# Histograms

## `centers2edges`

apav.core.histogram.centers2edges(data, bin_width)[source]

Convert the x values of a histogram from bin centers to edges. This increases the size of the domain by 1.

Parameters
• data (`ndarray`) – histogram centers

• bin_width (`float`) – width of the bins

Return type

`ndarray`

## `histogram2d`

apav.core.histogram.histogram2d(x, y, extents, bins)[source]

Calculate two dimensional histograms by specifying the number of bins.

Parameters
• x (`ndarray`) – Array 1

• y (`ndarray`) – Array 2

• extents ((`tuple`, `tuple`)) – (tuple, tuple) designating range to perform mass_histogram

• bins – Number of bins

Return type

`ndarray`

## `histogram1d`

apav.core.histogram.histogram1d(data, bin_width, rng)[source]

1d mass_histogram that returns array of counts and array of bin centers.

Parameters
• data (`ndarray`) – data to compute the histogram on

• bin_width (`float`) – bin width of the bins

• rng (`tuple`) – boundaries of the histogram

Return type

`Tuple`[`ndarray`, `ndarray`]

## `histogram2d_binwidth`

apav.core.histogram.histogram2d_binwidth(x, y, extents, bin_width=0.1)[source]

Calculate two dimensional histograms by bin width instead of number of bins.

Parameters
• x (`ndarray`) – Array 1

• y (`ndarray`) – Array 2

• extents ((`tuple`, `tuple`)) – (tuple, tuple) designating range to perform mass_histogram

• bin_width (`float`) – Width of the bins in Daltons

Return type

`ndarray`