Ejemplo n.º 1
0
def fftplt1(x,Mch,dtrnd=True,demean=True):
	fs=1

	if demean:
		x = x - x.mean()

	if dtrnd:
		Pout = plt.psd(x, NFFT=Mch, detrend=pylab.detrend_linear, noverlap=Mch/2, Fs=fs)
	else:
		Pout = plt.psd(x, NFFT=Mch, detrend=pylab.detrend_none, noverlap=Mch/2, Fs=fs)

	xdtrnd = pylab.detrend_linear(x)
	xauto = mcmath.acorr_mlab(xdtrnd,2)
	rhoxauto = (xauto[1] + np.sqrt(abs(xauto[2])))/2
	R = mcmath.redspec(rhoxauto,np.arange(Mch/2),Mch)

	P = Pout[0][:R.size]
	F = Pout[1][:R.size]
	Psum = P.sum()
	Rsum = R.sum()
	PRratio = Psum/Rsum
	Rcmp = R*PRratio

	plt.figure()
	plt.plot(F,P)
	plt.plot(F,Rcmp)

	return (F,P,Rcmp)
Ejemplo n.º 2
0
def fftplt3(x,Mch,pval=0.1,dtrnd=True,demean=True,titlestr='',Dt=0.01):
	"""Differs from fftplt3 solely by plotting the power spectral density
	in log-form, 10*log10(P)."""
	fs=1
	titl_plc = (1.,1.)

	if demean:
		x = x - x.mean()

	if dtrnd:
		Pout = plt.psd(x, NFFT=Mch, detrend=pylab.detrend_linear, noverlap=Mch/2, Fs=fs)
	else:
		Pout = plt.psd(x, NFFT=Mch, detrend=pylab.detrend_none, noverlap=Mch/2, Fs=fs)

	xdtrnd = pylab.detrend_linear(x)
	xauto = mcmath.acorr_mlab(xdtrnd,2)
	rhoxauto = (xauto[1] + np.sqrt(abs(xauto[2])))/2
	R = mcmath.redspec(rhoxauto,np.arange(Mch/2),Mch)

	P = Pout[0][:R.size]
	F = Pout[1][:R.size]
	Psum = P.sum()
	Rsum = R.sum()
	PRratio = Psum/Rsum
	Rcmp = R*PRratio

	dof = (x.size / (Mch/2.)) * 1.2
	Fval = stats.f.isf(pval,dof,dof)

	tst = P / Rcmp
	pass1 = np.where(tst > Fval)[0]
	maxs = mcmath.extrema_find(P,'max',t=F,dt=Dt)
	max_ind = np.intersect1d(maxs,pass1)
	Fmaxs = F[max_ind]
	Fmaxs2 = np.append(Fmaxs,0.1)
	Fmaxs2.sort()
	Tmaxs = 1/(Fmaxs2)
	Tmaxs = np.round(Tmaxs,2)

	ax = plt.gca()
	ax.plot(F,10*np.log10(Rcmp))

	ax.set_xticks(Fmaxs2)
	ax.set_xticklabels(Tmaxs)
	my_fmt_xdate(ax,rot=90,hal='center')
	multiline(Fmaxs,c='red',ls='--')

	xtl = ax.get_xticklabels()
	ytl = ax.get_yticklabels()
	plt.setp(xtl,'size',10)
	plt.setp(ytl,'size',9)

	ppct = int((1 - pval)*100)
	titl_str = '%s FFT (chunksize: %d) :: peak CL: %d%%' % (titlestr,Mch,ppct)
	plt.text(titl_plc[0],titl_plc[1],titl_str,ha='right',va='bottom',size=12,transform=ax.transAxes)
	plt.xlabel('Peak period (yrs)',size=11)


	return (F,P,Rcmp)
Ejemplo n.º 3
0
def fftplt1(x, Mch, dtrnd=True, demean=True):
    fs = 1

    if demean:
        x = x - x.mean()

    if dtrnd:
        Pout = plt.psd(x,
                       NFFT=Mch,
                       detrend=pylab.detrend_linear,
                       noverlap=Mch / 2,
                       Fs=fs)
    else:
        Pout = plt.psd(x,
                       NFFT=Mch,
                       detrend=pylab.detrend_none,
                       noverlap=Mch / 2,
                       Fs=fs)

    xdtrnd = pylab.detrend_linear(x)
    xauto = mcmath.acorr_mlab(xdtrnd, 2)
    rhoxauto = (xauto[1] + np.sqrt(abs(xauto[2]))) / 2
    R = mcmath.redspec(rhoxauto, np.arange(Mch / 2), Mch)

