613
+    18: 33.816904675960544
+18:
+  node_pos:
+  - 273.15000000000003
+  - 328.0
+  outward_edges:
+    17: 33.816904675960544
+    29: 39.92192993760109
+    78: 31.139087229967117
+    88: 29.735533845424655
+19:
+  node_pos:
+  - 278.75
+  - 249.40000000000003
+  outward_edges:
+    20: 39.80269113779068
+    29: 39.86482316851616
+    89: 30.352691137790682
+20:
+  node_pos:
+  - 281.15000000000003
+  - 210.05
+  outward_edges:
+    19: 39.80269113779068
+    41: 39.599137753248215
+    49: 32.98700572252274
+    79: 23.279898953437808
+21:
+  node_pos:
+  - 235.15
+  - 578.5
+  outward_edges:
+    6: 17.271320307254793
+    37: 50.37878409028053
+    54: 2.332842707633972
+24:
+  node_pos:
+  - 367.0
+  - 531.5500000000001
+  outward_edges:
+    8: 3.589949476718903
+    58: 134.71122596263885
+    80: 51.231118214130404
+25:
+  node_pos:
+  - 243.55
+  - 531.15
+  outward_edges:
+    37: 7.7142135381698616
+    96: 20.56984843015671
+26:
+  node_pos:
+  - 325.1
+  - 492.05
+  outward_edges:
+    28: 110.89066350460052
+    38: 39.95599190592766
+    39: 34.166904675960545
+27:
+  node_pos:
+  - 347.40000000000003
+  - 212.5
+  outward_edges:
+    49: 33.81629504561425
+    90: 33.28345233798027
+    91: 38.26629504561424
+28:
+  node_pos:
+  - 295.75
+  - 447.45000000000005
+  outward_edges:
+    1: 33.69619399905205
+    11: 32.211685752608886
+    26: 110.89066350460052
+    31: 41.606854152679446
+    39: 42.64472212195397
+29:
+  node_pos:
+  - 276.2
+  - 288.8
+  outward_edges:
+    18: 39.92192993760109
+    19: 39.86482316851616
+    99: 35.82903670668602
+30:
+  node_pos:
+  - 332.75
+  - 409.55
+  outward_edges:
+    11: 41.31543279886246
+    14: 32.90979790687561
+    31: 33.71690467596054
+    52: 47.23467159867287
+31:
+  node_pos:
+  - 299.90000000000003
+  - 406.20000000000005
+  outward_edges:
+    16: 46.9518288910389
+    28: 41.606854152679446
+    30: 33.71690467596054
+    32: 34.782590091228485
+32:
+  node_pos:
+  - 266.2
+  - 403.15000000000003
+  outward_edges:
+    1: 42.049747383594514
+    31: 34.782590091228485
+    87: 36.33614347577095
+    88: 47.31396092176438
+33:
+  node_pos:
+  - 416.0
+  - 593.35
+  outward_edges: {}
+34:
+  node_pos:
+  - 359.0
+  - 570.1
+  outward_edges:
+    7: 13.924873691797258
+    46: 56.6026170283556
+37:
+  node_pos:
+  - 235.8
+  - 532.1
+  outward_edges:
+    21: 50.37878409028053
+    25: 7.7142135381698616
+38:
+  node_pos:
+  - 356.15000000000003
+  - 498.95000000000005
+  outward_edges:
+    10: 8.716295045614244
+    26: 39.95599190592766
+    102: 183.0484843015671
+39:
+  node_pos:
+  - 291.85
+  - 489.0
+  outward_edges:
+    26: 34.166904675960545
+    28: 42.64472212195397
+    86: 33.92903670668602
+40:
+  node_pos:
+  - 361.85
+  - 453.5
+  outward_edges:
+    0: 33.51837655305862
+    11: 32.211877859025
+    14: 41.62903670668602
+    72: 43.07045806050301
+41:
+  node_pos:
+  - 283.0
+  - 170.75
+  outward_edges:
+    20: 39.599137753248215
+    67: 33.099137753248215
+    69: 22.71984843015671
+    71: 10.482842707633973
+42:
+  node_pos:
+  - 240.65
+  - 593.3000000000001
+  outward_edges:
+    4: 237.84589756131174
+    5: 6.91923879981041
+    64: 21.9911687374115
+43:
+  node_pos:
+  - 361.20000000000005
+  - 533.0500000000001
+  outward_edges:
+    74: 10.70710676908493
+    83: 14.811269783973694
+    94: 52.82056245803833
+44:
+  node_pos:
+  - 285.8
+  - 507.80000000000007
+  outward_edges:
+    48: 14.466295045614244
+    59: 5.210660153627396
+    100: 25.50269113779068
+45:
+  node_pos:
+  - 444.25
+  - 576.9
+  outward_edges:
+    55: 7.11923879981041
+    62: 5.807106769084931
+46:
+  node_pos:
+  - 405.95000000000005
+  - 573.4
+  outward_edges:
+    34: 56.6026170283556
+    56: 18.03198046088219
+    94: 27.294112491607667
+47:
+  node_pos:
+  - 448.05
+  - 549.45
+  outward_edges:
+    75: 39.6046244263649
+48:
+  node_pos:
+  - 276.85
+  - 501.45000000000005
+  outward_edges:
+    44: 14.466295045614244
+    59: 10.288477599620819
+49:
+  node_pos:
+  - 313.85
+  - 211.0
+  outward_edges:
+    20: 32.98700572252274
+    27: 33.81629504561425
+    67: 38.366295045614244
+51:
+  node_pos:
+  - 341.20000000000005
+  - 173.5
+  outward_edges:
+    67: 25.46776692271233
+    71: 68.2439642727375
+52:
+  node_pos:
+  - 337.40000000000003
+  - 363.65000000000003
+  outward_edges:
+    2: 32.1512192606926
+    16: 34.17903670668602
+    30: 47.23467159867287
+54:
+  node_pos:
+  - 237.9
+  - 579.0500000000001
+  outward_edges:
+    5: 8.156244522333145
+    21: 2.332842707633972
+55:
+  node_pos:
+  - 436.95000000000005
+  - 577.3000000000001
+  outward_edges:
+    45: 7.11923879981041
+    56: 13.866295045614244
+    62: 11.322792184352876
+56:
+  node_pos:
+  - 423.45000000000005
+  - 576.1
+  outward_edges:
+    46: 18.03198046088219
+    55: 13.866295045614244
+58:
+  node_pos:
+  - 432.75
+  - 548.65
+  outward_edges:
+    24: 134.71122596263885
+    62: 36.89472212195397
+59:
+  node_pos:
+  - 287.05
+  - 502.45000000000005
+  outward_edges:
+    44: 5.210660153627396
+    48: 10.288477599620819
+    63: 55.75954529047013
+60:
+  node_pos:
+  - 246.8
+  - 498.55
+  outward_edges:
+    65: 17.182337474822997
+    96: 64.93944424390793
+61:
+  node_pos:
+  - 343.75
+  - 173.10000000000002
+  outward_edges:
+    91: 5.493502861261368
+62:
+  node_pos:
+  - 444.15000000000003
+  - 570.75
+  outward_edges:
+    45: 5.807106769084931
+    55: 11.322792184352876
+    58: 36.89472212195397
+63:
+  node_pos:
+  - 334.90000000000003
+  - 527.1
+  outward_edges:
+    59: 55.75954529047013
+    92: 41.61248904466629
+    97: 6.239949476718903
+64:
+  node_pos:
+  - 253.3
+  - 602.25
+  outward_edges:
+    42: 21.9911687374115
+    93: 131.55519023537636
+65:
+  node_pos:
+  - 232.55
+  - 490.6
+  outward_edges:
+    6: 168.98473217487336
+    60: 17.182337474822997
+    86: 28.749494767189027
+66:
+  node_pos:
+  - 427.90000000000003
+  - 458.8
+  outward_edges:
+    0: 33.65979790687561
+    12: 41.99619399905205
+67:
+  node_pos:
+  - 315.75
+  - 172.85000000000002
+  outward_edges:
+    41: 33.099137753248215
+    49: 38.366295045614244
+    51: 25.46776692271233
+69:
+  node_pos:
+  - 260.65000000000003
+  - 169.20000000000002
+  outward_edges:
+    6: 1308.6000000000001
+    41: 22.71984843015671
+    71: 36.367261689901355
+    79: 40.36335129141808
+70:
+  node_pos:
+  - 415.25
+  - 187.35000000000002
+  outward_edges:
+    91: 105.20315254926682
+    98: 36.11873356699944
+71:
+  node_pos:
+  - 283.45
+  - 159.8
+  outward_edges:
+    41: 10.482842707633973
+    51: 68.2439642727375
+    69: 36.367261689901355
+72:
+  node_pos:
+  - 358.45000000000005
+  - 495.6
+  outward_edges:
+    40: 43.07045806050301
+    85: 33.80477264523506
+74:
+  node_pos:
+  - 350.15000000000003
+  - 533.2
+  outward_edges:
+    7: 38.91352979838848
+    43: 10.70710676908493
+    83: 2.5071067690849307
+75:
+  node_pos:
+  - 434.6
+  - 519.35
+  outward_edges:
+    47: 39.6046244263649
+    84: 96.33832938075066
+76:
+  node_pos:
+  - 345.05
+  - 498.20000000000005
+  outward_edges:
+    10: 3.847056245803833
+    84: 13.481549337506294
+77:
+  node_pos:
+  - 227.5
+  - 441.15000000000003
+  outward_edges:
+    1: 36.09619399905205
+    87: 41.729036706686024
+78:
+  node_pos:
+  - 242.60000000000002
+  - 325.3
+  outward_edges:
+    18: 31.139087229967117
+79:
+  node_pos:
+  - 257.90000000000003
+  - 208.75
+  outward_edges:
+    20: 23.279898953437808
+    69: 40.36335129141808
+    89: 41.60721116662026
+80:
+  node_pos:
+  - 416.95000000000005
+  - 536.1
+  outward_edges:
+    24: 51.231118214130404
+81:
+  node_pos:
+  - 342.35
+  - 567.25
+  outward_edges:
+    92: 11.334924215078354
+83:
+  node_pos:
+  - 350.25
+  - 530.6
+  outward_edges:
+    43: 14.811269783973694
+    74: 2.5071067690849307
+84:
+  node_pos:
+  - 347.90000000000003
+  - 518.8000000000001
+  outward_edges:
+    9: 7.502691137790681
+    75: 96.33832938075066
+    76: 13.481549337506294
+85:
+  node_pos:
+  - 391.45000000000005
+  - 497.90000000000003
+  outward_edges:
+    0: 42.60832602977753
+    72: 33.80477264523506
+86:
+  node_pos:
+  - 258.95
+  - 486.1
+  outward_edges:
+    1: 42.86543279886246
+    39: 33.92903670668602
+    65: 28.749494767189027
+87:
+  node_pos:
+  - 230.9
+  - 400.35
+  outward_edges:
+    32: 36.33614347577095
+    77: 41.729036706686024
+    99: 123.26848095059395
+88:
+  node_pos:
+  - 271.1
+  - 357.25
+  outward_edges:
+    16: 33.86690467596054
+    18: 29.735533845424655
+    32: 47.31396092176438
+89:
+  node_pos:
+  - 248.75
+  - 247.10000000000002
+  outward_edges:
+    19: 30.352691137790682
+    79: 41.60721116662026
+    99: 41.830865597724916
+90:
+  node_pos:
+  - 380.5
+  - 214.0
+  outward_edges:
+    27: 33.28345233798027
+91:
+  node_pos:
+  - 349.35
+  - 174.45000000000002
+  outward_edges:
+    27: 38.26629504561424
+    61: 5.493502861261368
+    70: 105.20315254926682
+92:
+  node_pos:
+  - 330.90000000000003
+  - 567.0500000000001
+  outward_edges:
+    63: 41.61248904466629
+    81: 11.334924215078354
+93:
+  node_pos:
+  - 316.95000000000005
+  - 618.75
+  outward_edges:
+    4: 24.224011445045473
+    64: 131.55519023537636
+94:
+  node_pos:
+  - 408.45000000000005
+  - 546.5
+  outward_edges:
+    43: 52.82056245803833
+    46: 27.294112491607667
+96:
+  node_pos:
+  - 263.7
+  - 533.15
+  outward_edges:
+    25: 20.56984843015671
+    60: 64.93944424390793
+    100: 47.37314919829369
+97:
+  node_pos:
+  - 341.35
+  - 527.7
+  outward_edges:
+    9: 13.035533845424652
+    63: 6.239949476718903
+98:
+  node_pos:
+  - 448.25
+  - 194.60000000000002
+  outward_edges:
+    70: 36.11873356699944
+99:
+  node_pos:
+  - 241.25
+  - 286.2
+  outward_edges:
+    29: 35.82903670668602
+    87: 123.26848095059395
+    89: 41.830865597724916
+100:
+  node_pos:
+  - 284.2564697265625
+  - 532.891845703125
+  outward_edges:
+    44: 25.50269113779068
+    96: 47.37314919829369
+101:
+  node_pos:
+  - 265.7926330566406
+  - 500.62896728515625
+  outward_edges: {}
+102:
+  node_pos:
+  - 425.0286865234375
+  - 500.0166931152344
+  outward_edges:
+    38: 183.0484843015671
+103:
+  node_pos:
+  - 431.6510009765625
+  - 372.10205078125
+  outward_edges:
+    12: 47.7721084445715
+    15: 31.85832602977753
+104:
+  node_pos:
+  - 400.8990478515625
+  - 387.8114013671875
+  outward_edges: {}
diff --git a/output_yaml/edges_edited.yaml b/output_yaml/edges_edited.yaml
new file mode 100644
index 0000000..78c3cc7
--- /dev/null
+++ b/output_yaml/edges_edited.yaml
@@ -0,0 +1,5272 @@
+? !!python/tuple
+- 0
+- 66
+- 101
+: - - 394.8
+    - 456.1
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 0
+- 85
+- 100
+: - - 394.8
+    - 456.1
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 0
+- 228
+- 412
+: - - 394.8
+    - 456.1
+  - - 394.0
+    - 466.65000000000003
+? !!python/tuple
+- 0
+- 231
+- 413
+: - - 394.8
+    - 456.1
+  - - 405.35
+    - 456.95000000000005
+? !!python/tuple
+- 1
+- 28
+- 109
+: - - 262.8
+    - 444.3
+  - - 295.75
+    - 447.45000000000005
+? !!python/tuple
+- 1
+- 86
+- 108
+: - - 262.8
+    - 444.3
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 1
+- 248
+- 432
+: - - 262.8
+    - 444.3
+  - - 261.85
+    - 454.85
+? !!python/tuple
+- 1
+- 251
+- 433
+: - - 262.8
+    - 444.3
+  - - 273.35
+    - 445.25
+? !!python/tuple
+- 2
+- 2
+- 137
+: - - 368.90000000000003
+    - 366.5
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 2
+- 14
+- 127
+: - - 368.90000000000003
+    - 366.5
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 2
+- 15
+- 128
+: - - 368.90000000000003
+    - 366.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 2
+- 297
+- 512
+: - - 368.90000000000003
+    - 366.5
+  - - 368.05
+    - 377.05
+? !!python/tuple
+- 2
+- 300
+- 513
+: - - 368.90000000000003
+    - 366.5
+  - - 379.45000000000005
+    - 367.45000000000005
+? !!python/tuple
+- 2
+- 330
+- 532
+: - - 368.90000000000003
+    - 366.5
+  - - 370.35
+    - 349.05
+? !!python/tuple
+- 3
+- 3
+- 0
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 3
+- 3
+- 1
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 3
+- 3
+- 180
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 3
+- 3
+- 183
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 5
+- 5
+- 12
+: - - 241.5
+    - 586.1
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 5
+- 5
+- 220
+: - - 241.5
+    - 586.1
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 5
+- 42
+- 11
+: - - 241.5
+    - 586.1
+  - - 240.65
+    - 593.3000000000001
+? !!python/tuple
+- 5
+- 42
+- 219
+: - - 241.5
+    - 586.1
+  - - 240.65
+    - 593.3000000000001
+? !!python/tuple
+- 6
+- 6
+- 16
+: - - 218.0
+    - 576.9
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 6
+- 6
+- 251
+: - - 218.0
+    - 576.9
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 6
+- 21
+- 18
+: - - 218.0
+    - 576.9
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 6
+- 21
+- 230
+: - - 218.0
+    - 576.9
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 7
+- 4
+- 30
+: - - 345.3
+    - 568.1
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 7
+- 34
+- 31
+: - - 345.3
+    - 568.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 7
+- 34
+- 246
+: - - 345.3
+    - 568.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 7
+- 139
+- 245
+: - - 345.3
+    - 568.1
+  - - 344.55
+    - 578.65
+? !!python/tuple
+- 8
+- 24
+- 68
+: - - 363.20000000000005
+    - 530.65
+  - - 367.0
+    - 531.5500000000001
+? !!python/tuple
+- 8
+- 24
+- 308
+: - - 363.20000000000005
+    - 530.65
+  - - 367.0
+    - 531.5500000000001
+? !!python/tuple
+- 9
+- 8
+- 75
+: - - 350.55
+    - 525.8000000000001
+  - - 363.20000000000005
+    - 530.65
+? !!python/tuple
+- 9
+- 8
+- 316
+: - - 350.55
+    - 525.8000000000001
+  - - 363.20000000000005
+    - 530.65
+? !!python/tuple
+- 10
+- 38
+- 87
+: - - 347.75
+    - 500.90000000000003
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 10
+- 38
+- 363
+: - - 347.75
+    - 500.90000000000003
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 11
+- 26
+- 104
+: - - 328.85
+    - 450.6
+  - - 325.1
+    - 492.05
+? !!python/tuple
+- 11
+- 40
+- 105
+: - - 328.85
+    - 450.6
+  - - 362.0938415527344
+    - 453.5181579589844
+? !!python/tuple
+- 11
+- 238
+- 422
+: - - 328.85
+    - 450.6
+  - - 327.90000000000003
+    - 461.1
+? !!python/tuple
+- 11
+- 241
+- 423
+: - - 328.85
+    - 450.6
+  - - 339.40000000000003
+    - 451.55
+? !!python/tuple
+- 12
+- 12
+- 113
+: - - 431.1
+    - 417.6
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 12
+- 66
+- 112
+: - - 431.1
+    - 417.6
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 12
+- 262
+- 457
+: - - 431.1
+    - 417.6
+  - - 441.55
+    - 418.5
+? !!python/tuple
+- 12
+- 325
+- 475
+: - - 431.1
+    - 417.6
+  - - 432.05
+    - 406.8
+? !!python/tuple
+- 13
+- 0
+- 114
+: - - 398.20000000000005
+    - 415.0
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 13
+- 12
+- 115
+: - - 398.20000000000005
+    - 415.0
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 13
+- 15
+- 126
+: - - 398.20000000000005
+    - 415.0
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 13
+- 264
+- 461
+: - - 398.20000000000005
+    - 415.0
+  - - 397.35
+    - 425.5
+? !!python/tuple
+- 13
+- 267
+- 462
+: - - 398.20000000000005
+    - 415.0
+  - - 408.75
+    - 415.90000000000003
+? !!python/tuple
+- 14
+- 13
+- 117
+: - - 365.1
+    - 412.35
+  - - 398.20000000000005
+    - 415.0
+? !!python/tuple
+- 14
+- 40
+- 116
+: - - 365.1
+    - 412.35
+  - - 362.0938415527344
+    - 453.5181579589844
+? !!python/tuple
+- 14
+- 269
+- 466
+: - - 365.1
+    - 412.35
+  - - 364.3
+    - 422.90000000000003
+? !!python/tuple
+- 14
+- 272
+- 467
+: - - 365.1
+    - 412.35
+  - - 375.6
+    - 413.20000000000005
+? !!python/tuple
+- 15
+- 15
+- 135
+: - - 401.95000000000005
+    - 369.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 15
+- 15
+- 136
+: - - 401.95000000000005
+    - 369.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 15
+- 321
+- 507
+: - - 401.95000000000005
+    - 369.5
+  - - 418.05
+    - 370.85
+? !!python/tuple
+- 15
+- 328
+- 520
+: - - 401.95000000000005
+    - 369.5
+  - - 402.65000000000003
+    - 361.70000000000005
+? !!python/tuple
+- 16
+- 31
+- 131
+: - - 304.15000000000003
+    - 360.5
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 16
+- 52
+- 132
+: - - 304.15000000000003
+    - 360.5
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 16
+- 307
+- 522
+: - - 304.15000000000003
+    - 360.5
+  - - 303.15000000000003
+    - 371.05
+? !!python/tuple
+- 16
+- 310
+- 523
+: - - 304.15000000000003
+    - 360.5
+  - - 314.65000000000003
+    - 361.55
+? !!python/tuple
+- 17
+- 16
+- 139
+: - - 306.1
+    - 331.3
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 17
+- 17
+- 140
+: - - 306.1
+    - 331.3
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 17
+- 17
+- 545
+: - - 306.1
+    - 331.3
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 17
+- 333
+- 543
+: - - 306.1
+    - 331.3
+  - - 305.85
+    - 341.8
+? !!python/tuple
+- 18
+- 17
+- 142
+: - - 273.15000000000003
+    - 328.0
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 18
+- 88
+- 141
+: - - 273.15000000000003
+    - 328.0
+  - - 271.1
+    - 357.25
+? !!python/tuple
+- 18
+- 335
+- 547
+: - - 273.15000000000003
+    - 328.0
+  - - 272.35
+    - 338.55
+? !!python/tuple
+- 18
+- 337
+- 548
+: - - 273.15000000000003
+    - 328.0
+  - - 283.65000000000003
+    - 328.90000000000003
+? !!python/tuple
+- 19
+- 19
+- 150
+: - - 278.75
+    - 249.40000000000003
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 19
+- 20
+- 155
+: - - 278.75
+    - 249.40000000000003
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 19
+- 361
+- 578
+: - - 278.75
+    - 249.40000000000003
+  - - 289.15000000000003
+    - 249.90000000000003
+? !!python/tuple
+- 19
+- 375
+- 583
+: - - 278.75
+    - 249.40000000000003
+  - - 279.40000000000003
+    - 240.55
+? !!python/tuple
+- 20
+- 41
+- 168
+: - - 281.15000000000003
+    - 210.05
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 20
+- 49
+- 156
+: - - 281.15000000000003
+    - 210.05
+  - - 313.85
+    - 211.0
+? !!python/tuple
+- 20
+- 376
+- 604
+: - - 281.15000000000003
+    - 210.05
+  - - 291.05
+    - 210.35000000000002
+? !!python/tuple
+- 20
+- 410
+- 612
+: - - 281.15000000000003
+    - 210.05
+  - - 281.5
+    - 201.25
+? !!python/tuple
+- 21
+- 54
+- 14
+: - - 235.15
+    - 578.5
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 21
+- 54
+- 224
+: - - 235.15
+    - 578.5
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 22
+- 58
+- 44
+: - - 428.3
+    - 545.8000000000001
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 22
+- 58
+- 267
+: - - 428.3
+    - 545.8000000000001
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 24
+- 50
+- 73
+: - - 367.0
+    - 531.5500000000001
+  - - 434.95000000000005
+    - 537.45
+? !!python/tuple
+- 24
+- 50
+- 314
+: - - 367.0
+    - 531.5500000000001
+  - - 434.95000000000005
+    - 537.45
+? !!python/tuple
+- 24
+- 80
+- 64
+: - - 367.0
+    - 531.5500000000001
+  - - 416.95000000000005
+    - 536.1
+? !!python/tuple
+- 24
+- 159
+- 303
+: - - 367.0
+    - 531.5500000000001
+  - - 377.5
+    - 532.65
+? !!python/tuple
+- 25
+- 96
+- 65
+: - - 243.55
+    - 531.15
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 25
+- 163
+- 304
+: - - 243.55
+    - 531.15
+  - - 254.05
+    - 532.65
+? !!python/tuple
+- 26
+- 38
+- 92
+: - - 325.1
+    - 492.05
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 26
+- 201
+- 375
+: - - 325.1
+    - 492.05
+  - - 335.6
+    - 493.65000000000003
+? !!python/tuple
+- 27
+- 90
+- 153
+: - - 347.40000000000003
+    - 212.5
+  - - 380.5
+    - 214.0
+? !!python/tuple
+- 27
+- 91
+- 162
+: - - 347.40000000000003
+    - 212.5
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 27
+- 369
+- 597
+: - - 347.40000000000003
+    - 212.5
+  - - 357.90000000000003
+    - 213.4
+? !!python/tuple
+- 27
+- 396
+- 609
+: - - 347.40000000000003
+    - 212.5
+  - - 347.75
+    - 204.95000000000002
+? !!python/tuple
+- 28
+- 11
+- 107
+: - - 295.75
+    - 447.45000000000005
+  - - 328.85
+    - 450.6
+? !!python/tuple
+- 28
+- 39
+- 106
+: - - 295.75
+    - 447.45000000000005
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 28
+- 243
+- 427
+: - - 295.8104248046875
+    - 447.5629577636719
+  - - 294.90000000000003
+    - 457.95000000000005
+? !!python/tuple
+- 28
+- 246
+- 428
+: - - 295.8104248046875
+    - 447.5629577636719
+  - - 306.25
+    - 448.45000000000005
+? !!python/tuple
+- 29
+- 18
+- 145
+: - - 276.2
+    - 288.8
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 29
+- 19
+- 149
+: - - 276.2
+    - 288.8
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 29
+- 29
+- 146
+: - - 276.2
+    - 288.8
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 29
+- 341
+- 562
+: - - 276.2
+    - 288.8
+  - - 275.55
+    - 299.3
+? !!python/tuple
+- 29
+- 344
+- 563
+: - - 276.2
+    - 288.8
+  - - 286.7
+    - 289.3
+? !!python/tuple
+- 30
+- 11
+- 118
+: - - 332.75
+    - 409.55
+  - - 328.85
+    - 450.6
+? !!python/tuple
+- 30
+- 14
+- 119
+: - - 332.75
+    - 409.55
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 30
+- 274
+- 471
+: - - 332.75
+    - 409.55
+  - - 331.75
+    - 420.1
+? !!python/tuple
+- 30
+- 277
+- 472
+: - - 332.75
+    - 409.55
+  - - 343.3
+    - 410.5
+? !!python/tuple
+- 31
+- 28
+- 120
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 295.75
+    - 447.45000000000005
+? !!python/tuple
+- 31
+- 30
+- 121
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 31
+- 279
+- 476
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 298.75
+    - 416.70000000000005
+? !!python/tuple
+- 31
+- 282
+- 477
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 310.40000000000003
+    - 407.35
+? !!python/tuple
+- 32
+- 1
+- 122
+: - - 266.2
+    - 403.15000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 32
+- 31
+- 123
+: - - 266.2
+    - 403.15000000000003
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 32
+- 284
+- 480
+: - - 266.2
+    - 403.15000000000003
+  - - 265.40000000000003
+    - 413.65000000000003
+? !!python/tuple
+- 32
+- 287
+- 481
+: - - 266.2
+    - 403.15000000000003
+  - - 276.65000000000003
+    - 404.05
+? !!python/tuple
+- 33
+- 33
+- 7
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 33
+- 33
+- 9
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 33
+- 33
+- 212
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 33
+- 33
+- 214
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 34
+- 34
+- 27
+: - - 359.0
+    - 570.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 34
+- 34
+- 29
+: - - 359.0
+    - 570.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 34
+- 34
+- 241
+: - - 359.0
+    - 570.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 34
+- 137
+- 244
+: - - 359.0
+    - 570.1
+  - - 368.95000000000005
+    - 570.4
+? !!python/tuple
+- 35
+- 22
+- 47
+: - - 429.8
+    - 540.35
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 35
+- 22
+- 277
+: - - 429.8
+    - 540.35
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 37
+- 21
+- 63
+: - - 235.8
+    - 532.1
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 37
+- 25
+- 66
+: - - 235.8
+    - 532.1
+  - - 243.55
+    - 531.15
+? !!python/tuple
+- 37
+- 25
+- 306
+: - - 235.8
+    - 532.1
+  - - 243.55
+    - 531.15
+? !!python/tuple
+- 37
+- 155
+- 301
+: - - 235.8
+    - 532.1
+  - - 239.4
+    - 541.0
+? !!python/tuple
+- 38
+- 75
+- 98
+: - - 356.15000000000003
+    - 498.95000000000005
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 38
+- 225
+- 372
+: - - 356.15000000000003
+    - 498.95000000000005
+  - - 399.40000000000003
+    - 504.5
+? !!python/tuple
+- 39
+- 26
+- 95
+: - - 291.85
+    - 489.0
+  - - 325.1
+    - 492.05
+? !!python/tuple
+- 39
+- 212
+- 381
+: - - 291.85
+    - 489.0
+  - - 302.3
+    - 490.6
+? !!python/tuple
+- 40
+- 0
+- 103
+: - - 362.0938415527344
+    - 453.5181579589844
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 40
+- 72
+- 102
+: - - 362.0938415527344
+    - 453.5181579589844
+  - - 358.45000000000005
+    - 495.6
+? !!python/tuple
+- 40
+- 233
+- 417
+: - - 362.0938415527344
+    - 453.5181579589844
+  - - 360.90000000000003
+    - 464.0
+? !!python/tuple
+- 40
+- 236
+- 418
+: - - 362.0938415527344
+    - 453.5181579589844
+  - - 372.35
+    - 454.3
+? !!python/tuple
+- 41
+- 67
+- 169
+: - - 283.0
+    - 170.75
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 41
+- 71
+- 172
+: - - 283.0
+    - 170.75
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 41
+- 71
+- 654
+: - - 283.0
+    - 170.75
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 41
+- 411
+- 646
+: - - 283.0
+    - 170.75
+  - - 293.5
+    - 171.15
+? !!python/tuple
+- 42
+- 4
+- 8
+: - - 240.65
+    - 593.3000000000001
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 42
+- 64
+- 6
+: - - 240.65
+    - 593.3000000000001
+  - - 253.3
+    - 602.25
+? !!python/tuple
+- 42
+- 105
+- 213
+: - - 240.65
+    - 593.3000000000001
+  - - 234.05
+    - 602.45
+? !!python/tuple
+- 43
+- 94
+- 61
+: - - 361.20000000000005
+    - 533.0500000000001
+  - - 408.45000000000005
+    - 546.5
+? !!python/tuple
+- 43
+- 151
+- 296
+: - - 361.20000000000005
+    - 533.0500000000001
+  - - 370.6
+    - 542.4
+? !!python/tuple
+- 44
+- 183
+- 344
+: - - 285.8
+    - 507.80000000000007
+  - - 285.35
+    - 518.3000000000001
+? !!python/tuple
+- 45
+- 45
+- 4
+: - - 444.25
+    - 576.9
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 45
+- 45
+- 17
+: - - 444.25
+    - 576.9
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 45
+- 45
+- 229
+: - - 444.25
+    - 576.9
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 46
+- 56
+- 23
+: - - 405.95000000000005
+    - 573.4
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 46
+- 56
+- 235
+: - - 405.95000000000005
+    - 573.4
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 47
+- 47
+- 35
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 36
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 37
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 38
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 39
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 42
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 45
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 260
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 48
+- 44
+- 85
+: - - 276.85
+    - 501.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 48
+- 44
+- 356
+: - - 276.85
+    - 501.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 48
+- 59
+- 86
+: - - 276.85
+    - 501.45000000000005
+  - - 287.05
+    - 502.45000000000005
+? !!python/tuple
+- 48
+- 59
+- 357
+: - - 276.85
+    - 501.45000000000005
+  - - 287.05
+    - 502.45000000000005
+? !!python/tuple
+- 49
+- 27
+- 154
+: - - 313.85
+    - 211.0
+  - - 347.40000000000003
+    - 212.5
+? !!python/tuple
+- 49
+- 67
+- 165
+: - - 313.85
+    - 211.0
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 49
+- 371
+- 600
+: - - 313.85
+    - 211.0
+  - - 324.35
+    - 211.9
+? !!python/tuple
+- 49
+- 406
+- 610
+: - - 313.85
+    - 211.0
+  - - 314.20000000000005
+    - 203.35000000000002
+? !!python/tuple
+- 50
+- 23
+- 53
+: - - 434.95000000000005
+    - 537.45
+  - - 441.0
+    - 538.15
+? !!python/tuple
+- 50
+- 23
+- 284
+: - - 434.95000000000005
+    - 537.45
+  - - 441.0
+    - 538.15
+? !!python/tuple
+- 52
+- 2
+- 130
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 52
+- 30
+- 129
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 52
+- 52
+- 138
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 52
+- 302
+- 517
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 336.35
+    - 374.15000000000003
+? !!python/tuple
+- 52
+- 305
+- 518
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 347.8
+    - 364.6
+? !!python/tuple
+- 53
+- 23
+- 59
+: - - 442.35
+    - 535.35
+  - - 441.0
+    - 538.15
+? !!python/tuple
+- 53
+- 23
+- 291
+: - - 442.35
+    - 535.35
+  - - 441.0
+    - 538.15
+? !!python/tuple
+- 53
+- 47
+- 58
+: - - 442.35
+    - 535.35
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 53
+- 47
+- 290
+: - - 442.35
+    - 535.35
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 54
+- 5
+- 13
+: - - 237.9
+    - 579.0500000000001
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 54
+- 5
+- 221
+: - - 237.9
+    - 579.0500000000001
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 54
+- 54
+- 22
+: - - 237.9
+    - 579.0500000000001
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 54
+- 54
+- 234
+: - - 237.9
+    - 579.0500000000001
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 55
+- 45
+- 19
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 55
+- 45
+- 231
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 55
+- 55
+- 5
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 55
+- 55
+- 15
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 55
+- 55
+- 227
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 55
+- 62
+- 28
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 56
+- 55
+- 21
+: - - 423.45000000000005
+    - 576.1
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 56
+- 55
+- 233
+: - - 423.45000000000005
+    - 576.1
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 56
+- 56
+- 20
+: - - 423.45000000000005
+    - 576.1
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 56
+- 56
+- 232
+: - - 423.45000000000005
+    - 576.1
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 57
+- 46
+- 25
+: - - 391.3
+    - 573.1
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 57
+- 46
+- 237
+: - - 391.3
+    - 573.1
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 57
+- 57
+- 24
+: - - 391.3
+    - 573.1
+  - - 391.3
+    - 573.1
+? !!python/tuple
+- 57
+- 57
+- 236
+: - - 391.3
+    - 573.1
+  - - 391.3
+    - 573.1
+? !!python/tuple
+- 58
+- 58
+- 40
+: - - 432.75
+    - 548.65
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 58
+- 58
+- 262
+: - - 432.75
+    - 548.65
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 58
+- 62
+- 41
+: - - 432.75
+    - 548.65
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 58
+- 146
+- 263
+: - - 432.75
+    - 548.65
+  - - 445.75
+    - 556.65
+? !!python/tuple
+- 59
+- 44
+- 83
+: - - 287.05
+    - 502.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 59
+- 44
+- 353
+: - - 287.05
+    - 502.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 59
+- 63
+- 84
+: - - 287.05
+    - 502.45000000000005
+  - - 334.90000000000003
+    - 527.1
+? !!python/tuple
+- 59
+- 190
+- 355
+: - - 287.05
+    - 502.45000000000005
+  - - 297.20000000000005
+    - 502.80000000000007
+? !!python/tuple
+- 60
+- 96
+- 90
+: - - 246.8
+    - 498.55
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 60
+- 195
+- 368
+: - - 246.8
+    - 498.55
+  - - 256.8
+    - 498.85
+? !!python/tuple
+- 61
+- 61
+- 164
+: - - 343.75
+    - 173.10000000000002
+  - - 343.75
+    - 173.10000000000002
+? !!python/tuple
+- 61
+- 61
+- 638
+: - - 343.75
+    - 173.10000000000002
+  - - 343.75
+    - 173.10000000000002
