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Commit 7ccb785e authored by Larkin Heintzman's avatar Larkin Heintzman
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small file organization fixes

parent 35708bd0
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Showing with 907 additions and 3370 deletions
.gitignore
View file @ 7ccb785e
...@@ -2,5 +2,5 @@ ...@@ -2,5 +2,5 @@
/matlab_data_hiker_10km/ /matlab_data_hiker_10km/
/matlab_data_locale/ /matlab_data_locale/
/matlab_data_va_20km/ /matlab_data_va_20km/
/map_layers/punchbowl_tmp/ /map_layers/punchbowl/
/map_layers/devilsditch_tmp/ /map_layers/devilsditch/
DevilsDitch_hikers.csv deleted 100644 → 0
View file @ 35708bd0
Order,Latitude,Longitude,Elevation,Date Created,Distance from Start,Distance to Next,Bearing
1,37.30167,-77.31710,,,0.000,0.010,191.3
2,37.30158,-77.31712,,,0.010,0.011,270.0
3,37.30158,-77.31725,,,0.021,0.011,270.0
4,37.30158,-77.31738,,,0.033,0.011,270.0
5,37.30158,-77.31751,,,0.044,0.010,258.7
6,37.30156,-77.31762,,,0.054,0.009,243.4
7,37.30153,-77.31770,,,0.062,0.010,248.2
8,37.30150,-77.31781,,,0.072,0.013,270.0
9,37.30150,-77.31796,,,0.086,0.010,258.7
10,37.30148,-77.31807,,,0.095,0.010,258.7
11,37.30146,-77.31818,,,0.105,0.011,270.0
12,37.30146,-77.31830,,,0.117,0.013,278.1
13,37.30148,-77.31845,,,0.130,0.013,278.1
14,37.30150,-77.31860,,,0.143,0.011,270.0
15,37.30150,-77.31873,,,0.155,0.011,270.0
16,37.30150,-77.31886,,,0.166,0.009,243.4
17,37.30146,-77.31895,,,0.175,0.010,258.7
18,37.30144,-77.31906,,,0.184,0.010,258.7
19,37.30143,-77.31916,,,0.194,0.010,258.7
20,37.30141,-77.31927,,,0.204,0.011,270.0
21,37.30141,-77.31940,,,0.215,0.011,270.0
22,37.30141,-77.31953,,,0.227,0.012,279.5
23,37.30143,-77.31966,,,0.238,0.011,270.0
24,37.30143,-77.31979,,,0.250,0.011,270.0
25,37.30143,-77.31991,,,0.261,0.011,270.0
26,37.30143,-77.32004,,,0.273,0.011,270.0
27,37.30143,-77.32017,,,0.284,0.013,270.0
28,37.30143,-77.32032,,,0.297,0.013,270.0
29,37.30143,-77.32047,,,0.311,0.015,270.0
30,37.30143,-77.32064,,,0.326,0.011,270.0
31,37.30143,-77.32077,,,0.337,0.011,270.0
32,37.30143,-77.32090,,,0.349,0.011,270.0
33,37.30143,-77.32103,,,0.360,0.011,270.0
34,37.30143,-77.32116,,,0.371,0.011,270.0
35,37.30143,-77.32129,,,0.383,0.011,270.0
36,37.30143,-77.32142,,,0.394,0.013,270.0
37,37.30143,-77.32157,,,0.408,0.011,270.0
38,37.30143,-77.32169,,,0.419,0.011,270.0
39,37.30143,-77.32182,,,0.430,0.012,251.6
40,37.30139,-77.32195,,,0.442,0.010,258.7
41,37.30138,-77.32206,,,0.452,0.012,260.5
42,37.30136,-77.32219,,,0.464,0.012,260.5
43,37.30134,-77.32232,,,0.475,0.011,270.0
44,37.30134,-77.32245,,,0.487,0.011,270.0
45,37.30134,-77.32257,,,0.498,0.011,270.0
46,37.30134,-77.32270,,,0.510,0.010,258.7
47,37.30132,-77.32281,,,0.519,0.011,270.0
48,37.30132,-77.32294,,,0.531,0.011,270.0
49,37.30132,-77.32307,,,0.542,0.011,270.0
50,37.30132,-77.32320,,,0.553,0.010,258.7
51,37.30131,-77.32330,,,0.563,0.011,270.0
52,37.30131,-77.32343,,,0.575,0.013,261.9
53,37.30129,-77.32358,,,0.588,0.013,270.0
54,37.30129,-77.32373,,,0.601,0.011,270.0
55,37.30129,-77.32386,,,0.613,0.012,260.5
56,37.30127,-77.32399,,,0.624,0.011,270.0
57,37.30127,-77.32412,,,0.636,0.011,270.0
58,37.30127,-77.32425,,,0.647,0.011,270.0
59,37.30127,-77.32438,,,0.659,0.011,270.0
60,37.30127,-77.32451,,,0.670,0.000,0.0
1,37.82520,-79.08191,,,0.000,0.011,80.5
2,37.82522,-79.08178,,,0.011,0.012,71.6
3,37.82525,-79.08165,,,0.023,0.011,80.5
4,37.82527,-79.08152,,,0.035,0.012,71.6
5,37.82530,-79.08139,,,0.047,0.011,80.5
6,37.82532,-79.08127,,,0.058,0.011,80.5
7,37.82533,-79.08114,,,0.070,0.011,59.0
8,37.82539,-79.08103,,,0.081,0.011,59.0
9,37.82544,-79.08092,,,0.092,0.014,66.8
10,37.82549,-79.08077,,,0.106,0.011,80.5
11,37.82550,-79.08064,,,0.118,0.010,68.2
12,37.82554,-79.08054,,,0.128,0.011,80.5
13,37.82556,-79.08041,,,0.139,0.011,80.5
14,37.82557,-79.08028,,,0.151,0.011,90.0
15,37.82557,-79.08015,,,0.162,0.010,101.3
16,37.82556,-79.08004,,,0.172,0.011,90.0
17,37.82556,-79.07991,,,0.183,0.011,90.0
18,37.82556,-79.07979,,,0.195,0.011,80.5
19,37.82557,-79.07966,,,0.206,0.011,80.5
20,37.82559,-79.07953,,,0.218,0.011,80.5
21,37.82561,-79.07940,,,0.229,0.011,90.0
22,37.82561,-79.07927,,,0.240,0.011,90.0
23,37.82561,-79.07914,,,0.252,0.011,99.5
24,37.82559,-79.07901,,,0.263,0.008,116.6
25,37.82556,-79.07893,,,0.272,0.011,90.0
26,37.82556,-79.07880,,,0.283,0.010,101.3
27,37.82554,-79.07869,,,0.293,0.010,101.3
28,37.82552,-79.07858,,,0.302,0.010,111.8
29,37.82549,-79.07848,,,0.312,0.011,99.5
30,37.82547,-79.07835,,,0.324,0.008,116.6
31,37.82544,-79.07826,,,0.332,0.011,90.0
32,37.82544,-79.07813,,,0.344,0.010,101.3
33,37.82542,-79.07803,,,0.353,0.010,101.3
34,37.82540,-79.07792,,,0.363,0.011,90.0
35,37.82540,-79.07779,,,0.374,0.010,101.3
36,37.82539,-79.07768,,,0.384,0.008,116.6
37,37.82535,-79.07760,,,0.392,0.008,116.6
38,37.82532,-79.07751,,,0.401,0.008,116.6
39,37.82528,-79.07743,,,0.409,0.008,116.6
40,37.82525,-79.07734,,,0.418,0.008,135.0
41,37.82520,-79.07728,,,0.426,0.008,116.6
42,37.82516,-79.07719,,,0.434,0.010,101.3
43,37.82515,-79.07708,,,0.444,0.010,111.8
44,37.82511,-79.07697,,,0.454,0.010,101.3
45,37.82510,-79.07687,,,0.464,0.008,116.6
46,37.82506,-79.07678,,,0.472,0.010,101.3
47,37.82505,-79.07667,,,0.482,0.008,116.6
48,37.82501,-79.07659,,,0.490,0.008,116.6
49,37.82498,-79.07650,,,0.499,0.010,101.3
50,37.82496,-79.07640,,,0.508,0.010,101.3
51,37.82494,-79.07629,,,0.518,0.011,99.5
52,37.82493,-79.07616,,,0.529,0.008,116.6
53,37.82489,-79.07607,,,0.538,0.010,111.8
54,37.82486,-79.07597,,,0.548,0.011,90.0
55,37.82486,-79.07584,,,0.559,0.010,101.3
