Quick numpy array extension
<p>I wonder if there is a trick to extending a numpy array with consecutive
numbers in between each original values, up to a user controlled default length. Perhaps there is already a built-in function that turns x into y</p>

<pre><code>x=np.array([4,8,4,10])

y=np.array([4,5,6,7,8,9,10,11,4,5,6,7,10,11,12,13])
</code></pre>

<p>Here the length between each element that I added was three. Speed is of the essence here. I need something like this for my column data to work in creating a sparse
matrix.</p>

<p>Also, if I have an array such as </p>

<pre><code>s=np.array([0,1])
</code></pre>

<p>is there a quick way to extend each element an arbitrary amount of
times, lets say 4 for example:</p>

<pre><code>s=np.array([0,0,0,0,1,1,1,1])
</code></pre>

<p>Broadcasted addition is probably the fastest</p>

<pre><code>In [241]: (x[:,None]+np.arange(4)).ravel()
Out[241]: array([ 4,  5,  6,  7,  8,  9, 10, 11,  4,  5,  6,  7, 10, 11, 12, 13])
</code></pre>

<p>It gets trickier if adding different amounts for each sublist. </p>

<p><code>repeat</code> is useful:</p>

<pre><code>In [242]: np.repeat(np.array([0,1]),[3,4])
Out[242]: array([0, 0, 0, 1, 1, 1, 1])
</code></pre>

<p><code>tile</code> is another good tool.</p>

python arrays numpy