Small updates
per.andreas.brodtkorb
14 years ago
parent
d0834a14b8
commit
afd3c87e22
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from core import *
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import dispersion_relation
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'''
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Created on 3. juni 2011
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@author: pab
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'''
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import numpy as np
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from numpy import exp, expm1, inf, nan, pi, hstack, where, atleast_1d, cos, sin
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from dispersion_relation import w2k, k2w
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def hyperbolic_ratio(a, b, sa, sb):
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'''
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Return ratio of hyperbolic functions
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to allow extreme variations of arguments.
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Parameters
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----------
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a, b : array-like
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arguments vectors of the same size
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sa, sb : scalar integers
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defining the hyperbolic function used, i.e., f(x,1)=cosh(x), f(x,-1)=sinh(x)
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Returns
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-------
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r : ndarray
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f(a,sa)/f(b,sb), ratio of hyperbolic functions of same
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size as a and b
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Examples
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--------
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>>> x = [-2,0,2]
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>>> hyperbolic_ratio(x,1,1,1) # gives r=cosh(x)/cosh(1)
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array([ 2.438107 , 0.64805427, 2.438107 ])
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>>> hyperbolic_ratio(x,1,1,-1) # gives r=cosh(x)/sinh(1)
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array([ 3.20132052, 0.85091813, 3.20132052])
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>>> hyperbolic_ratio(x,1,-1,1) # gives r=sinh(x)/cosh(1)
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array([-2.35040239, 0. , 2.35040239])
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>>> hyperbolic_ratio(x,1,-1,-1) # gives r=sinh(x)/sinh(1)
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array([-3.08616127, 0. , 3.08616127])
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>>> hyperbolic_ratio(1,x,1,1) # gives r=cosh(1)/cosh(x)
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array([ 0.41015427, 1.54308063, 0.41015427])
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>>> hyperbolic_ratio(1,x,1,-1) # gives r=cosh(1)/sinh(x)
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array([-0.42545906, inf, 0.42545906])
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>>> hyperbolic_ratio(1,x,-1,1) # gives r=sinh(1)/cosh(x)
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array([ 0.3123711 , 1.17520119, 0.3123711 ])
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>>> hyperbolic_ratio(1,x,-1,-1) # gives r=sinh(1)/sinh(x)
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array([-0.32402714, inf, 0.32402714])
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See also
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--------
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tran
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'''
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ak, bk, sak, sbk = np.atleast_1d(a, b, np.sign(sa), np.sign(sb))
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# old call
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#return exp(ak-bk)*(1+sak*exp(-2*ak))/(1+sbk*exp(-2*bk))
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# TODO: Does not always handle division by zero correctly
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signRatio = np.where(sak * ak < 0, sak, 1)
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signRatio = np.where(sbk * bk < 0, sbk * signRatio, signRatio)
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bk = np.abs(bk)
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ak = np.abs(ak)
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num = np.where(sak < 0, expm1(-2 * ak), 1 + exp(-2 * ak))
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den = np.where(sbk < 0, expm1(-2 * bk), 1 + exp(-2 * bk))
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iden = np.ones(den.shape) * inf
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ind = np.flatnonzero(den != 0)
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iden.flat[ind] = 1.0 / den[ind]
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val = np.where(num == den, 1, num * iden)
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return signRatio * exp(ak - bk) * val #((sak+exp(-2*ak))/(sbk+exp(-2*bk)))
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def sensor_typeid(*sensortypes):
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''' Return ID for sensortype name
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Parameter
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---------
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sensortypes : list of strings defining the sensortype
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Returns
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-------
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sensorids : list of integers defining the sensortype
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Valid senor-ids and -types for time series are as follows:
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0, 'n' : Surface elevation (n=Eta)
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1, 'n_t' : Vertical surface velocity
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2, 'n_tt' : Vertical surface acceleration
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3, 'n_x' : Surface slope in x-direction
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4, 'n_y' : Surface slope in y-direction
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5, 'n_xx' : Surface curvature in x-direction
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6, 'n_yy' : Surface curvature in y-direction
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7, 'n_xy' : Surface curvature in xy-direction
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8, 'P' : Pressure fluctuation about static MWL pressure
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9, 'U' : Water particle velocity in x-direction
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10, 'V' : Water particle velocity in y-direction
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11, 'W' : Water particle velocity in z-direction
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12, 'U_t' : Water particle acceleration in x-direction
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13, 'V_t' : Water particle acceleration in y-direction
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14, 'W_t' : Water particle acceleration in z-direction
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15, 'X_p' : Water particle displacement in x-direction from its mean position
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16, 'Y_p' : Water particle displacement in y-direction from its mean position
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17, 'Z_p' : Water particle displacement in z-direction from its mean position
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Example:
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>>> sensor_typeid('W','v')
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[11, 10]
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>>> sensor_typeid('rubbish')
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[nan]
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See also
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--------
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sensor_type
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'''
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sensorid_table = dict(n=0, n_t=1, n_tt=2, n_x=3, n_y=4, n_xx=5,
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n_yy=6, n_xy=7, p=8, u=9, v=10, w=11, u_t=12,
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v_t=13, w_t=14, x_p=15, y_p=16, z_p=17)
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try:
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return [sensorid_table.get(name.lower(), nan) for name in sensortypes]
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except:
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raise ValueError('Input must be a string!')
