Merge pull request #155 from ocefpaf/fix_links

build with linkchecker

.github/workflows/deploy-docs.yml

@@ -24,7 +24,7 @@ jobs:
         shell: bash -l {0}
         run: |
           set -e
-          jupyter-book build jupyterbook
+          jupyter-book build jupyterbook --builder linkcheck
 
       - name: GitHub Pages action
         if: github.ref == 'refs/heads/main'

jupyterbook/_config.yml

@@ -35,6 +35,7 @@ parse:
     - substitution
 
   myst_url_schemes: [mailto, http, https] # URI schemes that will be recognized as external URLs in Markdown links
+  myst_dmath_double_inline: true  # Allow display math ($$) within an inline context
 
 #######################################################################################
 # HTML-specific settings
@@ -55,7 +56,7 @@ html:
     (240) 533-9444
   google_analytics_id: "G-546J258RCJ"
   home_page_in_navbar: false # Whether to include your home page in the left Navigation Bar
-  baseurl: "" # The base URL where your book will be hosted. Used for creating image previews and social links. e.g.: https://mypage.com/mybook/
+  baseurl: "https://ioos.github.io/ioos_code_lab/" # The base URL where your book will be hosted. Used for creating image previews and social links. e.g.: https://mypage.com/mybook/
   comments:
     hypothesis: false
     utterances: false
@@ -83,4 +84,18 @@ repository:
 # Advanced and power-user settings
 sphinx:
   config:
+    linkcheck_anchors_ignore: ["aboutPanel", "searchPanel", "!forum/ioos_tech"]
     html_show_copyright: false
+    myst_heading_anchors: 3
+    nb_mime_priority_overrides: [
+      ["html", "application/vnd.jupyter.widget-view+json", 10],
+      ["html", "application/javascript", 20],
+      ["html", "text/html", 30],
+      ["html", "image/svg+xml", 40],
+      ["html", "image/png", 50],
+      ["html", "image/gif", 60],
+      ["html", "image/jpeg", 70],
+      ["html", "text/markdown", 80],
+      ["html", "text/latex", 90],
+      ["html", "text/plain", 100]
+    ]

