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797 lines
32 KiB
Python
797 lines
32 KiB
Python
from six import iteritems
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from numpy.testing import (run_module_suite, assert_equal, assert_almost_equal,
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assert_array_equal, assert_array_almost_equal,
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TestCase, assert_, assert_raises,)
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import numpy as np
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from numpy import array, cos, exp, linspace, pi, sin, diff, arange, ones
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from wafo.data import sea
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import wafo
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from wafo.misc import (JITImport, Bunch, detrendma, DotDict, findcross, ecross,
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findextrema, findrfc, rfcfilter, findtp, findtc,
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findrfc_astm,
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findoutliers, common_shape, argsreduce, stirlerr,
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getshipchar, betaloge,
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gravity, nextpow2, discretize, polar2cart,
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cart2polar, tranproc,
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rotation_matrix, rotate_2d, spaceline,
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args_flat, sub2index, index2sub, piecewise,
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parse_kwargs)
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def test_disufq():
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d_inf = [[0., -144.3090093, -269.37681737, -375.20342419, -461.78882978,
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-529.13303412, -577.23603722, -606.09783908, -615.7184397,
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-606.09783908, -577.23603722, -529.13303412, -461.78882978,
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-375.20342419, -269.37681737, -144.3090093, 0., 0., 0., 0.,
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0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
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[0.00000000e+00, 0.00000000e+00, 5.65917684e-01, 2.82958842e+00,
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7.92284757e+00, 1.69775305e+01, 3.11254726e+01, 5.14985092e+01,
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7.92284757e+01, 1.15447207e+02, 1.61286540e+02, 2.17878308e+02,
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2.86354348e+02, 3.67846494e+02, 4.63486583e+02, 5.74406449e+02,
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7.01737928e+02, 8.46612855e+02, 8.46046937e+02, 8.43783266e+02,
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8.38690007e+02, 8.29635324e+02, 8.15487382e+02, 7.95114345e+02,
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7.67384379e+02, 7.31165647e+02, 6.85326315e+02, 6.28734546e+02,
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5.60258507e+02, 4.78766360e+02, 3.83126272e+02, 2.72206406e+02]]
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# depth = 10
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d_10 = [[-3.43299449, -144.58425201, -269.97386241, -376.2314858,
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-463.35503499, -531.34450329, -580.19988853, -609.92118976,
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-620.50840653, -611.96153858, -584.28058577, -537.46554798,
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-471.51642516, -386.43321726, -282.21592426, -158.8601612, 0., 0.,
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0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0., 0.],
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[0., 0., 0.87964472, 3.30251807, 8.7088916, 18.1892694,
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32.87215973, 53.88831991, 82.36912798,
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119.44619211, 166.25122204, 223.91597801, 293.57224772,
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376.35183479, 473.38655268, 585.80822113, 714.74866403,
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861.33970818, 846.05101255, 843.78326617, 838.69000702,
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829.63532408, 815.48738199, 795.11434539, 767.38437889,
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731.16564714, 685.32631478, 628.73454642, 560.25850671,
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478.76636028, 383.12627176, 272.20640579]]
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g = 9.81
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n = 32
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amp = np.ones(n) + 1j * 1
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f = np.linspace(0., 3.0, n // 2 + 1)
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nmin = 2
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nmax = n // 2 + 1
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cases = 1
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ns = n
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w = 2.0 * pi * f
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from wafo import c_library
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d_truth = [d_10, d_inf]
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for i, water_depth in enumerate([10.0, 10000000]):
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kw = wafo.wave_theory.dispersion_relation.w2k(w, 0., water_depth, g)[0]
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data2 = wafo.numba_misc.disufq(amp.real, amp.imag, w, kw, water_depth,
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g, nmin, nmax, cases, ns)
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data = c_library.disufq(amp.real, amp.imag, w, kw, water_depth, g,
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nmin, nmax, cases, ns)
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# print(data[0])
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# print(data[1])
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# deep water
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assert_array_almost_equal(data, data2)
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assert_array_almost_equal(data, d_truth[i])
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# assert(False)
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def test_JITImport():
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np = JITImport('numpy')
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assert_equal(1.0, np.exp(0))
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def test_bunch():
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d = Bunch(test1=1, test2=3)
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assert_equal(1, getattr(d, 'test1'))
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assert_equal(3, getattr(d, 'test2'))
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def test_dotdict():
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d = DotDict(test1=1, test2=3)
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assert_equal(1, d.test1)
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assert_equal(3, d.test2)
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def test_detrendma():
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x = linspace(0, 1, 200)
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y = exp(x) + 0.1 * cos(20 * 2 * pi * x)
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y0 = detrendma(y, 20)
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tr = y - y0
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assert_array_almost_equal(
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y0,
