utils/preprocess/projections.py

from numpy import array


def project(time_step: int, test_data, model, days: int = 30):
    x_input = test_data[len(test_data) - time_step :].reshape(1, -1)
    temp_input = list(x_input)
    temp_input = temp_input[0].tolist()
    lst_output = []
    n_steps = time_step
    i = 0
    pred_days = days
    while i < pred_days:
        if len(temp_input) > time_step:
            x_input = array(temp_input[1:])
            # print("{} day input {}".format(i,x_input))
            x_input = x_input.reshape(1, -1)
            x_input = x_input.reshape((1, n_steps, 1))

            yhat = model.predict(x_input, verbose=0)
            # print("{} day output {}".format(i,yhat))
            temp_input.extend(yhat[0].tolist())
            temp_input = temp_input[1:]
            # print(temp_input)

            lst_output.extend(yhat.tolist())
            i = i + 1

        else:
            x_input = x_input.reshape((1, n_steps, 1))
            yhat = model.predict(x_input, verbose=0)
            temp_input.extend(yhat[0].tolist())

            lst_output.extend(yhat.tolist())
            i = i + 1
    return lst_output