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def sensor_type(*sensorids):
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'''
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Return sensortype name
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Parameter
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---------
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sensorids : vector or list of integers defining the sensortype
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Returns
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-------
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sensornames : tuple of strings defining the sensortype
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Valid senor-ids and -types for time series are as follows:
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0, 'n' : Surface elevation (n=Eta)
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1, 'n_t' : Vertical surface velocity
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2, 'n_tt' : Vertical surface acceleration
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3, 'n_x' : Surface slope in x-direction
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4, 'n_y' : Surface slope in y-direction
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5, 'n_xx' : Surface curvature in x-direction
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6, 'n_yy' : Surface curvature in y-direction
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7, 'n_xy' : Surface curvature in xy-direction
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8, 'P' : Pressure fluctuation about static MWL pressure
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9, 'U' : Water particle velocity in x-direction
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10, 'V' : Water particle velocity in y-direction
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11, 'W' : Water particle velocity in z-direction
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12, 'U_t' : Water particle acceleration in x-direction
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13, 'V_t' : Water particle acceleration in y-direction
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14, 'W_t' : Water particle acceleration in z-direction
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15, 'X_p' : Water particle displacement in x-direction from its mean position
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16, 'Y_p' : Water particle displacement in y-direction from its mean position
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17, 'Z_p' : Water particle displacement in z-direction from its mean position
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Example:
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>>> sensor_type(range(3))
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('n', 'n_t', 'n_tt')
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See also
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--------
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sensor_typeid, tran
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'''
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valid_names = ('n', 'n_t', 'n_tt', 'n_x', 'n_y', 'n_xx', 'n_yy', 'n_xy',
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'p', 'u', 'v', 'w', 'u_t', 'v_t', 'w_t', 'x_p', 'y_p', 'z_p',
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nan)
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ids = atleast_1d(*sensorids)
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if isinstance(ids, list):
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ids = hstack(ids)
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n = len(valid_names) - 1
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ids = where(((ids < 0) | (n < ids)), n , ids)
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return tuple(valid_names[i] for i in ids)
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class TransferFunction(object):
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'''
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Class for computing transfer functions based on linear wave theory
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of the system with input surface elevation,
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eta(x0,y0,t) = exp(i*(kx*x0+ky*y0-w*t)),
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and output Y determined by sensortype and position of sensor.
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Member methods
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--------------
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tran(w, theta, kw)
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Hw = a function of frequency only (not direction) size 1 x Nf
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Gwt = a function of frequency and direction size Nt x Nf
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w = vector of angular frequencies in Rad/sec. Length Nf
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theta = vector of directions in radians Length Nt (default 0)
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( theta = 0 -> positive x axis theta = pi/2 -> positive y axis)
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Member variables
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----------------
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pos : [x,y,z]
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vector giving coordinate position relative to [x0 y0 z0] (default [0,0,0])
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sensortype = string
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defining the sensortype or transfer function in output.