+? !!python/tuple
+- 61
+- 91
+- 166
+: - - 343.75
+    - 173.10000000000002
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 61
+- 91
+- 640
+: - - 343.75
+    - 173.10000000000002
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 62
+- 45
+- 26
+: - - 444.15000000000003
+    - 570.75
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 62
+- 45
+- 240
+: - - 444.15000000000003
+    - 570.75
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 62
+- 62
+- 32
+: - - 444.15000000000003
+    - 570.75
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 63
+- 63
+- 76
+: - - 334.90000000000003
+    - 527.1
+  - - 334.90000000000003
+    - 527.1
+? !!python/tuple
+- 63
+- 63
+- 319
+: - - 334.90000000000003
+    - 527.1
+  - - 334.90000000000003
+    - 527.1
+? !!python/tuple
+- 63
+- 92
+- 71
+: - - 334.90000000000003
+    - 527.1
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 63
+- 92
+- 312
+: - - 334.90000000000003
+    - 527.1
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 63
+- 97
+- 72
+: - - 334.90000000000003
+    - 527.1
+  - - 341.35
+    - 527.7
+? !!python/tuple
+- 63
+- 97
+- 313
+: - - 334.90000000000003
+    - 527.1
+  - - 341.35
+    - 527.7
+? !!python/tuple
+- 64
+- 93
+- 10
+: - - 253.3
+    - 602.25
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 64
+- 125
+- 209
+: - - 253.3
+    - 602.25
+  - - 263.0
+    - 594.1
+? !!python/tuple
+- 64
+- 130
+- 205
+: - - 253.3
+    - 602.25
+  - - 260.65000000000003
+    - 604.7
+? !!python/tuple
+- 65
+- 6
+- 93
+: - - 232.55
+    - 490.6
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 65
+- 60
+- 94
+: - - 232.55
+    - 490.6
+  - - 246.8
+    - 498.55
+? !!python/tuple
+- 65
+- 60
+- 378
+: - - 232.55
+    - 490.6
+  - - 246.8
+    - 498.55
+? !!python/tuple
+- 65
+- 65
+- 110
+: - - 232.55
+    - 490.6
+  - - 232.55
+    - 490.6
+? !!python/tuple
+- 65
+- 86
+- 97
+: - - 232.55
+    - 490.6
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 65
+- 216
+- 386
+: - - 232.55
+    - 490.6
+  - - 242.25
+    - 485.15000000000003
+? !!python/tuple
+- 66
+- 66
+- 99
+: - - 427.90000000000003
+    - 458.8
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 66
+- 217
+- 407
+: - - 427.90000000000003
+    - 458.8
+  - - 427.0
+    - 469.35
+? !!python/tuple
+- 66
+- 226
+- 408
+: - - 427.90000000000003
+    - 458.8
+  - - 438.45000000000005
+    - 459.65000000000003
+? !!python/tuple
+- 67
+- 51
+- 167
+: - - 315.75
+    - 172.85000000000002
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 67
+- 407
+- 642
+: - - 315.75
+    - 172.85000000000002
+  - - 325.90000000000003
+    - 172.85000000000002
+? !!python/tuple
+- 68
+- 35
+- 52
+: - - 430.70000000000005
+    - 537.3000000000001
+  - - 429.8
+    - 540.35
+? !!python/tuple
+- 68
+- 35
+- 283
+: - - 430.70000000000005
+    - 537.3000000000001
+  - - 429.8
+    - 540.35
+? !!python/tuple
+- 68
+- 50
+- 54
+: - - 430.70000000000005
+    - 537.3000000000001
+  - - 434.95000000000005
+    - 537.45
+? !!python/tuple
+- 68
+- 50
+- 285
+: - - 430.70000000000005
+    - 537.3000000000001
+  - - 434.95000000000005
+    - 537.45
+? !!python/tuple
+- 69
+- 41
+- 171
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 69
+- 71
+- 174
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 69
+- 416
+- 650
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 271.15000000000003
+    - 170.0
+? !!python/tuple
+- 69
+- 421
+- 657
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 265.45
+    - 155.05
+? !!python/tuple
+- 70
+- 98
+- 160
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 70
+- 98
+- 161
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 70
+- 392
+- 626
+: - - 415.25
+    - 187.35000000000002
+  - - 424.8
+    - 188.35000000000002
+? !!python/tuple
+- 71
+- 51
+- 173
+: - - 283.45
+    - 159.8
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 71
+- 417
+- 655
+: - - 283.45
+    - 159.8
+  - - 293.1
+    - 160.85000000000002
+? !!python/tuple
+- 72
+- 85
+- 91
+: - - 358.45000000000005
+    - 495.6
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 72
+- 199
+- 373
+: - - 358.45000000000005
+    - 495.6
+  - - 368.95000000000005
+    - 496.55
+? !!python/tuple
+- 73
+- 22
+- 46
+: - - 427.3
+    - 540.75
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 73
+- 22
+- 276
+: - - 427.3
+    - 540.75
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 73
+- 35
+- 48
+: - - 427.3
+    - 540.75
+  - - 429.8
+    - 540.35
+? !!python/tuple
+- 73
+- 35
+- 278
+: - - 427.3
+    - 540.75
+  - - 429.8
+    - 540.35
+? !!python/tuple
+- 74
+- 7
+- 60
+: - - 350.15000000000003
+    - 533.2
+  - - 345.3
+    - 568.1
+? !!python/tuple
+- 74
+- 43
+- 62
+: - - 350.15000000000003
+    - 533.2
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 74
+- 43
+- 298
+: - - 350.15000000000003
+    - 533.2
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 74
+- 149
+- 294
+: - - 350.15000000000003
+    - 533.2
+  - - 349.3
+    - 543.7
+? !!python/tuple
+- 75
+- 53
+- 77
+: - - 434.6
+    - 519.35
+  - - 442.35
+    - 535.35
+? !!python/tuple
+- 75
+- 53
+- 325
+: - - 434.6
+    - 519.35
+  - - 442.35
+    - 535.35
+? !!python/tuple
+- 76
+- 10
+- 89
+: - - 345.05
+    - 498.20000000000005
+  - - 347.75
+    - 500.90000000000003
+? !!python/tuple
+- 76
+- 10
+- 366
+: - - 345.05
+    - 498.20000000000005
+  - - 347.75
+    - 500.90000000000003
+? !!python/tuple
+- 76
+- 84
+- 82
+: - - 345.05
+    - 498.20000000000005
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 76
+- 194
+- 365
+: - - 345.05
+    - 498.20000000000005
+  - - 343.85
+    - 511.6
+? !!python/tuple
+- 77
+- 1
+- 111
+: - - 227.5
+    - 441.15000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 77
+- 253
+- 437
+: - - 227.5
+    - 441.15000000000003
+  - - 226.10000000000002
+    - 451.6
+? !!python/tuple
+- 77
+- 257
+- 438
+: - - 227.5
+    - 441.15000000000003
+  - - 238.0
+    - 441.90000000000003
+? !!python/tuple
+- 78
+- 18
+- 144
+: - - 242.60000000000002
+    - 325.3
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 78
+- 78
+- 143
+: - - 242.60000000000002
+    - 325.3
+  - - 242.60000000000002
+    - 325.3
+? !!python/tuple
+- 78
+- 78
+- 551
+: - - 242.60000000000002
+    - 325.3
+  - - 242.60000000000002
+    - 325.3
+? !!python/tuple
+- 78
+- 339
+- 552
+: - - 242.60000000000002
+    - 325.3
+  - - 253.10000000000002
+    - 326.05
+? !!python/tuple
+- 79
+- 20
+- 158
+: - - 257.90000000000003
+    - 208.75
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 79
+- 69
+- 170
+: - - 257.90000000000003
+    - 208.75
+  - - 260.65000000000003
+    - 169.20000000000002
+? !!python/tuple
+- 79
+- 381
+- 607
+: - - 257.90000000000003
+    - 208.75
+  - - 268.40000000000003
+    - 209.25
+? !!python/tuple
+- 79
+- 415
+- 613
+: - - 257.90000000000003
+    - 208.75
+  - - 257.95
+    - 199.65
+? !!python/tuple
+- 80
+- 36
+- 57
+: - - 416.95000000000005
+    - 536.1
+  - - 418.45000000000005
+    - 539.7
+? !!python/tuple
+- 80
+- 36
+- 288
+: - - 416.95000000000005
+    - 536.1
+  - - 418.45000000000005
+    - 539.7
+? !!python/tuple
+- 80
+- 95
+- 56
+: - - 416.95000000000005
+    - 536.1
+  - - 416.0
+    - 539.15
+? !!python/tuple
+- 80
+- 95
+- 287
+: - - 416.95000000000005
+    - 536.1
+  - - 416.0
+    - 539.15
+? !!python/tuple
+- 81
+- 81
+- 70
+: - - 342.35
+    - 567.25
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 82
+- 68
+- 55
+: - - 427.35
+    - 537.4
+  - - 430.70000000000005
+    - 537.3000000000001
+? !!python/tuple
+- 82
+- 68
+- 286
+: - - 427.35
+    - 537.4
+  - - 430.70000000000005
+    - 537.3000000000001
+? !!python/tuple
+- 82
+- 73
+- 51
+: - - 427.35
+    - 537.4
+  - - 427.3
+    - 540.75
+? !!python/tuple
+- 82
+- 73
+- 282
+: - - 427.35
+    - 537.4
+  - - 427.3
+    - 540.75
+? !!python/tuple
+- 83
+- 43
+- 69
+: - - 350.25
+    - 530.6
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 83
+- 43
+- 309
+: - - 350.25
+    - 530.6
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 83
+- 74
+- 67
+: - - 350.25
+    - 530.6
+  - - 350.15000000000003
+    - 533.2
+? !!python/tuple
+- 83
+- 74
+- 307
+: - - 350.25
+    - 530.6
+  - - 350.15000000000003
+    - 533.2
+? !!python/tuple
+- 84
+- 9
+- 78
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 84
+- 9
+- 327
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 84
+- 75
+- 79
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 84
+- 75
+- 80
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 84
+- 84
+- 88
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 85
+- 222
+- 367
+: - - 391.45000000000005
+    - 497.90000000000003
+  - - 405.6
+    - 499.70000000000005
+? !!python/tuple
+- 86
+- 39
+- 96
+: - - 258.95
+    - 486.1
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 86
+- 214
+- 385
+: - - 258.95
+    - 486.1
+  - - 269.45
+    - 487.70000000000005
+? !!python/tuple
+- 87
+- 32
+- 125
+: - - 230.9
+    - 400.35
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 87
+- 77
+- 124
+: - - 230.9
+    - 400.35
+  - - 227.5
+    - 441.15000000000003
+? !!python/tuple
+- 87
+- 289
+- 484
+: - - 230.9
+    - 400.35
+  - - 229.65
+    - 410.85
+? !!python/tuple
+- 87
+- 292
+- 486
+: - - 230.9
+    - 400.35
+  - - 241.45000000000002
+    - 401.05
+? !!python/tuple
+- 88
+- 16
+- 134
+: - - 271.1
+    - 357.25
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 88
+- 32
+- 133
+: - - 271.1
+    - 357.25
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 88
+- 312
+- 526
+: - - 271.1
+    - 357.25
+  - - 269.25
+    - 367.70000000000005
+? !!python/tuple
+- 88
+- 315
+- 527
+: - - 271.1
+    - 357.25
+  - - 281.6
+    - 358.45000000000005
+? !!python/tuple
+- 89
+- 19
+- 152
+: - - 248.75
+    - 247.10000000000002
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 89
+- 79
+- 157
+: - - 248.75
+    - 247.10000000000002
+  - - 257.90000000000003
+    - 208.75
+? !!python/tuple
+- 89
+- 99
+- 151
+: - - 248.75
+    - 247.10000000000002
+  - - 241.25
+    - 286.2
+? !!python/tuple
+- 89
+- 364
+- 581
+: - - 248.75
+    - 247.10000000000002
+  - - 245.4
+    - 257.55
+? !!python/tuple
+- 89
+- 367
+- 582
+: - - 248.75
+    - 247.10000000000002
+  - - 259.3
+    - 248.2
+? !!python/tuple
+- 89
+- 380
+- 584
+: - - 248.75
+    - 247.10000000000002
+  - - 250.45
+    - 239.20000000000002
+? !!python/tuple
+- 90
+- 386
+- 593
+: - - 380.5
+    - 214.0
+  - - 391.05
+    - 214.85000000000002
+? !!python/tuple
+- 90
+- 401
+- 615
+: - - 380.5
+    - 214.0
+  - - 381.20000000000005
+    - 197.9
+? !!python/tuple
+- 91
+- 70
+- 163
+: - - 349.35
+    - 174.45000000000002
+  - - 415.25
+    - 187.35000000000002
+? !!python/tuple
+- 91
+- 397
+- 637
+: - - 349.35
+    - 174.45000000000002
+  - - 359.5
+    - 175.3
+? !!python/tuple
+- 92
+- 81
+- 34
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 92
+- 81
+- 248
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 92
+- 92
+- 33
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 92
+- 92
+- 247
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 93
+- 4
+- 2
+: - - 316.95000000000005
+    - 618.75
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 93
+- 93
+- 3
+: - - 316.95000000000005
+    - 618.75
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 93
+- 100
+- 195
+: - - 316.95000000000005
+    - 618.75
+  - - 327.40000000000003
+    - 621.5
+? !!python/tuple
+- 94
+- 22
+- 50
+: - - 408.45000000000005
+    - 546.5
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 94
+- 22
+- 280
+: - - 408.45000000000005
+    - 546.5
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 94
+- 46
+- 43
+: - - 408.45000000000005
+    - 546.5
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 94
+- 147
+- 266
+: - - 408.45000000000005
+    - 546.5
+  - - 407.45000000000005
+    - 557.0
+? !!python/tuple
+- 95
+- 95
+- 49
+: - - 416.0
+    - 539.15
+  - - 416.0
+    - 539.15
+? !!python/tuple
+- 95
+- 95
+- 279
+: - - 416.0
+    - 539.15
+  - - 416.0
+    - 539.15
+? !!python/tuple
+- 96
+- 44
+- 81
+: - - 263.7
+    - 533.15
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 96
+- 185
+- 297
+: - - 263.7
+    - 533.15
+  - - 280.35
+    - 535.15
+? !!python/tuple
+- 97
+- 9
+- 74
+: - - 341.35
+    - 527.7
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 97
+- 9
+- 315
+: - - 341.35
+    - 527.7
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 97
+- 164
+- 311
+: - - 341.35
+    - 527.7
+  - - 338.6
+    - 537.6
+? !!python/tuple
+- 98
+- 98
+- 159
+: - - 448.25
+    - 194.60000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 98
+- 98
+- 619
+: - - 448.25
+    - 194.60000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 99
+- 29
+- 148
+: - - 241.25
+    - 286.2
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 99
+- 87
+- 147
+: - - 241.25
+    - 286.2
+  - - 230.9
+    - 400.35
+? !!python/tuple
+- 99
+- 347
+- 566
+: - - 241.25
+    - 286.2
+  - - 239.70000000000002
+    - 296.65000000000003
+? !!python/tuple
+- 99
+- 356
+- 567
+: - - 241.25
+    - 286.2
+  - - 251.7
+    - 286.90000000000003
+? !!python/tuple
+- 100
+- 4
+- 191
+: - - 327.40000000000003
+    - 621.5
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 101
+- 102
+- 204
+: - - 312.55
+    - 602.4
+  - - 318.15000000000003
+    - 611.2
+? !!python/tuple
+- 102
+- 93
+- 199
+: - - 318.15000000000003
+    - 611.2
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 103
+- 103
+- 210
+: - - 446.05
+    - 595.9
+  - - 446.05
+    - 595.9
+? !!python/tuple
+- 104
+- 64
+- 206
+: - - 243.8
+    - 601.65
+  - - 253.3
+    - 602.25
+? !!python/tuple
+- 104
+- 104
+- 211
+: - - 243.8
+    - 601.65
+  - - 243.8
+    - 601.65
+? !!python/tuple
+- 105
+- 106
+- 203
+: - - 234.05
+    - 602.45
+  - - 233.10000000000002
+    - 612.45
+? !!python/tuple
+- 106
+- 107
+- 198
+: - - 233.10000000000002
+    - 612.45
+  - - 237.45000000000002
+    - 619.3000000000001
+? !!python/tuple
+- 107
+- 108
+- 194
+: - - 237.45000000000002
+    - 619.3000000000001
+  - - 247.45
+    - 620.2
+? !!python/tuple
+- 108
+- 109
+- 193
+: - - 247.45
+    - 620.2
+  - - 257.45
+    - 621.1500000000001
+? !!python/tuple
+- 109
+- 110
+- 192
+: - - 257.45
+    - 621.1500000000001
+  - - 267.45
+    - 622.1
+? !!python/tuple
+- 110
+- 111
+- 190
+: - - 267.45
+    - 622.1
+  - - 277.45
+    - 623.0500000000001
+? !!python/tuple
+- 111
+- 112
+- 187
+: - - 277.45
+    - 623.0500000000001
+  - - 287.45
+    - 624.0
+? !!python/tuple
+- 112
+- 113
+- 185
+: - - 287.45
+    - 624.0
+  - - 292.25
+    - 629.9000000000001
+? !!python/tuple
+- 113
+- 114
+- 179
+: - - 292.25
+    - 629.9000000000001
+  - - 302.25
+    - 631.0
+? !!python/tuple
+- 114
+- 115
+- 178
+: - - 302.25
+    - 631.0
+  - - 312.25
+    - 632.0500000000001
+? !!python/tuple
+- 115
+- 116
+- 177
+: - - 312.25
+    - 632.0500000000001
+  - - 322.25
+    - 633.1
+? !!python/tuple
+- 116
+- 117
+- 176
+: - - 322.25
+    - 633.1
+  - - 332.25
+    - 634.1
+? !!python/tuple
+- 117
+- 118
+- 175
+: - - 332.25
+    - 634.1
+  - - 340.90000000000003
+    - 633.1500000000001
+? !!python/tuple
+- 119
+- 118
+- 189
+: - - 351.6
+    - 622.4000000000001
+  - - 340.90000000000003
+    - 633.1500000000001
+? !!python/tuple
+- 119
+- 120
+- 188
+: - - 351.6
+    - 622.4000000000001
+  - - 361.6
+    - 623.3000000000001
+? !!python/tuple
+- 120
+- 121
+- 186
+: - - 361.6
+    - 623.3000000000001
+  - - 368.1
+    - 627.85
+? !!python/tuple
+- 121
+- 121
+- 181
+: - - 368.1
+    - 627.85
+  - - 368.1
+    - 627.85
+? !!python/tuple
+- 122
+- 123
+- 184
+: - - 382.5
+    - 624.8000000000001
+  - - 392.5
+    - 625.6500000000001
+? !!python/tuple
+- 123
+- 3
+- 182
+: - - 392.5
+    - 625.6500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 124
+- 126
+- 218
+: - - 273.0
+    - 586.9
+  - - 283.0
+    - 587.65
+? !!python/tuple
+- 125
+- 124
+- 217
+: - - 263.0
+    - 594.1
+  - - 273.0
+    - 586.9
+? !!python/tuple
+- 126
+- 127
+- 216
+: - - 283.0
+    - 587.65
+  - - 285.90000000000003
+    - 597.25
+? !!python/tuple
+- 127
+- 128
+- 208
+: - - 285.90000000000003
+    - 597.25
+  - - 287.85
+    - 607.25
+? !!python/tuple
+- 129
+- 131
+- 201
+: - - 270.65000000000003
+    - 606.95
+  - - 296.85
+    - 613.45
+? !!python/tuple
+- 130
+- 129
+- 202
+: - - 260.65000000000003
+    - 604.7
+  - - 270.65000000000003
+    - 606.95
+? !!python/tuple
+- 131
+- 132
+- 197
+: - - 296.85
+    - 613.45
+  - - 306.85
+    - 616.45
+? !!python/tuple
+- 132
+- 93
+- 196
+: - - 306.85
+    - 616.45
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 133
+- 6
+- 228
+: - - 207.55
+    - 580.4
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 134
+- 133
+- 222
+: - - 197.55
+    - 579.4
+  - - 207.55
+    - 580.4
+? !!python/tuple
+- 135
+- 134
+- 225
+: - - 187.55
+    - 578.4
+  - - 197.55
+    - 579.4
+? !!python/tuple
+- 135
+- 135
+- 226
+: - - 187.55
+    - 578.4
+  - - 187.55
+    - 578.4
+? !!python/tuple
+- 136
+- 62
+- 243
+: - - 433.25
+    - 569.6
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 137
+- 137
+- 242
+: - - 368.95000000000005
+    - 570.4
+  - - 368.95000000000005
+    - 570.4
+? !!python/tuple
+- 138
+- 57
+- 238
+: - - 383.45000000000005
+    - 571.75
+  - - 391.3
+    - 573.1
+? !!python/tuple
+- 139
+- 140
+- 223
+: - - 344.55
+    - 578.65
+  - - 343.6
+    - 588.65
+? !!python/tuple
+- 140
+- 141
+- 215
+: - - 343.6
+    - 588.65
+  - - 342.65000000000003
+    - 598.65
+? !!python/tuple
+- 141
+- 142
+- 207
+: - - 342.65000000000003
+    - 598.65
+  - - 341.70000000000005
+    - 608.6500000000001
+? !!python/tuple
+- 142
+- 4
+- 200
+: - - 341.70000000000005
+    - 608.6500000000001
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 143
+- 143
+- 249
+: - - 472.5
+    - 567.75
+  - - 472.5
+    - 567.75
+? !!python/tuple
+- 144
+- 144
+- 256
+: - - 473.70000000000005
+    - 553.2
+  - - 473.70000000000005
+    - 553.2
+? !!python/tuple
+- 144
+- 144
+- 261
+: - - 473.70000000000005
+    - 553.2
+  - - 473.70000000000005
+    - 553.2
+? !!python/tuple
+- 145
+- 145
+- 259
+: - - 455.75
+    - 550.4
+  - - 455.75
+    - 550.4
+? !!python/tuple
+- 146
+- 62
+- 254
+: - - 445.75
+    - 556.65
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 147
+- 46
+- 253
+: - - 407.45000000000005
+    - 557.0
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 148
+- 148
+- 265
+: - - 473.85
+    - 543.65
+  - - 473.85
+    - 543.65
+? !!python/tuple
+- 148
+- 148
+- 271
+: - - 473.85
+    - 543.65
+  - - 473.85
+    - 543.65
+? !!python/tuple
+- 149
+- 150
+- 270
+: - - 349.3
+    - 543.7
+  - - 348.35
+    - 553.7
+? !!python/tuple
+- 150
+- 7
+- 255
+: - - 348.35
+    - 553.7
+  - - 345.3
+    - 568.1
+? !!python/tuple
+- 151
+- 152
+- 273
+: - - 370.6
+    - 542.4
+  - - 380.6
+    - 543.35
+? !!python/tuple
+- 152
+- 153
+- 272
+: - - 380.6
+    - 543.35
+  - - 390.6
+    - 544.3000000000001
+? !!python/tuple
+- 153
+- 154
+- 269
+: - - 390.6
+    - 544.3000000000001
+  - - 400.6
+    - 545.2
+? !!python/tuple
+- 154
+- 94
+- 268
+: - - 400.6
+    - 545.2
+  - - 408.45000000000005
+    - 546.5
+? !!python/tuple
+- 155
+- 156
+- 274
+: - - 239.4
+    - 541.0
+  - - 238.4
+    - 551.0
+? !!python/tuple
+- 156
+- 157
+- 257
+: - - 238.4
+    - 551.0
+  - - 237.45000000000002
+    - 561.0
+? !!python/tuple
+- 157
+- 158
+- 250
+: - - 237.45000000000002
+    - 561.0
+  - - 236.45000000000002
+    - 571.0
+? !!python/tuple
+- 158
+- 21
+- 239
+: - - 236.45000000000002
+    - 571.0
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 159
+- 160
+- 299
+: - - 377.5
+    - 532.65
+  - - 387.5
+    - 533.5
+? !!python/tuple
+- 160
+- 161
+- 295
+: - - 387.5
+    - 533.5
+  - - 397.5
+    - 534.35
+? !!python/tuple
+- 161
+- 162
+- 293
+: - - 397.5
+    - 534.35
+  - - 407.5
+    - 535.2
+? !!python/tuple
+- 162
+- 80
+- 292
+: - - 407.5
+    - 535.2
+  - - 416.95000000000005
+    - 536.1
+? !!python/tuple
+- 163
+- 96
+- 300
+: - - 254.05
+    - 532.65
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 164
+- 165
+- 281
+: - - 338.6
+    - 537.6
+  - - 337.90000000000003
+    - 547.6
+? !!python/tuple
+- 165
+- 166
+- 264
+: - - 337.90000000000003
+    - 547.6
+  - - 337.55
+    - 557.6
+? !!python/tuple
+- 166
+- 81
+- 252
+: - - 337.55
+    - 557.6
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 167
+- 168
+- 332
+: - - 359.05
+    - 516.1
+  - - 366.65000000000003
+    - 519.45
+? !!python/tuple
+- 167
+- 174
+- 333
+: - - 359.05
+    - 516.1
+  - - 426.65000000000003
+    - 524.7
+? !!python/tuple
+- 168
+- 169
+- 326
+: - - 366.65000000000003
+    - 519.45
+  - - 376.65000000000003
+    - 520.35
+? !!python/tuple
+- 169
+- 170
+- 324
+: - - 376.65000000000003
+    - 520.35
+  - - 386.65000000000003
+    - 521.25
+? !!python/tuple
+- 170
+- 171
+- 322
+: - - 386.65000000000003
+    - 521.25
+  - - 396.65000000000003
+    - 522.2
+? !!python/tuple
+- 171
+- 172
+- 320
+: - - 396.65000000000003
+    - 522.2
+  - - 406.65000000000003
+    - 523.1
+? !!python/tuple
+- 172
+- 173
+- 318
+: - - 406.65000000000003
+    - 523.1
+  - - 416.65000000000003
+    - 524.0
+? !!python/tuple
+- 173
+- 174
+- 317
+: - - 416.65000000000003
+    - 524.0
+  - - 426.65000000000003
+    - 524.7
+? !!python/tuple
+- 175
+- 84
+- 342
+: - - 352.70000000000005
+    - 509.9
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 175
+- 176
+- 343
+: - - 352.70000000000005
+    - 509.9
+  - - 364.90000000000003
+    - 511.20000000000005
+? !!python/tuple
+- 176
+- 177
+- 340
+: - - 364.90000000000003
+    - 511.20000000000005
+  - - 374.90000000000003
+    - 512.35
+? !!python/tuple
+- 177
+- 178
+- 337
+: - - 374.90000000000003
+    - 512.35
+  - - 384.90000000000003
+    - 513.5
+? !!python/tuple
+- 178
+- 179
+- 336
+: - - 384.90000000000003
+    - 513.5
+  - - 394.90000000000003
+    - 514.65
+? !!python/tuple
+- 179
+- 180
+- 335
+: - - 394.90000000000003
+    - 514.65
+  - - 404.90000000000003
+    - 515.8000000000001
+? !!python/tuple
+- 180
+- 182
+- 334
+: - - 404.90000000000003
+    - 515.8000000000001
+  - - 413.40000000000003
+    - 516.75
+? !!python/tuple
+- 181
+- 75
+- 330
+: - - 423.40000000000003
+    - 517.9
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 182
+- 181
+- 331
+: - - 413.40000000000003
+    - 516.75
+  - - 423.40000000000003
+    - 517.9
+? !!python/tuple
+- 183
+- 184
+- 328
+: - - 285.35
+    - 518.3000000000001
+  - - 284.45
+    - 528.3000000000001
+? !!python/tuple
+- 185
+- 186
+- 310
+: - - 280.35
+    - 535.15
+  - - 288.05
+    - 536.0
+? !!python/tuple
+- 186
+- 187
+- 289
+: - - 288.05
+    - 536.0
+  - - 298.05
+    - 536.85
+? !!python/tuple
+- 187
+- 187
+- 302
+: - - 298.05
+    - 536.85
+  - - 298.05
+    - 536.85
+? !!python/tuple
+- 188
+- 189
+- 346
+: - - 338.8
+    - 505.55000000000007
+  - - 336.85
+    - 515.5
+? !!python/tuple
+- 188
+- 189
+- 347
+: - - 338.8
+    - 505.55000000000007
+  - - 336.85
+    - 515.5
+? !!python/tuple
+- 190
+- 191
+- 354
+: - - 297.20000000000005
+    - 502.80000000000007
+  - - 307.20000000000005
+    - 503.75
+? !!python/tuple
+- 191
+- 191
+- 352
+: - - 307.20000000000005
+    - 503.75
+  - - 307.20000000000005
+    - 503.75
+? !!python/tuple
+- 192
+- 193
+- 351
+: - - 319.6
+    - 504.20000000000005
+  - - 329.6
+    - 504.9
+? !!python/tuple
+- 193
+- 193
+- 349
+: - - 329.6
+    - 504.9
+  - - 329.6
+    - 504.9
+? !!python/tuple
+- 194
+- 84
+- 338
+: - - 343.85
+    - 511.6
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 195
+- 196
+- 364
+: - - 256.8
+    - 498.85
+  - - 266.8
+    - 500.40000000000003
+? !!python/tuple
+- 196
+- 48
+- 359
+: - - 266.8
+    - 500.40000000000003
+  - - 276.85
+    - 501.45000000000005
+? !!python/tuple
+- 196
+- 197
+- 358
+: - - 266.8
+    - 500.40000000000003
+  - - 265.85
+    - 510.35
+? !!python/tuple
+- 197
+- 198
+- 341
+: - - 265.85
+    - 510.35
+  - - 264.85
+    - 520.35
+? !!python/tuple
+- 198
+- 96
+- 323
+: - - 264.85
+    - 520.35
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 199
+- 200
+- 371
+: - - 368.95000000000005
+    - 496.55
+  - - 378.95000000000005
+    - 497.40000000000003
+? !!python/tuple
+- 200
+- 85
+- 369
+: - - 378.95000000000005
+    - 497.40000000000003
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 201
+- 38
+- 374
+: - - 335.6
+    - 493.65000000000003
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 202
+- 203
+- 370
+: - - 227.0
+    - 500.05
+  - - 222.4
+    - 510.9
+? !!python/tuple
+- 202
+- 209
+- 377
+: - - 227.0
+    - 500.05
+  - - 236.0
+    - 506.15
+? !!python/tuple
+- 203
+- 204
+- 339
+: - - 222.4
+    - 510.9
+  - - 221.4
+    - 520.9
+? !!python/tuple
+- 204
+- 37
+- 321
+: - - 221.4
+    - 520.9
+  - - 235.8
+    - 532.1
+? !!python/tuple
+- 205
+- 206
+- 305
+: - - 221.20000000000002
+    - 530.9
+  - - 219.45000000000002
+    - 540.9
+? !!python/tuple
+- 206
+- 207
+- 275
+: - - 219.45000000000002
+    - 540.9
+  - - 218.45000000000002
+    - 550.9
+? !!python/tuple
+- 207
+- 208
+- 258
+: - - 218.45000000000002
+    - 550.9
+  - - 217.5
+    - 560.9
+? !!python/tuple
+- 209
+- 60
+- 362
+: - - 236.0
+    - 506.15
+  - - 246.8
+    - 498.55
+? !!python/tuple
+- 210
+- 211
+- 345
+: - - 245.70000000000002
+    - 507.75
+  - - 244.9
+    - 517.75
+? !!python/tuple
+- 211
+- 25
+- 329
+: - - 244.9
+    - 517.75
+  - - 243.55
+    - 531.15
+? !!python/tuple
+- 212
+- 213
+- 379
+: - - 302.3
+    - 490.6
+  - - 312.3
+    - 491.5
+? !!python/tuple
+- 213
+- 26
+- 376
+: - - 312.3
+    - 491.5
+  - - 325.1
+    - 492.05
+? !!python/tuple
+- 214
+- 215
+- 383
+: - - 269.45
+    - 487.70000000000005
+  - - 279.45
+    - 488.6
+? !!python/tuple
+- 215
+- 39
+- 382
+: - - 279.45
+    - 488.6
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 216
+- 86
+- 387
+: - - 242.25
+    - 485.15000000000003
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 217
+- 218
+- 398
+: - - 427.0
+    - 469.35
+  - - 426.20000000000005
+    - 479.35
+? !!python/tuple
+- 218
+- 219
+- 391
+: - - 426.20000000000005
+    - 479.35
+  - - 425.35
+    - 489.35
+? !!python/tuple
+- 219
+- 220
+- 380
+: - - 425.35
+    - 489.35
+  - - 424.55
+    - 499.35
+? !!python/tuple
+- 221
+- 223
+- 360
+: - - 415.6
+    - 500.5
+  - - 436.85
+    - 504.75
+? !!python/tuple
+- 222
+- 221
+- 361
+: - - 405.6
+    - 499.70000000000005
+  - - 415.6
+    - 500.5
+? !!python/tuple
+- 224
+- 223
+- 348
+: - - 429.40000000000003
+    - 507.35
+  - - 436.85
+    - 504.75
+? !!python/tuple
+- 225
+- 224
+- 350
+: - - 399.40000000000003
+    - 504.5
+  - - 429.40000000000003
+    - 507.35
+? !!python/tuple
+- 226
+- 227
+- 406
+: - - 438.45000000000005
+    - 459.65000000000003
+  - - 448.45000000000005
+    - 460.20000000000005
+? !!python/tuple
+- 227
+- 227
+- 405
+: - - 448.45000000000005
+    - 460.20000000000005
+  - - 448.45000000000005
+    - 460.20000000000005
+? !!python/tuple
+- 228
+- 229
+- 400
+: - - 394.0
+    - 466.65000000000003
+  - - 393.20000000000005
+    - 476.65000000000003
+? !!python/tuple
+- 229
+- 230
+- 393
+: - - 393.20000000000005
+    - 476.65000000000003
+  - - 392.40000000000003
+    - 486.65000000000003
+? !!python/tuple
+- 230
+- 85
+- 384
+: - - 392.40000000000003
+    - 486.65000000000003
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 231
+- 232
+- 411
+: - - 405.35
+    - 456.95000000000005
+  - - 415.35
+    - 457.75
+? !!python/tuple
+- 232
+- 66
+- 410
+: - - 415.35
+    - 457.75
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 233
+- 234
+- 402
+: - - 360.90000000000003
+    - 464.0
+  - - 360.1
+    - 474.0
+? !!python/tuple
+- 234
+- 235
+- 395
+: - - 360.1
+    - 474.0
+  - - 359.25
+    - 484.0
+? !!python/tuple
+- 235
+- 72
+- 388
+: - - 359.25
+    - 484.0
+  - - 358.45000000000005
+    - 495.6
+? !!python/tuple
+- 236
+- 237
+- 416
+: - - 372.35
+    - 454.3
+  - - 382.35
+    - 455.1
+? !!python/tuple
+- 237
+- 0
+- 415
+: - - 382.35
+    - 455.1
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 238
+- 239
+- 404
+: - - 327.90000000000003
+    - 461.1
+  - - 327.0
+    - 471.1
+? !!python/tuple
+- 239
+- 240
+- 397
+: - - 327.0
+    - 471.1
+  - - 326.20000000000005
+    - 481.1
+? !!python/tuple
+- 240
+- 26
+- 390
+: - - 326.20000000000005
+    - 481.1
+  - - 325.1
+    - 492.05
+? !!python/tuple
+- 241
+- 242
+- 421
+: - - 339.40000000000003
+    - 451.55
+  - - 349.40000000000003
+    - 452.40000000000003
+? !!python/tuple
+- 242
+- 40
+- 419
+: - - 349.40000000000003
+    - 452.40000000000003
+  - - 362.0938415527344
+    - 453.5181579589844
+? !!python/tuple
+- 243
+- 244
+- 409
+: - - 294.90000000000003
+    - 457.95000000000005
+  - - 293.95
+    - 467.95000000000005
+? !!python/tuple
+- 244
+- 245
+- 399
+: - - 293.95
+    - 467.95000000000005
+  - - 293.0
+    - 477.95000000000005
+? !!python/tuple
+- 245
+- 39
+- 392
+: - - 293.0
+    - 477.95000000000005
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 246
+- 247
+- 426
+: - - 306.25
+    - 448.45000000000005
+  - - 316.25
+    - 449.45000000000005
+? !!python/tuple
+- 247
+- 11
+- 424
+: - - 316.25
+    - 449.45000000000005
+  - - 328.85
+    - 450.6
+? !!python/tuple
+- 248
+- 249
+- 414
+: - - 261.85
+    - 454.85
+  - - 260.95
+    - 464.85
+? !!python/tuple
+- 249
+- 250
+- 401
+: - - 260.95
+    - 464.85
+  - - 260.1
+    - 474.85
+? !!python/tuple
+- 250
+- 86
+- 394
+: - - 260.1
+    - 474.85
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 251
+- 252
+- 431
+: - - 273.35
+    - 445.25
+  - - 283.35
+    - 446.25
+? !!python/tuple
+- 252
+- 28
+- 429
+: - - 283.35
+    - 446.25
+  - - 295.8104248046875
+    - 447.5629577636719
+? !!python/tuple
+- 253
+- 254
+- 420
+: - - 226.10000000000002
+    - 451.6
+  - - 225.20000000000002
+    - 461.6
+? !!python/tuple
+- 254
+- 255
+- 403
+: - - 225.20000000000002
+    - 461.6
+  - - 224.25
+    - 471.6
+? !!python/tuple
+- 255
+- 256
+- 396
+: - - 224.25
+    - 471.6
+  - - 224.20000000000002
+    - 481.6
+? !!python/tuple
+- 256
+- 65
+- 389
+: - - 224.20000000000002
+    - 481.6
+  - - 232.55
+    - 490.6
+? !!python/tuple
+- 257
+- 258
+- 436
+: - - 238.0
+    - 441.90000000000003
+  - - 248.0
+    - 442.90000000000003
+? !!python/tuple
+- 258
+- 1
+- 435
+: - - 248.0
+    - 442.90000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 259
+- 12
+- 456
+: - - 430.3
+    - 428.1
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 259
+- 260
+- 447
+: - - 430.3
+    - 428.1
+  - - 429.55
+    - 438.1
+? !!python/tuple
+- 260
+- 261
+- 440
+: - - 429.55
+    - 438.1
+  - - 428.75
+    - 448.1
+? !!python/tuple
+- 261
+- 66
+- 425
+: - - 428.75
+    - 448.1
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 262
+- 263
+- 454
+: - - 441.55
+    - 418.5
+  - - 451.55
+    - 419.25
+? !!python/tuple
+- 263
+- 263
+- 455
+: - - 451.55
+    - 419.25
+  - - 451.55
+    - 419.25
+? !!python/tuple
+- 264
+- 265
+- 449
+: - - 397.35
+    - 425.5
+  - - 396.5
+    - 435.5
+? !!python/tuple
+- 265
+- 266
+- 442
+: - - 396.5
+    - 435.5
+  - - 395.70000000000005
+    - 445.5
+? !!python/tuple
+- 266
+- 0
+- 430
+: - - 395.70000000000005
+    - 445.5
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 267
+- 268
+- 460
+: - - 408.75
+    - 415.90000000000003
+  - - 418.75
+    - 416.65000000000003
+? !!python/tuple
+- 268
+- 12
+- 459
+: - - 418.75
