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191 lines
8.4 KiB
Python
191 lines
8.4 KiB
Python
# -*- coding:utf-8 -*-
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"""
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Created on 5. aug. 2010
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@author: pab
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"""
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import unittest
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from numpy.testing import TestCase, assert_array_almost_equal
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import wafo.data
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import wafo.objects as wo
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import wafo.spectrum.models as sm
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import wafo.transform.models as tm
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class TestTimeSeries(TestCase):
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def setUp(self):
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x = wafo.data.sea()
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self.ts = wo.mat2timeseries(x)
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def test_sampling_period(self):
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ts = self.ts
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assert_array_almost_equal(ts.sampling_period(), 0.25)
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def test_tospecdata(self):
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S = self.ts.tospecdata(L=150)
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print(S.data[:10].tolist())
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assert_array_almost_equal(S.data[:10],
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[0.0050789888306202345, 0.0049411187454784225,
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0.004553923924951667, 0.003990722577978725,
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0.00335482379127744, 0.002755110296973988,
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0.002281782794825119, 0.0019941282234629933,
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0.0019329154962902488, 0.002164040256079313])
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# [0.00913087, 0.00881073, 0.00791944,
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# 0.00664244, 0.00522429, 0.00389816,
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# 0.00282753, 0.00207843, 0.00162678,
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# 0.0013916])
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def test_tocovdata(self):
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rf = self.ts.tocovdata(lag=150)
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assert_array_almost_equal(rf.data[:10],
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[0.22368637, 0.20838473, 0.17110733,
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0.12237803, 0.07024054, 0.02064859,
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-0.02218831, -0.0555993, -0.07859847,
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-0.09166187])
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def test_timeseries_trdata(self):
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Hs = 7.0
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Sj = sm.Jonswap(Hm0=Hs)
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S = Sj.tospecdata() # Make spectrum object from numerical values
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S.tr = tm.TrOchi(mean=0, skew=0.16, kurt=0, sigma=Hs/4, ysigma=Hs/4)
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xs = S.sim(ns=2**20, iseed=10)
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ts = wo.mat2timeseries(xs)
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g0, _gemp = ts.trdata(monitor=False) # Not Monitor the development
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# Equal weight on all points
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g1, _gemp = ts.trdata(method='mnonlinear', gvar=0.5)
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# Less weight on the ends
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g2, _gemp = ts.trdata(method='nonlinear', gvar=[3.5, 0.5, 3.5])
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self.assert_(1.2 < S.tr.dist2gauss() < 1.6)
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self.assert_(1.65 < g0.dist2gauss() < 2.05)
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self.assert_(0.54 < g1.dist2gauss() < 0.95)
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self.assert_(1.5 < g2.dist2gauss() < 1.9)
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def test_timeseries_wave_periods(self):
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true_t = ([-0.69, -0.86, -1.05],
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[0.42, 0.78, 1.37],
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[0.09, 0.51, -0.85],
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[-0.27, -0.08, 0.32],
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[3.84377468, 6.35707656, 4.15490909],
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[6.25273295, 6.10295202, 3.36978685],
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[2.48364668, 4.74282402, 1.75553431],
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[3.76908628, 1.360128, 1.61425254],
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[-5.05027968, -9.16405436, -15.60113092],
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[7.53392635, 13.90687837, 17.35666522],
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[-0.2811934, -7.11392635, -13.12687837],
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[4.05027968, 8.47405436, 14.74113092],
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[2.03999996, 0.07, 0.05],
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[-0.93, -0.07, -0.12],
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[1.10999996, 0., -0.07],
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[-0.86, -0.02, 0.3],
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[0.93, -0.8, -0.2],
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[1.10999996, 0., -0.07],
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[-0.02, 0.3, -0.34],
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[6.10295202, 3.36978685, 3.58501107],
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[6.25273295, 6.10295202, 3.36978685],
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)
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pdefs = ['t2c', 'c2t', 't2t', 'c2c',
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'd2d', 'u2u', 'd2u', 'u2d',
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'd2t', 't2u', 'u2c', 'c2d',
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'm2M', 'M2m', 'm2m', 'M2M', 'all',
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]
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ts = wo.TimeSeries(self.ts.data[0:400, :2], self.ts.args[:400])
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for pdef, truth in zip(pdefs, true_t):