56,37.82484,-79.07573,,,0.569,0.011,90.0
57,37.82484,-79.07560,,,0.580,0.011,90.0
58,37.82484,-79.07547,,,0.592,0.008,116.6
59,37.82481,-79.07539,,,0.600,0.010,101.3
60,37.82479,-79.07528,,,0.610,0.013,90.0
61,37.82479,-79.07513,,,0.623,0.011,90.0
62,37.82479,-79.07500,,,0.634,0.011,90.0
63,37.82479,-79.07487,,,0.646,0.011,90.0
64,37.82479,-79.07474,,,0.657,0.011,90.0
65,37.82479,-79.07461,,,0.668,0.011,90.0
66,37.82479,-79.07449,,,0.680,0.011,90.0
67,37.82479,-79.07436,,,0.691,0.011,90.0
68,37.82479,-79.07423,,,0.702,0.011,90.0
69,37.82479,-79.07410,,,0.714,0.010,68.2
70,37.82482,-79.07399,,,0.724,0.011,59.0
71,37.82487,-79.07389,,,0.735,0.012,71.6
72,37.82491,-79.07376,,,0.747,0.010,68.2
73,37.82494,-79.07365,,,0.757,0.011,59.0
74,37.82499,-79.07354,,,0.768,0.010,68.2
75,37.82503,-79.07343,,,0.778,0.012,71.6
76,37.82506,-79.07331,,,0.790,0.012,71.6
77,37.82510,-79.07318,,,0.802,0.011,59.0
78,37.82515,-79.07307,,,0.813,0.011,80.5
79,37.82516,-79.07294,,,0.824,0.011,59.0
80,37.82522,-79.07283,,,0.835,0.013,63.4
81,37.82527,-79.07271,,,0.848,0.011,59.0
82,37.82532,-79.07260,,,0.859,0.011,59.0
83,37.82537,-79.07249,,,0.870,0.011,45.0
84,37.82544,-79.07240,,,0.881,0.012,51.3
85,37.82550,-79.07230,,,0.893,0.012,71.6
86,37.82554,-79.07217,,,0.905,0.013,63.4
87,37.82559,-79.07204,,,0.918,0.014,56.3
88,37.82566,-79.07191,,,0.931,0.008,63.4
89,37.82569,-79.07183,,,0.940,0.011,59.0
90,37.82574,-79.07172,,,0.951,0.011,59.0
91,37.82579,-79.07161,,,0.962,0.011,59.0
92,37.82585,-79.07150,,,0.973,0.012,71.6
93,37.82588,-79.07137,,,0.985,0.012,71.6
94,37.82591,-79.07125,,,0.997,0.014,56.3
95,37.82598,-79.07112,,,1.010,0.011,80.5
96,37.82600,-79.07099,,,1.022,0.011,80.5
97,37.82602,-79.07086,,,1.033,0.011,90.0
98,37.82602,-79.07073,,,1.044,0.011,59.0
99,37.82607,-79.07062,,,1.056,0.011,80.5
100,37.82608,-79.07050,,,1.067,0.011,80.5
101,37.82610,-79.07037,,,1.078,0.011,90.0
102,37.82610,-79.07024,,,1.090,0.011,90.0
103,37.82610,-79.07011,,,1.101,0.011,90.0
104,37.82610,-79.06998,,,1.112,0.012,71.6
105,37.82613,-79.06985,,,1.124,0.012,71.6
106,37.82617,-79.06972,,,1.136,0.011,80.5
107,37.82619,-79.06959,,,1.148,0.011,59.0
108,37.82624,-79.06949,,,1.159,0.010,68.2
109,37.82627,-79.06938,,,1.169,0.011,59.0
110,37.82632,-79.06927,,,1.180,0.011,59.0
111,37.82637,-79.06916,,,1.191,0.009,53.1
112,37.82642,-79.06908,,,1.201,0.011,45.0
113,37.82649,-79.06899,,,1.211,0.011,45.0
114,37.82656,-79.06891,,,1.222,0.011,45.0
115,37.82663,-79.06882,,,1.233,0.011,45.0
116,37.82670,-79.06874,,,1.243,0.013,26.6
117,37.82680,-79.06867,,,1.256,0.011,45.0
118,37.82687,-79.06859,,,1.267,0.011,45.0
119,37.82693,-79.06850,,,1.277,0.011,45.0
120,37.82700,-79.06841,,,1.288,0.011,59.0
121,37.82705,-79.06831,,,1.299,0.011,31.0
122,37.82714,-79.06824,,,1.310,0.011,59.0
123,37.82719,-79.06813,,,1.321,0.011,45.0
124,37.82726,-79.06805,,,1.332,0.011,45.0
125,37.82733,-79.06796,,,1.342,0.011,31.0
126,37.82741,-79.06790,,,1.353,0.011,31.0
127,37.82750,-79.06783,,,1.364,0.011,59.0
128,37.82755,-79.06773,,,1.375,0.011,59.0
129,37.82760,-79.06762,,,1.386,0.011,59.0
130,37.82765,-79.06751,,,1.397,0.011,45.0
131,37.82772,-79.06743,,,1.408,0.011,45.0
132,37.82779,-79.06734,,,1.419,0.011,59.0
133,37.82784,-79.06723,,,1.430,0.011,59.0
134,37.82789,-79.06713,,,1.441,0.011,59.0
135,37.82794,-79.06702,,,1.452,0.011,59.0
136,37.82799,-79.06691,,,1.463,0.010,68.2
137,37.82802,-79.06680,,,1.473,0.011,59.0
138,37.82807,-79.06670,,,1.484,0.011,45.0
139,37.82814,-79.06661,,,1.495,0.011,31.0
140,37.82823,-79.06655,,,1.506,0.011,45.0
141,37.82830,-79.06646,,,1.516,0.005,45.0
142,37.82833,-79.06642,,,1.522,0.000,0.0
1,38.29276,-78.65871,2742.782,,0.000,0.045,329.0
2,38.29310,-78.65897,2703.412,,0.045,0.052,342.9
3,38.29354,-78.65914,2667.323,,0.098,0.045,31.0
4,38.29388,-78.65889,2627.953,,0.143,0.053,351.9
5,38.29435,-78.65897,2621.391,,0.196,0.048,341.6
6,38.29475,-78.65914,2627.953,,0.244,0.050,347.0
7,38.29519,-78.65927,2608.268,,0.294,0.060,0.0
8,38.29574,-78.65927,2614.829,,0.354,0.050,347.0
9,38.29618,-78.65940,2631.234,,0.405,0.046,311.6
10,38.29645,-78.65979,2598.425,,0.451,0.048,341.6
11,38.29685,-78.65996,2572.178,,0.499,0.046,318.4
12,38.29716,-78.66030,2549.213,,0.545,0.032,256.0
13,38.29709,-78.66065,2519.685,,0.577,0.038,288.4
14,38.29719,-78.66103,2480.315,,0.615,0.053,347.0
15,38.29763,-78.66116,2424.541,,0.667,0.051,337.4
16,38.29804,-78.66137,2375.328,,0.719,0.044,290.0
17,38.29817,-78.66185,2365.486,,0.763,0.042,275.2
18,38.29820,-78.66232,2355.643,,0.804,0.040,196.7
19,38.29787,-78.66245,2329.396,,0.844,0.033,215.5
20,38.29763,-78.66266,2316.273,,0.877,0.039,225.0
21,38.29739,-78.66296,2276.903,,0.916,0.039,240.9
22,38.29722,-78.66335,2250.656,,0.955,0.036,198.4
23,38.29692,-78.66348,2237.533,,0.991,0.041,191.3
24,38.29658,-78.66356,2191.601,,1.032,0.040,191.3
25,38.29624,-78.66365,2152.231,,1.072,0.034,206.6
26,38.29597,-78.66382,2132.546,,1.106,0.036,198.4
27,38.29567,-78.66395,2129.265,,1.142,0.043,190.3
28,38.29530,-78.66404,2103.018,,1.184,0.044,201.8
29,38.29496,-78.66421,2047.244,,1.228,0.037,198.4
30,38.29465,-78.66434,2020.997,,1.265,0.036,212.0
31,38.29438,-78.66455,2007.874,,1.300,0.032,225.0
32,38.29418,-78.66481,1998.031,,1.332,0.035,229.4
33,38.29398,-78.66511,1981.627,,1.367,0.033,215.5
34,38.29374,-78.66532,1958.661,,1.400,0.032,249.4
35,38.29364,-78.66567,1948.819,,1.433,0.032,215.5
36,38.29340,-78.66588,1945.538,,1.465,0.034,206.6
37,38.29313,-78.66605,1935.696,,1.499,0.036,220.6
38,38.29289,-78.66631,1906.168,,1.534,0.035,220.6
39,38.29266,-78.66657,1886.483,,1.570,0.032,225.0
40,38.29246,-78.66683,1889.764,,1.601,0.034,243.4
