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# medpy.metric.histogram.minowski¶

medpy.metric.histogram.minowski(h1, h2, p=2)[source]

Minowski distance.

With $$p=2$$ equal to the Euclidean distance, with $$p=1$$ equal to the Manhattan distance, and the Chebyshev distance implementation represents the case of $$p=\pm inf$$.

The Minowksi distance between two histograms $$H$$ and $$H'$$ of size $$m$$ is defined as:

$d_p(H, H') = \left(\sum_{m=1}^M|H_m - H'_m|^p \right)^{\frac{1}{p}}$

Attributes:

• a real metric

Attributes for normalized histograms:

• $$d(H, H')\in[0, \sqrt[p]{2}]$$
• $$d(H, H) = 0$$
• $$d(H, H') = d(H', H)$$

Attributes for not-normalized histograms:

• $$d(H, H')\in[0, \infty)$$
• $$d(H, H) = 0$$
• $$d(H, H') = d(H', H)$$

Attributes for not-equal histograms:

• not applicable
Parameters: h1 : sequence The first histogram. h2 : sequence The second histogram. p : float The $$p$$ value in the Minowksi distance formula. minowski : float Minowski distance. ValueError If p is zero.