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0, 'n' : Surface elevation (n=Eta) (default)
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1, 'n_t' : Vertical surface velocity
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2, 'n_tt' : Vertical surface acceleration
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3, 'n_x' : Surface slope in x-direction
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4, 'n_y' : Surface slope in y-direction
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5, 'n_xx' : Surface curvature in x-direction
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6, 'n_yy' : Surface curvature in y-direction
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7, 'n_xy' : Surface curvature in xy-direction
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8, 'P' : Pressure fluctuation about static MWL pressure
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9, 'U' : Water particle velocity in x-direction
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10, 'V' : Water particle velocity in y-direction
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11, 'W' : Water particle velocity in z-direction
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12, 'U_t' : Water particle acceleration in x-direction
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13, 'V_t' : Water particle acceleration in y-direction
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14, 'W_t' : Water particle acceleration in z-direction
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15, 'X_p' : Water particle displacement in x-direction from its mean position
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16, 'Y_p' : Water particle displacement in y-direction from its mean position
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17, 'Z_p' : Water particle displacement in z-direction from its mean position
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h : real scalar
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water depth (default inf)
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g : real scalar
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acceleration of gravity (default 9.81 m/s**2)
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rho : real scalar
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water density (default 1028 kg/m**3)
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bet : 1 or -1
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1, theta given in terms of directions toward which waves travel (default)
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-1, theta given in terms of directions from which waves come
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igam : 1,2 or 3
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1, if z is measured positive upward from mean water level (default)
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2, if z is measured positive downward from mean water level
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3, if z is measured positive upward from sea floor
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thetax, thetay : real scalars
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angle in degrees clockwise from true north to positive x-axis and
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positive y-axis, respectively. (default theatx=90, thetay=0)
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Example
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-------
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>>> import pylab as plt
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>>> N=50; f0=0.1; th0=0; h=50; w0 = 2*pi*f0
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>>> t = np.linspace(0,15,N)
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>>> eta0 = np.exp(-1j*w0*t)
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>>> stypes = ['n', 'n_x', 'n_y'];
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>>> tf = TransferFunction(pos=(0, 0, 0), h=50)
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>>> vals = []
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>>> fh = plt.plot(t, eta0.real, 'r.')
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>>> plt.hold(True)
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>>> for i,stype in enumerate(stypes):
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... tf.sensortype = stype
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... Hw, Gwt = tf.tran(w0,th0)
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... vals.append((Hw*Gwt*eta0).real.ravel())
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... vals[i]
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... fh = plt.plot(t, vals[i])
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>>> plt.show()
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See also
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--------
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dat2dspec, sensor_type, sensor_typeid
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Reference
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---------
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Young I.R. (1994)
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"On the measurement of directional spectra",
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Applied Ocean Research, Vol 16, pp 283-294
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'''
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def __init__(self, pos=(0, 0, 0), sensortype='n', h=inf, g=9.81, rho=1028,
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bet=1, igam=1, thetax=90, thetay=0):
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self.pos = pos
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self.sensortype = sensortype if isinstance(sensortype, str) else sensor_type(sensortype)
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self.h = h
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self.g = g
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self.rho = rho
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self.bet = bet
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self.igam = igam
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self.thetax = thetax
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self.thetay = thetay
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self._tran_dict = dict(n=self._n, n_t=self._n_t, n_tt=self._n_tt,
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n_x=self._n_x, n_y=self._n_y, n_xx=self._n_xx,
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n_yy=self._n_yy, n_xy=self._n_xy,
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P=self._p, p=self._p,
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U=self._u, u=self._u,
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V=self._v, v=self._v,
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W=self._w, w=self._w,
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U_t=self._u_t, u_t=self._u_t,
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V_t=self._v_t, v_t=self._v_t,
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W_t=self._w_t, w_t=self._w_t,
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X_p=self._x_p, x_p=self._x_p,
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Y_p=self._y_p, y_p=self._y_p,
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Z_p=self._z_p, z_p=self._z_p)
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def tran(self, w, theta=0, kw=None):
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'''
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Return transfer functions based on linear wave theory
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of the system with input surface elevation,
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eta(x0,y0,t) = exp(i*(kx*x0+ky*y0-w*t)),
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and output,
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Y = Hw*Gwt*eta, determined by sensortype and position of sensor.
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Parameters
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----------
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w : array-like
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vector of angular frequencies in Rad/sec. Length Nf
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theta : array-like
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vector of directions in radians Length Nt (default 0)
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( theta = 0 -> positive x axis theta = pi/2 -> positive y axis)
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kw : array-like
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vector of wave numbers corresponding to angular frequencies, w. Length Nf
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(default calculated with w2k)
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Returns
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-------
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Hw = transfer function of frequency only (not direction) size 1 x Nf
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Gwt = transfer function of frequency and direction size Nt x Nf
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The complete transfer function Hwt = Hw*Gwt is a function of
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w (columns) and theta (rows) size Nt x Nf
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'''
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if kw is None:
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kw, unusedkw2 = w2k(w, 0, self.h) #wave number as function of angular frequency
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w, theta, kw = np.atleast_1d(w, theta, kw)
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# make sure they have the correct orientation
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theta.shape = (-1, 1)
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kw.shape = (-1,)
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w.shape = (-1,)
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tran_fun = self._tran_dict[self.sensortype]
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Hw, Gwt = tran_fun(w, theta, kw)
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# New call to avoid singularities. pab 07.11.2000
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# Set Hw to 0 for expressions w*hyperbolic_ratio(z*k,h*k,1,-1)= 0*inf
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ind = np.flatnonzero(1 - np.isfinite(Hw))
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Hw.flat[ind] = 0
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sgn = np.sign(Hw);
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k0 = np.flatnonzero(sgn < 0)
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if len(k0): # make sure Hw>=0 ie. transfer negative signs to Gwt
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Gwt[:, k0] = -Gwt[:, k0]
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Hw[:, k0] = -Hw[:, k0]
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if self.igam == 2:
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#pab 09 Oct.2002: bug fix
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# Changing igam by 2 should affect the directional result in the same way that changing eta by -eta!
