From 1682d2b20b489ae1d781ec765b5423d6b3400d66 Mon Sep 17 00:00:00 2001 From: Ross Barnowski Date: Sat, 8 Nov 2025 14:20:04 -0800 Subject: [PATCH] MAINT: rm todo related to scipy minver. --- content/tutorial-svd.md | 6 +----- 1 file changed, 1 insertion(+), 5 deletions(-) diff --git a/content/tutorial-svd.md b/content/tutorial-svd.md index 494a4d3b..50fb1d72 100644 --- a/content/tutorial-svd.md +++ b/content/tutorial-svd.md @@ -38,11 +38,7 @@ After this tutorial, you should be able to: In this tutorial, we will use a [matrix decomposition](https://en.wikipedia.org/wiki/Matrix_decomposition) from linear algebra, the Singular Value Decomposition, to generate a compressed approximation of an image. We'll use the `face` image from the [scipy.datasets](https://docs.scipy.org/doc/scipy/reference/datasets.html) module: ```{code-cell} -# TODO: Rm try-except with scipy 1.10 is the minimum supported version -try: - from scipy.datasets import face -except ImportError: # Data was in scipy.misc prior to scipy v1.10 - from scipy.misc import face +from scipy.datasets import face img = face() ```