Untitled

import numpy as np
from sklearn.preprocessing import MinMaxScaler
import pandas as pd
import json


def generate_time_series_vector(data, window_size, axis=0):
    X = []
    for i in range(data.shape[axis] - window_size - 1):
        X.append(data[i : i + window_size])
    return np.array(X)


def preprocess(data, window_size=32, scale=True):
    predict_data = pd.DataFrame.from_dict(data, orient="index")

    scaler = MinMaxScaler()
    if scale:
        scale_train_data = scaler.fit_transform(predict_data)
        predict_data = pd.DataFrame(scale_train_data)

    processed_data = generate_time_series_vector(predict_data, window_size)
    return processed_data