41,38.29232,-78.66717,1883.202,,1.635,0.033,240.3
42,38.29218,-78.66747,1843.832,,1.668,0.040,228.8
43,38.29195,-78.66781,1856.955,,1.708,0.034,234.5
44,38.29178,-78.66811,1824.147,,1.742,0.035,229.4
45,38.29158,-78.66841,1833.990,,1.776,0.043,259.7
46,38.29151,-78.66889,1807.743,,1.819,0.038,258.7
47,38.29144,-78.66931,1794.619,,1.858,0.037,246.0
48,38.29131,-78.66970,1797.900,,1.895,0.037,251.6
49,38.29120,-78.67009,1765.092,,1.932,0.032,234.5
50,38.29103,-78.67039,1758.530,,1.964,0.037,246.0
51,38.29090,-78.67077,1751.969,,2.001,0.034,243.4
52,38.29076,-78.67112,1738.845,,2.035,0.034,243.4
53,38.29063,-78.67146,1725.722,,2.069,0.037,246.0
54,38.29049,-78.67185,1732.283,,2.106,0.033,225.0
55,38.29029,-78.67210,1758.530,,2.138,0.047,180.0
56,38.28988,-78.67210,1715.879,,2.185,0.036,198.4
57,38.28958,-78.67223,1706.037,,2.221,0.034,206.6
58,38.28931,-78.67240,1692.913,,2.255,0.037,204.0
59,38.28901,-78.67258,1683.071,,2.292,0.032,225.0
60,38.28880,-78.67283,1686.352,,2.324,0.032,234.5
61,38.28863,-78.67313,1696.194,,2.356,0.036,251.6
62,38.28853,-78.67352,1676.509,,2.392,0.037,238.0
63,38.28836,-78.67386,1646.982,,2.429,0.034,243.4
64,38.28823,-78.67421,1656.824,,2.463,0.038,258.7
65,38.28816,-78.67464,1653.543,,2.501,0.036,251.6
66,38.28806,-78.67502,1643.701,,2.537,0.038,233.1
67,38.28786,-78.67537,1650.262,,2.574,0.036,238.0
68,38.28769,-78.67571,1630.577,,2.610,0.035,229.4
69,38.28748,-78.67601,1650.262,,2.645,0.035,229.4
70,38.28728,-78.67631,1637.139,,2.680,0.033,234.5
71,38.28711,-78.67661,1653.543,,2.713,0.046,270.0
72,38.28711,-78.67712,1630.577,,2.758,0.036,251.6
73,38.28701,-78.67751,1617.454,,2.794,0.036,251.6
74,38.28691,-78.67790,1610.892,,2.830,0.039,240.9
75,38.28674,-78.67828,1617.454,,2.869,0.050,270.0
76,38.28674,-78.67884,1587.927,,2.918,0.043,254.7
77,38.28664,-78.67931,1578.084,,2.961,0.035,229.4
78,38.28643,-78.67961,1564.961,,2.996,0.039,240.9
79,38.28627,-78.68000,1578.084,,3.035,0.032,234.5
80,38.28610,-78.68030,1584.646,,3.067,0.034,243.4
81,38.28596,-78.68064,1578.084,,3.101,0.035,243.4
82,38.28583,-78.68099,1607.612,,3.136,0.038,246.0
83,38.28569,-78.68137,1578.084,,3.174,0.043,254.7
84,38.28559,-78.68185,1568.241,,3.217,0.049,265.6
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456,38.44412,-78.43642,,,9.178,0.016,135.0
457,38.44402,-78.43629,,,9.194,0.022,180.0
458,38.44382,-78.43629,,,9.216,0.022,180.0
459,38.44361,-78.43629,,,9.239,0.017,206.6
460,38.44348,-78.43637,,,9.255,0.022,180.0
461,38.44328,-78.43637,,,9.278,0.015,180.0
462,38.44314,-78.43637,,,9.293,0.019,168.7
463,38.44297,-78.43633,,,9.312,0.017,153.4
464,38.44284,-78.43624,,,9.329,0.020,158.2
465,38.44267,-78.43616,,,9.349,0.022,180.0
466,38.44247,-78.43616,,,9.371,0.017,153.4
467,38.44233,-78.43607,,,9.388,0.019,168.7
468,38.44216,-78.43603,,,9.407,0.016,225.0
469,38.44206,-78.43616,,,9.423,0.020,201.8
470,38.44189,-78.43624,,,9.443,0.019,191.3
471,38.44172,-78.43629,,,9.463,0.019,191.3
472,38.44156,-78.43633,,,9.482,0.019,191.3
473,38.44139,-78.43637,,,9.501,0.019,191.3
474,38.44122,-78.43642,,,9.520,0.022,180.0
475,38.44102,-78.43642,,,9.542,0.019,191.3
476,38.44085,-78.43646,,,9.561,0.023,189.5
477,38.44064,-78.43650,,,9.584,0.017,206.6
478,38.44051,-78.43659,,,9.601,0.019,191.3
479,38.44034,-78.43663,,,9.620,0.017,206.6
480,38.44021,-78.43672,,,9.637,0.019,191.3
481,38.44004,-78.43676,,,9.656,0.019,191.3
482,38.43987,-78.43680,,,9.675,0.016,135.0
483,38.43977,-78.43667,,,9.691,0.017,153.4
484,38.43963,-78.43659,,,9.708,0.016,135.0
485,38.43953,-78.43646,,,9.724,0.017,116.6
486,38.43946,-78.43629,,,9.740,0.016,135.0
487,38.43936,-78.43616,,,9.756,0.019,101.3
488,38.43933,-78.43594,,,9.775,0.017,116.6
489,38.43926,-78.43577,,,9.792,0.008,116.6
490,38.43923,-78.43569,,,9.800,0.037,126.9
491,38.43902,-78.43534,,,9.838,0.038,174.3
492,38.43869,-78.43530,,,9.876,0.032,200.6
493,38.43842,-78.43543,,,9.908,0.034,180.0
494,38.43811,-78.43543,,,9.941,0.030,180.0
495,38.43784,-78.43543,,,9.971,0.040,158.2
496,38.43751,-78.43526,,,10.012,0.051,162.9
497,38.43707,-78.43509,,,10.063,0.057,156.8
498,38.43659,-78.43483,,,10.120,0.027,123.7
499,38.43646,-78.43457,,,10.147,0.035,122.0
500,38.43629,-78.43423,,,10.182,0.042,153.4
501,38.43595,-78.43401,,,10.224,0.053,175.9
502,38.43548,-78.43397,,,10.277,0.044,211.0
503,38.43514,-78.43423,,,10.320,0.049,188.7
504,38.43470,-78.43431,,,10.370,0.029,156.8
505,38.43447,-78.43418,,,10.398,0.064,130.2
506,38.43410,-78.43363,,,10.462,0.050,132.0
507,38.43379,-78.43320,,,10.512,0.041,185.2
508,38.43342,-78.43324,,,10.554,0.035,192.5
509,38.43312,-78.43333,,,10.588,0.040,201.8
510,38.43278,-78.43350,,,10.629,0.020,201.8
511,38.43261,-78.43358,,,10.649,0.061,190.6
512,38.43207,-78.43371,,,10.710,0.053,309.3
513,38.43237,-78.43418,,,10.763,0.026,225.0
514,38.43221,-78.43440,,,10.789,0.056,199.7
515,38.43173,-78.43461,,,10.845,0.036,198.4
516,38.43143,-78.43474,,,10.881,0.055,195.9
517,38.43096,-78.43491,,,10.935,0.040,221.2
518,38.43069,-78.43521,,,10.975,0.037,233.1
519,38.43048,-78.43556,,,11.013,0.044,239.0
520,38.43028,-78.43599,,,11.056,0.014,213.7
521,38.43018,-78.43607,,,11.070,0.054,245.2
522,38.42998,-78.43663,,,11.123,0.034,270.0
523,38.42998,-78.43702,,,11.157,0.035,229.4
524,38.42978,-78.43732,,,11.192,0.068,266.8
525,38.42974,-78.43809,,,11.259,0.043,285.3
526,38.42984,-78.43856,,,11.302,0.038,264.3
527,38.42981,-78.43899,,,11.340,0.049,202.6
528,38.42940,-78.43921,,,11.388,0.061,217.6
529,38.42897,-78.43963,,,11.450,0.045,265.2
530,38.42893,-78.44015,,,11.495,0.083,267.4
531,38.42890,-78.44109,,,11.578,0.037,315.0