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Gwt = -Gwt
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|
return Hw, Gwt
|
||||||
|
__call__ = tran
|
||||||
|
#---Private member methods
|
||||||
|
def _get_ee_cthxy(self, theta, kw):
|
||||||
|
# convert from angle in degrees to radians
|
||||||
|
bet = self.bet
|
||||||
|
thxr = self.thetax * pi / 180
|
||||||
|
thyr = self.thetay * pi / 180
|
||||||
|
|
||||||
|
cthx = bet * cos(theta - thxr + pi / 2)
|
||||||
|
#cthy = cos(theta-thyr-pi/2)
|
||||||
|
cthy = bet * sin(theta - thyr)
|
||||||
|
|
||||||
|
# Compute location complex exponential
|
||||||
|
x, y, unused_z = list(self.pos)
|
||||||
|
ee = exp((1j * (x * cthx + y * cthy)) * kw) # exp(i*k(w)*(x*cos(theta)+y*sin(theta)) size Nt X Nf
|
||||||
|
return ee, cthx, cthy
|
||||||
|
|
||||||
|
def _get_zk(self, kw):
|
||||||
|
h = self.h
|
||||||
|
z = self.pos[2]
|
||||||
|
if self.igam == 1:
|
||||||
|
zk = kw * (h + z) # z measured positive upward from mean water level (default)
|
||||||
|
elif self.igam == 2:
|
||||||
|
zk = kw * (h - z) # z measured positive downward from mean water level
|
||||||
|
else:
|
||||||
|
zk = kw * z # z measured positive upward from sea floor
|
||||||
|
return zk
|
||||||
|
|
||||||
|
#--- Surface elevation ---
|
||||||
|
def _n(self, w, theta, kw):
|
||||||
|
'''n = Eta = wave profile
|
||||||
|
'''
|
||||||
|
ee, unused_cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
return np.ones_like(w), ee
|
||||||
|
|
||||||
|
#---- Vertical surface velocity and acceleration-----
|
||||||
|
def _n_t(self, w, theta, kw):
|
||||||
|
''' n_t = Eta_t '''
|
||||||
|
ee, unused_cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
return w, -1j * ee;
|
||||||
|
def _n_tt(self, w, theta, kw):
|
||||||
|
'''n_tt = Eta_tt'''
|
||||||
|
ee, unused_cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
return w ** 2, -ee
|
||||||
|
|
||||||
|
#--- Surface slopes ---
|
||||||
|
def _n_x(self, w, theta, kw):
|
||||||
|
''' n_x = Eta_x = x-slope'''
|
||||||
|
ee, cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
return kw, 1j * cthx * ee
|
||||||
|
def _n_y(self, w, theta, kw):
|
||||||
|
''' n_y = Eta_y = y-slope'''
|
||||||
|
ee, unused_cthx, cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
return kw, 1j * cthy * ee
|
||||||
|
|
||||||
|
#--- Surface curvatures ---
|
||||||
|
def _n_xx(self, w, theta, kw):
|
||||||
|
''' n_xx = Eta_xx = Surface curvature (x-dir)'''
|
||||||
|
ee, cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
return kw ** 2, -(cthx ** 2) * ee
|
||||||
|
def _n_yy(self, w, theta, kw):
|
||||||
|
''' n_yy = Eta_yy = Surface curvature (y-dir)'''
|
||||||
|
ee, unused_cthx, cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
return kw ** 2, -cthy ** 2 * ee
|
||||||
|
def _n_xy(self, w, theta, kw):
|
||||||
|
''' n_xy = Eta_xy = Surface curvature (xy-dir)'''
|
||||||
|
ee, cthx, cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
return kw ** 2, -cthx * cthy * ee
|
||||||
|
|
||||||
|
#--- Pressure---
|
||||||
|
def _p(self, w, theta, kw):
|
||||||
|
''' pressure fluctuations'''
|
||||||
|
ee, unused_cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return self.rho * self.g * hyperbolic_ratio(zk, hk, 1, 1), ee #hyperbolic_ratio = cosh(zk)/cosh(hk)
|
||||||