    P = Pout[0][:R.size]
    F = Pout[1][:R.size]
    Psum = P.sum()
    Rsum = R.sum()
    PRratio = Psum / Rsum
    Rcmp = R * PRratio

    plt.figure()
    plt.plot(F, P)
    plt.plot(F, Rcmp)

    return (F, P, Rcmp)
Ejemplo n.º 4
0
def fftplt2(x,Mch,pval=0.1,dtrnd=True,demean=True,titlestr='',Dt=0.01):
	"""Differs from fftplt1 by returning a plot highlighting sig peaks, with their
	freq axis tick marks notated by their period.  Also allows adjustment of sig level and title string."""
	fs=1
	titl_plc = (1.,1.)

	if demean:
		x = x - x.mean()

	if dtrnd:
		Pout = plt.psd(x, NFFT=Mch, detrend=pylab.detrend_linear, noverlap=Mch/2, Fs=fs)
	else:
		Pout = plt.psd(x, NFFT=Mch, detrend=pylab.detrend_none, noverlap=Mch/2, Fs=fs)

	xdtrnd = pylab.detrend_linear(x)
	xauto = mcmath.acorr_mlab(xdtrnd,2)
	rhoxauto = (xauto[1] + np.sqrt(abs(xauto[2])))/2
	R = mcmath.redspec(rhoxauto,np.arange(Mch/2),Mch)

	P = Pout[0][:R.size]
	F = Pout[1][:R.size]
	Psum = P.sum()
	Rsum = R.sum()
	PRratio = Psum/Rsum
	Rcmp = R*PRratio

	dof = (x.size / (Mch/2.)) * 1.2
	Fval = stats.f.isf(pval,dof,dof)

	tst = P / Rcmp
	pass1 = np.where(tst > Fval)[0]
	maxs = mcmath.extrema_find(P,'max',t=F,dt=Dt)
	max_ind = np.intersect1d(maxs,pass1)
	Fmaxs = F[max_ind]
	Fmaxs2 = np.append(Fmaxs,0.1)
	Fmaxs2.sort()
	Tmaxs = 1/(Fmaxs2)
	Tmaxs = np.round(Tmaxs,2)

	fig = plt.figure(figsize=(7,5))
	ax = fig.add_axes((0.1,0.14,0.88,0.81))
	ax.plot(F,P,)
	ax.plot(F,Rcmp)
	
	ax.set_xticks(Fmaxs2)
	ax.set_xticklabels(Tmaxs)
	my_fmt_xdate(ax,rot=90,hal='center')
	multiline(Fmaxs,c='red',ls='--')

	xtl = ax.get_xticklabels()
	ytl = ax.get_yticklabels()
	plt.setp(xtl,'size',10)
	plt.setp(ytl,'size',9)

	ppct = int((1 - pval)*100)
	titl_str = '%s FFT (chunksize: %d) :: peak CL: %d%%' % (titlestr,Mch,ppct)
	plt.text(titl_plc[0],titl_plc[1],titl_str,ha='right',va='bottom',size=12,transform=ax.transAxes)
	plt.xlabel('Peak period (yrs)',size=11)


	return (F,P,Rcmp)
Ejemplo n.º 5
0
def fftplt3(x, Mch, pval=0.1, dtrnd=True, demean=True, titlestr='', Dt=0.01):
    """Differs from fftplt3 solely by plotting the power spectral density
	in log-form, 10*log10(P)."""
    fs = 1
    titl_plc = (1., 1.)

    if demean:
        x = x - x.mean()

    if dtrnd:
        Pout = plt.psd(x,
                       NFFT=Mch,
                       detrend=pylab.detrend_linear,
                       noverlap=Mch / 2,
                       Fs=fs)
    else:
        Pout = plt.psd(x,
                       NFFT=Mch,
                       detrend=pylab.detrend_none,
                       noverlap=Mch / 2,
                       Fs=fs)

    xdtrnd = pylab.detrend_linear(x)
    xauto = mcmath.acorr_mlab(xdtrnd, 2)
    rhoxauto = (xauto[1] + np.sqrt(abs(xauto[2]))) / 2
    R = mcmath.redspec(rhoxauto, np.arange(Mch / 2), Mch)

