Simplified

master
Per A Brodtkorb 8 years ago
parent df22be4e17
commit efef019e91

@ -9,13 +9,23 @@ import numpy as np
from wafo.misc import lazywhere from wafo.misc import lazywhere
from numpy import (atleast_1d, sqrt, ones_like, zeros_like, arctan2, where, from numpy import (atleast_1d, sqrt, ones_like, zeros_like, arctan2, where,
tanh, sin, cos, sign, inf, tanh, sin, cos, sign, inf,
flatnonzero, finfo, cosh, abs) flatnonzero, finfo, cosh)
__all__ = ['k2w', 'w2k'] __all__ = ['k2w', 'w2k']
def _assert(cond, msg):
if not cond:
raise ValueError(msg)
def _assert_warn(cond, msg):
if not cond:
warnings.warn(msg)
def k2w(k1, k2=0e0, h=inf, g=9.81, u1=0e0, u2=0e0): def k2w(k1, k2=0e0, h=inf, g=9.81, u1=0e0, u2=0e0):
''' Translates from wave number to frequency """ Translates from wave number to frequency
using the dispersion relation using the dispersion relation
Parameters Parameters
@ -61,7 +71,7 @@ def k2w(k1, k2=0e0, h=inf, g=9.81, u1=0e0, u2=0e0):
array([ 0.3132092 , 1.43530485, 2.00551739]) array([ 0.3132092 , 1.43530485, 2.00551739])
>>> wsd.k2w(arange(0.01,.5,0.2),h=20)[0] >>> wsd.k2w(arange(0.01,.5,0.2),h=20)[0]
array([ 0.13914927, 1.43498213, 2.00551724]) array([ 0.13914927, 1.43498213, 2.00551724])
''' """
k1i, k2i, hi, gi, u1i, u2i = atleast_1d(k1, k2, h, g, u1, u2) k1i, k2i, hi, gi, u1i, u2i = atleast_1d(k1, k2, h, g, u1, u2)
@ -75,21 +85,19 @@ def k2w(k1, k2=0e0, h=inf, g=9.81, u1=0e0, u2=0e0):
k = sqrt(k1i ** 2 + k2i ** 2) k = sqrt(k1i ** 2 + k2i ** 2)
w = where(k > 0, ku1 + ku2 + sqrt(gi * k * tanh(k * hi)), 0.0) w = where(k > 0, ku1 + ku2 + sqrt(gi * k * tanh(k * hi)), 0.0)
cond = (w < 0) cond = (0 <= w)
if np.any(cond): _assert_warn(np.all(cond), """
txt0 = ''' Waves and current are in opposite directions
Waves and current are in opposite directions making some of the frequencies negative.
making some of the frequencies negative. Here we are forcing the negative frequencies to zero.
Here we are forcing the negative frequencies to zero. """)
'''
warnings.warn(txt0)
w = where(cond, 0.0, w) # force w to zero
w = where(cond, w, 0.0) # force w to zero
return w, theta return w, theta
def w2k(w, theta=0.0, h=inf, g=9.81, count_limit=100): def w2k(w, theta=0.0, h=inf, g=9.81, count_limit=100):
''' """
Translates from frequency to wave number Translates from frequency to wave number
using the dispersion relation using the dispersion relation
@ -136,7 +144,7 @@ def w2k(w, theta=0.0, h=inf, g=9.81, count_limit=100):
See also See also
-------- --------
k2w k2w
''' """
wi, th, hi, gi = atleast_1d(w, theta, h, g) wi, th, hi, gi = atleast_1d(w, theta, h, g)
if wi.size == 0: if wi.size == 0:
@ -147,10 +155,8 @@ def w2k(w, theta=0.0, h=inf, g=9.81, count_limit=100):
k2 = k * sin(th) * gi[0] / gi[-1] # size np x nf k2 = k * sin(th) * gi[0] / gi[-1] # size np x nf
k1 = k * cos(th) k1 = k * cos(th)
return k1, k2 return k1, k2
_assert(gi.size == 1, 'Finite depth in combination with 3D normalization'
if gi.size > 1: ' (len(g)=2) is not implemented yet.')
raise ValueError('Finite depth in combination with 3D normalization' +
' (len(g)=2) is not implemented yet.')
find = flatnonzero find = flatnonzero
eps = finfo(float).eps eps = finfo(float).eps
@ -193,9 +199,8 @@ def w2k(w, theta=0.0, h=inf, g=9.81, count_limit=100):
np.abs(hn) > sqrt(eps)) np.abs(hn) > sqrt(eps))
count += 1 count += 1
if count == count_limit: _assert_warn(count < count_limit, 'W2K did not converge. '
warnings.warn('W2K did not converge. The maximum error in the ' + 'Maximum error in the last step was: %13.8f' % max(hn[ix]))
'last step was: %13.8f' % max(hn[ix]))
k.shape = oshape k.shape = oshape

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