tobac.analysis.cell_analysis.lifetime_histogram#

tobac.analysis.cell_analysis.lifetime_histogram(Track, bin_edges=array([0, 20, 40, 60, 80, 100, 120, 140, 160, 180]), density=False, return_values=False)#

Compute the lifetime histogram of tracked cells.

Parameters:

  • Track (pandas.DataFrame) – Dataframe of linked features, containing the columns ‘cell’ and ‘time_cell’.

  • 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 ndarray, it defines a monotonically increasing array of bin edges, including the rightmost edge. The unit is minutes. Default is np.arange(0, 200, 20).

  • 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.

  • return_values (bool, optional) – Bool determining wether the lifetimes of the features are returned from this function. 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.

  • minutes, optional (ndarray) – Numpy.array of the lifetime of each feature in minutes. Returned if return_values is True.

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