clustering the consensus motif

[adityabhandwalkar]

Hello

I want to ask a help regarding a coding implementation, here is the code, What I would like to do is to cluster them

def osti(self,path):
        #Reading the data from the file
        df = pd.read_csv(path)
        
        data = np.array(df.iloc[:,0])
        #data = data[0:20000]
        
        split =input('Enter the split size?\n')
        newarr = np.array_split(data, int(split))
        print(newarr)
        # using ostinato function in for patterns discovery in stump
        window_size = input('Enter the window size?\n')
        rad, Ts_idx, Sub_idx = stumpy.ostinato(newarr ,m=int(window_size))
        # finding the motif from splitting array
        con_motif = newarr[Ts_idx][Sub_idx: Sub_idx + int(window_size)]
        nn_idx = []
        # mining every pattern from split array  
        for i, T in enumerate(newarr):
            nn_idx.append(np.argmin(stumpy.core.mass(con_motif, T)))
            lw = 1
            label = None
            if i == Ts_idx:
                lw = 4
                label = 'Consensus Motif'
               
               #label = 
            plt.plot(stumpy.core.z_norm(T[nn_idx[i] : nn_idx[i]+int(window_size)]), lw=lw, label=label)

        plt.title('The Consensus Motif (Z-normalized)')
        plt.xlabel('Time (s)')
        plt.legend()
        plt.show()

How can I use Hierarchical clustering as mentioned in this example ?
[(https://stumpy.readthedocs.io/en/latest/Tutorial_Consensus_Motif.html)]
using the data I have or should I use other clustering methods

Note: data is not labelled