Useful algorithms., func, which=95, boots=1000)[source]

Determine the confidence interval of a function applied to a data set by bootstrapping.

  • data (pandas.DataFrame) – The data to resample.
  • func (callable) – A function that is called on a resampled data
  • which (int) – The percentile to use for the confidence interval
  • boots (int (default = 1000):) – How many times to bootstrap

The confidence interval.

Return type:

(float, float)

cytoflow.utility.algorithms.percentiles(a, pcts, axis=None)[source]

Like scoreatpercentile but can take and return array of percentiles.

from seaborn:

  • a (array) – data
  • pcts (sequence of percentile values) – percentile or percentiles to find score at
  • axis (int or None) – if not None, computes scores over this axis

scores – array of scores at requested percentiles first dimension is length of object passed to pcts

Return type:


cytoflow.utility.algorithms.bootstrap(*args, **kwargs)[source]

Resample one or more arrays with replacement and store aggregate values. Positional arguments are a sequence of arrays to bootstrap along the first axis and pass to a summary function.

  • n_boot (int, default 10000) – Number of iterations
  • axis (int, default None) – Will pass axis to func as a keyword argument.
  • units (array, default None) – Array of sampling unit IDs. When used the bootstrap resamples units and then observations within units instead of individual datapoints.
  • smooth (bool, default False) – If True, performs a smoothed bootstrap (draws samples from a kernel destiny estimate); only works for one-dimensional inputs and cannot be used units is present.
  • func (callable, default np.mean) – Function to call on the args that are passed in.
  • random_seed (int | None, default None) – Seed for the random number generator; useful if you want reproducible resamples.

  • array – array of bootstrapped statistic values
  • from seaborn (