diff options
Diffstat (limited to 'numpy/lib/function_base.py')
| -rw-r--r-- | numpy/lib/function_base.py | 47 |
1 files changed, 28 insertions, 19 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index 96c3f2a35..7c5f0c5af 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -58,7 +58,7 @@ def iterable(y): except: return 0 return 1 -def histogram(a, bins=10, range=None, normed=False, weights=None): +def histogram(a, bins=10, range=None, normed=False, weights=None, density=None): """ Compute the histogram of a set of data. @@ -76,17 +76,27 @@ def histogram(a, bins=10, range=None, normed=False, weights=None): is simply ``(a.min(), a.max())``. Values outside the range are ignored. normed : bool, optional + This keyword is deprecated in Numpy 1.6 due to confusing/buggy + behavior. It will be removed in Numpy 2.0. Use the density keyword + instead. If False, the result will contain the number of samples in each bin. If True, the result is the value of the probability *density* function at the bin, normalized such that - the *integral* over the range is 1. Note that the sum of the - histogram values will not be equal to 1 unless bins of unity - width are chosen; it is not a probability *mass* function. + the *integral* over the range is 1. Note that this latter behavior is + known to be buggy with unequal bin widths; use `density` instead. weights : array_like, optional An array of weights, of the same shape as `a`. Each value in `a` only contributes its associated weight towards the bin count (instead of 1). If `normed` is True, the weights are normalized, so that the integral of the density over the range remains 1 + density : bool, optional + If False, the result will contain the number of samples + in each bin. If True, the result is the value of the + probability *density* function at the bin, normalized such that + the *integral* over the range is 1. Note that the sum of the + histogram values will not be equal to 1 unless bins of unity + width are chosen; it is not a probability *mass* function. + Overrides the `normed` keyword if given. Returns ------- @@ -116,13 +126,13 @@ def histogram(a, bins=10, range=None, normed=False, weights=None): -------- >>> np.histogram([1, 2, 1], bins=[0, 1, 2, 3]) (array([0, 2, 1]), array([0, 1, 2, 3])) - >>> np.histogram(np.arange(4), bins=np.arange(5), normed=True) + >>> np.histogram(np.arange(4), bins=np.arange(5), density=True) (array([ 0.25, 0.25, 0.25, 0.25]), array([0, 1, 2, 3, 4])) >>> np.histogram([[1, 2, 1], [1, 0, 1]], bins=[0,1,2,3]) (array([1, 4, 1]), array([0, 1, 2, 3])) >>> a = np.arange(5) - >>> hist, bin_edges = np.histogram(a, normed=True) + >>> hist, bin_edges = np.histogram(a, density=True) >>> hist array([ 0.5, 0. , 0.5, 0. , 0. , 0.5, 0. , 0.5, 0. , 0.5]) >>> hist.sum() @@ -155,10 +165,8 @@ def histogram(a, bins=10, range=None, normed=False, weights=None): mn -= 0.5 mx += 0.5 bins = linspace(mn, mx, bins+1, endpoint=True) - uniform = True else: bins = asarray(bins) - uniform = False if (np.diff(bins) < 0).any(): raise AttributeError( 'bins must increase monotonically.') @@ -191,18 +199,19 @@ def histogram(a, bins=10, range=None, normed=False, weights=None): n = np.diff(n) - if normed: - db = array(np.diff(bins), float) - if not uniform: - warnings.warn(""" - This release of NumPy (1.6) fixes a normalization bug in histogram - function occuring with non-uniform bin widths. The returned value - is now a density: n / (N * bin width), where n is the bin count and - N the total number of points. - """) - return n/db/n.sum(), bins + if density is not None: + if density: + db = array(np.diff(bins), float) + return n/db/n.sum(), bins + else: + return n, bins else: - return n, bins + # deprecated, buggy behavior. Remove for Numpy 2.0 + if normed: + db = array(np.diff(bins), float) + return n/(n*db).sum(), bins + else: + return n, bins def histogramdd(sample, bins=10, range=None, normed=False, weights=None): |