commit
dbee7b09a7
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@ -0,0 +1 @@
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/__pycache__
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@ -1,3 +0,0 @@
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# Default ignored files
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/shelf/
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/workspace.xml
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23
astar.py
23
astar.py
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@ -36,26 +36,3 @@ def astar(istate, goalx, goaly, passedFields):
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element.priority = value.priority
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return False
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# def bfs(istate, goalx, goaly, passedFields):
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# fringe = [istate]
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# explored = []
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# steps = []
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# while fringe:
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# state = fringe.pop(0)
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# if state.xpos == goalx and state.ypos == goaly:
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# steps.insert(0, state)
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# while (state.parent != None):
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# state = state.parent
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# steps.insert(0, state)
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# return steps
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# element = successors(state, passedFields)
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# explored.append((state.xpos, state.ypos, state.orientation))
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# for value in element:
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# val = (value.xpos, value.ypos, value.orientation)
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# if val not in explored and value not in fringe:
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# fringe.append(value)
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# return False
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@ -0,0 +1,105 @@
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digraph Tree {
|
||||
node [shape=box, fontname="helvetica"] ;
|
||||
edge [fontname="helvetica"] ;
|
||||
0 [label="distance <= 14.5\ngini = 0.484\nsamples = 200\nvalue = [118, 82]\nclass = collect"] ;
|
||||
1 [label="paid_on_time <= 0.5\ngini = 0.437\nsamples = 93\nvalue = [30, 63]\nclass = no-collect"] ;
|
||||
0 -> 1 [labeldistance=2.5, labelangle=45, headlabel="True"] ;
|
||||
2 [label="gini = 0.0\nsamples = 9\nvalue = [9, 0]\nclass = collect"] ;
|
||||
1 -> 2 ;
|
||||
3 [label="fuel <= 1508.0\ngini = 0.375\nsamples = 84\nvalue = [21, 63]\nclass = no-collect"] ;
|
||||
1 -> 3 ;
|
||||
4 [label="gini = 0.0\nsamples = 7\nvalue = [7, 0]\nclass = collect"] ;
|
||||
3 -> 4 ;
|
||||
5 [label="space_occupied <= 0.856\ngini = 0.298\nsamples = 77\nvalue = [14, 63]\nclass = no-collect"] ;
|
||||
3 -> 5 ;
|
||||
6 [label="days_since_last_collection <= 4.5\ngini = 0.187\nsamples = 67\nvalue = [7, 60]\nclass = no-collect"] ;
|
||||
5 -> 6 ;
|
||||
7 [label="fuel <= 11519.5\ngini = 0.48\nsamples = 5\nvalue = [3, 2]\nclass = collect"] ;
|
||||
6 -> 7 ;
|
||||
8 [label="gini = 0.0\nsamples = 3\nvalue = [3, 0]\nclass = collect"] ;
|
||||
7 -> 8 ;
|
||||
9 [label="gini = 0.0\nsamples = 2\nvalue = [0, 2]\nclass = no-collect"] ;
|
||||
7 -> 9 ;
|
||||
10 [label="fuel <= 16955.0\ngini = 0.121\nsamples = 62\nvalue = [4, 58]\nclass = no-collect"] ;
|
||||
6 -> 10 ;
|
||||
11 [label="garbage_weight <= 0.612\ngini = 0.094\nsamples = 61\nvalue = [3, 58]\nclass = no-collect"] ;
|
||||
10 -> 11 ;
|
||||
12 [label="distance <= 10.5\ngini = 0.5\nsamples = 2\nvalue = [1, 1]\nclass = collect"] ;
|
||||
11 -> 12 ;
|
||||
13 [label="gini = 0.0\nsamples = 1\nvalue = [1, 0]\nclass = collect"] ;
|
||||
12 -> 13 ;
|
||||
14 [label="gini = 0.0\nsamples = 1\nvalue = [0, 1]\nclass = no-collect"] ;
|
||||
12 -> 14 ;
|
||||
15 [label="garbage_type <= 2.5\ngini = 0.065\nsamples = 59\nvalue = [2, 57]\nclass = no-collect"] ;
|
||||
11 -> 15 ;
|
||||
16 [label="gini = 0.0\nsamples = 46\nvalue = [0, 46]\nclass = no-collect"] ;
|
||||
15 -> 16 ;
|
||||
17 [label="garbage_weight <= 15.925\ngini = 0.26\nsamples = 13\nvalue = [2, 11]\nclass = no-collect"] ;
|
||||
15 -> 17 ;
|
||||
18 [label="odour_intensity <= 5.724\ngini = 0.444\nsamples = 3\nvalue = [2, 1]\nclass = collect"] ;
|
||||
17 -> 18 ;
|
||||
19 [label="gini = 0.0\nsamples = 2\nvalue = [2, 0]\nclass = collect"] ;
|
||||
18 -> 19 ;
|
||||
20 [label="gini = 0.0\nsamples = 1\nvalue = [0, 1]\nclass = no-collect"] ;
|
||||
18 -> 20 ;
|
||||
21 [label="gini = 0.0\nsamples = 10\nvalue = [0, 10]\nclass = no-collect"] ;
|
||||
17 -> 21 ;
|
||||
22 [label="gini = 0.0\nsamples = 1\nvalue = [1, 0]\nclass = collect"] ;
|
||||
10 -> 22 ;
|
||||