jupyterbook/content/Video_Demo_Markdown/ioos.md

@@ -9,5 +9,4 @@ align: center
 ```
 
 - [COMT Tutorial](https://www.youtube.com/watch?v=Dqc1C1HeemQ)
-- [IOOS EDS Demo](https://nccospublicstor.blob.core.windows.net/ioos/ioos_demo_1280.mp4)
 - [MBON Portal Tutorial](https://www.youtube.com/watch?v=ZITqDRa6u9c)

jupyterbook/content/code_gallery/data_access_notebooks/2016-10-12-fetching_data.ipynb

@@ -51,7 +51,7 @@
     "Updated: 2022-05-26\n",
     "\n",
     "In this post we will use `erddapy` to find and download data from the\n",
-    "[Center for Operational Oceanographic Products and Services (CO-OPS)](https://opendap.co-ops.nos.noaa.gov/erddap/) ERDDAP server.\n",
+    "[Center for Operational Oceanographic Products and Services (CO-OPS)](https://opendap.co-ops.nos.noaa.gov/erddap/index.html) ERDDAP server.\n",
     "\n",
     "Here we will fetch data during the [hurricane Matthew](https://en.wikipedia.org/wiki/Hurricane_Matthew) passage over the southeast states from 2016-10-05 to 2016-10-12. The first step is to instantiate the server object and then add the constraints for our query."
    ]
@@ -78,7 +78,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The geographical bounding box includes all the states in the [SECOORA](http://secoora.org/) region: Florida, Georgia, South and North Carolina."
+    "The geographical bounding box includes all the states in the [SECOORA](https://secoora.org/) region: Florida, Georgia, South and North Carolina."
    ]
   },
   {
@@ -1691,7 +1691,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

jupyterbook/content/code_gallery/data_access_notebooks/2016-11-15-glider_data_example.ipynb

@@ -50,7 +50,7 @@
     "\n",
     "Updated: 2022-05-25\n",
     "\n",
-    "In this notebook we demonstrate how to obtain and plot glider data using cf-xarray . We will explore data from the Rutgers University RU29 [Challenger](http://challenger.marine.rutgers.edu) glider that was launched from Ubatuba, Brazil on June 23, 2015 to travel across the Atlantic Ocean. After 282 days at sea, the Challenger was picked up off the coast of South Africa, on March 31, 2016. For more information on this ground breaking excusion see: [https://marine.rutgers.edu/main/announcements/the-challenger-glider-mission-south-atlantic-mission-complete](https://marine.rutgers.edu/main/announcements/the-challenger-glider-mission-south-atlantic-mission-complete)\n",
+    "In this notebook we demonstrate how to obtain and plot glider data using cf-xarray . We will explore data from the Rutgers University RU29 [Challenger](https://challenger.marine.rutgers.edu/) glider that was launched from Ubatuba, Brazil on June 23, 2015 to travel across the Atlantic Ocean. After 282 days at sea, the Challenger was picked up off the coast of South Africa, on March 31, 2016. For more information on this ground breaking excusion see: [https://marine.rutgers.edu/announcements/the-challenger-glider-mission-south-atlantic-mission-complete](https://marine.rutgers.edu/announcements/the-challenger-glider-mission-south-atlantic-mission-complete)\n",
     "\n",
     "Data collected from this glider mission are available on the IOOS Glider DAC THREDDS via OPeNDAP."
    ]
@@ -906,7 +906,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

jupyterbook/content/code_gallery/data_access_notebooks/2016-12-20-searching_glider_deployments.ipynb

@@ -50,9 +50,9 @@
     "\n",
     "Modified: 2023-09-04\n",
     "\n",
-    "IOOS provides an [`API`](https://en.wikipedia.org/wiki/Application_programming_interface) for getting information on all the glider deployments available in the [Glider DAC](https://gliders.ioos.us/index.html).\n",
+    "IOOS provides an [`API`](https://en.wikipedia.org/wiki/Application_programming_interface) for getting information on all the glider deployments available in the [Glider DAC](https://gliders.ioos.us/).\n",
     "\n",
-    "The raw JSON can be accessed at [https://data.ioos.us/gliders/providers/api/deployment](https://data.ioos.us/gliders/providers/api/deployment) and it is quite simple to parse it with Python.\n",
+    "The raw JSON can be accessed at [https://gliders.ioos.us/providers/api/deployment](https://gliders.ioos.us/providers/api/deployment) and it is quite simple to parse it with Python.\n",
     "\n",
     "First, lets check how many glider deployments exist in the Glider DAC."
    ]

jupyterbook/content/code_gallery/data_access_notebooks/2017-03-21-ERDDAP_IOOS_Sensor_Map.ipynb

@@ -52,7 +52,7 @@
     "\n",
     "Web Map Services are a great way to find data you may be looking for in a particular geographic area.\n",
