On Fri, Aug 29, 2008 at 2:35 PM, Christopher Barker <[EMAIL PROTECTED]> wrote: > HI all, > > I need to do something I thought would be simple -- set all the values > of an array to some minimum. so I did this: > > >>> min_value = 2 > >>> a = np.array((1, 2, 3, 4, 5,)) > >>> np.maximum(a, min_value) > array([2, 2, 3, 4, 5]) > > all was well... then I realized that a could have negative numbers in > in, and I really wanted the absolute value to be greater than than minimum: > > >>> a = np.array((1, 2, 3, 4, -5,)) > >>> np.maximum(a, min_value) > array([2, 2, 3, 4, 2]) > > oops! > > so I added a sign() and abs(): > > >>> np.sign(a) * np.maximum(np.abs(a), min_value) > array([ 2, 2, 3, 4, -5]) > > all was well. However it turns out a could contain a zero: > > >>> a = np.array((0, 1, 2, 3, 4, -5,)) > >>> np.sign(a) * np.maximum(np.abs(a), min_value) > array([ 0, 2, 2, 3, 4, -5]) > > Darn! I want that zero to become a 2, but sign(0) = 0, so that doesn't > work. > > How can I do this without another line of code special casing the 0, > which isn't that big I deal, but it seems kind of ugly... > > >>> a[a==0] = min_value > >>> np.sign(a) * np.maximum(np.abs(a), min_value) > array([ 2, 2, 2, 3, 4, -5])
Does this work? >> x array([ 1., 2., -5., -1., 0.]) >> np.sign(x) * np.clip(np.absolute(x), 2, np.inf) array([ 2., 2., -5., -2., 0.]) _______________________________________________ Numpy-discussion mailing list [email protected] http://projects.scipy.org/mailman/listinfo/numpy-discussion
