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@ -1187,7 +1187,14 @@ def _findrfc(y, h):
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return ind, ix
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def nt2cmat(nt, kind=11):
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def _raise_kind_error(kind):
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if kind in (-1, 0):
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raise NotImplementedError('kind = {} not yet implemented'.format(kind))
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else:
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raise ValueError('kind = {}: not a valid value of kind'.format(kind))
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def nt2cmat(nt, kind=1):
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"""
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Return cycle matrix from a counting distribution.
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@ -1216,6 +1223,12 @@ def nt2cmat(nt, kind=11):
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... [ 0., 0., 0., 0.]])
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>>> nt = cmat2nt(cmat0)
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>>> np.allclose(nt,
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... [[ 0., 0., 0., 0.],
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... [ 20., 15., 9., 0.],
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... [ 28., 23., 16., 0.],
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... [ 32., 27., 20., 0.]])
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True
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>>> cmat = nt2cmat(nt)
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>>> np.allclose(cmat, [[ 0., 5., 6., 9.],
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... [ 0., 0., 1., 7.],
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@ -1227,47 +1240,64 @@ def nt2cmat(nt, kind=11):
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--------
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cmat2nt
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"""
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n = len(nt) # Number of discrete levels
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cmat = np.zeros((n, n))
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if kind == 1:
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I = np.r_[0:n-1]
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J = np.r_[1:n]
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cmat[I, J] = nt[I+1, J-1] - nt[I, J-1] - nt[I+1, J] + nt[I, J]
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c = nt[I+1][:, J-1] - nt[I][:, J-1] - nt[I+1][:, J] + nt[I][:, J]
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c2 = np.vstack((c, np.zeros((n-1))))
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cmat = np.hstack((np.zeros((n, 1)), c2))
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elif kind == 11: # same as def=1 but using for-loop
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cmat = np.zeros((n, n))
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j = np.r_[1:n]
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for i in range(n-1):
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cmat[i, j] = nt[i+1, j-1] - nt[i, j-1] - nt[i+1, j] + nt[i, j]
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elif kind == 0:
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raise NotImplementedError('kind == 0 not yet implemented')
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elif kind == -1:
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raise NotImplementedError('kind == -1 not yet implemented')
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else:
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raise ValueError('kind = {}: not a valid value of kind'.format(kind))
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_raise_kind_error(kind)
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return cmat
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def cmat2nt(cmat, kind=11):
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def cmat2nt(cmat, kind=1):
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"""
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CMAT2NT Calculates a counting distribution from a cycle matrix.
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CALL: NT = cmat2nt(F,def);
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NT = Counting distribution. [nxn]
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cmat = Cycle matrix. [nxn]
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Parameters
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----------
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cmat = Cycle matrix. [nxn]
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kind = 1: causes peaks to be projected upwards and troughs
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downwards to the closest discrete level (default).
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= 0: causes peaks and troughs to be projected to
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the closest discrete level.
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= -1: causes peaks to be projected downwards and the
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troughs upwards to the closest discrete level.
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Returns
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-------
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NT: n x n array
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Counting distribution.
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Example
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-------
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F = round(triu(rand(4),1)*10)
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NT = cmat2nt(F)
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>>> import numpy as np
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>>> cmat0 = np.round(np.triu(np.random.rand(4, 4), 1)*10)
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>>> cmat0 = np.array([[ 0., 5., 6., 9.],
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... [ 0., 0., 1., 7.],
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... [ 0., 0., 0., 4.],
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... [ 0., 0., 0., 0.]])
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>>> nt = cmat2nt(cmat0, kind=11)
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>>> np.allclose(nt,
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... [[ 0., 0., 0., 0.],
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... [ 20., 15., 9., 0.],
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... [ 28., 23., 16., 0.],
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... [ 32., 27., 20., 0.]])
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True
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>>> cmat = nt2cmat(nt, kind=11)
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>>> np.allclose(cmat, [[ 0., 5., 6., 9.],
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... [ 0., 0., 1., 7.],
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... [ 0., 0., 0., 4.],
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... [ 0., 0., 0., 0.]])
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True
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See also
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--------
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@ -1275,21 +1305,18 @@ def cmat2nt(cmat, kind=11):
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"""
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n = len(cmat) # Number of discrete levels
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nt = zeros((n, n))
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if kind == 1:
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nt[1:n, :n-1] = np.fliplr(np.cumsum(np.fliplr(np.cumsum(cmat[:-1,
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1:])),
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axis=1))
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csum = np.cumsum
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flip = np.fliplr
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nt[1:n, :n-1] = flip(csum(flip(csum(cmat[:-1, 1:], axis=0)), axis=1))
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elif kind == 11: # same as def=1 but using for-loop
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# j = np.r_[1:n]
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for i in range(1, n):
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for j in range(n-1):
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nt[i, j] = np.sum(np.sum(cmat[:i, j+1:n]))
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elif kind == 0:
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raise NotImplementedError('kind == 0 not yet implemented')
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elif kind == -1:
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raise NotImplementedError('kind == -1 not yet implemented')
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nt[i, j] = np.sum(cmat[:i, j+1:n])
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else:
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raise ValueError('kind = {}: not a valid value of kind'.format(kind))
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_raise_kind_error(kind)
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return nt
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@ -1564,57 +1591,7 @@ def mctp2rfc(fmM, fMm=None):
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return f_rfc
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def rfcfilter(x, h, method=0):
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"""
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Rainflow filter a signal.
