mapclassify.Pooled

class mapclassify.Pooled(Y, classifier='Quantiles', **kwargs)

Applying global binning across columns.

Parameters:

Ynumpy.array

\((n, m)\), values to classify, with \(m>1\).

classifierstr (default ‘Quantiles’)

Name of mapclassify.classifier to apply.

**kwargsdict

Additional keyword arguments for classifier.

Attributes:

global_classifiermapclassify.classifiers.MapClassifier

Instance of the pooled classifier defined as the classifier applied to the union of the columns.

col_classifierlist

Elements are MapClassifier instances with the pooled classifier applied to the associated column of Y.

Examples

>>> import mapclassify
>>> import numpy
>>> n = 20
>>> data = numpy.array([numpy.arange(n)+i*n for i in range(1,4)]).T
>>> res = mapclassify.Pooled(data)

>>> res.col_classifiers[0].counts.tolist()
[12, 8, 0, 0, 0]

>>> res.col_classifiers[1].counts.tolist()
[0, 4, 12, 4, 0]

>>> res.col_classifiers[2].counts.tolist()
[0, 0, 0, 8, 12]

>>> res.global_classifier.counts.tolist()
[12, 12, 12, 12, 12]

>>> res.global_classifier.bins == res.col_classifiers[0].bins
array([ True,  True,  True,  True,  True])

>>> res.global_classifier.bins
array([31.8, 43.6, 55.4, 67.2, 79. ])

__init__(Y, classifier='Quantiles', **kwargs)

Methods

__init__(Y[, classifier])