cytoflow.utility.algorithms¶
Useful algorithms.
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cytoflow.utility.algorithms.
ci
(data, func, which=95, boots=1000)[source]¶ Determine the confidence interval of a function applied to a data set by bootstrapping.
Parameters: - 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
Returns: The confidence interval.
Return type: (float, float)
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cytoflow.utility.algorithms.
percentiles
(a, pcts, axis=None)[source]¶ Like scoreatpercentile but can take and return array of percentiles.
from seaborn: https://github.com/mwaskom/seaborn/blob/master/seaborn/utils.py
Parameters: - 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
Returns: scores – array of scores at requested percentiles first dimension is length of object passed to
pcts
Return type: array
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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.
Parameters: - 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.
Returns: - array – array of bootstrapped statistic values
- from seaborn (https://github.com/mwaskom/seaborn/blob/master/seaborn/algorithms.py)