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updated spectrum.core

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master
pbrod 9 years ago
parent f091a08651
commit afc61e4fc5
2 changed files with 92 additions and 79 deletions
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4
wafo/misc.py
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@ -1145,6 +1145,10 @@ def _findrfc(y, h):
return ind, ix return ind, ix
def mctp2tc(fmM, ):
raise ValueError("Not implemented yet")
def mctp2rfc(fmM, fMm=None): def mctp2rfc(fmM, fMm=None):
''' '''
Return Rainflow matrix given a Markov chain of turning points Return Rainflow matrix given a Markov chain of turning points

167
wafo/spectrum/core.py
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@ -14,12 +14,12 @@ from scipy.special import erf
from scipy.linalg import toeplitz from scipy.linalg import toeplitz
import scipy.interpolate as interpolate import scipy.interpolate as interpolate
from scipy.interpolate.interpolate import interp1d, interp2d from scipy.interpolate.interpolate import interp1d, interp2d
from ..misc import meshgrid, gravity, cart2polar, polar2cart
from ..objects import TimeSeries, mat2timeseries from ..objects import TimeSeries, mat2timeseries
from ..interpolate import stineman_interp from ..interpolate import stineman_interp
from ..wave_theory.dispersion_relation import w2k # , k2w from ..wave_theory.dispersion_relation import w2k # , k2w
from ..containers import PlotData, now from ..containers import PlotData, now
from ..misc import sub_dict_select, nextpow2, discretize, JITImport from ..misc import sub_dict_select, nextpow2, discretize, JITImport, mctp2tc
from ..misc import meshgrid, gravity, cart2polar, polar2cart, mctp2rfc
from ..kdetools import qlevels from ..kdetools import qlevels
# from wafo.transform import TrData # from wafo.transform import TrData
@ -1486,6 +1486,7 @@ class SpecData1D(PlotData):
S = self.copy() S = self.copy()
S.normalize() S.normalize()
m, unused_mtxt = self.moment(nr=4, even=True) m, unused_mtxt = self.moment(nr=4, even=True)
L0, L2, L4 = m
A = sqrt(m[0] / m[1]) A = sqrt(m[0] / m[1])
if paramt is None: if paramt is None:
@ -1510,7 +1511,7 @@ class SpecData1D(PlotData):
print('The level u for Gaussian process = %g' % u) print('The level u for Gaussian process = %g' % u)
t0, tn, Nt = paramt t0, tn, Nt = paramt
t = linspace(0, tn / A, Nt) # normalized times t = np.linspace(0, tn / A, Nt) # normalized times
# the starting point to evaluate # the starting point to evaluate
Nstart = 1 + round(t0 / tn * (Nt - 1)) Nstart = 1 + round(t0 / tn * (Nt - 1))
@ -1554,7 +1555,7 @@ class SpecData1D(PlotData):
# ftmp = cov2mmtpdfexe(R,dt,u,defnr,Nstart,hg,options) # ftmp = cov2mmtpdfexe(R,dt,u,defnr,Nstart,hg,options)
# err = repmat(nan,size(ftmp)) # err = repmat(nan,size(ftmp))
# else # else
ftmp, err, terr, options = self._cov2mmtpdf(R, dt, u, defnr, Nstart, ftmp, err, _terr, options = self._cov2mmtpdf(R, dt, u, defnr, Nstart,
hg, options) hg, options)
# end # end
@ -1600,75 +1601,80 @@ class SpecData1D(PlotData):
f = PlotData(args=args, title=title, labx=labx, laby=laby) f = PlotData(args=args, title=title, labx=labx, laby=laby)