     "\n",
-    "Suppose you are exploring the [IOOS Sensor Map](https://sensors.ioos.us/#map),\n",
+    "Suppose you are exploring the [IOOS Sensor Map](https://sensors.ioos.us/),\n",
     "you select Oxygen and click on the only returned value, the Moss Landing Marine Laboratories (MLML) station.\n",
     "\n",
     "![sensor_map.png](https://user-images.githubusercontent.com/950575/178321765-74ed0562-b942-4d97-af8b-85158bc6488c.png)\n",
@@ -460,7 +460,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.5"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

jupyterbook/content/code_gallery/data_access_notebooks/2017-06-12-NCEI_RA_archive_history.ipynb

@@ -50,11 +50,9 @@
     "\n",
     "Created: 2017-06-12\n",
     "\n",
-    "IOOS regional associations archive their non-federal observational data with NOAA's National Center for Environmental Information (NCEI). In this notebook we will use the [RESTful](https://github.com/Esri/geoportal-server/wiki/REST-API-Syntax) services of the [NCEI geoportal](https://www.ncei.noaa.gov/metadata/geoportal/#searchPanel) to collect metadata from the archive packages found in the NCEI archives. The metadata information are stored in [ISO 19115-2](https://wiki.earthdata.nasa.gov/display/NASAISO/ISO+19115-2) xml files which the NCEI geoportal uses for discovery of Archival Information Packages (AIPs). This example uses the ISO metadata records to display publication information as well as plot the time coverage of each AIP at NCEI which meets the search criteria.\n",
+    "IOOS regional associations archive their non-federal observational data with NOAA's National Center for Environmental Information (NCEI). In this notebook we will use the [RESTful](https://github.com/Esri/geoportal-server/wiki/REST-API-Syntax) services of the [NCEI geoportal](https://www.ncei.noaa.gov/metadata/geoportal) to collect metadata from the archive packages found in the NCEI archives. The metadata information are stored in [ISO 19115-2](https://wiki.earthdata.nasa.gov/display/NASAISO/ISO+19115-2) xml files which the NCEI geoportal uses for discovery of Archival Information Packages (AIPs). This example uses the ISO metadata records to display publication information as well as plot the time coverage of each AIP at NCEI which meets the search criteria.\n",
     "\n",
-    "First we update the namespaces dictionary from owslib to include the appropriate namespace reference for gmi and gml.\n",
-    "\n",
-    "For more information on ISO Namespaces see:  https://geo-ide.noaa.gov/wiki/index.php?title=ISO_Namespaces"
+    "First we update the namespaces dictionary from owslib to include the appropriate namespace reference for gmi and gml."
    ]
   },
   {
@@ -103,9 +101,9 @@
    "source": [
     "## Next we generate a geoportal query and georss feed\n",
     "\n",
-    "To find more information about how to compile a geoportal query, have a look at [REST API Syntax](https://github.com/Esri/geoportal-server/wiki/REST-API-Syntax) and the [NCEI Search Tips](https://www.nodc.noaa.gov/search/granule/catalog/searchtips/searchtips.page) for the [NCEI geoportal](https://data.nodc.noaa.gov/geoportal/catalog/search/search.page). The example provided is specific to the NCEI-IOOS data pipeline project and only searches for non-federal timeseries data collected by each Regional Association.\n",
+    "To find more information about how to compile a geoportal query, have a look at [REST API Syntax](https://github.com/Esri/geoportal-server/wiki/REST-API-Syntax) and the [NCEI Search Tips](https://www.ncei.noaa.gov/metadata/geoportal/#aboutPanel) for the [NCEI geoportal](https://www.ncei.noaa.gov/metadata/geoportal/#searchPanel). The example provided is specific to the NCEI-IOOS data pipeline project and only searches for non-federal timeseries data collected by each Regional Association.\n",
     "\n",
-    "The query developed here can be updated to search for any Archival Information Packages at NCEI, therefore the user should develop the appropriate query using the [NCEI Geoportal](https://data.nodc.noaa.gov/geoportal/catalog/search/search.page) and update this portion of the code to identify the REST API of interest."
+    "The query developed here can be updated to search for any Archival Information Packages at NCEI, therefore the user should develop the appropriate query using the [NCEI Geoportal](https://www.ncei.noaa.gov/metadata/geoportal/#searchPanel) and update this portion of the code to identify the REST API of interest."
    ]
   },
   {
@@ -599,7 +597,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.0"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