+    - 416.65000000000003
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 269
+- 270
+- 451
+: - - 364.3
+    - 422.90000000000003
+  - - 363.5
+    - 432.90000000000003
+? !!python/tuple
+- 270
+- 271
+- 444
+: - - 363.5
+    - 432.90000000000003
+  - - 362.65000000000003
+    - 442.90000000000003
+? !!python/tuple
+- 271
+- 40
+- 434
+: - - 362.65000000000003
+    - 442.90000000000003
+  - - 362.0938415527344
+    - 453.5181579589844
+? !!python/tuple
+- 272
+- 273
+- 465
+: - - 375.6
+    - 413.20000000000005
+  - - 385.6
+    - 414.0
+? !!python/tuple
+- 273
+- 13
+- 464
+: - - 385.6
+    - 414.0
+  - - 398.20000000000005
+    - 415.0
+? !!python/tuple
+- 274
+- 275
+- 453
+: - - 331.75
+    - 420.1
+  - - 330.8
+    - 430.1
+? !!python/tuple
+- 275
+- 276
+- 446
+: - - 330.8
+    - 430.1
+  - - 329.8
+    - 440.1
+? !!python/tuple
+- 276
+- 11
+- 439
+: - - 329.8
+    - 440.1
+  - - 328.85
+    - 450.6
+? !!python/tuple
+- 277
+- 278
+- 470
+: - - 343.3
+    - 410.5
+  - - 353.3
+    - 411.35
+? !!python/tuple
+- 278
+- 14
+- 468
+: - - 353.3
+    - 411.35
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 279
+- 280
+- 458
+: - - 298.75
+    - 416.70000000000005
+  - - 297.8
+    - 426.70000000000005
+? !!python/tuple
+- 280
+- 281
+- 448
+: - - 297.8
+    - 426.70000000000005
+  - - 296.85
+    - 436.70000000000005
+? !!python/tuple
+- 281
+- 28
+- 441
+: - - 296.85
+    - 436.70000000000005
+  - - 295.8104248046875
+    - 447.5629577636719
+? !!python/tuple
+- 282
+- 283
+- 474
+: - - 310.40000000000003
+    - 407.35
+  - - 320.40000000000003
+    - 408.3
+? !!python/tuple
+- 283
+- 30
+- 473
+: - - 320.40000000000003
+    - 408.3
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 284
+- 285
+- 463
+: - - 265.40000000000003
+    - 413.65000000000003
+  - - 264.55
+    - 423.65000000000003
+? !!python/tuple
+- 285
+- 286
+- 450
+: - - 264.55
+    - 423.65000000000003
+  - - 263.7
+    - 433.65000000000003
+? !!python/tuple
+- 286
+- 1
+- 443
+: - - 263.7
+    - 433.65000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 287
+- 288
+- 479
+: - - 276.65000000000003
+    - 404.05
+  - - 286.65000000000003
+    - 405.0
+? !!python/tuple
+- 288
+- 31
+- 478
+: - - 286.65000000000003
+    - 405.0
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 289
+- 290
+- 469
+: - - 229.65
+    - 410.85
+  - - 228.8
+    - 420.85
+? !!python/tuple
+- 290
+- 291
+- 452
+: - - 228.8
+    - 420.85
+  - - 227.95000000000002
+    - 430.85
+? !!python/tuple
+- 291
+- 77
+- 445
+: - - 227.95000000000002
+    - 430.85
+  - - 227.5
+    - 441.15000000000003
+? !!python/tuple
+- 292
+- 293
+- 483
+: - - 241.45000000000002
+    - 401.05
+  - - 251.45
+    - 401.85
+? !!python/tuple
+- 293
+- 32
+- 482
+: - - 251.45
+    - 401.85
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 294
+- 15
+- 506
+: - - 401.05
+    - 380.05
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 295
+- 294
+- 498
+: - - 400.25
+    - 390.05
+  - - 401.05
+    - 380.05
+? !!python/tuple
+- 296
+- 13
+- 485
+: - - 399.40000000000003
+    - 400.05
+  - - 398.20000000000005
+    - 415.0
+? !!python/tuple
+- 296
+- 295
+- 491
+: - - 399.40000000000003
+    - 400.05
+  - - 400.25
+    - 390.05
+? !!python/tuple
+- 297
+- 298
+- 500
+: - - 368.05
+    - 377.05
+  - - 367.20000000000005
+    - 387.05
+? !!python/tuple
+- 298
+- 299
+- 493
+: - - 367.20000000000005
+    - 387.05
+  - - 366.40000000000003
+    - 397.05
+? !!python/tuple
+- 299
+- 14
+- 487
+: - - 366.40000000000003
+    - 397.05
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 300
+- 301
+- 510
+: - - 379.45000000000005
+    - 367.45000000000005
+  - - 389.45000000000005
+    - 368.35
+? !!python/tuple
+- 301
+- 15
+- 508
+: - - 389.45000000000005
+    - 368.35
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 302
+- 303
+- 503
+: - - 336.35
+    - 374.15000000000003
+  - - 335.3
+    - 384.15000000000003
+? !!python/tuple
+- 303
+- 304
+- 496
+: - - 335.3
+    - 384.15000000000003
+  - - 334.3
+    - 394.15000000000003
+? !!python/tuple
+- 304
+- 30
+- 489
+: - - 334.3
+    - 394.15000000000003
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 305
+- 306
+- 516
+: - - 347.8
+    - 364.6
+  - - 357.8
+    - 365.55
+? !!python/tuple
+- 306
+- 2
+- 514
+: - - 357.8
+    - 365.55
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 307
+- 308
+- 504
+: - - 303.15000000000003
+    - 371.05
+  - - 302.15000000000003
+    - 381.05
+? !!python/tuple
+- 308
+- 309
+- 497
+: - - 302.15000000000003
+    - 381.05
+  - - 301.20000000000005
+    - 391.05
+? !!python/tuple
+- 309
+- 31
+- 490
+: - - 301.20000000000005
+    - 391.05
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 310
+- 311
+- 521
+: - - 314.65000000000003
+    - 361.55
+  - - 324.65000000000003
+    - 362.5
+? !!python/tuple
+- 311
+- 52
+- 519
+: - - 324.65000000000003
+    - 362.5
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 312
+- 313
+- 509
+: - - 269.25
+    - 367.70000000000005
+  - - 268.40000000000003
+    - 377.70000000000005
+? !!python/tuple
+- 313
+- 314
+- 499
+: - - 268.40000000000003
+    - 377.70000000000005
+  - - 267.55
+    - 387.70000000000005
+? !!python/tuple
+- 314
+- 32
+- 492
+: - - 267.55
+    - 387.70000000000005
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 315
+- 316
+- 525
+: - - 281.6
+    - 358.45000000000005
+  - - 291.6
+    - 359.40000000000003
+? !!python/tuple
+- 316
+- 16
+- 524
+: - - 291.6
+    - 359.40000000000003
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 318
+- 317
+- 536
+: - - 433.35
+    - 355.05
+  - - 434.3
+    - 345.05
+? !!python/tuple
+- 319
+- 318
+- 529
+: - - 432.40000000000003
+    - 365.05
+  - - 433.35
+    - 355.05
+? !!python/tuple
+- 319
+- 322
+- 515
+: - - 432.40000000000003
+    - 365.05
+  - - 434.40000000000003
+    - 376.8
+? !!python/tuple
+- 321
+- 320
+- 505
+: - - 418.05
+    - 370.85
+  - - 428.05
+    - 371.70000000000005
+? !!python/tuple
+- 323
+- 322
+- 501
+: - - 433.65000000000003
+    - 386.8
+  - - 434.40000000000003
+    - 376.8
+? !!python/tuple
+- 324
+- 323
+- 494
+: - - 432.85
+    - 396.8
+  - - 433.65000000000003
+    - 386.8
+? !!python/tuple
+- 325
+- 324
+- 488
+: - - 432.05
+    - 406.8
+  - - 432.85
+    - 396.8
+? !!python/tuple
+- 327
+- 326
+- 538
+: - - 403.5
+    - 351.70000000000005
+  - - 405.15000000000003
+    - 341.85
+? !!python/tuple
+- 328
+- 327
+- 531
+: - - 402.65000000000003
+    - 361.70000000000005
+  - - 403.5
+    - 351.70000000000005
+? !!python/tuple
+- 330
+- 329
+- 539
+: - - 370.35
+    - 349.05
+  - - 371.95000000000005
+    - 339.15000000000003
+? !!python/tuple
+- 331
+- 332
+- 542
+: - - 340.5
+    - 336.75
+  - - 339.0
+    - 346.70000000000005
+? !!python/tuple
+- 332
+- 52
+- 534
+: - - 339.0
+    - 346.70000000000005
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 333
+- 334
+- 537
+: - - 305.85
+    - 341.8
+  - - 304.95000000000005
+    - 351.8
+? !!python/tuple
+- 334
+- 16
+- 530
+: - - 304.95000000000005
+    - 351.8
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 335
+- 336
+- 540
+: - - 272.35
+    - 338.55
+  - - 271.55
+    - 348.55
+? !!python/tuple
+- 336
+- 88
+- 533
+: - - 271.55
+    - 348.55
+  - - 271.1
+    - 357.25
+? !!python/tuple
+- 337
+- 338
+- 546
+: - - 283.65000000000003
+    - 328.90000000000003
+  - - 293.65000000000003
+    - 329.90000000000003
+? !!python/tuple
+- 338
+- 17
+- 544
+: - - 293.65000000000003
+    - 329.90000000000003
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 339
+- 340
+- 550
+: - - 253.10000000000002
+    - 326.05
+  - - 263.1
+    - 326.95000000000005
+? !!python/tuple
+- 340
+- 18
+- 549
+: - - 263.1
+    - 326.95000000000005
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 341
+- 342
+- 557
+: - - 275.55
+    - 299.3
+  - - 274.8
+    - 309.3
+? !!python/tuple
+- 342
+- 343
+- 555
+: - - 274.8
+    - 309.3
+  - - 274.05
+    - 319.3
+? !!python/tuple
+- 343
+- 18
+- 553
+: - - 274.05
+    - 319.3
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 344
+- 345
+- 561
+: - - 286.7
+    - 289.3
+  - - 296.7
+    - 289.85
+? !!python/tuple
+- 345
+- 346
+- 560
+: - - 296.7
+    - 289.85
+  - - 306.70000000000005
+    - 290.45
+? !!python/tuple
+- 346
+- 346
+- 559
+: - - 306.70000000000005
+    - 290.45
+  - - 306.70000000000005
+    - 290.45
+? !!python/tuple
+- 347
+- 348
+- 558
+: - - 239.70000000000002
+    - 296.65000000000003
+  - - 238.60000000000002
+    - 306.65000000000003
+? !!python/tuple
+- 348
+- 349
+- 556
+: - - 238.60000000000002
+    - 306.65000000000003
+  - - 237.5
+    - 316.65000000000003
+? !!python/tuple
+- 349
+- 350
+- 554
+: - - 237.5
+    - 316.65000000000003
+  - - 235.60000000000002
+    - 336.65000000000003
+? !!python/tuple
+- 350
+- 351
+- 541
+: - - 235.60000000000002
+    - 336.65000000000003
+  - - 234.8
+    - 346.65000000000003
+? !!python/tuple
+- 351
+- 352
+- 535
+: - - 234.8
+    - 346.65000000000003
+  - - 233.95000000000002
+    - 356.65000000000003
+? !!python/tuple
+- 352
+- 353
+- 528
+: - - 233.95000000000002
+    - 356.65000000000003
+  - - 233.20000000000002
+    - 366.65000000000003
+? !!python/tuple
+- 353
+- 354
+- 511
+: - - 233.20000000000002
+    - 366.65000000000003
+  - - 232.4
+    - 376.65000000000003
+? !!python/tuple
+- 354
+- 355
+- 502
+: - - 232.4
+    - 376.65000000000003
+  - - 231.60000000000002
+    - 386.65000000000003
+? !!python/tuple
+- 355
+- 87
+- 495
+: - - 231.60000000000002
+    - 386.65000000000003
+  - - 230.9
+    - 400.35
+? !!python/tuple
+- 356
+- 357
+- 565
+: - - 251.7
+    - 286.90000000000003
+  - - 261.7
+    - 287.65000000000003
+? !!python/tuple
+- 357
+- 29
+- 564
+: - - 261.7
+    - 287.65000000000003
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 358
+- 19
+- 577
+: - - 278.05
+    - 259.95
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 359
+- 358
+- 572
+: - - 277.45
+    - 269.95
+  - - 278.05
+    - 259.95
+? !!python/tuple
+- 360
+- 29
+- 568
+: - - 276.8
+    - 279.95
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 360
+- 359
+- 570
+: - - 276.8
+    - 279.95
+  - - 277.45
+    - 269.95
+? !!python/tuple
+- 361
+- 362
+- 576
+: - - 289.15000000000003
+    - 249.90000000000003
+  - - 299.15000000000003
+    - 250.5
+? !!python/tuple
+- 362
+- 363
+- 574
+: - - 299.15000000000003
+    - 250.5
+  - - 309.15000000000003
+    - 251.05
+? !!python/tuple
+- 363
+- 363
+- 575
+: - - 309.15000000000003
+    - 251.05
+  - - 309.15000000000003
+    - 251.05
+? !!python/tuple
+- 364
+- 365
+- 573
+: - - 245.4
+    - 257.55
+  - - 242.95000000000002
+    - 267.55
+? !!python/tuple
+- 365
+- 366
+- 571
+: - - 242.95000000000002
+    - 267.55
+  - - 241.45000000000002
+    - 277.55
+? !!python/tuple
+- 366
+- 99
+- 569
+: - - 241.45000000000002
+    - 277.55
+  - - 241.25
+    - 286.2
+? !!python/tuple
+- 367
+- 368
+- 580
+: - - 259.3
+    - 248.2
+  - - 269.3
+    - 248.8
+? !!python/tuple
+- 368
+- 19
+- 579
+: - - 269.3
+    - 248.8
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 369
+- 370
+- 595
+: - - 357.90000000000003
+    - 213.4
+  - - 367.90000000000003
+    - 213.85000000000002
+? !!python/tuple
+- 370
+- 90
+- 594
+: - - 367.90000000000003
+    - 213.85000000000002
+  - - 380.5
+    - 214.0
+? !!python/tuple
+- 371
+- 372
+- 599
+: - - 324.35
+    - 211.9
+  - - 334.35
+    - 212.35000000000002
+? !!python/tuple
+- 372
+- 27
+- 598
+: - - 334.35
+    - 212.35000000000002
+  - - 347.40000000000003
+    - 212.5
+? !!python/tuple
+- 373
+- 20
+- 602
+: - - 280.7
+    - 220.55
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 374
+- 373
+- 587
+: - - 280.05
+    - 230.55
+  - - 280.7
+    - 220.55
+? !!python/tuple
+- 375
+- 374
+- 585
+: - - 279.40000000000003
+    - 240.55
+  - - 280.05
+    - 230.55
+? !!python/tuple
+- 376
+- 377
+- 603
+: - - 291.05
+    - 210.35000000000002
+  - - 301.05
+    - 210.8
+? !!python/tuple
+- 377
+- 49
+- 601
+: - - 301.05
+    - 210.8
+  - - 313.85
+    - 211.0
+? !!python/tuple
+- 378
+- 79
+- 606
+: - - 255.8
+    - 219.20000000000002
+  - - 257.90000000000003
+    - 208.75
+? !!python/tuple
+- 379
+- 378
+- 588
+: - - 253.2
+    - 229.20000000000002
+  - - 255.8
+    - 219.20000000000002
+? !!python/tuple
+- 380
+- 379
+- 586
+: - - 250.45
+    - 239.20000000000002
+  - - 253.2
+    - 229.20000000000002
+? !!python/tuple
+- 381
+- 20
+- 605
+: - - 268.40000000000003
+    - 209.25
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 382
+- 70
+- 625
+: - - 414.6
+    - 197.9
+  - - 415.25
+    - 187.35000000000002
+? !!python/tuple
+- 383
+- 382
+- 614
+: - - 414.05
+    - 207.9
+  - - 414.6
+    - 197.9
+? !!python/tuple
+- 383
+- 387
+- 608
+: - - 414.05
+    - 207.9
+  - - 420.95000000000005
+    - 216.10000000000002
+? !!python/tuple
+- 385
+- 384
+- 591
+: - - 401.05
+    - 215.3
+  - - 411.05
+    - 215.70000000000002
+? !!python/tuple
+- 386
+- 385
+- 592
+: - - 391.05
+    - 214.85000000000002
+  - - 401.05
+    - 215.3
+? !!python/tuple
+- 387
+- 388
+- 590
+: - - 420.95000000000005
+    - 216.10000000000002
+  - - 430.95000000000005
+    - 216.5
+? !!python/tuple
+- 388
+- 389
+- 589
+: - - 430.95000000000005
+    - 216.5
+  - - 440.95000000000005
+    - 216.95000000000002
+? !!python/tuple
+- 390
+- 390
+- 596
+: - - 447.35
+    - 212.5
+  - - 447.35
+    - 212.5
+? !!python/tuple
+- 390
+- 391
+- 611
+: - - 447.35
+    - 212.5
+  - - 447.85
+    - 202.5
+? !!python/tuple
+- 391
+- 98
+- 617
+: - - 447.85
+    - 202.5
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 392
+- 393
+- 623
+: - - 424.8
+    - 188.35000000000002
+  - - 434.8
+    - 190.4
+? !!python/tuple
+- 393
+- 98
+- 621
+: - - 434.8
+    - 190.4
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 394
+- 91
+- 636
+: - - 348.70000000000005
+    - 184.95000000000002
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 395
+- 394
+- 627
+: - - 348.25
+    - 194.95000000000002
+  - - 348.70000000000005
+    - 184.95000000000002
+? !!python/tuple
+- 396
+- 395
+- 616
+: - - 347.75
+    - 204.95000000000002
+  - - 348.25
+    - 194.95000000000002
+? !!python/tuple
+- 397
+- 398
+- 635
+: - - 359.5
+    - 175.3
+  - - 369.5
+    - 177.0
+? !!python/tuple
+- 398
+- 399
+- 634
+: - - 369.5
+    - 177.0
+  - - 379.5
+    - 179.05
+? !!python/tuple
+- 399
+- 402
+- 633
+: - - 379.5
+    - 179.05
+  - - 393.6
+    - 181.95000000000002
+? !!python/tuple
+- 401
+- 400
+- 624
+: - - 381.20000000000005
+    - 197.9
+  - - 381.70000000000005
+    - 187.9
+? !!python/tuple
+- 402
+- 403
+- 630
+: - - 393.6
+    - 181.95000000000002
+  - - 403.6
+    - 184.0
+? !!python/tuple
+- 403
+- 70
+- 628
+: - - 403.6
+    - 184.0
+  - - 415.25
+    - 187.35000000000002
+? !!python/tuple
+- 404
+- 67
+- 639
+: - - 315.15000000000003
+    - 183.35000000000002
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 405
+- 404
+- 629
+: - - 314.70000000000005
+    - 193.35000000000002
+  - - 315.15000000000003
+    - 183.35000000000002
+? !!python/tuple
+- 406
+- 405
+- 618
+: - - 314.20000000000005
+    - 203.35000000000002
+  - - 314.70000000000005
+    - 193.35000000000002
+? !!python/tuple
+- 407
+- 51
+- 641
+: - - 325.90000000000003
+    - 172.85000000000002
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 408
+- 41
+- 644
+: - - 282.6
+    - 181.25
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 409
+- 408
+- 631
+: - - 282.05
+    - 191.25
+  - - 282.6
+    - 181.25
+? !!python/tuple
+- 410
+- 409
+- 620
+: - - 281.5
+    - 201.25
+  - - 282.05
+    - 191.25
+? !!python/tuple
+- 411
+- 412
+- 645
+: - - 293.5
+    - 171.15
+  - - 303.5
+    - 171.65
+? !!python/tuple
+- 412
+- 67
+- 643
+: - - 303.5
+    - 171.65
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 413
+- 69
+- 648
+: - - 259.3
+    - 179.65
+  - - 260.65000000000003
+    - 169.20000000000002
+? !!python/tuple
+- 414
+- 413
+- 632
+: - - 258.6
+    - 189.65
+  - - 259.3
+    - 179.65
+? !!python/tuple
+- 415
+- 414
+- 622
+: - - 257.95
+    - 199.65
+  - - 258.6
+    - 189.65
+? !!python/tuple
+- 416
+- 41
+- 647
+: - - 271.15000000000003
+    - 170.0
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 417
+- 418
+- 653
+: - - 293.1
+    - 160.85000000000002
+  - - 303.1
+    - 163.0
+? !!python/tuple
+- 418
+- 419
+- 652
+: - - 303.1
+    - 163.0
+  - - 313.1
+    - 165.10000000000002
+? !!python/tuple
+- 419
+- 420
+- 651
+: - - 313.1
+    - 165.10000000000002
+  - - 333.1
+    - 169.3
+? !!python/tuple
+- 420
+- 61
+- 649
+: - - 333.1
+    - 169.3
+  - - 343.75
+    - 173.10000000000002
+? !!python/tuple
+- 421
+- 422
+- 658
+: - - 265.45
+    - 155.05
+  - - 276.05
+    - 157.20000000000002
+? !!python/tuple
+- 422
+- 71
+- 656
+: - - 276.05
+    - 157.20000000000002
+  - - 283.45
+    - 159.8
diff --git a/output_yaml/edges_high_level.yaml b/output_yaml/edges_high_level.yaml
new file mode 100644
index 0000000..bb1eb46
--- /dev/null
+++ b/output_yaml/edges_high_level.yaml
@@ -0,0 +1,5296 @@
+? !!python/tuple
+- 0
+- 66
+- 101
+: - - 394.8
+    - 456.1
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 0
+- 85
+- 100
+: - - 394.8
+    - 456.1
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 0
+- 228
+- 412
+: - - 394.8
+    - 456.1
+  - - 394.0
+    - 466.65000000000003
+? !!python/tuple
+- 0
+- 231
+- 413
+: - - 394.8
+    - 456.1
+  - - 405.35
+    - 456.95000000000005
+? !!python/tuple
+- 1
+- 28
+- 109
+: - - 262.8
+    - 444.3
+  - - 295.75
+    - 447.45000000000005
+? !!python/tuple
+- 1
+- 86
+- 108
+: - - 262.8
+    - 444.3
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 1
+- 248
+- 432
+: - - 262.8
+    - 444.3
+  - - 261.85
+    - 454.85
+? !!python/tuple
+- 1
+- 251
+- 433
+: - - 262.8
+    - 444.3
+  - - 273.35
+    - 445.25
+? !!python/tuple
+- 2
+- 2
+- 137
+: - - 368.90000000000003
+    - 366.5
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 2
+- 14
+- 127
+: - - 368.90000000000003
+    - 366.5
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 2
+- 15
+- 128
+: - - 368.90000000000003
+    - 366.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 2
+- 297
+- 512
+: - - 368.90000000000003
+    - 366.5
+  - - 368.05
+    - 377.05
+? !!python/tuple
+- 2
+- 300
+- 513
+: - - 368.90000000000003
+    - 366.5
+  - - 379.45000000000005
+    - 367.45000000000005
+? !!python/tuple
+- 2
+- 330
+- 532
+: - - 368.90000000000003
+    - 366.5
+  - - 370.35
+    - 349.05
+? !!python/tuple
+- 3
+- 3
+- 0
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 3
+- 3
+- 1
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 3
+- 3
+- 180
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 3
+- 3
+- 183
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 5
+- 5
+- 12
+: - - 241.5
+    - 586.1
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 5
+- 5
+- 220
+: - - 241.5
+    - 586.1
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 5
+- 42
+- 11
+: - - 241.5
+    - 586.1
+  - - 240.65
+    - 593.3000000000001
+? !!python/tuple
+- 5
+- 42
+- 219
+: - - 241.5
+    - 586.1
+  - - 240.65
+    - 593.3000000000001
+? !!python/tuple
+- 6
+- 6
+- 16
+: - - 218.0
+    - 576.9
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 6
+- 6
+- 251
+: - - 218.0
+    - 576.9
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 6
+- 21
+- 18
+: - - 218.0
+    - 576.9
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 6
+- 21
+- 230
+: - - 218.0
+    - 576.9
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 7
+- 4
+- 30
+: - - 345.3
+    - 568.1
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 7
+- 34
+- 31
+: - - 345.3
+    - 568.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 7
+- 34
+- 246
+: - - 345.3
+    - 568.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 7
+- 139
+- 245
+: - - 345.3
+    - 568.1
+  - - 344.55
+    - 578.65
+? !!python/tuple
+- 8
+- 24
+- 68
+: - - 363.20000000000005
+    - 530.65
+  - - 367.0
+    - 531.5500000000001
+? !!python/tuple
+- 8
+- 24
+- 308
+: - - 363.20000000000005
+    - 530.65
+  - - 367.0
+    - 531.5500000000001
+? !!python/tuple
+- 9
+- 8
+- 75
+: - - 350.55
+    - 525.8000000000001
+  - - 363.20000000000005
+    - 530.65
+? !!python/tuple
+- 9
+- 8
+- 316
+: - - 350.55
+    - 525.8000000000001
+  - - 363.20000000000005
+    - 530.65
+? !!python/tuple
+- 10
+- 38
+- 87
+: - - 347.75
+    - 500.90000000000003
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 10
+- 38
+- 363
+: - - 347.75
+    - 500.90000000000003
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 11
+- 26
+- 104
+: - - 328.85
+    - 450.6
+  - - 325.1
+    - 492.05
+? !!python/tuple
+- 11
+- 40
+- 105
+: - - 328.85
+    - 450.6
+  - - 361.85
+    - 453.5
+? !!python/tuple
+- 11
+- 238
+- 422
+: - - 328.85
+    - 450.6
+  - - 327.90000000000003
+    - 461.1
+? !!python/tuple
+- 11
+- 241
+- 423
+: - - 328.85
+    - 450.6
+  - - 339.40000000000003
+    - 451.55
+? !!python/tuple
+- 12
+- 12
+- 113
+: - - 431.1
+    - 417.6
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 12
+- 66
+- 112
+: - - 431.1
+    - 417.6
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 12
+- 262
+- 457
+: - - 431.1
+    - 417.6
+  - - 441.55
+    - 418.5
+? !!python/tuple
+- 12
+- 325
+- 475
+: - - 431.1
+    - 417.6
+  - - 432.05
+    - 406.8
+? !!python/tuple
+- 13
+- 0
+- 114
+: - - 398.20000000000005
+    - 415.0
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 13
+- 12
+- 115
+: - - 398.20000000000005
+    - 415.0
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 13
+- 15
+- 126
+: - - 398.20000000000005
+    - 415.0
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 13
+- 264
+- 461
+: - - 398.20000000000005
+    - 415.0
+  - - 397.35
+    - 425.5
+? !!python/tuple
+- 13
+- 267
+- 462
+: - - 398.20000000000005
+    - 415.0
+  - - 408.75
+    - 415.90000000000003
+? !!python/tuple
+- 14
+- 13
+- 117
+: - - 365.1
+    - 412.35
+  - - 398.20000000000005
+    - 415.0
+? !!python/tuple
+- 14
+- 40
+- 116
+: - - 365.1
+    - 412.35
+  - - 361.85
+    - 453.5
+? !!python/tuple
+- 14
+- 269
+- 466
+: - - 365.1
+    - 412.35
+  - - 364.3
+    - 422.90000000000003
+? !!python/tuple
+- 14
+- 272
+- 467
+: - - 365.1
+    - 412.35
+  - - 375.6
+    - 413.20000000000005
+? !!python/tuple
+- 15
+- 15
+- 135
+: - - 401.95000000000005
+    - 369.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 15
+- 15
+- 136
+: - - 401.95000000000005
+    - 369.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 15
+- 321
+- 507
+: - - 401.95000000000005
+    - 369.5
+  - - 418.05
+    - 370.85
+? !!python/tuple
+- 15
+- 328
+- 520
+: - - 401.95000000000005
+    - 369.5
+  - - 402.65000000000003
+    - 361.70000000000005
+? !!python/tuple
+- 16
+- 31
+- 131
+: - - 304.15000000000003
+    - 360.5
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 16
+- 52
+- 132
+: - - 304.15000000000003
+    - 360.5
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 16
+- 307
+- 522
+: - - 304.15000000000003
+    - 360.5
+  - - 303.15000000000003
+    - 371.05
+? !!python/tuple
+- 16
+- 310
+- 523
+: - - 304.15000000000003
+    - 360.5
+  - - 314.65000000000003
+    - 361.55
+? !!python/tuple
+- 17
+- 16
+- 139
+: - - 306.1
+    - 331.3
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 17
+- 17
+- 140
+: - - 306.1
+    - 331.3
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 17
+- 17
+- 545
+: - - 306.1
+    - 331.3
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 17
+- 333
+- 543
+: - - 306.1
+    - 331.3
+  - - 305.85
+    - 341.8
+? !!python/tuple
+- 18
+- 17
+- 142
+: - - 273.15000000000003
+    - 328.0
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 18
+- 88
+- 141
+: - - 273.15000000000003
+    - 328.0
+  - - 271.1
+    - 357.25
+? !!python/tuple
+- 18
+- 335
+- 547
+: - - 273.15000000000003
+    - 328.0
+  - - 272.35
+    - 338.55
+? !!python/tuple
+- 18
+- 337
+- 548
+: - - 273.15000000000003
+    - 328.0
+  - - 283.65000000000003
+    - 328.90000000000003
+? !!python/tuple
+- 19
+- 19
+- 150
+: - - 278.75
+    - 249.40000000000003
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 19
+- 20
+- 155
+: - - 278.75
+    - 249.40000000000003
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 19
+- 361
+- 578
+: - - 278.75
+    - 249.40000000000003
+  - - 289.15000000000003
+    - 249.90000000000003
+? !!python/tuple
+- 19
+- 375
+- 583
+: - - 278.75
+    - 249.40000000000003
+  - - 279.40000000000003
+    - 240.55
+? !!python/tuple
+- 20
+- 41
+- 168
+: - - 281.15000000000003
+    - 210.05
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 20
+- 49
+- 156
+: - - 281.15000000000003
+    - 210.05
+  - - 313.85
+    - 211.0
+? !!python/tuple
+- 20
+- 376
+- 604
+: - - 281.15000000000003
+    - 210.05
+  - - 291.05
+    - 210.35000000000002
+? !!python/tuple
+- 20
+- 410
+- 612
+: - - 281.15000000000003
+    - 210.05
+  - - 281.5
+    - 201.25
+? !!python/tuple
+- 21
+- 54
+- 14
+: - - 235.15
+    - 578.5
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 21
+- 54
+- 224
+: - - 235.15
+    - 578.5
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 22
+- 58
+- 44
+: - - 428.3
+    - 545.8000000000001
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 22
+- 58
+- 267
+: - - 428.3
+    - 545.8000000000001
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 24
+- 50
+- 73
+: - - 367.0
+    - 531.5500000000001
+  - - 434.95000000000005
+    - 537.45
+? !!python/tuple
+- 24
+- 50
+- 314
+: - - 367.0
+    - 531.5500000000001
+  - - 434.95000000000005
+    - 537.45
+? !!python/tuple
+- 24
+- 80
+- 64
+: - - 367.0
+    - 531.5500000000001
+  - - 416.95000000000005
+    - 536.1
+? !!python/tuple
+- 24
+- 159
+- 303
+: - - 367.0
+    - 531.5500000000001
+  - - 377.5
+    - 532.65
+? !!python/tuple
+- 25
+- 96
+- 65
+: - - 243.55
+    - 531.15
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 25
+- 163
+- 304
+: - - 243.55
+    - 531.15
+  - - 254.05
+    - 532.65
+? !!python/tuple
+- 26
+- 38
+- 92
+: - - 325.1
+    - 492.05
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 26
+- 201
+- 375
+: - - 325.1
+    - 492.05
+  - - 335.6
+    - 493.65000000000003
+? !!python/tuple
+- 27
+- 90
+- 153
+: - - 347.40000000000003
+    - 212.5
+  - - 380.5
+    - 214.0
+? !!python/tuple
+- 27
+- 91
+- 162
+: - - 347.40000000000003
+    - 212.5
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 27
+- 369
+- 597
+: - - 347.40000000000003
+    - 212.5
+  - - 357.90000000000003
+    - 213.4
+? !!python/tuple
+- 27
+- 396
+- 609
+: - - 347.40000000000003
+    - 212.5
+  - - 347.75
+    - 204.95000000000002
+? !!python/tuple
+- 28
+- 11
+- 107
+: - - 295.75
+    - 447.45000000000005
+  - - 328.85
+    - 450.6
+? !!python/tuple
+- 28
+- 39
+- 106
+: - - 295.75
+    - 447.45000000000005
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 28
+- 243
+- 427
+: - - 295.75
+    - 447.45000000000005
+  - - 294.90000000000003
+    - 457.95000000000005
+? !!python/tuple
+- 28
+- 246
+- 428
+: - - 295.75
+    - 447.45000000000005
+  - - 306.25
+    - 448.45000000000005
+? !!python/tuple
+- 29
+- 18
+- 145
+: - - 276.2
+    - 288.8
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 29
+- 19
+- 149
+: - - 276.2
+    - 288.8
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 29
+- 29
+- 146
+: - - 276.2
+    - 288.8
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 29
+- 341
+- 562
+: - - 276.2
+    - 288.8
+  - - 275.55
+    - 299.3
+? !!python/tuple
+- 29
+- 344
+- 563
+: - - 276.2
+    - 288.8
+  - - 286.7
+    - 289.3
+? !!python/tuple
+- 30
+- 11
+- 118
+: - - 332.75
+    - 409.55
+  - - 328.85
+    - 450.6
+? !!python/tuple
+- 30
+- 14
+- 119
+: - - 332.75
+    - 409.55
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 30
+- 274
+- 471
+: - - 332.75
+    - 409.55
+  - - 331.75
+    - 420.1
+? !!python/tuple
+- 30
+- 277
+- 472
+: - - 332.75
+    - 409.55
+  - - 343.3
+    - 410.5
+? !!python/tuple
+- 31
+- 28
+- 120
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 295.75
+    - 447.45000000000005
+? !!python/tuple
+- 31
+- 30
+- 121
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 31
+- 279
+- 476
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 298.75
+    - 416.70000000000005
+? !!python/tuple
+- 31
+- 282
+- 477
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 310.40000000000003
+    - 407.35
+? !!python/tuple
+- 32
+- 1
+- 122
+: - - 266.2
+    - 403.15000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 32
+- 31
+- 123
+: - - 266.2
+    - 403.15000000000003
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 32
+- 284
+- 480
+: - - 266.2
+    - 403.15000000000003
+  - - 265.40000000000003
+    - 413.65000000000003
+? !!python/tuple
+- 32
+- 287
+- 481
+: - - 266.2
+    - 403.15000000000003
+  - - 276.65000000000003
+    - 404.05
+? !!python/tuple
+- 33
+- 33
+- 7
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 33
+- 33
+- 9
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 33
+- 33
+- 212
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 33
+- 33
+- 214
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 34
+- 34
+- 27
+: - - 359.0
+    - 570.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 34
+- 34
+- 29
+: - - 359.0
+    - 570.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 34
+- 34
+- 241
+: - - 359.0
+    - 570.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 34
+- 137
+- 244
+: - - 359.0
+    - 570.1
+  - - 368.95000000000005
+    - 570.4
+? !!python/tuple
+- 35
+- 22
+- 47
+: - - 429.8
+    - 540.35
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 35
+- 22
+- 277
+: - - 429.8
+    - 540.35
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 37
+- 21
+- 63
+: - - 235.8
+    - 532.1
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 37
+- 25
+- 66
+: - - 235.8
+    - 532.1
+  - - 243.55
+    - 531.15
+? !!python/tuple
+- 37
+- 25
+- 306
+: - - 235.8
+    - 532.1
+  - - 243.55
+    - 531.15
+? !!python/tuple
+- 37
+- 155
+- 301
+: - - 235.8
+    - 532.1
+  - - 239.4
+    - 541.0
+? !!python/tuple
+- 38
+- 75
+- 98
+: - - 356.15000000000003
+    - 498.95000000000005
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 38
+- 225
+- 372
+: - - 356.15000000000003
+    - 498.95000000000005
+  - - 399.40000000000003
+    - 504.5
+? !!python/tuple
+- 39
+- 26
+- 95
+: - - 291.85
+    - 489.0
+  - - 325.1
+    - 492.05
+? !!python/tuple
+- 39
+- 212
+- 381
+: - - 291.85
+    - 489.0
+  - - 302.3
+    - 490.6
+? !!python/tuple
+- 40
+- 0
+- 103
+: - - 361.85
+    - 453.5
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 40
+- 72
+- 102
+: - - 361.85
+    - 453.5
+  - - 358.45000000000005
+    - 495.6
+? !!python/tuple
+- 40
+- 233
+- 417
+: - - 361.85
+    - 453.5
+  - - 360.90000000000003
+    - 464.0
+? !!python/tuple
+- 40
+- 236
+- 418
+: - - 361.85
+    - 453.5
+  - - 372.35
+    - 454.3
+? !!python/tuple
+- 41
+- 67
+- 169
+: - - 283.0
+    - 170.75
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 41
+- 71
+- 172
+: - - 283.0
+    - 170.75
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 41
+- 71
+- 654
+: - - 283.0
+    - 170.75
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 41
+- 411
+- 646
+: - - 283.0
+    - 170.75
+  - - 293.5
+    - 171.15
+? !!python/tuple
+- 42
+- 4
+- 8
+: - - 240.65
+    - 593.3000000000001
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 42
+- 64
+- 6
+: - - 240.65
+    - 593.3000000000001
