CS3910-Coursework/Test_PSO.py at master · JordanL1/CS3910-Coursework · GitHub

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import statistics
import time
import csv
from Swarm import Swarm
from Pallets import Pallets

FILE = "data/cwk_train.csv"

fieldnames = ['Runs', 'LSI', 'Swarm Size','Run Time', 'Cognitive Coefficient', 'Mean', 'Standard Deviation', 'Costs', 'Solutions']

def run_test(runs: int, LSI: bool, swarm_size: int, run_time: int, cog_coefficient = 1.1193):
    pallet_prob = Pallets(FILE)
    swarm = Swarm(pallet_prob, cog_coefficient)

    results = []
    result_costs = []

    for i in range(runs):
        if LSI == True:
            result = swarm.timed_swarm_search_with_lsi(swarm_size, run_time)
        else:
            result = swarm.timed_swarm_search(swarm_size, run_time)
        results.append(result[0])
        result_costs.append(result[1])

    mean = statistics.mean(result_costs)
    stdev = statistics.stdev(result_costs)

    with open('data/test_results_training_file.csv', mode='a') as csv_file:
        writer = csv.DictWriter(csv_file, fieldnames=fieldnames)
        writer.writerow({'Runs' : runs, 'LSI' : LSI, 'Swarm Size' : swarm_size, 'Run Time' : run_time, 'Cognitive Coefficient' : cog_coefficient, 'Mean' : mean, 'Standard Deviation' : stdev, 'Costs' : result_costs, 'Solutions' : results})

    print("Test Complete!")

def compare_solutions_on_different_datasets(file1 : str, file2: str, solutions: list):
    """
    Compare the results produced by a list of solutions on two different datasets.
    """
    pallets_one = Pallets(file1)
    pallets_two = Pallets(file2)
    dataset1_costs = []
    dataset2_costs = []

    for solution in solutions:
        dataset1_costs.append(pallets_one.evaluate_cost(solution))
        dataset2_costs.append(pallets_two.evaluate_cost(solution))

    with open('comparing_datasets.csv', mode='w') as csv_file:
        writer = csv.writer(csv_file)
        writer.writerow(dataset1_costs)
        writer.writerow(dataset2_costs)

# Test different swarm sizes
#run_test(100, False, 30, 15)
#run_test(100, True, 30, 15)
#run_test(100, False, 100, 15)
#run_test(100, True, 100, 15)
#run_test(100, False, 500, 15)
#run_test(100, True, 500, 15)

# Test with different cognitive coefficient
#run_test(100, False, 100, 15, 1.5)
#run_test(100, True, 100, 15, 1.5)
#run_test(100, False, 100, 15, 1.8)
#run_test(100, True, 100, 15, 1.8)