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Parameters
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-----------
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x : vector
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Signal. [nx1]
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h : real, scalar
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Threshold for rainflow filter.
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method : scalar, integer
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0 : removes cycles with range < h. (default)
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1 : removes cycles with range <= h.
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Returns
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--------
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y = Rainflow filtered signal.
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Examples:
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---------
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# 1. Filtered signal y is the turning points of x.
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>>> import wafo.data as data
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>>> import wafo.misc as wm
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>>> x = data.sea()
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>>> y = wm.rfcfilter(x[:,1], h=0, method=1)
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>>> np.all(np.abs(y[0:5]-np.array([-1.2004945 , 0.83950546, -0.09049454,
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... -0.02049454, -0.09049454]))<1e-7)
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True
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>>> y.shape
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(2172,)
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# 2. This removes all rainflow cycles with range less than 0.5.
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>>> y1 = wm.rfcfilter(x[:,1], h=0.5)
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>>> y1.shape
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(863,)
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>>> np.all(np.abs(y1[0:5]-np.array([-1.2004945 , 0.83950546, -0.43049454,
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... 0.34950546, -0.51049454]))<1e-7)
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True
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>>> ind = wm.findtp(x[:,1], h=0.5)
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>>> y2 = x[ind,1]
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>>> y2[0:5]
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array([-1.2004945 , 0.83950546, -0.43049454, 0.34950546, -0.51049454])
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>>> y2[-5::]
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array([ 0.83950546, -0.64049454, 0.65950546, -1.0004945 , 0.91950546])
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See also
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--------
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findrfc
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"""
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# TODO merge rfcfilter and findrfc
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y = atleast_1d(x).ravel()
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def _findrfc2(y, h, method):
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n = len(y)
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t = zeros(n, dtype=np.int)
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j = 0
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@ -1622,18 +1599,18 @@ def rfcfilter(x, h, method=0):
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y0 = y[t0]
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z0 = 0
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def aleb(a, b):
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def a_le_b(a, b):
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return a <= b
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def altb(a, b):
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def a_lt_b(a, b):
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return a < b
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if method == 0:
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cmpfun1 = aleb
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cmpfun2 = altb
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cmpfun1 = a_le_b
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cmpfun2 = a_lt_b
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else:
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cmpfun1 = altb
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cmpfun2 = aleb
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cmpfun1 = a_lt_b
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cmpfun2 = a_le_b
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# The rainflow filter
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for tim1, yi in enumerate(y[1::]):
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@ -1683,7 +1660,62 @@ def rfcfilter(x, h, method=0):
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if cmpfun1(h, abs(y0 - y[t[j]])):
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j += 1
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t[j] = t0
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return y[t[:j + 1]]
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return t[:j + 1]
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def rfcfilter(x, h, method=0):
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"""
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Rainflow filter a signal.
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Parameters
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-----------
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x : vector
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Signal. [nx1]
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h : real, scalar
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Threshold for rainflow filter.
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method : scalar, integer
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0 : removes cycles with range < h. (default)
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1 : removes cycles with range <= h.
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Returns
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--------
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y = Rainflow filtered signal.
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Examples:
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---------
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# 1. Filtered signal y is the turning points of x.
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>>> import wafo.data as data
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>>> import wafo.misc as wm
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>>> x = data.sea()
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>>> y = wm.rfcfilter(x[:,1], h=0, method=1)
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>>> np.all(np.abs(y[0:5]-np.array([-1.2004945 , 0.83950546, -0.09049454,
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... -0.02049454, -0.09049454]))<1e-7)
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True
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>>> y.shape
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(2172,)
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# 2. This removes all rainflow cycles with range less than 0.5.
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>>> y1 = wm.rfcfilter(x[:,1], h=0.5)
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>>> y1.shape
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(863,)
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>>> np.all(np.abs(y1[0:5]-np.array([-1.2004945 , 0.83950546, -0.43049454,
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... 0.34950546, -0.51049454]))<1e-7)
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True
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>>> ind = wm.findtp(x[:,1], h=0.5)
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>>> y2 = x[ind,1]
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>>> y2[0:5]
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array([-1.2004945 , 0.83950546, -0.43049454, 0.34950546, -0.51049454])
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>>> y2[-5::]
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array([ 0.83950546, -0.64049454, 0.65950546, -1.0004945 , 0.91950546])
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See also
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--------
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findrfc
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"""
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# TODO merge rfcfilter and findrfc
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y = atleast_1d(x).ravel()
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ix = _findrfc2(y, h, method)
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return y[ix]
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def findtp(x, h=0.0, kind=None):
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pbrod
9 years ago