From b580973e24e6339072790dcf08cadb230d4b6453 Mon Sep 17 00:00:00 2001 From: Per A Brodtkorb Date: Tue, 6 Sep 2016 00:27:31 +0200 Subject: [PATCH] Replaced methods with function calls --- wafo/spectrum/models.py | 33 +++++++++++++++++++-------------- 1 file changed, 19 insertions(+), 14 deletions(-) diff --git a/wafo/spectrum/models.py b/wafo/spectrum/models.py index 888fa66..f0b31b6 100644 --- a/wafo/spectrum/models.py +++ b/wafo/spectrum/models.py @@ -47,7 +47,7 @@ from .core import SpecData1D, SpecData2D __all__ = ['Bretschneider', 'Jonswap', 'Torsethaugen', 'Wallop', 'McCormick', 'OchiHubble', 'Tmaspec', 'jonswap_peakfact', 'jonswap_seastate', - 'spreading', 'w2k', 'k2w', 'phi1'] + 'Spreading', 'w2k', 'k2w', 'phi1'] _EPS = finfo(float).eps @@ -1034,7 +1034,7 @@ class Torsethaugen(ModelSpectrum): print('Hm0 = %g' % Hm0) print('Ns, Ms = %g, %g Nw, Mw = %g, %g' % (Ns, Ms, Nw, Mw)) - print('gammas = %g gammaw = ' % (gammas, gammaw)) + print('gammas = %g gammaw = %g' % (gammas, gammaw)) print('Rps = %g Rpw = %g' % (Rps, Rpw)) print('Hps = %g Hpw = %g' % (Hps, Hpw)) print('Tps = %g Tpw = %g' % (Tps, Tpw)) @@ -1600,7 +1600,7 @@ class Spreading(object): phi0 : real scalar Parameter defining the actual principal direction of D. ''' - S, TH, phi0, unused_Nt = self.chk_input(theta, w, wc) + S, TH, phi0 = self.chk_input(theta, w, wc)[:3] gammaln = sp.gammaln @@ -1630,7 +1630,7 @@ class Spreading(object): phi0 : real scalar Parameter defining the actual principal direction of D. ''' - [X, TH, phi0, unused_Nt] = self.chk_input(theta, w, wc) + X, TH, phi0 = self.chk_input(theta, w, wc)[:3] D = (1 - X ** 2.) / (1. - (2. * cos(TH) - X) * X) / (2. * pi) return D, phi0 @@ -1659,7 +1659,7 @@ class Spreading(object): Parameter defining the actual principal direction of D. ''' - [par, TH, phi0, Nt] = self.chk_input(theta, w, wc) + par, TH, phi0, Nt = self.chk_input(theta, w, wc) D1 = par ** 2. / 2. @@ -1700,7 +1700,7 @@ class Spreading(object): Parameter defining the actual principal direction of D. ''' - [B, TH, phi0, unused_Nt] = self.chk_input(theta, w, wc) + B, TH, phi0 = self.chk_input(theta, w, wc)[:3] NB = tanh(pi * B) # % Normalization factor. NB = where(NB == 0, 1.0, NB) # Avoid division by zero @@ -1730,7 +1730,7 @@ class Spreading(object): Parameter defining the actual principal direction of D. ''' - [K, TH, phi0, unused_Nt] = self.chk_input(theta, w, wc) + K, TH, phi0 = self.chk_input(theta, w, wc)[:3] D = exp(K * (cos(TH) - 1.)) / (2 * pi * sp.ive(0, K)) return D, phi0 @@ -1758,7 +1758,7 @@ class Spreading(object): Parameter defining the actual principal direction of D. ''' - [A, TH, phi0, unused_Nt] = self.chk_input(theta, w, wc) + A, TH, phi0 = self.chk_input(theta, w, wc)[:3] D = ((-A <= TH) & (TH <= A)) / (2. * A) return D, phi0 @@ -1794,7 +1794,8 @@ class Spreading(object): fourierfun = self._fourierdispatch.get(self.type[0]) return fourierfun(r1) - def fourier2x(self, r1): + @staticmethod + def fourier2x(r1): ''' Returns the solution of r1 = x. ''' X = r1 @@ -1802,7 +1803,8 @@ class Spreading(object): raise ValueError('POISSON spreading: X value must be less than 1') return X - def fourier2a(self, r1): + @staticmethod + def fourier2a(r1): ''' Returns the solution of R1 = sin(A)/A. ''' A0 = flipud(linspace(0, pi + 0.1, 1025)) @@ -1833,7 +1835,8 @@ class Spreading(object): warnings.warn('Newton raphson method did not converge.') return A.clip(min=1e-16) # Avoid division by zero - def fourier2k(self, r1): + @staticmethod + def fourier2k(r1): ''' Returns the solution of R1 = besseli(1,K)/besseli(0,K), ''' @@ -1967,12 +1970,14 @@ class Spreading(object): s_par = s_par[newaxis, :] return s_par - def _donelan(self, wn): + @staticmethod + def _donelan(wn): ''' High frequency decay of B of sech2 paramater ''' return 10.0 ** (-0.4 + 0.8393 * exp(-0.567 * log(wn ** 2))) - def _r1ofsech2(self, B): + @staticmethod + def _r1ofsech2(B): ''' R1OFSECH2 Computes R1 = pi./(2*B.*sinh(pi./(2*B))) ''' realmax = finfo(float).max @@ -2111,7 +2116,7 @@ def _test_spreading(): D2 = Spreading('cos2s', theta0=lambda w: w * plb.pi / 6.0) d1 = D2(theta, w)[0] - _t = plb.contour(d1.squeeze()) + plb.contour(d1.squeeze()) pi = plb.pi D = Spreading('wrap_norm', s_a=10.0)