hoi.utils.landscape

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hoi.utils.landscape#

hoi.utils.landscape(x, mult_size, n_bins=100, centered=False, stat='probability', output='numpy')[source]#

Compute the landscape from HOI values.

The landscape represents the how estimates of HOI are distributed per order.

Parameters:
xarray_like

Array of data containing the HOI estimates of shape (n_hoi,)

multi_sizearray_like

Size of the multiplet associated to each HOI estimates. It should be an array of shape (n_hoi,)

n_binsarray_like | 100

Number of bins to use to build the histogram at each order

centeredbool | False

Specify whether bin edges should be centered around zero

stat{‘probability’, ‘frequency’, ‘count’, ‘density’, ‘percent’}

Aggregate statistic to compute in each bin.

  • count: show the number of observations in each bin

  • frequency: show the number of observations divided by the bin width

  • probability or proportion: normalize such that bar heights sum to 1

  • percent: normalize such that bar heights sum to 100

  • density: normalize such that the total area of the histogram equals 1

output{‘numpy’, ‘pandas’, ‘xarray’} | None

Output type. Use either :

  • ‘numpy’: in that case this function will returns the landscape, the unique orders (x-axis) and the central bins (y-axis)

  • ‘pandas’: 2-dimensional pandas dataframe

  • ‘xarray’: 2-dimensional dataarray

Returns:
landcapearray_like

Returns depend on the output parameter. Check to see what is returned

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