532,38.42913,-78.44139,,,11.615,0.042,296.6
533,38.42930,-78.44182,,,11.656,0.049,270.0
534,38.42930,-78.44238,,,11.705,0.054,245.2
535,38.42910,-78.44294,,,11.759,0.045,274.8
536,38.42913,-78.44345,,,11.804,0.048,315.0
537,38.42944,-78.44384,,,11.852,0.059,309.8
538,38.42978,-78.44436,,,11.910,0.052,291.0
539,38.42994,-78.44491,,,11.962,0.075,306.9
540,38.43035,-78.44560,,,12.037,0.042,296.6
541,38.43052,-78.44603,,,12.079,0.066,286.4
542,38.43069,-78.44676,,,12.146,0.054,294.8
543,38.43089,-78.44732,,,12.199,0.034,296.6
544,38.43102,-78.44766,,,12.233,0.032,315.0
545,38.43123,-78.44792,,,12.265,0.047,331.4
546,38.43160,-78.44817,,,12.312,0.047,341.6
547,38.43200,-78.44835,,,12.359,0.037,323.1
548,38.43227,-78.44860,,,12.396,0.043,307.9
549,38.43251,-78.44899,,,12.439,0.062,302.7
550,38.43281,-78.44959,,,12.502,0.035,302.0
551,38.43298,-78.44993,,,12.537,0.071,288.4
552,38.43318,-78.45071,,,12.608,0.014,326.3
553,38.43329,-78.45079,,,12.621,0.049,355.6
554,38.43372,-78.45084,,,12.670,0.051,342.9
555,38.43416,-78.45101,,,12.721,0.059,320.2
556,38.43457,-78.45144,,,12.780,0.049,355.6
557,38.43501,-78.45148,,,12.829,0.040,338.2
558,38.43534,-78.45165,,,12.869,0.051,342.9
559,38.43578,-78.45182,,,12.920,0.029,23.2
560,38.43602,-78.45169,,,12.949,0.037,24.0
561,38.43632,-78.45152,,,12.985,0.032,35.5
562,38.43656,-78.45131,,,13.018,0.053,50.7
563,38.43686,-78.45084,,,13.071,0.047,28.6
564,38.43724,-78.45058,,,13.118,0.056,0.0
565,38.43774,-78.45058,,,13.174,0.045,318.4
566,38.43805,-78.45092,,,13.219,0.035,319.4
567,38.43828,-78.45118,,,13.254,0.047,331.4
568,38.43865,-78.45144,,,13.301,0.042,296.6
569,38.43882,-78.45187,,,13.343,0.043,322.1
570,38.43913,-78.45217,,,13.385,0.055,298.3
571,38.43936,-78.45272,,,13.441,0.043,285.3
572,38.43946,-78.45320,,,13.483,0.040,291.8
573,38.43960,-78.45363,,,13.524,0.054,294.8
574,38.43980,-78.45418,,,13.577,0.037,306.9
575,38.44000,-78.45453,,,13.615,0.058,315.0
576,38.44037,-78.45500,,,13.673,0.053,309.3
577,38.44068,-78.45547,,,13.726,0.047,298.6
578,38.44088,-78.45594,,,13.773,0.044,290.0
579,38.44102,-78.45641,,,13.817,0.059,309.8
580,38.44135,-78.45693,,,13.876,0.035,282.5
581,38.44142,-78.45732,,,13.910,0.058,284.9
582,38.44156,-78.45796,,,13.968,0.043,285.3
583,38.44166,-78.45843,,,14.011,0.065,283.2
584,38.44179,-78.45916,,,14.077,0.069,292.4
585,38.44203,-78.45989,,,14.145,0.070,285.5
586,38.44220,-78.46066,,,14.215,0.039,299.1
587,38.44237,-78.46105,,,14.254,0.039,286.7
588,38.44247,-78.46148,,,14.293,0.045,294.4
589,38.44264,-78.46195,,,14.338,0.032,290.6
590,38.44274,-78.46229,,,14.370,0.052,291.0
591,38.44291,-78.46285,,,14.423,0.046,279.5
592,38.44297,-78.46337,,,14.468,0.051,287.1
593,38.44311,-78.46392,,,14.519,0.042,280.3
594,38.44318,-78.46440,,,14.561,0.049,274.4
595,38.44321,-78.46495,,,14.610,0.046,279.5
596,38.44328,-78.46547,,,14.655,0.021,315.0
597,38.44341,-78.46564,,,14.677,0.029,23.2
598,38.44365,-78.46551,,,14.705,0.064,69.4
599,38.44385,-78.46483,,,14.769,0.055,61.7
600,38.44409,-78.46427,,,14.824,0.057,66.8
601,38.44429,-78.46367,,,14.882,0.037,90.0
602,38.44429,-78.46324,,,14.919,0.064,83.3
603,38.44436,-78.46251,,,14.983,0.049,90.0
604,38.44436,-78.46195,,,15.032,0.061,100.6
605,38.44426,-78.46126,,,15.093,0.056,86.2
606,38.44429,-78.46062,,,15.149,0.076,69.8
607,38.44453,-78.45980,,,15.225,0.039,73.3
608,38.44463,-78.45938,,,15.264,0.063,72.6
609,38.44480,-78.45869,,,15.327,0.044,59.0
610,38.44500,-78.45826,,,15.371,0.038,101.3
611,38.44493,-78.45783,,,15.409,0.052,120.3
612,38.44469,-78.45732,,,15.461,0.087,97.4
613,38.44459,-78.45633,,,15.548,0.066,106.4
614,38.44442,-78.45560,,,15.614,0.074,120.5
615,38.44409,-78.45487,,,15.688,0.044,70.0
616,38.44422,-78.45440,,,15.732,0.052,90.0
617,38.44422,-78.45380,,,15.784,0.056,90.0
618,38.44422,-78.45315,,,15.841,0.060,86.4
619,38.44426,-78.45247,,,15.901,0.068,80.5
620,38.44436,-78.45169,,,15.969,0.058,75.1
621,38.44449,-78.45105,,,16.027,0.072,84.0
622,38.44456,-78.45023,,,16.099,0.068,83.7
623,38.44463,-78.44946,,,16.167,0.025,63.4
624,38.44473,-78.44920,,,16.192,0.032,54.5
625,38.44490,-78.44890,,,16.224,0.050,26.6
626,38.44530,-78.44865,,,16.274,0.029,66.8
627,38.44540,-78.44835,,,16.303,0.027,33.7
628,38.44561,-78.44817,,,16.330,0.064,61.9
629,38.44588,-78.44753,,,16.393,0.026,81.9
630,38.44591,-78.44723,,,16.420,0.023,80.5
631,38.44594,-78.44697,,,16.443,0.050,77.0
632,38.44604,-78.44642,,,16.493,0.039,60.9
633,38.44621,-78.44603,,,16.531,0.037,66.0
634,38.44635,-78.44564,,,16.568,0.046,80.5
635,38.44642,-78.44513,,,16.614,0.032,110.6
636,38.44631,-78.44478,,,16.646,0.060,82.9
637,38.44638,-78.44410,,,16.706,0.041,123.7
638,38.44618,-78.44371,,,16.747,0.012,108.4
639,38.44615,-78.44358,,,16.759,0.054,123.7
640,38.44588,-78.44307,,,16.813,0.046,125.0
641,38.44564,-78.44264,,,16.858,0.044,121.0
642,38.44544,-78.44221,,,16.902,0.040,131.2
643,38.44520,-78.44187,,,16.942,0.061,127.6
644,38.44486,-78.44131,,,17.003,0.058,135.0
645,38.44449,-78.44084,,,17.062,0.045,138.4
646,38.44419,-78.44049,,,17.107,0.053,135.0
647,38.44385,-78.44006,,,17.160,0.046,104.0
648,38.44375,-78.43955,,,17.206,0.087,121.0
649,38.44334,-78.43869,,,17.293,0.015,104.0
650,38.44331,-78.43852,,,17.309,0.044,110.0
651,38.44318,-78.43805,,,17.353,0.060,90.0
652,38.44318,-78.43736,,,17.413,0.038,101.3
653,38.44311,-78.43693,,,17.451,0.000,0.0
Punchbowl_hiker.csv deleted 100644 → 0
View file @ 35708bd0
Order,Latitude,Longitude,Elevation,Date Created,Distance from Start,Distance to Next,Bearing
1,37.30167,-77.31710,,,0.000,0.010,191.3
2,37.30158,-77.31712,,,0.010,0.011,270.0