    P = Pout[0][:R.size]
    F = Pout[1][:R.size]
    Psum = P.sum()
    Rsum = R.sum()
    PRratio = Psum / Rsum
    Rcmp = R * PRratio

    dof = (x.size / (Mch / 2.)) * 1.2
    Fval = stats.f.isf(pval, dof, dof)

    tst = P / Rcmp
    pass1 = np.where(tst > Fval)[0]
    maxs = mcmath.extrema_find(P, 'max', t=F, dt=Dt)
    max_ind = np.intersect1d(maxs, pass1)
    Fmaxs = F[max_ind]
    Fmaxs2 = np.append(Fmaxs, 0.1)
    Fmaxs2.sort()
    Tmaxs = 1 / (Fmaxs2)
    Tmaxs = np.round(Tmaxs, 2)

    ax = plt.gca()
    ax.plot(F, 10 * np.log10(Rcmp))

    ax.set_xticks(Fmaxs2)
    ax.set_xticklabels(Tmaxs)
    my_fmt_xdate(ax, rot=90, hal='center')
    multiline(Fmaxs, c='red', ls='--')

    xtl = ax.get_xticklabels()
    ytl = ax.get_yticklabels()
    plt.setp(xtl, 'size', 10)
    plt.setp(ytl, 'size', 9)

    ppct = int((1 - pval) * 100)
    titl_str = '%s FFT (chunksize: %d) :: peak CL: %d%%' % (titlestr, Mch,
                                                            ppct)
    plt.text(titl_plc[0],
             titl_plc[1],
             titl_str,
             ha='right',
             va='bottom',
             size=12,
             transform=ax.transAxes)
    plt.xlabel('Peak period (yrs)', size=11)

    return (F, P, Rcmp)
Ejemplo n.º 6
0
def fftplt2(x, Mch, pval=0.1, dtrnd=True, demean=True, titlestr='', Dt=0.01):
    """Differs from fftplt1 by returning a plot highlighting sig peaks, with their
	freq axis tick marks notated by their period.  Also allows adjustment of sig level and title string."""
    fs = 1
    titl_plc = (1., 1.)

    if demean:
        x = x - x.mean()

    if dtrnd:
        Pout = plt.psd(x,
                       NFFT=Mch,
                       detrend=pylab.detrend_linear,
                       noverlap=Mch / 2,
                       Fs=fs)
    else:
        Pout = plt.psd(x,
                       NFFT=Mch,
                       detrend=pylab.detrend_none,
                       noverlap=Mch / 2,
                       Fs=fs)

    xdtrnd = pylab.detrend_linear(x)
    xauto = mcmath.acorr_mlab(xdtrnd, 2)
    rhoxauto = (xauto[1] + np.sqrt(abs(xauto[2]))) / 2
    R = mcmath.redspec(rhoxauto, np.arange(Mch / 2), Mch)

    P = Pout[0][:R.size]
    F = Pout[1][:R.size]
    Psum = P.sum()
    Rsum = R.sum()
    PRratio = Psum / Rsum
    Rcmp = R * PRratio

    dof = (x.size / (Mch / 2.)) * 1.2
    Fval = stats.f.isf(pval, dof, dof)

    tst = P / Rcmp
    pass1 = np.where(tst > Fval)[0]
    maxs = mcmath.extrema_find(P, 'max', t=F, dt=Dt)
    max_ind = np.intersect1d(maxs, pass1)
    Fmaxs = F[max_ind]
    Fmaxs2 = np.append(Fmaxs, 0.1)
    Fmaxs2.sort()
    Tmaxs = 1 / (Fmaxs2)
    Tmaxs = np.round(Tmaxs, 2)

    fig = plt.figure(figsize=(7, 5))
    ax = fig.add_axes((0.1, 0.14, 0.88, 0.81))
    ax.plot(
        F,
        P,
    )
    ax.plot(F, Rcmp)

    ax.set_xticks(Fmaxs2)
    ax.set_xticklabels(Tmaxs)
    my_fmt_xdate(ax, rot=90, hal='center')
    multiline(Fmaxs, c='red', ls='--')

    xtl = ax.get_xticklabels()
    ytl = ax.get_yticklabels()
    plt.setp(xtl, 'size', 10)
    plt.setp(ytl, 'size', 9)

    ppct = int((1 - pval) * 100)
    titl_str = '%s FFT (chunksize: %d) :: peak CL: %d%%' % (titlestr, Mch,
                                                            ppct)
    plt.text(titl_plc[0],
             titl_plc[1],
             titl_str,
             ha='right',
             va='bottom',
             size=12,
             transform=ax.transAxes)
    plt.xlabel('Peak period (yrs)', size=11)

    return (F, P, Rcmp)