23 [label="garbage_type <= 1.0\ngini = 0.42\nsamples = 10\nvalue = [7, 3]\nclass = collect"] ;
|
||||
5 -> 23 ;
|
||||
24 [label="gini = 0.0\nsamples = 2\nvalue = [0, 2]\nclass = no-collect"] ;
|
||||
23 -> 24 ;
|
||||
25 [label="odour_intensity <= 8.841\ngini = 0.219\nsamples = 8\nvalue = [7, 1]\nclass = collect"] ;
|
||||
23 -> 25 ;
|
||||
26 [label="gini = 0.0\nsamples = 6\nvalue = [6, 0]\nclass = collect"] ;
|
||||
25 -> 26 ;
|
||||
27 [label="space_occupied <= 0.936\ngini = 0.5\nsamples = 2\nvalue = [1, 1]\nclass = collect"] ;
|
||||
25 -> 27 ;
|
||||
28 [label="gini = 0.0\nsamples = 1\nvalue = [0, 1]\nclass = no-collect"] ;
|
||||
27 -> 28 ;
|
||||
29 [label="gini = 0.0\nsamples = 1\nvalue = [1, 0]\nclass = collect"] ;
|
||||
27 -> 29 ;
|
||||
30 [label="odour_intensity <= 7.156\ngini = 0.292\nsamples = 107\nvalue = [88, 19]\nclass = collect"] ;
|
||||
0 -> 30 [labeldistance=2.5, labelangle=-45, headlabel="False"] ;
|
||||
31 [label="garbage_weight <= 49.659\ngini = 0.116\nsamples = 81\nvalue = [76, 5]\nclass = collect"] ;
|
||||
30 -> 31 ;
|
||||
32 [label="days_since_last_collection <= 24.5\ngini = 0.095\nsamples = 80\nvalue = [76, 4]\nclass = collect"] ;
|
||||
31 -> 32 ;
|
||||
33 [label="gini = 0.0\nsamples = 65\nvalue = [65, 0]\nclass = collect"] ;
|
||||
32 -> 33 ;
|
||||
34 [label="distance <= 19.0\ngini = 0.391\nsamples = 15\nvalue = [11, 4]\nclass = collect"] ;
|
||||
32 -> 34 ;
|
||||
35 [label="fuel <= 6122.0\ngini = 0.444\nsamples = 6\nvalue = [2, 4]\nclass = no-collect"] ;
|
||||
34 -> 35 ;
|
||||
36 [label="gini = 0.0\nsamples = 2\nvalue = [2, 0]\nclass = collect"] ;
|
||||
35 -> 36 ;
|
||||
37 [label="gini = 0.0\nsamples = 4\nvalue = [0, 4]\nclass = no-collect"] ;
|
||||
35 -> 37 ;
|
||||
38 [label="gini = 0.0\nsamples = 9\nvalue = [9, 0]\nclass = collect"] ;
|
||||
34 -> 38 ;
|
||||
39 [label="gini = 0.0\nsamples = 1\nvalue = [0, 1]\nclass = no-collect"] ;
|
||||
31 -> 39 ;
|
||||
40 [label="days_since_last_collection <= 13.5\ngini = 0.497\nsamples = 26\nvalue = [12, 14]\nclass = no-collect"] ;
|
||||
30 -> 40 ;
|
||||
41 [label="gini = 0.0\nsamples = 8\nvalue = [8, 0]\nclass = collect"] ;
|
||||
40 -> 41 ;
|
||||
42 [label="distance <= 20.0\ngini = 0.346\nsamples = 18\nvalue = [4, 14]\nclass = no-collect"] ;
|
||||
40 -> 42 ;
|
||||
43 [label="gini = 0.0\nsamples = 8\nvalue = [0, 8]\nclass = no-collect"] ;
|
||||
42 -> 43 ;
|
||||
44 [label="days_since_last_collection <= 20.0\ngini = 0.48\nsamples = 10\nvalue = [4, 6]\nclass = no-collect"] ;
|
||||
42 -> 44 ;
|
||||
45 [label="gini = 0.0\nsamples = 2\nvalue = [2, 0]\nclass = collect"] ;
|
||||
44 -> 45 ;
|
||||
46 [label="paid_on_time <= 0.5\ngini = 0.375\nsamples = 8\nvalue = [2, 6]\nclass = no-collect"] ;
|
||||
44 -> 46 ;
|
||||
47 [label="gini = 0.0\nsamples = 1\nvalue = [1, 0]\nclass = collect"] ;
|
||||
46 -> 47 ;
|
||||
48 [label="space_occupied <= 0.243\ngini = 0.245\nsamples = 7\nvalue = [1, 6]\nclass = no-collect"] ;
|
||||
46 -> 48 ;
|
||||
49 [label="gini = 0.0\nsamples = 1\nvalue = [1, 0]\nclass = collect"] ;
|
||||
48 -> 49 ;
|
||||
50 [label="gini = 0.0\nsamples = 6\nvalue = [0, 6]\nclass = no-collect"] ;
|
||||
48 -> 50 ;
|
||||
}
|
||||
Binary file not shown.
|
|
@ -0,0 +1,201 @@
|
|||
garbage_type,fuel,distance,space_occupied,days_since_last_collection,paid_on_time,odour_intensity,garbage_weight,collect
|
||||
recyclable,6858,1,0.38943502197015845,29,True,6.28805984614285,31.096305244645166,True
|
||||
bio,8383,21,0.9783983457146607,14,True,6.707753087002224,20.60776725387002,False
|
||||
mixed,16767,15,0.41993855549014525,4,False,5.463860044558358,30.805902479603375,False
|
||||
mixed,4618,8,0.025718378803866293,7,True,7.861619200083265,14.1759921868727,True
|
||||
mixed,3749,29,0.6874398304046323,27,True,4.716734486018472,47.37291145202405,False
|
||||
mixed,6893,2,0.3001510840581795,8,True,3.878888089004194,19.996360389397914,True
|
||||
electronics,14924,1,0.7997366072420831,24,True,5.973094339762372,2.1960136215621597,True
|
||||
bio,7970,13,0.31037944811473195,26,True,5.391145637081767,39.14660991818736,True
|
||||
electronics,7566,7,0.044065498651120305,4,True,2.52686741420688,3.783918766707756,False
|
||||
recyclable,13581,11,0.3029291371776017,15,True,7.985626019620043,5.327771280989707,True
|
||||
mixed,16818,8,0.878067948875321,13,True,4.014134116482834,1.7349754412586627,False
|
||||
bio,16881,30,0.8470777393096841,14,True,0.1508008943936856,9.66913380182971,False
|
||||
mixed,6990,10,0.7003280893926476,12,True,8.128384270607079,4.676920620947417,True
|
||||
electronics,14086,30,0.2182437464175937,3,True,1.766466032409443,49.43307520335931,False
|
||||
recyclable,3389,10,0.8579499065505017,19,True,3.247657682340906,45.78622737374704,False
|
||||
electronics,6057,16,0.589008682632531,27,True,5.010436042547771,23.589036188265304,False
|
||||
electronics,10251,7,0.11552896376668076,15,True,3.380450749316256,22.243992634560716,True
|
||||
mixed,16614,14,0.2444832090788266,16,True,6.015757811660775,12.110210730052446,True
|
||||
mixed,8603,25,0.16671039135639254,12,True,2.0426316125825617,47.053226873037204,False
|
||||
electronics,2343,16,0.0019177537789323296,4,True,2.353885718716456,4.0522152593080785,False
|
||||
