#!/usr/bin/python3
# -*- coding: utf-8 -*-
from typing import List

import matplotlib.pyplot as plt
import numpy as np


def process_speech_probs(signal: np.ndarray, speech_probs: List[float], frame_step: int) -> np.ndarray:
    speech_probs_ = list()
    for p in speech_probs[1:]:
        speech_probs_.extend([p] * frame_step)

    pad = (signal.shape[0] - len(speech_probs_))
    speech_probs_ = speech_probs_ + [0.0] * pad
    speech_probs_ = np.array(speech_probs_, dtype=np.float32)

    if len(speech_probs_) != len(signal):
        raise AssertionError
    return speech_probs_


def make_visualization(signal: np.ndarray, speech_probs, sample_rate: int):
    time = np.arange(0, len(signal)) / sample_rate
    plt.figure(figsize=(12, 5))
    plt.plot(time, signal, color='b')
    plt.plot(time, speech_probs, color='gray')
    plt.show()
    return


if __name__ == "__main__":
    pass