statstream.exact.streaming_var

statstream.exact.streaming_var(X, steps=None)

Variance of a streaming dataset.

Computes the variance of a dataset from a stream of batches of samples. The data has to be provided by an iterator yielding batches of samples. Either a number of steps can be specified, or the iterator is assumed to be emptied in a finite number of steps. In the first case only the given number of batches is extracted from the iterator and used for the variance calculation, even if the iterator could yield more data.

Samples are given along the first axis. The variance has the same shape as the remaining axes, e.g. batches of shape [batch_size, d1, ..., dN] will produce variance of shape [d1, ..., dN].

This function consumes an iterator, thus finite iterators will be empty after a call to this function, unless steps is set to a smaller number than batches in the iterator.

Parameters:

Xiterable

An iterator yielding batches of samples.

stepsint, optional

The number of batches to use from the iterator (all available batches are used if set to None). The defaul is None.

Returns:

array

The variance of the seen data samples.

See also

streaming_mean_and_var

get the mean and variance in a single pass.

Notes

Computing variances necessarily includes computing the mean as well, so there is no computational benefit of using streaming_var over using streaming_mean_and_var.

The streamed variances are calculated as described in [1].

References

[1]

Tony F. Chan & Gene H. Golub & Randall J. LeVeque, “Updating formulae and a pairwise algorithm for computing sample variances”, 1979.