|
|
||||||
|
#---- Water particle velocities ---
|
||||||
|
def _u(self, w, theta, kw):
|
||||||
|
''' U = x-velocity'''
|
||||||
|
ee, cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return w * hyperbolic_ratio(zk, hk, 1, -1), cthx * ee# w*cosh(zk)/sinh(hk), cos(theta)*ee
|
||||||
|
def _v(self, w, theta, kw):
|
||||||
|
'''V = y-velocity'''
|
||||||
|
ee, unused_cthx, cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return w * hyperbolic_ratio(zk, hk, 1, -1), cthy * ee # w*cosh(zk)/sinh(hk), sin(theta)*ee
|
||||||
|
def _w(self, w, theta, kw):
|
||||||
|
''' W = z-velocity'''
|
||||||
|
ee, unused_cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return w * hyperbolic_ratio(zk, hk, -1, -1), -1j * ee # w*sinh(zk)/sinh(hk), -?
|
||||||
|
|
||||||
|
#---- Water particle acceleration ---
|
||||||
|
def _u_t(self, w, theta, kw):
|
||||||
|
''' U_t = x-acceleration'''
|
||||||
|
ee, cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return (w ** 2) * hyperbolic_ratio(zk, hk, 1, -1), -1j * cthx * ee # w^2*cosh(zk)/sinh(hk), ?
|
||||||
|
|
||||||
|
def _v_t(self, w, theta, kw):
|
||||||
|
''' V_t = y-acceleration'''
|
||||||
|
ee, unused_cthx, cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return (w ** 2) * hyperbolic_ratio(zk, hk, 1, -1), -1j * cthy * ee # w^2*cosh(zk)/sinh(hk), ?
|
||||||
|
def _w_t(self, w, theta, kw):
|
||||||
|
''' W_t = z-acceleration'''
|
||||||
|
ee, unused_cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return (w ** 2) * hyperbolic_ratio(zk, hk, -1, -1), -ee # w*sinh(zk)/sinh(hk), ?
|
||||||
|
|
||||||
|
#---- Water particle displacement ---
|
||||||
|
def _x_p(self, w, theta, kw):
|
||||||
|
''' X_p = x-displacement'''
|
||||||
|
ee, cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return hyperbolic_ratio(zk, hk, 1, -1), 1j * cthx * ee # cosh(zk)./sinh(hk), ?
|
||||||
|
def _y_p(self, w, theta, kw):
|
||||||
|
''' Y_p = y-displacement'''
|
||||||
|
ee, unused_cthx, cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return hyperbolic_ratio(zk, hk, 1, -1), 1j * cthy * ee # cosh(zk)./sinh(hk), ?
|
||||||
|
def _z_p(self, w, theta, kw):
|
||||||
|
''' Z_p = z-displacement'''
|
||||||
|
ee, unused_cthx, unused_cthy = self._get_ee_cthxy(theta, kw)
|
||||||
|
hk = kw * self.h
|
||||||
|
zk = self._get_zk(kw)
|
||||||
|
return hyperbolic_ratio(zk, hk, -1, -1), ee # sinh(zk)./sinh(hk), ee
|
||||||
|
|
||||||
|
def wave_pressure(z, Hm0, h=10000, g=9.81, rho=1028):
|
||||||
|
'''
|
||||||
|
Calculate pressure amplitude due to water waves.
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
z : array-like
|
||||||
|
depth where pressure is calculated [m]
|
||||||
|
Hm0 : array-like
|
||||||
|
significant wave height (same as the average of the 1/3'rd highest
|
||||||
|
waves in a seastate. [m]
|
||||||
|
h : real scalar
|
||||||
|
waterdepth (default 10000 [m])
|
||||||
|
g : real scalar
|
||||||
|
acceleration of gravity (default 9.81 m/s**2)
|
||||||
|
rho : real scalar
|
||||||
|
water density (default 1028 kg/m**3)
|
||||||
|
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
p : ndarray
|
||||||
|
pressure amplitude due to water waves at water depth z. [Pa]
|
||||||
|
|
||||||
|
PRESSURE calculate pressure amplitude due to water waves according to
|
||||||
|
linear theory.