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array(
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[-1.05815186e-02, -2.48280355e-02, -7.01800760e-02,
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-1.27193089e-01, -1.71915213e-01, -1.85125121e-01,
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-1.59745361e-01, -1.03571981e-01, -3.62676515e-02,
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1.82219951e-02, 4.09039083e-02, 2.50630186e-02,
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-2.11478040e-02, -7.78521440e-02, -1.21116040e-01,
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-1.32178923e-01, -1.04689244e-01, -4.71541301e-02,
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2.03417510e-02, 7.38826137e-02, 8.95349902e-02,
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6.68738432e-02, 1.46828486e-02, -4.68648556e-02,
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-9.39871606e-02, -1.08465407e-01, -8.46710629e-02,
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-3.17365657e-02, 2.99669288e-02, 7.66864134e-02,
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9.04482283e-02, 6.59902473e-02, 1.27914062e-02,
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-4.85841870e-02, -9.44185349e-02, -1.06987444e-01,
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-8.13964951e-02, -2.74687460e-02, 3.40438793e-02,
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7.94643163e-02, 9.13222681e-02, 6.50922520e-02,
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1.09390148e-02, -5.02028639e-02, -9.47031411e-02,
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-1.05349757e-01, -7.79872833e-02, -2.31196073e-02,
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3.81412653e-02, 8.22178144e-02, 9.21605209e-02,
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6.41850565e-02, 9.13184690e-03, -5.17149253e-02,
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-9.48363260e-02, -1.03549587e-01, -7.44424124e-02,
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-1.86890490e-02, 4.22594607e-02, 8.49486437e-02,
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9.29666543e-02, 6.32740911e-02, 7.37625254e-03,
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-5.31142920e-02, -9.48133620e-02, -1.01584110e-01,
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-7.07607748e-02, -1.41768231e-02, 4.63990484e-02,
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8.76587937e-02, 9.37446001e-02, 6.23650231e-02,
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5.67876495e-03, -5.43947621e-02, -9.46294406e-02,
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-9.94504301e-02, -6.69411601e-02, -9.58252265e-03,
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5.05608316e-02, 9.03505172e-02, 9.44985623e-02,
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6.14637631e-02, 4.04610591e-03, -5.55500040e-02,
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-9.42796647e-02, -9.71455674e-02, -6.29822440e-02,
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-4.90556961e-03, 5.47458452e-02, 9.30263409e-02,
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9.52330253e-02, 6.05764719e-02, 2.48519180e-03,
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-5.65735506e-02, -9.37590405e-02, -9.46664506e-02,
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-5.88825766e-02, -1.45202622e-04, 5.89553685e-02,
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9.56890756e-02, 9.59527629e-02, 5.97095676e-02,
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1.00314001e-03, -5.74587921e-02, -9.30624694e-02,
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-9.20099048e-02, -5.46405701e-02, 4.69953603e-03,
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6.31909369e-02, 9.83418277e-02, 9.66628470e-02,
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5.88697331e-02, -3.92724035e-04, -5.81989687e-02,
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-9.21847386e-02, -8.91726414e-02, -5.02544862e-02,
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9.62981387e-03, 6.74543554e-02, 1.00988010e-01,
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9.73686580e-02, 5.80639242e-02, -1.69485946e-03,
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-5.87871620e-02, -9.11205115e-02, -8.61512458e-02,
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-4.57224228e-02, 1.46470222e-02, 7.17477118e-02,
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1.03631355e-01, 9.80758938e-02, 5.72993780e-02,
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-2.89550192e-03, -5.92162868e-02, -8.98643173e-02,
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-8.29421650e-02, -4.10422999e-02, 1.97527907e-02,
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7.60733908e-02, 1.06275925e-01, 9.87905812e-02,
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5.65836223e-02, -3.98665495e-03, -5.94790815e-02,
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-8.84105398e-02, -7.95416952e-02, -3.62118451e-02,
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2.49490024e-02, 8.04340881e-02, 1.08926128e-01,
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9.95190863e-02, 5.59244846e-02, -4.96008086e-03,
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-5.95680980e-02, -8.67534061e-02, -7.59459673e-02,
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-3.12285782e-02, 3.02378095e-02, 8.48328258e-02,
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1.11586726e-01, 1.00268126e-01, 5.53301029e-02,
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-5.80729079e-03, -5.94756912e-02, -8.48869734e-02,
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-7.21509330e-02, -2.60897955e-02, 3.56216499e-02,
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8.92729678e-02, 1.14262857e-01, 1.01044781e-01,
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5.48089359e-02, -6.51953427e-03, -5.91940075e-02,
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-8.28051165e-02, -6.81523491e-02, -2.07925530e-02,
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4.11032641e-02, 9.37582360e-02, 1.16960041e-01,
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1.13824241e-01, 7.82451609e-02, 2.87461256e-02,
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-1.07566250e-02, -2.01779675e-02, 8.98967999e-03,
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7.03952281e-02, 1.45278564e-01, 2.09706186e-01,
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2.43802139e-01, 2.39414013e-01, 2.03257341e-01,
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1.54325635e-01, 1.16564992e-01, 1.09638547e-01,
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1.41342814e-01, 2.04600808e-01, 2.80191671e-01,
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3.44164010e-01, 3.77073744e-01
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]))
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assert_array_almost_equal(tr, array([
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1.11058152, 1.11058152, 1.11058152, 1.11058152, 1.11058152,
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1.11058152, 1.11058152, 1.11058152, 1.11058152, 1.11058152,
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1.11058152, 1.11058152, 1.11058152, 1.11058152, 1.11058152,
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1.11058152, 1.11058152, 1.11058152, 1.11058152, 1.11058152,
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1.11599212, 1.12125245, 1.12643866, 1.13166607, 1.13704477,
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1.14263723, 1.14843422, 1.15435845, 1.16029443, 1.16613308,
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1.17181383, 1.17734804, 1.18281471, 1.18833001, 1.19400259,
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1.19989168, 1.20598434, 1.21220048, 1.21842384, 1.22454684,
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1.23051218, 1.23633498, 1.24209697, 1.24791509, 1.25389641,