+  - - 253.3
+    - 602.25
+? !!python/tuple
+- 42
+- 105
+- 213
+: - - 240.65
+    - 593.3000000000001
+  - - 234.05
+    - 602.45
+? !!python/tuple
+- 43
+- 94
+- 61
+: - - 361.20000000000005
+    - 533.0500000000001
+  - - 408.45000000000005
+    - 546.5
+? !!python/tuple
+- 43
+- 151
+- 296
+: - - 361.20000000000005
+    - 533.0500000000001
+  - - 370.6
+    - 542.4
+? !!python/tuple
+- 44
+- 183
+- 344
+: - - 285.8
+    - 507.80000000000007
+  - - 285.35
+    - 518.3000000000001
+? !!python/tuple
+- 45
+- 45
+- 4
+: - - 444.25
+    - 576.9
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 45
+- 45
+- 17
+: - - 444.25
+    - 576.9
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 45
+- 45
+- 229
+: - - 444.25
+    - 576.9
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 46
+- 56
+- 23
+: - - 405.95000000000005
+    - 573.4
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 46
+- 56
+- 235
+: - - 405.95000000000005
+    - 573.4
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 47
+- 47
+- 35
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 36
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 37
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 38
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 39
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 42
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 45
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 260
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 48
+- 44
+- 85
+: - - 276.85
+    - 501.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 48
+- 44
+- 356
+: - - 276.85
+    - 501.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 48
+- 59
+- 86
+: - - 276.85
+    - 501.45000000000005
+  - - 287.05
+    - 502.45000000000005
+? !!python/tuple
+- 48
+- 59
+- 357
+: - - 276.85
+    - 501.45000000000005
+  - - 287.05
+    - 502.45000000000005
+? !!python/tuple
+- 49
+- 27
+- 154
+: - - 313.85
+    - 211.0
+  - - 347.40000000000003
+    - 212.5
+? !!python/tuple
+- 49
+- 67
+- 165
+: - - 313.85
+    - 211.0
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 49
+- 371
+- 600
+: - - 313.85
+    - 211.0
+  - - 324.35
+    - 211.9
+? !!python/tuple
+- 49
+- 406
+- 610
+: - - 313.85
+    - 211.0
+  - - 314.20000000000005
+    - 203.35000000000002
+? !!python/tuple
+- 50
+- 23
+- 53
+: - - 434.95000000000005
+    - 537.45
+  - - 441.0
+    - 538.15
+? !!python/tuple
+- 50
+- 23
+- 284
+: - - 434.95000000000005
+    - 537.45
+  - - 441.0
+    - 538.15
+? !!python/tuple
+- 52
+- 2
+- 130
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 52
+- 30
+- 129
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 52
+- 52
+- 138
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 52
+- 302
+- 517
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 336.35
+    - 374.15000000000003
+? !!python/tuple
+- 52
+- 305
+- 518
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 347.8
+    - 364.6
+? !!python/tuple
+- 53
+- 23
+- 59
+: - - 442.35
+    - 535.35
+  - - 441.0
+    - 538.15
+? !!python/tuple
+- 53
+- 23
+- 291
+: - - 442.35
+    - 535.35
+  - - 441.0
+    - 538.15
+? !!python/tuple
+- 53
+- 47
+- 58
+: - - 442.35
+    - 535.35
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 53
+- 47
+- 290
+: - - 442.35
+    - 535.35
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 54
+- 5
+- 13
+: - - 237.9
+    - 579.0500000000001
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 54
+- 5
+- 221
+: - - 237.9
+    - 579.0500000000001
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 54
+- 54
+- 22
+: - - 237.9
+    - 579.0500000000001
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 54
+- 54
+- 234
+: - - 237.9
+    - 579.0500000000001
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 55
+- 45
+- 19
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 55
+- 45
+- 231
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 55
+- 55
+- 5
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 55
+- 55
+- 15
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 55
+- 55
+- 227
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 55
+- 62
+- 28
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 56
+- 55
+- 21
+: - - 423.45000000000005
+    - 576.1
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 56
+- 55
+- 233
+: - - 423.45000000000005
+    - 576.1
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 56
+- 56
+- 20
+: - - 423.45000000000005
+    - 576.1
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 56
+- 56
+- 232
+: - - 423.45000000000005
+    - 576.1
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 57
+- 46
+- 25
+: - - 391.3
+    - 573.1
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 57
+- 46
+- 237
+: - - 391.3
+    - 573.1
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 57
+- 57
+- 24
+: - - 391.3
+    - 573.1
+  - - 391.3
+    - 573.1
+? !!python/tuple
+- 57
+- 57
+- 236
+: - - 391.3
+    - 573.1
+  - - 391.3
+    - 573.1
+? !!python/tuple
+- 58
+- 58
+- 40
+: - - 432.75
+    - 548.65
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 58
+- 58
+- 262
+: - - 432.75
+    - 548.65
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 58
+- 62
+- 41
+: - - 432.75
+    - 548.65
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 58
+- 146
+- 263
+: - - 432.75
+    - 548.65
+  - - 445.75
+    - 556.65
+? !!python/tuple
+- 59
+- 44
+- 83
+: - - 287.05
+    - 502.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 59
+- 44
+- 353
+: - - 287.05
+    - 502.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 59
+- 63
+- 84
+: - - 287.05
+    - 502.45000000000005
+  - - 334.90000000000003
+    - 527.1
+? !!python/tuple
+- 59
+- 190
+- 355
+: - - 287.05
+    - 502.45000000000005
+  - - 297.20000000000005
+    - 502.80000000000007
+? !!python/tuple
+- 60
+- 96
+- 90
+: - - 246.8
+    - 498.55
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 60
+- 195
+- 368
+: - - 246.8
+    - 498.55
+  - - 256.8
+    - 498.85
+? !!python/tuple
+- 61
+- 61
+- 164
+: - - 343.75
+    - 173.10000000000002
+  - - 343.75
+    - 173.10000000000002
+? !!python/tuple
+- 61
+- 61
+- 638
+: - - 343.75
+    - 173.10000000000002
+  - - 343.75
+    - 173.10000000000002
+? !!python/tuple
+- 61
+- 91
+- 166
+: - - 343.75
+    - 173.10000000000002
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 61
+- 91
+- 640
+: - - 343.75
+    - 173.10000000000002
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 62
+- 45
+- 26
+: - - 444.15000000000003
+    - 570.75
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 62
+- 45
+- 240
+: - - 444.15000000000003
+    - 570.75
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 62
+- 62
+- 32
+: - - 444.15000000000003
+    - 570.75
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 63
+- 63
+- 76
+: - - 334.90000000000003
+    - 527.1
+  - - 334.90000000000003
+    - 527.1
+? !!python/tuple
+- 63
+- 63
+- 319
+: - - 334.90000000000003
+    - 527.1
+  - - 334.90000000000003
+    - 527.1
+? !!python/tuple
+- 63
+- 92
+- 71
+: - - 334.90000000000003
+    - 527.1
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 63
+- 92
+- 312
+: - - 334.90000000000003
+    - 527.1
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 63
+- 97
+- 72
+: - - 334.90000000000003
+    - 527.1
+  - - 341.35
+    - 527.7
+? !!python/tuple
+- 63
+- 97
+- 313
+: - - 334.90000000000003
+    - 527.1
+  - - 341.35
+    - 527.7
+? !!python/tuple
+- 64
+- 93
+- 10
+: - - 253.3
+    - 602.25
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 64
+- 125
+- 209
+: - - 253.3
+    - 602.25
+  - - 263.0
+    - 594.1
+? !!python/tuple
+- 64
+- 130
+- 205
+: - - 253.3
+    - 602.25
+  - - 260.65000000000003
+    - 604.7
+? !!python/tuple
+- 65
+- 6
+- 93
+: - - 232.50047302246094
+    - 490.51361083984375
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 65
+- 60
+- 94
+: - - 232.50047302246094
+    - 490.51361083984375
+  - - 246.8
+    - 498.55
+? !!python/tuple
+- 65
+- 60
+- 378
+: - - 232.47743225097656
+    - 490.1767883300781
+  - - 246.8
+    - 498.55
+? !!python/tuple
+- 65
+- 65
+- 110
+: - - 232.50047302246094
+    - 490.51361083984375
+  - - 232.50047302246094
+    - 490.51361083984375
+? !!python/tuple
+- 65
+- 86
+- 97
+: - - 232.50047302246094
+    - 490.51361083984375
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 65
+- 216
+- 386
+: - - 232.47743225097656
+    - 490.1767883300781
+  - - 242.25
+    - 485.15000000000003
+? !!python/tuple
+- 66
+- 66
+- 99
+: - - 427.90000000000003
+    - 458.8
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 66
+- 217
+- 407
+: - - 427.90000000000003
+    - 458.8
+  - - 427.0
+    - 469.35
+? !!python/tuple
+- 66
+- 226
+- 408
+: - - 427.90000000000003
+    - 458.8
+  - - 438.45000000000005
+    - 459.65000000000003
+? !!python/tuple
+- 67
+- 51
+- 167
+: - - 315.75
+    - 172.85000000000002
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 67
+- 407
+- 642
+: - - 315.75
+    - 172.85000000000002
+  - - 325.90000000000003
+    - 172.85000000000002
+? !!python/tuple
+- 68
+- 35
+- 52
+: - - 430.70000000000005
+    - 537.3000000000001
+  - - 429.8
+    - 540.35
+? !!python/tuple
+- 68
+- 35
+- 283
+: - - 430.70000000000005
+    - 537.3000000000001
+  - - 429.8
+    - 540.35
+? !!python/tuple
+- 68
+- 50
+- 54
+: - - 430.70000000000005
+    - 537.3000000000001
+  - - 434.95000000000005
+    - 537.45
+? !!python/tuple
+- 68
+- 50
+- 285
+: - - 430.70000000000005
+    - 537.3000000000001
+  - - 434.95000000000005
+    - 537.45
+? !!python/tuple
+- 69
+- 41
+- 171
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 69
+- 71
+- 174
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 69
+- 416
+- 650
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 271.15000000000003
+    - 170.0
+? !!python/tuple
+- 69
+- 421
+- 657
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 265.45
+    - 155.05
+? !!python/tuple
+- 70
+- 98
+- 160
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 70
+- 98
+- 161
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 70
+- 392
+- 626
+: - - 415.25
+    - 187.35000000000002
+  - - 424.8
+    - 188.35000000000002
+? !!python/tuple
+- 71
+- 51
+- 173
+: - - 283.45
+    - 159.8
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 71
+- 417
+- 655
+: - - 283.45
+    - 159.8
+  - - 293.1
+    - 160.85000000000002
+? !!python/tuple
+- 72
+- 85
+- 91
+: - - 358.45000000000005
+    - 495.6
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 72
+- 199
+- 373
+: - - 358.45000000000005
+    - 495.6
+  - - 368.95000000000005
+    - 496.55
+? !!python/tuple
+- 73
+- 22
+- 46
+: - - 427.3
+    - 540.75
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 73
+- 22
+- 276
+: - - 427.3
+    - 540.75
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 73
+- 35
+- 48
+: - - 427.3
+    - 540.75
+  - - 429.8
+    - 540.35
+? !!python/tuple
+- 73
+- 35
+- 278
+: - - 427.3
+    - 540.75
+  - - 429.8
+    - 540.35
+? !!python/tuple
+- 74
+- 7
+- 60
+: - - 350.15000000000003
+    - 533.2
+  - - 345.3
+    - 568.1
+? !!python/tuple
+- 74
+- 43
+- 62
+: - - 350.15000000000003
+    - 533.2
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 74
+- 43
+- 298
+: - - 350.15000000000003
+    - 533.2
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 74
+- 149
+- 294
+: - - 350.15000000000003
+    - 533.2
+  - - 349.3
+    - 543.7
+? !!python/tuple
+- 75
+- 53
+- 77
+: - - 434.6
+    - 519.35
+  - - 442.35
+    - 535.35
+? !!python/tuple
+- 75
+- 53
+- 325
+: - - 434.6
+    - 519.35
+  - - 442.35
+    - 535.35
+? !!python/tuple
+- 76
+- 10
+- 89
+: - - 345.05
+    - 498.20000000000005
+  - - 347.75
+    - 500.90000000000003
+? !!python/tuple
+- 76
+- 10
+- 366
+: - - 345.05
+    - 498.20000000000005
+  - - 347.75
+    - 500.90000000000003
+? !!python/tuple
+- 76
+- 84
+- 82
+: - - 345.05
+    - 498.20000000000005
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 76
+- 194
+- 365
+: - - 345.05
+    - 498.20000000000005
+  - - 343.85
+    - 511.6
+? !!python/tuple
+- 77
+- 1
+- 111
+: - - 227.5
+    - 441.15000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 77
+- 253
+- 437
+: - - 227.5
+    - 441.15000000000003
+  - - 226.10000000000002
+    - 451.6
+? !!python/tuple
+- 77
+- 257
+- 438
+: - - 227.5
+    - 441.15000000000003
+  - - 238.0
+    - 441.90000000000003
+? !!python/tuple
+- 78
+- 18
+- 144
+: - - 242.60000000000002
+    - 325.3
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 78
+- 78
+- 143
+: - - 242.60000000000002
+    - 325.3
+  - - 242.60000000000002
+    - 325.3
+? !!python/tuple
+- 78
+- 78
+- 551
+: - - 242.60000000000002
+    - 325.3
+  - - 242.60000000000002
+    - 325.3
+? !!python/tuple
+- 78
+- 339
+- 552
+: - - 242.60000000000002
+    - 325.3
+  - - 253.10000000000002
+    - 326.05
+? !!python/tuple
+- 79
+- 20
+- 158
+: - - 257.90000000000003
+    - 208.75
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 79
+- 69
+- 170
+: - - 257.90000000000003
+    - 208.75
+  - - 260.65000000000003
+    - 169.20000000000002
+? !!python/tuple
+- 79
+- 381
+- 607
+: - - 257.90000000000003
+    - 208.75
+  - - 268.40000000000003
+    - 209.25
+? !!python/tuple
+- 79
+- 415
+- 613
+: - - 257.90000000000003
+    - 208.75
+  - - 257.95
+    - 199.65
+? !!python/tuple
+- 80
+- 36
+- 57
+: - - 416.95000000000005
+    - 536.1
+  - - 418.45000000000005
+    - 539.7
+? !!python/tuple
+- 80
+- 36
+- 288
+: - - 416.95000000000005
+    - 536.1
+  - - 418.45000000000005
+    - 539.7
+? !!python/tuple
+- 80
+- 95
+- 56
+: - - 416.95000000000005
+    - 536.1
+  - - 416.0
+    - 539.15
+? !!python/tuple
+- 80
+- 95
+- 287
+: - - 416.95000000000005
+    - 536.1
+  - - 416.0
+    - 539.15
+? !!python/tuple
+- 81
+- 81
+- 70
+: - - 342.35
+    - 567.25
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 82
+- 68
+- 55
+: - - 427.35
+    - 537.4
+  - - 430.70000000000005
+    - 537.3000000000001
+? !!python/tuple
+- 82
+- 68
+- 286
+: - - 427.35
+    - 537.4
+  - - 430.70000000000005
+    - 537.3000000000001
+? !!python/tuple
+- 82
+- 73
+- 51
+: - - 427.35
+    - 537.4
+  - - 427.3
+    - 540.75
+? !!python/tuple
+- 82
+- 73
+- 282
+: - - 427.35
+    - 537.4
+  - - 427.3
+    - 540.75
+? !!python/tuple
+- 83
+- 43
+- 69
+: - - 350.25
+    - 530.6
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 83
+- 43
+- 309
+: - - 350.25
+    - 530.6
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 83
+- 74
+- 67
+: - - 350.25
+    - 530.6
+  - - 350.15000000000003
+    - 533.2
+? !!python/tuple
+- 83
+- 74
+- 307
+: - - 350.25
+    - 530.6
+  - - 350.15000000000003
+    - 533.2
+? !!python/tuple
+- 84
+- 9
+- 78
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 84
+- 9
+- 327
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 84
+- 75
+- 79
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 84
+- 75
+- 80
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 84
+- 84
+- 88
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 85
+- 222
+- 367
+: - - 391.45000000000005
+    - 497.90000000000003
+  - - 405.6
+    - 499.70000000000005
+? !!python/tuple
+- 86
+- 39
+- 96
+: - - 258.95
+    - 486.1
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 86
+- 214
+- 385
+: - - 258.95
+    - 486.1
+  - - 269.45
+    - 487.70000000000005
+? !!python/tuple
+- 87
+- 32
+- 125
+: - - 230.9
+    - 400.35
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 87
+- 77
+- 124
+: - - 230.9
+    - 400.35
+  - - 227.5
+    - 441.15000000000003
+? !!python/tuple
+- 87
+- 289
+- 484
+: - - 230.9
+    - 400.35
+  - - 229.65
+    - 410.85
+? !!python/tuple
+- 87
+- 292
+- 486
+: - - 230.9
+    - 400.35
+  - - 241.45000000000002
+    - 401.05
+? !!python/tuple
+- 88
+- 16
+- 134
+: - - 271.1
+    - 357.25
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 88
+- 32
+- 133
+: - - 271.1
+    - 357.25
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 88
+- 312
+- 526
+: - - 271.1
+    - 357.25
+  - - 269.25
+    - 367.70000000000005
+? !!python/tuple
+- 88
+- 315
+- 527
+: - - 271.1
+    - 357.25
+  - - 281.6
+    - 358.45000000000005
+? !!python/tuple
+- 89
+- 19
+- 152
+: - - 248.75
+    - 247.10000000000002
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 89
+- 79
+- 157
+: - - 248.75
+    - 247.10000000000002
+  - - 257.90000000000003
+    - 208.75
+? !!python/tuple
+- 89
+- 99
+- 151
+: - - 248.75
+    - 247.10000000000002
+  - - 241.25
+    - 286.2
+? !!python/tuple
+- 89
+- 364
+- 581
+: - - 248.75
+    - 247.10000000000002
+  - - 245.4
+    - 257.55
+? !!python/tuple
+- 89
+- 367
+- 582
+: - - 248.75
+    - 247.10000000000002
+  - - 259.3
+    - 248.2
+? !!python/tuple
+- 89
+- 380
+- 584
+: - - 248.75
+    - 247.10000000000002
+  - - 250.45
+    - 239.20000000000002
+? !!python/tuple
+- 90
+- 386
+- 593
+: - - 380.5
+    - 214.0
+  - - 391.05
+    - 214.85000000000002
+? !!python/tuple
+- 90
+- 401
+- 615
+: - - 380.5
+    - 214.0
+  - - 381.20000000000005
+    - 197.9
+? !!python/tuple
+- 91
+- 70
+- 163
+: - - 349.35
+    - 174.45000000000002
+  - - 415.25
+    - 187.35000000000002
+? !!python/tuple
+- 91
+- 397
+- 637
+: - - 349.35
+    - 174.45000000000002
+  - - 359.5
+    - 175.3
+? !!python/tuple
+- 92
+- 81
+- 34
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 92
+- 81
+- 248
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 92
+- 92
+- 33
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 92
+- 92
+- 247
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 93
+- 4
+- 2
+: - - 316.95000000000005
+    - 618.75
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 93
+- 93
+- 3
+: - - 316.95000000000005
+    - 618.75
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 93
+- 100
+- 195
+: - - 316.95000000000005
+    - 618.75
+  - - 327.40000000000003
+    - 621.5
+? !!python/tuple
+- 94
+- 22
+- 50
+: - - 408.45000000000005
+    - 546.5
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 94
+- 22
+- 280
+: - - 408.45000000000005
+    - 546.5
+  - - 428.3
+    - 545.8000000000001
+? !!python/tuple
+- 94
+- 46
+- 43
+: - - 408.45000000000005
+    - 546.5
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 94
+- 147
+- 266
+: - - 408.45000000000005
+    - 546.5
+  - - 407.45000000000005
+    - 557.0
+? !!python/tuple
+- 95
+- 95
+- 49
+: - - 416.0
+    - 539.15
+  - - 416.0
+    - 539.15
+? !!python/tuple
+- 95
+- 95
+- 279
+: - - 416.0
+    - 539.15
+  - - 416.0
+    - 539.15
+? !!python/tuple
+- 96
+- 44
+- 81
+: - - 263.7
+    - 533.15
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 96
+- 185
+- 297
+: - - 263.7
+    - 533.15
+  - - 280.35
+    - 535.15
+? !!python/tuple
+- 97
+- 9
+- 74
+: - - 341.35
+    - 527.7
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 97
+- 9
+- 315
+: - - 341.35
+    - 527.7
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 97
+- 164
+- 311
+: - - 341.35
+    - 527.7
+  - - 338.6
+    - 537.6
+? !!python/tuple
+- 98
+- 98
+- 159
+: - - 448.25
+    - 194.60000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 98
+- 98
+- 619
+: - - 448.25
+    - 194.60000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 99
+- 29
+- 148
+: - - 241.25
+    - 286.2
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 99
+- 87
+- 147
+: - - 241.25
+    - 286.2
+  - - 230.9
+    - 400.35
+? !!python/tuple
+- 99
+- 347
+- 566
+: - - 241.25
+    - 286.2
+  - - 239.70000000000002
+    - 296.65000000000003
+? !!python/tuple
+- 99
+- 356
+- 567
+: - - 241.25
+    - 286.2
+  - - 251.7
+    - 286.90000000000003
+? !!python/tuple
+- 100
+- 4
+- 191
+: - - 327.40000000000003
+    - 621.5
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 101
+- 102
+- 204
+: - - 312.55
+    - 602.4
+  - - 318.15000000000003
+    - 611.2
+? !!python/tuple
+- 102
+- 93
+- 199
+: - - 318.15000000000003
+    - 611.2
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 103
+- 103
+- 210
+: - - 446.05
+    - 595.9
+  - - 446.05
+    - 595.9
+? !!python/tuple
+- 104
+- 64
+- 206
+: - - 243.8
+    - 601.65
+  - - 253.3
+    - 602.25
+? !!python/tuple
+- 104
+- 104
+- 211
+: - - 243.8
+    - 601.65
+  - - 243.8
+    - 601.65
+? !!python/tuple
+- 105
+- 106
+- 203
+: - - 234.05
+    - 602.45
+  - - 233.10000000000002
+    - 612.45
+? !!python/tuple
+- 106
+- 107
+- 198
+: - - 233.10000000000002
+    - 612.45
+  - - 237.45000000000002
+    - 619.3000000000001
+? !!python/tuple
+- 107
+- 108
+- 194
+: - - 237.45000000000002
+    - 619.3000000000001
+  - - 247.45
+    - 620.2
+? !!python/tuple
+- 108
+- 109
+- 193
+: - - 247.45
+    - 620.2
+  - - 257.45
+    - 621.1500000000001
+? !!python/tuple
+- 109
+- 110
+- 192
+: - - 257.45
+    - 621.1500000000001
+  - - 267.45
+    - 622.1
+? !!python/tuple
+- 110
+- 111
+- 190
+: - - 267.45
+    - 622.1
+  - - 277.45
+    - 623.0500000000001
+? !!python/tuple
+- 111
+- 112
+- 187
+: - - 277.45
+    - 623.0500000000001
+  - - 287.45
+    - 624.0
+? !!python/tuple
+- 112
+- 113
+- 185
+: - - 287.45
+    - 624.0
+  - - 292.25
+    - 629.9000000000001
+? !!python/tuple
+- 113
+- 114
+- 179
+: - - 292.25
+    - 629.9000000000001
+  - - 302.25
+    - 631.0
+? !!python/tuple
+- 114
+- 115
+- 178
+: - - 302.25
+    - 631.0
+  - - 312.25
+    - 632.0500000000001
+? !!python/tuple
+- 115
+- 116
+- 177
+: - - 312.25
+    - 632.0500000000001
+  - - 322.25
+    - 633.1
+? !!python/tuple
+- 116
+- 117
+- 176
+: - - 322.25
+    - 633.1
+  - - 332.25
+    - 634.1
+? !!python/tuple
+- 117
+- 118
+- 175
+: - - 332.25
+    - 634.1
+  - - 340.90000000000003
+    - 633.1500000000001
+? !!python/tuple
+- 119
+- 118
+- 189
+: - - 351.6
+    - 622.4000000000001
+  - - 340.90000000000003
+    - 633.1500000000001
+? !!python/tuple
+- 119
+- 120
+- 188
+: - - 351.6
+    - 622.4000000000001
+  - - 361.6
+    - 623.3000000000001
+? !!python/tuple
+- 120
+- 121
+- 186
+: - - 361.6
+    - 623.3000000000001
+  - - 368.1
+    - 627.85
+? !!python/tuple
+- 121
+- 121
+- 181
+: - - 368.1
+    - 627.85
+  - - 368.1
+    - 627.85
+? !!python/tuple
+- 122
+- 123
+- 184
+: - - 382.5
+    - 624.8000000000001
+  - - 392.5
+    - 625.6500000000001
+? !!python/tuple
+- 123
+- 3
+- 182
+: - - 392.5
+    - 625.6500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 124
+- 126
+- 218
+: - - 273.0
+    - 586.9
+  - - 283.0
+    - 587.65
+? !!python/tuple
+- 125
+- 124
+- 217
+: - - 263.0
+    - 594.1
+  - - 273.0
+    - 586.9
+? !!python/tuple
+- 126
+- 127
+- 216
+: - - 283.0
+    - 587.65
+  - - 285.90000000000003
+    - 597.25
+? !!python/tuple
+- 127
+- 128
+- 208
+: - - 285.90000000000003
+    - 597.25
+  - - 287.85
+    - 607.25
+? !!python/tuple
+- 129
+- 131
+- 201
+: - - 270.65000000000003
+    - 606.95
+  - - 296.85
+    - 613.45
+? !!python/tuple
+- 130
+- 129
+- 202
+: - - 260.65000000000003
+    - 604.7
+  - - 270.65000000000003
+    - 606.95
+? !!python/tuple
+- 131
+- 132
+- 197
+: - - 296.85
+    - 613.45
+  - - 306.85
+    - 616.45
+? !!python/tuple
+- 132
+- 93
+- 196
+: - - 306.85
+    - 616.45
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 133
+- 6
+- 228
+: - - 207.55
+    - 580.4
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 134
+- 133
+- 222
+: - - 197.55
+    - 579.4
+  - - 207.55
+    - 580.4
+? !!python/tuple
+- 135
+- 134
+- 225
+: - - 187.55
+    - 578.4
+  - - 197.55
+    - 579.4
+? !!python/tuple
+- 135
+- 135
+- 226
+: - - 187.55
+    - 578.4
+  - - 187.55
+    - 578.4
+? !!python/tuple
+- 136
+- 62
+- 243
+: - - 433.25
+    - 569.6
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 137
+- 137
+- 242
+: - - 368.95000000000005
+    - 570.4
+  - - 368.95000000000005
+    - 570.4
+? !!python/tuple
+- 138
+- 57
+- 238
+: - - 383.45000000000005
+    - 571.75
+  - - 391.3
+    - 573.1
+? !!python/tuple
+- 139
+- 140
+- 223
+: - - 344.55
+    - 578.65
+  - - 343.6
+    - 588.65
+? !!python/tuple
+- 140
+- 141
+- 215
+: - - 343.6
+    - 588.65
+  - - 342.65000000000003
+    - 598.65
+? !!python/tuple
+- 141
+- 142
+- 207
+: - - 342.65000000000003
+    - 598.65
+  - - 341.70000000000005
+    - 608.6500000000001
+? !!python/tuple
+- 142
+- 4
+- 200
+: - - 341.70000000000005
+    - 608.6500000000001
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 143
+- 143
+- 249
+: - - 472.5
+    - 567.75
+  - - 472.5
+    - 567.75
+? !!python/tuple
+- 144
+- 144
+- 256
+: - - 473.70000000000005
+    - 553.2
+  - - 473.70000000000005
+    - 553.2
+? !!python/tuple
+- 144
+- 144
+- 261
+: - - 473.70000000000005
+    - 553.2
+  - - 473.70000000000005
+    - 553.2
+? !!python/tuple
+- 145
+- 145
+- 259
+: - - 455.75
+    - 550.4
+  - - 455.75
+    - 550.4
+? !!python/tuple
+- 146
+- 62
+- 254
+: - - 445.75
+    - 556.65
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 147
+- 46
+- 253
+: - - 407.45000000000005
+    - 557.0
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 148
+- 148
+- 265
+: - - 473.85
+    - 543.65
+  - - 473.85
+    - 543.65
+? !!python/tuple
+- 148
+- 148
+- 271
+: - - 473.85
+    - 543.65
+  - - 473.85
+    - 543.65
+? !!python/tuple
+- 149
+- 150
+- 270
+: - - 349.3
+    - 543.7
+  - - 348.35
+    - 553.7
+? !!python/tuple
+- 150
+- 7
+- 255
+: - - 348.35
+    - 553.7
+  - - 345.3
+    - 568.1
+? !!python/tuple
+- 151
+- 152
+- 273
+: - - 370.6
+    - 542.4
+  - - 380.6
+    - 543.35
+? !!python/tuple
+- 152
+- 153
+- 272
+: - - 380.6
+    - 543.35
+  - - 390.6
+    - 544.3000000000001
+? !!python/tuple
+- 153
+- 154
+- 269
+: - - 390.6
+    - 544.3000000000001
+  - - 400.6
+    - 545.2
+? !!python/tuple
+- 154
+- 94
+- 268
+: - - 400.6
+    - 545.2
+  - - 408.45000000000005
+    - 546.5
+? !!python/tuple
+- 155
+- 156
+- 274
+: - - 239.4
+    - 541.0
+  - - 238.4
+    - 551.0
+? !!python/tuple
+- 156
+- 157
+- 257
+: - - 238.4
+    - 551.0
+  - - 237.45000000000002
+    - 561.0
+? !!python/tuple
+- 157
+- 158
+- 250
+: - - 237.45000000000002
+    - 561.0
+  - - 236.45000000000002
+    - 571.0
+? !!python/tuple
+- 158
+- 21
+- 239
+: - - 236.45000000000002
+    - 571.0
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 159
+- 160
+- 299
+: - - 377.5
+    - 532.65
+  - - 387.5
+    - 533.5
+? !!python/tuple
+- 160
+- 161
+- 295
+: - - 387.5
+    - 533.5
+  - - 397.5
+    - 534.35
+? !!python/tuple
+- 161
+- 162
+- 293
+: - - 397.5
+    - 534.35
+  - - 407.5
+    - 535.2
+? !!python/tuple
+- 162
+- 80
+- 292
+: - - 407.5
+    - 535.2
+  - - 416.95000000000005
+    - 536.1
+? !!python/tuple
+- 163
+- 96
+- 300
+: - - 254.05
+    - 532.65
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 164
+- 165
+- 281
+: - - 338.6
+    - 537.6
+  - - 337.90000000000003
+    - 547.6
+? !!python/tuple
+- 165
+- 166
+- 264
+: - - 337.90000000000003
+    - 547.6
+  - - 337.55
+    - 557.6
+? !!python/tuple
+- 166
+- 81
+- 252
+: - - 337.55
+    - 557.6
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 167
+- 168
+- 332
+: - - 359.05
+    - 516.1
+  - - 366.65000000000003
+    - 519.45
+? !!python/tuple
+- 167
+- 174
+- 333
+: - - 359.05
+    - 516.1
+  - - 426.65000000000003
+    - 524.7
+? !!python/tuple
+- 168
+- 169
+- 326
+: - - 366.65000000000003
+    - 519.45
+  - - 376.65000000000003
+    - 520.35
+? !!python/tuple
+- 169
+- 170
+- 324
+: - - 376.65000000000003
+    - 520.35
+  - - 386.65000000000003
+    - 521.25
+? !!python/tuple
+- 170
+- 171
+- 322
+: - - 386.65000000000003
+    - 521.25
+  - - 396.65000000000003
+    - 522.2
+? !!python/tuple
+- 171
+- 172
+- 320
+: - - 396.65000000000003
+    - 522.2
+  - - 406.65000000000003
+    - 523.1
+? !!python/tuple
+- 172
+- 173
+- 318
+: - - 406.65000000000003
+    - 523.1
+  - - 416.65000000000003
+    - 524.0
+? !!python/tuple
+- 173
+- 174
+- 317
+: - - 416.65000000000003
+    - 524.0
+  - - 426.65000000000003
+    - 524.7
+? !!python/tuple
+- 175
+- 84
+- 342
+: - - 352.70000000000005
+    - 509.9
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 175
+- 176
+- 343
+: - - 352.70000000000005
+    - 509.9
+  - - 364.90000000000003
+    - 511.20000000000005
+? !!python/tuple
+- 176
+- 177
+- 340
+: - - 364.90000000000003
+    - 511.20000000000005
+  - - 374.90000000000003
+    - 512.35
+? !!python/tuple
+- 177
+- 178
+- 337
+: - - 374.90000000000003
+    - 512.35
+  - - 384.90000000000003
+    - 513.5
+? !!python/tuple
+- 178
+- 179
+- 336
+: - - 384.90000000000003
+    - 513.5
+  - - 394.90000000000003
+    - 514.65
+? !!python/tuple
+- 179
+- 180
+- 335
+: - - 394.90000000000003
+    - 514.65
+  - - 404.90000000000003
+    - 515.8000000000001
+? !!python/tuple
+- 180
+- 182
+- 334
+: - - 404.90000000000003
+    - 515.8000000000001
+  - - 413.40000000000003
+    - 516.75
+? !!python/tuple
+- 181
+- 75
+- 330
+: - - 423.40000000000003
+    - 517.9
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 182
+- 181
+- 331
+: - - 413.40000000000003
+    - 516.75
+  - - 423.40000000000003
+    - 517.9
+? !!python/tuple
+- 183
+- 184
+- 328
+: - - 285.35
+    - 518.3000000000001
+  - - 284.45
+    - 528.3000000000001
+? !!python/tuple
+- 185
+- 186
+- 310
+: - - 280.35
+    - 535.15
+  - - 288.05
+    - 536.0
+? !!python/tuple
+- 186
+- 187
+- 289
+: - - 288.05
+    - 536.0
+  - - 298.05
+    - 536.85
+? !!python/tuple
+- 187
+- 187
+- 302
+: - - 298.05
+    - 536.85
+  - - 298.05
+    - 536.85
+? !!python/tuple
+- 188
+- 189
+- 346
+: - - 338.8
+    - 505.55000000000007
+  - - 336.85
+    - 515.5
+? !!python/tuple
+- 188
+- 189
+- 347
+: - - 338.8
+    - 505.55000000000007
+  - - 336.85
+    - 515.5
+? !!python/tuple
+- 190
+- 191
+- 354
+: - - 297.20000000000005
+    - 502.80000000000007
+  - - 307.20000000000005
+    - 503.75
+? !!python/tuple
+- 191
+- 191
+- 352
+: - - 307.20000000000005
+    - 503.75
+  - - 307.20000000000005
+    - 503.75
+? !!python/tuple
+- 192
+- 193
+- 351
+: - - 319.6
+    - 504.20000000000005
+  - - 329.6
+    - 504.9
+? !!python/tuple
+- 193
+- 193
+- 349
+: - - 329.6
+    - 504.9
+  - - 329.6
+    - 504.9
+? !!python/tuple
+- 194
+- 84
+- 338
+: - - 343.85
+    - 511.6
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 195
+- 196
+- 364
+: - - 256.8
+    - 498.85
+  - - 266.8
+    - 500.40000000000003
+? !!python/tuple
+- 196
+- 48
+- 359
+: - - 266.8
+    - 500.40000000000003
+  - - 276.85
+    - 501.45000000000005
+? !!python/tuple
+- 196
+- 197
+- 358
+: - - 266.8
+    - 500.40000000000003
+  - - 265.85
+    - 510.35
+? !!python/tuple
+- 197
+- 198
+- 341
+: - - 265.85
+    - 510.35
+  - - 264.85
+    - 520.35
+? !!python/tuple
+- 198
+- 96
+- 323
+: - - 264.85
+    - 520.35
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 199
+- 200
+- 371
+: - - 368.95000000000005
+    - 496.55
+  - - 378.95000000000005
+    - 497.40000000000003
+? !!python/tuple
+- 200
+- 85
+- 369
+: - - 378.95000000000005
+    - 497.40000000000003
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 201
+- 38
+- 374
+: - - 335.6
+    - 493.65000000000003
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 202
+- 203
+- 370
+: - - 227.0
+    - 500.05
+  - - 222.4
+    - 510.9
+? !!python/tuple
+- 202
+- 209
+- 377
+: - - 227.0
+    - 500.05
+  - - 236.0
+    - 506.15
+? !!python/tuple
+- 203
+- 204
+- 339
+: - - 222.4
+    - 510.9
+  - - 221.4
+    - 520.9
+? !!python/tuple
+- 204
+- 37
+- 321
+: - - 221.4
+    - 520.9
+  - - 235.8
+    - 532.1
+? !!python/tuple
+- 205
+- 206
+- 305
+: - - 221.20000000000002
+    - 530.9
+  - - 219.45000000000002
+    - 540.9
+? !!python/tuple
+- 206
+- 207
+- 275
+: - - 219.45000000000002
+    - 540.9
