def plot_one_class_3()

in tools/visualize.py [0:0]

• 32 lines of code
• 14 McCabe index (conditional complexity)

def plot_one_class_3(umap_Y,
                     umap_T,
                     train_Y,
                     train_T,
                     test_Y, 
                     test_T, 
                     target           = 0, 
                     col              = "red", 
                     total_train_size = "", 
                     total_test_size  = "", 
                     info             = "",
                     output_dir       = "",
                     orig_space_dim   = 0):
    
    size = 1
    
    fig, (ax0, ax1, ax2) = plt.subplots(1, 3)
    fig.suptitle("UMAP: "+ info + " space dim "+str(orig_space_dim))

    ind_l_umap     = [i for i,x in enumerate(umap_T) if x == target]
    Y_umap_l       = np.array([umap_Y[i,:] for i in ind_l_umap])

    ax0.scatter(Y_umap_l[:,0], Y_umap_l[:,1], s=size, c=col, marker=".", linewidth=0)
    ax0.set_title("UMAP, ("+str(len(umap_T))+" of "+ total_train_size+")", fontsize=7)
    
    if train_Y is not None and train_T is not None:
        ind_l_test = [i for i,x in enumerate(train_T) if x == target]
        Y_test_l   = np.array([train_Y[i,:] for i in ind_l_test])
        
        ax1.scatter(Y_test_l[:,0], Y_test_l[:,1], s=size, c=col, marker=".", linewidth=0)
        ax1.set_title("Train, ("+str(len(train_T))+" of "+ total_train_size+")", fontsize=7)

    if test_Y is not None and test_T is not None:
        ind_l_test = [i for i,x in enumerate(test_T) if x == target]
        Y_test_l   = np.array([test_Y[i,:] for i in ind_l_test])

        ax2.scatter(Y_test_l[:,0], Y_test_l[:,1], s=size, c=col, marker=".", linewidth=0)
        ax2.set_title("Test, ("+str(len(test_T))+" of "+ total_test_size+")", fontsize=7)

    plt.savefig(output_dir+"/"+info+"-umap.png")
    plt.close()