mixed,9279,3,0.46016405802400917,12,True,6.9289984673929452,24.15422401013634,True
|
||||
bio,15621,10,0.3233247817672673,5,True,8.466791831736632,23.608920139906314,True
|
||||
bio,11780,15,0.003124570102083446,16,True,7.747913539805339,49.29577415013314,True
|
||||
recyclable,15224,4,0.03393311087464668,11,True,5.780151215389308,42.38594368650846,True
|
||||
recyclable,535,14,0.4776940289436078,0,True,8.494877610224057,23.248207177875784,False
|
||||
electronics,15007,23,0.7631342797146662,10,True,0.1793546216957731,41.32221567095075,False
|
||||
electronics,13535,9,0.7002708517558823,29,True,4.543146377877752,0.3812690587078782,False
|
||||
mixed,12460,7,0.6532804013948539,22,True,8.852004069677973,34.19708152289112,True
|
||||
recyclable,17025,10,0.2111830840475586,11,True,0.8139222112362365,14.761273939229502,False
|
||||
mixed,16885,3,0.0975949844763121,27,True,1.5388814313627621,9.501289389032975,True
|
||||
mixed,14821,25,0.5231352723059987,13,True,3.6950211926323115,19.618546801578105,False
|
||||
recyclable,6723,24,0.08341759172764396,4,True,4.292133714797208,5.9636773580797,False
|
||||
bio,13344,28,0.4054966875913566,7,True,8.155300248287965,2.6431453529897175,False
|
||||
electronics,7067,4,0.18735850162710033,1,True,2.735687662737821,42.52061030278156,False
|
||||
mixed,14883,28,0.8809908906796138,17,True,7.13642752409897,28.984329544863023,False
|
||||
electronics,15327,16,0.8653586203448479,10,True,3.8134989189454647,43.44212224831813,False
|
||||
recyclable,1852,3,0.29161758342646915,27,True,1.845882845057485,37.95248266834494,True
|
||||
mixed,14063,10,0.88735326349903,25,True,9.625440487741033,21.41966124312023,True
|
||||
electronics,4735,18,0.1252510557255211,13,False,8.809939106819362,17.200057730092645,False
|
||||
bio,4092,19,0.7556427499119933,4,True,3.610989402681027,32.038861874477554,False
|
||||
electronics,12823,1,0.7375871558645424,14,True,3.12238343732133,16.67997617867717,True
|
||||
bio,12360,3,0.3865979303090342,13,True,4.448309991392886,9.896631997968996,True
|
||||
recyclable,9995,9,0.6800124218236376,28,True,2.0962119840774807,45.05860783045714,True
|
||||
bio,857,20,0.36392075025020776,25,True,4.4895067182730166,9.406278983853117,False
|
||||
recyclable,10139,26,0.9066040779286622,20,False,0.7309817001963181,14.912659873544886,False
|
||||
mixed,11367,30,0.7257029480054457,12,True,8.296118143388021,30.120689961002995,False
|
||||
bio,2004,22,0.7384839037490499,20,True,1.6610395917967113,37.12329587330876,False
|
||||
bio,13718,9,0.06421815231705275,9,False,8.9060063296501186,32.86630823851767,False
|
||||
mixed,14594,17,0.24593434160148464,1,True,5.507095860755648,21.410155232517504,False
|
||||
mixed,12592,8,0.47050946446896347,17,True,2.4322073604255134,12.82067348792581,True
|
||||
mixed,16059,28,0.7995568646748424,1,True,5.556787942194185,8.789906454780377,False
|
||||
mixed,1210,16,0.9461663853861345,0,True,2.5620254206135806,39.92136033622557,False
|
||||
mixed,12953,18,0.0598916012395212,27,True,2.810396268707139,25.886625456241696,True
|
||||
electronics,17774,25,0.26581024512537343,23,True,2.955583055546205,33.351645476151084,False
|
||||
mixed,13595,23,0.3713870997608135,11,True,1.6069501479828574,43.79700923082427,False
|
||||
mixed,3118,7,0.6936408840161455,28,False,8.669795911175331,49.7583760134488,False
|
||||
recyclable,12193,26,0.969969668681659,3,True,3.756475032068799,41.73283262204557,False
|
||||
electronics,13374,1,0.7678121182374196,7,True,4.95820018411122,9.476031948059054,True
|
||||
mixed,7457,17,0.21293177387216733,26,True,8.202412261856102,0.3829029481382584,True
|
||||
mixed,7398,16,0.49410144025444536,16,True,7.698928135887976,33.24640393208706,True
|
||||
mixed,11939,18,0.04797159785003968,13,False,5.492245453793608,37.36873260877674,False
|
||||
electronics,4744,29,0.05115067774462534,24,True,7.631570324488663,30.754951936967018,False
|
||||
bio,13219,29,0.8591801844097859,28,True,8.850869168838038,37.690349688214006,True
|
||||
mixed,11622,25,0.5067305325569674,7,True,4.6346103758999755,4.704504516207297,False
|
||||
mixed,11692,12,0.17347617422332506,22,True,5.114145437118437,24.395276804323178,True
|
||||
bio,12296,24,0.5799754812241465,14,True,5.929568201554035,20.04153646842107,False
|
||||
mixed,12430,9,0.7943934891555092,2,True,8.688396325515924,12.860980097196428,True
|
||||
mixed,16648,30,0.1354303765809669,22,True,4.446396215536957,24.06405240646432,False
|
||||
mixed,10871,29,0.43478843148386526,27,True,8.90718082268031,35.461520882501006,True
|
||||
recyclable,13541,9,0.45405615353057316,7,True,3.4615446151786844,11.532681978881138,False
|
||||
mixed,9494,14,0.004782166130939736,5,True,9.258834218622681,43.761301608448555,True
|
||||
mixed,7626,18,0.027106139170503862,8,False,6.746581921499086,5.586416737760485,False
|
||||
recyclable,17511,2,0.1687883078260003,2,True,3.533163673996471,9.580063428681257,True
|
||||
mixed,9610,7,0.695059583332655,25,True,2.3401557803901185,2.3705609534927454,True
|
||||
mixed,3040,15,0.1574864696817655,2,True,6.825464319706567,6.814407869306499,False
|
||||
bio,9841,2,0.1895252320742898,26,False,9.889708159437411,44.94835767750827,False
|
||||
bio,6885,10,0.7629703662996873,10,False,4.850662639613831,33.02584201142315,False
