47 lines
1.2 KiB
Python
47 lines
1.2 KiB
Python
import numpy as np
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from scipy.stats import rankdata as _sp_rankdata
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# To remove when we support scipy 0.13
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def _rankdata(a, method="average"):
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"""Assign ranks to data, dealing with ties appropriately.
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Ranks begin at 1. The method argument controls how ranks are assigned
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to equal values.
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Parameters
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----------
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a : array_like
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The array of values to be ranked. The array is first flattened.
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method : str, optional
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The method used to assign ranks to tied elements.
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The options are 'max'.
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'max': The maximum of the ranks that would have been assigned
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to all the tied values is assigned to each value.
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Returns
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-------
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ranks : ndarray
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An array of length equal to the size of a, containing rank scores.
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Note
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----
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We only backport the 'max' method
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"""
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if method != "max":
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raise NotImplementedError()
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unique_all, inverse = np.unique(a, return_inverse=True)
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count = np.bincount(inverse, minlength=unique_all.size)
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cum_count = count.cumsum()
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rank = cum_count[inverse]
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return rank
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try:
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_sp_rankdata([1.], 'max')
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rankdata = _sp_rankdata
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except TypeError as e:
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rankdata = _rankdata
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