From 24f0f409f5c5aa6fcaed6c47703b5d8728708e86 Mon Sep 17 00:00:00 2001 From: SKVP Owner Date: Sun, 27 May 2018 00:50:58 +0300 Subject: [PATCH] readme fix --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index cbf4984..22b1c42 100644 --- a/README.md +++ b/README.md @@ -57,7 +57,7 @@ The function **simpledtw.dtw()** returns 5 outputs: In order to use norms that are different from **L2 distance**, which is the default behavior of **numpy.linalg.norm**, you could use a lambda expression, for example, for L1 distance you could use: ``` >>> norm_func = lambda x : numpy.linalg.norm(x, ord = 1) ->>> matches, mapping_1, mapping_2, matrix = simpledtw.dtw(series_1, series_2, norm_func) +>>> matches, cost, mapping_1, mapping_2, matrix = simpledtw.dtw(series_1, series_2, norm_func) ``` You might want to check NumPy's norm function documentation [here](https://docs.scipy.org/doc/numpy/reference/generated/numpy.linalg.norm.html)