|
||||
bio,3487,25,0.4059023944818234,26,True,0.5487554506182057,26.482581038110297,False
|
||||
bio,13124,18,0.3208609348871274,14,True,7.714846611937395,5.336809899885014,True
|
||||
mixed,11532,4,0.9839866498612999,19,True,9.782297099352132,36.47452307128158,False
|
||||
bio,13629,25,0.9255282254327359,18,True,4.768952675438898,21.220696047775256,False
|
||||
electronics,4218,26,0.643899092841499,13,True,6.252405819718647,1.0382261772403756,False
|
||||
bio,10119,27,0.33713760854710817,2,True,8.871634154885593,5.427123034736042,False
|
||||
mixed,14237,18,0.2515135349860018,17,True,2.63435728911785,26.348605217474137,False
|
||||
electronics,12316,23,0.13513972842597843,14,True,3.435826288771592,49.21215054667067,False
|
||||
bio,16469,1,0.9100349749865474,14,True,5.183443706926657,43.99603946668627,True
|
||||
mixed,2254,24,0.22321781629342174,7,True,3.758392411693926,32.078459445867466,False
|
||||
bio,5184,25,0.3726201549710213,12,False,2.3258260841300693,28.930776464888712,False
|
||||
mixed,11992,5,0.37136935114748215,12,False,7.944810878729637,15.764730161260648,False
|
||||
recyclable,14852,17,0.9669504391513694,11,True,4.3814601810147344,42.5325985730309,False
|
||||
mixed,14788,18,0.15747540939044535,23,True,0.8202398859201865,34.287976972812764,False
|
||||
mixed,4127,12,0.5705532308529626,22,True,4.34197948257461475,13.21045335312487,True
|
||||
recyclable,1781,27,0.6119028273203277,27,True,3.832758551729495,20.419268022539832,False
|
||||
recyclable,1961,8,0.050683227336650094,18,True,4.944070899462293,20.316554868079322,True
|
||||
mixed,4065,2,0.2777985173757125,17,True,1.88190772834955,38.44905744099713,True
|
||||
mixed,4028,7,0.08768360859117563,13,True,4.596363030469549,25.390975629302094,True
|
||||
mixed,12667,23,0.7263372730324396,3,True,6.983673440089592,6.3271012844971946,False
|
||||
electronics,902,10,0.0972446120759014,7,True,1.7007332471135728,2.4875140164366094,False
|
||||
mixed,4133,25,0.8863142047204092,26,True,8.86434876905877,23.146736584299048,True
|
||||
mixed,16907,19,0.6413162554313889,14,True,3.931847480053995,21.564811955711722,False
|
||||
electronics,12129,17,0.3255998096481383,21,False,5.834549250003657,24.404139636994316,False
|
||||
recyclable,9388,7,0.18480810633503664,8,True,3.307342994428133,29.47279722274338,True
|
||||
electronics,12282,19,0.787940768129883,3,True,1.9425612340575626,44.338448409498895,False
|
||||
recyclable,16843,18,0.3006615497630535,4,True,0.306619782743337,0.10183018082673412,False
|
||||
mixed,14387,13,0.9070926514128955,3,True,2.42929766024208,11.249774077666292,False
|
||||
electronics,15436,27,0.06941730562384307,26,True,4.5631172094766175,27.34477833807143,False
|
||||
mixed,15465,13,0.08353207908213156,16,False,6.820610862001022,28.32262519003446,False
|
||||
electronics,14811,2,0.3949179382540411,23,True,0.381962545476181,41.11931445912492,True
|
||||
bio,2151,3,0.9129936622264005,22,True,9.17371100015908136,33.74134732997111,True
|
||||
mixed,237,11,0.9964787642547496,25,True,5.211086288207052,16.330679822388745,False
|
||||
mixed,111,22,0.4711301611274815,18,True,8.30571757605114,48.73704630000289,False
|
||||
electronics,4463,18,0.5607936953252097,9,True,5.340209435107365,10.017097722357493,False
|
||||
electronics,15244,3,0.3869275687952053,18,True,3.652817201742993,37.26534729300576,True
|
||||
mixed,11816,29,0.04079719450519703,18,True,7.2327475650423647,11.744528538216914,False
|
||||
mixed,7419,13,0.03779749101113905,15,True,7.672313681492664,5.861975978144901,True
|
||||
electronics,9401,14,0.3103153528084557,26,True,5.2103976136388175,38.08987567003111,True
|
||||
mixed,16276,3,0.479034009007552,27,True,4.651924221072261,10.953743088081447,True
|
||||
mixed,4532,2,0.747513820128898,29,True,0.2586713125686746,19.881947016208546,True
|
||||
mixed,11549,8,0.49394575237900273,6,True,2.5440665374161995,32.4915857099389873,True
|
||||
recyclable,3813,4,0.22880151196725018,6,True,7.220713613387959,46.890649430682544,True
|
||||
bio,17962,18,0.624644549751732,11,False,8.475303217255203,5.3631616817744865,False
|
||||
bio,3940,25,0.8584303157289703,30,True,7.295573469672193,19.75062441304104,True
|
||||
bio,3540,1,0.16268575368033733,13,True,5.880093986834379,13.761791968844527,True
|
||||
recyclable,5461,20,0.9720273624310242,9,True,7.150632586077218,22.90010680963285,False
|
||||
bio,11821,19,0.4890954252362738,5,True,5.243707979141446,34.04257151648786,False
|
||||
bio,4151,13,0.7741603691526736,24,True,8.797747697546043,23.594349450180914,True
|
||||
recyclable,9015,12,0.06465113909613351,16,True,6.820701685767977,0.20513555254460525,True
|
||||
mixed,6611,16,0.6367050551717114,9,True,1.1168941403754773,22.01478968287895,False
|
||||
bio,5523,14,0.7903120332698462,13,True,5.584457456040392,49.05459466627317,True
|
||||
mixed,5789,27,0.9382743640127215,15,True,6.322173697254331,47.602736117018026,False
|
||||
bio,3441,20,0.2704566556023139,9,True,6.034883457792668,5.934602634889502,False
|
||||
bio,12771,17,0.9036479407267245,6,True,4.983318099275128,4.7884656590729495,False
|
||||
mixed,14202,21,0.1829947029669602,19,True,6.351850543526715,49.88486222532098,True
|
||||
