"""Expected results for average module."""

import numpy as np

expected_petitjean_ba_univariate = np.array(
    [
        [
            1.4108696053220873,
            2.394226235189873,
            1.1060488942437015,
            2.623297561062815,
            0.527766384447058,
            1.43188098329184,
            1.6236753043608105,
            1.2058072160220672,
            1.1967764056706969,
            2.0004477079532927,
        ]
    ]
)

expected_petitjean_ba_multivariate = np.array(
    [
        [
            0.7267915954182468,
            1.3623320157069627,
            1.4495279596147028,
            0.5926686136095334,
            0.9971756690146295,
            1.3283383084721943,
            0.7659577046471742,
            1.9660527002664323,
            1.063255339395868,
            1.58993866039882,
        ],
        [
            1.2617459283113774,
            1.205815463685702,
            1.2234939638872127,
            1.7840697833529937,
            0.6722624075103683,
            1.835414289773766,
            0.9514286846149641,
            1.2908899681880017,
            1.416361929410518,
            1.5241706749949016,
        ],
        [
            1.3034322787744397,
            1.5436844012461954,
            1.632959525575443,
            1.0384357523605505,
            1.250310558432616,
            0.7533753079264169,
            0.7766566039307113,
            1.2180892807545585,
            1.6222668068442372,
            1.3287035370261573,
        ],
    ]
)

expected_subgradient_ba_univariate = np.array(
    [
        [
            1.4140771762669202,
            2.3521252702615345,
            1.1029707218683025,
            2.6528492580432323,
            0.5563623066732906,
            1.3725322344250663,
            1.3878962721692019,
            1.189052333096126,
            1.1762820445060347,
            2.000033260869454,
        ]
    ]
)

expected_subgradient_ba_multivariate = np.array(
    [
        [
            0.7267297069134186,
            1.3571256821332844,
            1.4470543677943613,
            0.7898616210203327,
            0.9159704540236109,
            1.3671774206489038,
            0.7028964621365015,
            1.9493364012536372,
            1.05990955295937,
            1.5906095734500851,
        ],
        [
            1.265482193230198,
            1.2087409747406466,
            1.2211572419145225,
            1.9394421655524658,
            0.7257069525960554,
            1.8652436429886237,
            0.9243031634782574,
            1.2858204600569865,
            1.4144716162773516,
            1.5246235389905667,
        ],
        [
            1.3039918248410391,
            1.5407704722162578,
            1.6266931584714321,
            1.2238187948084867,
            1.099261725637896,
            0.7232081092152858,
            0.8987466413415865,
            1.1954707110685778,
            1.6197874375001684,
            1.3284104408054522,
        ],
    ]
)

expected_shift_invariant_uni = [
    [
        0.21202708,
        0.38396126,
        0.30766178,
        0.29813882,
        0.26171993,
        0.30061257,
        0.29738316,
        0.32877191,
        0.32979092,
        0.3999009,
    ]
]

expected_shift_invariant_multi = [
    [
        0.14159688,
        0.38267823,
        0.32657886,
        0.25545555,
        0.31114448,
        0.31847882,
        0.25068386,
        0.36475845,
        0.32154177,
        0.40506361,
    ],
    [
        0.33220459,
        0.3688084,
        0.26411603,
        0.36515407,
        0.24629686,
        0.29242235,
        0.37619778,
        0.27963954,
        0.3403057,
        0.26233892,
    ],
    [
        0.28391082,
        0.39358395,
        0.37242576,
        0.20912892,
        0.35526779,
        0.27858964,
        0.32993588,
        0.30269441,
        0.28902656,
        0.30692856,
    ],
]

