From 991fe2fe74f0e391f9501667aa01288c047493d6 Mon Sep 17 00:00:00 2001 From: Nataliia Sosnovshchenko Date: Mon, 13 Oct 2025 12:12:42 +0300 Subject: [PATCH] Use URLs for images and badges in README.md --- README.md | 6 +++--- 1 file changed, 3 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index 06b60fe4..e6e34f3f 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,6 @@ ![JOSS](https://joss.theoj.org/papers/3f87f562264c4e5174d9e6ed6d8812aa/status.svg) [![License](https://img.shields.io/badge/License-BSD_2--Clause-orange.svg)](https://opensource.org/licenses/BSD-2-Clause) ![Documentation Status](https://readthedocs.org/projects/pyinterpolate/badge/?version=latest) [![CodeFactor](https://www.codefactor.io/repository/github/dataverselabs/pyinterpolate/badge)](https://www.codefactor.io/repository/github/dataverselabs/pyinterpolate) -[![Run Unit Test via Pytest](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/python-install-and-test-on-linux-always.yml/badge.svg)](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/python-install-and-test-on-linux-always.yml) [![CodeQL](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/github-code-scanning/codeql/badge.svg)](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/github-code-scanning/codeql) ![Tests Coverage](https://github.com/DataverseLabs/pyinterpolate/blob/main/coverage.svg) +[![Run Unit Test via Pytest](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/python-install-and-test-on-linux-always.yml/badge.svg)](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/python-install-and-test-on-linux-always.yml) [![CodeQL](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/github-code-scanning/codeql/badge.svg)](https://github.com/DataverseLabs/pyinterpolate/actions/workflows/github-code-scanning/codeql) ![Tests Coverage](https://raw.githubusercontent.com/DataverseLabs/pyinterpolate/6a18f86ab3927e48009107e7eda7d6c833a4a610/coverage.svg) @@ -10,7 +10,7 @@ **version 1.0.3** -![Logo](pyinterpolate-banner.png) +![Logo](https://raw.githubusercontent.com/DataverseLabs/pyinterpolate/refs/heads/main/pyinterpolate-banner.png) ## Important notice @@ -113,7 +113,7 @@ print(prediction) # [predicted, variance error, lon, lat] With Pyinterpolate you can analyze and transform aggregated data. Here is the example of spatial disaggregation of areal data into point support using Poisson Kriging: -![Example use case](fig1_example.png) +![Example use case](https://raw.githubusercontent.com/DataverseLabs/pyinterpolate/refs/heads/main/fig1_example.png) ## Status