electronics,5853,7,0.25211596914266365,19,False,6.04880922544101,44.15037893145479,False
|
||||
bio,1013,28,0.2328958888157674,10,True,5.722313037134815,44.5605489804229,False
|
||||
mixed,4382,25,0.9629592705464354,15,True,0.7262561290537561,49.22062156968296,False
|
||||
electronics,303,15,0.1935869262999148,28,True,4.825010078601935,32.304918866098134,False
|
||||
mixed,11291,3,0.4987501399891241,19,True,7.593017186381552,17.60598885484067,True
|
||||
mixed,228,11,0.7482870715914006,15,True,4.99089814924729,10.43107633070246,False
|
||||
bio,1164,11,0.5377166416978679,22,True,5.107421661337108,14.616108271654959,False
|
||||
mixed,16153,28,0.10319171233491664,9,False,4.403420968891197,2.0814455890390384,False
|
||||
mixed,5727,8,0.6742508678514485,12,True,5.806819175818928,40.39841656773793,True
|
||||
mixed,8684,28,0.28952554683233755,4,True,3.6507840151179174,14.380642477352534,False
|
||||
bio,15036,25,0.3013529193213179,28,True,2.8003869601469213,1.7050484121073906,False
|
||||
electronics,9081,15,0.552743466291092,2,True,3.64259133151227,46.66783990228206,False
|
||||
bio,9195,11,0.39260282046107997,24,True,9.000375724293816,9.358015869334334,True
|
||||
recyclable,8258,17,0.9173355631818932,24,True,5.696271382671787,11.838799672256089,False
|
||||
mixed,5203,16,0.20853652624054675,7,False,7.218874544155853,3.3802787098178633,False
|
||||
mixed,10353,4,0.6612627593282159,12,True,0.8160458268763704,48.21072530277851,True
|
||||
mixed,1801,26,0.1724747032914301,5,True,9.767546930194213,48.306921765049395,False
|
||||
mixed,9787,3,0.12733427196255642,6,True,2.878806668582902,19.141664339310555,True
|
||||
recyclable,3968,8,0.13408211860863806,19,True,7.004806522643715,21.695728722138725,True
|
||||
mixed,14638,26,0.6610180396198244,25,True,5.004704839665123,8.611752981253796,False
|
||||
mixed,8548,17,0.6919756512026707,26,True,8.7096013024813113,47.49247425366768,True
|
||||
mixed,1491,18,0.9820986051525684,9,True,9.258025774670367,15.98094975265509,False
|
||||
recyclable,3668,17,0.7640578172220626,14,True,3.3725194345302,20.997519420207006,False
|
||||
mixed,9787,4,0.4690947509402401,17,True,0.5513818386579639,35.515442456358294,True
|
||||
mixed,11328,16,0.05659862491548939,28,True,6.580525503234329,40.057728572365605,True
|
||||
mixed,4016,27,0.7672970359948862,1,True,0.6970633008301563,45.40712539668869,False
|
||||
bio,235,8,0.1340953149733236,18,True,8.0577551256497664,24.750364306492106,False
|
||||
mixed,4125,11,0.32068177017369326,24,True,2.0819986305961913,30.206075317324398,True
|
||||
mixed,7794,5,0.7237994849277903,20,True,1.182186279436862,15.700974509225196,True
|
||||
electronics,5395,16,0.8055586819904074,24,True,4.031003133386356,23.875466510639743,False
|
||||
mixed,15505,18,0.45203522304151467,17,True,7.160642286283462,45.612740804260326,True
|
||||
electronics,1348,21,0.9644616372108747,25,True,6.634919820603092,46.44550586828582,False
|
||||
mixed,13686,1,0.8528583962138082,5,True,0.6350681726528817,0.8430687396440373,True
|
||||
electronics,13873,30,0.294532542273514,12,True,4.044317910413886,29.99919461949812,False
|
||||
mixed,930,14,0.46484946768172597,23,True,7.293222367859043,17.888778031470803,False
|
||||
recyclable,6370,7,0.3266741326325917,9,True,6.774166929984485,28.671638946376447,True
|
||||
recyclable,13159,18,0.5742087586584416,3,True,2.8310145159793643,40.38310972219153,False
|
||||
recyclable,8149,23,0.4840066004404705,10,True,6.860051045888277,29.211740461959135,False
|
||||
recyclable,396,16,0.504161153047322,22,True,1.1809202381636141,21.642509975194923,False
|
||||
mixed,17012,15,0.36468655494367364,17,True,9.146259705631856,30.88331825323704,True
|
||||
bio,8100,30,0.454702411813268,22,True,9.779578763490457,11.101202564362856,True
|
||||
mixed,8726,9,0.5227832599121376,18,False,8.2472402461143006,23.712317819323303,False
|
||||
mixed,5613,27,0.6288843449715512,13,True,0.48282122404645356,14.460408589324647,False
|
||||
recyclable,13042,1,0.99875193495793,28,True,8.056286187944535,19.768446255164413,False
|
||||
electronics,1873,23,0.7266911060409714,26,True,6.289322618112965,25.655151095201717,False
|
||||
mixed,13898,3,0.6023654342268365,21,False,4.18436411688805,30.68913330956739,False
|
||||
mixed,8500,16,0.3132189683797034,20,True,9.665381836688276,26.531016057140715,True
|
||||
mixed,10609,12,0.7957280975350293,3,True,5.967088403839806,30.980907594987215,False
|
||||
mixed,14060,9,0.8533975340326421,26,True,5.081066967675499,3.5703010248585523,True
|
||||
bio,10428,9,0.12952527618075171,16,True,8.409694306302747,38.25806756331836,True
|
||||
mixed,12129,10,0.16679000401714317,8,True,3.4722510171543055,39.07152515129634,True
|
||||
recyclable,6077,6,0.9688896707567596,1,True,2.2628928125079515,25.143203629333183,False
|
||||
electronics,17942,30,0.9333715534636539,16,True,0.8192317565547003,6.090205324669523,False
|
||||
mixed,12312,1,0.7589005664492561,5,True,5.319612963692009,48.574652948536254,True
|
||||
mixed,10378,25,0.525947228730475,22,True,8.650164549728183,37.47486500747239,True
|
||||
bio,10538,17,0.24441031022066229,25,True,4.9354317996121857,10.573213306548123,True
|
||||
recyclable,6187,16,0.48862304056788397,26,True,2.3657930824249473,37.65868384027124,True