jupyterbook/content/code_gallery/data_access_notebooks/2017-08-01-xtractoR.ipynb

@@ -221,7 +221,7 @@
     "For more information and example on the other routines see the full example from the documentation at [https://rmendels.github.io/Usingxtractomatic_3.4.0.nb.html](https://rmendels.github.io/Usingxtractomatic_3.4.0.nb.html)\n",
     "\n",
     "\n",
-    "PS: note that R and all the `xtractomatic` dependencies are already included in the [IOOS conda environment](http://ioos.github.io/notebooks_demos/other_resources/)."
+    "PS: note that R and all the `xtractomatic` dependencies are already included in the [IOOS conda environment](https://ioos.github.io/ioos_code_lab/content/ioos_installation_conda.html)."
    ]
   }
  ],
@@ -237,7 +237,7 @@
    "mimetype": "text/x-r-source",
    "name": "R",
    "pygments_lexer": "r",
-   "version": "4.0.5"
+   "version": "4.3.1"
   }
  },
  "nbformat": 4,

jupyterbook/content/code_gallery/data_access_notebooks/2017-09-09-hurricane_irma.ipynb

@@ -54,7 +54,7 @@
     "\n",
     "See https://tidesandcurrents.noaa.gov/quicklook/view.html?name=IRMA for the latest information on Irma.\n",
     "\n",
-    "1. http://www.nhc.noaa.gov/gis/\n",
+    "1. https://www.nhc.noaa.gov/gis/\n",
     "1. https://opendap.co-ops.nos.noaa.gov/ioos-dif-sos/\n",
     "\n",
     "First we have to download the National Hurricane Center (NHC) GIS 5 day predictions data for Irma.\n",
@@ -994,7 +994,7 @@
     "We can observe the sea level retreating around 10-Sep 9:00 and then a significant surge after 19:00.\n",
     "The lower winds at beginning of the surge is probably the eye of the hurricane.\n",
     "\n",
-    "For our interactive map we will use [`bokeh`](https://bokeh.pydata.org/en/latest) HTML plots instead of the usual raster [`matplotlib`](https://matplotlib.org) ones to enhance the user experience when exploring the graphs."
+    "For our interactive map we will use [`bokeh`](https://docs.bokeh.org/en/latest/) HTML plots instead of the usual raster [`matplotlib`](https://matplotlib.org) ones to enhance the user experience when exploring the graphs."
    ]
   },
   {

jupyterbook/content/code_gallery/data_access_notebooks/2017-11-30-rerddap.ipynb

@@ -354,7 +354,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We can navigate to ERDDAP's [info page](http://gcoos4.tamu.edu:8080/erddap/info/fk_CREMP_yearly_revisited_DATA_v3_1996/index.html) to find the variables description. Let's check what is `organismQuantity`:\n",
+    "We can navigate to ERDDAP's [info page](https://gcoos4.tamu.edu/erddap/info/fk_CREMP_yearly_revisited_DATA_v3_1996/index.html) to find the variables description. Let's check what is `organismQuantity`:\n",
     "\n",
     "```\n",
     "The is value of the derived information product, such as the numerical value for biomass. This term does not include units. Mean number of observed fish per species for 5 Minutes\n",
@@ -846,7 +846,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "`rerddap`'s info request does not have enough metadata about the variables to explain the blank, and most abundant, `genus`. [Checking the sever](http://gcoos4.tamu.edu:8080/erddap/tabledap/fk_CREMP_yearly_revisited_DATA_v3_1996.html) did not help figure that out. We'll remove that for now to deal with only those that are identified."
+    "`rerddap`'s info request does not have enough metadata about the variables to explain the blank, and most abundant, `genus`. [Checking the sever](https://gcoos4.tamu.edu/erddap/tabledap/fk_CREMP_yearly_revisited_DATA_v3_1996.html) did not help figure that out. We'll remove that for now to deal with only those that are identified."
    ]
   },
   {

jupyterbook/content/code_gallery/data_access_notebooks/2018-02-20-obis.ipynb

@@ -48,7 +48,7 @@
     "\n",
     "Created: 2018-02-20\n",
     "\n",
-    "The [Ocean Biogeographic Information System (OBIS)](http://www.iobis.org) is an open-access data and information system for marine biodiversity for science, conservation and sustainable development.\n",
+    "The [Ocean Biogeographic Information System (OBIS)](https://www.obis.org/) is an open-access data and information system for marine biodiversity for science, conservation and sustainable development.\n",
     "\n",
     "In this example we will use R libraries [`obistools`](https://iobis.github.io/obistools) and [`robis`](https://iobis.github.io/robis) to search data regarding marine turtles occurrence in the South Atlantic Ocean.\n",
     "\n",
@@ -212,7 +212,7 @@
     "\n",
