How to crop zero edges of a numpy array?
<p>I have this ugly, un-pythonic beast:</p>



<pre><code>def crop(dat, clp=True):
    '''Crops zero-edges of an array and (optionally) clips it to [0,1].

    Example:
    &gt;&gt;&gt; crop( np.array(
    ...       [[0,0,0,0,0,0],
    ...        [0,0,0,0,0,0],
    ...        [0,1,0,2,9,0],
    ...        [0,0,0,0,0,0],
    ...        [0,7,4,1,0,0],
    ...        [0,0,0,0,0,0]]
    ...     ))
    array([[1, 0, 1, 1],
           [0, 0, 0, 0],
           [1, 1, 1, 0]])
    '''
    if clp: np.clip( dat, 0, 1, out=dat )
    while np.all( dat[0,:]==0 ):
        dat = dat[1:,:]
    while np.all( dat[:,0]==0 ):
        dat = dat[:,1:]
    while np.all( dat[-1,:]==0 ):
        dat = dat[:-1,:]
    while np.all( dat[:,-1]==0 ):
        dat = dat[:,:-1]
    return dat
    # Below gets rid of zero-lines/columns in the middle
    #+so not usable.
    #dat = dat[~np.all(dat==0, axis=1)]      
    #dat = dat[:, ~np.all(dat == 0, axis=0)]
</code></pre>

<p>How do I tame it, and make it beautiful?</p>

<p>Try incorporating something like this:</p>

<pre><code># argwhere will give you the coordinates of every non-zero point
true_points = np.argwhere(dat)
# take the smallest points and use them as the top left of your crop
top_left = true_points.min(axis=0)
# take the largest points and use them as the bottom right of your crop
bottom_right = true_points.max(axis=0)
out = dat[top_left[0]:bottom_right[0]+1,  # plus 1 because slice isn't
          top_left[1]:bottom_right[1]+1]  # inclusive
</code></pre>

<p>This could be expanded without reasonable difficulty for the general <code>n-d</code> case.</p>

python numpy crop