From 560995835bc81b8620d38b9eed579a49a54c710c Mon Sep 17 00:00:00 2001 From: "per.andreas.brodtkorb" Date: Tue, 11 Oct 2011 04:36:34 +0000 Subject: [PATCH] Small updates --- pywafo/src/wafo/misc.py | 16 ++--- pywafo/src/wafo/spectrum/core.py | 107 +++++++++++++++------------- pywafo/src/wafo/spectrum/models.py | 7 +- pywafo/src/wafo/wave_theory/core.py | 1 - 4 files changed, 72 insertions(+), 59 deletions(-) diff --git a/pywafo/src/wafo/misc.py b/pywafo/src/wafo/misc.py index 4b3d015..9fa3993 100644 --- a/pywafo/src/wafo/misc.py +++ b/pywafo/src/wafo/misc.py @@ -642,7 +642,7 @@ def findrfc(tp, hmin=0.0, method='clib'): ind, ix = clib.findrfc(y, hmin) return np.sort(ind[:ix]) -def mctp2rfc(f_mM, f_Mm=None): +def mctp2rfc(fmM, fMm=None): ''' Return Rainflow matrix given a Markov matrix of a Markov chain of turning points @@ -650,8 +650,8 @@ def mctp2rfc(f_mM, f_Mm=None): Parameters ---------- - f_mM = the min2max Markov matrix, - f_Mm = the max2min Markov matrix, + fmM = the min2max Markov matrix, + fMm = the max2min Markov matrix, Returns ------- @@ -679,12 +679,12 @@ def mctp2rfc(f_mM, f_Mm=None): ''' - if f_Mm is None: - f_mM = np.atleast_1d(f_mM) - f_Mm = f_mM.copy() + if fMm is None: + fmM = np.atleast_1d(fmM) + fMm = fmM.copy() else: - f_mM, f_Mm = np.atleast_1d(f_mM, f_Mm) - + fmM, fMm = np.atleast_1d(fmM, fMm) + f_mM, f_Mm = fmM.copy(), fMm.copy() N = max(f_mM.shape) f_max = np.sum(f_mM, axis=1) f_min = np.sum(f_mM, axis=0) diff --git a/pywafo/src/wafo/spectrum/core.py b/pywafo/src/wafo/spectrum/core.py index e2f00a6..3c39661 100644 --- a/pywafo/src/wafo/spectrum/core.py +++ b/pywafo/src/wafo/spectrum/core.py @@ -160,39 +160,40 @@ def plotspec(specdata, linetype='b-', flag=1): ''' PLOTSPEC Plot a spectral density - CALL: plotspec(S,plotflag,linetype) - - S = an array of spectral density structs: - 1D (see dat2spec) - 2D (see createspec) - 1D: - plotflag = 1 plots the density, S, (default) - 2 plot 10log10(S) - 3 plots both the above plots - 2D: - Directional spectra: S(w,theta), S(f,theta) - plotflag = 1 polar plot S (default) - 2 plots spectral density and the directional + Parameters + ---------- + S : SpecData1D or SpecData2D object + defining spectral density. + linetype : string + defining color and linetype, see plot for possibilities + flag : scalar integer + defining the type of plot + 1D: + 1 plots the density, S, (default) + 2 plot 10log10(S) + 3 plots both the above plots + 2D: + Directional spectra: S(w,theta), S(f,theta) + 1 polar plot S (default) + 2 plots spectral density and the directional spreading, int S(w,theta) dw or int S(f,theta) df - 3 plots spectral density and the directional + 3 plots spectral density and the directional spreading, int S(w,theta)/S(w) dw or int S(f,theta)/S(f) df - 4 mesh of S - 5 mesh of S in polar coordinates - 6 contour plot of S - 7 filled contour plot of S - Wavenumber spectra: S(k1,k2) - plotflag = 1 contour plot of S (default) - 2 filled contour plot of S - lintype : specify color and lintype, see PLOT for possibilities. - - NOTE: - lintype may be given anywhere after S. - - Examples + 4 mesh of S + 5 mesh of S in polar coordinates + 6 contour plot of S + 7 filled contour plot of S + Wavenumber spectra: S(k1,k2) + 1 contour plot of S (default) + 2 filled contour plot of S + + Example + ------- >>> import numpy as np - >>> import wafo.spectrum.models as sm - >>> Sj = sm.Jonswap(Hm0=3, Tp=7) + >>> import wafo.spectrum as ws + >>> Sj = ws.models.Jonswap(Hm0=3, Tp=7) >>> S = Sj.tospecdata() - >>> plotspec(S,1) + >>> ws.plotspec(S,flag=1) S = demospec('dir'); S2 = mkdspec(jonswap,spreading); plotspec(S,2), hold on @@ -205,8 +206,7 @@ def plotspec(specdata, linetype='b-', flag=1): See also dat2spec, createspec, simpson ''' - - + # label the contour levels txtFlag = 0; LegendOn = 1; @@ -281,13 +281,13 @@ def plotspec(specdata, linetype='b-', flag=1): for i, fp in enumerate(Fp.tolist()): txt.append(('fp%d = %0.2g' % (i, fp)) + funit) - + txt = ''.join(txt) if (flag == 