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Replaced methods with function calls

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master
Per A Brodtkorb 8 years ago
parent b580973e24
commit 30bf392f80
1 changed files with 26 additions and 22 deletions
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48
wafo/spectrum/core.py
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@ -5,7 +5,7 @@ import numpy as np
from numpy import (pi, inf, zeros, ones, where, nonzero, from numpy import (pi, inf, zeros, ones, where, nonzero,
flatnonzero, ceil, sqrt, exp, log, arctan2, flatnonzero, ceil, sqrt, exp, log, arctan2,
tanh, cosh, sinh, random, atleast_1d, tanh, cosh, sinh, random, atleast_1d,
minimum, diff, isnan, any, r_, conj, mod, minimum, diff, isnan, r_, conj, mod,
hstack, vstack, interp, ravel, finfo, linspace, hstack, vstack, interp, ravel, finfo, linspace,
arange, array, nan, newaxis, sign) arange, array, nan, newaxis, sign)
from numpy.fft import fft from numpy.fft import fft
@ -56,7 +56,7 @@ def _set_seed(iseed):
if iseed is not None: if iseed is not None:
try: try:
random.set_state(iseed) random.set_state(iseed)
except: except KeyError:
random.seed(iseed) random.seed(iseed)
@ -592,7 +592,8 @@ class SpecData1D(PlotData):
print('theoretical. Solution:') print('theoretical. Solution:')
raise ValueError('use larger dt or sparser grid for spectrum.') raise ValueError('use larger dt or sparser grid for spectrum.')
def _check_cov_matrix(self, acfmat, nt, dt): @staticmethod
def _check_cov_matrix(acfmat, nt, dt):
eps0 = 0.0001 eps0 = 0.0001
if nt + 1 >= 5: if nt + 1 >= 5:
cc2 = acfmat[0, 0] - acfmat[4, 0] * (acfmat[4, 0] / acfmat[0, 0]) cc2 = acfmat[0, 0] - acfmat[4, 0] * (acfmat[4, 0] / acfmat[0, 0])
@ -751,7 +752,7 @@ class SpecData1D(PlotData):
Correct it with resample, for example.''' Correct it with resample, for example.'''
raise ValueError(txt) raise ValueError(txt)
d_w = abs(diff(freq, n=2, axis=0)) d_w = abs(diff(freq, n=2, axis=0))
if any(d_w > 1.0e-8): if np.any(d_w > 1.0e-8):
txt = '''Not equidistant frequencies/wave numbers in spectrum. txt = '''Not equidistant frequencies/wave numbers in spectrum.
Correct it with resample, for example.''' Correct it with resample, for example.'''
raise ValueError(txt) raise ValueError(txt)
@ -995,18 +996,18 @@ class SpecData1D(PlotData):
Hw12 = Hw1 - Hw2 Hw12 = Hw1 - Hw2
maxHw12 = max(abs(Hw12)) maxHw12 = max(abs(Hw12))
if trace == 1: if trace == 1:
plotbackend.figure(1), plotbackend.figure(1)
plotbackend.semilogy(freq, Hw1, 'r') plotbackend.semilogy(freq, Hw1, 'r')
plotbackend.title('Hw') plotbackend.title('Hw')
plotbackend.figure(2), plotbackend.figure(2)
plotbackend.semilogy(freq, abs(Hw12), 'r') plotbackend.semilogy(freq, abs(Hw12), 'r')
plotbackend.title('Hw-HwOld') plotbackend.title('Hw-HwOld')
# pause(3) # pause(3)
plotbackend.figure(1), plotbackend.figure(1)
plotbackend.semilogy(freq, Hw1, 'b') plotbackend.semilogy(freq, Hw1, 'b')