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1.26009689, 1.26649987, 1.27302256, 1.27954802, 1.28597031,
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1.29223546, 1.29836228, 1.30443522, 1.31057183, 1.31687751,
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1.32340488, 1.3301336, 1.33697825, 1.34382132, 1.35055864,
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1.35713958, 1.36358668, 1.36998697, 1.37645853, 1.38310497,
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1.38997553, 1.39704621, 1.40422902, 1.41140604, 1.41847493,
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1.4253885, 1.43217295, 1.43891784, 1.44574164, 1.45274607,
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1.45997696, 1.46740665, 1.47494469, 1.48247285, 1.48989073,
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1.49715462, 1.50429437, 1.51140198, 1.51859618, 1.52597672,
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1.53358594, 1.54139257, 1.5493038, 1.55720119, 1.56498641,
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1.57261924, 1.58013316, 1.58762252, 1.5952062, 1.60298187,
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1.61098836, 1.6191908, 1.62749412, 1.63577979, 1.64395163,
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1.65197298, 1.65988092, 1.66777202, 1.67576523, 1.68395602,
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1.69237968, 1.70099778, 1.70971307, 1.71840707, 1.72698583,
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1.73541631, 1.74373911, 1.75205298, 1.76047677, 1.76910369,
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1.77796544, 1.78702008, 1.79616827, 1.80529169, 1.81429875,
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1.82316, 1.83191959, 1.84067831, 1.84955481, 1.85863994,
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1.86796178, 1.87747491, 1.88707803, 1.89665308, 1.9061109,
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1.91542572, 1.92464514, 1.9338719, 1.94322436, 1.9527909,
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1.96259596, 1.97259069, 1.9826719, 1.99272195, 2.00265419,
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2.01244653, 2.02215, 2.0318692, 2.04172204, 2.05179437,
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2.06210696, 2.07260759, 2.08319129, 2.09374092, 2.10417247,
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2.11446752, 2.12468051, 2.13491776, 2.14529665, 2.1559004,
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2.16674609, 2.17777817, 2.18889002, 2.19996511, 2.21092214,
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2.22174641, 2.23249567, 2.24327791, 2.25420982, 2.26537192,
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2.2767776, 2.28836802, 2.30003501, 2.3116628, 2.32317284,
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2.33455419, 2.34586786, 2.35722337, 2.36873665, 2.38048542,
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2.39247934, 2.4046564, 2.41690694, 2.42911606, 2.44120808,
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2.44120808, 2.44120808, 2.44120808, 2.44120808, 2.44120808,
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2.44120808, 2.44120808, 2.44120808, 2.44120808, 2.44120808,
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2.44120808, 2.44120808, 2.44120808, 2.44120808, 2.44120808,
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2.44120808, 2.44120808, 2.44120808, 2.44120808, 2.44120808]))
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def test_findcross_and_ecross():
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assert_array_equal(findcross([0, 0, 1, -1, 1], 0), np.array([1, 2, 3]))
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assert_array_equal(findcross([0, 1, -1, 1], 0), np.array([0, 1, 2]))
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t = linspace(0, 7 * pi, 250)
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x = sin(t)
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ind = findcross(x, 0.75)
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assert_array_equal(ind, np.array([9, 25, 80, 97, 151, 168, 223, 239]))
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t0 = ecross(t, x, ind, 0.75)
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assert_array_almost_equal(t0, np.array([0.84910514, 2.2933879, 7.13205663,
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8.57630119, 13.41484739,
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14.85909194,
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19.69776067, 21.14204343]))
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def test_findextrema():
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t = linspace(0, 7 * pi, 250)
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x = sin(t)
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ind = findextrema(x)
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assert_array_almost_equal(ind, np.array([18, 53, 89, 125, 160, 196, 231]))
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def test_findrfc():
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t = linspace(0, 7 * pi, 250)
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x = sin(t) + 0.1 * sin(50 * t)
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ind = findextrema(x)
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assert_array_almost_equal(
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ind,
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np.array(
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[1, 3, 4, 6, 7, 9, 11, 13, 14, 16, 18, 19, 21,
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23, 25, 26, 28, 29, 31, 33, 35, 36, 38, 39, 41, 43,
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45, 46, 48, 50, 51, 53, 55, 56, 58, 60, 61, 63, 65,
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67, 68, 70, 71, 73, 75, 77, 78, 80, 81, 83, 85, 87,
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88, 90, 92, 93, 95, 97, 99, 100, 102, 103, 105, 107, 109,
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110, 112, 113, 115, 117, 119, 120, 122, 124, 125, 127, 129, 131,
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132, 134, 135, 137, 139, 141, 142, 144, 145, 147, 149, 151, 152,
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154, 156, 157, 159, 161, 162, 164, 166, 167, 169, 171, 173, 174,
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176, 177, 179, 181, 183, 184, 186, 187, 189, 191, 193, 194, 196,
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198, 199, 201, 203, 205, 206, 208, 209, 211, 213, 215, 216, 218,
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219, 221, 223, 225, 226, 228, 230, 231, 233, 235, 237, 238, 240,
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241, 243, 245, 247, 248]))
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_ti, tp = t[ind], x[ind]
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for method in ['clib', 2, 1, 0]:
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ind1 = findrfc(tp, 0.3, method=method)
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if method in [1, 0]:
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ind1 = ind1[:-1]
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assert_array_almost_equal(
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ind1,
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np.array([0, 9, 32, 53, 74, 95, 116, 137]))
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assert_array_almost_equal(
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tp[ind1],
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np.array(
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[-0.00743352, 1.08753972, -1.07206545, 1.09550837, -1.07940458,
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1.07849396, -1.0995006, 1.08094452]))
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def test_rfcfilter():
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# 1. Filtered signal y is the turning points of x.
