예제 #1
0
파일: plot.py 프로젝트: mschachter/prorn
def plot_pseudospectra_single(perf_data, contour=False, levels=False, invert=True, linewidth=3.0):
    
    W = perf_data.net.W
    N = W.shape[0]
    
    plt.figure()
    fig = plt.gcf()
    ax = fig.add_subplot(1, 1, 1)
    if contour:
        plot_pseudospectra_contour(W, bounds=[-3, 3, -3, 3], npts=50, ax=ax, colorbar=False, invert=False, log=False, levels=levels, linewidth=linewidth)
    else:
        plot_pseudospectra(W, bounds=[-3, 3, -3, 3], npts=50, ax=ax, colorbar=True, log=True, invert=invert)
    plt.axhline(0.0, color='k', axes=ax)
    plt.axvline(0.0, color='k', axes=ax)
    
    cir = pylab.Circle((0.0, 0.0), radius=1.00,  fc='gray', fill=False)
    pylab.gca().add_patch(cir)
    
    plt.xticks([], [])
    plt.yticks([], [])
    
    if not contour:
        for m in range(N):
            ev = perf_data.eigen_values[m]
            ax.plot(ev.real, ev.imag, 'ko', markerfacecolor='w')
예제 #2
0
파일: plot.py 프로젝트: mschachter/prorn
def plot_pseudospectra_by_perf(pdata, perf_attr='logit_perf', contour=False, levels=None, invert=True):
    
    num_plots = 25
    
    indx_off = [0, len(pdata)-num_plots]
    weights = [[], []]
    for k,offset in enumerate(indx_off):
        pend = offset + num_plots
        for m,p in enumerate(pdata[offset:pend]):
            weights[k].append(p.W)        
            
    perrow = int(np.sqrt(num_plots))
    percol = perrow
    
    for j,offset in enumerate(indx_off):
        fig = plt.figure()
        fig.subplots_adjust(wspace=0.1, hspace=0.1)    
        for k in range(num_plots):
            W = weights[j][k]
            N = W.shape[0]
            ax = fig.add_subplot(perrow, percol, k)
            if contour:
                plot_pseudospectra_contour(W, bounds=[-3, 3, -3, 3], npts=50, ax=ax, colorbar=False, invert=False, log=False, levels=levels)
            else:
                plot_pseudospectra(W, bounds=[-3, 3, -3, 3], npts=50, ax=ax, colorbar=True, log=True, invert=invert)
            plt.axhline(0.0, color='k', axes=ax)
            plt.axvline(0.0, color='k', axes=ax)
            
            cir = pylab.Circle((0.0, 0.0), radius=1.00,  fc='gray', fill=False)
            pylab.gca().add_patch(cir)
            
            plt.xticks([], [])
            plt.yticks([], [])
            
            if not contour:
                p = pdata[offset + k]
                for m in range(N):
                    ev = p.eigen_values[m]
                    ax.plot(ev.real, ev.imag, 'ko', markerfacecolor='w')
        if offset == 0:
            plt.suptitle('Pseudospectra of Top %d Networks' % num_plots)
        else:
            plt.suptitle('Pseudospectra of Bottom %d Networks' % num_plots)
            
    plt.show()