plotbackend.title('Hw') plotbackend.title('Hw')
plotbackend.figure(2), plotbackend.figure(2)
plotbackend.semilogy(freq, abs(Hw12), 'b') plotbackend.semilogy(freq, abs(Hw12), 'b')
plotbackend.title('Hw-HwOld') plotbackend.title('Hw-HwOld')
# figtile # figtile
@ -1079,7 +1080,7 @@ class SpecData1D(PlotData):
S = self.copy() S = self.copy()
S.normalize() S.normalize()
m, unused_mtxt = self.moment(nr=4, even=True) m = self.moment(nr=4, even=True)[0]
A = sqrt(m[0] / m[1]) A = sqrt(m[0] / m[1])
if paramt is None: if paramt is None:
@ -1103,7 +1104,7 @@ class SpecData1D(PlotData):
if verbose: if verbose:
print('The level u for Gaussian process = %g' % u) print('The level u for Gaussian process = %g' % u)
unused_t0, tn, Nt = paramt tn, Nt = paramt[1:]
t = linspace(0, tn / A, Nt) # normalized times t = linspace(0, tn / A, Nt) # normalized times
# Transform amplitudes to Gaussian levels: # Transform amplitudes to Gaussian levels:
@ -1210,7 +1211,7 @@ class SpecData1D(PlotData):
S = self.copy() S = self.copy()
S.normalize() S.normalize()
m, unused_mtxt = self.moment(nr=2, even=True) m = self.moment(nr=2, even=True)[0]
A = sqrt(m[0] / m[1]) A = sqrt(m[0] / m[1])
if self.tr is None: if self.tr is None:
@ -1303,7 +1304,8 @@ class SpecData1D(PlotData):
pdf.options = opts pdf.options = opts
return pdf return pdf
def _covinput_t_pdf(self, pt, R): @staticmethod
def _covinput_t_pdf(pt, R):
""" """
Return covariance matrix for Tc or Tt period problems Return covariance matrix for Tc or Tt period problems
@ -1764,7 +1766,7 @@ class SpecData1D(PlotData):
(indI(3)=Nt+1); for i\in (indI(3)+1,indI(4)], Y(i)>0 (deriv. X''(tn)) (indI(3)=Nt+1); for i\in (indI(3)+1,indI(4)], Y(i)>0 (deriv. X''(tn))
(indI(4)=Nt+2); for i\in (indI(4)+1,indI(5)], Y(i)<0 (deriv. X'(ts)) (indI(4)=Nt+2); for i\in (indI(4)+1,indI(5)], Y(i)<0 (deriv. X'(ts))
''' '''
R0, _R1, R2, _R3, R4 = R[:, :5].T R0, R2, R4 = R[:, :5:2].T
covinput = self._covinput_mmt_pdf covinput = self._covinput_mmt_pdf
Ntime = len(R0) Ntime = len(R0)
Nx0 = max(1, len(hg)) Nx0 = max(1, len(hg))
@ -2121,7 +2123,8 @@ class SpecData1D(PlotData):
# end # end
return pdf, err, terr, options return pdf, err, terr, options
def _covinput_mmt_pdf(self, BIG, R, tn, ts, tnold=-1): @staticmethod
def _covinput_mmt_pdf(BIG, R, tn, ts, tnold=-1):
""" """
COVINPUT Sets up the covariance matrix COVINPUT Sets up the covariance matrix
@ -2340,7 +2343,8 @@ class SpecData1D(PlotData):
return dens return dens
def _cleanup(self, *files): @staticmethod
def _cleanup(*files):
'''Removes files from harddisk if they exist''' '''Removes files from harddisk if they exist'''
for f in files: for f in files:
if os.path.exists(f): if os.path.exists(f):
@ -3095,7 +3099,7 @@ class SpecData1D(PlotData):
xs = acf.sim(ns=ns, cases=Nstep) xs = acf.sim(ns=ns, cases=Nstep)
for iy in range(1, xs.shape[-1]): for iy in range(1, xs.shape[-1]):
