def formatspec_generals(ax,
                        htax,
                        fontsize=12,
                        xlm=[1 / (dt * 12 * 15000), 1 / (dt * 1)],
                        ylm=[-.01, .4]):
    # Condensed axis adjustments for general exam

    # Set grid, adjust axis
    #ax.grid(True,which='both',ls='dotted',lw=0.5)
    ax, htax = viz.make_axtime(ax, htax)

    # Set Axis limits and labels
    ax = viz.add_yrlines(ax)
    ax.set_xlim(xlm)
    htax.set_xlim(xlm)
    ax.set_ylim(ylm)
    ax.set_xlabel(r"Frequency (cycles/year)", fontsize=fontsize)
    return ax, htax
Ejemplo n.º 2
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def lin_quickformat(ax, plotdt, freq):
    # Set tickparams and clone
    xtick = np.arange(0, 1.7, .2)
    ax.set_xticks(xtick)
    ax.set_ylabel("Power ($\degree C^{2} / cpy$)", fontsize=12)
    ax.set_xlabel("Frequency (cycles/year)", fontsize=12)
    htax = viz.twin_freqaxis(ax,
                             freq,
                             "Years",
                             dt,
                             mode='lin-lin',
                             xtick=xtick)

    # Set xtick labels
    xtkl = ["%.1f" % (1 / x) for x in xtick]
    htax.set_xticklabels(xtkl)

    # Set some key lines
    ax = viz.add_yrlines(ax, dt=plotdt)

    ax.legend(fontsize=10)
    return ax, htax
Ejemplo n.º 3
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    P, freq, dof, r1 = sps

    # Plot if option is set
    if plotcesm:
        pps = ybx.yo_specplot(freq,
                              P,
                              dof,
                              r1,
                              tunit,
                              dt=dt,
                              clvl=clvl,
                              axopt=axopt,
                              clopt=clopt)
        fig, ax, h, hcl, htax, hleg = pps
        #ax,htax = viz.make_axtime(ax,htax)
        ax = viz.add_yrlines(ax)
        ax.set_title("%s Spectral Estimate \n nsmooth=%i, taper = %.2f" %
                     (cnames[i], nsmooths[i], pct * 100) + r"%")
        ax.grid(True, which='both', ls='dotted')
        ax.set_ylabel(r"Frequency x Power $(^{\circ}C)^{2}$", fontsize=13)
        plt.tight_layout()
        plt.savefig("%sSpectralEstimate_%s_nsmooth%i_taper%i.png" %
                    (outpath, cnames[i], nsmooths[i], pct * 100),
                    dpi=200)
    CC = ybx.yo_speccl(freq, P, dof, r1, clvl)
    P = P * dt
    freq = freq / dt
    CC = CC * dt
    P1s.append(P)
    freq1s.append(freq)
    CLs.append(CC)