|
||||
mixed,13968,13,0.9178321609964433,0,True,2.9607729258033775,7.084392850555182,False
|
||||
electronics,9805,15,0.17688249183631466,13,True,3.655335256007239,20.687030526697665,False
|
||||
recyclable,8650,11,0.5509231139255383,18,True,4.995396641282026,29.262501847653766,True
|
||||
recyclable,9498,14,0.24820888510715444,16,True,2.752760360379596,3.736430768304949,False
|
||||
mixed,11052,23,0.5825446526885096,13,True,2.625836401148206,19.3834716160646,False
|
||||
bio,16212,23,0.9097101570818567,26,False,9.766445054530736,11.374414855314813,False
|
||||
mixed,8855,6,0.11681132733819222,28,True,7.162264591925456,1.4784965471126454,True
|
||||
mixed,16243,14,0.3066015436426298,11,True,7.527387665529669,27.536003398124848,True
|
||||
mixed,12805,27,0.2980093260554303,12,True,1.2954787682496038,26.763165725254694,False
|
||||
recyclable,8656,28,0.06481336166041907,19,True,7.13282912045492,38.64738564701376,False
|
||||
|
|
|
@ -1,31 +1,38 @@
|
|||
from heuristicfn import heuristicfn
|
||||
|
||||
FIELDWIDTH = 50
|
||||
TURN_FUEL_COST = 10
|
||||
MOVE_FUEL_COST = 200
|
||||
MAX_FUEL = 20000
|
||||
MAX_SPACE = 5
|
||||
MAX_WEIGHT = 200
|
||||
|
||||
class GarbageTank:
|
||||
def __init__(self, volume_capacity, mass_capacity):
|
||||
self.vcapacity = volume_capacity #m^3
|
||||
self.mcapacity = mass_capacity #kg
|
||||
|
||||
class Engine:
|
||||
def __init__(self, power):
|
||||
self.power = power #HP
|
||||
|
||||
class GarbageTruck:
|
||||
def __init__(self, dump_location, fuel_capacity, rect, orientation):
|
||||
self.dump_location = dump_location
|
||||
self.tank = GarbageTank(15, 18000)
|
||||
self.engine = Engine(400)
|
||||
self.fuel = fuel_capacity
|
||||
|
||||
garbage_types = {'bio': 0, 'electronics': 1, 'mixed': 2, 'recyclable': 3}
|
||||
|
||||
def __init__(self, dump_x, dump_y, rect, orientation, request_list: list, clf):
|
||||
self.dump_x = dump_x
|
||||
self.dump_y = dump_y
|
||||
self.fuel = MAX_FUEL
|
||||
self.free_space = MAX_SPACE
|
||||
self.weight_capacity = MAX_WEIGHT
|
||||
self.rect = rect
|
||||
self.orientation = orientation
|
||||
self.houses = [] #lista domów do odwiedzenia
|
||||
self.request_list = request_list #lista domów do odwiedzenia
|
||||
self.clf = clf
|
||||
|
||||
def turn_left(self):
|
||||
self.orientation = (self.orientation - 1) % 4
|
||||
self.fuel -= TURN_FUEL_COST
|
||||
|
||||
def turn_right(self):
|
||||
self.orientation = (self.orientation + 1) % 4
|
||||
self.fuel -= TURN_FUEL_COST
|
||||
|
||||
def forward(self):
|
||||
self.fuel -= MOVE_FUEL_COST
|
||||
if self.orientation == 0:
|
||||
self.rect.x += FIELDWIDTH
|
||||
elif self.orientation == 1:
|
||||
|
|
@ -33,4 +40,48 @@ class GarbageTruck:
|
|||
elif self.orientation == 2:
|
||||
self.rect.x -= FIELDWIDTH
|
||||
else:
|
||||
self.rect.y -= FIELDWIDTH
|
||||
self.rect.y -= FIELDWIDTH
|
||||
|
||||
def next_destination(self):
|
||||
|
||||
for i in range(len(self.request_list)):
|
||||
request = self.request_list[i]
|
||||
|
||||
#nie ma miejsca w zbiorniku lub za ciężkie śmieci
|
||||
if request.volume > self.free_space or request.weight > self.weight_capacity:
|
||||
continue
|
||||
|
||||
#nie straczy paliwa na dojechanie i powrót na wysypisko
|
||||
if heuristicfn(request.x_pos, request.y_pos, self.dump_x, self.dump_y) // 50 * 200 > self.fuel:
|
||||
continue
|
||||
|
||||
|
||||
|
||||
distance = heuristicfn(self.rect.x, self.rect.y, request.x_pos, request.y_pos) // 50
|
||||
|
||||
r = [
|
||||
self.fuel,
|
||||
distance,
|
||||
request.volume,
|
||||
request.last_collection,
|
||||
request.is_paid,
|
||||
request.odour_intensity,
|
||||
request.weight,
|
||||
request.type
|
||||
]
|
||||
if self.clf.predict([r]) == True:
|
||||
self.request_list.pop(i)
|
||||
self.free_space -= request.volume
|
||||
self.weight_capacity -= request.weight
|
||||
return request.x_pos, request.y_pos
|
||||
return self.dump_x, self.dump_y
|
||||
|
||||
|
||||
|
||||
def collect(self):
|
||||
if self.rect.x == self.dump_x and self.rect.y == self.dump_y:
|
||||
self.fuel = MAX_FUEL
|
||||
self.free_space = MAX_SPACE
|
||||
self.weight_capacity = MAX_WEIGHT
|
||||
print(f'agent at ({self.rect.x}, {self.rect.y}); fuel: {self.fuel}; free space: {self.free_space}; weight capacity: {self.weight_capacity}')
|
||||
pass
|
||||
4
home.py
4
home.py
|
|
@ -1,4 +0,0 @@
|
|||
class Home:
|
||||
def __init__(self, coord):
|
||||
self.coord = coord
|
||||
self.collect_request = False
|
||||
|
|
@ -1,8 +0,0 @@
|
|||
class Litter:
|
||||
|
||||
types = ['PAPER', 'GLASS', 'PLASTIC', 'METAL', 'BIO', 'MUNICIPAL', 'ELECTRONICS']
|
||||
|
||||
def __init__(self, type, volume, mass):
|
||||
self.type = type
|
||||
self.volume = volume
|
||||
self.mass = mass
|
||||
72
main.py
72
main.py
|
|
@ -1,10 +1,13 @@
|
|||
import pygame
|
||||
import random
|
||||
from treelearn import treelearn
|
||||
|
||||
|
||||
from astar import astar
|
||||
from state import State
|
||||
import time
|
||||
from garbage_truck import GarbageTruck
|
||||
from heuristicfn import heuristicfn
|
||||
from map import randomize_map
|
||||
|
||||
pygame.init()
|
||||
WIDTH, HEIGHT = 800, 800
|
||||
|
|
@ -12,52 +15,12 @@ window = pygame.display.set_mode((WIDTH, HEIGHT))
