tobac.plotting.histogram_featurewise

tobac.plotting.histogram_featurewise(Track, variable=None, bin_edges=None, density=False)

Create a histogram of a variable from the features (detected objects at a single time step) of a track. Essentially a wrapper of the numpy.histogram() method.

Parameters:

• Track (pandas.DataFrame) – The track containing the variable to create the histogram from.

• variable (string, optional) – Column of the DataFrame with the variable on which the histogram is to be based on. Default is None.

• bin_edges (int or ndarray, optional) – If bin_edges is an int, it defines the number of equal-width bins in the given range. If bins is a sequence, it defines a monotonically increasing array of bin edges, including the rightmost edge.

• density (bool, optional) – If False, the result will contain the number of samples in each bin. If True, the result is the value of the probability density function at the bin, normalized such that the integral over the range is 1. Default is False.

Returns:

• hist (ndarray) – The values of the histogram

• bin_edges (ndarray) – The edges of the histogram

• bin_centers (ndarray) – The centers of the histogram intervalls