f.options = options f.options = options
if defnr>1 or defnr==-2: if defnr > 1 or defnr == -2:
f.u = utc # save level u f.u = utc # save level u
if Nx>2: # amplitude distributions wanted
f.x{2} = h
f.labx{2} = 'min [m]'
if Nx > 2: # amplitude distributions wanted
# f.x{2} = h
# f.labx{2} = 'min [m]'
if defnr>2 || defnr==1 if defnr > 2 or defnr == 1:
der0 = der1[:,None] * der[None,:] der0 = der1[:, None] * der[None, :]
ftmp = np.reshape(ftmp,Nx,Nx,Nt) * der0[:,:, None] / A shape = (Nx, Nx, Nt)
err = np.reshape(err,Nx,Nx,Nt) * der0[:,:, None] / A ftmp = np.reshape(ftmp, shape) * der0[:, :, None] / A
err = np.reshape(err, shape) * der0[:, :, None] / A
f.x{3} = t(:)*A f.args[2] = t[:]*A
labz = 'wave length [m]' if in_space else 'period [sec]' _labz = 'wave length [m]' if in_space else 'period [sec]'
else: else:
der0 = der[:,None] * der[None,:] der0 = der[:, None] * der[None, :]
ftmp = np.reshape(ftmp,Nx,Nx) * der0 ftmp = np.reshape(ftmp, [Nx, Nx]) * der0
err = np.reshape(err,Nx,Nx) * der0 err = np.reshape(err, [Nx, Nx]) * der0
if (defnr==-1): if (defnr == -1):
ftmp0 = fliplr(mctp2rfc(fliplr(ftmp))) ftmp0 = np.fliplr(mctp2rfc(np.fliplr(ftmp)))
err = abs(ftmp0-fliplr(mctp2rfc(fliplr(ftmp+err)))) err = np.abs(ftmp0 -
np.fliplr(mctp2rfc(np.fliplr(ftmp+err))))
ftmp = ftmp0 ftmp = ftmp0
elif (defnr==-2): elif (defnr == -2):
ftmp0=fliplr(mctp2tc(fliplr(ftmp),utc,paramu))*sqrt(L4*L0)/L2 ftmp0 = np.fliplr(mctp2tc(np.fliplr(ftmp), utc,
err =abs(ftmp0-fliplr(mctp2tc(fliplr(ftmp+err),utc,paramu))*sqrt(L4*L0)/L2) paramu)) * sqrt(L4*L0)/L2
index1=find(f.x{1}>0) err = np.abs(ftmp0 -
index2=find(f.x{2}<0) np.fliplr(mctp2tc(np.fliplr(ftmp+err),
ftmp=flipud(ftmp0(index2,index1)) utc,paramu)) *
err =flipud(err(index2,index1)) sqrt(L4*L0)/L2)
f.x{1} = f.x{1}(index1) index1 = np.flatnonzero(f.args[0] > 0)
f.x{2} = abs(flipud(f.x{2}(index2))) index2 = np.flatnonzero(f.args[1] < 0)
ftmp = np.flipud(ftmp0[index2, index1])
err = np.flipud(err[index2, index1])
f.args[0] = f.args[0][index1]
f.args[1] = np.abs(np.flipud(f.args[1][index2]))
# end # end
#end # end
f.f = ftmp f.data = ftmp
f.err = err f.err = err
else: # Only time or wave length distributions wanted else: # Only time or wave length distributions wanted
f.f = ftmp/A f.data = ftmp/A
f.err = err/A f.err = err/A
f.x{1}=A*t' f.args[0] = A*t
if strcmpi(def(1),'t') # if def_[0] == 't':
f.labx{1} = 'period [sec]' # f.labx{1} = 'period [sec]'
else: # else:
f.labx{1} = 'wave length [m]' # f.labx{1} = 'wave length [m]'
# end # end
if defnr>3, if defnr > 3:
f.f = reshape(f.f,[Nt, Nt]) f.data = np.reshape(f.data, [Nt, Nt])
f.err = reshape(f.err,[Nt, Nt]) f.err = np.reshape(f.err, [Nt, Nt])
f.x{2}= A*t' f.args[1] = A*t
if strcmpi(def(1),'t') # if def_[0] == 't':
f.labx{2} = 'period [sec]' # f.labx{2} = 'period [sec]'
else: # else:
f.labx{2} = 'wave length [m]' # f.labx{2} = 'wave length [m]'
# end # end
#end # end
#end # end
try try:
[f.cl,f.pl]=qlevels(f.f,[10 30 50 70 90 95 99 99.9],f.x{1},f.x{2}) f.cl, f.pl = qlevels(f.f, [10, 30, 50, 70, 90, 95, 99, 99.9],
f.args[0], f.args[1])
except: except:
warnings.warn('Singularity likely in pdf') warnings.warn('Singularity likely in pdf')
