diff --git a/docs/howto/edl.ipynb b/docs/howto/edl.ipynb index d26503dc..5949ddb5 100644 --- a/docs/howto/edl.ipynb +++ b/docs/howto/edl.ipynb @@ -17,17 +17,7 @@ "execution_count": 1, "id": "ce723d6f-8b5f-43e1-9531-19ee08a056fe", "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "You're now authenticated with NASA Earthdata Login\n", - "Using token with expiration date: 09/25/2023\n", - "Using environment variables for EDL\n" - ] - } - ], + "outputs": [], "source": [ "import earthaccess\n", "\n", @@ -40,32 +30,17 @@ "metadata": {}, "source": [ "### Data in AWS\n", - "If the data we want to access is on AWS, we can use earthaccess to generate temporary S3 credentials for any of the DAACs" + "If the data we want to access is on AWS, we can use earthaccess to generate temporary S3 credentials for any of the DAACs. This line is commented out for security reasons. " ] }, { "cell_type": "code", - "execution_count": 3, - "id": "3108ff21-1ea2-449b-b2f5-b442dd3b61f5", + "execution_count": 2, + "id": "f1f45172-c9c3-4f25-ad7e-acf94fba8b1d", "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{'accessKeyId': 'ASIA2D3OGJNTE2UAIDHR',\n", - " 'secretAccessKey': '9+6D3m76HTuNi3qvbgUMBFlJECsCgPyJ4ur2CfZL',\n", - " 'sessionToken': 'FwoGZXIvYXdzEPL//////////wEaDIVnMBd6zBaEKmG58CLpAXrPN52vpRHvs+0y960kNwGOdFHPD81WVsdeUciP/vQvsU/xX4Cg+iLH/OXDlH/PBWCmSgfk4vgXD9k6r2JRmnpkwyF4v4K4+ciIuUHNG43ZegSFtkzZoLHShLtEnNu/OIT0TlcrOLJIY+TnjEDcKkXiLSsLYB7qDKZIeg654oPCkjeXyDuoWOumJa7utBEwHmakOGdGJTthOfbfJ6RJ9sbPbmsEXg0bHF5PY9h3/Eoq0rjyRmlb1WYuopw5YK8dL5N9IwSKlKiu19Cj0nd04XVNuiB02+fLDubsnKK1b3j0jR53qAU3FxobKLHgj6YGMi0kDN7xWP6yqI7Ry69Lf5EEcDRVp4UVz6llGYoDpsKr9s3cXaBljkhEjH7N5dQ=',\n", - " 'expiration': '2023-07-28 17:43:29+00:00'}" - ] - }, - "execution_count": 3, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "s3_credentials = auth.get_s3_credentials(\"NSIDC\")\n", - "s3_credentials" + "#s3_credentials = auth.get_s3_credentials(\"NSIDC\")" ] }, { @@ -88,7 +63,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 3, "id": "a7bb1a93-6f85-40cd-93b4-ce821a03a8b5", "metadata": {}, "outputs": [], @@ -102,7 +77,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 4, "id": "c0f4e286-8ce9-4cde-b3a2-631b361a0d51", "metadata": {}, "outputs": [ @@ -112,7 +87,7 @@ "'�HDF\\r\\n\\x1a\\n\\x00\\x00\\x00\\x00\\x00\\x08\\x08\\x00\\x04\\x00\\x10\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00���������HUn\\x00\\x00\\x00\\x00��������\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00`\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00OHDR\\x02'" ] }, - "execution_count": 15, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -133,7 +108,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 5, "id": "1e5f5f7a-0643-42cb-b70c-4ac982824ff9", "metadata": {}, "outputs": [], @@ -143,7 +118,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 6, "id": "fbc7bc5f-b984-4324-b095-3648a437fba2", "metadata": {}, "outputs": [ @@ -153,7 +128,7 @@ "b'\\x89HDF\\r\\n\\x1a\\n\\x00\\x00\\x00\\x00\\x00\\x08\\x08\\x00\\x04\\x00\\x10\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\xff\\xff\\xff\\xff\\xff\\xff\\xff\\xff\\xd7HUn\\x00\\x00\\x00\\x00\\xff\\xff\\xff\\xff\\xff\\xff\\xff\\xff\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00`\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00\\x00OHDR'" ] }, - "execution_count": 11, + "execution_count": 6, "metadata": {}, "output_type": "execute_result" } @@ -166,19 +141,19 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 7, "id": "07433a9f-f276-4d2b-9ed3-f556df2884af", "metadata": {}, "outputs": [ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "f68d214c1c4b4d0fb0b44d878a003a33", + "model_id": "c76e3afc58a84118a04144f2f08ff6bc", "version_major": 2, "version_minor": 0 }, "text/plain": [ - "QUEUEING TASKS | : 0it [00:00, ?it/s]" + "QUEUEING TASKS | : 0%| | 0/1 [00:00, ?it/s]" ] }, "metadata": {}, @@ -187,7 +162,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "185025ed0c284481982459d85c8dbb1f", + "model_id": "98f4219952eb4e9bb8f60ad67f438454", "version_major": 2, "version_minor": 0 }, @@ -201,7 +176,7 @@ { "data": { "application/vnd.jupyter.widget-view+json": { - "model_id": "ec660bd64a284df28a03705f56eea208", + "model_id": "9451a7fda27e4569968054028576999d", "version_major": 2, "version_minor": 0 }, @@ -216,8 +191,8 @@ "name": "stdout", "output_type": "stream", "text": [ - "CPU times: user 983 ms, sys: 101 ms, total: 1.08 s\n", - "Wall time: 18.3 s\n" + "CPU times: user 1.4 s, sys: 179 ms, total: 1.58 s\n", + "Wall time: 10.5 s\n" ] }, { @@ -586,25 +561,25 @@ " stroke: currentColor;\n", " fill: currentColor;\n", "}\n", - "
<xarray.Dataset>\n", + "" ], "text/plain": [ - "<xarray.Dataset> Size: 3kB\n", "Dimensions: (bands: 285)\n", "Dimensions without coordinates: bands\n", "Data variables:\n", - " wavelengths (bands) float32 ...\n", - " fwhm (bands) float32 ...\n", - " good_wavelengths (bands) float32 ..." + " wavelengths (bands) float32 1kB ...\n", + " fwhm (bands) float32 1kB ...\n", + " good_wavelengths (bands) float32 1kB ...