From fd73812099277495f463fdc732d159e745d08c69 Mon Sep 17 00:00:00 2001
From: amsnyder <asnyder@usgs.gov>
Date: Mon, 8 Apr 2024 13:06:33 -0500
Subject: [PATCH] fix crs var detection
---
.../collection.json | 2 +-
.../collection.json | 2 +-
.../collection.json | 2 +-
.../collection.json | 2 +-
.../collection.json | 2 +-
.../collection.json | 2 +-
...d_annual_create_collection_from_zarr.ipynb | 152 ++++++++++++----
...ion_data_create_collection_from_zarr.ipynb | 160 +++++++++++++----
...e_slices_create_collection_from_zarr.ipynb | 160 +++++++++++++----
...d_annual_create_collection_from_zarr.ipynb | 160 +++++++++++++----
...ion_data_create_collection_from_zarr.ipynb | 168 +++++++++++++-----
...e_slices_create_collection_from_zarr.ipynb | 156 ++++++++++++----
12 files changed, 735 insertions(+), 233 deletions(-)
diff --git a/catalog/TTU_2019_rcp45_gridded_annual/collection.json b/catalog/TTU_2019_rcp45_gridded_annual/collection.json
index 76672c22..6ad26e12 100644
--- a/catalog/TTU_2019_rcp45_gridded_annual/collection.json
+++ b/catalog/TTU_2019_rcp45_gridded_annual/collection.json
@@ -320,7 +320,7 @@
},
"crs": {
"dimensions": [],
- "type": "data",
+ "type": "auxiliary",
"description": null,
"unit": null
},
diff --git a/catalog/TTU_2019_rcp45_station_data/collection.json b/catalog/TTU_2019_rcp45_station_data/collection.json
index 66e6647f..e011ce6d 100644
--- a/catalog/TTU_2019_rcp45_station_data/collection.json
+++ b/catalog/TTU_2019_rcp45_station_data/collection.json
@@ -68,7 +68,7 @@
},
"crs": {
"dimensions": [],
- "type": "data",
+ "type": "auxiliary",
"description": null,
"unit": null
},
diff --git a/catalog/TTU_2019_rcp45_time_slices/collection.json b/catalog/TTU_2019_rcp45_time_slices/collection.json
index f61855bd..92971f57 100644
--- a/catalog/TTU_2019_rcp45_time_slices/collection.json
+++ b/catalog/TTU_2019_rcp45_time_slices/collection.json
@@ -80,7 +80,7 @@
},
"crs": {
"dimensions": [],
- "type": "data",
+ "type": "auxiliary",
"description": null,
"unit": null
},
diff --git a/catalog/TTU_2019_rcp85_gridded_annual/collection.json b/catalog/TTU_2019_rcp85_gridded_annual/collection.json
index 1ce3aed4..689b2443 100644
--- a/catalog/TTU_2019_rcp85_gridded_annual/collection.json
+++ b/catalog/TTU_2019_rcp85_gridded_annual/collection.json
@@ -320,7 +320,7 @@
},
"crs": {
"dimensions": [],
- "type": "data",
+ "type": "auxiliary",
"description": null,
"unit": null
},
diff --git a/catalog/TTU_2019_rcp85_station_data/collection.json b/catalog/TTU_2019_rcp85_station_data/collection.json
index eb6782d6..32beafd9 100644
--- a/catalog/TTU_2019_rcp85_station_data/collection.json
+++ b/catalog/TTU_2019_rcp85_station_data/collection.json
@@ -68,7 +68,7 @@
},
"crs": {
"dimensions": [],
- "type": "data",
+ "type": "auxiliary",
"description": null,
"unit": null
},
diff --git a/catalog/TTU_2019_rcp85_time_slices/collection.json b/catalog/TTU_2019_rcp85_time_slices/collection.json
index 95cc8bb6..b1dcad86 100644
--- a/catalog/TTU_2019_rcp85_time_slices/collection.json
+++ b/catalog/TTU_2019_rcp85_time_slices/collection.json
@@ -80,7 +80,7 @@
},
"crs": {
"dimensions": [],
- "type": "data",
+ "type": "auxiliary",
"description": null,
"unit": null
},
diff --git a/workflows/archive/TTU_2019_rcp45_gridded_annual_create_collection_from_zarr.ipynb b/workflows/archive/TTU_2019_rcp45_gridded_annual_create_collection_from_zarr.ipynb
index b0615328..1b891a19 100644
--- a/workflows/archive/TTU_2019_rcp45_gridded_annual_create_collection_from_zarr.ipynb
+++ b/workflows/archive/TTU_2019_rcp45_gridded_annual_create_collection_from_zarr.ipynb
@@ -19,7 +19,9 @@
"cell_type": "code",
"execution_count": null,
"id": "201e0945-de55-45ff-b095-c2af009a4e62",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"import pystac\n",
@@ -132,7 +134,9 @@
"cell_type": "code",
"execution_count": null,
"id": "708f2cf5-79ab-49af-8067-de31d0d13ee6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# open and view zarr dataset\n",
@@ -154,7 +158,9 @@
"cell_type": "code",
"execution_count": null,
"id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# description of STAC collection\n",
@@ -188,7 +194,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ab91268f-7200-4cb1-979a-c7d75531d2c0",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# dims_auto_extract = ['X', 'Y', 'T']\n",
@@ -209,15 +217,29 @@
