Merge pull request #31 from m2lines/fix-links

Fixed binder and leaphub links in notebooks
m2lines · Feb 24, 2024 · aa2f149 · aa2f149
2 parents f31bb9d + 4bfce6b
commit aa2f149
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diff --git a/src/notebooks/OM4_SE_animation.ipynb b/src/notebooks/OM4_SE_animation.ipynb
@@ -4,16 +4,11 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "# OM4 Animation\n",
+    "\n",
     "To run this notebook, you will have to use LEAP-Pangeo hub!\n",
     "\n",
-    "<a href=\"https://leap.2i2c.cloud/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fm2lines%2Fdata-gallery&urlpath=lab%2Ftree%2Fdata-gallery%2Fnotebooks%2FOM4_SE_animation.ipynb&branch=main\"><img src=\"https://custom-icon-badges.demolab.com/badge/LEAP-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:30px;\"></a>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# OM4 Animation\n",
+    "<a href=\"https://leap.2i2c.cloud/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fm2lines%2Fdata-gallery&urlpath=lab%2Ftree%2Fdata-gallery%2Fsrc%2Fnotebooks%2FOM4_SE_animation.ipynb&branch=main\"><img src=\"https://custom-icon-badges.demolab.com/badge/LEAP-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:30px;\"></a>\n",
     "\n",
     "In this notebook, we will visualize the OM4 data using the `xarray` and `matplotlib` libraries and create an animation of the Surface Kinetic Energy over time. We will explore visualizations in both global and regional scales. \n",
     "\n",

diff --git a/src/notebooks/pycnocline_depth_mom6.ipynb b/src/notebooks/pycnocline_depth_mom6.ipynb
diff --git a/src/notebooks/xarray_intro.ipynb b/src/notebooks/xarray_intro.ipynb
@@ -4,18 +4,13 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "# Introduction to Xarray\n",
+    "\n",
     "Before we get started, you may choose to run this notebook on LEAP-Pangeo hub or Binder!\n",
     "\n",
-    "<a href=\"https://leap.2i2c.cloud/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fm2lines%2Fdata-gallery&urlpath=lab%2Ftree%2Fdata-gallery%2Fnotebooks%2Fxarray_intro.ipynb&branch=main\"><img src=\"https://custom-icon-badges.demolab.com/badge/LEAP-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:30px;\"></a>\n",
+    "<a href=\"https://leap.2i2c.cloud/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fm2lines%2Fdata-gallery&urlpath=lab%2Ftree%2Fdata-gallery%2Fsrc%2Fnotebooks%2Fxarray_intro.ipynb&branch=main\"><img src=\"https://custom-icon-badges.demolab.com/badge/LEAP-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:30px;\"></a>\n",
     "\n",
-    "<a href=\"https://mybinder.org/v2/gh/m2lines/data-gallery/main?labpath=notebooks%2Fxarray_intro.ipynb\"><img src=\"https://custom-icon-badges.demolab.com/badge/Binder-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:28px;\"></a>"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Introduction to Xarray\n",
+    "<a href=\"https://mybinder.org/v2/gh/m2lines/data-gallery/main?labpath=src%2Fnotebooks%2Fxarray_intro.ipynb\"><img src=\"https://custom-icon-badges.demolab.com/badge/Binder-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:28px;\"></a>\n",
     "\n",
     "[Xarray](https://github.com/pydata/xarray) is an open source Python package designed to work with lablled multidimensional arrays in an efficient manner. By multidimensional data (also often called N-dimensional), we mean data with many independent dimensions or axes. For example, we might represent Earth’s surface temperature $T$ as a three dimensional variable:\n",
     "\n",

diff --git a/src/notebooks/xgcm_intro.ipynb b/src/notebooks/xgcm_intro.ipynb
@@ -8,9 +8,9 @@
     "\n",
     "Before we get started, you may choose to run this notebook on LEAP-Pangeo hub or Binder!\n",
     "\n",
-    "<a href=\"https://leap.2i2c.cloud/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fm2lines%2Fdata-gallery&urlpath=lab%2Ftree%2Fdata-gallery%2Fnotebooks%2Fxgcm_intro.ipynb&branch=main\"><img src=\"https://custom-icon-badges.demolab.com/badge/LEAP-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:30px;\"></a>\n",
+    "<a href=\"https://leap.2i2c.cloud/hub/user-redirect/git-pull?repo=https%3A%2F%2Fgithub.com%2Fm2lines%2Fdata-gallery&urlpath=lab%2Ftree%2Fdata-gallery%2Fsrc%2Fnotebooks%2Fxgcm_intro.ipynb&branch=main\"><img src=\"https://custom-icon-badges.demolab.com/badge/LEAP-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:30px;\"></a>\n",
     "\n",
-    "<a href=\"https://mybinder.org/v2/gh/m2lines/data-gallery/main?labpath=notebooks%2Fxgcm_intro.ipynb\"><img src=\"https://custom-icon-badges.demolab.com/badge/Binder-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:28px;\"></a>\n",
+    "<a href=\"https://mybinder.org/v2/gh/m2lines/data-gallery/main?labpath=src%2Fnotebooks%2Fxgcm_intro.ipynb\"><img src=\"https://custom-icon-badges.demolab.com/badge/Binder-Launch%20%F0%9F%9A%80-blue?style=for-the-badge&logo=leap-globe\" style=\"height:28px;\"></a>\n",
     "\n",
     "[Xgcm](https://xgcm.readthedocs.io/en/latest/index.html) is a python packge for working with the datasets produced by numerical General Circulation Models (GCMs) and similar gridded datasets that are amenable to finite volume analysis. In these datasets, different variables are located at different positions with respect to a volume or area element (e.g. cell center, cell face, etc.) xgcm solves the problem of how to interpolate and difference these variables from one position to another.\n",
     "\n",