3): plotbackend.subplot(2, 1, 1) if (flag == 1) or (flag == 3):#% Plot in normal scale - plotbackend.plot(np.vstack([Fp, Fp]), np.vstack([zeros(len(indm)), data.take(indm)]), ':', - freq, data, linetype) - + plotbackend.plot(np.vstack([Fp, Fp]), np.vstack([zeros(len(indm)), data.take(indm)]), ':', label=txt) + plotbackend.plot(freq, data, linetype) + specdata.labels.labelfig() # if isfield(S,'CI'), # plot(freq,S.S*S.CI(1), 'r:' ) # plot(freq,S.S*S.CI(2), 'r:' ) @@ -299,9 +299,9 @@ def plotspec(specdata, linetype='b-', flag=1): a1 = max(min(Fn, 10 * max(Fp)), a[1]); plotbackend.axis([0, a1 , 0, max(1.01 * maxS, a[3])]) - plotbackend.title('Spectral density') - plotbackend.xlabel(xlbl_txt) - plotbackend.ylabel(ylbl1_txt) + #plotbackend.title('Spectral density') + #plotbackend.xlabel(xlbl_txt) + #plotbackend.ylabel(ylbl1_txt) if (flag == 3): @@ -310,8 +310,9 @@ def plotspec(specdata, linetype='b-', flag=1): if (flag == 2) or (flag == 3) : # Plot in logaritmic scale ind = np.flatnonzero(data > 0) - plotbackend.plot(np.vstack([Fp, Fp]), np.vstack((min(10 * log10(data.take(ind) / maxS)).repeat(len(Fp)), - 10 * log10(data.take(indm) / maxS))), ':') + plotbackend.plot(np.vstack([Fp, Fp]), + np.vstack((min(10 * log10(data.take(ind) / maxS)).repeat(len(Fp)), + 10 * log10(data.take(indm) / maxS))), ':',label=txt) # hold on # if isfield(S,'CI'), # plot(freq(ind),10*log10(S.S(ind)*S.CI(1)/maxS), 'r:' ) @@ -319,13 +320,21 @@ def plotspec(specdata, linetype='b-', flag=1): # end plotbackend.plot(freq[ind], 10 * log10(data[ind] / maxS), linetype) -# if ih, a=axis; else a=[0 0 0 0]; end -# axis([0 max(min(Fn,max(10*Fp)),a(2)) -20 max(1.01*10*log10(1),a(4))]) % log10(maxS) -# title('Spectral density') -# xlabel(xlbl_txt) -# ylabel(ylbl2_txt ) -# -# if LegendOn + a = plotbackend.axis() + + a1 = Fn + if (Fp > 0): + a1 = max(min(Fn, 10 * max(Fp)), a[1]); + + plotbackend.axis([0, a1 , -20, max(1.01 * 10 * log10(1), a[3])]) + + specdata.labels.labelfig() + #plotbackend.title('Spectral density') + #plotbackend.xlabel(xlbl_txt) + plotbackend.ylabel(ylbl2_txt) + + if LegendOn: + plotbackend.legend() # if isfield(S,'CI'), # legend(txt{:},txtCI,1) # else @@ -3148,7 +3157,7 @@ class SpecData1D(WafoData): title = 'Directional Spectrum' if self.freqtype.startswith('w'): labels[0] = 'Frequency [rad/s]' - labels[2] = r'S(w,$\theta$) $[m^2 s / rad^2]$' + labels[2] = r'S($\omega$,$\theta$) $[m^2 s / rad^2]$' else: labels[0] = 'Frequency [Hz]' labels[2] = r'S(f,$\theta$) $[m^2 s / rad]$' @@ -3161,7 +3170,7 @@ class SpecData1D(WafoData): title = 'Spectral density' if self.freqtype.startswith('w'): labels[0] = 'Frequency [rad/s]' - labels[1] = r'S(w) $[m^2 s/ rad]$' + labels[1] = r'S($\omega$) $[m^2 s/ rad]$' else: labels[0] = 'Frequency [Hz]' labels[1] = r'S(f) $[m^2 s]$' diff --git a/pywafo/src/wafo/spectrum/models.py b/pywafo/src/wafo/spectrum/models.py index c169e09..ef3d9f8 100644 --- a/pywafo/src/wafo/spectrum/models.py +++ b/pywafo/src/wafo/spectrum/models.py @@ -1374,12 +1374,17 @@ class Spreading(object): >>> import wafo.spectrum.models as wsm >>> import pylab as plb >>> D = wsm.Spreading('cos2s',s_a=10.0) + + # Make directionale spectrum + >>> S = wsm.Jonswap().tospecdata() + >>> SD = D.tospecdata2d(S) + >>> h = SD.plot() >>> w = plb.linspace(0,3,257) >>> theta = plb.linspace(-pi,pi,129) >>> t = plb.contour(D(theta,w)[0].squeeze()) - # Make frequency dependent direction + # Make frequency dependent direction spreading >>> theta0 = lambda w: w*plb.pi/6.0 >>> D2 = wsm.Spreading('cos2s',theta0=theta0) >>> t = plb.contour(D2(theta,w)[0]) diff --git a/pywafo/src/wafo/wave_theory/core.py b/pywafo/src/wafo/wave_theory/core.py index e51ed9a..15e2ebf 100644 --- a/pywafo/src/wafo/wave_theory/core.py +++ b/pywafo/src/wafo/wave_theory/core.py @@ -7,7 +7,6 @@ import numpy as np from numpy import exp, expm1, inf, nan, pi, hstack, where, atleast_1d, cos, sin from dispersion_relation import w2k, k2w - def hyperbolic_ratio(a, b, sa, sb): ''' Return ratio of hyperbolic functions