+  - - 218.45000000000002
+    - 550.9
+? !!python/tuple
+- 207
+- 208
+- 258
+: - - 218.45000000000002
+    - 550.9
+  - - 217.5
+    - 560.9
+? !!python/tuple
+- 209
+- 60
+- 362
+: - - 236.0
+    - 506.15
+  - - 246.8
+    - 498.55
+? !!python/tuple
+- 210
+- 211
+- 345
+: - - 245.70000000000002
+    - 507.75
+  - - 244.9
+    - 517.75
+? !!python/tuple
+- 211
+- 25
+- 329
+: - - 244.9
+    - 517.75
+  - - 243.55
+    - 531.15
+? !!python/tuple
+- 212
+- 213
+- 379
+: - - 302.3
+    - 490.6
+  - - 312.3
+    - 491.5
+? !!python/tuple
+- 212
+- 247
+- 659
+: - - 302.533203125
+    - 490.032958984375
+  - - 316.3983154296875
+    - 449.4606018066406
+? !!python/tuple
+- 213
+- 26
+- 376
+: - - 312.3
+    - 491.5
+  - - 325.1
+    - 492.05
+? !!python/tuple
+- 214
+- 215
+- 383
+: - - 269.45
+    - 487.70000000000005
+  - - 279.45
+    - 488.6
+? !!python/tuple
+- 215
+- 39
+- 382
+: - - 279.45
+    - 488.6
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 216
+- 86
+- 387
+: - - 242.25
+    - 485.15000000000003
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 217
+- 218
+- 398
+: - - 427.0
+    - 469.35
+  - - 426.20000000000005
+    - 479.35
+? !!python/tuple
+- 218
+- 219
+- 391
+: - - 426.20000000000005
+    - 479.35
+  - - 425.35
+    - 489.35
+? !!python/tuple
+- 219
+- 220
+- 380
+: - - 425.35
+    - 489.35
+  - - 424.55
+    - 499.35
+? !!python/tuple
+- 221
+- 223
+- 360
+: - - 415.6
+    - 500.5
+  - - 436.85
+    - 504.75
+? !!python/tuple
+- 222
+- 221
+- 361
+: - - 405.6
+    - 499.70000000000005
+  - - 415.6
+    - 500.5
+? !!python/tuple
+- 224
+- 223
+- 348
+: - - 429.40000000000003
+    - 507.35
+  - - 436.85
+    - 504.75
+? !!python/tuple
+- 225
+- 224
+- 350
+: - - 399.40000000000003
+    - 504.5
+  - - 429.40000000000003
+    - 507.35
+? !!python/tuple
+- 226
+- 227
+- 406
+: - - 438.45000000000005
+    - 459.65000000000003
+  - - 448.45000000000005
+    - 460.20000000000005
+? !!python/tuple
+- 227
+- 227
+- 405
+: - - 448.45000000000005
+    - 460.20000000000005
+  - - 448.45000000000005
+    - 460.20000000000005
+? !!python/tuple
+- 228
+- 229
+- 400
+: - - 394.0
+    - 466.65000000000003
+  - - 393.20000000000005
+    - 476.65000000000003
+? !!python/tuple
+- 229
+- 230
+- 393
+: - - 393.20000000000005
+    - 476.65000000000003
+  - - 392.40000000000003
+    - 486.65000000000003
+? !!python/tuple
+- 230
+- 85
+- 384
+: - - 392.40000000000003
+    - 486.65000000000003
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 231
+- 232
+- 411
+: - - 405.35
+    - 456.95000000000005
+  - - 415.35
+    - 457.75
+? !!python/tuple
+- 232
+- 66
+- 410
+: - - 415.35
+    - 457.75
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 233
+- 234
+- 402
+: - - 360.90000000000003
+    - 464.0
+  - - 360.1
+    - 474.0
+? !!python/tuple
+- 234
+- 235
+- 395
+: - - 360.1
+    - 474.0
+  - - 359.25
+    - 484.0
+? !!python/tuple
+- 235
+- 72
+- 388
+: - - 359.25
+    - 484.0
+  - - 358.45000000000005
+    - 495.6
+? !!python/tuple
+- 236
+- 237
+- 416
+: - - 372.35
+    - 454.3
+  - - 382.35
+    - 455.1
+? !!python/tuple
+- 237
+- 0
+- 415
+: - - 382.35
+    - 455.1
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 238
+- 239
+- 404
+: - - 327.90000000000003
+    - 461.1
+  - - 327.0
+    - 471.1
+? !!python/tuple
+- 239
+- 240
+- 397
+: - - 327.0
+    - 471.1
+  - - 326.20000000000005
+    - 481.1
+? !!python/tuple
+- 240
+- 26
+- 390
+: - - 326.20000000000005
+    - 481.1
+  - - 325.1
+    - 492.05
+? !!python/tuple
+- 241
+- 242
+- 421
+: - - 339.40000000000003
+    - 451.55
+  - - 349.40000000000003
+    - 452.40000000000003
+? !!python/tuple
+- 242
+- 40
+- 419
+: - - 349.40000000000003
+    - 452.40000000000003
+  - - 361.85
+    - 453.5
+? !!python/tuple
+- 243
+- 244
+- 409
+: - - 294.90000000000003
+    - 457.95000000000005
+  - - 293.95
+    - 467.95000000000005
+? !!python/tuple
+- 244
+- 245
+- 399
+: - - 293.95
+    - 467.95000000000005
+  - - 293.0
+    - 477.95000000000005
+? !!python/tuple
+- 245
+- 39
+- 392
+: - - 293.0
+    - 477.95000000000005
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 246
+- 240
+- 660
+: - - 306.3183288574219
+    - 448.5001525878906
+  - - 326.6719970703125
+    - 480.9545593261719
+? !!python/tuple
+- 247
+- 11
+- 424
+: - - 316.25
+    - 449.45000000000005
+  - - 328.85
+    - 450.6
+? !!python/tuple
+- 248
+- 249
+- 414
+: - - 261.85
+    - 454.85
+  - - 260.95
+    - 464.85
+? !!python/tuple
+- 249
+- 250
+- 401
+: - - 260.95
+    - 464.85
+  - - 260.1
+    - 474.85
+? !!python/tuple
+- 250
+- 86
+- 394
+: - - 260.1
+    - 474.85
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 251
+- 252
+- 431
+: - - 273.35
+    - 445.25
+  - - 283.35
+    - 446.25
+? !!python/tuple
+- 252
+- 28
+- 429
+: - - 283.35
+    - 446.25
+  - - 295.75
+    - 447.45000000000005
+? !!python/tuple
+- 253
+- 254
+- 420
+: - - 226.10000000000002
+    - 451.6
+  - - 225.20000000000002
+    - 461.6
+? !!python/tuple
+- 254
+- 255
+- 403
+: - - 225.20000000000002
+    - 461.6
+  - - 224.25
+    - 471.6
+? !!python/tuple
+- 255
+- 256
+- 396
+: - - 224.25
+    - 471.6
+  - - 224.20000000000002
+    - 481.6
+? !!python/tuple
+- 256
+- 65
+- 389
+: - - 224.20000000000002
+    - 481.6
+  - - 232.47743225097656
+    - 490.1767883300781
+? !!python/tuple
+- 257
+- 258
+- 436
+: - - 238.0
+    - 441.90000000000003
+  - - 248.0
+    - 442.90000000000003
+? !!python/tuple
+- 258
+- 1
+- 435
+: - - 248.0
+    - 442.90000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 259
+- 12
+- 456
+: - - 430.3
+    - 428.1
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 259
+- 260
+- 447
+: - - 430.3
+    - 428.1
+  - - 429.55
+    - 438.1
+? !!python/tuple
+- 260
+- 261
+- 440
+: - - 429.55
+    - 438.1
+  - - 428.75
+    - 448.1
+? !!python/tuple
+- 261
+- 66
+- 425
+: - - 428.75
+    - 448.1
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 262
+- 263
+- 454
+: - - 441.55
+    - 418.5
+  - - 451.55
+    - 419.25
+? !!python/tuple
+- 263
+- 263
+- 455
+: - - 451.55
+    - 419.25
+  - - 451.55
+    - 419.25
+? !!python/tuple
+- 264
+- 265
+- 449
+: - - 397.35
+    - 425.5
+  - - 396.5
+    - 435.5
+? !!python/tuple
+- 265
+- 266
+- 442
+: - - 396.5
+    - 435.5
+  - - 395.70000000000005
+    - 445.5
+? !!python/tuple
+- 266
+- 0
+- 430
+: - - 395.70000000000005
+    - 445.5
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 267
+- 268
+- 460
+: - - 408.75
+    - 415.90000000000003
+  - - 418.75
+    - 416.65000000000003
+? !!python/tuple
+- 268
+- 12
+- 459
+: - - 418.75
+    - 416.65000000000003
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 269
+- 270
+- 451
+: - - 364.3
+    - 422.90000000000003
+  - - 363.5
+    - 432.90000000000003
+? !!python/tuple
+- 270
+- 271
+- 444
+: - - 363.5
+    - 432.90000000000003
+  - - 362.65000000000003
+    - 442.90000000000003
+? !!python/tuple
+- 271
+- 40
+- 434
+: - - 362.65000000000003
+    - 442.90000000000003
+  - - 361.85
+    - 453.5
+? !!python/tuple
+- 272
+- 273
+- 465
+: - - 375.6
+    - 413.20000000000005
+  - - 385.6
+    - 414.0
+? !!python/tuple
+- 273
+- 13
+- 464
+: - - 385.6
+    - 414.0
+  - - 398.20000000000005
+    - 415.0
+? !!python/tuple
+- 274
+- 275
+- 453
+: - - 331.75
+    - 420.1
+  - - 330.8
+    - 430.1
+? !!python/tuple
+- 275
+- 276
+- 446
+: - - 330.8
+    - 430.1
+  - - 329.8
+    - 440.1
+? !!python/tuple
+- 276
+- 11
+- 439
+: - - 329.8
+    - 440.1
+  - - 328.85
+    - 450.6
+? !!python/tuple
+- 277
+- 278
+- 470
+: - - 343.3
+    - 410.5
+  - - 353.3
+    - 411.35
+? !!python/tuple
+- 278
+- 14
+- 468
+: - - 353.3
+    - 411.35
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 279
+- 280
+- 458
+: - - 298.75
+    - 416.70000000000005
+  - - 297.8
+    - 426.70000000000005
+? !!python/tuple
+- 280
+- 281
+- 448
+: - - 297.8
+    - 426.70000000000005
+  - - 296.85
+    - 436.70000000000005
+? !!python/tuple
+- 281
+- 28
+- 441
+: - - 296.85
+    - 436.70000000000005
+  - - 295.75
+    - 447.45000000000005
+? !!python/tuple
+- 282
+- 283
+- 474
+: - - 310.40000000000003
+    - 407.35
+  - - 320.40000000000003
+    - 408.3
+? !!python/tuple
+- 283
+- 30
+- 473
+: - - 320.40000000000003
+    - 408.3
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 284
+- 285
+- 463
+: - - 265.40000000000003
+    - 413.65000000000003
+  - - 264.55
+    - 423.65000000000003
+? !!python/tuple
+- 285
+- 286
+- 450
+: - - 264.55
+    - 423.65000000000003
+  - - 263.7
+    - 433.65000000000003
+? !!python/tuple
+- 286
+- 1
+- 443
+: - - 263.7
+    - 433.65000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 287
+- 288
+- 479
+: - - 276.65000000000003
+    - 404.05
+  - - 286.65000000000003
+    - 405.0
+? !!python/tuple
+- 288
+- 31
+- 478
+: - - 286.65000000000003
+    - 405.0
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 289
+- 290
+- 469
+: - - 229.65
+    - 410.85
+  - - 228.8
+    - 420.85
+? !!python/tuple
+- 290
+- 291
+- 452
+: - - 228.8
+    - 420.85
+  - - 227.95000000000002
+    - 430.85
+? !!python/tuple
+- 291
+- 77
+- 445
+: - - 227.95000000000002
+    - 430.85
+  - - 227.5
+    - 441.15000000000003
+? !!python/tuple
+- 292
+- 293
+- 483
+: - - 241.45000000000002
+    - 401.05
+  - - 251.45
+    - 401.85
+? !!python/tuple
+- 293
+- 32
+- 482
+: - - 251.45
+    - 401.85
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 294
+- 15
+- 506
+: - - 401.05
+    - 380.05
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 295
+- 294
+- 498
+: - - 400.25
+    - 390.05
+  - - 401.05
+    - 380.05
+? !!python/tuple
+- 296
+- 13
+- 485
+: - - 399.40000000000003
+    - 400.05
+  - - 398.20000000000005
+    - 415.0
+? !!python/tuple
+- 296
+- 295
+- 491
+: - - 399.40000000000003
+    - 400.05
+  - - 400.25
+    - 390.05
+? !!python/tuple
+- 297
+- 298
+- 500
+: - - 368.05
+    - 377.05
+  - - 367.20000000000005
+    - 387.05
+? !!python/tuple
+- 298
+- 299
+- 493
+: - - 367.20000000000005
+    - 387.05
+  - - 366.40000000000003
+    - 397.05
+? !!python/tuple
+- 299
+- 14
+- 487
+: - - 366.40000000000003
+    - 397.05
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 300
+- 301
+- 510
+: - - 379.45000000000005
+    - 367.45000000000005
+  - - 389.45000000000005
+    - 368.35
+? !!python/tuple
+- 301
+- 15
+- 508
+: - - 389.45000000000005
+    - 368.35
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 302
+- 303
+- 503
+: - - 336.35
+    - 374.15000000000003
+  - - 335.3
+    - 384.15000000000003
+? !!python/tuple
+- 303
+- 304
+- 496
+: - - 335.3
+    - 384.15000000000003
+  - - 334.3
+    - 394.15000000000003
+? !!python/tuple
+- 304
+- 30
+- 489
+: - - 334.3
+    - 394.15000000000003
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 305
+- 306
+- 516
+: - - 347.8
+    - 364.6
+  - - 357.8
+    - 365.55
+? !!python/tuple
+- 306
+- 2
+- 514
+: - - 357.8
+    - 365.55
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 307
+- 308
+- 504
+: - - 303.15000000000003
+    - 371.05
+  - - 302.15000000000003
+    - 381.05
+? !!python/tuple
+- 308
+- 309
+- 497
+: - - 302.15000000000003
+    - 381.05
+  - - 301.20000000000005
+    - 391.05
+? !!python/tuple
+- 309
+- 31
+- 490
+: - - 301.20000000000005
+    - 391.05
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 310
+- 311
+- 521
+: - - 314.65000000000003
+    - 361.55
+  - - 324.65000000000003
+    - 362.5
+? !!python/tuple
+- 311
+- 52
+- 519
+: - - 324.65000000000003
+    - 362.5
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 312
+- 313
+- 509
+: - - 269.25
+    - 367.70000000000005
+  - - 268.40000000000003
+    - 377.70000000000005
+? !!python/tuple
+- 313
+- 314
+- 499
+: - - 268.40000000000003
+    - 377.70000000000005
+  - - 267.55
+    - 387.70000000000005
+? !!python/tuple
+- 314
+- 32
+- 492
+: - - 267.55
+    - 387.70000000000005
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 315
+- 316
+- 525
+: - - 281.6
+    - 358.45000000000005
+  - - 291.6
+    - 359.40000000000003
+? !!python/tuple
+- 316
+- 16
+- 524
+: - - 291.6
+    - 359.40000000000003
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 318
+- 317
+- 536
+: - - 433.35
+    - 355.05
+  - - 434.3
+    - 345.05
+? !!python/tuple
+- 319
+- 318
+- 529
+: - - 432.40000000000003
+    - 365.05
+  - - 433.35
+    - 355.05
+? !!python/tuple
+- 319
+- 322
+- 515
+: - - 432.40000000000003
+    - 365.05
+  - - 434.40000000000003
+    - 376.8
+? !!python/tuple
+- 321
+- 320
+- 505
+: - - 418.05
+    - 370.85
+  - - 428.05
+    - 371.70000000000005
+? !!python/tuple
+- 323
+- 322
+- 501
+: - - 433.65000000000003
+    - 386.8
+  - - 434.40000000000003
+    - 376.8
+? !!python/tuple
+- 324
+- 323
+- 494
+: - - 432.85
+    - 396.8
+  - - 433.65000000000003
+    - 386.8
+? !!python/tuple
+- 325
+- 324
+- 488
+: - - 432.05
+    - 406.8
+  - - 432.85
+    - 396.8
+? !!python/tuple
+- 327
+- 326
+- 538
+: - - 403.5
+    - 351.70000000000005
+  - - 405.15000000000003
+    - 341.85
+? !!python/tuple
+- 328
+- 327
+- 531
+: - - 402.65000000000003
+    - 361.70000000000005
+  - - 403.5
+    - 351.70000000000005
+? !!python/tuple
+- 330
+- 329
+- 539
+: - - 370.35
+    - 349.05
+  - - 371.95000000000005
+    - 339.15000000000003
+? !!python/tuple
+- 331
+- 332
+- 542
+: - - 340.5
+    - 336.75
+  - - 339.0
+    - 346.70000000000005
+? !!python/tuple
+- 332
+- 52
+- 534
+: - - 339.0
+    - 346.70000000000005
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 333
+- 334
+- 537
+: - - 305.85
+    - 341.8
+  - - 304.95000000000005
+    - 351.8
+? !!python/tuple
+- 334
+- 16
+- 530
+: - - 304.95000000000005
+    - 351.8
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 335
+- 336
+- 540
+: - - 272.35
+    - 338.55
+  - - 271.55
+    - 348.55
+? !!python/tuple
+- 336
+- 88
+- 533
+: - - 271.55
+    - 348.55
+  - - 271.1
+    - 357.25
+? !!python/tuple
+- 337
+- 338
+- 546
+: - - 283.65000000000003
+    - 328.90000000000003
+  - - 293.65000000000003
+    - 329.90000000000003
+? !!python/tuple
+- 338
+- 17
+- 544
+: - - 293.65000000000003
+    - 329.90000000000003
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 339
+- 340
+- 550
+: - - 253.10000000000002
+    - 326.05
+  - - 263.1
+    - 326.95000000000005
+? !!python/tuple
+- 340
+- 18
+- 549
+: - - 263.1
+    - 326.95000000000005
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 341
+- 342
+- 557
+: - - 275.55
+    - 299.3
+  - - 274.8
+    - 309.3
+? !!python/tuple
+- 342
+- 343
+- 555
+: - - 274.8
+    - 309.3
+  - - 274.05
+    - 319.3
+? !!python/tuple
+- 343
+- 18
+- 553
+: - - 274.05
+    - 319.3
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 344
+- 345
+- 561
+: - - 286.7
+    - 289.3
+  - - 296.7
+    - 289.85
+? !!python/tuple
+- 345
+- 346
+- 560
+: - - 296.7
+    - 289.85
+  - - 306.70000000000005
+    - 290.45
+? !!python/tuple
+- 346
+- 346
+- 559
+: - - 306.70000000000005
+    - 290.45
+  - - 306.70000000000005
+    - 290.45
+? !!python/tuple
+- 347
+- 348
+- 558
+: - - 239.70000000000002
+    - 296.65000000000003
+  - - 238.60000000000002
+    - 306.65000000000003
+? !!python/tuple
+- 348
+- 349
+- 556
+: - - 238.60000000000002
+    - 306.65000000000003
+  - - 237.5
+    - 316.65000000000003
+? !!python/tuple
+- 349
+- 350
+- 554
+: - - 237.5
+    - 316.65000000000003
+  - - 235.60000000000002
+    - 336.65000000000003
+? !!python/tuple
+- 350
+- 351
+- 541
+: - - 235.60000000000002
+    - 336.65000000000003
+  - - 234.8
+    - 346.65000000000003
+? !!python/tuple
+- 351
+- 352
+- 535
+: - - 234.8
+    - 346.65000000000003
+  - - 233.95000000000002
+    - 356.65000000000003
+? !!python/tuple
+- 352
+- 353
+- 528
+: - - 233.95000000000002
+    - 356.65000000000003
+  - - 233.20000000000002
+    - 366.65000000000003
+? !!python/tuple
+- 353
+- 354
+- 511
+: - - 233.20000000000002
+    - 366.65000000000003
+  - - 232.4
+    - 376.65000000000003
+? !!python/tuple
+- 354
+- 355
+- 502
+: - - 232.4
+    - 376.65000000000003
+  - - 231.60000000000002
+    - 386.65000000000003
+? !!python/tuple
+- 355
+- 87
+- 495
+: - - 231.60000000000002
+    - 386.65000000000003
+  - - 230.9
+    - 400.35
+? !!python/tuple
+- 356
+- 357
+- 565
+: - - 251.7
+    - 286.90000000000003
+  - - 261.7
+    - 287.65000000000003
+? !!python/tuple
+- 357
+- 29
+- 564
+: - - 261.7
+    - 287.65000000000003
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 358
+- 19
+- 577
+: - - 278.05
+    - 259.95
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 359
+- 358
+- 572
+: - - 277.45
+    - 269.95
+  - - 278.05
+    - 259.95
+? !!python/tuple
+- 360
+- 29
+- 568
+: - - 276.8
+    - 279.95
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 360
+- 359
+- 570
+: - - 276.8
+    - 279.95
+  - - 277.45
+    - 269.95
+? !!python/tuple
+- 361
+- 362
+- 576
+: - - 289.15000000000003
+    - 249.90000000000003
+  - - 299.15000000000003
+    - 250.5
+? !!python/tuple
+- 362
+- 363
+- 574
+: - - 299.15000000000003
+    - 250.5
+  - - 309.15000000000003
+    - 251.05
+? !!python/tuple
+- 363
+- 363
+- 575
+: - - 309.15000000000003
+    - 251.05
+  - - 309.15000000000003
+    - 251.05
+? !!python/tuple
+- 364
+- 365
+- 573
+: - - 245.4
+    - 257.55
+  - - 242.95000000000002
+    - 267.55
+? !!python/tuple
+- 365
+- 366
+- 571
+: - - 242.95000000000002
+    - 267.55
+  - - 241.45000000000002
+    - 277.55
+? !!python/tuple
+- 366
+- 99
+- 569
+: - - 241.45000000000002
+    - 277.55
+  - - 241.25
+    - 286.2
+? !!python/tuple
+- 367
+- 368
+- 580
+: - - 259.3
+    - 248.2
+  - - 269.3
+    - 248.8
+? !!python/tuple
+- 368
+- 19
+- 579
+: - - 269.3
+    - 248.8
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 369
+- 370
+- 595
+: - - 357.90000000000003
+    - 213.4
+  - - 367.90000000000003
+    - 213.85000000000002
+? !!python/tuple
+- 370
+- 90
+- 594
+: - - 367.90000000000003
+    - 213.85000000000002
+  - - 380.5
+    - 214.0
+? !!python/tuple
+- 371
+- 372
+- 599
+: - - 324.35
+    - 211.9
+  - - 334.35
+    - 212.35000000000002
+? !!python/tuple
+- 372
+- 27
+- 598
+: - - 334.35
+    - 212.35000000000002
+  - - 347.40000000000003
+    - 212.5
+? !!python/tuple
+- 373
+- 20
+- 602
+: - - 280.7
+    - 220.55
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 374
+- 373
+- 587
+: - - 280.05
+    - 230.55
+  - - 280.7
+    - 220.55
+? !!python/tuple
+- 375
+- 374
+- 585
+: - - 279.40000000000003
+    - 240.55
+  - - 280.05
+    - 230.55
+? !!python/tuple
+- 376
+- 377
+- 603
+: - - 291.05
+    - 210.35000000000002
+  - - 301.05
+    - 210.8
+? !!python/tuple
+- 377
+- 49
+- 601
+: - - 301.05
+    - 210.8
+  - - 313.85
+    - 211.0
+? !!python/tuple
+- 378
+- 79
+- 606
+: - - 255.8
+    - 219.20000000000002
+  - - 257.90000000000003
+    - 208.75
+? !!python/tuple
+- 379
+- 378
+- 588
+: - - 253.2
+    - 229.20000000000002
+  - - 255.8
+    - 219.20000000000002
+? !!python/tuple
+- 380
+- 379
+- 586
+: - - 250.45
+    - 239.20000000000002
+  - - 253.2
+    - 229.20000000000002
+? !!python/tuple
+- 381
+- 20
+- 605
+: - - 268.40000000000003
+    - 209.25
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 382
+- 70
+- 625
+: - - 414.6
+    - 197.9
+  - - 415.25
+    - 187.35000000000002
+? !!python/tuple
+- 383
+- 382
+- 614
+: - - 414.05
+    - 207.9
+  - - 414.6
+    - 197.9
+? !!python/tuple
+- 383
+- 387
+- 608
+: - - 414.05
+    - 207.9
+  - - 420.95000000000005
+    - 216.10000000000002
+? !!python/tuple
+- 385
+- 384
+- 591
+: - - 401.05
+    - 215.3
+  - - 411.05
+    - 215.70000000000002
+? !!python/tuple
+- 386
+- 385
+- 592
+: - - 391.05
+    - 214.85000000000002
+  - - 401.05
+    - 215.3
+? !!python/tuple
+- 387
+- 388
+- 590
+: - - 420.95000000000005
+    - 216.10000000000002
+  - - 430.95000000000005
+    - 216.5
+? !!python/tuple
+- 388
+- 389
+- 589
+: - - 430.95000000000005
+    - 216.5
+  - - 440.95000000000005
+    - 216.95000000000002
+? !!python/tuple
+- 390
+- 390
+- 596
+: - - 447.35
+    - 212.5
+  - - 447.35
+    - 212.5
+? !!python/tuple
+- 390
+- 391
+- 611
+: - - 447.35
+    - 212.5
+  - - 447.85
+    - 202.5
+? !!python/tuple
+- 391
+- 98
+- 617
+: - - 447.85
+    - 202.5
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 392
+- 393
+- 623
+: - - 424.8
+    - 188.35000000000002
+  - - 434.8
+    - 190.4
+? !!python/tuple
+- 393
+- 98
+- 621
+: - - 434.8
+    - 190.4
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 394
+- 91
+- 636
+: - - 348.70000000000005
+    - 184.95000000000002
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 395
+- 394
+- 627
+: - - 348.25
+    - 194.95000000000002
+  - - 348.70000000000005
+    - 184.95000000000002
+? !!python/tuple
+- 396
+- 395
+- 616
+: - - 347.75
+    - 204.95000000000002
+  - - 348.25
+    - 194.95000000000002
+? !!python/tuple
+- 397
+- 398
+- 635
+: - - 359.5
+    - 175.3
+  - - 369.5
+    - 177.0
+? !!python/tuple
+- 398
+- 399
+- 634
+: - - 369.5
+    - 177.0
+  - - 379.5
+    - 179.05
+? !!python/tuple
+- 399
+- 402
+- 633
+: - - 379.5
+    - 179.05
+  - - 393.6
+    - 181.95000000000002
+? !!python/tuple
+- 401
+- 400
+- 624
+: - - 381.20000000000005
+    - 197.9
+  - - 381.70000000000005
+    - 187.9
+? !!python/tuple
+- 402
+- 403
+- 630
+: - - 393.6
+    - 181.95000000000002
+  - - 403.6
+    - 184.0
+? !!python/tuple
+- 403
+- 70
+- 628
+: - - 403.6
+    - 184.0
+  - - 415.25
+    - 187.35000000000002
+? !!python/tuple
+- 404
+- 67
+- 639
+: - - 315.15000000000003
+    - 183.35000000000002
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 405
+- 404
+- 629
+: - - 314.70000000000005
+    - 193.35000000000002
+  - - 315.15000000000003
+    - 183.35000000000002
+? !!python/tuple
+- 406
+- 405
+- 618
+: - - 314.20000000000005
+    - 203.35000000000002
+  - - 314.70000000000005
+    - 193.35000000000002
+? !!python/tuple
+- 407
+- 51
+- 641
+: - - 325.90000000000003
+    - 172.85000000000002
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 408
+- 41
+- 644
+: - - 282.6
+    - 181.25
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 409
+- 408
+- 631
+: - - 282.05
+    - 191.25
+  - - 282.6
+    - 181.25
+? !!python/tuple
+- 410
+- 409
+- 620
+: - - 281.5
+    - 201.25
+  - - 282.05
+    - 191.25
+? !!python/tuple
+- 411
+- 412
+- 645
+: - - 293.5
+    - 171.15
+  - - 303.5
+    - 171.65
+? !!python/tuple
+- 412
+- 67
+- 643
+: - - 303.5
+    - 171.65
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 413
+- 69
+- 648
+: - - 259.3
+    - 179.65
+  - - 260.65000000000003
+    - 169.20000000000002
+? !!python/tuple
+- 414
+- 413
+- 632
+: - - 258.6
+    - 189.65
+  - - 259.3
+    - 179.65
+? !!python/tuple
+- 415
+- 414
+- 622
+: - - 257.95
+    - 199.65
+  - - 258.6
+    - 189.65
+? !!python/tuple
+- 416
+- 41
+- 647
+: - - 271.15000000000003
+    - 170.0
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 417
+- 418
+- 653
+: - - 293.1
+    - 160.85000000000002
+  - - 303.1
+    - 163.0
+? !!python/tuple
+- 418
+- 419
+- 652
+: - - 303.1
+    - 163.0
+  - - 313.1
+    - 165.10000000000002
+? !!python/tuple
+- 419
+- 420
+- 651
+: - - 313.1
+    - 165.10000000000002
+  - - 333.1
+    - 169.3
+? !!python/tuple
+- 420
+- 61
+- 649
+: - - 333.1
+    - 169.3
+  - - 343.75
+    - 173.10000000000002
+? !!python/tuple
+- 421
+- 422
+- 658
+: - - 265.45
+    - 155.05
+  - - 276.05
+    - 157.20000000000002
+? !!python/tuple
+- 422
+- 71
+- 656
+: - - 276.05
+    - 157.20000000000002
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 423
+- 239
+- 662
+: - - 315.40435791015625
+    - 477.9844970703125
+  - - 327.10369873046875
+    - 470.9964599609375
+? !!python/tuple
+- 424
+- 423
+- 661
+: - - 312.3125
+    - 485.1031799316406
+  - - 315.40435791015625
+    - 477.9844970703125
diff --git a/output_yaml/edges_low_level.yaml b/output_yaml/edges_low_level.yaml
new file mode 100644
index 0000000..a384410
--- /dev/null
+++ b/output_yaml/edges_low_level.yaml
@@ -0,0 +1,2320 @@
+? !!python/tuple
+- 0
+- 66
+- 85
+: - - 394.8
+    - 456.1
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 0
+- 85
+- 84
+: - - 394.8
+    - 456.1
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 1
+- 28
+- 91
+: - - 262.8
+    - 444.3
+  - - 295.75
+    - 447.45000000000005
+? !!python/tuple
+- 1
+- 28
+- 93
+: - - 262.8
+    - 444.3
+  - - 296.23443603515625
+    - 446.56121826171875
+? !!python/tuple
+- 1
+- 86
+- 90
+: - - 262.8
+    - 444.3
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 1
+- 86
+- 92
+: - - 262.8
+    - 444.3
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 2
+- 2
+- 119
+: - - 368.90000000000003
+    - 366.5
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 2
+- 2
+- 123
+: - - 368.90000000000003
+    - 366.5
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 2
+- 2
+- 129
+: - - 368.90000000000003
+    - 366.5
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 2
+- 14
+- 109
+: - - 368.90000000000003
+    - 366.5
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 2
+- 14
+- 113
+: - - 368.90000000000003
+    - 366.5
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 2
+- 14
+- 119
+: - - 368.90000000000003
+    - 366.5
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 2
+- 15
+- 110
+: - - 368.90000000000003
+    - 366.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 2
+- 15
+- 114
+: - - 368.90000000000003
+    - 366.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 2
+- 15
+- 120
+: - - 368.90000000000003
+    - 366.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 3
+- 3
+- 0
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 3
+- 3
+- 1
+: - - 407.40000000000003
+    - 628.1500000000001
+  - - 407.40000000000003
+    - 628.1500000000001
+? !!python/tuple
+- 5
+- 5
+- 12
+: - - 241.5
+    - 586.1
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 5
+- 42
+- 11
+: - - 241.5
+    - 586.1
+  - - 240.65
+    - 593.3000000000001
+? !!python/tuple
+- 6
+- 6
+- 16
+: - - 218.0
+    - 576.9
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 6
+- 21
+- 18
+: - - 218.0
+    - 576.9
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 7
+- 4
+- 28
+: - - 345.3
+    - 568.1
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 7
+- 34
+- 29
+: - - 345.3
+    - 568.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 8
+- 24
+- 52
+: - - 363.20000000000005
+    - 530.65
+  - - 367.0
+    - 531.5500000000001
+? !!python/tuple
+- 9
+- 8
+- 59
+: - - 350.55
+    - 525.8000000000001
+  - - 363.20000000000005
+    - 530.65
+? !!python/tuple
+- 10
+- 38
+- 71
+: - - 347.75
+    - 500.90000000000003
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 11
+- 40
+- 158
+: - - 329.2942810058594
+    - 450.0257263183594
+  - - 361.371337890625
+    - 452.96978759765625
+? !!python/tuple
+- 12
+- 12
+- 95
+: - - 431.1
+    - 417.6
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 12
+- 12
+- 97
+: - - 431.1
+    - 417.6
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 12
+- 66
+- 94
+: - - 431.1
+    - 417.6
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 12
+- 66
+- 96
+: - - 431.1
+    - 417.6
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 12
+- 103
+- 113
+: - - 431.1
+    - 417.6
+  - - 432.0601806640625
+    - 372.5963134765625
+? !!python/tuple
+- 13
+- 0
+- 96
+: - - 398.20000000000005
+    - 415.0
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 13
+- 0
+- 98
+: - - 398.20000000000005
+    - 415.0
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 13
+- 12
+- 97
+: - - 398.20000000000005
+    - 415.0
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 13
+- 12
+- 99
+: - - 398.20000000000005
+    - 415.0
+  - - 431.1
+    - 417.6
+? !!python/tuple
+- 13
+- 15
+- 108
+: - - 398.20000000000005
+    - 415.0
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 13
+- 15
+- 111
+: - - 398.20000000000005
+    - 415.0
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 13
+- 15
+- 117
+: - - 398.20000000000005
+    - 415.0
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 14
+- 13
+- 99
+: - - 365.1
+    - 412.35
+  - - 398.20000000000005
+    - 415.0
+? !!python/tuple
+- 14
+- 13
+- 101
+: - - 365.1
+    - 412.35
+  - - 398.20000000000005
+    - 415.0
+? !!python/tuple
+- 14
+- 40
+- 98
+: - - 365.1
+    - 412.35
+  - - 361.85
+    - 453.5
+? !!python/tuple
+- 14
+- 40
+- 100
+: - - 365.1
+    - 412.35
+  - - 361.371337890625
+    - 452.96978759765625
+? !!python/tuple
+- 15
+- 15
+- 117
+: - - 401.95000000000005
+    - 369.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 15
+- 15
+- 118
+: - - 401.95000000000005
+    - 369.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 15
+- 15
+- 122
+: - - 401.95000000000005
+    - 369.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 15
+- 15
+- 128
+: - - 401.95000000000005
+    - 369.5
+  - - 401.95000000000005
+    - 369.5
+? !!python/tuple
+- 15
+- 103
+- 112
+: - - 401.95000000000005
+    - 369.5
+  - - 431.1551818847656
+    - 371.0977783203125
+? !!python/tuple
+- 15
+- 103
+- 118
+: - - 401.95000000000005
+    - 369.5
+  - - 432.0601806640625
+    - 372.5963134765625
+? !!python/tuple
+- 16
+- 31
+- 113
+: - - 304.15000000000003
+    - 360.5
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 16
+- 31
+- 117
+: - - 304.15000000000003
+    - 360.5
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 16
+- 31
+- 123
+: - - 304.15000000000003
+    - 360.5
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 16
+- 52
+- 114
+: - - 304.15000000000003
+    - 360.5
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 16
+- 52
+- 118
+: - - 304.15000000000003
+    - 360.5
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 16
+- 52
+- 124
+: - - 304.15000000000003
+    - 360.5
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 17
+- 16
+- 121
+: - - 306.1
+    - 331.3
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 17
+- 16
+- 125
+: - - 306.1
+    - 331.3
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 17
+- 16
+- 131
+: - - 306.1
+    - 331.3
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 17
+- 17
+- 122
+: - - 306.1
+    - 331.3
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 17
+- 17
+- 126
+: - - 306.1
+    - 331.3
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 17
+- 17
+- 132
+: - - 306.1
+    - 331.3
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 18
+- 17
+- 124
+: - - 273.15000000000003
+    - 328.0
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 18
+- 17
+- 128
+: - - 273.15000000000003
+    - 328.0
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 18
+- 17
+- 134
+: - - 273.15000000000003
+    - 328.0
+  - - 306.1
+    - 331.3
+? !!python/tuple
+- 18
+- 88
+- 123
+: - - 273.15000000000003
+    - 328.0
+  - - 271.1
+    - 357.25
+? !!python/tuple
+- 18
+- 88
+- 127
+: - - 273.15000000000003
+    - 328.0
+  - - 271.1
+    - 357.25
+? !!python/tuple
+- 18
+- 88
+- 133
+: - - 273.15000000000003
+    - 328.0
+  - - 271.1
+    - 357.25
+? !!python/tuple
+- 19
+- 19
+- 132
+: - - 278.75
+    - 249.40000000000003
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 19
+- 19
+- 136
+: - - 278.75
+    - 249.40000000000003
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 19
+- 19
+- 142
+: - - 278.75
+    - 249.40000000000003
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 19
+- 20
+- 137
+: - - 278.75
+    - 249.40000000000003
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 19
+- 20
+- 141
+: - - 278.75
+    - 249.40000000000003
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 19