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x = sea()
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y = rfcfilter(x[:, 1], h=0.0, method=1)
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assert_array_almost_equal(
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y[0:5],
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np.array([-1.2004945, 0.83950546, -0.09049454,
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-0.02049454, -0.09049454]))
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# 2. This removes all rainflow cycles with range less than 0.5.
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y1 = rfcfilter(x[:, 1], h=0.5, method=0)
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assert_array_almost_equal(
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y1[0:5],
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np.array([-1.2004945, 0.83950546, -0.43049454,
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0.34950546, -0.51049454]))
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# return
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t = linspace(0, 7 * pi, 250)
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x = sin(t) + 0.1 * sin(50 * t)
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ind = findextrema(x)
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assert_array_almost_equal(
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ind,
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np.array(
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[1, 3, 4, 6, 7, 9, 11, 13, 14, 16, 18, 19, 21,
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|
23, 25, 26, 28, 29, 31, 33, 35, 36, 38, 39, 41, 43,
|
|
45, 46, 48, 50, 51, 53, 55, 56, 58, 60, 61, 63, 65,
|
|
67, 68, 70, 71, 73, 75, 77, 78, 80, 81, 83, 85, 87,
|
|
88, 90, 92, 93, 95, 97, 99, 100, 102, 103, 105, 107, 109,
|
|
110, 112, 113, 115, 117, 119, 120, 122, 124, 125, 127, 129, 131,
|
|
132, 134, 135, 137, 139, 141, 142, 144, 145, 147, 149, 151, 152,
|
|
154, 156, 157, 159, 161, 162, 164, 166, 167, 169, 171, 173, 174,
|
|
176, 177, 179, 181, 183, 184, 186, 187, 189, 191, 193, 194, 196,
|
|
198, 199, 201, 203, 205, 206, 208, 209, 211, 213, 215, 216, 218,
|
|
219, 221, 223, 225, 226, 228, 230, 231, 233, 235, 237, 238, 240,
|
|
241, 243, 245, 247, 248]))
|
|
_ti, tp = t[ind], x[ind]
|
|
tp03 = rfcfilter(tp, 0.3)
|
|
assert_array_almost_equal(
|
|
tp03,
|
|
np.array(
|
|
[-0.00743352, 1.08753972, -1.07206545, 1.09550837, -1.07940458,
|
|
1.07849396, -1.0995006, 1.08094452, 0.11983423]))
|
|
|
|
tp3 = findrfc_astm(tp)
|
|
assert_array_almost_equal((77, 3), tp3.shape)
|
|
# print(tp3[-5:])
|
|
assert_array_almost_equal(tp3[-5:],
|
|
[[0.01552179, 0.42313414, 1.],
|
|
[1.09750448, -0.00199612, 0.5],
|
|
[1.09022256, -0.00927804, 0.5],
|
|
[0.48055514, 0.60038938, 0.5],
|
|
[0.03200274, 0.15183698, 0.5]])
|
|
assert_array_almost_equal(tp3[:5],
|
|
[[0.03578165, 0.28906389, 1.],
|
|
[0.03602834, 0.56726584, 1.],
|
|
[0.03816623, 0.76461446, 1.],
|
|
[0.0638364, 0.92381302, 1.],
|
|
[0.07759006, 0.99628738, 1.]])
