heatmap.py 文件源码

def heat_map_reliability(data):
    nb_runs = get_data_info(data)
    nb_func = len(get_data_info(data, 'fnames'))
    methods = get_data_info(data, 'methods')
    mat = np.empty([nb_func, len(methods)])
    for j, k in enumerate(data):
        for i, f in enumerate(data[k]):
            success = np.sum(
                data[k][f]['success']) * 100 / nb_runs
            if np.isnan(success):
                success = 0
            mat[i, j] = success
    # mat.sort(axis=0)
    fig = plt.figure()
    ax1 = fig.add_axes([0.7, 0.1, 0.18, 0.8])
    Y = fastcluster.linkage(mat, method='ward')
    Z1 = sch.dendrogram(Y, orientation='right')
    ax1.set_xticks([])
    ax1.set_yticks([])
    axmatrix = fig.add_axes([0.1, 0.1, 0.6, 0.8])
    axmatrix.set_title(
            'Success rate across test functions (reliability over 200 runs)')
    im = axmatrix.matshow(
            mat[Z1['leaves'], :], aspect='auto', origin='lower',
            cmap=plt.cm.RdYlGn,
            )
    methods.insert(0, ' ')
    axmatrix.set_xticklabels(methods)
    # Reorder functions indexes:
    c = np.arange(0, nb_func)[Z1['leaves']]
    axmatrix.set_yticks(np.arange(0, nb_func, 10))
    axmatrix.set_yticklabels(c)
    axmatrix.set_ylabel('Test function number')
    axcolor = fig.add_axes([0.9, 0.1, 0.02, 0.8])
    plt.colorbar(im, cax=axcolor)
    # fig.show()
    fig.save('heatmap.pdf', bbox_inches='tight', format='pdf')