recipe_clustering.py 文件源码

def tsne_cluster_cuisine(df,sublist):
    lenlist=[0]
    df_sub = df[df['cuisine']==sublist[0]]
    lenlist.append(df_sub.shape[0])
    for cuisine in sublist[1:]:
        temp = df[df['cuisine']==cuisine]
        df_sub = pd.concat([df_sub, temp],axis=0,ignore_index=True)
        lenlist.append(df_sub.shape[0])
    df_X = df_sub.drop(['cuisine','recipeName'],axis=1)
    print df_X.shape, lenlist

    dist = squareform(pdist(df_X, metric='cosine'))
    tsne = TSNE(metric='precomputed').fit_transform(dist)

    palette = sns.color_palette("hls", len(sublist))
    plt.figure(figsize=(10,10))
    for i,cuisine in enumerate(sublist):
        plt.scatter(tsne[lenlist[i]:lenlist[i+1],0],\
        tsne[lenlist[i]:lenlist[i+1],1],c=palette[i],label=sublist[i])
    plt.legend()

#interactive plot with boken; set up for four categories, with color palette; pass in df for either ingredient or flavor