|
|||
pygame.display.set_caption("Intelligent Garbage Collector")
|
||||
AGENT_IMG = pygame.image.load("garbage-truck-nbg.png")
|
||||
AGENT = pygame.transform.scale(AGENT_IMG, (50, 50))
|
||||
DIRT_IMG = pygame.image.load("dirt.jpg")
|
||||
DIRT = pygame.transform.scale(DIRT_IMG, (50, 50))
|
||||
GRASS_IMG = pygame.image.load("grass.png")
|
||||
GRASS = pygame.transform.scale(GRASS_IMG, (50, 50))
|
||||
SAND_IMG = pygame.image.load("sand.jpeg")
|
||||
SAND = pygame.transform.scale(SAND_IMG, (50, 50))
|
||||
COBBLE_IMG = pygame.image.load("cobble.jpeg")
|
||||
COBBLE = pygame.transform.scale(COBBLE_IMG, (50, 50))
|
||||
FPS = 10
|
||||
FIELDCOUNT = 16
|
||||
FIELDWIDTH = 50
|
||||
|
||||
|
||||
class Agent:
|
||||
def __init__(self, rect, direction):
|
||||
self.rect = rect
|
||||
self.direction = direction
|
||||
|
||||
|
||||
def randomize_map(): # tworzenie mapy z losowymi polami
|
||||
field_array_1 = []
|
||||
field_array_2 = []
|
||||
field_priority = []
|
||||
for i in range(16):
|
||||
temp_priority = []
|
||||
for j in range(16):
|
||||
if i in (0, 1) and j in (0, 1):
|
||||
field_array_2.append(GRASS)
|
||||
temp_priority.append(1)
|
||||
else:
|
||||
prob = random.uniform(0, 100)
|
||||
if 0 <= prob <= 12:
|
||||
field_array_2.append(COBBLE)
|
||||
temp_priority.append(3)
|
||||
elif 12 < prob <= 24:
|
||||
field_array_2.append(SAND)
|
||||
temp_priority.append(2)
|
||||
else:
|
||||
field_array_2.append(GRASS)
|
||||
temp_priority.append(1)
|
||||
field_array_1.append(field_array_2)
|
||||
field_array_2 = []
|
||||
field_priority.append(temp_priority)
|
||||
return field_array_1, field_priority
|
||||
|
||||
|
||||
GRASS_IMG = pygame.image.load("grass.png")
|
||||
GRASS = pygame.transform.scale(GRASS_IMG, (50, 50))
|
||||
def draw_window(agent, fields, flip):
|
||||
if flip:
|
||||
direction = pygame.transform.flip(AGENT, True, False)
|
||||
|
|
@ -71,21 +34,22 @@ def draw_window(agent, fields, flip):
|
|||
|
||||
|
||||
def main():
|
||||
clf = treelearn()
|
||||
clock = pygame.time.Clock()
|
||||
run = True
|
||||
x, y = [0, 0]
|
||||
agent = GarbageTruck(0, 0, pygame.Rect(x, y, 50, 50), 0) # tworzenie pola dla agenta
|
||||
fields, priority_array = randomize_map()
|
||||
print(priority_array)
|
||||
final_x, final_y = [100, 300]
|
||||
fields, priority_array, request_list = randomize_map()
|
||||
agent = GarbageTruck(0, 0, pygame.Rect(0, 0, 50, 50), 0, request_list, clf) # tworzenie pola dla agenta
|
||||
while run:
|
||||
clock.tick(FPS)
|
||||
for event in pygame.event.get():
|
||||
if event.type == pygame.QUIT:
|
||||
run = False
|
||||
# keys_pressed = pygame.key.get_pressed()
|
||||
draw_window(agent, fields, False) # false = kierunek east (domyslny), true = west
|
||||
steps = astar(State(None, None, x, y, 'E', priority_array[0][0], heuristicfn(x, y, final_x, final_y)), final_x, final_y, priority_array)
|
||||
x, y = agent.next_destination()
|
||||
if x == agent.rect.x and y == agent.rect.y:
|
||||
print('out of jobs')
|
||||
break
|
||||
steps = astar(State(None, None, agent.rect.x, agent.rect.y, agent.orientation, priority_array[agent.rect.x//50][agent.rect.y//50], heuristicfn(agent.rect.x, agent.rect.y, x, y)), x, y, priority_array)
|
||||
for interm in steps:
|
||||
if interm.action == 'LEFT':
|
||||
agent.turn_left()
|
||||
|
|
@ -101,10 +65,12 @@ def main():
|
|||
draw_window(agent, fields, True)
|
||||
else:
|
||||
draw_window(agent, fields, False)
|
||||
time.sleep(0.5)
|
||||
time.sleep(0.3)
|
||||
agent.collect()
|
||||
fields[agent.rect.x//50][agent.rect.y//50] = GRASS
|
||||
priority_array[agent.rect.x//50][agent.rect.y//50] = 1
|
||||
time.sleep(0.5)
|
||||
|
||||
while True:
|
||||
pass
|
||||
|
||||
pygame.quit()
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,44 @@
|
|||
import pygame, random
|
||||
from request import Request
|
||||
|
||||
DIRT_IMG = pygame.image.load("dirt.jpg")
|
||||
DIRT = pygame.transform.scale(DIRT_IMG, (50, 50))
|
||||
GRASS_IMG = pygame.image.load("grass.png")
|
||||
GRASS = pygame.transform.scale(GRASS_IMG, (50, 50))
|
||||
SAND_IMG = pygame.image.load("sand.jpeg")
|
||||
SAND = pygame.transform.scale(SAND_IMG, (50, 50))
|
||||
COBBLE_IMG = pygame.image.load("cobble.jpeg")
|
||||
COBBLE = pygame.transform.scale(COBBLE_IMG, (50, 50))
|
||||
|
||||
def randomize_map(): # tworzenie mapy z losowymi polami
|
||||
request_list = []
|
||||
field_array_1 = []
|
||||
field_array_2 = []
|
||||
field_priority = []
|
||||
for i in range(16):
|
||||
temp_priority = []
|
||||
for j in range(16):
|
||||
if i in (0, 1) and j in (0, 1):
|
||||
field_array_2.append(GRASS)
|
||||
temp_priority.append(1)
|
||||
else:
|
||||
prob = random.uniform(0, 100)
|
||||
if 0 <= prob <= 12:
|
||||
field_array_2.append(COBBLE)
|
||||
temp_priority.append(100)
|
||||
request_list.append(Request(
|
||||
i*50,j*50, #lokacja
|
||||
random.randint(0,3), #typ śmieci
|
||||
random.random(), #objętość śmieci
|
||||
random.randint(0,30), #ostatni odbiór
|
||||
random.randint(0,1), #czy opłacone w terminie
|
||||
random.random() * 10, #intensywność odoru
|
||||
random.random() * 50 #waga śmieci
|
||||
))
|
||||
else:
|
||||
field_array_2.append(GRASS)
|
||||