|
|
|
|
# assert(False)
|
|
|
|
|
|
def test_findtp():
|
|
x = sea()
|
|
x1 = x[0:200, :]
|
|
itp = findtp(x1[:, 1], 0, 'Mw')
|
|
itph = findtp(x1[:, 1], 0.3, 'Mw')
|
|
assert_array_almost_equal(
|
|
itp,
|
|
np.array(
|
|
[11, 21, 22, 24, 26, 28, 31, 39, 43, 45, 47, 51, 56,
|
|
64, 70, 78, 82, 84, 89, 94, 101, 108, 119, 131, 141, 148,
|
|
149, 150, 159, 173, 184, 190, 199]))
|
|
assert_array_almost_equal(
|
|
itph,
|
|
np.array(
|
|
[11, 28, 31, 39, 47, 51, 56, 64, 70, 78, 89, 94, 101,
|
|
108, 119, 131, 141, 148, 159, 173, 184, 190, 199]))
|
|
|
|
|
|
def test_findtc():
|
|
x = sea()
|
|
x1 = x[0:200, :]
|
|
itc, iv = findtc(x1[:, 1], 0, 'dw')
|
|
assert_array_almost_equal(
|
|
itc,
|
|
np.array(
|
|
[28, 31, 39, 56, 64, 69, 78, 82, 83, 89, 94, 101, 108,
|
|
119, 131, 140, 148, 159, 173, 184]))
|
|
assert_array_almost_equal(
|
|
iv,
|
|
np.array(
|
|
[19, 29, 34, 53, 60, 67, 76, 81, 82, 84, 90, 99, 103,
|
|
112, 127, 137, 143, 154, 166, 180, 185]))
|
|
|
|
|
|
def test_findoutliers():
|
|
xx = sea()
|
|
dt = diff(xx[:2, 0])
|
|
dcrit = 5 * dt
|
|
ddcrit = 9.81 / 2 * dt * dt
|
|
zcrit = 0
|
|
[inds, indg] = findoutliers(xx[:, 1], zcrit, dcrit, ddcrit, verbose=False)
|
|
assert_array_almost_equal(inds[np.r_[0, 1, 2, -3, -2, -1]],
|
|
np.array([6, 7, 8, 9509, 9510, 9511]))
|
|
assert_array_almost_equal(indg[np.r_[0, 1, 2, -3, -2, -1]],
|
|
np.array([0, 1, 2, 9521, 9522, 9523]))
|
|
|
|
|
|
def test_common_shape():
|
|
A = np.ones((4, 1))
|
|
B = 2
|
|
C = np.ones((1, 5)) * 5
|
|
assert_array_equal(common_shape(A, B, C), (4, 5))
|
|
assert_array_equal(common_shape(A, B, C, shape=(3, 4, 1)), (3, 4, 5))
|
|
A = np.ones((4, 1))
|
|
B = 2
|
|
C = np.ones((1, 5)) * 5
|
|
assert_array_equal(common_shape(A, B, C), (4, 5))
|
|
assert_array_equal(common_shape(A, B, C, shape=(3, 4, 1)), (3, 4, 5))
|
|
|
|
|
|
def test_argsreduce():
|
|
A = np.reshape(linspace(0, 19, 20), (4, 5))
|
|
B = 2
|
|
C = range(5)
|
|
cond = np.ones(A.shape)
|
|
[_A1, B1, _C1] = argsreduce(cond, A, B, C)
|
|
assert_equal(B1.shape, (20,))
|
|
cond[2, :] = 0
|
|
[A2, B2, C2] = argsreduce(cond, A, B, C)
|
|
assert_equal(B2.shape, (15,))
|
|
assert_array_equal(A2,
|
|
np.array([0., 1., 2., 3., 4., 5., 6., 7.,
|
|
8., 9., 15., 16., 17., 18., 19.]))
|
|
assert_array_equal(
|
|
B2, np.array([2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2]))
|
|
assert_array_equal(
|
|
C2, np.array([0, 1, 2, 3, 4, 0, 1, 2, 3, 4, 0, 1, 2, 3, 4]))
|
|
|
|
|
|
def test_stirlerr():
|
|
assert_array_almost_equal(stirlerr(range(5)),
|
|
np.array([np.inf, 0.08106147, 0.0413407,
|
|
0.02767793, 0.02079067]))
|
|
|
|
|
|
def test_parse_kwargs():
|
|
opt = dict(arg1=1, arg2=3)
|
|
opt = parse_kwargs(opt, arg1=5)
|
|
assert(opt['arg1'] == 5)
|
|
assert(opt['arg2'] == 3)
|
|
opt2 = dict(arg3=15)
|
|
|
|
opt = parse_kwargs(opt, **opt2)
|
|
assert('arg3' not in opt)
|
|
|
|
|
|
def test_getshipchar():
|
|
sc = getshipchar(service_speed=10)
|
|
true_sc = dict(beam=29,
|
|
beamSTD=2.9,
|
|
draught=9.6,
|
|
draughtSTD=2.112,
|
|
length=216,
|
|
lengthSTD=2.011309883194276,
|
|
max_deadweight=30969,
|
|
max_deadweightSTD=3096.9,
|
|
propeller_diameter=6.761165385916601,
|
|
propeller_diameterSTD=0.20267047566705432,
|
|
service_speed=10,
|
|
service_speedSTD=0)
|
|
|