ts = TimeSeries(xs[:, iy], xs[:, 0].ravel()) ts = TimeSeries(xs[:, iy], xs[:, 0].ravel())
g, _tmp = ts.trdata(method, **opt) g = ts.trdata(method, **opt)[0]
test1.append(g.dist2gauss()) test1.append(g.dist2gauss())
if verbose: if verbose:
print('finished %d of %d ' % (ix + 1, rep)) print('finished %d of %d ' % (ix + 1, rep))
@ -3304,7 +3308,7 @@ class SpecData1D(PlotData):
wnNew = Cnf2dt / dt # % New Nyquist frequency wnNew = Cnf2dt / dt # % New Nyquist frequency
dWn = wnNew - wnOld dWn = wnNew - wnOld
doInterpolate = dWn > 0 or w[1] > 0 or ( doInterpolate = dWn > 0 or w[1] > 0 or (
nfft != n) or dt != dTold or any(abs(diff(w, axis=0)) > 1.0e-8) nfft != n) or dt != dTold or np.any(abs(diff(w, axis=0)) > 1.0e-8)
if doInterpolate > 0: if doInterpolate > 0:
S1 = self.data S1 = self.data
@ -3341,7 +3345,7 @@ class SpecData1D(PlotData):
wnc = wnNew wnc = wnNew
# specfun = lambda xi : stineman_interp(xi, w, S1) # specfun = lambda xi : stineman_interp(xi, w, S1)
specfun = interpolate.interp1d(w, S1, kind='cubic') specfun = interpolate.interp1d(w, S1, kind='cubic')
x, unused_y = discretize(specfun, 0, wnc) x = discretize(specfun, 0, wnc)[0]
dwMin = minimum(min(diff(x)), dwMin) dwMin = minimum(min(diff(x)), dwMin)
newNfft = 2 ** nextpow2(ceil(wnNew / dwMin)) + 1 newNfft = 2 ** nextpow2(ceil(wnNew / dwMin)) + 1
@ -3396,7 +3400,7 @@ class SpecData1D(PlotData):
>>> np.allclose(Sn.moment(2)[0], [1.0, 1.0]) >>> np.allclose(Sn.moment(2)[0], [1.0, 1.0])
True True
''' '''
mom, unused_mtext = self.moment(nr=4, even=True) mom = self.moment(nr=4, even=True)[0]
m0 = mom[0] m0 = mom[0]
m2 = mom[1] m2 = mom[1]
m4 = mom[2] m4 = mom[2]
@ -3448,7 +3452,7 @@ class SpecData1D(PlotData):
array([ 0.73062845, 0.34476034, 0.68277527, 2.90817052]) array([ 0.73062845, 0.34476034, 0.68277527, 2.90817052])
''' '''
m, unused_mtxt = self.moment(nr=4, even=False) m = self.moment(nr=4, even=False)[0]
if isinstance(factors, str): if isinstance(factors, str):
factors = [factors] factors = [factors]
fact_dict = dict(alpha=0, eps2=1, eps4=3, qp=3, Qp=3) fact_dict = dict(alpha=0, eps2=1, eps4=3, qp=3, Qp=3)
@ -3594,7 +3598,7 @@ class SpecData1D(PlotData):
nfact = atleast_1d(nfact) nfact = atleast_1d(nfact)
if any((nfact > 14) | (nfact < 0)): if np.any((nfact > 14) | (nfact < 0)):
raise ValueError('Factor outside range (0,...,14)') raise ValueError('Factor outside range (0,...,14)')
# vari = self.freqtype # vari = self.freqtype
@ -3656,7 +3660,7 @@ class SpecData1D(PlotData):
# if nargout>1, # if nargout>1,
# covariance between the moments: # covariance between the moments:
# COV(mi,mj |T=t0) = int f^(i+j)*S(f)^2 df/T # COV(mi,mj |T=t0) = int f^(i+j)*S(f)^2 df/T
mij, unused_mijtxt = self.moment(nr=8, even=False, j=1) mij = self.moment(nr=8, even=False, j=1)[0]
for ix, tmp in enumerate(mij): for ix, tmp in enumerate(mij):
mij[ix] = tmp / T / ((2. * pi) ** (ix - 1.0)) mij[ix] = tmp / T / ((2. * pi) ** (ix - 1.0))

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