MAAP CMR and .ops updates

docs/source/technical_tutorials/access/accessing_gedi_l3_data.ipynb

@@ -2,20 +2,20 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "2852ea6a",
+   "id": "d78d160b",
    "metadata": {},
    "source": [
     "## Accessing Global Ecosystem Dynamics Investigation (GEDI) Level 3 Granule Data\n",
     "\n",
     "In this example, we demonstrate how to access GEDI Level 3 granule data on the MAAP ADE.\n",
     "\n",
-    "Within your Jupyter Notebook, start by importing the `maap` package. Then invoke the `MAAP` constructor, setting the `maap_host` argument to `'api.ops.maap-project.org'`."
+    "Within your Jupyter Notebook, start by importing the `maap` package. Then invoke the `MAAP` constructor, setting the `maap_host` argument to `'api.maap-project.org'`."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "id": "65ed6944",
+   "execution_count": 8,
+   "id": "3ed66695",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -24,66 +24,71 @@
     "# import the maap package to handle queries\n",
     "from maap.maap import MAAP\n",
     "# invoke the MAAP constructor using the maap_host argument\n",
-    "maap = MAAP(maap_host='api.ops.maap-project.org')"
+    "maap = MAAP(maap_host='api.maap-project.org')"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "5957f899",
+   "id": "f96596fb",
    "metadata": {},
    "source": [
-    "Search for a granule using the `searchGranule` function (for more information on searching for granules, see [Searching for Granules in MAAP](https://docs.maap-project.org/en/latest/search/granules.html)). Note that we can use `searchGranule`'s `cmr_host` argument to specify `cmr.maap-project.org` as the CMR instance. "
+    "Search for a granule using the `searchGranule` function (for more information on searching for granules, see [Searching for Granules in MAAP](https://docs.maap-project.org/en/latest/search/granules.html)). Note that we can use `searchGranule`'s `cmr_host` argument to specify `cmr.earthdata.nasa.gov` as the CMR instance. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "bb76be55",
+   "execution_count": 11,
+   "id": "1818a6af",
    "metadata": {},
    "outputs": [],
    "source": [
     "# search for granule data using CMR host name and collection concept ID arguments\n",
     "results = maap.searchGranule(\n",
-    "    cmr_host='cmr.maap-project.org',\n",
-    "    collection_concept_id='C1201702030-NASA_MAAP'\n",
+    "    cmr_host='cmr.earthdata.nasa.gov',\n",
+    "    collection_concept_id='C2153683336-ORNL_CLOUD'\n",
     ")"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "2d08b82b",
+   "id": "9dbee756",
    "metadata": {},
    "source": [
     "Let's view the list of `GranuleUR`s within our `results`:"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "02acc4b5",
+   "execution_count": 12,
+   "id": "83b55546",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
        "['GEDI_L3_LandSurface_Metrics_V2.GEDI03_elev_lowestmode_stddev_2019108_2020287_002_02.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_counts_2019108_2020287_002_02.tif',\n",
        " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_counts_2019108_2021104_002_02.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_mean_2019108_2020287_002_02.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_stddev_2019108_2020287_002_02.tif',\n",
        " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_elev_lowestmode_stddev_2019108_2021104_002_02.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_stddev_2019108_2021104_002_02.tif',\n",
        " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_elev_lowestmode_mean_2019108_2020287_002_02.tif',\n",
        " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_elev_lowestmode_mean_2019108_2021104_002_02.tif',\n",
-       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_stddev_2019108_2021104_002_02.tif',\n",
-       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_counts_2019108_2020287_002_02.tif',\n",
        " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_mean_2019108_2021104_002_02.tif',\n",
-       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_mean_2019108_2020287_002_02.tif',\n",
-       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_stddev_2019108_2020287_002_02.tif',\n",
-       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_counts_2019108_2021216_002_02.tif',\n",
-       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_mean_2019108_2021216_002_02.tif',\n",
        " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_elev_lowestmode_stddev_2019108_2021216_002_02.tif',\n",
        " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_elev_lowestmode_mean_2019108_2021216_002_02.tif',\n",
-       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_stddev_2019108_2021216_002_02.tif']"
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_stddev_2019108_2021216_002_02.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_mean_2019108_2021216_002_02.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_counts_2019108_2021216_002_02.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_elev_lowestmode_mean_2019108_2022019_002_03.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_counts_2019108_2022019_002_03.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_mean_2019108_2022019_002_03.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_elev_lowestmode_stddev_2019108_2022019_002_03.tif',\n",
+       " 'GEDI_L3_LandSurface_Metrics_V2.GEDI03_rh100_stddev_2019108_2022019_002_03.tif']"
       ]
      },
-     "execution_count": 3,
+     "execution_count": 12,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -95,16 +100,16 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e777c700",
+   "id": "ca5a52ac",
    "metadata": {},
    "source": [
     "For this example, we are interested in downloading `GEDI03_elev_lowestmode_stddev_2019108_2021104_002_02.tif`."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
-   "id": "18ab7e6a",
+   "execution_count": 13,
+   "id": "8765d0e4",
    "metadata": {},
    "outputs": [
     {
@@ -113,49 +118,49 @@
        "'GEDI_L3_LandSurface_Metrics_V2.GEDI03_elev_lowestmode_stddev_2019108_2021104_002_02.tif'"
       ]
      },
-     "execution_count": 4,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "# select item\n",
-    "results[2]['Granule']['GranuleUR']"
+    "results[5]['Granule']['GranuleUR']"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "332503ca",
+   "id": "bc450bee",
    "metadata": {},
    "source": [
     "Now utilize the `getData` function, which downloads granule data if it doesn't already exist locally. We can use `getData` to download the third result from our granule search into the file system and assign its local path to a variable (in this case `download`)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
-   "id": "39e575aa",
+   "execution_count": 16,
+   "id": "ced4e2c4",
    "metadata": {},
    "outputs": [],
    "source": [
     "# download granule item\n",
     "local_dir = '/projects/local_data'  # download directory (absolute path or relative to current directory)\n",
     "os.makedirs(local_dir, exist_ok=True) # create directories, as necessary\n",
-    "download = results[2].getData(local_dir)  # default download directory is current directory, if no directory is given"
+    "download = results[5].getData(local_dir)  # default download directory is current directory, if no directory is given"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "65d960ba",
+   "id": "c00b4678",
    "metadata": {},
    "source": [
     "We can then use the `print` function to see the file name and directory."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
-   "id": "ccdfc922",
+   "execution_count": 17,
+   "id": "7b02a2ec",
    "metadata": {},
    "outputs": [
     {