"## Get crs info"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2d34fbc5-f0ce-4860-8cc5-9f3dcafb927d",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "crs_var = 'crs'"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
"id": "b03d52f3-1367-4255-a561-52ee4fc9e92d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# use pyproj to automatically extract crs info\n",
- "crs = pyproj.CRS.from_cf(ds.crs.attrs)\n",
+ "crs = pyproj.CRS.from_cf(ds[crs_var].attrs)\n",
"\n",
"# alternatively, create the appropriate cartopy projection\n",
"# crs = ccrs.LambertConformal(central_longitude=crs_info.longitude_of_central_meridian, \n",
@@ -246,7 +268,9 @@
"cell_type": "code",
"execution_count": null,
"id": "d46805e0-8e94-4ebe-aa01-d9a2d7051459",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out lat/lon bbox for data\n",
@@ -265,7 +289,9 @@
"cell_type": "code",
"execution_count": null,
"id": "cd7db627-4776-4780-ae42-413104c6a43a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"XX, YY = np.meshgrid(ds[dim_names_dict['X']].data, ds[dim_names_dict['Y']].data)"
@@ -275,7 +301,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4b3516fe-df9b-4855-be40-422f82a28ab0",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"transformer = Transformer.from_crs(crs, \"EPSG:4326\", always_xy=True)\n",
@@ -286,7 +314,9 @@
"cell_type": "code",
"execution_count": null,
"id": "70c7d699-83d1-4ba7-9d46-7831d946f4c4",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(f'lower left coordinates (WGS84): {min(lon)}, {min(lat)}')\n",
@@ -297,7 +327,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8b4c75c9-0f03-4466-8df6-d2c78bdecbb5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a spatial extent object \n",
@@ -316,7 +348,9 @@
"cell_type": "code",
"execution_count": null,
"id": "41a84995-867c-4152-8c57-85e3758bbb77",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out first and last timestamps\n",
@@ -336,7 +370,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1e37c4-5348-46ad-abc9-e005b5d6c02b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"collection_extent = pystac.Extent(spatial=spatial_extent, temporal=temporal_extent)"
@@ -356,7 +392,9 @@
"cell_type": "code",
"execution_count": null,
"id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# define folder location where your STAC catalog json file is\n",
@@ -369,7 +407,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7e96811b-95ae-406a-9728-55fc429d4e1f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -398,7 +438,9 @@
"cell_type": "code",
"execution_count": null,
"id": "094832af-d22b-4359-b0f6-cf687acce5cc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"asset_id = \"zarr-s3-osn\"\n",
@@ -440,7 +482,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fc00946d-2880-491d-9b3b-3aeeb4414d6c",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# instantiate extention on collection\n",
@@ -459,7 +503,9 @@
"cell_type": "code",
"execution_count": null,
"id": "120a4914-3302-44a5-a282-0308ac84f040",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# list out dataset dimensions\n",
@@ -473,7 +519,9 @@
"cell_type": "code",
"execution_count": null,
"id": "00a18a29-fb9a-4b56-8009-493122997b16",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# get x, y bounds for extent of those dimensions (required)\n",
@@ -494,7 +542,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ea452f62-5644-49b6-8a4e-7dc4f649fd1a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# print out crs information in dataset\n",
@@ -505,7 +555,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1d05ff-8e43-44a7-8343-178b112c4ad6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # create the appropriate cartopy projection\n",
@@ -546,7 +598,9 @@
"cell_type": "code",
"execution_count": null,
"id": "82f1e9bd-52ee-46f5-9e95-c2359d95fcf3",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"#time_step = pd.Timedelta(get_step(ds, dim_names_dict['T'], time_dim=True)).isoformat()\n",
@@ -558,7 +612,9 @@
"cell_type": "code",
"execution_count": null,
"id": "64be65b2-de20-447a-a9c2-bd8eca3e440e",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps: get all step values and locations\n",
@@ -569,7 +625,9 @@
"cell_type": "code",
"execution_count": null,
"id": "bc8dff39-2a2e-44a0-9b30-987107c2d1e2",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps, cont:\n",
@@ -591,7 +649,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a8ba7695-ca45-4db2-bd46-c465f4e37eff",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"x_step = stac_helpers.get_step(ds, dim_names_dict['X'])\n",