temp_priority.append(1)
|
||||
field_array_1.append(field_array_2)
|
||||
field_array_2 = []
|
||||
field_priority.append(temp_priority)
|
||||
return field_array_1, field_priority, request_list
|
||||
|
|
@ -0,0 +1,13 @@
|
|||
from dataclasses import dataclass
|
||||
|
||||
@dataclass
|
||||
class Request:
|
||||
def __init__(self, x_pos, y_pos, type, volume, last_collection, is_paid, odour_intensity, weight):
|
||||
self.x_pos = x_pos
|
||||
self.y_pos = y_pos
|
||||
self.type = type
|
||||
self.volume = volume
|
||||
self.last_collection = last_collection
|
||||
self.is_paid = is_paid
|
||||
self.odour_intensity = odour_intensity
|
||||
self.weight = weight
|
||||
32
succ.py
32
succ.py
|
|
@ -5,27 +5,27 @@ FIELDWIDTH, FIELDCOUNT = 50, 16
|
|||
def succ(st: State, passedPriorities, goalx, goaly):
|
||||
successors = []
|
||||
|
||||
if st.orientation == 'N':
|
||||
successors.append(State(st, 'LEFT', st.xpos, st.ypos, 'W', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st, 'RIGHT', st.xpos, st.ypos, 'E', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
if st.orientation == 3:
|
||||
successors.append(State(st, 'LEFT', st.xpos, st.ypos, 2, passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st, 'RIGHT', st.xpos, st.ypos, 0, passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
if st.ypos > 0:
|
||||
successors.append(State(st, 'FORWARD', st.xpos, st.ypos - FIELDWIDTH , 'N', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st, 'FORWARD', st.xpos, st.ypos - FIELDWIDTH , 3, passedPriorities[st.xpos//50][st.ypos//50 - 1], heuristicfn(st.xpos, st.ypos - 50, goalx, goaly)))
|
||||
|
||||
if st.orientation == 'S':
|
||||
successors.append(State(st, 'LEFT', st.xpos, st.ypos, 'E', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st,'RIGHT', st.xpos, st.ypos, 'W', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
if st.orientation == 1:
|
||||
successors.append(State(st, 'LEFT', st.xpos, st.ypos, 0, passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st,'RIGHT', st.xpos, st.ypos, 2, passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
if st.ypos < FIELDWIDTH * (FIELDCOUNT - 1):
|
||||
successors.append(State(st, 'FORWARD', st.xpos, st.ypos + FIELDWIDTH , 'S', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st, 'FORWARD', st.xpos, st.ypos + FIELDWIDTH , 1, passedPriorities[st.xpos//50][st.ypos//50 + 1], heuristicfn(st.xpos, st.ypos + 50, goalx, goaly)))
|
||||
|
||||
if st.orientation == 'W':
|
||||
successors.append(State(st, 'LEFT', st.xpos, st.ypos, 'S', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st,'RIGHT', st.xpos, st.ypos, 'N', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
if st.orientation == 2:
|
||||
successors.append(State(st, 'LEFT', st.xpos, st.ypos, 1, passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st,'RIGHT', st.xpos, st.ypos, 3, passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
if st.xpos > 0:
|
||||
successors.append(State(st, 'FORWARD', st.xpos - FIELDWIDTH , st.ypos, 'W', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st, 'FORWARD', st.xpos - FIELDWIDTH , st.ypos, 2, passedPriorities[st.xpos//50 - 1][st.ypos//50], heuristicfn(st.xpos - 50, st.ypos, goalx, goaly)))
|
||||
|
||||
if st.orientation == 'E':
|
||||
successors.append(State(st, 'LEFT', st.xpos, st.ypos, 'N', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st, 'RIGHT', st.xpos, st.ypos, 'S', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
if st.orientation == 0:
|
||||
successors.append(State(st, 'LEFT', st.xpos, st.ypos, 3, passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st, 'RIGHT', st.xpos, st.ypos, 1, passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
if st.xpos < FIELDWIDTH * (FIELDCOUNT - 1):
|
||||
successors.append(State(st, 'FORWARD', st.xpos + FIELDWIDTH , st.ypos, 'E', passedPriorities[st.xpos//50][st.ypos//50], heuristicfn(st.xpos, st.ypos, goalx, goaly)))
|
||||
successors.append(State(st, 'FORWARD', st.xpos + FIELDWIDTH , st.ypos, 0, passedPriorities[st.xpos//50 + 1][st.ypos//50], heuristicfn(st.xpos + 50, st.ypos, goalx, goaly)))
|
||||
return successors
|
||||
|
|
|
|||
|
|
@ -0,0 +1,20 @@
|
|||
import pandas as pd
|
||||
from sklearn import tree
|
||||
from sklearn.preprocessing import LabelEncoder
|
||||
import graphviz
|
||||
|
||||
def treelearn():
|
||||
train_data = pd.read_csv('./data_set.csv')
|
||||
attributes = train_data.drop('collect', axis='columns')
|
||||
e_type = LabelEncoder()
|
||||
attributes['type_num'] = e_type.fit_transform(attributes['garbage_type'])
|
||||
attr_encoded = attributes.drop(['garbage_type'], axis='columns')
|
||||
attr_names = ['fuel','distance','space_occupied','days_since_last_collection','paid_on_time','odour_intensity','garbage_weight', 'garbage_type']
|
||||
label_names = ['collect', 'no-collect']
|
||||
label = train_data['collect']
|
||||
classifier = tree.DecisionTreeClassifier()
|
||||
classifier.fit(attr_encoded.values, label)
|
||||
dot_data = tree.export_graphviz(classifier, out_file=None, feature_names=attr_names, class_names=label_names)
|
||||
graph = graphviz.Source(dot_data)
|
||||
graph.render('collect')
|
||||
return classifier
|
||||
Loading…
Reference in New Issue