     "Now let us try to obtain the occurrence data for the South Atlantic. We will need a vector geometry for the ocean basin in the [well-known test (WKT)](https://en.wikipedia.org/wiki/Well-known_text) format to feed into the `robis` `occurrence` function.\n",
     "\n",
-    "In this example we converted a South Atlantic shapefile to WKT with geopandas, but one can also obtain geometries by simply drawing them on a map with [iobis maptool](http://iobis.org/maptool)."
+    "In this example we converted a South Atlantic shapefile to WKT with geopandas, but one can also obtain geometries by simply drawing them on a map with [iobis maptool](https://obis.org/maptool)."
    ]
   },
   {
@@ -1050,7 +1050,7 @@
    "source": [
     "One interesting feature of this map is *Dermochelys coriacea*'s migration between Brazilian and African shores.\n",
     "\n",
-    "More information on [*Dermochelys coriacea*](http://www.iucnredlist.org/details/6494/0) and the other Sea Turtles can be found in the species [IUCN red list](http://www.iucnredlist.org)."
+    "More information on [*Dermochelys coriacea*](https://www.iucnredlist.org/species/6494/43526147) and the other Sea Turtles can be found in the species [IUCN red list](https://www.iucnredlist.org/)."
    ]
   }
  ],
@@ -1070,7 +1070,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.1"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

jupyterbook/content/code_gallery/data_access_notebooks/2018-03-01-erddapy.ipynb

@@ -56,11 +56,11 @@
     "\n",
     "A typical ERDDAP RESTful URL looks like:\n",
     "\n",
-    "[https://data.ioos.us/gliders/erddap/tabledap/whoi_406-20160902T1700.mat?depth,latitude,longitude,salinity,temperature,time&time>=2016-07-10T00:00:00Z&time\\<=2017-02-10T00:00:00Z &latitude>=38.0&latitude\\<=41.0&longitude>=-72.0&longitude\\<=-69.0](https://data.ioos.us/gliders/erddap/tabledap/whoi_406-20160902T1700.mat?depth,latitude,longitude,salinity,temperature,time&time%3E=2016-07-10T00:00:00Z&time%3C=2017-02-10T00:00:00Z&latitude%3E=38.0&latitude%3C=41.0&longitude%3E=-72.0&longitude%3C=-69.0)\n",
+    "[https://gliders.ioos.us/gliders/erddap/tabledap/whoi_406-20160902T1700.mat?depth,latitude,longitude,salinity,temperature,time&time>=2016-07-10T00:00:00Z&time\\<=2017-02-10T00:00:00Z &latitude>=38.0&latitude\\<=41.0&longitude>=-72.0&longitude\\<=-69.0](https://gliders.ioos.us/erddap/tabledap/whoi_406-20160902T1700.mat?depth,latitude,longitude,salinity,temperature,time&time%3E=2016-07-10T00:00:00Z&time%3C=2017-02-10T00:00:00Z&latitude%3E=38.0&latitude%3C=41.0&longitude%3E=-72.0&longitude%3C=-69.0)\n",
     "\n",
     "Let's break it down to smaller parts:\n",
     "\n",
-    "- **server**: https://data.ioos.us/gliders/erddap/\n",
+    "- **server**: https://gliders.ioos.us/erddap/index.html\n",
     "- **protocol**: tabledap\n",
     "- **dataset_id**: whoi_406-20160902T1700\n",
     "- **response**: .mat\n",
@@ -872,7 +872,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "One can build the proper variables programmatically, feed them in erddapy, and then build a service like [this notebook](https://mybinder.org/v2/gh/ioos/BioData-Training-Workshop/master?filepath=notebooks/ERDDAP_timeseries_explorer-IOOS.ipynb). However, erddapy is also designed for interactive work. One can explore interactively the ERDDAP server from Python.\n",
+    "One can build the proper variables programmatically, feed them in erddapy, and then build a service like [this notebook](https://github.com/ioos/BioData-Training-Workshop/blob/master/notebooks/ERDDAP_timeseries_explorer-IOOS.ipynb). However, erddapy is also designed for interactive work. One can explore interactively the ERDDAP server from Python.\n",
     "\n",
     "PS: Note that in this example below we did not feed any variables other than the server URL"
    ]
@@ -2003,7 +2003,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

jupyterbook/content/code_gallery/data_access_notebooks/2019-03-08-grids-temperature.ipynb

@@ -55,7 +55,7 @@
     "In this post we will demostrante how to leverage Python's libraries to plot\n",
     "horizontal temperature slices from a variety of ocean models with minimum specific code.\n",
     "\n",
-    "Be sure to check the [first post on the series](http://ioos.github.io/notebooks_demos/notebooks/2018-12-04-grids/)."
+    "Be sure to check the [first post on the series](https://ioos.github.io/ioos_code_lab/content/code_gallery/data_analysis_and_visualization_notebooks/2018-12-04-grids.html)."
    ]
   },
   {
@@ -497,7 +497,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.7"
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,