# Test of spec2mmtpdf # Test of spec2mmtpdf
# cd f:\matlab\matlab\wafo\source\sp2thpdfalan # cd f:\matlab\matlab\wafo\source\sp2thpdfalan
# addpath f:\matlab\matlab\wafo ,initwafo, addpath f:\matlab\matlab\graphutil # addpath f:\matlab\matlab\wafo ,initwafo,
# addpath f:\matlab\matlab\graphutil
# Hm0=7;Tp=11; S = jonswap(4*pi/Tp,[Hm0 Tp]) # Hm0=7;Tp=11; S = jonswap(4*pi/Tp,[Hm0 Tp])
# ft = spec2mmtpdf(S,0,'vMmTMm',[0.3,.4,11],[0 .00005 2]) # ft = spec2mmtpdf(S,0,'vMmTMm',[0.3,.4,11],[0 .00005 2])
@ -1932,9 +1938,9 @@ class SpecData1D(PlotData):
err[1:Nx1, i, Ntd] += (err0[IJ:J].T) ** 2 err[1:Nx1, i, Ntd] += (err0[IJ:J].T) ** 2
terr[1:Nx1, i, Ntd] += (terr0[IJ:J].T) terr[1:Nx1, i, Ntd] += (terr0[IJ:J].T)
IJ = J IJ = J
# end %do # end do
# end % SELECT # end SELECT
# end %ENDIF # end ENDIF
# waitTxt = sprintf('%s Ready: %d of %d',datestr(now),Ntd,Ntime) # waitTxt = sprintf('%s Ready: %d of %d',datestr(now),Ntd,Ntime)
# fwaitbar(Ntd/Ntime,h11,waitTxt) # fwaitbar(Ntd/Ntime,h11,waitTxt)
@ -1967,13 +1973,13 @@ class SpecData1D(PlotData):
# tnold = tn # tnold = tn
if def_nr in [3, 4]: if def_nr in [3, 4]:
if (Nx == 1): if (Nx == 1):
# Joint density (TMd,TMm) given the Max and the min. # Joint density (TMd,TMm) given the Max and min
# Note the density is not scaled to unity # Note the density is not scaled to unity
pdf[0, ts, tn] = fxind[0] # *CC pdf[0, ts, tn] = fxind[0] # *CC
err[0, ts, tn] = err0[0] ** 2 # *CC err[0, ts, tn] = err0[0] ** 2 # *CC
terr[0, ts, tn] = terr0[0] # *CC terr[0, ts, tn] = terr0[0] # *CC
else: else:
# 4, gives level u separated Max2min and wave period # level u separated Max2min and wave period
# from Max to the crossing of level u # from Max to the crossing of level u
# (M,m,TMd). # (M,m,TMd).
IJ = 0 IJ = 0
@ -1987,19 +1993,20 @@ class SpecData1D(PlotData):
# end # end
elif def_nr == 5: elif def_nr == 5:
if (Nx == 1): if (Nx == 1):
# Joint density (Tdm,TMm) given the Max and the min. # Joint density (Tdm,TMm) given the Max and min
# Note the density is not scaled to unity # Note the density is not scaled to unity
pdf[0, tn - ts, tn] = fxind[0] # %*CC pdf[0, tn - ts, tn] = fxind[0] # *CC
err[0, tn - ts, tn] = err0[0] ** 2 err[0, tn - ts, tn] = err0[0] ** 2
terr[0, tn - ts, tn] = terr0[0] terr[0, tn - ts, tn] = terr0[0]
else: else:
# 5, gives level u separated Max2min and wave period from # level u separated Max2min and wave period
# the crossing of level u to the min (M,m,Tdm). # from the crossing of level u to the
# min (M,m,Tdm).
IJ = 0 IJ = 0
for i in range(1, Nx1): # = 2:Nx1 for i in range(1, Nx1): # = 2:Nx1
J = IJ + Nx1 J = IJ + Nx1
# %*CC # *CC
pdf[1:Nx1, i, tn - ts] += fxind[IJ:J].T * dt pdf[1:Nx1, i, tn - ts] += fxind[IJ:J].T * dt
err[1:Nx1, i, tn - ts] += (err0[IJ:J].T * dt) ** 2 err[1:Nx1, i, tn - ts] += (err0[IJ:J].T * dt) ** 2
terr[1:Nx1, i, tn - ts] += (terr0[IJ:J].T * dt) terr[1:Nx1, i, tn - ts] += (terr0[IJ:J].T * dt)
@ -2011,19 +2018,20 @@ class SpecData1D(PlotData):
else: # % exploit symmetry else: # % exploit symmetry
# 300 Symmetry # 300 Symmetry
for ts in range(1, Ntd // 2): # = 2:floor(Ntd//2) for ts in range(1, Ntd // 2): # = 2:floor(Ntd//2)
