diff options
Diffstat (limited to 'numpy/lib/function_base.py')
-rw-r--r-- | numpy/lib/function_base.py | 40 |
1 files changed, 25 insertions, 15 deletions
diff --git a/numpy/lib/function_base.py b/numpy/lib/function_base.py index d7ba85add..02e7f605e 100644 --- a/numpy/lib/function_base.py +++ b/numpy/lib/function_base.py @@ -67,21 +67,31 @@ def iterable(y): return 1 def histogram(a, bins=10, range=None, normed=False): - """histogram(sample, bins = 10, range = None, normed = False) -> H, ledges - - Return the distribution of a sample. - - Parameters - ---------- - bins: Number of bins - range: Lower and upper bin edges (default: [sample.min(), sample.max()]). - All values greater than range are stored in the last bin. - normed: If False (default), return the number of samples in each bin. - If True, return a frequency distribution. - - Output - ------ - histogram array, left bin edges array. + """Compute the histogram from a set of data. + + :Parameters: + - `a` : array + The data to histogram. n-D arrays will be flattened. + - `bins` : int or sequence of floats, optional + If an int, then the number of equal-width bins in the given range. + Otherwise, a sequence of the lower bound of each bin. + - `range` : (float, float), optional + The lower and upper range of the bins. If not provided, then (a.min(), + a.max()) is used. Values outside of this range are allocated to the + closest bin. + - `normed` : bool, optional + If False, the result array will contain the number of samples in each bin. + If True, the result array 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 all of the histogram values will not usually + be 1; it is not a probability *mass* function. + + :Returns: + - `hist` : array (n,) + The values of the histogram. See `normed` for a description of the + possible semantics. + - `lower_edges` : float array (n,) + The lower edges of each bin. """ a = asarray(a).ravel() if not iterable(bins): |