|
||||||
|
|
||||||
|
Example
|
||||||
|
-----
|
||||||
|
>>> import pylab as plt
|
||||||
|
>>> z = -np.linspace(10,20)
|
||||||
|
>>> fh = plt.plot(z, wave_pressure(z, Hm0=1, h=20))
|
||||||
|
>>> plt.show()
|
||||||
|
|
||||||
|
See also
|
||||||
|
--------
|
||||||
|
w2k
|
||||||
|
|
||||||
|
|
||||||
|
u = psweep.Fn*sqrt(mgf.length*9.81)
|
||||||
|
z = -10; h = inf;
|
||||||
|
Hm0 = 1.5;Tp = 4*sqrt(Hm0);
|
||||||
|
S = jonswap([],[Hm0,Tp]);
|
||||||
|
Hw = tran(S.w,0,[0 0 -z],'P',h)
|
||||||
|
Sm = S;
|
||||||
|
Sm.S = Hw.'.*S.S;
|
||||||
|
x1 = spec2sdat(Sm,1000);
|
||||||
|
pwave = pressure(z,Hm0,h)
|
||||||
|
|
||||||
|
plot(psweep.x{1}/u, psweep.f)
|
||||||
|
hold on
|
||||||
|
plot(x1(1:100,1)-30,x1(1:100,2),'r')
|
||||||
|
'''
|
||||||
|
|
||||||
|
|
||||||
|
# Assume seastate with jonswap spectrum:
|
||||||
|
|
||||||
|
Tp = 4 * np.sqrt(Hm0)
|
||||||
|
gam = jonswap_peakfact(Hm0, Tp)
|
||||||
|
Tm02 = Tp / (1.30301 - 0.01698 * gam + 0.12102 / gam)
|
||||||
|
w = 2 * np.pi / Tm02
|
||||||
|
kw, unused_kw2 = w2k(w, 0, h)
|
||||||
|
|
||||||
|
hk = kw * h
|
||||||
|
zk1 = kw * z
|
||||||
|
zk = hk + zk1 # z measured positive upward from mean water level (default)
|
||||||
|
#zk = hk-zk1; % z measured positive downward from mean water level
|
||||||
|
#zk1 = -zk1;
|
||||||
|
#zk = zk1; % z measured positive upward from sea floor
|
||||||
|
|
||||||
|
# cosh(zk)/cosh(hk) approx exp(zk) for large h
|
||||||
|
# hyperbolic_ratio(zk,hk,1,1) = cosh(zk)/cosh(hk)
|
||||||
|
# pr = np.where(np.pi < hk, np.exp(zk1), hyperbolic_ratio(zk, hk, 1, 1))
|
||||||
|
pr = hyperbolic_ratio(zk, hk, 1, 1)
|
||||||
|
pressure = (rho * g * Hm0 / 2) * pr
|
||||||
|
|
||||||
|
# pos = [np.zeros_like(z),np.zeros_like(z),z]
|
||||||
|
# tf = TransferFunction(pos=pos, sensortype='p', h=h, rho=rho, g=g)
|
||||||
|
# Hw, Gwt = tf.tran(w,0)
|
||||||
|
# pressure2 = np.abs(Hw) * Hm0 / 2
|
||||||
|
|
||||||
|
return pressure
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
pass
|
||||||
@ -0,0 +1,205 @@
|
|||||||
|
"""
|
||||||
|
Dispersion relation module
|
||||||
|
--------------------------
|
||||||
|
k2w - Translates from wave number to frequency
|
||||||
|
w2k - Translates from frequency to wave number
|
||||||
|
"""
|
||||||
|
import warnings
|
||||||
|
#import numpy as np
|
||||||
|
from numpy import (atleast_1d, sqrt, zeros_like, arctan2, where, tanh, any, #@UnresolvedImport
|
||||||
|
sin, cos, sign, inf, flatnonzero, finfo, cosh, abs) #@UnresolvedImport
|
||||||
|
|
||||||
|
__all__ = ['k2w', 'w2k']
|
||||||
|
|
||||||
|
def k2w(k1, k2=0e0, h=inf, g=9.81, u1=0e0, u2=0e0):
|
||||||
|
''' Translates from wave number to frequency
|
||||||
|
using the dispersion relation
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
k1 : array-like
|
||||||
|
wave numbers [rad/m].
|
||||||
|
k2 : array-like, optional
|
||||||
|
second dimension wave number
|
||||||
|
h : real scalar, optional
|
||||||
|
water depth [m].