3,37.30158,-77.31725,,,0.021,0.011,270.0
4,37.30158,-77.31738,,,0.033,0.011,270.0
5,37.30158,-77.31751,,,0.044,0.010,258.7
6,37.30156,-77.31762,,,0.054,0.009,243.4
7,37.30153,-77.31770,,,0.062,0.010,248.2
8,37.30150,-77.31781,,,0.072,0.013,270.0
9,37.30150,-77.31796,,,0.086,0.010,258.7
10,37.30148,-77.31807,,,0.095,0.010,258.7
11,37.30146,-77.31818,,,0.105,0.011,270.0
12,37.30146,-77.31830,,,0.117,0.013,278.1
13,37.30148,-77.31845,,,0.130,0.013,278.1
14,37.30150,-77.31860,,,0.143,0.011,270.0
15,37.30150,-77.31873,,,0.155,0.011,270.0
16,37.30150,-77.31886,,,0.166,0.009,243.4
17,37.30146,-77.31895,,,0.175,0.010,258.7
18,37.30144,-77.31906,,,0.184,0.010,258.7
19,37.30143,-77.31916,,,0.194,0.010,258.7
20,37.30141,-77.31927,,,0.204,0.011,270.0
21,37.30141,-77.31940,,,0.215,0.011,270.0
22,37.30141,-77.31953,,,0.227,0.012,279.5
23,37.30143,-77.31966,,,0.238,0.011,270.0
24,37.30143,-77.31979,,,0.250,0.011,270.0
25,37.30143,-77.31991,,,0.261,0.011,270.0
26,37.30143,-77.32004,,,0.273,0.011,270.0
27,37.30143,-77.32017,,,0.284,0.013,270.0
28,37.30143,-77.32032,,,0.297,0.013,270.0
29,37.30143,-77.32047,,,0.311,0.015,270.0
30,37.30143,-77.32064,,,0.326,0.011,270.0
31,37.30143,-77.32077,,,0.337,0.011,270.0
32,37.30143,-77.32090,,,0.349,0.011,270.0
33,37.30143,-77.32103,,,0.360,0.011,270.0
34,37.30143,-77.32116,,,0.371,0.011,270.0
35,37.30143,-77.32129,,,0.383,0.011,270.0
36,37.30143,-77.32142,,,0.394,0.013,270.0
37,37.30143,-77.32157,,,0.408,0.011,270.0
38,37.30143,-77.32169,,,0.419,0.011,270.0
39,37.30143,-77.32182,,,0.430,0.012,251.6
40,37.30139,-77.32195,,,0.442,0.010,258.7
41,37.30138,-77.32206,,,0.452,0.012,260.5
42,37.30136,-77.32219,,,0.464,0.012,260.5
43,37.30134,-77.32232,,,0.475,0.011,270.0
44,37.30134,-77.32245,,,0.487,0.011,270.0
45,37.30134,-77.32257,,,0.498,0.011,270.0
46,37.30134,-77.32270,,,0.510,0.010,258.7
47,37.30132,-77.32281,,,0.519,0.011,270.0
48,37.30132,-77.32294,,,0.531,0.011,270.0
49,37.30132,-77.32307,,,0.542,0.011,270.0
50,37.30132,-77.32320,,,0.553,0.010,258.7
51,37.30131,-77.32330,,,0.563,0.011,270.0
52,37.30131,-77.32343,,,0.575,0.013,261.9
53,37.30129,-77.32358,,,0.588,0.013,270.0
54,37.30129,-77.32373,,,0.601,0.011,270.0
55,37.30129,-77.32386,,,0.613,0.012,260.5
56,37.30127,-77.32399,,,0.624,0.011,270.0
57,37.30127,-77.32412,,,0.636,0.011,270.0
58,37.30127,-77.32425,,,0.647,0.011,270.0
59,37.30127,-77.32438,,,0.659,0.011,270.0
60,37.30127,-77.32451,,,0.670,0.000,0.0
1,37.82520,-79.08191,,,0.000,0.011,80.5
2,37.82522,-79.08178,,,0.011,0.012,71.6
3,37.82525,-79.08165,,,0.023,0.011,80.5
4,37.82527,-79.08152,,,0.035,0.012,71.6
5,37.82530,-79.08139,,,0.047,0.011,80.5
6,37.82532,-79.08127,,,0.058,0.011,80.5
7,37.82533,-79.08114,,,0.070,0.011,59.0
8,37.82539,-79.08103,,,0.081,0.011,59.0
9,37.82544,-79.08092,,,0.092,0.014,66.8
10,37.82549,-79.08077,,,0.106,0.011,80.5
11,37.82550,-79.08064,,,0.118,0.010,68.2
12,37.82554,-79.08054,,,0.128,0.011,80.5
13,37.82556,-79.08041,,,0.139,0.011,80.5
14,37.82557,-79.08028,,,0.151,0.011,90.0
15,37.82557,-79.08015,,,0.162,0.010,101.3
16,37.82556,-79.08004,,,0.172,0.011,90.0
17,37.82556,-79.07991,,,0.183,0.011,90.0
18,37.82556,-79.07979,,,0.195,0.011,80.5
19,37.82557,-79.07966,,,0.206,0.011,80.5
20,37.82559,-79.07953,,,0.218,0.011,80.5
21,37.82561,-79.07940,,,0.229,0.011,90.0
22,37.82561,-79.07927,,,0.240,0.011,90.0
23,37.82561,-79.07914,,,0.252,0.011,99.5
24,37.82559,-79.07901,,,0.263,0.008,116.6
25,37.82556,-79.07893,,,0.272,0.011,90.0
26,37.82556,-79.07880,,,0.283,0.010,101.3
27,37.82554,-79.07869,,,0.293,0.010,101.3
28,37.82552,-79.07858,,,0.302,0.010,111.8
29,37.82549,-79.07848,,,0.312,0.011,99.5
30,37.82547,-79.07835,,,0.324,0.008,116.6
31,37.82544,-79.07826,,,0.332,0.011,90.0
32,37.82544,-79.07813,,,0.344,0.010,101.3
33,37.82542,-79.07803,,,0.353,0.010,101.3
34,37.82540,-79.07792,,,0.363,0.011,90.0
35,37.82540,-79.07779,,,0.374,0.010,101.3
36,37.82539,-79.07768,,,0.384,0.008,116.6
37,37.82535,-79.07760,,,0.392,0.008,116.6
38,37.82532,-79.07751,,,0.401,0.008,116.6
39,37.82528,-79.07743,,,0.409,0.008,116.6
40,37.82525,-79.07734,,,0.418,0.008,135.0
41,37.82520,-79.07728,,,0.426,0.008,116.6
42,37.82516,-79.07719,,,0.434,0.010,101.3
43,37.82515,-79.07708,,,0.444,0.010,111.8
44,37.82511,-79.07697,,,0.454,0.010,101.3
45,37.82510,-79.07687,,,0.464,0.008,116.6
46,37.82506,-79.07678,,,0.472,0.010,101.3
47,37.82505,-79.07667,,,0.482,0.008,116.6
48,37.82501,-79.07659,,,0.490,0.008,116.6
49,37.82498,-79.07650,,,0.499,0.010,101.3
50,37.82496,-79.07640,,,0.508,0.010,101.3
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devilsditch_track_meters.csv deleted 100644 → 0
View file @ 35708bd0
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feature_set.py
View file @ 7ccb785e
...@@ -31,7 +31,7 @@ def trim_extent(x_pts, y_pts, scaled_extent): ...@@ -31,7 +31,7 @@ def trim_extent(x_pts, y_pts, scaled_extent):
y_pts_trimmed = y_pts[np.invert(rm_mask)] # trim points y_pts_trimmed = y_pts[np.invert(rm_mask)] # trim points
return [x_pts_trimmed, y_pts_trimmed] return [x_pts_trimmed, y_pts_trimmed]
def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_files = False, file_id = 'temp', plot_data = False): def grab_features(anchor_point, extent, sample_dist = 10, case_name = 'blah', heading = 0, save_files = False, save_to_folder = False, file_id = 'temp', plot_data = False):
roads_url = "https://carto.nationalmap.gov/arcgis/rest/services/transportation/MapServer/30" roads_url = "https://carto.nationalmap.gov/arcgis/rest/services/transportation/MapServer/30"
river_url = "https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServer/6" river_url = "https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServer/6"
