NumPy

README.md

@@ -2652,7 +2652,7 @@ import numpy as np
 ```
 
 ```python
-<array> = np.copy/int64/float64(<array>)                # Returns new array of the same shape.
+<array> = np.copy/abs/sqrt/log/int64(<array>)           # Returns new array of the same shape.
 <array> = <array>.sum/max/mean/argmax/all([axis])       # Passed dimension gets aggregated.
 <array> = np.apply_along_axis(<func>, axis, <array>)    # Func can return a scalar or array.
 ```

index.html

@@ -2170,7 +2170,7 @@ drawer = cg.output.GraphvizOutput(output_file=filename)
 &lt;array&gt; = &lt;array&gt;.flatten()                             <span class="hljs-comment"># Also `&lt;view&gt; = &lt;array&gt;.ravel()`.</span>
 &lt;view&gt;  = &lt;array&gt;.transpose()                           <span class="hljs-comment"># Also `&lt;view&gt; = &lt;array&gt;.T`.</span>
 </code></pre>
-<pre><code class="python language-python hljs">&lt;array&gt; = np.copy/int64/float64(&lt;array&gt;)                <span class="hljs-comment"># Returns new array of the same shape.</span>
+<pre><code class="python language-python hljs">&lt;array&gt; = np.copy/abs/sqrt/log/int64(&lt;array&gt;)           <span class="hljs-comment"># Returns new array of the same shape.</span>
 &lt;array&gt; = &lt;array&gt;.sum/max/mean/argmax/all([axis])       <span class="hljs-comment"># Passed dimension gets aggregated.</span>
 &lt;array&gt; = np.apply_along_axis(&lt;func&gt;, axis, &lt;array&gt;)    <span class="hljs-comment"># Func can return a scalar or array.</span>
 </code></pre>