|
for name, val in iteritems(true_sc):
|
|
assert_almost_equal(val, sc[name])
|
|
|
|
|
|
def test_betaloge():
|
|
assert_array_almost_equal(betaloge(3, arange(4)),
|
|
np.array([np.inf, -1.09861229, -2.48490665,
|
|
-3.40119738]))
|
|
|
|
|
|
def test_gravity():
|
|
phi = linspace(0, 45, 5)
|
|
assert_array_almost_equal(gravity(phi),
|
|
np.array([9.78049, 9.78245014, 9.78803583,
|
|
9.79640552, 9.80629387]))
|
|
|
|
|
|
def test_nextpow2():
|
|
assert_equal(nextpow2(10), 4)
|
|
assert_equal(nextpow2(np.arange(5)), 3)
|
|
|
|
|
|
def test_discretize():
|
|
x, y = discretize(np.cos, 0, np.pi, tol=0.01)
|
|
assert_array_almost_equal(
|
|
x,
|
|
np.array(
|
|
[0., 0.19634954, 0.39269908, 0.58904862, 0.78539816,
|
|
0.9817477, 1.17809725, 1.37444679, 1.57079633, 1.76714587,
|
|
1.96349541, 2.15984495, 2.35619449, 2.55254403, 2.74889357,
|
|
2.94524311, 3.14159265]))
|
|
assert_array_almost_equal(
|
|
y, np.array([1.00000000e+00, 9.80785280e-01,
|
|
9.23879533e-01,
|
|
8.31469612e-01, 7.07106781e-01, 5.55570233e-01,
|
|
3.82683432e-01, 1.95090322e-01, 6.12323400e-17,
|
|
-1.95090322e-01, -3.82683432e-01, -5.55570233e-01,
|
|
-7.07106781e-01, -8.31469612e-01, -9.23879533e-01,
|
|
-9.80785280e-01, -1.00000000e+00]))
|
|
|
|
|
|
def test_discretize_adaptive():
|
|
x, y = discretize(np.cos, 0, np.pi, method='adaptive')
|
|
assert_array_almost_equal(
|
|
x,
|
|
np.array(
|
|
[0., 0.19634954, 0.39269908, 0.58904862, 0.78539816,
|
|
0.9817477, 1.17809725, 1.37444679, 1.57079633, 1.76714587,
|
|
1.96349541, 2.15984495, 2.35619449, 2.55254403, 2.74889357,
|
|
2.94524311, 3.14159265]))
|
|
assert_array_almost_equal(
|
|
y,
|
|
np.array(
|
|
[1.00000000e+00, 9.80785280e-01, 9.23879533e-01,
|
|
8.31469612e-01, 7.07106781e-01, 5.55570233e-01,
|
|
3.82683432e-01, 1.95090322e-01, 6.12323400e-17,
|
|
-1.95090322e-01, -3.82683432e-01, -5.55570233e-01,
|
|
-7.07106781e-01, -8.31469612e-01, -9.23879533e-01,
|
|
-9.80785280e-01, -1.00000000e+00]))
|
|
|
|
|
|
def test_polar2cart_n_cart2polar():
|
|
r = 5
|
|
t = linspace(0, pi, 20)
|
|
x, y = polar2cart(t, r)
|
|
assert_array_almost_equal(
|
|
x,
|
|
np.array(
|
|
[5., 4.93180652, 4.72908621, 4.39736876, 3.94570255,
|
|
3.38640786, 2.73474079, 2.00847712, 1.22742744, 0.41289673,
|
|
-0.41289673, -1.22742744, -2.00847712, -2.73474079, -3.38640786,
|
|
-3.94570255, -4.39736876, -4.72908621, -4.93180652, -5.]))
|
|
assert_array_almost_equal(
|
|
y,
|
|
np.array(
|
|
[0.00000000e+00, 8.22972951e-01, 1.62349735e+00,
|
|
2.37973697e+00, 3.07106356e+00, 3.67861955e+00,
|
|
4.18583239e+00, 4.57886663e+00, 4.84700133e+00,
|
|
4.98292247e+00, 4.98292247e+00, 4.84700133e+00,
|
|
4.57886663e+00, 4.18583239e+00, 3.67861955e+00,
|
|
3.07106356e+00, 2.37973697e+00, 1.62349735e+00,
|
|
8.22972951e-01, 6.12323400e-16]))
|
|
ti, ri = cart2polar(x, y)
|
|
assert_array_almost_equal(
|
|
ti,
|
|
np.array(
|
|
[0., 0.16534698, 0.33069396, 0.49604095, 0.66138793,
|
|
0.82673491, 0.99208189, 1.15742887, 1.32277585, 1.48812284,
|
|
1.65346982, 1.8188168, 1.98416378, 2.14951076, 2.31485774,
|
|
2.48020473, 2.64555171, 2.81089869, 2.97624567, 3.14159265]))
|
|
assert_array_almost_equal(
|
|
ri,
|
|
np.array(
|
|
[5., 5., 5., 5., 5., 5., 5., 5., 5., 5., 5., 5., 5.,
|
|
5., 5., 5., 5., 5., 5., 5.]))