+- 20
+- 147
+: - - 278.75
+    - 249.40000000000003
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 20
+- 41
+- 150
+: - - 281.15000000000003
+    - 210.05
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 20
+- 41
+- 154
+: - - 281.15000000000003
+    - 210.05
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 20
+- 41
+- 160
+: - - 281.15000000000003
+    - 210.05
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 20
+- 49
+- 138
+: - - 281.15000000000003
+    - 210.05
+  - - 313.85
+    - 211.0
+? !!python/tuple
+- 20
+- 49
+- 142
+: - - 281.15000000000003
+    - 210.05
+  - - 313.85
+    - 211.0
+? !!python/tuple
+- 20
+- 49
+- 148
+: - - 281.15000000000003
+    - 210.05
+  - - 313.85
+    - 211.0
+? !!python/tuple
+- 21
+- 54
+- 14
+: - - 235.15
+    - 578.5
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 24
+- 58
+- 57
+: - - 367.0
+    - 531.5500000000001
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 24
+- 80
+- 48
+: - - 367.0
+    - 531.5500000000001
+  - - 416.95000000000005
+    - 536.1
+? !!python/tuple
+- 25
+- 96
+- 49
+: - - 243.55
+    - 531.15
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 26
+- 38
+- 76
+: - - 325.7059631347656
+    - 492.0518798828125
+  - - 356.15000000000003
+    - 498.95000000000005
+? !!python/tuple
+- 27
+- 90
+- 135
+: - - 347.40000000000003
+    - 212.5
+  - - 380.5
+    - 214.0
+? !!python/tuple
+- 27
+- 90
+- 139
+: - - 347.40000000000003
+    - 212.5
+  - - 380.5
+    - 214.0
+? !!python/tuple
+- 27
+- 90
+- 145
+: - - 347.40000000000003
+    - 212.5
+  - - 380.5
+    - 214.0
+? !!python/tuple
+- 27
+- 91
+- 144
+: - - 347.40000000000003
+    - 212.5
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 27
+- 91
+- 148
+: - - 347.40000000000003
+    - 212.5
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 27
+- 91
+- 154
+: - - 347.40000000000003
+    - 212.5
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 28
+- 11
+- 157
+: - - 296.23443603515625
+    - 446.56121826171875
+  - - 328.30914306640625
+    - 449.5286865234375
+? !!python/tuple
+- 28
+- 26
+- 90
+: - - 296.23443603515625
+    - 446.56121826171875
+  - - 325.7059631347656
+    - 492.0518798828125
+? !!python/tuple
+- 28
+- 28
+- 91
+: - - 296.23443603515625
+    - 446.56121826171875
+  - - 296.23443603515625
+    - 446.56121826171875
+? !!python/tuple
+- 28
+- 39
+- 88
+: - - 295.75
+    - 447.45000000000005
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 28
+- 39
+- 89
+: - - 296.23443603515625
+    - 446.56121826171875
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 29
+- 18
+- 127
+: - - 276.2
+    - 288.8
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 29
+- 18
+- 131
+: - - 276.2
+    - 288.8
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 29
+- 18
+- 137
+: - - 276.2
+    - 288.8
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 29
+- 19
+- 131
+: - - 276.2
+    - 288.8
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 29
+- 19
+- 135
+: - - 276.2
+    - 288.8
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 29
+- 19
+- 141
+: - - 276.2
+    - 288.8
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 29
+- 29
+- 128
+: - - 276.2
+    - 288.8
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 29
+- 29
+- 132
+: - - 276.2
+    - 288.8
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 29
+- 29
+- 138
+: - - 276.2
+    - 288.8
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 30
+- 11
+- 100
+: - - 332.75
+    - 409.55
+  - - 328.98284912109375
+    - 449.8285217285156
+? !!python/tuple
+- 30
+- 11
+- 102
+: - - 332.75
+    - 409.55
+  - - 329.2942810058594
+    - 450.0257263183594
+? !!python/tuple
+- 30
+- 14
+- 101
+: - - 332.75
+    - 409.55
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 30
+- 14
+- 103
+: - - 332.75
+    - 409.55
+  - - 365.1
+    - 412.35
+? !!python/tuple
+- 31
+- 28
+- 102
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 295.75
+    - 447.45000000000005
+? !!python/tuple
+- 31
+- 28
+- 104
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 296.23443603515625
+    - 446.56121826171875
+? !!python/tuple
+- 31
+- 30
+- 103
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 31
+- 30
+- 105
+: - - 299.90000000000003
+    - 406.20000000000005
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 32
+- 1
+- 104
+: - - 266.2
+    - 403.15000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 32
+- 1
+- 106
+: - - 266.2
+    - 403.15000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 32
+- 31
+- 105
+: - - 266.2
+    - 403.15000000000003
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 32
+- 31
+- 107
+: - - 266.2
+    - 403.15000000000003
+  - - 299.90000000000003
+    - 406.20000000000005
+? !!python/tuple
+- 33
+- 33
+- 7
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 33
+- 33
+- 9
+: - - 416.0
+    - 593.35
+  - - 416.0
+    - 593.35
+? !!python/tuple
+- 34
+- 34
+- 25
+: - - 359.0
+    - 570.1
+  - - 359.0
+    - 570.1
+? !!python/tuple
+- 34
+- 46
+- 27
+: - - 359.0
+    - 570.1
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 37
+- 21
+- 46
+: - - 235.8
+    - 532.1
+  - - 235.15
+    - 578.5
+? !!python/tuple
+- 37
+- 25
+- 50
+: - - 235.8
+    - 532.1
+  - - 243.55
+    - 531.15
+? !!python/tuple
+- 38
+- 102
+- 82
+: - - 356.15000000000003
+    - 498.95000000000005
+  - - 425.0286865234375
+    - 500.0166931152344
+? !!python/tuple
+- 39
+- 26
+- 79
+: - - 291.85
+    - 489.0
+  - - 325.7059631347656
+    - 492.0518798828125
+? !!python/tuple
+- 40
+- 0
+- 87
+: - - 361.85
+    - 453.5
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 40
+- 0
+- 88
+: - - 361.371337890625
+    - 452.96978759765625
+  - - 394.8
+    - 456.1
+? !!python/tuple
+- 40
+- 40
+- 87
+: - - 361.371337890625
+    - 452.96978759765625
+  - - 361.371337890625
+    - 452.96978759765625
+? !!python/tuple
+- 40
+- 72
+- 86
+: - - 361.371337890625
+    - 452.96978759765625
+  - - 358.45000000000005
+    - 495.6
+? !!python/tuple
+- 41
+- 67
+- 151
+: - - 283.0
+    - 170.75
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 41
+- 67
+- 155
+: - - 283.0
+    - 170.75
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 41
+- 67
+- 161
+: - - 283.0
+    - 170.75
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 41
+- 71
+- 154
+: - - 283.0
+    - 170.75
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 41
+- 71
+- 158
+: - - 283.0
+    - 170.75
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 41
+- 71
+- 164
+: - - 283.0
+    - 170.75
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 42
+- 4
+- 8
+: - - 240.65
+    - 593.3000000000001
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 42
+- 64
+- 6
+: - - 240.65
+    - 593.3000000000001
+  - - 253.3
+    - 602.25
+? !!python/tuple
+- 43
+- 94
+- 44
+: - - 361.20000000000005
+    - 533.0500000000001
+  - - 408.45000000000005
+    - 546.5
+? !!python/tuple
+- 44
+- 100
+- 65
+: - - 285.8
+    - 507.80000000000007
+  - - 284.2564697265625
+    - 532.891845703125
+? !!python/tuple
+- 45
+- 45
+- 4
+: - - 444.25
+    - 576.9
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 45
+- 45
+- 17
+: - - 444.25
+    - 576.9
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 46
+- 56
+- 23
+: - - 405.95000000000005
+    - 573.4
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 47
+- 47
+- 33
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 34
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 35
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 36
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 37
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 40
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 47
+- 47
+- 42
+: - - 448.05
+    - 549.45
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 48
+- 44
+- 69
+: - - 276.85
+    - 501.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 48
+- 59
+- 70
+: - - 276.85
+    - 501.45000000000005
+  - - 287.05
+    - 502.45000000000005
+? !!python/tuple
+- 49
+- 27
+- 136
+: - - 313.85
+    - 211.0
+  - - 347.40000000000003
+    - 212.5
+? !!python/tuple
+- 49
+- 27
+- 140
+: - - 313.85
+    - 211.0
+  - - 347.40000000000003
+    - 212.5
+? !!python/tuple
+- 49
+- 27
+- 146
+: - - 313.85
+    - 211.0
+  - - 347.40000000000003
+    - 212.5
+? !!python/tuple
+- 49
+- 67
+- 147
+: - - 313.85
+    - 211.0
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 49
+- 67
+- 151
+: - - 313.85
+    - 211.0
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 49
+- 67
+- 157
+: - - 313.85
+    - 211.0
+  - - 315.75
+    - 172.85000000000002
+? !!python/tuple
+- 52
+- 2
+- 112
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 52
+- 2
+- 116
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 52
+- 2
+- 122
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 368.90000000000003
+    - 366.5
+? !!python/tuple
+- 52
+- 30
+- 111
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 52
+- 30
+- 115
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 52
+- 30
+- 121
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 332.75
+    - 409.55
+? !!python/tuple
+- 52
+- 52
+- 120
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 52
+- 52
+- 124
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 52
+- 52
+- 130
+: - - 337.40000000000003
+    - 363.65000000000003
+  - - 337.40000000000003
+    - 363.65000000000003
+? !!python/tuple
+- 54
+- 5
+- 13
+: - - 237.9
+    - 579.0500000000001
+  - - 241.5
+    - 586.1
+? !!python/tuple
+- 54
+- 54
+- 22
+: - - 237.9
+    - 579.0500000000001
+  - - 237.9
+    - 579.0500000000001
+? !!python/tuple
+- 55
+- 45
+- 19
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 55
+- 55
+- 5
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 55
+- 55
+- 15
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 55
+- 62
+- 26
+: - - 436.95000000000005
+    - 577.3000000000001
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 56
+- 55
+- 21
+: - - 423.45000000000005
+    - 576.1
+  - - 436.95000000000005
+    - 577.3000000000001
+? !!python/tuple
+- 56
+- 56
+- 20
+: - - 423.45000000000005
+    - 576.1
+  - - 423.45000000000005
+    - 576.1
+? !!python/tuple
+- 58
+- 58
+- 38
+: - - 432.75
+    - 548.65
+  - - 432.75
+    - 548.65
+? !!python/tuple
+- 58
+- 62
+- 39
+: - - 432.75
+    - 548.65
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 59
+- 44
+- 67
+: - - 287.05
+    - 502.45000000000005
+  - - 285.8
+    - 507.80000000000007
+? !!python/tuple
+- 59
+- 63
+- 68
+: - - 287.05
+    - 502.45000000000005
+  - - 334.90000000000003
+    - 527.1
+? !!python/tuple
+- 60
+- 96
+- 74
+: - - 246.8
+    - 498.55
+  - - 263.7
+    - 533.15
+? !!python/tuple
+- 61
+- 61
+- 146
+: - - 343.75
+    - 173.10000000000002
+  - - 343.75
+    - 173.10000000000002
+? !!python/tuple
+- 61
+- 61
+- 150
+: - - 343.75
+    - 173.10000000000002
+  - - 343.75
+    - 173.10000000000002
+? !!python/tuple
+- 61
+- 61
+- 156
+: - - 343.75
+    - 173.10000000000002
+  - - 343.75
+    - 173.10000000000002
+? !!python/tuple
+- 61
+- 91
+- 148
+: - - 343.75
+    - 173.10000000000002
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 61
+- 91
+- 152
+: - - 343.75
+    - 173.10000000000002
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 61
+- 91
+- 158
+: - - 343.75
+    - 173.10000000000002
+  - - 349.35
+    - 174.45000000000002
+? !!python/tuple
+- 62
+- 45
+- 24
+: - - 444.15000000000003
+    - 570.75
+  - - 444.25
+    - 576.9
+? !!python/tuple
+- 62
+- 62
+- 30
+: - - 444.15000000000003
+    - 570.75
+  - - 444.15000000000003
+    - 570.75
+? !!python/tuple
+- 63
+- 63
+- 60
+: - - 334.90000000000003
+    - 527.1
+  - - 334.90000000000003
+    - 527.1
+? !!python/tuple
+- 63
+- 92
+- 55
+: - - 334.90000000000003
+    - 527.1
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 63
+- 97
+- 56
+: - - 334.90000000000003
+    - 527.1
+  - - 341.35
+    - 527.7
+? !!python/tuple
+- 64
+- 93
+- 10
+: - - 253.3
+    - 602.25
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 65
+- 6
+- 77
+: - - 232.55
+    - 490.6
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 65
+- 60
+- 78
+: - - 232.55
+    - 490.6
+  - - 246.8
+    - 498.55
+? !!python/tuple
+- 65
+- 65
+- 92
+: - - 232.55
+    - 490.6
+  - - 232.55
+    - 490.6
+? !!python/tuple
+- 65
+- 65
+- 94
+: - - 232.55
+    - 490.6
+  - - 232.55
+    - 490.6
+? !!python/tuple
+- 65
+- 86
+- 81
+: - - 232.55
+    - 490.6
+  - - 258.95
+    - 486.1
+? !!python/tuple
+- 66
+- 66
+- 83
+: - - 427.90000000000003
+    - 458.8
+  - - 427.90000000000003
+    - 458.8
+? !!python/tuple
+- 67
+- 51
+- 149
+: - - 315.75
+    - 172.85000000000002
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 67
+- 51
+- 153
+: - - 315.75
+    - 172.85000000000002
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 67
+- 51
+- 159
+: - - 315.75
+    - 172.85000000000002
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 69
+- 6
+- 0
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 218.0
+    - 576.9
+? !!python/tuple
+- 69
+- 41
+- 153
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 69
+- 41
+- 157
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 69
+- 41
+- 163
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.0
+    - 170.75
+? !!python/tuple
+- 69
+- 71
+- 156
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 69
+- 71
+- 160
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 69
+- 71
+- 166
+: - - 260.65000000000003
+    - 169.20000000000002
+  - - 283.45
+    - 159.8
+? !!python/tuple
+- 70
+- 98
+- 142
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 70
+- 98
+- 143
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 70
+- 98
+- 146
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 70
+- 98
+- 147
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 70
+- 98
+- 152
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 70
+- 98
+- 153
+: - - 415.25
+    - 187.35000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 71
+- 51
+- 155
+: - - 283.45
+    - 159.8
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 71
+- 51
+- 159
+: - - 283.45
+    - 159.8
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 71
+- 51
+- 165
+: - - 283.45
+    - 159.8
+  - - 341.20000000000005
+    - 173.5
+? !!python/tuple
+- 72
+- 85
+- 75
+: - - 358.45000000000005
+    - 495.6
+  - - 391.45000000000005
+    - 497.90000000000003
+? !!python/tuple
+- 74
+- 7
+- 43
+: - - 350.15000000000003
+    - 533.2
+  - - 345.3
+    - 568.1
+? !!python/tuple
+- 74
+- 43
+- 45
+: - - 350.15000000000003
+    - 533.2
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 75
+- 47
+- 61
+: - - 434.6
+    - 519.35
+  - - 448.05
+    - 549.45
+? !!python/tuple
+- 76
+- 10
+- 73
+: - - 345.05
+    - 498.20000000000005
+  - - 347.75
+    - 500.90000000000003
+? !!python/tuple
+- 76
+- 84
+- 66
+: - - 345.05
+    - 498.20000000000005
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 77
+- 1
+- 93
+: - - 227.5
+    - 441.15000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 77
+- 1
+- 95
+: - - 227.5
+    - 441.15000000000003
+  - - 262.8
+    - 444.3
+? !!python/tuple
+- 78
+- 18
+- 126
+: - - 242.60000000000002
+    - 325.3
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 78
+- 18
+- 130
+: - - 242.60000000000002
+    - 325.3
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 78
+- 18
+- 136
+: - - 242.60000000000002
+    - 325.3
+  - - 273.15000000000003
+    - 328.0
+? !!python/tuple
+- 78
+- 78
+- 125
+: - - 242.60000000000002
+    - 325.3
+  - - 242.60000000000002
+    - 325.3
+? !!python/tuple
+- 78
+- 78
+- 129
+: - - 242.60000000000002
+    - 325.3
+  - - 242.60000000000002
+    - 325.3
+? !!python/tuple
+- 78
+- 78
+- 135
+: - - 242.60000000000002
+    - 325.3
+  - - 242.60000000000002
+    - 325.3
+? !!python/tuple
+- 79
+- 20
+- 140
+: - - 257.90000000000003
+    - 208.75
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 79
+- 20
+- 144
+: - - 257.90000000000003
+    - 208.75
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 79
+- 20
+- 150
+: - - 257.90000000000003
+    - 208.75
+  - - 281.15000000000003
+    - 210.05
+? !!python/tuple
+- 79
+- 69
+- 152
+: - - 257.90000000000003
+    - 208.75
+  - - 260.65000000000003
+    - 169.20000000000002
+? !!python/tuple
+- 79
+- 69
+- 156
+: - - 257.90000000000003
+    - 208.75
+  - - 260.65000000000003
+    - 169.20000000000002
+? !!python/tuple
+- 79
+- 69
+- 162
+: - - 257.90000000000003
+    - 208.75
+  - - 260.65000000000003
+    - 169.20000000000002
+? !!python/tuple
+- 81
+- 81
+- 54
+: - - 342.35
+    - 567.25
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 83
+- 43
+- 53
+: - - 350.25
+    - 530.6
+  - - 361.20000000000005
+    - 533.0500000000001
+? !!python/tuple
+- 83
+- 74
+- 51
+: - - 350.25
+    - 530.6
+  - - 350.15000000000003
+    - 533.2
+? !!python/tuple
+- 84
+- 9
+- 62
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 84
+- 75
+- 63
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 84
+- 75
+- 64
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 434.6
+    - 519.35
+? !!python/tuple
+- 84
+- 84
+- 72
+: - - 347.90000000000003
+    - 518.8000000000001
+  - - 347.90000000000003
+    - 518.8000000000001
+? !!python/tuple
+- 86
+- 39
+- 80
+: - - 258.95
+    - 486.1
+  - - 291.85
+    - 489.0
+? !!python/tuple
+- 87
+- 32
+- 107
+: - - 230.9
+    - 400.35
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 87
+- 32
+- 109
+: - - 230.9
+    - 400.35
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 87
+- 77
+- 106
+: - - 230.9
+    - 400.35
+  - - 227.5
+    - 441.15000000000003
+? !!python/tuple
+- 87
+- 77
+- 108
+: - - 230.9
+    - 400.35
+  - - 227.5
+    - 441.15000000000003
+? !!python/tuple
+- 88
+- 16
+- 116
+: - - 271.1
+    - 357.25
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 88
+- 16
+- 120
+: - - 271.1
+    - 357.25
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 88
+- 16
+- 126
+: - - 271.1
+    - 357.25
+  - - 304.15000000000003
+    - 360.5
+? !!python/tuple
+- 88
+- 32
+- 115
+: - - 271.1
+    - 357.25
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 88
+- 32
+- 119
+: - - 271.1
+    - 357.25
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 88
+- 32
+- 125
+: - - 271.1
+    - 357.25
+  - - 266.2
+    - 403.15000000000003
+? !!python/tuple
+- 89
+- 19
+- 134
+: - - 248.75
+    - 247.10000000000002
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 89
+- 19
+- 138
+: - - 248.75
+    - 247.10000000000002
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 89
+- 19
+- 144
+: - - 248.75
+    - 247.10000000000002
+  - - 278.75
+    - 249.40000000000003
+? !!python/tuple
+- 89
+- 79
+- 139
+: - - 248.75
+    - 247.10000000000002
+  - - 257.90000000000003
+    - 208.75
+? !!python/tuple
+- 89
+- 79
+- 143
+: - - 248.75
+    - 247.10000000000002
+  - - 257.90000000000003
+    - 208.75
+? !!python/tuple
+- 89
+- 79
+- 149
+: - - 248.75
+    - 247.10000000000002
+  - - 257.90000000000003
+    - 208.75
+? !!python/tuple
+- 89
+- 99
+- 133
+: - - 248.75
+    - 247.10000000000002
+  - - 241.25
+    - 286.2
+? !!python/tuple
+- 89
+- 99
+- 137
+: - - 248.75
+    - 247.10000000000002
+  - - 241.25
+    - 286.2
+? !!python/tuple
+- 89
+- 99
+- 143
+: - - 248.75
+    - 247.10000000000002
+  - - 241.25
+    - 286.2
+? !!python/tuple
+- 91
+- 70
+- 145
+: - - 349.35
+    - 174.45000000000002
+  - - 415.25
+    - 187.35000000000002
+? !!python/tuple
+- 91
+- 70
+- 149
+: - - 349.35
+    - 174.45000000000002
+  - - 415.25
+    - 187.35000000000002
+? !!python/tuple
+- 91
+- 70
+- 155
+: - - 349.35
+    - 174.45000000000002
+  - - 415.25
+    - 187.35000000000002
+? !!python/tuple
+- 92
+- 81
+- 32
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 342.35
+    - 567.25
+? !!python/tuple
+- 92
+- 92
+- 31
+: - - 330.90000000000003
+    - 567.0500000000001
+  - - 330.90000000000003
+    - 567.0500000000001
+? !!python/tuple
+- 93
+- 4
+- 2
+: - - 316.95000000000005
+    - 618.75
+  - - 340.05
+    - 622.0
+? !!python/tuple
+- 93
+- 93
+- 3
+: - - 316.95000000000005
+    - 618.75
+  - - 316.95000000000005
+    - 618.75
+? !!python/tuple
+- 94
+- 46
+- 41
+: - - 408.45000000000005
+    - 546.5
+  - - 405.95000000000005
+    - 573.4
+? !!python/tuple
+- 96
+- 100
+- 47
+: - - 263.7
+    - 533.15
+  - - 284.2564697265625
+    - 532.891845703125
+? !!python/tuple
+- 97
+- 9
+- 58
+: - - 341.35
+    - 527.7
+  - - 350.55
+    - 525.8000000000001
+? !!python/tuple
+- 98
+- 98
+- 141
+: - - 448.25
+    - 194.60000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 98
+- 98
+- 145
+: - - 448.25
+    - 194.60000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 98
+- 98
+- 151
+: - - 448.25
+    - 194.60000000000002
+  - - 448.25
+    - 194.60000000000002
+? !!python/tuple
+- 99
+- 29
+- 130
+: - - 241.25
+    - 286.2
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 99
+- 29
+- 134
+: - - 241.25
+    - 286.2
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 99
+- 29
+- 140
+: - - 241.25
+    - 286.2
+  - - 276.2
+    - 288.8
+? !!python/tuple
+- 99
+- 87
+- 129
+: - - 241.25
+    - 286.2
+  - - 230.9
+    - 400.35
+? !!python/tuple
+- 99
+- 87
+- 133
+: - - 241.25
+    - 286.2
+  - - 230.9
+    - 400.35
+? !!python/tuple
+- 99
+- 87
+- 139
+: - - 241.25
+    - 286.2
+  - - 230.9
+    - 400.35
+? !!python/tuple
+- 103
+- 103
+- 110
+: - - 431.1551818847656
+    - 371.0977783203125
+  - - 431.1551818847656
+    - 371.0977783203125
+? !!python/tuple
+- 103
+- 103
+- 111
+: - - 432.0601806640625
+    - 372.5963134765625
+  - - 432.0601806640625
+    - 372.5963134765625
+? !!python/tuple
+- 103
+- 103
+- 112
+: - - 432.0601806640625
+    - 372.5963134765625
+  - - 432.0601806640625
+    - 372.5963134765625
+? !!python/tuple
+- 103
+- 103
+- 114
+: - - 432.0601806640625
+    - 372.5963134765625
+  - - 432.0601806640625
+    - 372.5963134765625
+? !!python/tuple
+- 103
+- 103
+- 115
+: - - 432.0601806640625
+    - 372.5963134765625
+  - - 432.0601806640625
+    - 372.5963134765625
+? !!python/tuple
+- 103
+- 103
+- 116
+: - - 432.0601806640625
+    - 372.5963134765625
+  - - 432.0601806640625
+    - 372.5963134765625
+? !!python/tuple
+- 103
+- 103
+- 121
+: - - 431.1551818847656
+    - 371.0977783203125
+  - - 431.1551818847656
+    - 371.0977783203125
+? !!python/tuple
+- 103
+- 103
+- 127
+: - - 432.0601806640625
+    - 372.5963134765625
+  - - 432.0601806640625
+    - 372.5963134765625
+? !!python/tuple
+- 104
+- 104
+- 110
+: - - 401.18572998046875
+    - 387.29254150390625
+  - - 401.18572998046875
+    - 387.29254150390625
diff --git a/output_yaml/way_pts_edited.yaml b/output_yaml/way_pts_edited.yaml
new file mode 100644
index 0000000..7086630
--- /dev/null
+++ b/output_yaml/way_pts_edited.yaml
@@ -0,0 +1,1269 @@
+0:
+- 394.8
+- 456.1
+1:
+- 262.5809631347656
+- 444.19354248046875
+2:
+- 368.90000000000003
+- 366.5
+3:
+- 407.40000000000003
+- 628.1500000000001
+4:
+- 340.05
+- 622.0
+5:
+- 241.5
+- 586.1
+6:
+- 218.0
+- 576.9
+7:
+- 345.3
+- 568.1
+8:
+- 363.20000000000005
+- 530.65
+9:
+- 350.55
+- 525.8000000000001
+10:
+- 347.75
+- 500.90000000000003
+11:
+- 329.0235290527344
+- 450.93743896484375
+12:
+- 431.1
+- 417.6
+13:
+- 398.20000000000005
+- 415.0
+14:
+- 365.1
+- 412.35
+15:
+- 401.95000000000005
+- 369.5
+16:
+- 304.15000000000003
+- 360.5
+17:
+- 306.1
+- 331.3
+18:
+- 273.15000000000003
+- 328.0
+19:
+- 278.75
+- 249.40000000000003
+20:
+- 281.15000000000003
+- 210.05
+21:
+- 235.15
+- 578.5
+22:
+- 428.3
+- 545.8000000000001
+23:
+- 441.0
+- 538.15
+24:
+- 367.0
+- 531.5500000000001
+25:
+- 243.55
+- 531.15
+26:
+- 325.1
+- 492.05
+27:
+- 347.40000000000003
+- 212.5
+28:
+- 295.8104248046875
+- 447.5629577636719
+29:
+- 276.2
+- 288.8
+30:
+- 332.75
+- 409.55
+31:
+- 299.90000000000003
+- 406.20000000000005
+32:
+- 266.2
+- 403.15000000000003
+33:
+- 416.0
+- 593.35
+34:
+- 359.0
+- 570.1
+35:
+- 429.8
+- 540.35
+36:
+- 418.45000000000005
+- 539.7
+37:
+- 235.8
+- 532.1
+38:
+- 356.15000000000003
+- 498.95000000000005
+39:
+- 291.85
+- 489.0
+40:
+- 362.0938415527344
+- 453.5181579589844
+41:
+- 283.0
+- 170.75
+42:
+- 240.65
+- 593.3000000000001
+43:
+- 361.20000000000005
+- 533.0500000000001
+44:
+- 285.8
+- 507.80000000000007
+45:
+- 444.25
+- 576.9
+46:
+- 405.95000000000005
+- 573.4
+47:
+- 448.05
+- 549.45
+48:
+- 276.85
+- 501.45000000000005
+49:
+- 313.85
+- 211.0
+50:
+- 434.95000000000005
+- 537.45
+51:
+- 341.20000000000005
+- 173.5
+52:
+- 337.40000000000003
+- 363.65000000000003
+53:
+- 442.35
+- 535.35
+54:
+- 237.9
+- 579.0500000000001
+55:
+- 436.95000000000005
+- 577.3000000000001
+56:
+- 423.45000000000005
+- 576.1
+57:
+- 391.3
+- 573.1
+58:
+- 432.75
+- 548.65
+59:
+- 287.05
+- 502.45000000000005
+60:
+- 246.8
+- 498.55
+61:
+- 343.75
+- 173.10000000000002
+62:
+- 444.15000000000003
+- 570.75
+63:
+- 334.90000000000003
+- 527.1
+64:
+- 253.3
+- 602.25
+65:
+- 232.55
+- 490.6
+66:
+- 427.90000000000003
+- 458.8
+67:
+- 315.75
+- 172.85000000000002
+68:
+- 430.70000000000005
+- 537.3000000000001
+69:
+- 260.65000000000003
+- 169.20000000000002
+70:
+- 415.25
+- 187.35000000000002
+71:
+- 283.45
+- 159.8
+72:
+- 358.45000000000005
+- 495.6
+73:
+- 427.3
+- 540.75
+74:
+- 350.15000000000003
+- 533.2
+75:
+- 434.6
+- 519.35
+76:
+- 345.05
+- 498.20000000000005
+77:
+- 227.5
+- 441.15000000000003
+78:
+- 242.60000000000002
+- 325.3
+79:
+- 257.90000000000003
+- 208.75
+80:
+- 416.95000000000005
+- 536.1
+81:
+- 342.35
+- 567.25
+82:
+- 427.35
+- 537.4
+83:
+- 350.25
+- 530.6
+84:
+- 347.90000000000003
+- 518.8000000000001
+85:
+- 391.45000000000005
+- 497.90000000000003
+86:
+- 258.95
+- 486.1
+87:
+- 230.9
+- 400.35
+88:
+- 271.1
+- 357.25
+89:
+- 248.75
+- 247.10000000000002
+90:
+- 380.5
+- 214.0
+91:
+- 349.35
+- 174.45000000000002
+92:
+- 330.90000000000003
+- 567.0500000000001
+93:
+- 316.95000000000005
+- 618.75
+94:
+- 408.45000000000005
+- 546.5
+95:
+- 416.0
+- 539.15
+96:
+- 263.7
+- 533.15
+97:
+- 341.35
+- 527.7
+98:
+- 448.25
+- 194.60000000000002
+99:
+- 241.25
+- 286.2
+100:
+- 327.40000000000003
+- 621.5
+101:
+- 312.55
+- 602.4
+102:
+- 318.15000000000003
+- 611.2
+103:
+- 446.05
+- 595.9
+104:
+- 243.8
+- 601.65
+105:
+- 234.05
+- 602.45
+106:
+- 233.10000000000002
+- 612.45
+107:
+- 237.45000000000002
+- 619.3000000000001
+108:
+- 247.45
+- 620.2
+109:
+- 257.45
+- 621.1500000000001
+110:
+- 267.45
+- 622.1
+111:
+- 277.45
+- 623.0500000000001
+112:
+- 287.45
+- 624.0
+113:
+- 292.25
+- 629.9000000000001
+114:
+- 302.25
+- 631.0
+115:
+- 312.25
+- 632.0500000000001
+116:
+- 322.25
+- 633.1
+117:
+- 332.25
+- 634.1
+118:
+- 340.90000000000003
+- 633.1500000000001
+119:
+- 351.6
+- 622.4000000000001
+120:
+- 361.6
+- 623.3000000000001
+121:
+- 368.1
+- 627.85
+122:
+- 382.5
+- 624.8000000000001
+123:
+- 392.5
+- 625.6500000000001
+124:
+- 273.0
+- 586.9
+125:
+- 263.0
+- 594.1
+126:
+- 283.0
+- 587.65
+127:
+- 285.90000000000003
+- 597.25
+128:
+- 287.85
+- 607.25
+129:
+- 270.65000000000003
+- 606.95
+130:
+- 260.65000000000003
+- 604.7
+131:
+- 296.85
+- 613.45
+132:
+- 306.85
+- 616.45
+133:
+- 207.55
+- 580.4
+134:
+- 197.55
+- 579.4
+135:
+- 187.55
+- 578.4
+136:
+- 433.25
+- 569.6
+137:
+- 368.95000000000005
+- 570.4
+138:
+- 383.45000000000005
+- 571.75
+139:
+- 344.55
+- 578.65
+140:
+- 343.6
+- 588.65
+141:
+- 342.65000000000003
+- 598.65
+142:
+- 341.70000000000005
+- 608.6500000000001
+143:
+- 472.5
+- 567.75
+144:
+- 473.70000000000005
+- 553.2
+145:
+- 455.75
+- 550.4
+146:
+- 445.75
+- 556.65
+147:
+- 407.45000000000005
+- 557.0
+148:
+- 473.85
+- 543.65
+149:
+- 349.3
+- 543.7
+150:
+- 348.35
+- 553.7
+151:
+- 370.6
+- 542.4
+152:
+- 380.6
+- 543.35
+153:
+- 390.6
+- 544.3000000000001
+154:
+- 400.6
+- 545.2
+155:
+- 239.4
+- 541.0
+156:
+- 238.4
+- 551.0
+157:
+- 237.45000000000002
+- 561.0
+158:
+- 236.45000000000002
+- 571.0
+159:
+- 377.5
+- 532.65
+160:
+- 387.5
+- 533.5
+161:
+- 397.5
+- 534.35
+162:
+- 407.5
+- 535.2
+163:
+- 254.05
+- 532.65
+164:
+- 338.6
+- 537.6
+165:
+- 337.90000000000003
+- 547.6
+166:
+- 337.55
+- 557.6
+167:
+- 359.05
+- 516.1
+168:
+- 366.65000000000003
+- 519.45
+169:
+- 376.65000000000003
+- 520.35
+170:
+- 386.65000000000003
+- 521.25
+171:
+- 396.65000000000003
+- 522.2
+172:
+- 406.65000000000003
+- 523.1
+173:
+- 416.65000000000003
+- 524.0
+174:
+- 426.65000000000003
+- 524.7
+175:
+- 352.70000000000005
+- 509.9
+176:
+- 364.90000000000003
+- 511.20000000000005
+177:
+- 374.90000000000003
+- 512.35
+178:
+- 384.90000000000003
+- 513.5
+179:
+- 394.90000000000003
+- 514.65
+180:
+- 404.90000000000003
+- 515.8000000000001
+181:
+- 423.40000000000003
+- 517.9
+182:
+- 413.40000000000003
+- 516.75
+183:
+- 285.35
+- 518.3000000000001
+184:
+- 284.45
+- 528.3000000000001
+185:
+- 280.35
+- 535.15
+186:
+- 288.05
+- 536.0
+187:
+- 298.05
+- 536.85
+188:
+- 338.8
+- 505.55000000000007
+189:
+- 336.85
+- 515.5
+190:
+- 297.20000000000005
+- 502.80000000000007
+191:
+- 307.20000000000005
+- 503.75
+192:
+- 319.6
+- 504.20000000000005
+193:
+- 329.6
+- 504.9
+194:
+- 343.85
+- 511.6
+195:
+- 256.8
+- 498.85
+196:
+- 266.8
+- 500.40000000000003
+197:
+- 265.85
+- 510.35
+198:
+- 264.85
+- 520.35
+199:
+- 368.95000000000005
+- 496.55
+200:
+- 378.95000000000005
+- 497.40000000000003
+201:
+- 335.6
+- 493.65000000000003
+202:
+- 227.0
+- 500.05
+203:
+- 222.4
+- 510.9
+204:
+- 221.4
+- 520.9
+205:
+- 221.20000000000002
+- 530.9
+206:
+- 219.45000000000002
+- 540.9
+207:
+- 218.45000000000002
+- 550.9
+208:
+- 217.5
+- 560.9
+209:
+- 236.0
+- 506.15
+210:
+- 245.70000000000002
+- 507.75
+211:
+- 244.9
+- 517.75
+212:
+- 302.3
+- 490.6
+213:
+- 312.3
+- 491.5
+214:
+- 269.45
+- 487.70000000000005
+215:
+- 279.45
+- 488.6
+216:
+- 242.25
+- 485.15000000000003
+217:
+- 427.0
+- 469.35
+218:
+- 426.20000000000005
+- 479.35
+219:
+- 425.35
+- 489.35
+220:
+- 424.55
+- 499.35
+221:
+- 415.6
+- 500.5
+222:
+- 405.6
+- 499.70000000000005
+223:
+- 436.85
+- 504.75
+224:
+- 429.40000000000003
+- 507.35
+225:
+- 399.40000000000003
+- 504.5
+226:
+- 438.45000000000005
+- 459.65000000000003
+227:
+- 448.45000000000005
+- 460.20000000000005
+228:
+- 394.0
+- 466.65000000000003
+229:
+- 393.20000000000005
+- 476.65000000000003
+230:
+- 392.40000000000003
+- 486.65000000000003
+231:
+- 405.35
+- 456.95000000000005
+232:
+- 415.35
+- 457.75
+233:
+- 360.90000000000003
+- 464.0
+234:
+- 360.1
+- 474.0
+235:
+- 359.25
+- 484.0
+236:
+- 372.35
+- 454.3
+237:
+- 382.35
+- 455.1
+238:
+- 327.90000000000003
+- 461.1
+239:
+- 327.0
+- 471.1
+240:
+- 326.20000000000005
+- 481.1
+241:
+- 339.40000000000003
+- 451.55
+242:
+- 349.40000000000003
+- 452.40000000000003
+243:
+- 294.90000000000003
+- 457.95000000000005
+244:
+- 293.95
+- 467.95000000000005
+245:
+- 293.0
+- 477.95000000000005
+246:
+- 306.25
+- 448.45000000000005
+247:
+- 316.25
+- 449.45000000000005
+248:
+- 261.85
+- 454.85
+249:
+- 260.95
+- 464.85
+250:
+- 260.1
+- 474.85
+251:
+- 273.35
+- 445.25
+252:
+- 283.35
+- 446.25
+253:
+- 226.10000000000002
+- 451.6
+254:
+- 225.20000000000002
+- 461.6
+255:
+- 224.25
+- 471.6
+256:
+- 224.20000000000002
+- 481.6
+257:
+- 238.0
+- 441.90000000000003
+258:
+- 248.0
+- 442.90000000000003
+259:
+- 430.3
+- 428.1
+260:
+- 429.55
+- 438.1
+261:
+- 428.75
+- 448.1
+262:
+- 441.55
+- 418.5
+263:
+- 451.55
+- 419.25
+264:
+- 397.35
+- 425.5