riverw_url = "https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServer/8" riverw_url = "https://hydro.nationalmap.gov/arcgis/rest/services/nhd/MapServer/8"
...@@ -74,7 +74,7 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file ...@@ -74,7 +74,7 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file
q = [] q = []
query_cnt = 0 query_cnt = 0
while type(q)==list and query_cnt <= 20: # have to do this because arcgis is sketchy as hell and doesnt always come back while type(q)==list and query_cnt <= 30: # have to do this because arcgis is sketchy as hell and doesnt always come back
try: try:
print("querying {} layer...".format(name_list[i])) print("querying {} layer...".format(name_list[i]))
query_starttime = time.time() query_starttime = time.time()
...@@ -95,14 +95,21 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file ...@@ -95,14 +95,21 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file
print("query time {}".format(query_endtime - query_starttime)) print("query time {}".format(query_endtime - query_starttime))
if query_cnt > 20 and not q: if query_cnt > 30 and not q:
print("{} layer failed too many times, leaving empty".format(name_list[i])) print("{} layer failed too many times, leaving empty".format(name_list[i]))
if save_files: if save_files:
fn = "map_layers/"+name_list[i]+"_data_"+file_id+".csv" if save_to_folder:
np.savetxt(fn,bin_map,delimiter=",", fmt='%f') fn = "map_layers\\" + case_name + "\\"+name_list[i]+"_data_"+file_id+".csv"
if name_list[i] in inac_layers: np.savetxt(fn,bin_map,delimiter=",", fmt='%f')
fn = "map_layers/" + name_list[i] + "_inac_data_" + file_id + ".csv" if name_list[i] in inac_layers:
np.savetxt(fn, bin_map, delimiter=",", fmt='%f') fn = "map_layers\\" + case_name + "\\" + name_list[i] + "_inac_data_" + file_id + ".csv"
np.savetxt(fn, bin_map, delimiter=",", fmt='%f')
else:
fn = "map_layers\\" + name_list[i]+"_data_"+file_id+".csv"
np.savetxt(fn,bin_map,delimiter=",", fmt='%f')
if name_list[i] in inac_layers:
fn = "map_layers\\" + name_list[i] + "_inac_data_" + file_id + ".csv"
np.savetxt(fn, bin_map, delimiter=",", fmt='%f')
continue continue
print("{} layer sucessfully queried".format(name_list[i])) print("{} layer sucessfully queried".format(name_list[i]))
...@@ -238,14 +245,24 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file ...@@ -238,14 +245,24 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file
viz_map[:, :, viz_cnt] = inac_bin_map viz_map[:, :, viz_cnt] = inac_bin_map
viz_cnt = viz_cnt + 1 viz_cnt = viz_cnt + 1
if save_files: if save_files:
fn = "map_layers/" + name_list[i] + "_inac_data_" + file_id + ".csv" if save_to_folder:
np.savetxt(fn, inac_bin_map, delimiter=",", fmt='%f') fn = "map_layers\\" + case_name + "\\" + name_list[i] + "_inac_data_" + file_id + ".csv"
np.savetxt(fn, inac_bin_map, delimiter=",", fmt='%f')
else:
fn = "map_layers\\" + name_list[i] + "_inac_data_" + file_id + ".csv"
np.savetxt(fn, inac_bin_map, delimiter=",", fmt='%f')
viz_map[:, :, viz_cnt] = bin_map viz_map[:, :, viz_cnt] = bin_map
viz_cnt = viz_cnt + 1 viz_cnt = viz_cnt + 1
if save_files: if save_files:
fn = "map_layers/"+name_list[i]+"_data_"+file_id+".csv" if save_to_folder:
np.savetxt(fn,bin_map,delimiter=",", fmt='%f') fn = "map_layers\\" + case_name + "\\" + name_list[i]+"_data_"+file_id+".csv"
np.savetxt(fn,bin_map,delimiter=",", fmt='%f')
else:
fn = "map_layers\\" + name_list[i]+"_data_"+file_id+".csv"
np.savetxt(fn,bin_map,delimiter=",", fmt='%f')
# save terrain as csv file (this method is pretty slow, but can compensate with interp) # save terrain as csv file (this method is pretty slow, but can compensate with interp)
[e,e_interp,x,y,data,ll_pt] = get_terrain_map(lat_lon=anchor_point, [e,e_interp,x,y,data,ll_pt] = get_terrain_map(lat_lon=anchor_point,
...@@ -253,10 +270,13 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file ...@@ -253,10 +270,13 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file
extent = extent, extent = extent,
heading = -heading) # because flipping heading = -heading) # because flipping
elv_filename = "map_layers\\elv_data_"+file_id+".csv"
if save_files: if save_files:
np.savetxt(elv_filename,e_interp,delimiter=",", fmt='%f') if save_to_folder:
elv_filename = "map_layers\\" + case_name + "\\elv_data_" + file_id + ".csv"
np.savetxt(elv_filename,e_interp,delimiter=",", fmt='%f')
else:
elv_filename = "map_layers\\elv_data_" + file_id + ".csv"
np.savetxt(elv_filename,e_interp,delimiter=",", fmt='%f')
if plot_data: if plot_data:
plt.imshow(e_interp) plt.imshow(e_interp)
...@@ -282,33 +302,137 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file ...@@ -282,33 +302,137 @@ def grab_features(anchor_point, extent, sample_dist = 10, heading = 0, save_file
if __name__ == "__main__": if __name__ == "__main__":
ics = [ ics = [
[38.29288, -78.65848, 'BrownMtn_hiker'], # [38.29288, -78.65848, 'brownmountain'],
[38.44706, -78.46993, 'DevilsDitch_hikers'], # [38.44706, -78.46993, 'devilsditch'],
[37.67752, -79.33887, 'Punchbowl_hiker'], # [37.67752, -79.33887, 'punchbowl'],
[37.99092, -78.52798, 'BiscuitRun_hikers'], # [37.99092, -78.52798, 'biscuitrun'],
[38.24969, -78.39555, 'Quinque_dementia'], # [37.82520, -79.081910, 'priest'] ,
[38.20656, -78.67878, 'BrownsCove'], # [34.12751, -116.93247, 'sanbernardino'] ,
[38.02723, -78.45076, 'Charlottesville_dementia'], [31.92245, -109.9673,'[31.92245, -109.9673]'],
[34.12751, -116.93247, 'SanBernardinoPeak'] , [31.9024, -109.2785,'[31.9024, -109.2785]'],