# Using the symmetry since U = 0 and the transformation is # Using the symmetry since U = 0 and the
# linear. # transformation is linear.
# positive wave period # positive wave period
BIG[:Ntdc, :Ntdc] = covinput(BIG[:Ntdc, :Ntdc], BIG[:Ntdc, :Ntdc] = covinput(BIG[:Ntdc, :Ntdc],
R, tn, ts, tnold) R, tn, ts, tnold)
fxind, err0, terr0 = rind(BIG[:Ntdc, :Ntdc], ex[:Ntdc], fxind, err0, terr0 = rind(BIG[:Ntdc, :Ntdc], ex[:Ntdc],
a_lo, a_up, indI, xc, Nt) a_lo, a_up, indI, xc, Nt)
#[fxind,err0] = rind(BIG(1:Ntdc,1:Ntdc),ex,a_lo,a_up,indI, xc,Nt,opt0{:}) # [fxind,err0] = rind(BIG(1:Ntdc,1:Ntdc),ex,a_lo,a_up,
# indI, xc,Nt,opt0{:})
# tnold = tn # tnold = tn
if (Nx == 1): # % THEN if (Nx == 1): # % THEN
# Joint density of (TMd,TMm),(Tdm,TMm) given the max and # Joint density of (TMd,TMm),(Tdm,TMm) given
# the min. # the max and the min.
# Note that the density is not scaled to unity # Note that the density is not scaled to unity
pdf[0, ts, tn] = fxind[0] # %*CC pdf[0, ts, tn] = fxind[0] # %*CC
err[0, ts, tn] = err0[0] ** 2 err[0, ts, tn] = err0[0] ** 2
@ -2037,11 +2045,12 @@ class SpecData1D(PlotData):
else: else:
IJ = 0 IJ = 0
if def_nr == 4: if def_nr == 4:
# 4, gives level u separated Max2min and wave period from # level u separated Max2min and wave period
# Max to the crossing of level u (M,m,TMd). # from Max to the crossing of level u (M,m,TMd)
for i in range(1, Nx1): for i in range(1, Nx1):
J = IJ + Nx1 J = IJ + Nx1
pdf[1:Nx1, i, ts] += fxind[IJ:J] * dt # %*CC # *CC
pdf[1:Nx1, i, ts] += fxind[IJ:J] * dt
err[1:Nx1, i, ts] += (err0[IJ:J] * dt) ** 2 err[1:Nx1, i, ts] += (err0[IJ:J] * dt) ** 2
terr[1:Nx1, i, ts] += (terr0[IJ:J] * dt) terr[1:Nx1, i, ts] += (terr0[IJ:J] * dt)
if (ts < tn - ts): if (ts < tn - ts):
@ -2054,8 +2063,8 @@ class SpecData1D(PlotData):
IJ = J IJ = J
# end %do # end %do
elif def_nr == 5: elif def_nr == 5:
# 5, gives level u separated Max2min and wave period # level u separated Max2min and wave period
# from the crossing of level u to min (M,m,Tdm). # from the crossing of level u to min (M,m,Tdm)
for i in range(1, Nx1): # = 2:Nx1, for i in range(1, Nx1): # = 2:Nx1,
J = IJ + Nx1 J = IJ + Nx1
pdf[1:Nx1, i, tn - ts] += fxind[IJ:J] * dt pdf[1:Nx1, i, tn - ts] += fxind[IJ:J] * dt
@ -3916,7 +3925,7 @@ class SpecData2D(PlotData):
[th, r] = cart2polar(k, k2) [th, r] = cart2polar(k, k2)
[k, k2] = polar2cart(th + self.phi, r) [k, k2] = polar2cart(th + self.phi, r)
ki1, ki2 = self.args ki1, ki2 = self.args
Sn = interp2(ki1, ki2, self.data, k, k2, method) Sn = interp2d(ki1, ki2, self.data, kind=method)(k, k2)
self.data = np.where(np.isnan(Sn), 0, Sn) self.data = np.where(np.isnan(Sn), 0, Sn)
self.phi = 0 self.phi = 0
else: else:

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