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T, _ix = ts.wave_periods(vh=0.0, pdef=pdef)
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# print(T[:3,])
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assert_array_almost_equal(T[:3], truth)
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true_t2 = ([1.10999996, 0., - 0.07],
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[-0.02, 0.3, - 0.34],
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[6.10295202, 3.369787, 3.585011],
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[6.25273295, 6.102952, 3.369787],
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[-0.27, -0.08, 0.32],
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[-0.27, -0.08, 0.32])
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wdefs = ['mw', 'Mw', 'dw', 'uw', 'tw', 'cw', ]
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for wdef, truth in zip(wdefs, true_t2):
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pdef = '{0}2{0}'.format(wdef[0].lower())
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T, _ix = ts.wave_periods(vh=0.0, pdef=pdef, wdef=wdef)
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print(T[:3])
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assert_array_almost_equal(T[:3], truth)
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class TestObjects(TestCase):
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def setUp(self):
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x = wafo.data.sea()
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self.ts = wo.mat2timeseries(x)
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def test_cycles_and_levelcrossings(self):
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tp = self.ts.turning_points()
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assert_array_almost_equal(tp.data[:10],
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[-1.200495, 0.839505, -0.090495, -0.020495,
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-0.090495, -0.040495, -0.160495, 0.259505,
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-0.430495, -0.080495]
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)
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mm = tp.cycle_pairs()
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assert_array_almost_equal(mm.data[:10],
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[0.839505, -0.020495, -0.040495, 0.259505,
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-0.080495, -0.080495, 0.349505, 0.859505,
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0.009505, 0.319505])
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true_lcs = (([0., 1., 2., 2., 3., 4., 5., 6., 7., 9.],
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[-1.7504945, -1.4404945, -1.4204945, -1.4004945,
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-1.3704945, -1.3204945, -1.2704945, -1.2604945,
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-1.2504945, -1.2004945]),
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([0., 1., 2., 3., 3., 4., 5., 6., 7., 9.],
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[-1.7504945, -1.4404945, -1.4204945, -1.4004945,
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-1.3704945, -1.3204945, -1.2704945, -1.2604945,
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-1.2504945, -1.2004945]),
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([1., 2., 3., 4., 4., 5., 6., 7., 9., 11.],
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[-1.7504945, -1.4404945, -1.4204945, -1.4004945,
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-1.3704945, -1.3204945, -1.2704945, -1.2604945,
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-1.2504945, -1.2004945]),
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([1., 2., 3., 3., 4., 5., 6., 7., 9., 11.],
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[-1.7504945, -1.4404945, -1.4204945, -1.4004945,
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-1.3704945, -1.3204945, -1.2704945, -1.2604945,
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-1.2504945, -1.2004945]))
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for i, true_lc in enumerate(true_lcs):
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true_count, true_levels = true_lc
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lc = mm.level_crossings(kind=i+1)
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assert_array_almost_equal(lc.data[:10], true_count)
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assert_array_almost_equal(lc.args[:10], true_levels)
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def test_levelcrossings_extrapolate(self):
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tp = self.ts.turning_points()
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mm = tp.cycle_pairs()
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lc = mm.level_crossings()
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s = lc.sigma # x[:, 1].std()
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ix = slice(0, 1000, 100)
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lc_ray = lc.extrapolate(-2 * s, 2 * s, dist='rayleigh')
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assert_array_almost_equal(lc_ray.data[ix],
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[1.78925398e-37, 9.61028192e-23,
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2.05282628e-11, 1.74389448e-03,
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5.89169345e+01, 5.240000e+02,
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6.72609651e+01, 4.46086175e-01,
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2.23463577e-04, 8.45526153e-09])
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lc_exp = lc.extrapolate(-2 * s, 2 * s, dist='expon')
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lc_gpd = lc.extrapolate(-2 * s, 2 * s, dist='genpareto')
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assert_array_almost_equal(lc_exp.data[ix],
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[6.51864195e-12, 1.13025876e-08,
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1.95974080e-05, 3.39796881e-02,
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5.89169345e+01, 5.24000000e+02,
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6.43476951e+01, 1.13478843e+00,
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2.00122906e-02, 3.52921977e-04])
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assert_array_almost_equal(lc_gpd.data[ix],
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[0.00000000e+00, 0.00000000e+00,
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0.00000000e+00, 0.00000000e+00,
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5.89169345e+01, 5.24000000e+02,
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6.80484770e+01, 1.41019390e-01,
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0.00000000e+00, 0.00000000e+00])
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if __name__ == "__main__":
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# import sys;sys.argv = ['', 'Test.testName']
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unittest.main()
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