[31.42903, -110.2933,'[31.42903, -110.2933]'],
[34.55, -111.6333,'[34.55, -111.6333]'],
[34.6, -112.55,'[34.6, -112.55]'],
[34.82167, -111.8067,'[34.82167, -111.8067]'],
[33.3975, -111.3478,'[33.3975, -111.3478]'],
[33.70542, -111.338,'[33.70542, -111.338]'],
[31.39708, -111.2064,'[31.39708, -111.2064]'],
[32.4075, -110.825,'[32.4075, -110.825]'],
[34.89333, -111.8633,'[34.89333, -111.8633]'],
[34.94833, -111.795,'[34.94833, -111.795]'],
[31.72262, -110.1878,'[31.72262, -110.1878]'],
[33.39733, -111.348,'[33.39733, -111.348]'],
[34.63042, -112.5553,'[34.63042, -112.5553]'],
[34.55977, -111.6539,'[34.55977, -111.6539]'],
[34.90287, -111.8131,'[34.90287, -111.8131]'],
[34.86667, -111.8833,'[34.86667, -111.8833]'],
[32.43543, -110.7893,'[32.43543, -110.7893]'],
[32.40917, -110.7098,'[32.40917, -110.7098]'],
[35.33068, -111.7111,'[35.33068, -111.7111]'],
[32.01237, -109.3157,'[32.01237, -109.3157]'],
[31.85073, -109.4219,'[31.85073, -109.4219]'],
[34.88683, -111.784,'[34.88683, -111.784]'],
[32.41977, -110.7473,'[32.41977, -110.7473]'],
[33.60398, -112.5151,'[33.60398, -112.5151]'],
[33.3968, -111.3481,'[33.3968, -111.3481]'],
[33.52603, -111.3905,'[33.52603, -111.3905]'],
[32.33333, -110.8528,'[32.33333, -110.8528]'],
[32.33583, -110.9102,'[32.33583, -110.9102]'],
[32.337, -110.9167,'[32.337, -110.9167]'],
[35.08133, -111.0711,'[35.08133, -111.0711]'],
[33.25, -113.5093,'[33.25, -113.5093]'],
[31.50572, -110.6762,'[31.50572, -110.6762]'],
[34.91667, -111.8,'[34.91667, -111.8]'],
[35.1938, -114.057,'[35.1938, -114.057]'],
[33.39715, -111.3479,'[33.39715, -111.3479]'],
[33.37055, -111.1152,'[33.37055, -111.1152]'],
[34.0927, -111.4246,'[34.0927, -111.4246]'],
[31.83522, -110.3567,'[31.83522, -110.3567]'],
[35.24375, -111.5997,'[35.24375, -111.5997]'],
[34.82513, -111.7875,'[34.82513, -111.7875]'],
[33.39705, -111.3479,'[33.39705, -111.3479]'],
[33.38885, -111.3657,'[33.38885, -111.3657]'],
[32.82142, -111.2021,'[32.82142, -111.2021]'],
[34.97868, -111.8964,'[34.97868, -111.8964]'],
[33.47802, -111.4377,'[33.47802, -111.4377]'],
[34.82387, -111.7751,'[34.82387, -111.7751]'],
[34.9253, -111.7341,'[34.9253, -111.7341]'],
[34.09278, -111.421,'[34.09278, -111.421]'],
[36.23878, -112.6892,'[36.23878, -112.6892]'],
[31.33447, -109.8186,'[31.33447, -109.8186]'],
[36.37473, -106.6795,'[36.37473, -106.6795]'],
[42.02893, -74.33659,'[42.02893, -74.33659]'],
[41.54819, -80.33056,'[41.54819, -80.33056]'],
[42.0097, -74.42595,'[42.0097, -74.42595]'],
[42.17965, -74.21362,'[42.17965, -74.21362]'],
[42.55121, -73.4874,'[42.55121, -73.4874]'],
[42.01362, -80.35002,'[42.01362, -80.35002]'],
[42.74271, -73.45475,'[42.74271, -73.45475]'],
[42.1549, -74.20523,'[42.1549, -74.20523]'],
[42.90324, -73.8047,'[42.90324, -73.8047]'],
[44.16065, -73.85545,'[44.16065, -73.85545]'],
[43.42736, -74.4481,'[43.42736, -74.4481]'],
[44.18, -72.99531,'[44.18, -72.99531]'],
[43.52022, -73.59601,'[43.52022, -73.59601]'],
[44.12531, -73.78635,'[44.12531, -73.78635]'],
[43.73413, -74.25577,'[43.73413, -74.25577]'],
[43.06902, -74.48481,'[43.06902, -74.48481]'],
[43.8756, -74.43076,'[43.8756, -74.43076]'],
[43.41544, -74.4148,'[43.41544, -74.4148]'],
[43.42473, -73.73209,'[43.42473, -73.73209]'],
[43.59779, -74.55354,'[43.59779, -74.55354]'],
[43.4449, -74.4086,'[43.4449, -74.4086]'],
[43.4332, -74.41433,'[43.4332, -74.41433]'],
[43.4539, -74.52317,'[43.4539, -74.52317]'],
[43.63354, -74.55927,'[43.63354, -74.55927]'],
[44.19204, -74.26329,'[44.19204, -74.26329]'],
[44.31349, -74.56818,'[44.31349, -74.56818]'],
[43.42498, -74.41496,'[43.42498, -74.41496]'],
[43.33195, -74.49095,'[43.33195, -74.49095]'],
[43.95385, -75.15748,'[43.95385, -75.15748]'],
[44.12993, -74.58844,'[44.12993, -74.58844]'],
[44.28656, -74.61429,'[44.28656, -74.61429]'],
[43.51063, -74.57393,'[43.51063, -74.57393]'],
[44.19013, -74.81336,'[44.19013, -74.81336]'],
[43.65649, -76.00019,'[43.65649, -76.00019]'],
[42.42501, -76.47478,'[42.42501, -76.47478]'],
[42.31735, -76.47791,'[42.31735, -76.47791]'],
[42.34432, -77.47638,'[42.34432, -77.47638]'],
[42.25618, -77.78988,'[42.25618, -77.78988]'],
[42.39831, -72.88675,'[42.39831, -72.88675]'],
[48.1103, -121.4917,'[48.1103, -121.4917]'],
[48.64606, -122.4247,'[48.64606, -122.4247]']
] ]
base_dir = 'C:/Users/Larkin/ags_grabber' base_dir = 'C:/Users/Larkin/ags_grabber'
# for item in ics:
# try:
# os.mkdir(base_dir + '/map_layers/' + item[2])
# except FileExistsError:
# pass
#
eng = matlab.engine.start_matlab() # engine for running matlab eng = matlab.engine.start_matlab() # engine for running matlab
for i,ics_pt in enumerate(ics): for i,ics_pt in enumerate(ics):
# try:
# os.mkdir(base_dir + '/map_layers/' + str(ics_pt[2]))
# except FileExistsError:
# pass
anchor_point = [float(ics_pt[0]), float(ics_pt[1])] anchor_point = [float(ics_pt[0]), float(ics_pt[1])]
extent = 20e3 extent = 20e3
save_flag = True save_flag = True
plot_flag = False plot_flag = False
file_extension = 'temp' file_extension = ''
sample_dist = int(extent/100) sample_dist = int(extent/100)
heading = 0 heading = 0
start_time = time.time() start_time = time.time()
grab_features(anchor_point = anchor_point, extent = extent, sample_dist = sample_dist, grab_features(anchor_point = anchor_point, extent = extent, sample_dist = sample_dist, case_name = str(ics_pt[2]),
heading = heading, save_files = save_flag, file_id = file_extension, plot_data = plot_flag) heading = heading, save_files = save_flag, save_to_folder = False, file_id = file_extension, plot_data = plot_flag)
time.sleep(1) # wait for... files to settle? time.sleep(1) # wait for... files to settle?
