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88f68782f7
* chore: add pylint to devcontainer Signed-off-by: Dev Singh <dev@devksingh.com> * feat: init LSC fitting cuda and cpu-based LSC fitting using cupy and numpy Signed-off-by: Dev Singh <dev@devksingh.com> * docs: add changelog entry and module to class list Signed-off-by: Dev Singh <dev@devksingh.com> * docs: fix typo in comment Signed-off-by: Dev Singh <dev@devksingh.com> * fix: only import cupy if cuda available Signed-off-by: Dev Singh <dev@devksingh.com> * fix: move to own file, abandon cupy Signed-off-by: Dev Singh <dev@devksingh.com> * fix: remove numba dep Signed-off-by: Dev Singh <dev@devksingh.com> * deps: remove cupy dep Signed-off-by: Dev Singh <dev@devksingh.com> * feat: add tests Signed-off-by: Dev Singh <dev@devksingh.com> * fix: correct indentation Signed-off-by: Dev Singh <dev@devksingh.com> * fix: variable names Signed-off-by: Dev Singh <dev@devksingh.com> * fix: add self when refering to coords Signed-off-by: Dev Singh <dev@devksingh.com> * fix: numpy ordering Signed-off-by: Dev Singh <dev@devksingh.com> * docs: remove version bump, nomaintain add notice that module is not actively maintained, may be removed in future release Signed-off-by: Dev Singh <dev@devksingh.com> * fix: remove hyperfit as not being impled Signed-off-by: Dev Singh <dev@devksingh.com>
35 lines
3.8 KiB
Python
35 lines
3.8 KiB
Python
from tra_analysis import analysis as an
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from tra_analysis import metrics
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from tra_analysis import fits
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def test_():
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test_data_linear = [1, 3, 6, 7, 9]
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x_data_circular = []
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y_data_circular = []
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y_data_ccu = [1, 3, 7, 14, 21]
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y_data_ccd = [1, 5, 7, 8.5, 8.66]
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test_data_scrambled = [-32, 34, 19, 72, -65, -11, -43, 6, 85, -17, -98, -26, 12, 20, 9, -92, -40, 98, -78, 17, -20, 49, 93, -27, -24, -66, 40, 84, 1, -64, -68, -25, -42, -46, -76, 43, -3, 30, -14, -34, -55, -13, 41, -30, 0, -61, 48, 23, 60, 87, 80, 77, 53, 73, 79, 24, -52, 82, 8, -44, 65, 47, -77, 94, 7, 37, -79, 36, -94, 91, 59, 10, 97, -38, -67, 83, 54, 31, -95, -63, 16, -45, 21, -12, 66, -48, -18, -96, -90, -21, -83, -74, 39, 64, 69, -97, 13, 55, 27, -39]
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test_data_sorted = [-98, -97, -96, -95, -94, -92, -90, -83, -79, -78, -77, -76, -74, -68, -67, -66, -65, -64, -63, -61, -55, -52, -48, -46, -45, -44, -43, -42, -40, -39, -38, -34, -32, -30, -27, -26, -25, -24, -21, -20, -18, -17, -14, -13, -12, -11, -3, 0, 1, 6, 7, 8, 9, 10, 12, 13, 16, 17, 19, 20, 21, 23, 24, 27, 30, 31, 34, 36, 37, 39, 40, 41, 43, 47, 48, 49, 53, 54, 55, 59, 60, 64, 65, 66, 69, 72, 73, 77, 79, 80, 82, 83, 84, 85, 87, 91, 93, 94, 97, 98]
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assert an.basic_stats(test_data_linear) == {"mean": 5.2, "median": 6.0, "standard-deviation": 2.85657137141714, "variance": 8.16, "minimum": 1.0, "maximum": 9.0}
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assert an.z_score(3.2, 6, 1.5) == -1.8666666666666665
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assert an.z_normalize([test_data_linear], 1).tolist() == [[0.07537783614444091, 0.22613350843332272, 0.45226701686664544, 0.5276448530110863, 0.6784005252999682]]
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assert all(isinstance(item, str) for item in an.regression(test_data_linear, y_data_ccu, ["lin"])) == True
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#assert all(isinstance(item, str) for item in an.regression(test_data_linear, y_data_ccd, ["log"])) == True
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#assert all(isinstance(item, str) for item in an.regression(test_data_linear, y_data_ccu, ["exp"])) == True
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#assert all(isinstance(item, str) for item in an.regression(test_data_linear, y_data_ccu, ["ply"])) == True
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#assert all(isinstance(item, str) for item in an.regression(test_data_linear, y_data_ccd, ["sig"])) == True
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assert an.Metric().elo(1500, 1500, [1, 0], 400, 24) == 1512.0
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assert an.Metric().glicko2(1500, 250, 0.06, [1500, 1400], [250, 240], [1, 0]) == (1478.864307445517, 195.99122679202452, 0.05999602937563585)
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#assert an.Metric().trueskill([[(25, 8.33), (24, 8.25), (32, 7.5)], [(25, 8.33), (25, 8.33), (21, 6.5)]], [1, 0]) == [(metrics.trueskill.Rating(mu=21.346, sigma=7.875), metrics.trueskill.Rating(mu=20.415, sigma=7.808), metrics.trueskill.Rating(mu=29.037, sigma=7.170)), (metrics.trueskill.Rating(mu=28.654, sigma=7.875), metrics.trueskill.Rating(mu=28.654, sigma=7.875), metrics.trueskill.Rating(mu=23.225, sigma=6.287))]
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assert all(a == b for a, b in zip(an.Sort().quicksort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().mergesort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().introsort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().heapsort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().insertionsort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().timsort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().selectionsort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().shellsort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().bubblesort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().cyclesort(test_data_scrambled), test_data_sorted))
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assert all(a == b for a, b in zip(an.Sort().cocktailsort(test_data_scrambled), test_data_sorted))
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assert fits.CircleFit(x=[0,0,-1,1], y=[1, -1, 0, 0]).LSC() == (0.0, 0.0, 1.0, 0.0) |