def test_rfcfilter():
# 1. Filtered signal y is the turning points of x.
x = sea()
y = rfcfilter(x[:, 1], h=0.0, method=1)
assert_array_almost_equal(
y[0:5],
np.array([-1.2004945, 0.83950546, -0.09049454,
-0.02049454, -0.09049454]))
# 2. This removes all rainflow cycles with range less than 0.5.
y1 = rfcfilter(x[:, 1], h=0.5, method=0)
assert_array_almost_equal(
y1[0:5],
np.array([-1.2004945, 0.83950546, -0.43049454,
0.34950546, -0.51049454]))
# return
t = linspace(0, 7 * pi, 250)
x = sin(t) + 0.1 * sin(50 * t)
ind = findextrema(x)
assert_array_almost_equal(
ind,
np.array(
[1, 3, 4, 6, 7, 9, 11, 13, 14, 16, 18, 19, 21,
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.]])
def test_rfcfilter():
# 1. Filtered signal y is the turning points of x.
x = sea()
y = rfcfilter(x[:, 1], h=0.0, method=1)
assert_array_almost_equal(
y[0:5],
np.array(
[-1.2004945, 0.83950546, -0.09049454, -0.02049454, -0.09049454]))
# 2. This removes all rainflow cycles with range less than 0.5.
y1 = rfcfilter(x[:, 1], h=0.5, method=0)
assert_array_almost_equal(
y1[0:5],
np.array(
[-1.2004945, 0.83950546, -0.43049454, 0.34950546, -0.51049454]))
# return
t = linspace(0, 7 * pi, 250)
x = sin(t) + 0.1 * sin(50 * t)
ind = findextrema(x)
assert_array_almost_equal(
ind,
np.array([
1, 3, 4, 6, 7, 9, 11, 13, 14, 16, 18, 19, 21, 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.]])
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_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_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_rfcfilter():
# 1. Filtered signal y is the turning points of x.
x = sea()
y = rfcfilter(x[:, 1], h=0, method=1)
assert_array_almost_equal(
y[0:5],
np.array([-1.2004945, 0.83950546, -0.09049454,
-0.02049454, -0.09049454]))
# 2. This removes all rainflow cycles with range less than 0.5.
y1 = rfcfilter(x[:, 1], h=0.5)
assert_array_almost_equal(
y1[0:5],
np.array([-1.2004945, 0.83950546, -0.43049454,
0.34950546, -0.51049454]))
t = linspace(0, 7 * pi, 250)
x = sin(t) + 0.1 * sin(50 * t)
ind = findextrema(x)
assert_array_almost_equal(
ind,
np.array(
[1, 3, 4, 6, 7, 9, 11, 13, 14, 16, 18, 19, 21,
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]))
#! Created by GL July 13, 2000 #! from commands used in Chapter 4 #! #! Chapter 4 Fatigue load analysis and rain-flow cycles #!------------------------------------------------------ printing = 0 #! Section 4.3.1 Crossing intensity #!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import wafo.data as wd import wafo.objects as wo xx_sea = wd.sea() ts = wo.mat2timeseries(xx_sea) tp = ts.turning_points() mM = tp.cycle_pairs(kind="min2max") lc = mM.level_crossings(intensity=True) T_sea = ts.args[-1] - ts.args[0] subplot(1, 2, 1) lc.plot() subplot(1, 2, 2) lc.setplotter(plotmethod="step") lc.plot() show() m_sea = ts.data.mean()
#! Some of the commands are edited for fast computation. #! #! Section 3.2 Estimation of wave characteristics from data #!---------------------------------------------------------- #! Example 1 #!~~~~~~~~~~ speed = 'fast' #speed = 'slow' import scipy.signal as ss import wafo.data as wd import wafo.misc as wm import wafo.objects as wo import wafo.stats as ws import wafo.spectrum.models as wsm xx = wd.sea() xx[:, 1] = ss.detrend(xx[:, 1]) ts = wo.mat2timeseries(xx) Tcrcr, ix = ts.wave_periods(vh=0, pdef='c2c', wdef='tw', rate=8) Tc, ixc = ts.wave_periods(vh=0, pdef='u2d', wdef='tw', rate=8) #! Histogram of crestperiod compared to the kernel density estimate #!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import wafo.kdetools as wk plt.clf() print(Tc.mean()) print(Tc.max()) t = np.linspace(0.01,8,200); ftc = wk.TKDE(Tc, L2=0, inc=128)
#! Some of the commands are edited for fast computation. #! #! Section 3.2 Estimation of wave characteristics from data #!---------------------------------------------------------- #! Example 1 #!~~~~~~~~~~ speed = 'fast' #speed = 'slow' import scipy.signal as ss import wafo.data as wd import wafo.misc as wm import wafo.objects as wo import wafo.stats as ws import wafo.spectrum.models as wsm xx = wd.sea() xx[:, 1] = ss.detrend(xx[:, 1]) ts = wo.mat2timeseries(xx) Tcrcr, ix = ts.wave_periods(vh=0, pdef='c2c', wdef='tw', rate=8) Tc, ixc = ts.wave_periods(vh=0, pdef='u2d', wdef='tw', rate=8) #! Histogram of crestperiod compared to the kernel density estimate #!~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ import wafo.kdetools as wk plt.clf() print(Tc.mean()) print(Tc.max()) t = np.linspace(0.01, 8, 200) ftc = wk.TKDE(Tc, L2=0, inc=128)
