擅长:python、mysql、java
<p>从<a href="http://shop.oreilly.com/product/0636920023784.do" rel="noreferrer">Python for Data Analysis</a>开始,模块<code>numpy.random</code>用函数来补充Python <code>random</code>,从而有效地从多种概率分布中生成样本值的整个数组。</p>
<p>相比之下,Python的内置<code>random</code>模块一次只采样一个值,而<code>numpy.random</code>可以更快地生成非常大的样本。使用IPython magic函数<code>%timeit</code>可以看到哪个模块执行得更快:</p>
<pre><code>In [1]: from random import normalvariate
In [2]: N = 1000000
In [3]: %timeit samples = [normalvariate(0, 1) for _ in xrange(N)]
1 loop, best of 3: 963 ms per loop
In [4]: %timeit np.random.normal(size=N)
10 loops, best of 3: 38.5 ms per loop
</code></pre>