|
||||||
|
g : real scalar, optional
|
||||||
|
acceleration of gravity, see gravity
|
||||||
|
u1, u2 : real scalars, optional
|
||||||
|
current velocity [m/s] along dimension 1 and 2.
|
||||||
|
note: when u1!=0 | u2!=0 then theta is not calculated correctly
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
w : ndarray
|
||||||
|
angular frequency [rad/s].
|
||||||
|
theta : ndarray
|
||||||
|
direction [rad].
|
||||||
|
|
||||||
|
Dispersion relation
|
||||||
|
-------------------
|
||||||
|
w = sqrt(g*K*tanh(K*h)) ( 0 < w < inf)
|
||||||
|
theta = arctan2(k2,k1) (-pi < theta < pi)
|
||||||
|
where
|
||||||
|
K = sqrt(k1**2+k2**2)
|
||||||
|
|
||||||
|
The shape of w and theta is the common shape of k1 and k2 according to the
|
||||||
|
numpy broadcasting rules.
|
||||||
|
|
||||||
|
See also
|
||||||
|
--------
|
||||||
|
w2k
|
||||||
|
|
||||||
|
Example
|
||||||
|
-------
|
||||||
|
>>> from numpy import arange
|
||||||
|
>>> import wafo.spectrum.dispersion_relation as wsd
|
||||||
|
>>> wsd.k2w(arange(0.01,.5,0.2))[0]
|
||||||
|
array([ 0.3132092 , 1.43530485, 2.00551739])
|
||||||
|
>>> wsd.k2w(arange(0.01,.5,0.2),h=20)[0]
|
||||||
|
array([ 0.13914927, 1.43498213, 2.00551724])
|
||||||
|
'''
|
||||||
|
|
||||||
|
k1i, k2i, hi, gi, u1i, u2i = atleast_1d(k1, k2, h, g, u1, u2)
|
||||||
|
|
||||||
|
if k1i.size == 0:
|
||||||
|
return zeros_like(k1i)
|
||||||
|
ku1 = k1i*u1i
|
||||||
|
ku2 = k2i*u2i
|
||||||
|
|
||||||
|
theta = arctan2(k2, k1)
|
||||||
|
|
||||||
|
k = sqrt(k1i**2+k2i**2)
|
||||||
|
w = where(k>0, ku1+ku2+sqrt(gi*k*tanh(k*hi)), 0.0)
|
||||||
|
|
||||||
|
cond = (w<0)
|
||||||
|
if any(cond):
|
||||||
|
txt0 = '''
|
||||||
|
Waves and current are in opposite directions
|
||||||
|
making some of the frequencies negative.
|
||||||
|
Here we are forcing the negative frequencies to zero.
|
||||||
|
'''
|
||||||
|
warnings.warn(txt0)
|
||||||
|
w = where(cond, 0.0, w) # force w to zero
|
||||||
|
|
||||||
|
return w, theta
|
||||||
|
|
||||||
|
def w2k(w, theta=0.0, h=inf, g=9.81, count_limit=100):
|
||||||
|
'''
|
||||||
|
Translates from frequency to wave number
|
||||||
|
using the dispersion relation
|
||||||
|
|
||||||
|
Parameters
|
||||||
|
----------
|
||||||
|
w : array-like
|
||||||
|
angular frequency [rad/s].
|
||||||
|
theta : array-like, optional
|
||||||
|
direction [rad].
|
||||||
|
h : real scalar, optional
|
||||||
|
water depth [m].
|
||||||
|
g : real scalar or array-like of size 2.
|
||||||
|
constant of gravity [m/s**2] or 3D normalizing constant
|
||||||
|
|
||||||
|
Returns
|
||||||
|
-------
|
||||||
|
k1, k2 : ndarray
|
||||||
|
wave numbers [rad/m] along dimension 1 and 2.
|
||||||
|
|
||||||
|
Description
|
||||||
|
-----------
|
||||||
|
Uses Newton Raphson method to find the wave number k in the dispersion relation
|
||||||
|
w**2= g*k*tanh(k*h).
|
||||||
|
The solution k(w) => k1 = k(w)*cos(theta)
|
||||||
|
k2 = k(w)*sin(theta)
|
||||||
|
The size of k1,k2 is the common shape of w and theta according to numpy
|
||||||
|
broadcasting rules. If w or theta is scalar it functions as a constant
|
||||||
|
matrix of the same shape as the other.
