Project: s41467-024-48446-3 | Function: CT (python)

system: You are an expert Python programmer implementing algorithms from scientific papers.
Complete the masked function based on the algorithm description.
Follow Python best practices and maintain consistent code style.
Return **only** the complete Python function code.

user: Complete this Python function:

**DESCRIPTION:** Conjoint Triad (CT) method for protein sequence feature encoding, converting amino acid sequences into numerical feature vectors by classifying 20 amino acids into 7 groups based on dipoles and volumes, then counting occurrence frequencies of consecutive triplets to generate 343-dimensional feature representations

**KEY TERMS:** {
  "classMap": "amino acid to class mapping based on physicochemical properties",
  "coding": "343-dimensional feature vector representing triplet frequencies",
  "seq": "protein sequence converted to class representation",
  "index": "position in feature vector calculated from triplet classes",
  "length": "protein sequence length for sliding window processing"
}

**CONTEXT CODE:** import numpy as np
import pandas as pd
import h5py
from tqdm import tqdm

# def find_amino_acid(x):
#     return ('B' in x) | ('O' in x) | ('J' in x) | ('U' in x) | ('X' in x) | ('Z' in x)
def write_fasta(database, save_path):
    filename = save_path + "uniprot_seq.fas"
    with open(filename, "w") as f:
        for i,row in database.iterrows():
            f.write(">" + str(i) + "\n")
            f.write(row['Sequence'] + "\n")

def CT(sequence):
    """Conjoint Triad (CT) method for protein sequence feature encoding, converting amino acid sequences into numerical feature vectors by classifying 20 amino acids into 7 groups based on dipoles and volumes"""
    raise NotImplementedError("Function has been masked for testing purposes")

if __name__ == "__main__":
    print("Start processing data from the Uniprot database...")
    print("Importing data...")
    data_path = "../data/"
    uniprot = pd.read_csv(data_path + "uniprot.tsv", sep="\t")
    # uniprot = uniprot.loc[~uniprot['Sequence'].apply(find_amino_acid)]
    # uniprot.reset_index(drop = True, inplace = True)
    uniprot.loc[:,'features_seq'] = uniprot['Sequence'].apply(CT)

    print("Collect all CT embeddings")
    features = h5py.File(data_path + "DeepDSI_features.hdf5", "w")
    for i in tqdm(range(len(uniprot))):
        group = features.create_group(uniprot.loc[i, "Entry"])
        group.create_dataset("E", data=uniprot.loc[i, "features_seq"])
        dt = h5py.special_dtype(vlen=str)
        group.create_dataset("S", dtype=dt, data=uniprot.loc[i, "Sequence"])
    features.close()

    # print("Start generating FAS files for building local BLAST")
    write_fasta(uniprot, save_path = data_path + "blast/")

    print("The end")

Complete the function implementation replacing "raise NotImplementedError".