|
|
|
|
|
|
def test_tranproc():
|
|
import wafo.transform.models as wtm
|
|
tr = wtm.TrHermite()
|
|
x = linspace(-5, 5, 501)
|
|
g = tr(x)
|
|
y0, y1 = tranproc(x, g, range(5), ones(5))
|
|
assert_array_almost_equal(
|
|
y0,
|
|
np.array([0.02659612, 1.00115284, 1.92872532,
|
|
2.81453257, 3.66292878]))
|
|
assert_array_almost_equal(
|
|
y1,
|
|
np.array([1.00005295, 0.9501118, 0.90589954,
|
|
0.86643821, 0.83096482]))
|
|
|
|
|
|
class TestPiecewise(TestCase):
|
|
|
|
def test_condition_is_single_bool_list(self):
|
|
assert_raises(ValueError, piecewise, [True, False], [1], [0, 0])
|
|
|
|
def test_condition_is_list_of_single_bool_list(self):
|
|
x = piecewise([[True, False]], [1], [0, 0])
|
|
assert_array_equal(x, [1, 0])
|
|
|
|
def test_conditions_is_list_of_single_bool_array(self):
|
|
x = piecewise([np.array([True, False])], [1], [0, 0])
|
|
assert_array_equal(x, [1, 0])
|
|
|
|
def test_condition_is_single_int_array(self):
|
|
assert_raises(ValueError, piecewise, np.array([1, 0]), [1], [0, 0])
|
|
|
|
def test_condition_is_list_of_single_int_array(self):
|
|
x = piecewise([np.array([1, 0])], [1], [0, 0])
|
|
assert_array_equal(x, [1, 0])
|
|
|
|
def test_simple(self):
|
|
x = piecewise([[False, True]], [lambda x:-1], [0, 0])
|
|
assert_array_equal(x, [0, -1])
|
|
|
|
x = piecewise([[True, False], [False, True]], [3, 4], [1, 2])
|
|
assert_array_equal(x, [3, 4])
|
|
|
|
def test_default(self):
|
|
# No value specified for x[1], should be 0
|
|
x = piecewise([[True, False]], [2], [1, 2],)
|
|
assert_array_equal(x, [2, 0])
|
|
|
|
# Should set x[1] to 3
|
|
x = piecewise([[True, False]], [2, 3], [1, 2])
|
|
assert_array_equal(x, [2, 3])
|
|
|
|
def test_0d(self):
|
|
x = np.array(3)
|
|
y = piecewise([x > 3], [4, 0], x)
|
|
assert_(y.ndim == 0)
|
|
assert_(y == 0)
|
|
|
|
x = 5
|
|
y = piecewise([[True], [False]], [1, 0], x)
|
|
assert_(y == 1)
|
|
assert_(y.ndim == 0)
|
|
|
|
def test_abs_function(self):
|
|
x = np.linspace(-2.5, 2.5, 6)
|
|
vals = piecewise([x < 0, x >= 0], [lambda x: -x, lambda x: x], (x,))
|
|
assert_array_equal(vals,
|
|
[2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
|
|
|
|
def test_abs_function_with_scalar(self):
|
|
x = np.array(-2.5)
|
|
vals = piecewise([x < 0, x >= 0], [lambda x: -x, lambda x: x], (x,))
|
|
assert_(vals == 2.5)
|
|
|
|
def test_otherwise_condition(self):
|
|
x = np.linspace(-2.5, 2.5, 6)
|
|
vals = piecewise([x < 0, ], [lambda x: -x, lambda x: x], (x,))
|
|
assert_array_equal(vals, [2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
|
|
|
|
def test_passing_further_args_to_fun(self):
|
|
def fun0(x, y, scale=1.):
|
|
return -x * y / scale
|
|
|
|
def fun1(x, y, scale=1.):
|
|
return x * y / scale
|
|
x = np.linspace(-2.5, 2.5, 6)
|
|
vals = piecewise([x < 0, ], [fun0, fun1], (x,), args=(2.,), scale=2.)
|
|
assert_array_equal(vals, [2.5, 1.5, 0.5, 0.5, 1.5, 2.5])
|
|
|
|
def test_step_function(self):
|
|
x = np.linspace(-2.5, 2.5, 6)
|
|
vals = piecewise([x < 0, x >= 0], [-1, 1], x)
|
|
assert_array_equal(vals, [-1., -1., -1., 1., 1., 1.])
|
|
|
|
def test_step_function_with_scalar(self):
|
|
x = 1
|
|
vals = piecewise([x < 0, x >= 0], [-1, 1], x)
|
|
assert_(vals == 1)
|
|
|
|
def test_function_with_two_args(self):
|
|
x = np.linspace(-2, 2, 5)
|
|
X, Y = np.meshgrid(x, x)
|
|
vals = piecewise(
|
|
[X * Y < 0, ], [lambda x, y: -x * y, lambda x, y: x * y], (X, Y))
|
|
assert_array_equal(vals, [[4., 2., -0., 2., 4.],
|
|
[2., 1., -0., 1., 2.],
|
|
[-0., -0., 0., 0., 0.],
|
|
[2., 1., 0., 1., 2.],
|
|
[4., 2., 0., 2., 4.]])
|
|
|
|
def test_fill_value_and_function_with_two_args(self):
|
|
x = np.linspace(-2, 2, 5)
|
|
X, Y = np.meshgrid(x, x)
|
|
vals = piecewise([X * Y < -0.5, X * Y > 0.5],
|
|
[lambda x, y: -x * y, lambda x, y: x * y], (X, Y),
|
|
fill_value=np.nan)
|
|
nan = np.nan
|
|
assert_array_equal(vals, [[4., 2., nan, 2., 4.],
|
|
[2., 1., nan, 1., 2.],
|
|
[nan, nan, nan, nan, nan],
|
|
[2., 1., nan, 1., 2.],
|
|
[4., 2., nan, 2., 4.]])
|
|
|
|
def test_fill_value2_and_function_with_two_args(self):
|
|
x = np.linspace(-2, 2, 5)
|
|
X, Y = np.meshgrid(x, x)
|
|
vals = piecewise([X * Y < -0.5, X * Y > 0.5],
|
|
[lambda x, y: -x * y, lambda x, y: x * y, np.nan],
|
|
(X, Y))
|
|
nan = np.nan
|
|
assert_array_equal(vals, [[4., 2., nan, 2., 4.],
|
|
[2., 1., nan, 1., 2.],
|
|
[nan, nan, nan, nan, nan],
|
|
[2., 1., nan, 1., 2.],
|
|
[4., 2., nan, 2., 4.]])
|
|
|
|
|
|
class TestRotationMatrix(TestCase):
|
|
|
|
def test_h0_p0_r0(self):
|
|
vals = rotation_matrix(heading=0, pitch=0, roll=0).tolist()
|
|
truevals = [[1., 0., 0.],
|
|
[0., 1., 0.],
|
|
[0., 0., 1.]]