docs/source/technical_tutorials/access/accessing_gedi_l4a_data.ipynb

@@ -2,20 +2,20 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "2e8d6183",
+   "id": "ce359129",
    "metadata": {},
    "source": [
     "## Accessing Global Ecosystem Dynamics Investigation (GEDI) Level 4A Granule Data\n",
     "\n",
     "In this example, we demonstrate how to access GEDI Level 4A granule data on the MAAP ADE.\n",
     "\n",
-    "Within your Jupyter Notebook, start by importing the `maap` package. Then invoke the `MAAP` constructor, setting the `maap_host` argument to `'api.ops.maap-project.org'`."
+    "Within your Jupyter Notebook, start by importing the `maap` package. Then invoke the `MAAP` constructor, setting the `maap_host` argument to `'api.maap-project.org'`."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 1,
-   "id": "2f250d6c",
+   "execution_count": 7,
+   "id": "7bb460a0",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -24,28 +24,28 @@
     "# import the maap package to handle queries\n",
     "from maap.maap import MAAP\n",
     "# invoke the MAAP constructor using the maap_host argument\n",
-    "maap = MAAP(maap_host='api.ops.maap-project.org')"
+    "maap = MAAP(maap_host='api.maap-project.org')"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "f6342077",
+   "id": "da26a534",
    "metadata": {},
    "source": [
-    "Search for a granule using the `searchGranule` function (for more information on searching for granules, see [Searching for Granules in MAAP](https://docs.maap-project.org/en/latest/search/granules.html)). Note that we can use `searchGranule`'s `cmr_host` argument to specify `cmr.maap-project.org` as the CMR instance. Then utilize the `getData` function, which downloads granule data if it doesn't already exist locally. We can use `getData` to download the first result from our granule search into the file system and assign its local path to a variable (in this case `download`)."
+    "Search for a granule using the `searchGranule` function (for more information on searching for granules, see [Searching for Granules in MAAP](https://docs.maap-project.org/en/latest/search/granules.html)). Note that we can use `searchGranule`'s `cmr_host` argument to specify `cmr.earthdata.nasa.gov` as the CMR instance. Then utilize the `getData` function, which downloads granule data if it doesn't already exist locally. We can use `getData` to download the first result from our granule search into the file system and assign its local path to a variable (in this case `download`)."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
-   "id": "d1fbb45b",
+   "execution_count": 8,
+   "id": "6e1cecce",
    "metadata": {},
    "outputs": [],
    "source": [
     "# search for granule data using CMR host name, collection concept ID, and Granule UR arguments\n",
     "results = maap.searchGranule(\n",
-    "    cmr_host='cmr.maap-project.org',\n",
-    "    collection_concept_id='C1202028193-NASA_MAAP',\n",
+    "    cmr_host='cmr.earthdata.nasa.gov',\n",
+    "    collection_concept_id='C2237824918-ORNL_CLOUD',\n",
     "    granule_ur='GEDI_L4A_AGB_Density_V2_1.GEDI04_A_2019107224731_O01958_01_T02638_02_002_02_V002.h5')\n",
     "# download first result\n",
     "local_dir = '/projects/local_data'  # Download directory (absolute path or relative to current directory)\n",
@@ -55,16 +55,16 @@
   },
   {
    "cell_type": "markdown",
-   "id": "73d354d9",
+   "id": "0dc32190",
    "metadata": {},
    "source": [
     "We can then use the `print` function to see the file name and directory."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
-   "id": "d71d4bcc",
+   "execution_count": 9,
+   "id": "356b97d2",
    "metadata": {},
    "outputs": [
     {

docs/source/technical_tutorials/search/granules.ipynb

@@ -1,7 +1,6 @@
 {
  "cells": [
   {
-   "attachments": {},
    "cell_type": "markdown",
    "metadata": {},
    "source": [
@@ -14,7 +13,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "We begin by importing the `maap` and `pprint` packages. Then invoke the `MAAP` constructor, setting the `maap_host` argument to `'api.ops.maap-project.org'`."
+    "We begin by importing the `maap` and `pprint` packages. Then invoke the `MAAP` constructor, setting the `maap_host` argument to `'api.maap-project.org'`."
    ]
   },
   {
@@ -30,7 +29,7 @@
     "from pprint import pprint\n",
     "\n",
     "# invoke the MAAP constructor using the maap_host argument\n",
-    "maap = MAAP(maap_host='api.ops.maap-project.org')"
+    "maap = MAAP(maap_host='api.maap-project.org')"
    ]
   },
   {