# run matlab # run matlab
......
importmap_py.m
View file @ 7ccb785e
...@@ -27,16 +27,29 @@ function result = importmap_py(save_filename, basedir) ...@@ -27,16 +27,29 @@ function result = importmap_py(save_filename, basedir)
% fnamelbd = 'C:\\Users\\Larkin\\ags_grabber\\map_layers\\lakes_data_temp.csv'; % fnamelbd = 'C:\\Users\\Larkin\\ags_grabber\\map_layers\\lakes_data_temp.csv';
% fnamelin = 'C:\\Users\\Larkin\\ags_grabber\\map_layers\\lakes_inac_data_temp.csv'; % fnamelin = 'C:\\Users\\Larkin\\ags_grabber\\map_layers\\lakes_inac_data_temp.csv';
fnameelev = strjoin({basedir, '/map_layers/elv_data_temp.csv'},''); %fnameelev = strjoin({basedir, '/map_layers/',save_filename,'/elv_data_.csv'},'');
fnameriv = strjoin({basedir, '/map_layers/rivers_data_temp.csv'},''); %fnameriv = strjoin({basedir, '/map_layers/',save_filename,'/rivers_data_.csv'},'');
fnamerivbd = strjoin({basedir, '/map_layers/rivers_bdd_data_temp.csv'},''); %fnamerivbd = strjoin({basedir, '/map_layers/',save_filename,'/rivers_bdd_data_.csv'},'');
fnamerivin = strjoin({basedir, '/map_layers/rivers_bdd_inac_data_temp.csv'},''); %fnamerivin = strjoin({basedir, '/map_layers/',save_filename,'/rivers_bdd_inac_data_.csv'},'');
fnameroad = strjoin({basedir, '/map_layers/roads_data_temp.csv'},''); %fnameroad = strjoin({basedir, '/map_layers/',save_filename,'/roads_data_.csv'},'');
fnamerr = strjoin({basedir, '/map_layers/railroads_data_temp.csv'},''); %fnamerr = strjoin({basedir, '/map_layers/',save_filename,'/railroads_data_.csv'},'');
fnamep = strjoin({basedir, '/map_layers/powerlines_data_temp.csv'},''); %fnamep = strjoin({basedir, '/map_layers/',save_filename,'/powerlines_data_.csv'},'');
fnamelbd = strjoin({basedir, '/map_layers/lakes_data_temp.csv'},''); %fnamelbd = strjoin({basedir, '/map_layers/',save_filename,'/lakes_data_.csv'},'');
fnamelin = strjoin({basedir, '/map_layers/lakes_inac_data_temp.csv'},''); %fnamelin = strjoin({basedir, '/map_layers/',save_filename,'/lakes_inac_data_.csv'},'');
fnametr = strjoin({basedir, '/map_layers/trails_data_temp.csv'},''); %fnametr = strjoin({basedir, '/map_layers/',save_filename,'/trails_data_.csv'},'');
fnameelev = strjoin({basedir, '/map_layers','/elv_data_.csv'},'');
fnameriv = strjoin({basedir, '/map_layers','/rivers_data_.csv'},'');
fnamerivbd = strjoin({basedir, '/map_layers','/rivers_bdd_data_.csv'},'');
fnamerivin = strjoin({basedir, '/map_layers','/rivers_bdd_inac_data_.csv'},'');
fnameroad = strjoin({basedir, '/map_layers','/roads_data_.csv'},'');
fnamerr = strjoin({basedir, '/map_layers','/railroads_data_.csv'},'');
fnamep = strjoin({basedir, '/map_layers','/powerlines_data_.csv'},'');
fnamelbd = strjoin({basedir, '/map_layers','/lakes_data_.csv'},'');
fnamelin = strjoin({basedir, '/map_layers','/lakes_inac_data_.csv'},'');
fnametr = strjoin({basedir, '/map_layers','/trails_data_.csv'},'');
Zelev = load(fnameelev); Zelev = load(fnameelev);
BWriver = load(fnameriv); BWriver = load(fnameriv);
......
lat_lon_limits.txt 0 → 100644
View file @ 7ccb785e
lat lon points at the cornerns of each map, points are listed starting with the lower left-hand corner and wrapping around the square in the ccw direction
punchbowl
(37.60638757329171, -79.42870152841193)
(37.60638757329171, -79.24903847158804)
(37.74858429321619, -79.24903847158804)
(37.74858429321619, -79.42870152841193)
-----------------
brownmountain
(38.22234117764744, -78.74831152841195)
(38.22234117764744, -78.56864847158805)
(38.36335032216281, -78.56864847158805)
(38.36335032216281, -78.74831152841195)
-----------------
devilsditch
(38.37667118597197, -78.55976152841195)
(38.37667118597197, -78.38009847158806)
(38.51738022690628, -78.38009847158806)
(38.51738022690628, -78.55976152841195)
-----------------
biscuitrun
(37.920088870781036, -78.61781152841195)
(37.920088870781036, -78.43814847158804)
(38.06168280503042, -78.43814847158804)
(38.06168280503042, -78.61781152841195)
-----------------
priest
(37.75420928537992, -79.17174152841194)
(37.75420928537992, -78.99207847158804)
(37.89612249025089, -78.99207847158804)
(37.89612249025089, -79.17174152841194)
-----------------
sanbernardino
(34.05311557052717, -117.02230152841194)
(34.05311557052717, -116.84263847158803)
(34.20183901911491, -116.84263847158803)
(34.20183901911491, -117.02230152841194)
-----------------
\ No newline at end of file
punchbowl_track_meters.csv deleted 100644 → 0
View file @ 35708bd0
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track_converter.py
View file @ 7ccb785e
...@@ -4,38 +4,46 @@ import csv ...@@ -4,38 +4,46 @@ import csv
import numpy as np import numpy as np
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
with open("C:\\Users\\Larkin\\ags_grabber\\DevilsDitch_hikers.csv") as f: # params = [37.67752, -79.33887, 'punchbowl']
reader = csv.reader(f, delimiter=',') # # params = [38.29288, -78.65848, 'brownmountain']
headers = next(reader) # # params = [38.44706, -78.46993, 'devilsditch']
data = list(reader) # # params = [37.99092, -78.52798, 'biscuitrun']
# # params = [37.82520, -79.081910, 'priest']
# plot each track based on order column # # params = [34.12751, -116.93247, 'sanbernardino']
done = False #
last_idx = 0 # with open("C:\\Users\\Larkin\\ags_grabber\\track_temp.csv") as f:
start_idx = 0 # reader = csv.reader(f, delimiter=',')
# data = []
ap = [38.44706, -78.46993] # for row in reader:
ap_meters = lat_lon2meters(ap[0], ap[1]) # if any(x.strip() for x in row):
# data.append(row)
# track = np.array(data).astype(np.float)
#
# ap_meters = lat_lon2meters(params[0], params[1])
extent = 20e3 extent = 20e3
scale_factor = 3/20 # factor to get 6.66667m mapping from 1m mapping (1/6.6667) scale_factor = 3/20 # factor to get 6.66667m mapping from 1m mapping (1/6.6667)
#
order = [np.int(d[0]) for d in data] # order column # xy = lat_lon2meters(track[:,1], track[:,0])
lat_lon = np.array([[np.float(d[1]), np.float(d[2])] for d in data]) #
# x_pts = (np.array(xy[0]) - (ap_meters[0] - (extent/2)))*scale_factor # reduces number of interpolants
for i in range(order.count(1)): # y_pts = (np.array(xy[1]) - (ap_meters[1] - (extent/2)))*scale_factor
if i == order.count(1)-1: # last iterations #
xy = lat_lon2meters(lat_lon[start_idx:,0], lat_lon[start_idx:,1]) # np.savetxt(params[2] + '_track_meters.csv',np.array([x_pts, y_pts]),delimiter=",", fmt='%f')
plt.plot(xy[0],xy[1]) # plt.plot(x_pts, y_pts)
# plt.show()
x_pts = (np.array(xy[0]) - (ap_meters[0] - (extent/2)))*scale_factor # reduces number of interpolants
y_pts = (np.array(xy[1]) - (ap_meters[1] - (extent/2)))*scale_factor points = [[37.67752, -79.33887, 'punchbowl'],
[38.29288, -78.65848, 'brownmountain'],
np.savetxt('devilsditch_track_meters.csv',np.array([x_pts, y_pts]),delimiter=",", fmt='%f') [38.44706, -78.46993, 'devilsditch'],
else: [37.99092, -78.52798, 'biscuitrun'],
last_idx = order.index(1,last_idx+1) [37.82520, -79.081910, 'priest'],
xy = lat_lon2meters(lat_lon[start_idx:last_idx,0], lat_lon[start_idx:last_idx,1]) [34.12751, -116.93247, 'sanbernardino']]
plt.plot(xy[0],xy[1])
start_idx = last_idx for pt in points:
# plt.show() pt_meters = lat_lon2meters(pt[0], pt[1])
# print(len(xy[0])) print(pt[2])
print(meters2lat_lon(pt_meters[0] - extent/2, pt_meters[1] - extent/2))
print(meters2lat_lon(pt_meters[0] + extent/2, pt_meters[1] - extent/2))
print(meters2lat_lon(pt_meters[0] + extent/2, pt_meters[1] + extent/2))
print(meters2lat_lon(pt_meters[0] - extent/2, pt_meters[1] + extent/2))
print("-----------------")
\ No newline at end of file
track_temp.csv 0 → 100644
View file @ 7ccb785e
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