from_centers#

classmethod Hist1d.from_centers(values, centers, lower=None, upper=None, title='', xlabel='', ylabel='')[source]#

Initiate a Hist1d instance from values and bin-centers.

If the bins don’t have constant size, at least one limit has to be provided, from which the edges can be determined

Attention

If centers are not the centers of all bins, or if lower or upper are not indeed the lower or upper edge, from_centers will silently produce nonsense.

Parameters:

centersndarray, shape(n)

centers of the bins

lower, uppperfloat, optional

Lower/upper limits of the range.

At least one limit must be provided if bins don’t have a constant size. If both lower and upper limits are provided, the lower one will be prioritized.

titlestr, default “”

Optional title of the histogram.

xlabelstr, default “”

Optional x-label of the histogram.

ylabelstr, default “”

Optional y-label of the histogram.

See also

centers_to_edges

Examples

Initiate a histogram with constant bin sizes:

>>> x = 0.5, 1.5, 2.5, 3.5, 4.5
>>> y =   1,   2,   3,   4,   5
>>> hist = ap.Hist1d.from_centers(x, y)
>>> hist.edges
[0. 1. 2. 3. 4. 5.]

Initiate a histogram with non-constant bin sizes. Then, a lower (or upper) bound has to be passed:

>>> x = 0.5, 1.5, 3.0, 4.5, 5.5
>>> y =   1,   2,   3,   4,   5
>>> hist = ap.Hist1d.from_centers(x, y, lower=0.0)
>>> hist.edges
[0. 1. 2. 4. 5. 6.]