在python numpy中，如果我用10^6长度随机生成的list生成numpy array,那么生成耗时0.1s, 但是得到这个array的mean只需要init的2%的时间。 而我自己implement的array得到mean需要十几秒。
所以numpy的array十分黑科技是应为:
1)用底层代码太厉害？
2)init的时候partially compute了某一些中间量？(应为求mean的时间比access慢，比O(n)快 )
如果是2的话能否讲一下大概思路(不需要用python O(n)就能得mean)？
感激不禁！
<code class="language-python"><span class="n">a</span><span class="o">=</span><span class="p">[];</span><span class="n">s</span><span class="o">=</span><span class="mi">0</span><span class="p">;</span><span class="n">n</span><span class="o">=</span><span class="mi">1000000</span> <span class="kn">from</span> <span class="nn">time</span> <span class="kn">import</span><span class="o">*</span> <span class="kn">from</span> <span class="nn">math</span> <span class="kn">import</span><span class="o">*</span> <span class="kn">from</span> <span class="nn">random</span> <span class="kn">import</span><span class="o">*</span> <span class="n">st</span><span class="o">=</span><span class="n">clock</span><span class="p">()</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="nb">range</span><span class="p">(</span><span class="n">n</span><span class="p">):</span> <span class="n">a</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">random</span><span class="p">())</span> <span class="k">for</span> <span class="n">i</span> <span class="ow">in</span> <span class="n">a</span><span class="p">:</span><span class="n">s</span><span class="o">=</span><span class="n">s</span><span class="o">+</span><span class="n">i</span> <span class="n">et</span><span class="o">=</span><span class="n">clock</span><span class="p">()</span> <span class="k">print</span> <span class="s">"mean="</span><span class="p">,</span><span class="n">s</span><span class="o">/</span><span class="n">n</span><span class="p">,</span><span class="s">"time="</span><span class="p">,</span><span class="n">et</span><span class="o">-</span><span class="n">st</span><span class="p">,</span><span class="s">"seconds"</span> </code>
