在数字信号处理中，信号量化是将连续的信号转换为离散的信号的过程。在量化过程中，我们需要将信号分为均匀的区域，然后将每个区域的幅度表示为一个数字。标量信号是一维信号，向量信号是多维信号。

对于标量信号的量化，我们可以使用下面的代码进行演示：

import numpy as np

Generate a test signal

signal = np.sin(2 * np.pi * 5 * np.linspace(0, 1, 1000))

Define the number of bits for quantization

num_bits = 4

Calculate the range of the signal

signal_range = np.abs(np.min(signal)) + np.abs(np.max(signal))

Calculate the quantization step size

quant_step = signal_range / (2**num_bits)

Quantize the signal

quant_signal = np.floor(signal / quant_step) * quant_step

对于向量信号的量化，我们可以使用下面的代码进行演示：

import numpy as np

Generate a test signal

signal = np.array([[1, 2], [3, 4], [5, 6]])

Define the number of bits for quantization

num_bits = 4

Calculate the range of the signal

signal_range = np.max(signal, axis=0) - np.min(signal, axis=0)

Calculate the quantization step size

quant_step = signal_range / (2**num_bits)

Quantize the signal

quant_signal = np.floor(signal / quant_step) * quant_step