# histogram1d

sherpa.utils.histogram1d(x, x_lo, x_hi)[source] [edit on github]

Create a 1D histogram from a sequence of samples.

See the `numpy.histogram` routine for a version with more options.

Changed in version 4.15.0: The x_lo and x_hi arguments are no-longer changed (sorted) by this routine.

Parameters:
• x (sequence of numbers) – The array of samples

• x_lo (sequence of numbers) – The lower-edges of each bin.

• x_hi (sequence of numbers) – The upper-edges of each bin, which must be the same size as `x_lo`.

Returns:

y – The number of samples in each histogram bin defined by the `x_lo` and `x_hi` arrays.

Return type:

NumPy array

Examples

A simple example, calculating the histogram of 1000 values randomly distributed over [0, 1).

```>>> x = np.random.random(1000)
>>> edges = np.arange(0, 1.1, 0.1)
>>> xlo = edges[:-1]
>>> xhi = edges[1:]
>>> y = histogram1d(x, xlo, xhi)
```

Given a list of samples, bin them up so that they can be used as the dependent axis (the value to be fitted) in a Sherpa data set:

```>>> dataspace1d(1, 10, 1)
>>> lo, hi = get_indep()
>>> n = histogram1d([2, 3, 2, 8, 5, 2], lo, hi)
>>> set_dep(n)
```