danh
/
pywafo
1
0
Fork 0
Code Issues Pull Requests Releases Wiki Activity

Replaced methods with function calls

Browse Source
master
Per A Brodtkorb 8 years ago
parent b580973e24
commit 30bf392f80
1 changed files with 26 additions and 22 deletions
Show Stats Download Patch File Download Diff File

48
wafo/spectrum/core.py
Unescape Escape View File

@ -5,7 +5,7 @@ import numpy as np
from numpy import (pi, inf, zeros, ones, where, nonzero,
flatnonzero, ceil, sqrt, exp, log, arctan2,
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,
arange, array, nan, newaxis, sign)
from numpy.fft import fft
@ -56,7 +56,7 @@ def _set_seed(iseed):
if iseed is not None:
try:
random.set_state(iseed)
except:
except KeyError:
random.seed(iseed)
@ -592,7 +592,8 @@ class SpecData1D(PlotData):
print('theoretical. Solution:')
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
if nt + 1 >= 5:
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.'''
raise ValueError(txt)
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.
Correct it with resample, for example.'''
raise ValueError(txt)
@ -995,18 +996,18 @@ class SpecData1D(PlotData):
Hw12 = Hw1 - Hw2
maxHw12 = max(abs(Hw12))
if trace == 1:
plotbackend.figure(1),
plotbackend.figure(1)
plotbackend.semilogy(freq, Hw1, 'r')
plotbackend.title('Hw')
plotbackend.figure(2),
plotbackend.figure(2)
plotbackend.semilogy(freq, abs(Hw12), 'r')
plotbackend.title('Hw-HwOld')
# pause(3)
plotbackend.figure(1),
plotbackend.figure(1)
plotbackend.semilogy(freq, Hw1, 'b')
plotbackend.title('Hw')
plotbackend.figure(2),
plotbackend.figure(2)
plotbackend.semilogy(freq, abs(Hw12), 'b')
plotbackend.title('Hw-HwOld')
# figtile
@ -1079,7 +1080,7 @@ class SpecData1D(PlotData):
S = self.copy()
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])
if paramt is None:
@ -1103,7 +1104,7 @@ class SpecData1D(PlotData):
if verbose:
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
# Transform amplitudes to Gaussian levels:
@ -1210,7 +1211,7 @@ class SpecData1D(PlotData):
S = self.copy()
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])
if self.tr is None:
@ -1303,7 +1304,8 @@ class SpecData1D(PlotData):
pdf.options = opts
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
@ -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(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
Ntime = len(R0)
Nx0 = max(1, len(hg))
@ -2121,7 +2123,8 @@ class SpecData1D(PlotData):
# end
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
@ -2340,7 +2343,8 @@ class SpecData1D(PlotData):
return dens
def _cleanup(self, *files):
@staticmethod
def _cleanup(*files):
'''Removes files from harddisk if they exist'''
for f in files:
if os.path.exists(f):
@ -3095,7 +3099,7 @@ class SpecData1D(PlotData):
xs = acf.sim(ns=ns, cases=Nstep)
for iy in range(1, xs.shape[-1]):
ts = TimeSeries(xs[:, iy], xs[:, 0].ravel())
g, _tmp = ts.trdata(method, **opt)
g = ts.trdata(method, **opt)[0]
test1.append(g.dist2gauss())
if verbose:
print('finished %d of %d ' % (ix + 1, rep))
@ -3304,7 +3308,7 @@ class SpecData1D(PlotData):
wnNew = Cnf2dt / dt # % New Nyquist frequency
dWn = wnNew - wnOld
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:
S1 = self.data
@ -3341,7 +3345,7 @@ class SpecData1D(PlotData):
wnc = wnNew
# specfun = lambda xi : stineman_interp(xi, w, S1)
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)
newNfft = 2 ** nextpow2(ceil(wnNew / dwMin)) + 1
@ -3396,7 +3400,7 @@ class SpecData1D(PlotData):
>>> np.allclose(Sn.moment(2)[0], [1.0, 1.0])
True
'''
mom, unused_mtext = self.moment(nr=4, even=True)
mom = self.moment(nr=4, even=True)[0]
m0 = mom[0]
m2 = mom[1]
m4 = mom[2]
@ -3448,7 +3452,7 @@ class SpecData1D(PlotData):
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):
factors = [factors]
fact_dict = dict(alpha=0, eps2=1, eps4=3, qp=3, Qp=3)
@ -3594,7 +3598,7 @@ class SpecData1D(PlotData):
nfact = atleast_1d(nfact)
if any((nfact > 14) | (nfact < 0)):
if np.any((nfact > 14) | (nfact < 0)):
raise ValueError('Factor outside range (0,...,14)')
# vari = self.freqtype
@ -3656,7 +3660,7 @@ class SpecData1D(PlotData):
# if nargout>1,
# covariance between the moments:
# 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):
mij[ix] = tmp / T / ((2. * pi) ** (ix - 1.0))

Write Preview
Loading…
Cancel
Save