|
|
self.assertListEqual(vals, truevals)
|
|
|
|
def test_h180_p0_r0(self):
|
|
vals = rotation_matrix(heading=180, pitch=0, roll=0).tolist()
|
|
truevals = [[-1.0, -1.2246467991473532e-16, 0.0],
|
|
[1.2246467991473532e-16, -1.0, 0.0],
|
|
[-0.0, 0.0, 1.0]]
|
|
self.assertListEqual(vals, truevals)
|
|
|
|
def test_h0_p180_r0(self):
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vals = rotation_matrix(heading=0, pitch=180, roll=0).tolist()
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truevals = [[-1.0, 0.0, 1.2246467991473532e-16],
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|
[-0.0, 1.0, 0.0],
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|
[-1.2246467991473532e-16, -0.0, -1.0]]
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self.assertListEqual(vals, truevals)
|
|
|
|
def test_h0_p0_r180(self):
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|
vals = rotation_matrix(heading=0, pitch=180, roll=0).tolist()
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truevals = [[-1.0, 0.0, 1.2246467991473532e-16],
|
|
[-0.0, 1.0, 0.0],
|
|
[-1.2246467991473532e-16, -0.0, -1.0]]
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|
self.assertListEqual(vals, truevals)
|
|
|
|
|
|
class TestRotate2d(TestCase):
|
|
|
|
def test_rotate_0deg(self):
|
|
vals = list(rotate_2d(x=1, y=0, angle_deg=0))
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|
truevals = [1.0, 0.0]
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|
self.assertListEqual(vals, truevals)
|
|
|
|
def test_rotate_90deg(self):
|
|
vals = list(rotate_2d(x=1, y=0, angle_deg=90))
|
|
truevals = [6.123233995736766e-17, 1.0]
|
|
self.assertListEqual(vals, truevals)
|
|
|
|
def test_rotate_180deg(self):
|
|
vals = list(rotate_2d(x=1, y=0, angle_deg=180))
|
|
truevals = [-1.0, 1.2246467991473532e-16]
|
|
self.assertListEqual(vals, truevals)
|
|
|
|
def test_rotate_360deg(self):
|
|
vals = list(rotate_2d(x=1, y=0, angle_deg=360))
|
|
truevals = [1.0, -2.4492935982947064e-16]
|
|
self.assertListEqual(vals, truevals)
|
|
|
|
|
|
class TestSpaceLine(TestCase):
|
|
|
|
def test_space_line(self):
|
|
vals = spaceline((2, 0, 0), (3, 0, 0), num=5).tolist()
|
|
truevals = [[2., 0., 0.],
|
|
[2.25, 0., 0.],
|
|
[2.5, 0., 0.],
|
|
[2.75, 0., 0.],
|
|
[3., 0., 0.]]
|
|
self.assertListEqual(vals, truevals)
|
|
|
|
|
|
class TestArgsFlat(TestCase):
|
|
|
|
def test_1_vector_and_2_scalar_args(self):
|
|
x = [1, 2, 3]
|
|
pos, c_shape = args_flat(x, 2, 3)
|
|
truepos = [[1, 2, 3],
|
|
[2, 2, 3],
|
|
[3, 2, 3]]
|
|
truec_shape = [3, ]
|
|
self.assertListEqual(pos.tolist(), truepos)
|
|
self.assertListEqual(list(c_shape), truec_shape)
|
|
|
|
def test_1_vector_args(self):
|
|
pos1, c_shape1 = args_flat([1, 2, 3])
|
|
truepos1 = [[1, 2, 3]]
|
|
truec_shape1 = None
|
|
self.assertListEqual(pos1.tolist(), truepos1)
|
|
self.assertIs(c_shape1, truec_shape1)
|
|
|
|
def test_3_scalar_args(self):
|
|
pos1, c_shape1 = args_flat(1, 2, 3)
|
|
truepos1 = [[1, 2, 3]]
|
|
truec_shape1 = []
|
|
self.assertListEqual(pos1.tolist(), truepos1)
|
|
self.assertListEqual(list(c_shape1), truec_shape1)
|
|
|
|
def test_3_scalar_args_version2(self):
|
|
pos1, c_shape1 = args_flat([1], 2, 3)
|
|
truepos1 = [[1, 2, 3]]
|
|
truec_shape1 = [1, ]
|
|
self.assertListEqual(pos1.tolist(), truepos1)
|
|
self.assertListEqual(list(c_shape1), truec_shape1)
|
|
|
|
|
|
class TestSub2index2Sub(TestCase):
|
|
|
|
def test_sub2index_and_index2sub(self):
|
|
shape = (3, 3, 4)
|
|
a = np.arange(np.prod(shape)).reshape(shape)
|
|
trueval = a[1, 2, 3]
|
|
order = 'C'
|
|
i = sub2index(shape, 1, 2, 3, order=order)
|
|
self.assertEquals(i, 23)
|
|
|
|
val = a.ravel(order)[i]
|
|
self.assertEquals(val, trueval)
|
|
|
|
sub = index2sub(shape, i, order=order)
|
|
for j, true_sub_j in enumerate([1, 2, 3]):
|
|
self.assertEquals(sub[j].tolist(), true_sub_j)
|
|
|
|
if __name__ == '__main__':
|
|
run_module_suite()
|