+265:
+- 396.5
+- 435.5
+266:
+- 395.70000000000005
+- 445.5
+267:
+- 408.75
+- 415.90000000000003
+268:
+- 418.75
+- 416.65000000000003
+269:
+- 364.3
+- 422.90000000000003
+270:
+- 363.5
+- 432.90000000000003
+271:
+- 362.65000000000003
+- 442.90000000000003
+272:
+- 375.6
+- 413.20000000000005
+273:
+- 385.6
+- 414.0
+274:
+- 331.75
+- 420.1
+275:
+- 330.8
+- 430.1
+276:
+- 329.8
+- 440.1
+277:
+- 343.3
+- 410.5
+278:
+- 353.3
+- 411.35
+279:
+- 298.75
+- 416.70000000000005
+280:
+- 297.8
+- 426.70000000000005
+281:
+- 296.85
+- 436.70000000000005
+282:
+- 310.40000000000003
+- 407.35
+283:
+- 320.40000000000003
+- 408.3
+284:
+- 265.40000000000003
+- 413.65000000000003
+285:
+- 264.55
+- 423.65000000000003
+286:
+- 263.7
+- 433.65000000000003
+287:
+- 276.65000000000003
+- 404.05
+288:
+- 286.78643798828125
+- 405.05059814453125
+289:
+- 229.65
+- 410.85
+290:
+- 228.8
+- 420.85
+291:
+- 227.95000000000002
+- 430.85
+292:
+- 241.45000000000002
+- 401.05
+293:
+- 251.45
+- 401.85
+294:
+- 401.05
+- 380.05
+295:
+- 400.25
+- 390.05
+296:
+- 399.40000000000003
+- 400.05
+297:
+- 368.05
+- 377.05
+298:
+- 367.20000000000005
+- 387.05
+299:
+- 366.40000000000003
+- 397.05
+300:
+- 379.45000000000005
+- 367.45000000000005
+301:
+- 389.45000000000005
+- 368.35
+302:
+- 336.35
+- 374.15000000000003
+303:
+- 335.3
+- 384.15000000000003
+304:
+- 334.3
+- 394.15000000000003
+305:
+- 347.8
+- 364.6
+306:
+- 357.8
+- 365.55
+307:
+- 303.15000000000003
+- 371.05
+308:
+- 302.15000000000003
+- 381.05
+309:
+- 301.20000000000005
+- 391.05
+310:
+- 314.65000000000003
+- 361.55
+311:
+- 324.65000000000003
+- 362.5
+312:
+- 269.25
+- 367.70000000000005
+313:
+- 268.40000000000003
+- 377.70000000000005
+314:
+- 267.55
+- 387.70000000000005
+315:
+- 281.6
+- 358.45000000000005
+316:
+- 291.6
+- 359.40000000000003
+317:
+- 434.3
+- 345.05
+318:
+- 433.35
+- 355.05
+319:
+- 432.40000000000003
+- 365.05
+320:
+- 428.05
+- 371.70000000000005
+321:
+- 418.05
+- 370.85
+322:
+- 434.40000000000003
+- 376.8
+323:
+- 433.65000000000003
+- 386.8
+324:
+- 432.85
+- 396.8
+325:
+- 432.05
+- 406.8
+326:
+- 405.15000000000003
+- 341.85
+327:
+- 403.5
+- 351.70000000000005
+328:
+- 402.65000000000003
+- 361.70000000000005
+329:
+- 371.95000000000005
+- 339.15000000000003
+330:
+- 370.35
+- 349.05
+331:
+- 340.5
+- 336.75
+332:
+- 339.0
+- 346.70000000000005
+333:
+- 305.85
+- 341.8
+334:
+- 304.95000000000005
+- 351.8
+335:
+- 272.35
+- 338.55
+336:
+- 271.55
+- 348.55
+337:
+- 283.65000000000003
+- 328.90000000000003
+338:
+- 293.65000000000003
+- 329.90000000000003
+339:
+- 253.10000000000002
+- 326.05
+340:
+- 263.1
+- 326.95000000000005
+341:
+- 275.55
+- 299.3
+342:
+- 274.8
+- 309.3
+343:
+- 274.05
+- 319.3
+344:
+- 286.7
+- 289.3
+345:
+- 296.7
+- 289.85
+346:
+- 306.70000000000005
+- 290.45
+347:
+- 239.70000000000002
+- 296.65000000000003
+348:
+- 238.60000000000002
+- 306.65000000000003
+349:
+- 237.5
+- 316.65000000000003
+350:
+- 235.60000000000002
+- 336.65000000000003
+351:
+- 234.8
+- 346.65000000000003
+352:
+- 233.95000000000002
+- 356.65000000000003
+353:
+- 233.20000000000002
+- 366.65000000000003
+354:
+- 232.4
+- 376.65000000000003
+355:
+- 231.60000000000002
+- 386.65000000000003
+356:
+- 251.7
+- 286.90000000000003
+357:
+- 261.7
+- 287.65000000000003
+358:
+- 278.05
+- 259.95
+359:
+- 277.45
+- 269.95
+360:
+- 276.8
+- 279.95
+361:
+- 289.15000000000003
+- 249.90000000000003
+362:
+- 299.15000000000003
+- 250.5
+363:
+- 309.15000000000003
+- 251.05
+364:
+- 245.4
+- 257.55
+365:
+- 242.95000000000002
+- 267.55
+366:
+- 241.45000000000002
+- 277.55
+367:
+- 259.3
+- 248.2
+368:
+- 269.3
+- 248.8
+369:
+- 357.90000000000003
+- 213.4
+370:
+- 367.90000000000003
+- 213.85000000000002
+371:
+- 324.35
+- 211.9
+372:
+- 334.35
+- 212.35000000000002
+373:
+- 280.7
+- 220.55
+374:
+- 280.05
+- 230.55
+375:
+- 279.40000000000003
+- 240.55
+376:
+- 291.05
+- 210.35000000000002
+377:
+- 301.05
+- 210.8
+378:
+- 255.8
+- 219.20000000000002
+379:
+- 253.2
+- 229.20000000000002
+380:
+- 250.45
+- 239.20000000000002
+381:
+- 268.40000000000003
+- 209.25
+382:
+- 414.6
+- 197.9
+383:
+- 414.05
+- 207.9
+384:
+- 411.05
+- 215.70000000000002
+385:
+- 401.05
+- 215.3
+386:
+- 391.05
+- 214.85000000000002
+387:
+- 420.95000000000005
+- 216.10000000000002
+388:
+- 430.95000000000005
+- 216.5
+389:
+- 440.95000000000005
+- 216.95000000000002
+390:
+- 447.35
+- 212.5
+391:
+- 447.85
+- 202.5
+392:
+- 424.8
+- 188.35000000000002
+393:
+- 434.8
+- 190.4
+394:
+- 348.70000000000005
+- 184.95000000000002
+395:
+- 348.25
+- 194.95000000000002
+396:
+- 347.75
+- 204.95000000000002
+397:
+- 359.5
+- 175.3
+398:
+- 369.5
+- 177.0
+399:
+- 379.5
+- 179.05
+400:
+- 381.70000000000005
+- 187.9
+401:
+- 381.20000000000005
+- 197.9
+402:
+- 393.6
+- 181.95000000000002
+403:
+- 403.6
+- 184.0
+404:
+- 315.15000000000003
+- 183.35000000000002
+405:
+- 314.70000000000005
+- 193.35000000000002
+406:
+- 314.20000000000005
+- 203.35000000000002
+407:
+- 325.90000000000003
+- 172.85000000000002
+408:
+- 282.6
+- 181.25
+409:
+- 282.05
+- 191.25
+410:
+- 281.5
+- 201.25
+411:
+- 293.5
+- 171.15
+412:
+- 303.5
+- 171.65
+413:
+- 259.3
+- 179.65
+414:
+- 258.6
+- 189.65
+415:
+- 257.95
+- 199.65
+416:
+- 271.15000000000003
+- 170.0
+417:
+- 293.1
+- 160.85000000000002
+418:
+- 303.1
+- 163.0
+419:
+- 313.1
+- 165.10000000000002
+420:
+- 333.1
+- 169.3
+421:
+- 265.45
+- 155.05
+422:
+- 276.05
+- 157.20000000000002
diff --git a/output_yaml/way_pts_high_level.yaml b/output_yaml/way_pts_high_level.yaml
new file mode 100644
index 0000000..991748a
--- /dev/null
+++ b/output_yaml/way_pts_high_level.yaml
@@ -0,0 +1,1275 @@
+0:
+- 394.8
+- 456.1
+1:
+- 262.8
+- 444.3
+2:
+- 368.90000000000003
+- 366.5
+3:
+- 407.40000000000003
+- 628.1500000000001
+4:
+- 340.05
+- 622.0
+5:
+- 241.5
+- 586.1
+6:
+- 218.0
+- 576.9
+7:
+- 345.3
+- 568.1
+8:
+- 363.20000000000005
+- 530.65
+9:
+- 350.55
+- 525.8000000000001
+10:
+- 347.75
+- 500.90000000000003
+11:
+- 328.85
+- 450.6
+12:
+- 431.1
+- 417.6
+13:
+- 398.20000000000005
+- 415.0
+14:
+- 365.1
+- 412.35
+15:
+- 401.95000000000005
+- 369.5
+16:
+- 304.15000000000003
+- 360.5
+17:
+- 306.1
+- 331.3
+18:
+- 273.15000000000003
+- 328.0
+19:
+- 278.75
+- 249.40000000000003
+20:
+- 281.15000000000003
+- 210.05
+21:
+- 235.15
+- 578.5
+22:
+- 428.3
+- 545.8000000000001
+23:
+- 441.0
+- 538.15
+24:
+- 367.0
+- 531.5500000000001
+25:
+- 243.55
+- 531.15
+26:
+- 325.1
+- 492.05
+27:
+- 347.40000000000003
+- 212.5
+28:
+- 295.75
+- 447.45000000000005
+29:
+- 276.2
+- 288.8
+30:
+- 332.75
+- 409.55
+31:
+- 299.90000000000003
+- 406.20000000000005
+32:
+- 266.2
+- 403.15000000000003
+33:
+- 416.0
+- 593.35
+34:
+- 359.0
+- 570.1
+35:
+- 429.8
+- 540.35
+36:
+- 418.45000000000005
+- 539.7
+37:
+- 235.8
+- 532.1
+38:
+- 356.15000000000003
+- 498.95000000000005
+39:
+- 291.85
+- 489.0
+40:
+- 361.85
+- 453.5
+41:
+- 283.0
+- 170.75
+42:
+- 240.65
+- 593.3000000000001
+43:
+- 361.20000000000005
+- 533.0500000000001
+44:
+- 285.8
+- 507.80000000000007
+45:
+- 444.25
+- 576.9
+46:
+- 405.95000000000005
+- 573.4
+47:
+- 448.05
+- 549.45
+48:
+- 276.85
+- 501.45000000000005
+49:
+- 313.85
+- 211.0
+50:
+- 434.95000000000005
+- 537.45
+51:
+- 341.20000000000005
+- 173.5
+52:
+- 337.40000000000003
+- 363.65000000000003
+53:
+- 442.35
+- 535.35
+54:
+- 237.9
+- 579.0500000000001
+55:
+- 436.95000000000005
+- 577.3000000000001
+56:
+- 423.45000000000005
+- 576.1
+57:
+- 391.3
+- 573.1
+58:
+- 432.75
+- 548.65
+59:
+- 287.05
+- 502.45000000000005
+60:
+- 246.8
+- 498.55
+61:
+- 343.75
+- 173.10000000000002
+62:
+- 444.15000000000003
+- 570.75
+63:
+- 334.90000000000003
+- 527.1
+64:
+- 253.3
+- 602.25
+65:
+- 232.47743225097656
+- 490.1767883300781
+66:
+- 427.90000000000003
+- 458.8
+67:
+- 315.75
+- 172.85000000000002
+68:
+- 430.70000000000005
+- 537.3000000000001
+69:
+- 260.65000000000003
+- 169.20000000000002
+70:
+- 415.25
+- 187.35000000000002
+71:
+- 283.45
+- 159.8
+72:
+- 358.45000000000005
+- 495.6
+73:
+- 427.3
+- 540.75
+74:
+- 350.15000000000003
+- 533.2
+75:
+- 434.6
+- 519.35
+76:
+- 345.05
+- 498.20000000000005
+77:
+- 227.5
+- 441.15000000000003
+78:
+- 242.60000000000002
+- 325.3
+79:
+- 257.90000000000003
+- 208.75
+80:
+- 416.95000000000005
+- 536.1
+81:
+- 342.35
+- 567.25
+82:
+- 427.35
+- 537.4
+83:
+- 350.25
+- 530.6
+84:
+- 347.90000000000003
+- 518.8000000000001
+85:
+- 391.45000000000005
+- 497.90000000000003
+86:
+- 258.95
+- 486.1
+87:
+- 230.9
+- 400.35
+88:
+- 271.1
+- 357.25
+89:
+- 248.75
+- 247.10000000000002
+90:
+- 380.5
+- 214.0
+91:
+- 349.35
+- 174.45000000000002
+92:
+- 330.90000000000003
+- 567.0500000000001
+93:
+- 316.95000000000005
+- 618.75
+94:
+- 408.45000000000005
+- 546.5
+95:
+- 416.0
+- 539.15
+96:
+- 263.7
+- 533.15
+97:
+- 341.35
+- 527.7
+98:
+- 448.25
+- 194.60000000000002
+99:
+- 241.25
+- 286.2
+100:
+- 327.40000000000003
+- 621.5
+101:
+- 312.55
+- 602.4
+102:
+- 318.15000000000003
+- 611.2
+103:
+- 446.05
+- 595.9
+104:
+- 243.8
+- 601.65
+105:
+- 234.05
+- 602.45
+106:
+- 233.10000000000002
+- 612.45
+107:
+- 237.45000000000002
+- 619.3000000000001
+108:
+- 247.45
+- 620.2
+109:
+- 257.45
+- 621.1500000000001
+110:
+- 267.45
+- 622.1
+111:
+- 277.45
+- 623.0500000000001
+112:
+- 287.45
+- 624.0
+113:
+- 292.25
+- 629.9000000000001
+114:
+- 302.25
+- 631.0
+115:
+- 312.25
+- 632.0500000000001
+116:
+- 322.25
+- 633.1
+117:
+- 332.25
+- 634.1
+118:
+- 340.90000000000003
+- 633.1500000000001
+119:
+- 351.6
+- 622.4000000000001
+120:
+- 361.6
+- 623.3000000000001
+121:
+- 368.1
+- 627.85
+122:
+- 382.5
+- 624.8000000000001
+123:
+- 392.5
+- 625.6500000000001
+124:
+- 273.0
+- 586.9
+125:
+- 263.0
+- 594.1
+126:
+- 283.0
+- 587.65
+127:
+- 285.90000000000003
+- 597.25
+128:
+- 287.85
+- 607.25
+129:
+- 270.65000000000003
+- 606.95
+130:
+- 260.65000000000003
+- 604.7
+131:
+- 296.85
+- 613.45
+132:
+- 306.85
+- 616.45
+133:
+- 207.55
+- 580.4
+134:
+- 197.55
+- 579.4
+135:
+- 187.55
+- 578.4
+136:
+- 433.25
+- 569.6
+137:
+- 368.95000000000005
+- 570.4
+138:
+- 383.45000000000005
+- 571.75
+139:
+- 344.55
+- 578.65
+140:
+- 343.6
+- 588.65
+141:
+- 342.65000000000003
+- 598.65
+142:
+- 341.70000000000005
+- 608.6500000000001
+143:
+- 472.5
+- 567.75
+144:
+- 473.70000000000005
+- 553.2
+145:
+- 455.75
+- 550.4
+146:
+- 445.75
+- 556.65
+147:
+- 407.45000000000005
+- 557.0
+148:
+- 473.85
+- 543.65
+149:
+- 349.3
+- 543.7
+150:
+- 348.35
+- 553.7
+151:
+- 370.6
+- 542.4
+152:
+- 380.6
+- 543.35
+153:
+- 390.6
+- 544.3000000000001
+154:
+- 400.6
+- 545.2
+155:
+- 239.4
+- 541.0
+156:
+- 238.4
+- 551.0
+157:
+- 237.45000000000002
+- 561.0
+158:
+- 236.45000000000002
+- 571.0
+159:
+- 377.5
+- 532.65
+160:
+- 387.5
+- 533.5
+161:
+- 397.5
+- 534.35
+162:
+- 407.5
+- 535.2
+163:
+- 254.05
+- 532.65
+164:
+- 338.6
+- 537.6
+165:
+- 337.90000000000003
+- 547.6
+166:
+- 337.55
+- 557.6
+167:
+- 359.05
+- 516.1
+168:
+- 366.65000000000003
+- 519.45
+169:
+- 376.65000000000003
+- 520.35
+170:
+- 386.65000000000003
+- 521.25
+171:
+- 396.65000000000003
+- 522.2
+172:
+- 406.65000000000003
+- 523.1
+173:
+- 416.65000000000003
+- 524.0
+174:
+- 426.65000000000003
+- 524.7
+175:
+- 352.70000000000005
+- 509.9
+176:
+- 364.90000000000003
+- 511.20000000000005
+177:
+- 374.90000000000003
+- 512.35
+178:
+- 384.90000000000003
+- 513.5
+179:
+- 394.90000000000003
+- 514.65
+180:
+- 404.90000000000003
+- 515.8000000000001
+181:
+- 423.40000000000003
+- 517.9
+182:
+- 413.40000000000003
+- 516.75
+183:
+- 285.35
+- 518.3000000000001
+184:
+- 284.45
+- 528.3000000000001
+185:
+- 280.35
+- 535.15
+186:
+- 288.05
+- 536.0
+187:
+- 298.05
+- 536.85
+188:
+- 338.8
+- 505.55000000000007
+189:
+- 336.85
+- 515.5
+190:
+- 297.20000000000005
+- 502.80000000000007
+191:
+- 307.20000000000005
+- 503.75
+192:
+- 319.6
+- 504.20000000000005
+193:
+- 329.6
+- 504.9
+194:
+- 343.85
+- 511.6
+195:
+- 256.8
+- 498.85
+196:
+- 266.8
+- 500.40000000000003
+197:
+- 265.85
+- 510.35
+198:
+- 264.85
+- 520.35
+199:
+- 368.95000000000005
+- 496.55
+200:
+- 378.95000000000005
+- 497.40000000000003
+201:
+- 335.6
+- 493.65000000000003
+202:
+- 227.0
+- 500.05
+203:
+- 222.4
+- 510.9
+204:
+- 221.4
+- 520.9
+205:
+- 221.20000000000002
+- 530.9
+206:
+- 219.45000000000002
+- 540.9
+207:
+- 218.45000000000002
+- 550.9
+208:
+- 217.5
+- 560.9
+209:
+- 236.0
+- 506.15
+210:
+- 245.70000000000002
+- 507.75
+211:
+- 244.9
+- 517.75
+212:
+- 302.533203125
+- 490.032958984375
+213:
+- 312.3
+- 491.5
+214:
+- 269.45
+- 487.70000000000005
+215:
+- 279.45
+- 488.6
+216:
+- 242.25
+- 485.15000000000003
+217:
+- 427.0
+- 469.35
+218:
+- 426.20000000000005
+- 479.35
+219:
+- 425.35
+- 489.35
+220:
+- 424.55
+- 499.35
+221:
+- 415.6
+- 500.5
+222:
+- 405.6
+- 499.70000000000005
+223:
+- 436.85
+- 504.75
+224:
+- 429.40000000000003
+- 507.35
+225:
+- 399.40000000000003
+- 504.5
+226:
+- 438.45000000000005
+- 459.65000000000003
+227:
+- 448.45000000000005
+- 460.20000000000005
+228:
+- 394.0
+- 466.65000000000003
+229:
+- 393.20000000000005
+- 476.65000000000003
+230:
+- 392.40000000000003
+- 486.65000000000003
+231:
+- 405.35
+- 456.95000000000005
+232:
+- 415.35
+- 457.75
+233:
+- 360.90000000000003
+- 464.0
+234:
+- 360.1
+- 474.0
+235:
+- 359.25
+- 484.0
+236:
+- 372.35
+- 454.3
+237:
+- 382.35
+- 455.1
+238:
+- 327.90000000000003
+- 461.1
+239:
+- 326.94915771484375
+- 470.8092956542969
+240:
+- 326.6719970703125
+- 480.9545593261719
+241:
+- 339.40000000000003
+- 451.55
+242:
+- 349.40000000000003
+- 452.40000000000003
+243:
+- 294.90000000000003
+- 457.95000000000005
+244:
+- 293.95
+- 467.95000000000005
+245:
+- 293.0
+- 477.95000000000005
+246:
+- 306.3183288574219
+- 448.5001525878906
+247:
+- 316.58544921875
+- 449.3061218261719
+248:
+- 261.85
+- 454.85
+249:
+- 260.95
+- 464.85
+250:
+- 260.1
+- 474.85
+251:
+- 273.35
+- 445.25
+252:
+- 283.35
+- 446.25
+253:
+- 226.10000000000002
+- 451.6
+254:
+- 225.20000000000002
+- 461.6
+255:
+- 224.25
+- 471.6
+256:
+- 224.20000000000002
+- 481.6
+257:
+- 238.0
+- 441.90000000000003
+258:
+- 248.0
+- 442.90000000000003
+259:
+- 430.3
+- 428.1
+260:
+- 429.55
+- 438.1
+261:
+- 428.75
+- 448.1
+262:
+- 441.55
+- 418.5
+263:
+- 451.55
+- 419.25
+264:
+- 397.35
+- 425.5
+265:
+- 396.5
+- 435.5
+266:
+- 395.70000000000005
+- 445.5
+267:
+- 408.75
+- 415.90000000000003
+268:
+- 418.75
+- 416.65000000000003
+269:
+- 364.3
+- 422.90000000000003
+270:
+- 363.5
+- 432.90000000000003
+271:
+- 362.65000000000003
+- 442.90000000000003
+272:
+- 375.6
+- 413.20000000000005
+273:
+- 385.6
+- 414.0
+274:
+- 331.75
+- 420.1
+275:
+- 330.8
+- 430.1
+276:
+- 329.8
+- 440.1
+277:
+- 343.3
+- 410.5
+278:
+- 353.3
+- 411.35
+279:
+- 298.75
+- 416.70000000000005
+280:
+- 297.8
+- 426.70000000000005
+281:
+- 296.85
+- 436.70000000000005
+282:
+- 310.40000000000003
+- 407.35
+283:
+- 320.40000000000003
+- 408.3
+284:
+- 265.40000000000003
+- 413.65000000000003
+285:
+- 264.55
+- 423.65000000000003
+286:
+- 263.7
+- 433.65000000000003
+287:
+- 276.65000000000003
+- 404.05
+288:
+- 286.65000000000003
+- 405.0
+289:
+- 229.65
+- 410.85
+290:
+- 228.8
+- 420.85
+291:
+- 227.95000000000002
+- 430.85
+292:
+- 241.45000000000002
+- 401.05
+293:
+- 251.45
+- 401.85
+294:
+- 401.05
+- 380.05
+295:
+- 400.25
+- 390.05
+296:
+- 399.40000000000003
+- 400.05
+297:
+- 368.05
+- 377.05
+298:
+- 367.20000000000005
+- 387.05
+299:
+- 366.40000000000003
+- 397.05
+300:
+- 379.45000000000005
+- 367.45000000000005
+301:
+- 389.45000000000005
+- 368.35
+302:
+- 336.35
+- 374.15000000000003
+303:
+- 335.3
+- 384.15000000000003
+304:
+- 334.3
+- 394.15000000000003
+305:
+- 347.8
+- 364.6
+306:
+- 357.8
+- 365.55
+307:
+- 303.15000000000003
+- 371.05
+308:
+- 302.15000000000003
+- 381.05
+309:
+- 301.20000000000005
+- 391.05
+310:
+- 314.65000000000003
+- 361.55
+311:
+- 324.65000000000003
+- 362.5
+312:
+- 269.25
+- 367.70000000000005
+313:
+- 268.40000000000003
+- 377.70000000000005
+314:
+- 267.55
+- 387.70000000000005
+315:
+- 281.6
+- 358.45000000000005
+316:
+- 291.6
+- 359.40000000000003
+317:
+- 434.3
+- 345.05
+318:
+- 433.35
+- 355.05
+319:
+- 432.40000000000003
+- 365.05
+320:
+- 428.05
+- 371.70000000000005
+321:
+- 418.05
+- 370.85
+322:
+- 434.40000000000003
+- 376.8
+323:
+- 433.65000000000003
+- 386.8
+324:
+- 432.85
+- 396.8
+325:
+- 432.05
+- 406.8
+326:
+- 405.15000000000003
+- 341.85
+327:
+- 403.5
+- 351.70000000000005
+328:
+- 402.65000000000003
+- 361.70000000000005
+329:
+- 371.95000000000005
+- 339.15000000000003
+330:
+- 370.35
+- 349.05
+331:
+- 340.5
+- 336.75
+332:
+- 339.0
+- 346.70000000000005
+333:
+- 305.85
+- 341.8
+334:
+- 304.95000000000005
+- 351.8
+335:
+- 272.35
+- 338.55
+336:
+- 271.55
+- 348.55
+337:
+- 283.65000000000003
+- 328.90000000000003
+338:
+- 293.65000000000003
+- 329.90000000000003
+339:
+- 253.10000000000002
+- 326.05
+340:
+- 263.1
+- 326.95000000000005
+341:
+- 275.55
+- 299.3
+342:
+- 274.8
+- 309.3
+343:
+- 274.05
+- 319.3
+344:
+- 286.7
+- 289.3
+345:
+- 296.7
+- 289.85
+346:
+- 306.70000000000005
+- 290.45
+347:
+- 239.70000000000002
+- 296.65000000000003
+348:
+- 238.60000000000002
+- 306.65000000000003
+349:
+- 237.5
+- 316.65000000000003
+350:
+- 235.60000000000002
+- 336.65000000000003
+351:
+- 234.8
+- 346.65000000000003
+352:
+- 233.95000000000002
+- 356.65000000000003
+353:
+- 233.20000000000002
+- 366.65000000000003
+354:
+- 232.4
+- 376.65000000000003
+355:
+- 231.60000000000002
+- 386.65000000000003
+356:
+- 251.7
+- 286.90000000000003
+357:
+- 261.7
+- 287.65000000000003
+358:
+- 278.05
+- 259.95
+359:
+- 277.45
+- 269.95
+360:
+- 276.8
+- 279.95
+361:
+- 289.15000000000003
+- 249.90000000000003
+362:
+- 299.15000000000003
+- 250.5
+363:
+- 309.15000000000003
+- 251.05
+364:
+- 245.4
+- 257.55
+365:
+- 242.95000000000002
+- 267.55
+366:
+- 241.45000000000002
+- 277.55
+367:
+- 259.3
+- 248.2
+368:
+- 269.3
+- 248.8
+369:
+- 357.90000000000003
+- 213.4
+370:
+- 367.90000000000003
+- 213.85000000000002
+371:
+- 324.35
+- 211.9
+372:
+- 334.35
+- 212.35000000000002
+373:
+- 280.7
+- 220.55
+374:
+- 280.05
+- 230.55
+375:
+- 279.40000000000003
+- 240.55
+376:
+- 291.05
+- 210.35000000000002
+377:
+- 301.05
+- 210.8
+378:
+- 255.8
+- 219.20000000000002
+379:
+- 253.2
+- 229.20000000000002
+380:
+- 250.45
+- 239.20000000000002
+381:
+- 268.40000000000003
+- 209.25
+382:
+- 414.6
+- 197.9
+383:
+- 414.05
+- 207.9
+384:
+- 411.05
+- 215.70000000000002
+385:
+- 401.05
+- 215.3
+386:
+- 391.05
+- 214.85000000000002
+387:
+- 420.95000000000005
+- 216.10000000000002
+388:
+- 430.95000000000005
+- 216.5
+389:
+- 440.95000000000005
+- 216.95000000000002
+390:
+- 447.35
+- 212.5
+391:
+- 447.85
+- 202.5
+392:
+- 424.8
+- 188.35000000000002
+393:
+- 434.8
+- 190.4
+394:
+- 348.70000000000005
+- 184.95000000000002
+395:
+- 348.25
+- 194.95000000000002
+396:
+- 347.75
+- 204.95000000000002
+397:
+- 359.5
+- 175.3
+398:
+- 369.5
+- 177.0
+399:
+- 379.5
+- 179.05
+400:
+- 381.70000000000005
+- 187.9
+401:
+- 381.20000000000005
+- 197.9
+402:
+- 393.6
+- 181.95000000000002
+403:
+- 403.6
+- 184.0
+404:
+- 315.15000000000003
+- 183.35000000000002
+405:
+- 314.70000000000005
+- 193.35000000000002
+406:
+- 314.20000000000005
+- 203.35000000000002
+407:
+- 325.90000000000003
+- 172.85000000000002
+408:
+- 282.6
+- 181.25
+409:
+- 282.05
+- 191.25
+410:
+- 281.5
+- 201.25
+411:
+- 293.5
+- 171.15
+412:
+- 303.5
+- 171.65
+413:
+- 259.3
+- 179.65
+414:
+- 258.6
+- 189.65
+415:
+- 257.95
+- 199.65
+416:
+- 271.15000000000003
+- 170.0
+417:
+- 293.1
+- 160.85000000000002
+418:
+- 303.1
+- 163.0
+419:
+- 313.1
+- 165.10000000000002
+420:
+- 333.1
+- 169.3
+421:
+- 265.45
+- 155.05
+422:
+- 276.05
+- 157.20000000000002
+423:
+- 315.40435791015625
+- 477.9844970703125
+424:
+- 312.3125
+- 485.1031799316406
diff --git a/output_yaml/way_pts_low_level.yaml b/output_yaml/way_pts_low_level.yaml
new file mode 100644
index 0000000..7a6ea83
--- /dev/null
+++ b/output_yaml/way_pts_low_level.yaml
@@ -0,0 +1,288 @@
+0:
+- 394.8
+- 456.1
+1:
+- 262.8
+- 444.3
+2:
+- 368.90000000000003
+- 366.5
+3:
+- 407.40000000000003
+- 628.1500000000001
+4:
+- 340.05
+- 622.0
+5:
+- 241.5
+- 586.1
+6:
+- 218.0
+- 576.9
+7:
+- 345.3
+- 568.1
+8:
+- 363.20000000000005
+- 530.65
+9:
+- 350.55
+- 525.8000000000001
+10:
+- 347.75
+- 500.90000000000003
+11:
+- 329.2942810058594
+- 450.0257263183594
+12:
+- 431.1
+- 417.6
+13:
+- 398.20000000000005
+- 415.0
+14:
+- 365.1
+- 412.35
+15:
+- 401.95000000000005
+- 369.5
+16:
+- 304.41143798828125
+- 359.6991271972656
+17:
+- 306.1
+- 331.3
+18:
+- 273.15000000000003
+- 328.0
+19:
+- 278.75
+- 249.40000000000003
+20:
+- 281.15000000000003
+- 210.05
+21:
+- 235.15
+- 578.5
+23:
+- 441.0
+- 538.15
+24:
+- 367.0
+- 531.5500000000001
+25:
+- 243.55
+- 531.15
+26:
+- 325.7059631347656
+- 492.0518798828125
+27:
+- 347.40000000000003
+- 212.5
+28:
+- 296.23443603515625
+- 446.56121826171875
+29:
+- 276.2
+- 288.8
+30:
+- 332.75
+- 409.55
+31:
+- 299.90000000000003
+- 406.20000000000005
+32:
+- 266.2
+- 403.15000000000003
+33:
+- 416.0
+- 593.35
+34:
+- 359.0
+- 570.1
+37:
+- 235.8
+- 532.1
+38:
+- 356.15000000000003
+- 498.95000000000005
+39:
+- 291.85
+- 489.0
+40:
+- 361.371337890625
+- 452.96978759765625
+41:
+- 283.0
+- 170.75
+42:
+- 240.65
+- 593.3000000000001
+43:
+- 361.20000000000005
+- 533.0500000000001
+44:
+- 285.8
+- 507.80000000000007
+45:
+- 444.25
+- 576.9
+46:
+- 405.95000000000005
+- 573.4
+47:
+- 448.05
+- 549.45
+48:
+- 276.85
+- 501.45000000000005
+49:
+- 313.85
+- 211.0
+51:
+- 341.20000000000005
+- 173.5
+52:
+- 337.40000000000003
+- 363.65000000000003
+54:
+- 237.9
+- 579.0500000000001
+55:
+- 436.95000000000005
+- 577.3000000000001
+56:
+- 423.45000000000005
+- 576.1
+58:
+- 432.75
+- 548.65
+59:
+- 287.05
+- 502.45000000000005
+60:
+- 246.8
+- 498.55
+61:
+- 343.75
+- 173.10000000000002
+62:
+- 444.15000000000003
+- 570.75
+63:
+- 334.90000000000003
+- 527.1
+64:
+- 253.3
+- 602.25
+65:
+- 232.55
+- 490.6
+66:
+- 427.90000000000003
+- 458.8
+67:
+- 315.75
+- 172.85000000000002
+69:
+- 260.65000000000003
+- 169.20000000000002
+70:
+- 415.25
+- 187.35000000000002
+71:
+- 283.45
+- 159.8
+72:
+- 358.45000000000005
+- 495.6
+74:
+- 350.15000000000003
+- 533.2
+75:
+- 434.6
+- 519.35
+76:
+- 345.05
+- 498.20000000000005
+77:
+- 227.5
+- 441.15000000000003
+78:
+- 242.60000000000002
+- 325.3
+79:
+- 257.90000000000003
+- 208.75
+80:
+- 416.95000000000005
+- 536.1
+81:
+- 342.35
+- 567.25
+82:
+- 431.2927551269531
+- 536.7435302734375
+83:
+- 350.25
+- 530.6
+84:
+- 347.90000000000003
+- 518.8000000000001
+85:
+- 391.45000000000005
+- 497.90000000000003
+86:
+- 258.95
+- 486.1
+87:
+- 230.9
+- 400.35
+88:
+- 271.1
+- 357.25
+89:
+- 248.75
+- 247.10000000000002
+90:
+- 380.5
+- 214.0
+91:
+- 349.35
+- 174.45000000000002
+92:
+- 330.90000000000003
+- 567.0500000000001
+93:
+- 316.95000000000005
+- 618.75
+94:
+- 408.45000000000005
+- 546.5
+96:
+- 263.7
+- 533.15
+97:
+- 341.35
+- 527.7
+98:
+- 448.25
+- 194.60000000000002
+99:
+- 241.25
+- 286.2
+100:
+- 284.2564697265625
+- 532.891845703125
+101:
+- 265.7926330566406
+- 500.62896728515625
+102:
+- 425.0286865234375
+- 500.0166931152344
+103:
+- 432.0601806640625
+- 372.5963134765625
+104:
+- 401.0057373046875
+- 388.52801513671875
diff --git a/readme/graph.png b/readme/graph.png
new file mode 100644
index 0000000..b1a0e08
Binary files /dev/null and b/readme/graph.png differ
diff --git a/readme/img.png b/readme/img.png
new file mode 100644
index 0000000..249716d
Binary files /dev/null and b/readme/img.png differ
diff --git a/readme/img2.png b/readme/img2.png
new file mode 100644
index 0000000..2142f71
Binary files /dev/null and b/readme/img2.png differ
diff --git a/readme/img_2.png b/readme/img_2.png
new file mode 100644
index 0000000..bfa74ef
Binary files /dev/null and b/readme/img_2.png differ
diff --git a/readme/in_bw_waypts.png b/readme/in_bw_waypts.png
new file mode 100644
index 0000000..baaef3d
Binary files /dev/null and b/readme/in_bw_waypts.png differ
diff --git a/readme/readme.md b/readme/readme.md
new file mode 100644
index 0000000..6a8d718
--- /dev/null
+++ b/readme/readme.md
@@ -0,0 +1,85 @@
+# MAKE CONNECTIVITY GRAPH FROM 2D MAP
+
+This package detects waypoints from a 2D map and then makes a connectivity graph from it. first open the waypoint folder and then install the required python packages:
+
+1) OpenCV: 3.4.4
+2) Numpy: 1.16.6
+3) Skimage: 0.14.5
+
+Then, in the imput image make sure that the roads are in white color and the obstacles are in black color as shown in the example image
+
+![Screenshot](img.png)
+
+## STEPS TO USE:
+
+1) In src/skeleton.py specify the path of the map image and then run it.This will convert all the roads to a single pixel wide line.
+2) Edit the input image path in src/waypoint.py somewhere around line 977 to include the skeleton image.
+3) To run the code:
+   1) start roscore
+   
+        ``` roscore ```
+   2) run map_server to publish the map, navigate to waypoint/map_server and run:
+   
+        ``` rosrun map_server map_server map.yaml ```
+    
+   3) publish transform to the map:
+   
+        ``` rosrun tf static_transform_publisher 0 0 0 0 0 0 base_link map 50 ```
+
+   4) run rviz with the waypt_rviz_config.rviz config file
+   5) run waypoint.py
+   
+        ``` python waypoint.py ```
+
+4)  Then after a few seconds, waypoints will be visible in rviz as:
+    ![Screenshot](img_2.png)
+
+5) To add a waypoint publish a point whereever you want to add it, to remove the waypoint rightclick on it and click on delete. You can also move the waypoints by dragging the arrows.
+6) Adjust the waypoints properly before making the connected graph.
+7) Right click on any of the waypoint and click on "make connected graph" button, this will connect the waypoints to each other and lines will be visible one by one. 
+   ![Screenshot](graph.png)
+8) To delete an edge between two waypoints, rightclick on the first one and select delete edge, then rightclick on the second one and select delete edge.
+9)  To make an edge between two waypoints, rightclick on the first and select make edge and rightclick on the second and select make edge, this will create an edge between two waypoints.
+10) For the edges which are manually added, the program stores the length of the edge as euclidian distance between the two waypoints. For the edges which were automatically generated, it stores the length of edge as the length of the path that connects the two waypoints.
+11) There is no undo button so make changes carefully.
+12) After adjusting the edges, rightclick on any waypoint and select save to yaml.
+13) This will save three files 
+    
+    1)connected_graph_high_level.yaml: this is our connectivity graph
+
+    2)edges_high_level: this is to be used when we want to edit our connected_graph_low_level.yaml using this tool.
+
+    3)way_pts_high_level.yaml: this is to be used when we want to edit our connected_graph_low_level.yaml using this tool.
+
+14) When we press the save to yaml for the first time, it will save the above three files to output_yaml folder and then detect the inbetween waypoints in approximately 10 metres apart and then make their connectivity graph and it will be visible on rviz. This will take about a minute.
+    
+    ![Screenshot](in_bw_waypts.png)
+   
+15) Now edit this and then when you press save to yaml, it will save three new files:
+    1) connected_graph_low_level.yaml: this is our connected graph with additional inbetween waypoints.
+    2) edges_low_level.yaml: this file is used to edit the connected_graph_low_level.yaml using this tool
+    3) way_pts_low_level.yaml: this file is used to edit the connected_graph_low_level.yaml using this tool
+
+16) Now you can quit the program.
+    
+17) To edit previous work, run everything on step 3, and rightclick on any waypoint and select load previous.
+18) In terminal, it will ask for the path to the three yaml files that were saved.
+19) Specify the path and then press enter.
+20) Depending on the yaml files you choosed (low level or high level), the waypoints and edges will be visible in rviz and you can edit them and press save to yaml. This will save the files as: 
+    
+    1)connected_graph_edited.yaml
+
+    2)edges_edited.yaml
+
+    3)way_pts_edited.yaml
+
+21) While loading the files make sure you enter the path of way_pts yaml and edge yaml file corresponding to your connected_graph yaml file
+22) The format of the saved connected graph yaml will be different from the one required, to change it go to src/convert_format.py change the input yaml path and run the code using:
+    ```
+    python3 convert_format.py
+    ```
+23) This will save a converted_graph.yaml in the src folder. 
+### CONTACT: ###
+Nisarg Panchal, email: nisargnileshpanchal@gmail.com|
+
+
diff --git a/src/broken_roads.png b/src/broken_roads.png
new file mode 100644
index 0000000..bf1ba6e
Binary files /dev/null and b/src/broken_roads.png differ
diff --git a/src/convert_format.py b/src/convert_format.py
new file mode 100644
index 0000000..f1e6abe
--- /dev/null
+++ b/src/convert_format.py
@@ -0,0 +1,17 @@
+import yaml
+
+# Load the original YAML data
+with open("connected_graph_high_level.yaml", "r") as f:
+    data = yaml.safe_load(f)
+
+# Convert the data to the desired format
+waypoints_cpp = []
+for node_num, node_data in data.items():
+    node_pos = node_data["node_pos"]
+    edges = [{"outward_edge_to": str(edge_num), "path_length": str(distance)} for edge_num, distance in node_data["outward_edges"].items()]
+    node_name = int(node_num)
+    waypoints_cpp.append({"node_name": node_name,"node_pos": node_pos, "out_edges": edges})
+
+# Save the converted YAML data
+with open("converted_graph.yaml", "w") as f:
+    yaml.dump({"waypoints_cpp": waypoints_cpp}, f, sort_keys=True)
diff --git a/src/output_graph.png b/src/output_graph.png
new file mode 100644
index 0000000..0de17fa
Binary files /dev/null and b/src/output_graph.png differ
diff --git a/src/skeletonise.py b/src/skeletonise.py
new file mode 100644
index 0000000..eedbbde
--- /dev/null
+++ b/src/skeletonise.py
@@ -0,0 +1,40 @@
+import cv2
+import numpy as np
+from skimage import morphology
+bw_map = cv2.imread("map_pringle_dilate.png")
+# kernel = np.ones((20, 20), np.uint8)
+
+gray = cv2.cvtColor(bw_map, cv2.COLOR_BGR2GRAY)
+im = cv2.threshold(bw_map, 100, 255, cv2.THRESH_BINARY)[1]#if roads white then use binary_inv, if roads black use binary
+im=255-im
+
+# im = cv2.erode(im, kernel, iterations=1)
+# im = cv2.dilate(im, kernel, iterations=1)
+
+# showim(im)
+# kernel = np.asanyarray([[1,1,1], [1,1,1], [1,1,1]], np.float32)/9.0
+# im = cv2.filter2D(im, -1, kernel)
+# showim(im)
+# im = cv2.ximgproc.thinning(gray, thinningType=cv2.ximgproc.THINNING_ZHANGSUEN)
+
+im = morphology.skeletonize(im > 0)
+im = im.astype(np.uint8)
+# im=np.vstack([im,im,im])
+im = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY )
+
+# gray = cv2.bitwise_and(bw_map, bw_map, mask = im)
+
+# im = cv2.threshold(im, 100, 255, cv2.THRESH_BINARY)[1]
+# detect corners with the goodFeaturesToTrack function.
+corners = cv2.goodFeaturesToTrack(im, 1000, 0.375, 50)
+# showim(im)
+corners = np.int0(corners)
+  
+# we iterate through each corner, 
+# making a circle at each point that we think is a corner.