# Compare a set of solutions on the two different datasets
SOLUTIONS = [[0.9302016390570997, 0.4490373156115222, -1.269217407253632, 2.3065813688026306, -2.6763239786898554, 0.14749140401561914, 0.0028133436952706642, 0.9571118155856959, 100.73779648361301, 101.16109560601733, 76.48326072498244, 41.70911980344192, 39.886283459031006], [1.2103600928929128, -0.09202396297945234, -0.3094879995485397, 1.7913536807041472, -2.3283074432018833, -0.004348397150747719, 0.13066165028191248, 1.0200906069793494, 96.46038794087251, 142.51989594901926, 126.80047128294389, 94.94893601291642, 104.06690983019645], [0.9782291463085847, 0.333755669265449, -1.2263535658833564, 2.108939999220196, -2.7630053286293665, 0.24243460855834265, -0.08053092782835883, 0.9957334875218286, 95.65627112646557, 105.14554818258314, 82.82239162602896, 52.19876007956984, 50.767991381001906], [1.3822838391105492, 0.33111350529382383, -0.4577810111642039, 2.6901915036031165, -2.740603072712513, -0.04469828706988909, 0.12967837024409892, 0.4907709420540358, 93.51105418604801, 96.82221846021038, 74.26873366942075, 29.209192625900805, 26.98584842627773], [1.5724634757235951, 0.026978514711840738, -0.2738510811259408, 1.5977380671263495, -2.545325950922345, -0.378348506318641, 0.4965755797432791, 1.4202174886838512, 98.53509091328448, 127.99073169312346, 113.97774486260494, 86.26090245177554, 90.95344642120546], [0.9008961732763393, 0.2392195048028815, -1.0996638894687296, 1.835612894605401, -2.814232433915421, 0.5580866084414244, -0.39888258075636746, 1.0067720373950726, 89.28856179584587, 100.1505017925676, 75.08859563899874, 56.17186900925023, 58.62318177268591], [0.65705471074636, 0.3567811825836535, -1.2706486450788506, 1.6328662943053436, -2.370411580355292, 0.8117518824647005, -0.6964089371297943, 0.8340931027382451, 92.3239066452128, 81.00879734355361, 62.59253133455313, 51.909220938644786, 41.17811290698571], [1.3084377708390251, -0.13307533949882747, -0.24351577598222537, 1.793998095391125, -2.41340137952053, -0.22170821503423024, 0.36188912390245714, 1.1331088469265223, 100.06495392605305, 155.3382814224863, 138.50489925494838, 107.85034825208055, 114.29481862515387], [1.2282522647437901, 0.46459413773224745, -1.0912945610620637, 2.33263563675002, -2.564795803893445, 0.1122674446419692, 0.07119193657866271, 0.768551730299904, 88.44598771339933, 76.58745406568244, 57.18071673710202, 23.523992472167627, 17.80925466142816], [1.0484796968605525, -0.05296843638571697, -0.4662472930261504, 1.6320601316311245, -2.232151160161968, -0.02007087513754548, 0.17204535406183843, 1.2044579057643523, 101.38915744287877, 149.4553653383541, 130.58429198360733, 101.70986685920184, 108.8874563392163], [1.3738290456446274, 0.19056929000039574, -0.5928627443943368, 1.6137903636838102, -2.31778267997627, -0.21193226679117916, 0.33956961874565206, 1.4012012146967865, 96.8855379726721, 111.12257036775, 96.01248526508641, 67.98742342945411, 71.6200362665464], [1.292232714530479, 0.06525170594466871, -0.6028821525865787, 1.7306274196128315, -2.8947601111643144, 0.20865745266303787, -0.040798485706829944, 1.2128856603352625, 85.24044067591397, 103.9470753465004, 88.72362324563844, 67.11091871864573, 81.07821717591516], [1.0797376048714538, 0.3072610290487078, -0.8783401995446984, 2.208495745447034, -2.5250540189413084, 0.19758796812259638, -0.09523494996894007, 0.8153118377608732, 96.203736534453, 101.80552156677922, 82.79190270037193, 49.72356054046686, 44.21380017013731], [1.4416740397684364, -0.010040913286582067, -0.14007269794167201, 1.6463977585153304, -1.7205293606365215, -0.10019720521712139, 0.19271772724414266, 0.7599702879017132, 92.65870127655631, 119.3271920344022, 113.02345133226424, 81.1908577905724, 77.42288983763767], [1.1333867607294388, 0.48803933848719766, -1.0263250219729358, 1.784118912570145, -2.5467037273075137, 0.41355737877903187, -0.30426246075757785, 0.8576524158860318, 87.50598964590911, 60.07458543855494, 42.74391400571662, 19.450135786932236, 12.556941288620893], 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1.279940672582949, 98.81268611510896, 84.62969683078126, 59.60428049028041, 37.52993051665646, 37.02194018688345], [1.5550096413844996, -0.0036751050827719687, -0.26660136709518445, 2.504972549073045, -2.8252950861096138, -0.10574016548949966, 0.2141603499461666, 0.6894132688409219, 87.14292309117393, 124.63085106973787, 109.49687250864642, 64.71715146887405, 77.94286828954358], [0.678176247723475, 0.015331086970249123, -0.8312161367242176, 1.6869052096803774, -1.1645640328931777, 0.29472803013193366, -0.22165152137628327, 0.9781016863032855, 101.2529610417588, 147.06884774350107, 136.37551254993136, 105.67994732459239, 99.49733247606099], [1.507254192522168, 0.4875528265311708, -1.0012951716338012, 1.6200328800893895, -2.585623920395767, -0.3082821995540738, 0.4825067191389356, 1.3657754827170843, 92.97666843271936, 79.84948581710843, 61.36520573354575, 32.47974536840427, 35.51536390120399], [1.2750163372110255, 0.16571799277827926, -0.6285202636041038, 2.5833234712298223, -2.915922510477616, 0.05944664716758425, 0.06555553972527976, 0.7361898789686102, 91.85722792059275, 115.08227660618324, 95.9477397803647, 53.25035508419271, 59.35365570069348], [1.0326350457154323, 0.170505437854062, -0.8934187832466371, 2.0765239668334603, -2.283935284778951, 0.058573547025098927, 0.05565501676143429, 0.86406379674919, 101.33123182005686, 129.5349588586353, 111.20835439088322, 74.39857122096738, 73.66350672845878], [1.2253996974331747, -0.14593060984943332, -0.19433583598360718, 1.9054719509897546, -2.542535289440718, 0.10333715797267048, 0.005710661384551622, 0.8669325734390486, 95.31528282658567, 141.26873357407257, 126.20423417361994, 95.1404038720797, 107.73226881659377], [1.0695494640476504, 0.07082781355749898, -0.6291376443609842, 2.113607048044935, -3.005635273382092, 0.16679451388605965, 0.02239583911399478, 1.2348950568774504, 93.59023365474675, 127.59456282191047, 101.00591627793914, 72.2715521603929, 85.2680105366041], [1.2040249336188502, 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83.50625319946064, 97.49367744397564], [1.6116127082565332, 0.15545199966677142, -0.43872385567548344, 1.8289033980696752, -2.4943681157371396, -0.29965964317061333, 0.4399367231313422, 1.0574080006508293, 91.35678726419981, 110.39794456988268, 95.95605076273262, 60.63071900767846, 63.669363931220936], [1.1402089300944336, 0.2842847817265538, -0.8821941342878196, 2.7609221511873003, -2.8352226130918465, 0.10438585746174564, 0.050134971625893664, 0.6534671115794003, 93.91222686016627, 109.23301627277623, 86.24886734356059, 42.41320081177106, 46.22865986710812], [1.13344110591779, 0.19868219772610338, -1.0374240631225966, 2.1321749649154955, -2.831441317640997, 0.4156770751362016, -0.2860759172902869, 0.7633652332542884, 86.51848414279044, 107.15953142903575, 80.7121609855682, 53.07216128751877, 57.87570786962339], [1.3513286336320087, -0.041516309719676084, -0.3474870009061069, 2.348131042569806, -2.757225993342618, -0.16199208921904076, 0.30217366151321023, 0.9100542156772788, 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compare_solutions_on_different_datasets("data/cwk_train.csv", "data/cwk_test.csv", SOLUTIONS)