|
||||||
|
|
||||||
|
Example
|
||||||
|
-------
|
||||||
|
>>> import pylab as plb
|
||||||
|
>>> import wafo.spectrum.dispersion_relation as wsd
|
||||||
|
>>> w = plb.linspace(0,3);
|
||||||
|
>>> h = plb.plot(w,w2k(w)[0])
|
||||||
|
>>> wsd.w2k(range(4))[0]
|
||||||
|
array([ 0. , 0.1019368 , 0.4077472 , 0.91743119])
|
||||||
|
>>> wsd.w2k(range(4),h=20)[0]
|
||||||
|
array([ 0. , 0.10503601, 0.40774726, 0.91743119])
|
||||||
|
|
||||||
|
>>> plb.close('all')
|
||||||
|
|
||||||
|
See also
|
||||||
|
--------
|
||||||
|
k2w
|
||||||
|
'''
|
||||||
|
wi, th, gi = atleast_1d(w, theta, g)
|
||||||
|
|
||||||
|
if wi.size == 0:
|
||||||
|
return zeros_like(wi)
|
||||||
|
|
||||||
|
k = 1.0*sign(wi)*wi**2.0 #% deep water
|
||||||
|
if h > 10. ** 25:
|
||||||
|
k2 = k*sin(th)/gi[-1] #%size np x nf
|
||||||
|
k1 = k*cos(th)/gi[0]
|
||||||
|
return k1, k2
|
||||||
|
|
||||||
|
|
||||||
|
if gi.size > 1:
|
||||||
|
txt0 = '''
|
||||||
|
Finite depth in combination with 3D normalization (len(g)=2) is not implemented yet.
|
||||||
|
'''
|
||||||
|
raise ValueError(txt0)
|
||||||
|
|
||||||
|
|
||||||
|
find = flatnonzero
|
||||||
|
eps = finfo(float).eps
|
||||||
|
|
||||||
|
oshape = k.shape
|
||||||
|
wi, k = wi.ravel(), k.ravel()
|
||||||
|
|
||||||
|
# Newton's Method
|
||||||
|
# Permit no more than count_limit iterations.
|
||||||
|
|
||||||
|
hn = zeros_like(k)
|
||||||
|
ix = find((wi<0) | (0<wi))
|
||||||
|
|
||||||
|
# Break out of the iteration loop for three reasons:
|
||||||
|
# 1) the last update is very small (compared to x)
|
||||||
|
# 2) the last update is very small (compared to sqrt(eps))
|
||||||
|
# 3) There are more than 100 iterations. This should NEVER happen.
|
||||||
|
count = 0
|
||||||
|
while (ix.size>0 and count < count_limit):
|
||||||
|
ki = k[ix]
|
||||||
|
hn[ix] = (ki*tanh(ki*h)-wi[ix]**2.0/gi)/(tanh(ki*h)+ki*h/(cosh(ki*h)**2.0))
|
||||||
|
knew = ki - hn[ix]
|
||||||
|
# Make sure that the current guess is not zero.
|
||||||
|
# When Newton's Method suggests steps that lead to zero guesses
|
||||||
|
# take a step 9/10ths of the way to zero:
|
||||||
|
ksmall = find(abs(knew)==0)
|
||||||
|
if ksmall.size>0:
|
||||||
|
knew[ksmall] = ki[ksmall] / 10.0
|
||||||
|
hn[ix[ksmall]] = ki[ksmall]-knew[ksmall]
|
||||||
|
|
||||||
|
k[ix] = knew
|
||||||
|
# disp(['Iteration ',num2str(count),' Number of points left: ' num2str(length(ix)) ]),
|
||||||
|
|
||||||
|
ix = find((abs(hn) > sqrt(eps)*abs(k)) * abs(hn) > sqrt(eps))
|
||||||
|
count += 1
|
||||||
|
|
||||||
|
if count == count_limit:
|
||||||
|
txt1 = ''' W2K did not converge.
|
||||||
|
The maximum error in the last step was: %13.8f''' % max(hn[ix])
|
||||||
|
warnings.warn(txt1)
|
||||||
|
|
||||||
|
k.shape = oshape
|
||||||
|
|
||||||
|
k2 = k*sin(th)
|
||||||
|
k1 = k*cos(th)
|
||||||
|
return k1, k2
|
||||||
|
|
||||||
|
def main():
|
||||||
|
import doctest
|
||||||
|
doctest.testmod()
|
||||||
|
|
||||||
|
if __name__ == '__main__':
|
||||||
|
main()
|
||||||
Loading…
Reference in New Issue