+for i in corners:
+    x, y = i.ravel()
+    cv2.circle(bw_map, (x, y), 30, (0,0,255), -1)
+print(len(corners))
+
+cv2.imwrite("123.png",im)
\ No newline at end of file
diff --git a/src/waypoint.py b/src/waypoint.py
new file mode 100644
index 0000000..5da55dc
--- /dev/null
+++ b/src/waypoint.py
@@ -0,0 +1,1005 @@
+from geometry_msgs.msg import PointStamped
+import cv2
+import numpy as np
+import yaml
+import time
+import rospy
+import copy
+from interactive_markers.interactive_marker_server import *
+from interactive_markers.menu_handler import *
+from visualization_msgs.msg import *
+from geometry_msgs.msg import Point
+from tf.broadcaster import TransformBroadcaster
+from visualization_msgs.msg import Marker
+import os
+from geometry_msgs.msg import Point
+from random import random
+from math import sin
+# import sknw
+global press_count
+press_count = 1
+server = None
+menu_handler = MenuHandler()
+br = None
+counter = 0
+global count
+count=0
+global graph
+graph={}
+global line_pub
+line_pub = rospy.Publisher('edges', Marker, queue_size=10)
+global lines
+lines={}
+# lines=[]
+global make_edge_bw
+make_edge_bw=[]
+global delete_edge_bw
+delete_edge_bw=[]
+
+# global del_count
+# class dictionary(dict):
+ 
+#   # __init__ function
+#   def __init__(self):
+#     self = dict()
+ 
+#   # Function to add key:value
+#   def add(self, key, value):
+#     self[key] = value
+
+
+def frameCallback( msg ):
+    global counter, br
+    time = rospy.Time.now()
+    br.sendTransform( (0, 0, sin(counter/140.0)*2.0), (0, 0, 0, 1.0), time, "base_link", "moving_frame" )
+    counter += 1
+
+#function that reads the feedback on the interactive markers
+def processFeedback( feedback):
+    s = "Feedback from marker '" + feedback.marker_name
+    s += "' / control '" + feedback.control_name + "'"
+
+    mp = ""
+    if feedback.mouse_point_valid:
+        mp = " at " + str(feedback.mouse_point.x)
+        mp += ", " + str(feedback.mouse_point.y)
+        mp += ", " + str(feedback.mouse_point.z)
+        mp += " in frame " + feedback.header.frame_id
+        way_pts[int(feedback.marker_name)]=[feedback.mouse_point.x,feedback.mouse_point.y]#IF WE DRAG AND CHANGE POSITION OF WAYPOINT THEN UPDATE ITS IN THE DICTIONARY
+        print("UPDATED DICTIONARY FOR WAYPOINT :", feedback.marker_name,"  [x,y] = ",way_pts[int(feedback.marker_name)])#PRINT THE UPDATED POSITION
+
+    if feedback.event_type == InteractiveMarkerFeedback.BUTTON_CLICK:
+        rospy.loginfo( s + ": button click" + mp + "." )
+    
+    elif feedback.event_type == InteractiveMarkerFeedback.MENU_SELECT:
+        #IF FIRST MENU ITEM (DELETE WAYPOINT) SELECTED
+        if feedback.menu_entry_id == 1:
+            server.erase(feedback.marker_name) #REMOVE MARKER FROM RVIZ
+            print("DELETED WAYPOINT :",feedback.marker_name) #PRINT THE NAME OF MARKER THAT WAS DELETED
+            del way_pts[int(feedback.marker_name)] #REMOVE IT FROM THE DICTIONARY
+            print("UPDATED DICTIONARY") 
+            server.applyChanges() 
+        
+        #IF SECOND MENU ITEM (MAKE CONNECTED GRAPH) IS SELECTED
+        if feedback.menu_entry_id  == 2:
+            global im
+            global line_pub
+            yaml_string=yaml.dump(way_pts)
+            print(yaml_string)
+
+            #DRAW BLACK CIRCLES ON THE WAYPOINTS TO CREATE SEPARATE SEGMENTS FOR EACH ROAD
+            for i in way_pts:
+                x=way_pts[i][0]
+                y=way_pts[i][1]
+                cv2.circle(im,(int(((x+10)/0.05)),int(((y+10)/0.05))),10,255,-1)
+
+            im=255-im
+            cv2.imwrite("broken_roads.png",im)
+            im=cv2.imread("broken_roads.png")
+            im_orig=im
+            im = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY)
+            im = cv2.threshold(im, 100, 255, cv2.THRESH_BINARY)[1]
+            #FIND CONTOURS
+            _,contours, _ = cv2.findContours(im, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+            global graph
+            # global lines
+            print("Number of edges found = ",len(contours))
+            global indx
+            indx=0
+            #LOOP THROUGH EACH CONTOUR
+            for contour in  contours:
+                #FIND THE EXTREME POINTS OF EACH CONTOUR
+                extLeft = tuple(contour[contour[:, :, 0].argmin()][0])
+                extRight = tuple(contour[contour[:, :, 0].argmax()][0])
+                extTop = tuple(contour[contour[:, :, 1].argmin()][0])
+                extBot = tuple(contour[contour[:, :, 1].argmax()][0])
+                dist_e_w = ((extLeft[0]-extRight[1])**2 + (extLeft[0]-extRight[1])**2 )**0.5
+                dist_n_s = ((extTop[0]-extBot[1])**2 + (extTop[0]-extBot[1])**2 )**0.5
+                #IF DISTANCE FROM EAST TO WEST EXTREME POINT IS MORE THAN NORTH TO SOUTH THEN OUT EXTREME POINTS ARE EAST AND WEST
+                if dist_e_w > dist_n_s:
+                    p1=[extLeft[0],extLeft[1]]
+                    p2=[extRight[0],extRight[1]]
+                #ELSE OUR EXTREME POINTS ARE NORTH AND SOUTH
+                else:
+                    p1=[extTop[0],extTop[1]]
+                    p2=[extBot[0],extBot[1]]
+
+                
+                cv2.circle(im_orig, (p1[0], p1[1]), 5, (0,0,255), -1)
+                cv2.circle(im_orig, (p2[0], p2[1]), 5, (0,0,255), -1)
+
+                # way_pts_values=np.array(list(way_pts.values()))
+                p1_arr = np.array(p1)
+                p2_arr = np.array(p2)
+                
+                #FROM EACH CONTOUR EXTREME POINT, FIND THE NEAREST WAYPOINT AND MAKE AN EDGE BETWEEN BOTH THE WAYPOINTS
+                p1_key = None
+                p1_dist = float('inf')
+                p2_key = None
+                p2_dist = float('inf')
+                for key, value in way_pts.items():
+                    value_arr = np.array(value)
+                    value_arr=(value_arr+10)/0.05
+                    dist_p1 = np.linalg.norm(value_arr - p1_arr)
+                    if dist_p1 < p1_dist:
+                        p1_dist = dist_p1
+                        p1_key = key
+                    dist_p2 = np.linalg.norm(value_arr - p2_arr)
+                    if dist_p2 < p2_dist:
+                        p2_dist = dist_p2
+                        p2_key = key
+                
+                p1_idx=p1_key
+                p2_idx=p2_key
+
+                # lines[indx]=[[way_pts[p1_idx][0],way_pts[p1_idx][1]],[way_pts[p2_idx][0],way_pts[p2_idx][1]]]
+                # lines.append([[way_pts[p1_idx][0],way_pts[p1_idx][1]],[way_pts[p2_idx][0],way_pts[p2_idx][1]]])
+                # if [[way_pts[p1_idx][0],way_pts[p1_idx][1]]!=[way_pts[p2_idx][0],way_pts[p2_idx][1]]]:
+
+                #LINES DICTIONARY: (WAYPOINT1_ID, WAYPOINT2_ID, EDGE ID) = [[x1,y1],[x2,y2]]
+                lines[(p1_idx,p2_idx,indx)]=[[way_pts[p1_idx][0],way_pts[p1_idx][1]],[way_pts[p2_idx][0],way_pts[p2_idx][1]]]
+
+                #DRAW LINES
+                line = Marker()
+                line.header.frame_id = "map"
+                line.header.stamp = rospy.Time.now()
+                line.ns = "edges"
+                line.id = indx
+                indx+=1
+                line.type = Marker.LINE_STRIP
+                line.action = Marker.ADD
+                line.scale.x = 0.3
+                line.color.r = 0.0
+                line.color.g = 1.0
+                line.color.b = 0.0
+                line.color.a = 1.0
+
+                point1 = Point()
+                point1.x = way_pts[p1_idx][0]
+                point1.y = way_pts[p1_idx][1]
+                point1.z = 0.0
+
+                point2 = Point()
+                point2.x = way_pts[p2_idx][0]
+                point2.y = way_pts[p2_idx][1]
+                point2.z = 0.0
+
+                line.points.append(point1)
+                line.points.append(point2)
+                line_pub.publish(line)
+                time.sleep(0.1)
+                cv2.line(im_orig, (int((way_pts[p1_idx][0]+10)/0.05), int((way_pts[p1_idx][1]+10)/0.05)), (int((way_pts[p2_idx][0]+10)/0.05), int((way_pts[p2_idx][1]+10)/0.05)), (255, 0, 0), 1)
+                
+                #CALCULATE THE PERIMETER
+                perimeter = cv2.arcLength(contour,True)
+                #DIVIDE PERIMETER BY 2 TO GET LENGTH AND SUBTRACT 10 BECAUSE WHEN WE DRAW BLACK CIRCLES OF RADIUS 10, 5 PIXELS WILL BE REMOVED FROM EACH SIDE, AND MULTIPLY WITH 0.05 TO CONVERT IT TO METRES
+                perimeter = ((perimeter/2)+10)*0.05
+
+                ########################
+                ########################
+                #MAKE THE GRAPH
+                if p1_idx not in graph:
+                    graph[p1_idx] = {
+                        'node_pos': way_pts[p1_idx],
+                        'outward_edges': {
+                            p2_idx: perimeter
+                        }
+                    }
+                else:
+                        graph[p1_idx]['outward_edges'][p2_idx] = perimeter
+                    
+                if p2_idx not in graph:
+                        graph[p2_idx] = {
+                            'node_pos': way_pts[p2_idx],
+                            'outward_edges': {
+                                p1_idx: perimeter
+                            }
+                        }
+                else:
+                    graph[p2_idx]['outward_edges'][p1_idx] = perimeter
+                    
+
+            # for i in graph:
+            #     cv2.putText(im_orig, str(i), (graph[i]["node_pos"][0] + 15, graph[i]["node_pos"][1] + 15), cv2.FONT_HERSHEY_SIMPLEX, 1, (0, 0, 255), 1)
+
+            # for i in corners:
+            #     x,y = i.ravel()
+            #     cv2.circle(im_orig,(x,y),15,(0,255,0),-1)
+            
+            cv2.imwrite("output_graph.png",im_orig)
+
+            #IF A WAYPOINT HAS EDGE WITH ITSELF THEN REMOVE THE EDGE
+            for node, node_data in graph.items():
+                if node in node_data['outward_edges']:
+                    del node_data['outward_edges'][node]
+                    print("removed")
+            # for i in graph:
+                # print(i,graph[i])
+            for i in range(0,5):
+                print("")
+            print("DONE MAKING THE GRAPH")
+            for i in range(0,5):
+                print("")
+                
+        # IF THIRD MENU ITEM IS SELECTED (MAKE EDGE) THEN:
+        if feedback.menu_entry_id==3:
+            global count
+            global make_edge_bw
+            #APPEND THE ID OF THE MARKER THAT WE CLICKED TO make_edge_bw LIST
+            make_edge_bw.append(int(feedback.marker_name))
+            #IF MORE THAN TWO POINTS ARE SELECTED
+            if len(make_edge_bw) > 2:
+                #KEEP FIRST TWO
+                make_edge_bw=[make_edge_bw[0],make_edge_bw[1]]
+
+            print(make_edge_bw)
+            print("")
+            print("")
+            print(make_edge_bw)
+            print("")
+            print("")
+            #WHEN TWO POINTS ARE SELECTED
+            if len(make_edge_bw)==2:
+                try:
+                    # global lines
+                    count+1
+                    print("BOTH POINTS SELECTED")
+                    #CALCULATE EUCLIDIAN DISTANCE BETWEEN THE WAYPOINTS
+                    eu_dist = ((way_pts[make_edge_bw[0]][0] - way_pts[make_edge_bw[1]][0])**2 + (way_pts[make_edge_bw[0]][1] - way_pts[make_edge_bw[1]][1])**2)**(0.5)
+
+                    #ADD THE EDGE TO GRAPH
+                    graph[make_edge_bw[0]]["outward_edges"][make_edge_bw[1]]=eu_dist
+                    graph[make_edge_bw[1]]["outward_edges"][make_edge_bw[0]]=eu_dist
+                    print(graph[make_edge_bw[0]])
+                    print(graph[make_edge_bw[1]])
+
+                    #DRAW THE EDGE
+                    line = Marker()
+                    line.header.frame_id = "map"
+                    line.header.stamp = rospy.Time.now()
+                    line.ns = "edges"
+                    
+                    ids = []
+                    # for i in lines.keys:
+                        # print(i)
+                    for i in lines:
+                        # print(i)
+                        ids.append(int(i[2]))
+                    id = max(ids)+1
+                    line.id = id
+                    line.type = Marker.LINE_STRIP
+                    line.action = Marker.ADD
+                    line.scale.x = 0.3
+                    line.color.r = 0.0
+                    line.color.g = 1.0
+                    line.color.b = 0.0
+                    line.color.a = 1.0
+
+                    point1 = Point()
+                    point1.x = way_pts[make_edge_bw[0]][0]
+                    point1.y = way_pts[make_edge_bw[0]][1]
+                    point1.z = 0.0
+
+                    point2 = Point()
+                    point2.x = way_pts[make_edge_bw[1]][0]
+                    point2.y = way_pts[make_edge_bw[1]][1]
+                    point2.z = 0.0
+
+                    line.points.append(point1)
+                    line.points.append(point2)
+                    line_pub.publish(line)
+                    # lines[len(lines)+count]=[[ way_pts[make_edge_bw[0]][0], way_pts[make_edge_bw[0]][1]],[ way_pts[make_edge_bw[1]][0], way_pts[make_edge_bw[1]][1]]]
+                    # lines.append([[way_pts[make_edge_bw[0]][0],way_pts[make_edge_bw[0]][1]],[way_pts[make_edge_bw[1]][0], way_pts[make_edge_bw[1]][1],2]])
+                    lines[(make_edge_bw[0],make_edge_bw[1],id)]=[[way_pts[make_edge_bw[0]][0],way_pts[make_edge_bw[0]][1]],[way_pts[make_edge_bw[1]][0], way_pts[make_edge_bw[1]][1]]]
+                    #EMPTY THE LIST SO WE CAN USE IT AGAIN
+                    make_edge_bw=[]
+                except Exception as e:
+                    print(e)
+                    make_edge_bw=[]
+
+        #IF 4TH MENU ITEM (DELETE EDGE) IS SELECTED
+        if feedback.menu_entry_id==4:
+            print("YOU PRESSED DELETE")
+            global delete_edge_bw
+            #APPEND THE ID OF THE MARKER WE CLICKED TO THE LIST
+            delete_edge_bw.append(int(feedback.marker_name))
+            print(" ")
+            print(delete_edge_bw)
+            print("")
+            #IF TWO ARE SELECTED
+            if len(delete_edge_bw)==2:
+                print("BEFORE DELETE :")
+                print(graph[delete_edge_bw[0]])
+                print(graph[delete_edge_bw[1]])
+                print("AFTER DELETE")
+                #DELETE FROM GRAPH
+                del graph[delete_edge_bw[0]]["outward_edges"][delete_edge_bw[1]]
+                del graph[delete_edge_bw[1]]["outward_edges"][delete_edge_bw[0]]
+                print(graph[delete_edge_bw[0]])
+                print(graph[delete_edge_bw[1]])
+
+                print("NO OF LINES: ",len(lines))
+
+                #SEARCH FOR THE ID OF THE LINE MARKER BETWEEN THE SELECTED WAYPOINTS AND REMOVE THAT MARKER
+                for i in lines.keys():
+                    if [i[0],i[1]]==delete_edge_bw:
+                        del lines[i]
+                        line = Marker()
+                        line.header.frame_id = "map"
+                        line.ns = "edges"
+                        line.id = i[2]
+                        line.action = line.DELETE
+                        line_pub.publish(line)
+                        print("REMOVEDDDDDDDDDDDDDDDDDDDDDDDDDDDDd")
+                for i in lines.keys():
+                    if [i[1],i[0]]==delete_edge_bw:
+                        del lines[i]
+                        line = Marker()
+                        line.header.frame_id = "map"
+                        line.ns = "edges"
+                        line.id = i[2]
+                        line.action = line.DELETE
+                        line_pub.publish(line)
+                        print("REMOVEDDDDDDDDDDDDDDDDDDDDDDDDDDDDd")
+                
+                #EMPTY THE LIST SO THAT WE CAN USE IT AGAIN
+                delete_edge_bw=[]
+
+
+#code this:
+# save_to yaml do baar press hoga first time bade pts save aur uske baad nae banao waypoints, wo edit krke dusri bar save karo to naya save hoga 
+#if load previous kia hai to jo files select ki hai wo load hogi, use edit karo aur fir save dabane se save ho jaegi. agar files load ki hai to kitni bhi baar save dabao bas save hi hoga nae points nai banenge.
+
+        #WHEN WE PRESS SAVE TO YAML THE FIRST TIME, IT WILL SAVE THE YAMLS AND THEN CALCULATE INBETWEEN WAYPOINTS, PUBLISH THEM AND CREATE A CONNECTED GRAPH WITH IN BETWEEN WAYPOINTS AND THEN PUBLISH THE EDGES
+        #IF WE HAVE SELECTED THE LOAD PREVIOUS OPTION THEN NO MATTER HOW MANY TIMES WE PRESS SAVE TO YAML IT WILL SAVE IT AND THEN DO NOTHING (LIKE WILL NOT FIND INBETWEEN POINTS)
+        if feedback.menu_entry_id==5:
+            #WE ARE NOT IN LOAD PREVIOUS MODE
+            if load == 0:
+                #KEEP A NOT OF HOW MANY TIMES WE HAVE PRESSED SAVE
+                global press_count
+                print(press_count)
+                # graph.clear()
+
+                #IF PRESSED FIRST TIME:
+                if press_count ==1:
+                    # global lines
+                    print(" ")
+                    print(" ")
+                    print(" ")
+                    print("YOU PRESSED SAVE TO YAMl")
+                    print(" ")
+                    print(" ")
+                    print(" ")
+
+                    #SAVE THE YAMLS
+                    file=open(home+"/Downloads/waypoint/output_yaml/connected_graph_low_level.yaml","w")
+                    yaml.dump(graph,file)
+                    file.close()
+
+                    file=open(home+"//Downloads/waypoint/output_yaml/way_pts_low_level.yaml","w")
+                    yaml.dump(way_pts,file)
+                    file.close()
+
+                    file=open(home+"/Downloads/waypoint/output_yaml/edges_low_level.yaml","w")
+                    yaml.dump(lines,file)
+                    print(lines)
+                    file.close()
+
+                    #INCREMENT PRESS COUNT BY ONE
+                    press_count+=1
+
+                    #CLEAR THE LINE
+                    line = Marker()
+                    line.header.frame_id = "map"
+                    line.ns = "edges"
+                    line.action = line.DELETEALL
+                    line_pub.publish(line)
+                    
+                    img = gray
+                    img = cv2.flip(img, 0)
+                    img = cv2.threshold(img, 100, 255, cv2.THRESH_BINARY)[1]
+
+                    corners = cv2.goodFeaturesToTrack(img, 1000, 0.375, 50)
+                    corners = np.int0(corners)
+                    for i in corners:
+                        x, y = i.ravel()
+                        cv2.circle(img, (x, y), 10, 0, -1)
+
+                    _, contours, _ = cv2.findContours(img, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+
+                    #FIND INBETWEEN WAYPOINTS AND THEN APPEND TO WAYPOINTS DICTIONARY AND THEN CALCULATE THE GRAPH AGAIN
+                    import math
+                    keypoints = []
+                    global index
+                    interval = 200
+                    min_distance = 150
+                    # keys_way_pts = list(way_pts.keys())
+                    for i in list(way_pts.values()):
+                        pt = [(i[0]+10)/0.05,(i[1]+10)/0.05]
+                        keypoints.append(pt)
+                    for contour in contours:
+                        points = contour.reshape(-1, 2)                                               
+                        for i in range(0, len(points), interval):#                                 
+                            keypoint = tuple(points[i])#                                           
+                            #if it is not too close to any previously added point then only append
+                            if not any(math.sqrt((keypoint[0]-kp[0])**2 + (keypoint[1]-kp[1])**2) < min_distance for kp in keypoints):
+                                keypoints.append(keypoint)
+                                cv2.circle(img, (int(keypoint[0]),int(keypoint[1])),10,0,-1)
+                                way_pts[index] = [float(keypoint[0] * 0.05 - 10.0),float(keypoint[1] * 0.05 - 10.0)]
+                                x=way_pts[index][0]
+                                y=way_pts[index][1]
+                                position = Point(x, y, 0)
+                                make6DofMarker( False, InteractiveMarkerControl.NONE, position, True,name=str(index))
+                                server.applyChanges()
+                                index+= 1       
+
+                         
+                    _,contours,_ = cv2.findContours(img,cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
+                    
+                    for contour in contours:
+                        extLeft = tuple(contour[contour[:, :, 0].argmin()][0])
+                        extRight = tuple(contour[contour[:, :, 0].argmax()][0])
+                        extTop = tuple(contour[contour[:, :, 1].argmin()][0])
+                        extBot = tuple(contour[contour[:, :, 1].argmax()][0])
+                        dist_e_w = ((extLeft[0]-extRight[1])**2 + (extLeft[0]-extRight[1])**2 )**0.5
+                        dist_n_s = ((extTop[0]-extBot[1])**2 + (extTop[0]-extBot[1])**2 )**0.5
+                        if dist_e_w > dist_n_s:
+                            p1=[extLeft[0],extLeft[1]]
+                            p2=[extRight[0],extRight[1]]
+                        else:
+                            p1=[extTop[0],extTop[1]]
+                            p2=[extBot[0],extBot[1]]
+
+                        # cv2.circle(im_orig, (p1[0], p1[1]), 5, (0,0,255), -1)
+                        # cv2.circle(im_orig, (p2[0], p2[1]), 5, (0,0,255), -1)
+
+                        way_pts_values=np.array(list(way_pts.values()))
+                        p1_arr = np.array(p1)
+                        p2_arr = np.array(p2)
+
+                        p1_key = None
+                        p1_dist = float('inf')
+                        p2_key = None
+                        p2_dist = float('inf')
+                        for key, value in way_pts.items():
+                            value_arr = np.array(value)
+                            value_arr=(value_arr+10)/0.05
+                            dist_p1 = np.linalg.norm(value_arr - p1_arr)
+                            if dist_p1 < p1_dist:
+                                p1_dist = dist_p1
+                                p1_key = key
+                            dist_p2 = np.linalg.norm(value_arr - p2_arr)
+                            if dist_p2 < p2_dist:
+                                p2_dist = dist_p2
+                                p2_key = key
+                        
+                        p1_idx=p1_key
+                        p2_idx=p2_key
+
+
+                        # lines[indx]=[[way_pts[p1_idx][0],way_pts[p1_idx][1]],[way_pts[p2_idx][0],way_pts[p2_idx][1]]]
+                        # lines.append([[way_pts[p1_idx][0],way_pts[p1_idx][1]],[way_pts[p2_idx][0],way_pts[p2_idx][1]]])
+                        # if [[way_pts[p1_idx][0],way_pts[p1_idx][1]]!=[way_pts[p2_idx][0],way_pts[p2_idx][1]]]:
+                        lines[(p1_idx,p2_idx,indx)]=[[way_pts[p1_idx][0],way_pts[p1_idx][1]],[way_pts[p2_idx][0],way_pts[p2_idx][1]]]
+                        #DRAW NEW LINES
+                        line = Marker()
+                        line.header.frame_id = "map"
+                        line.header.stamp = rospy.Time.now()
+                        line.ns = "edges"
+                        line.id = indx
+                        indx+=1
+                        line.type = Marker.LINE_STRIP
+                        line.action = Marker.ADD
+                        line.scale.x = 0.3
+                        line.color.r = 0.0
+                        line.color.g = 1.0
+                        line.color.b = 0.0
+                        line.color.a = 1.0
+
+                        point1 = Point()
+                        point1.x = way_pts[p1_idx][0]
+                        point1.y = way_pts[p1_idx][1]
+                        point1.z = 0.0
+
+                        point2 = Point()
+                        point2.x = way_pts[p2_idx][0]
+                        point2.y = way_pts[p2_idx][1]
+                        point2.z = 0.0
+
+                        line.points.append(point1)
+                        line.points.append(point2)
+                        line_pub.publish(line)
+                        time.sleep(0.1)
+                        # cv2.line(im_orig, (int((way_pts[p1_idx][0]+10)/0.05), int((way_pts[p1_idx][1]+10)/0.05)), (int((way_pts[p2_idx][0]+10)/0.05), int((way_pts[p2_idx][1]+10)/0.05)), (255, 0, 0), 1)
+                        
+                        perimeter = cv2.arcLength(contour,True)
+                        perimeter = ((perimeter/2)+10)*0.05
+
+                        ########################
+                        ########################
+                        if p1_idx not in graph:
+                            graph[p1_idx] = {
+                                'node_pos': way_pts[p1_idx],
+                                'outward_edges': {
+                                    p2_idx: perimeter
+                                }
+                            }
+                        else:
+                                graph[p1_idx]['outward_edges'][p2_idx] = perimeter
+                            
+                        if p2_idx not in graph:
+                                graph[p2_idx] = {
+                                    'node_pos': way_pts[p2_idx],
+                                    'outward_edges': {
+                                        p1_idx: perimeter
+                                    }
+                                }
+                        else:
+                            graph[p2_idx]['outward_edges'][p1_idx] = perimeter
+
+
+                elif press_count ==2:
+                    #IF PRESSED SECOND TIME JUST SAVE THE YAMLS
+                    for i in range(0,5):
+                        print("")
+                    print("PRESSED SECOND TIME")
+                    for i in range(0,5):
+                        print("")
+                    press_count = 1
+
+                    file=open(home+"/waypoint/output_yaml/connected_graph_high_level.yaml","w")
+                    yaml.dump(graph,file)
+                    file.close()
+
+
+
+                    file=open(home+"/waypoint/output_yaml/way_pts_high_level.yaml","w")
+                    yaml.dump(way_pts,file)
+                    file.close()
+
+                    file=open(home+"/waypoint/output_yaml/edges_high_level.yaml","w")
+                    yaml.dump(lines,file)
+                    file.close()
+                    press_count+=1
+
+            if load == 1:
+                #IF WE ARE IN LOAD MODE THEN JUST SAVE THE YAMLS
+                for i in range(0,5):
+                    print("")
+                print(" SAVED ")
+                for i in range(0,5):
+                    print("")
+                press_count = 1
+
+                file=open(home+"/waypoint/output_yaml/connected_graph__edited.yaml","w")
+                yaml.dump(graph,file)
+                file.close()
+
+
+
+                file=open(home+"/waypoint/output_yaml/way_pts_edited.yaml","w")
+                yaml.dump(way_pts,file)
+                file.close()
+
+                file=open(home+"/waypoint/output_yaml/edges_edited.yaml","w")
+                yaml.dump(lines,file)
+                
+                server.clear()
+                server.applyChanges()
+                
+                line = Marker()
+                line.header.frame_id = "map"
+                line.ns = "edges"
+                line.action = line.DELETEALL
+                line_pub.publish(line)
+                # print(lines)
+                file.close()
+
+        #IF INSIDE LOAD PREVIOUS MODE
+        if feedback.menu_entry_id==6:
+            global lines
+            # lines={}
+            global way_pts
+            global graph
+            global load
+            load = 1
+            way_pts={}
+            print("")
+            print("")
+            print("")
+            print("LOAD PREVIOUS WORK")
+            print("")
+            print("")
+            print("")
+            #CLEAR THE MARKERS
+            server.clear()
+            server.applyChanges()
+
+            #CLEAR THE LINE MARKERS
+            line = Marker()
+            line.header.frame_id = "map"
+            line.ns = "edges"
+            line.action = line.DELETEALL
+            line_pub.publish(line)
+            # print("REMOVEDDDDDDDDDDDDDDDDDDDDDDDDDDDDd")
+
+            #ASK FOR THE PATH OF FILES
+            lines_path=raw_input("Enter path for edges.yaml :")
+            graph_path=raw_input("Enter path for connected_graph.yaml :")
+            way_pts_path=raw_input("Enter path for way_pts.yaml :")
+
+            #IF NO ENTERED, TAKE DEFAULT PATH
+            if lines_path=="":
+                lines_path=home+"/waypoint/output_yaml/edges_high_level.yaml"
+            if graph_path=="":
+                graph_path=home+"/waypoint/output_yaml/connected_graph_high_level.yaml"
+            if way_pts_path=="":
+                way_pts_path=home+"/waypoint/output_yaml/way_pts_high_level.yaml"
+
+            #MAKE DICTINARY FROM YAMLS
+            with open(lines_path, 'r') as stream:
+                lines=yaml.load(stream)
+
+            with open(graph_path, 'r') as stream:
+                # Converts yaml document to python object
+                graph=yaml.load(stream)
+            
+            with open(way_pts_path, 'r') as stream:
+                # Converts yaml document to python object
+                way_pts=yaml.load(stream)
+
+            #DRAW THE WAYPOINTS
+            for i in way_pts:
+                x=way_pts[i][0]
+                y=way_pts[i][1]
+                position = Point(x, y, 0)
+                make6DofMarker( False, InteractiveMarkerControl.NONE, position, True,name=str(i))
+                server.applyChanges()
+            print("way_pts=",way_pts)
+            
+            #DRAW THE LINES
+            for i in lines:
+                line = Marker()
+                line.header.frame_id = "map"
+                line.ns = "edges"
+                line.type = Marker.LINE_STRIP
+                line.header.stamp = rospy.Time.now()
+                line.action = line.ADD
+                line.scale.x = 0.3
+                line.color.r = 0.0
+                line.color.g = 1.0
+                line.color.b = 0.0
+                line.color.a = 1.0
+                line.id=i[2]
+
+                print(i,lines[i])
+                print("")
+                print("")
+                # print(lines[i][0][1])
+                p1_x=lines[i][0][0]
+                p1_y=lines[i][0][1]
+                p2_x=lines[i][1][0]
+                p2_y=lines[i][1][1]
+                point1 = Point(p1_x,p1_y,0)
+
+                point2 = Point(p2_x,p2_y,0)
+
+                line.points.append(point1)
+                line.points.append(point2)
+                line_pub.publish(line)
+                time.sleep(0.2)
+                # print(lines)   
+            print("LENGTH :",len(lines))  
+                   
+        rospy.loginfo( s + ": menu item " + str(feedback.menu_entry_id) + " clicked" + mp + "." )
+    elif feedback.event_type == InteractiveMarkerFeedback.POSE_UPDATE:
+        rospy.loginfo( s + ": pose changed")
+
+    elif feedback.event_type == InteractiveMarkerFeedback.MOUSE_DOWN:
+        rospy.loginfo( s + ": mouse down" + mp + "." )
+    elif feedback.event_type == InteractiveMarkerFeedback.MOUSE_UP:
+        rospy.loginfo( s + ": mouse up" + mp + "." )
+    server.applyChanges()
+
+def alignMarker( feedback ):
+    pose = feedback.pose
+
+    pose.position.x = round(pose.position.x-0.5)+0.5
+    pose.position.y = round(pose.position.y-0.5)+0.5
+
+    rospy.loginfo( feedback.marker_name + ": aligning position = " + str(feedback.pose.position.x) + "," + str(feedback.pose.position.y) + "," + str(feedback.pose.position.z) + " to " +
+                                                                     str(pose.position.x) + "," + str(pose.position.y) + "," + str(pose.position.z) )
+
+    server.setPose( feedback.marker_name, pose )
+    server.applyChanges()
+
+def rand( min_, max_ ):
+    return min_ + random()*(max_-min_)
+
+def makeBox( msg ):
+    marker = Marker()
+
+    marker.type = Marker.CUBE
+    marker.scale.x = msg.scale * 0.45
+    marker.scale.y = msg.scale * 0.45
+    marker.scale.z = msg.scale * 0.45
+    marker.color.r = 1
+    marker.color.g = 0
+    marker.color.b = 0
+    marker.color.a = 1.0
+
+    return marker
+
+def makeBoxControl( msg ):
+    control =  InteractiveMarkerControl()
+    control.always_visible = True
+    control.markers.append( makeBox(msg) )
+    msg.controls.append( control )
+    return control
+
+def saveMarker( int_marker ):
+  server.insert(int_marker, processFeedback)
+
+
+#####################################################################
+# Marker Creation
+
+def make6DofMarker( fixed, interaction_mode, position, show_6dof = False, name=""):
+    int_marker = InteractiveMarker()
+    int_marker.header.frame_id = "map"
+    int_marker.pose.position = position
+    int_marker.scale = 5
+
+    int_marker.name = name
+    int_marker.description = name
+
+    # insert a box
+    makeBoxControl(int_marker)
+    int_marker.controls[0].interaction_mode = interaction_mode
+
+    if fixed:
+        int_marker.name += "_fixed"
+        int_marker.description += "\n(fixed orientation)"
+
+    if interaction_mode != InteractiveMarkerControl.NONE:
+        control_modes_dict = { 
+                          InteractiveMarkerControl.MOVE_3D : "MOVE_3D",
+                          InteractiveMarkerControl.ROTATE_3D : "ROTATE_3D",
+                          InteractiveMarkerControl.MOVE_ROTATE_3D : "MOVE_ROTATE_3D" }
+        int_marker.name += "_" + control_modes_dict[interaction_mode]
+        int_marker.description = "3D Control"
+        if show_6dof: 
+          int_marker.description += " + 6-DOF controls"
+        int_marker.description += "\n" + control_modes_dict[interaction_mode]
+    
+    if show_6dof: 
+        control = InteractiveMarkerControl()
+        control.orientation.w = 1
+        control.orientation.x = 1
+        control.orientation.y = 0
+        control.orientation.z = 0
+        control.name = "rotate_x"
+        control.interaction_mode = InteractiveMarkerControl.ROTATE_AXIS
+        if fixed:
+            control.orientation_mode = InteractiveMarkerControl.FIXED
+        int_marker.controls.append(control)
+
+        control = InteractiveMarkerControl()
+        control.orientation.w = 1
+        control.orientation.x = 1
+        control.orientation.y = 0
+        control.orientation.z = 0
+        control.name = "move_x"
+        control.interaction_mode = InteractiveMarkerControl.MOVE_AXIS
+        if fixed:
+            control.orientation_mode = InteractiveMarkerControl.FIXED
+        int_marker.controls.append(control)
+
+        control = InteractiveMarkerControl()
+        control.orientation.w = 1
+        control.orientation.x = 0
+        control.orientation.y = 1
+        control.orientation.z = 0
+        control.name = "rotate_z"
+        control.interaction_mode = InteractiveMarkerControl.ROTATE_AXIS
+        if fixed:
+            control.orientation_mode = InteractiveMarkerControl.FIXED
+        int_marker.controls.append(control)
+
+        control = InteractiveMarkerControl()
+        control.orientation.w = 1
+        control.orientation.x = 0
+        control.orientation.y = 1
+        control.orientation.z = 0
+        control.name = "move_z"
+        control.interaction_mode = InteractiveMarkerControl.MOVE_AXIS
+        if fixed:
+            control.orientation_mode = InteractiveMarkerControl.FIXED
+        int_marker.controls.append(control)
+
+        control = InteractiveMarkerControl()
+        control.orientation.w = 1
+        control.orientation.x = 0
+        control.orientation.y = 0
+        control.orientation.z = 1
+        control.name = "rotate_y"
+        control.interaction_mode = InteractiveMarkerControl.ROTATE_AXIS
+        if fixed:
+            control.orientation_mode = InteractiveMarkerControl.FIXED
+        int_marker.controls.append(control)
+
+        control = InteractiveMarkerControl()
+        control.orientation.w = 1
+        control.orientation.x = 0
+        control.orientation.y = 0
+        control.orientation.z = 1
+        control.name = "move_y"
+        control.interaction_mode = InteractiveMarkerControl.MOVE_AXIS
+        if fixed:
+            control.orientation_mode = InteractiveMarkerControl.FIXED
+        int_marker.controls.append(control)
+
+    server.insert(int_marker, processFeedback)
+    menu_handler.apply( server, int_marker.name )
+
+
+def makeMenuMarker(position):
+    int_marker = InteractiveMarker()
+    int_marker.header.frame_id = "base_link"
+    int_marker.pose.position = position
+    int_marker.scale = 1
+
+    int_marker.name = "context_menu"
+    int_marker.description = "Context Menu\n(Right Click)"
+
+    # make one control using default visuals
+    control = InteractiveMarkerControl()
+    control.interaction_mode = InteractiveMarkerControl.MENU
+    control.description="Options"
+    control.name = "menu_only_control"
+    int_marker.controls.append(copy.deepcopy(control))
+
+    # make one control showing a box
+    marker = makeBox( int_marker )
+    control.markers.append( marker )
+    control.always_visible = True
+    int_marker.controls.append(control)
+
+    server.insert(int_marker, processFeedback)
+    menu_handler.apply( server, int_marker.name )
+
+def callback(msg): 
+    global graph
+    rospy.loginfo("coordinates:x=%f y=%f" %(msg.point.x,msg.point.y))
+    name_of_waypt=max([k for k in way_pts])+1
+    way_pts[name_of_waypt]=[msg.point.x,msg.point.y]
+    print("added waypoint :",name_of_waypt)
+    position=Point(msg.point.x, msg.point.y, 0)
+    make6DofMarker( False, InteractiveMarkerControl.NONE, position, True,name=str(name_of_waypt)) 
+    graph[name_of_waypt] = {'node_pos': way_pts[name_of_waypt],'outward_edges': {}}
+    server.applyChanges()
+ 
+    
+
+#####################################
+#                                   #
+#       CODE STARTS FROM HERE       #
+#                                   #
+#####################################
+
+#get path to home directory
+home = os. path. expanduser("~")
+path = home + "/Downloads/waypoint/input_images/skeleton_neom.png"
+print(path)
+#load the input image
+bw_map = cv2.imread(home+"/Downloads/waypoint/input_images/skeleton_neom.png")
+
+global im
+#we have not selected load previous option so load = 0
+load = 0
+
+#find the corners
+gray = cv2.cvtColor(bw_map, cv2.COLOR_BGR2GRAY)
+im = cv2.threshold(bw_map, 100, 255, cv2.THRESH_BINARY_INV)[1]
+im = cv2.cvtColor(im, cv2.COLOR_BGR2GRAY )
+im = cv2.flip(im, 0)
+# max_x,max_y=im.shape
+corners = cv2.goodFeaturesToTrack(im, 1000, 0.375, 50)
+corners = np.int0(corners)
+global way_pts
+way_pts = {}
+global index
+index=0
+
+for i in corners:
+    x, y = i.ravel()
+    #add detected corners to the way_pts dictionary after converting from image coordinates to map coordinates
+    way_pts[index]=[float(x * 0.05 - 10.0),float(y * 0.05 - 10.0)]
+    # cv2.circle(bw_map, (x, y), 30, (0,0,255), -1)
+    # print(i)
+    index+=1
+    
+
+#MAIN CODE
+if __name__=="__main__":
+    rospy.init_node("basic_controls")
+    br = TransformBroadcaster()
+    rospy.point_pub = rospy.Subscriber('/clicked_point', PointStamped, callback)
+    
+    # create a timer to update the published transforms
+    rospy.Timer(rospy.Duration(0.01), frameCallback)
+
+    server = InteractiveMarkerServer("basic_controls")
+
+    #add menu options
+    menu_handler.insert( "Delete waypoint", callback=processFeedback )
+    menu_handler.insert( "Make connected graph", callback=processFeedback )        
+    menu_handler.insert( "Add edge", callback=processFeedback )
+    menu_handler.insert( "Delete Edge", callback=processFeedback )
+    menu_handler.insert( "Save to YAML", callback=processFeedback)
+    menu_handler.insert( "Load previous", callback=processFeedback)
+
+    # sub_menu_handle = menu_handler.insert( "Submenu" )
+    # menu_handler.insert( "First Entry", parent=sub_menu_handle, callback=processFeedback )
+    # menu_handler.insert( "Second Entry", parent=sub_menu_handle, callback=processFeedback )
+    
+    index=0
+
+    #pulish the interactive markers on rviz
+    for i in way_pts:
+        x=way_pts[i][0]
+        y=way_pts[i][1]
+        position = Point(x, y, 0)
+        make6DofMarker( False, InteractiveMarkerControl.NONE, position, True,name=str(index))
+        index+=1
+
+    #EXAMPLE TO MAKE DIFFERENT TYPES OF MARKERS
+    # position = Point(-3, 3, 0)
+    # make6DofMarker( False, InteractiveMarkerControl.NONE, position, True,name="NISARG")
+    # position = Point( 0, 3, 0)
+    # make6DofMarker( True, InteractiveMarkerControl.NONE, position, True)
+    # position = Point( 3, 3, 0)
+    # makeRandomDofMarker( position )
+    # position = Point(-3, 0, 0)
+    # make6DofMarker( False, InteractiveMarkerControl.ROTATE_3D, position, False)
+    # position = Point( 0, 0, 0)
+    # make6DofMarker( False, InteractiveMarkerControl.MOVE_ROTATE_3D, position, True )
+    # position = Point( 3, 0, 0)
+    # make6DofMarker( False, InteractiveMarkerControl.MOVE_3D, position, False)
+    # position = Point(-3, -3, 0)
+    # makeViewFacingMarker( position )
+    # position = Point( 0, -3, 0)
+    # makeQuadrocopterMarker( position )
+    # position = Point( 3, -3, 0)
+    # makeChessPieceMarker( position )
+    # position = Point(-3, -6, 0)
+    # makePanTiltMarker( position )
+    # position = Point( 0, -6, 0)
+    # makeMovingMarker( position )
+    # position = Point( 3, -6, 0)
+    # makeMenuMarker( position )
+    #number of detected waypoints
+
+    print(len(way_pts))
+    server.applyChanges()
+    rospy.spin()
\ No newline at end of file
diff --git a/waypt_rviz_config.rviz b/waypt_rviz_config.rviz
new file mode 100644
index 0000000..30032dc
--- /dev/null
+++ b/waypt_rviz_config.rviz
@@ -0,0 +1,143 @@
+Panels:
+  - Class: rviz/Displays
+    Help Height: 78
+    Name: Displays
+    Property Tree Widget:
+      Expanded:
+        - /Global Options1
+        - /Status1
+        - /Map1
+      Splitter Ratio: 0.5
+    Tree Height: 728
+  - Class: rviz/Selection
+    Name: Selection
+  - Class: rviz/Tool Properties
+    Expanded:
+      - /2D Pose Estimate1
+      - /2D Nav Goal1
+      - /Publish Point1
+    Name: Tool Properties
+    Splitter Ratio: 0.5886790156364441
+  - Class: rviz/Views
+    Expanded:
+      - /Current View1
+    Name: Views
+    Splitter Ratio: 0.5
+  - Class: rviz/Time
+    Experimental: false
+    Name: Time
+    SyncMode: 0
+    SyncSource: ""
+Preferences:
+  PromptSaveOnExit: true
+Toolbars:
+  toolButtonStyle: 2
+Visualization Manager:
+  Class: ""
+  Displays:
+    - Alpha: 0.5
+      Cell Size: 1
+      Class: rviz/Grid
+      Color: 160; 160; 164
+      Enabled: true
+      Line Style:
+        Line Width: 0.029999999329447746
+        Value: Lines
+      Name: Grid
+      Normal Cell Count: 0
+      Offset:
+        X: 0
+        Y: 0
+        Z: 0
+      Plane: XY
+      Plane Cell Count: 10
+      Reference Frame: <Fixed Frame>
+      Value: true
+    - Alpha: 0.30000001192092896
+      Class: rviz/Map
+      Color Scheme: map
+      Draw Behind: false
+      Enabled: true
+      Name: Map
+      Topic: /map
+      Unreliable: false
+      Use Timestamp: false
+      Value: true
+    - Class: rviz/InteractiveMarkers
+      Enable Transparency: true
+      Enabled: true
+      Name: InteractiveMarkers
+      Show Axes: false
+      Show Descriptions: true
+      Show Visual Aids: false
+      Update Topic: /basic_controls/update
+      Value: true
+    - Class: rviz/Marker
+      Enabled: true
+      Marker Topic: /edges
+      Name: Marker
+      Namespaces:
+        {}
+      Queue Size: 100
+      Value: true
+  Enabled: true
+  Global Options:
+    Background Color: 48; 48; 48
+    Default Light: true
+    Fixed Frame: map
+    Frame Rate: 30
+  Name: root
+  Tools:
+    - Class: rviz/Interact
+      Hide Inactive Objects: true
+    - Class: rviz/MoveCamera
+    - Class: rviz/Select
+    - Class: rviz/FocusCamera
+    - Class: rviz/Measure
+    - Class: rviz/SetInitialPose
+      Theta std deviation: 0.2617993950843811
+      Topic: /initialpose
+      X std deviation: 0.5
+      Y std deviation: 0.5
+    - Class: rviz/SetGoal
+      Topic: /move_base_simple/goal
+    - Class: rviz/PublishPoint
+      Single click: true
+      Topic: /clicked_point
+  Value: true
+  Views:
+    Current:
+      Angle: 0.030000019818544388
+      Class: rviz/TopDownOrtho
+      Enable Stereo Rendering:
+        Stereo Eye Separation: 0.05999999865889549
+        Stereo Focal Distance: 1
+        Swap Stereo Eyes: false
+        Value: false
+      Invert Z Axis: false
+      Name: Current View
+      Near Clip Distance: 0.009999999776482582
+      Scale: 1.6785107851028442
+      Target Frame: <Fixed Frame>
+      Value: TopDownOrtho (rviz)
+      X: 347.3327941894531
+      Y: 425.5577392578125
+    Saved: ~
+Window Geometry:
+  Displays:
+    collapsed: true
+  Height: 1025
+  Hide Left Dock: true
+  Hide Right Dock: false
+  QMainWindow State: 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
+  Selection:
+    collapsed: false
+  Time:
+    collapsed: false
+  Tool Properties:
+    collapsed: false
+  Views:
+    collapsed: false
+  Width: 1853
+  X: 67
+  Y: 27