expected_shift_with_params = [
    [
        -0.06970511,
        -0.07524158,
        -0.0855859,
        -0.08536938,
        -0.08474463,
        -0.08397242,
        -0.08348801,
        -0.08337623,
        -0.08325212,
        -0.08325443,
        -0.08330007,
        -0.08327083,
        -0.08330829,
        -0.08334199,
        -0.08333183,
        -0.08303182,
        -0.08250814,
        -0.08094021,
        -0.07873833,
        -0.07583918,
        -0.07291457,
        -0.07012965,
        -0.06796154,
        -0.06644994,
        -0.06565636,
        -0.0647156,
        -0.06373273,
        -0.06284954,
        -0.061914,
        -0.06128938,
        -0.06058979,
        -0.05980234,
        -0.05856685,
        -0.05698044,
        -0.05514379,
        -0.05274212,
        -0.04922944,
        -0.04460011,
        -0.03840232,
        -0.03099803,
        -0.02245942,
        -0.01242792,
        -0.00234979,
        0.00737382,
        0.01616795,
        0.02443241,
        0.0322885,
        0.04000181,
        0.04793694,
        0.05603125,
        0.06495882,
        0.07345718,
        0.08144559,
        0.0886841,
        0.09562103,
        0.10225545,
        0.10845322,
        0.11398232,
        0.11819766,
        0.12086673,
        0.12235296,
        0.12312705,
        0.12359997,
        0.12367804,
        0.1237006,
        0.12358171,
        0.12356881,
        0.12362762,
        0.12374729,
        0.12367848,
        0.12374656,
        0.12378735,
        0.12369702,
        0.12363038,
        0.12369176,
        0.12358862,
        0.1235492,
        0.12350022,
        0.12322623,
        0.12295472,
        0.12237259,
        0.12168894,
        0.12052438,
        0.11910681,
        0.11731959,
        0.11506372,
        0.11248901,
        0.10932015,
        0.10587216,
        0.10193271,
        0.09757553,
        0.09311642,
        0.08795862,
        0.08251217,
        0.07669033,
        0.07089404,
        0.06484404,
        0.0586602,
        0.05232688,
        0.04542419,
        0.03840013,
        0.03110547,
        0.02357983,
        0.0164401,
        0.0094151,
        0.00220803,
        -0.00435163,
        -0.01109575,
        -0.01748173,
        -0.02356507,
        -0.02911341,
        -0.03428729,
        -0.03881576,
        -0.04254768,
        -0.04534214,
        -0.04782416,
        -0.04971247,
        -0.05133592,
        -0.05287152,
        -0.05452229,
        -0.05619686,
        -0.05816211,
        -0.06041638,
        -0.06254839,
        -0.06475007,
        -0.06682629,
        -0.06870101,
        -0.07030764,
        -0.07152161,
        -0.0725368,
        -0.07322947,
        -0.07390214,
        -0.0745344,
        -0.07553438,
        -0.07655488,
        -0.07790736,
        -0.07960412,
        -0.08115919,
        -0.08274493,
        -0.08407786,
        -0.08507001,
        -0.08589683,
        -0.08642586,
        -0.08668667,
        -0.08648433,
        -0.08618434,
        -0.08581321,
        -0.08525205,
        -0.06750001,
        -0.0644152,
    ]
]

expected_kasba_ba_univariate = [
    [
        1.66927775,
        2.00725484,
        0.95286261,
        1.98356308,
        0.81880663,
        1.37102377,
        1.77943005,
        1.37294541,
        1.33994775,
        1.67563731,
    ]
]

expected_kasba_ba_multivariate = [
    [
        0.71767481,
        1.39930349,
        1.29434224,
        0.72628471,
        1.12290607,
        1.23966907,
        0.78614546,
        1.56670693,
        1.09827156,
        1.57560871,
    ],
    [
        1.13660818,
        1.36478053,
        1.09463845,
        1.65103481,
        0.97217855,
        1.41841601,
        1.2157067,
        1.11209033,
        1.30966526,
        1.47004663,
    ],
    [
        1.19600771,
        1.52977945,
        1.38014143,
        1.08513837,
        1.18066111,
        0.99505074,
        1.12834455,
        1.0172058,
        1.32168863,
        1.30702151,
    ],
]
