diff options
Diffstat (limited to 'numpy/lib/function_base.py')
| -rw-r--r-- | numpy/lib/function_base.py | 16 |
1 files changed, 11 insertions, 5 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index b2ec9bb5a..7610c2db3 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -2924,7 +2924,7 @@ def percentile(a, q, axis=None, out=None, overwrite_input=False): ----- Given a vector V of length N, the qth percentile of V is the qth ranked value in a sorted copy of V. A weighted average of the two nearest neighbors - is used if the normalized ranking does not match q exactly. + is used if the normalized ranking does not match q exactly. The same as the median if q is 0.5; the same as the min if q is 0; and the same as the max if q is 1 @@ -2962,7 +2962,7 @@ def percentile(a, q, axis=None, out=None, overwrite_input=False): return a.min(axis=axis, out=out) elif q == 100: return a.max(axis=axis, out=out) - + if overwrite_input: if axis is None: sorted = a.ravel() @@ -3072,11 +3072,11 @@ def trapz(y, x=None, dx=1.0, axis=-1): array([ 2., 8.]) """ - y = asarray(y) + y = asanyarray(y) if x is None: d = dx else: - x = asarray(x) + x = asanyarray(x) if x.ndim == 1: d = diff(x) # reshape to correct shape @@ -3090,7 +3090,13 @@ def trapz(y, x=None, dx=1.0, axis=-1): slice2 = [slice(None)]*nd slice1[axis] = slice(1,None) slice2[axis] = slice(None,-1) - return add.reduce(d * (y[slice1]+y[slice2])/2.0,axis) + try: + ret = (d * (y[slice1] +y [slice2]) / 2.0).sum(axis) + except ValueError: # Operations didn't work, cast to ndarray + d = np.asarray(d) + y = np.asarray(y) + ret = add.reduce(d * (y[slice1]+y[slice2])/2.0, axis) + return ret #always succeed def add_newdoc(place, obj, doc): |