Merge branch 'development' into traffic

.all-contributorsrc

@@ -382,7 +382,8 @@
       "avatar_url": "https://avatars.githubusercontent.com/u/54070345?v=4",
       "profile": "https://github.com/jpswinski",
       "contributions": [
-        "code"
+        "code",
+        "review"
       ]
     },
     {
@@ -422,6 +423,31 @@
       "contributions": [
         "review"
       ]
+    },
+    {
+      "login": "rwegener2",
+      "name": "Rachel Wegener",
+      "avatar_url": "https://avatars.githubusercontent.com/u/35503632?v=4",
+      "profile": "https://rwegener2.github.io/",
+      "contributions": [
+        "bug",
+        "code",
+        "doc",
+        "ideas",
+        "maintenance",
+        "review",
+        "test",
+        "tutorial"
+      ]
+    },
+    {
+      "login": "whyjz",
+      "name": "Whyjay Zheng",
+      "avatar_url": "https://avatars.githubusercontent.com/u/19339926?v=4",
+      "profile": "https://whyjz.github.io/",
+      "contributions": [
+        "tutorial"
+      ]
     }
   ],
   "contributorsPerLine": 7,
@@ -430,5 +456,6 @@
   "repoType": "github",
   "repoHost": "https://github.com",
   "skipCi": true,
-  "commitConvention": "angular"
+  "commitConvention": "angular",
+  "commitType": "docs"
 }

doc/source/contributing/quest-available-datasets.rst

@@ -0,0 +1,29 @@
+.. _quest_supported_label:
+
+QUEST Supported Datasets
+========================
+
+On this page, we outline the datasets that are supported by the QUEST module. Click on the links for each dataset to view information about the API and sensor/data platform used.
+
+
+List of Datasets
+----------------
+
+`Argo <https://argo.ucsd.edu/data/>`_
+^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
+The Argo mission involves a series of floats that are designed to capture vertical ocean profiles of temperature, salinity, and pressure down to ~2000 m. Some floats are in support of BGC-Argo, which also includes data relevant for biogeochemical applications: oxygen, nitrate, chlorophyll, backscatter, and solar irradiance.
+
+A paper outlining the Argo extension to QUEST is currently in preparation, with a citable preprint available in the near future.
+
+:ref:`Argo Workflow Example<quest_workbook_label>`
+
+
+Adding a Dataset to QUEST
+-------------------------
+
+Want to add a new dataset to QUEST? No problem! QUEST includes a template script (``dataset.py``) that may be used to create your own querying module for a dataset of interest.
+
+Once you have developed a script with the template, you may request for the module to be added to QUEST via GitHub.
+Please see the How to Contribute page :ref:`dev_guide_label` for instructions on how to contribute to icepyx.
+
+Detailed guidelines on how to construct your dataset module are currently a work in progress.

doc/source/example_notebooks/IS2_data_access.ipynb

@@ -79,7 +79,7 @@
     "\n",
     "There are three required inputs, depending on how you want to search for data. Two are required in all cases:\n",
     "- `short_name` = the data product of interest, known as its \"short name\".\n",
-    "See https://nsidc.org/data/icesat-2/data-sets for a list of the available data products.\n",
+    "See https://nsidc.org/data/icesat-2/products for a list of the available data products.\n",
     "- `spatial extent` = a region of interest to search within. This can be entered as a bounding box, polygon vertex coordinate pairs, or a polygon geospatial file (currently shp, kml, and gpkg are supported).\n",
     "    - bounding box: Given in decimal degrees for the lower left longitude, lower left latitude, upper right longitude, and upper right latitude\n",
     "    - polygon vertices: Given as longitude, latitude coordinate pairs of decimal degrees with the last entry a repeat of the first.\n",

doc/source/example_notebooks/IS2_data_access2-subsetting.ipynb

@@ -51,7 +51,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "user_expressions": []
+   },
    "source": [
     "Create a query object and log in to Earthdata\n",
     "\n",
@@ -83,7 +85,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "user_expressions": []
+   },
    "source": [
     "## Discover Subsetting Options\n",
     "\n",
@@ -108,7 +112,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "user_expressions": []
+   },
    "source": [
     "By default, spatial and temporal subsetting based on your initial inputs is applied to your order unless you specify `subset=False` to `order_granules()` or `download_granules()` (which calls `order_granules` under the hood if you have not already placed your order) functions.\n",
     "Additional subsetting options must be specified as keyword arguments to the order/download functions.\n",
@@ -118,7 +124,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "user_expressions": []
+   },
    "source": [
     "### _Why do I have to provide spatial bounds to icepyx even if I don't use them to subset my data order?_\n",
     "\n",
@@ -132,7 +140,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "user_expressions": []
+   },
    "source": [
     "## About Data Variables in a query object\n",
     "\n",
@@ -145,7 +155,9 @@
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "user_expressions": []
+   },
    "source": [
     "### Determine what variables are available for your data product\n",
     "There are multiple ways to get a complete list of available variables.\n",
@@ -159,23 +171,29 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "region_a.order_vars.avail()"
    ]
   },
   {
    "cell_type": "markdown",
-   "metadata": {},
+   "metadata": {
+    "user_expressions": []
+   },
    "source": [
     "By passing the boolean `options=True` to the `avail` method, you can obtain lists of unique possible variable inputs (var_list inputs) and path subdirectory inputs (keyword_list and beam_list inputs) for your data product. These can be helpful for building your wanted variable list."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "outputs": [],
    "source": [
     "region_a.order_vars.avail(options=True)"
@@ -353,9 +371,9 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "icepyx-dev",
    "language": "python",
-   "name": "python3"
+   "name": "icepyx-dev"
   },
   "language_info": {
    "codemirror_mode": {
@@ -367,7 +385,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,