@@ -602,7 +662,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps: get all step values and locations\n",
@@ -615,7 +677,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8d0b5a2d-dc58-4ad6-b890-859ce6bb08de",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -637,7 +701,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7405583b-ecb9-44b0-8815-048e42e55a42",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"y_step = stac_helpers.get_step(ds, dim_names_dict['Y'])\n",
@@ -648,7 +714,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps: get all step values and locations\n",
@@ -661,7 +729,9 @@
"cell_type": "code",
"execution_count": null,
"id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -687,7 +757,9 @@
"cell_type": "code",
"execution_count": null,
"id": "acd45d3c-7845-47e6-9b7d-e35627a7ca9a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(dims)"
@@ -697,7 +769,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5a443497-67a9-4dce-a8e9-b08d31a88223",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a dictionary of datacube dimensions you would like to assign to this dataset\n",
@@ -727,7 +801,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e9272931-fc0b-4f2a-9546-283033e9cde8",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# drop metpy_crs coordinate we have added\n",
@@ -750,7 +826,7 @@
"vars_dict={}\n",
"for v in vars:\n",
" unit = stac_helpers.get_unit(ds, v)\n",
- " var_type = stac_helpers.get_var_type(ds, v)\n",
+ " var_type = stac_helpers.get_var_type(ds, v, crs_var)\n",
" long_name = stac_helpers.get_long_name(ds, v)\n",
" vars_dict[v] = pystac.extensions.datacube.Variable({'dimensions':list(ds[v].dims), 'type': var_type, 'description': long_name, 'unit': unit})"
]
@@ -767,7 +843,9 @@
"cell_type": "code",
"execution_count": null,
"id": "10141fd4-91d6-491d-878b-02653720891d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# add dimesions and variables to collection extension\n",
@@ -800,7 +878,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4b75791b-6b2d-40be-b7c6-330a60888fb5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
diff --git a/workflows/archive/TTU_2019_rcp45_station_data_create_collection_from_zarr.ipynb b/workflows/archive/TTU_2019_rcp45_station_data_create_collection_from_zarr.ipynb
index f6c4fd1d..958ab8e3 100644
--- a/workflows/archive/TTU_2019_rcp45_station_data_create_collection_from_zarr.ipynb
+++ b/workflows/archive/TTU_2019_rcp45_station_data_create_collection_from_zarr.ipynb
@@ -19,7 +19,9 @@
"cell_type": "code",
"execution_count": null,
"id": "201e0945-de55-45ff-b095-c2af009a4e62",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"import pystac\n",
@@ -55,7 +57,9 @@
"cell_type": "code",
"execution_count": null,
"id": "15ee060d-3127-4024-a1ad-6aa0648667e1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection - should match name of zarr dataset\n",
@@ -128,7 +132,9 @@
"cell_type": "code",
"execution_count": null,
"id": "708f2cf5-79ab-49af-8067-de31d0d13ee6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# open and view zarr dataset\n",
@@ -150,7 +156,9 @@
"cell_type": "code",
"execution_count": null,
"id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# description of STAC collection\n",
@@ -175,7 +183,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ab91268f-7200-4cb1-979a-c7d75531d2c0",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# dims_auto_extract = ['X', 'Y', 'T']\n",
@@ -195,15 +205,29 @@
"If there is no crs info that can be automatically extracted from the dataset with pyproj, you will need to manually identify the crs and create a crs object. This reference list of cartopy projections may be a helpful resource: https://scitools.org.uk/cartopy/docs/latest/reference/projections.html"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "d92e5107-4902-4cf7-8e38-28db2c840662",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "crs_var = 'crs'"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
"id": "b03d52f3-1367-4255-a561-52ee4fc9e92d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# use pyproj to automatically extract crs info\n",
- "crs = pyproj.CRS.from_cf(ds.crs.attrs)\n",
+ "crs = pyproj.CRS.from_cf(ds[crs_var].attrs)\n",
"\n",
"# alternatively, create the appropriate cartopy projection\n",
"# crs = ccrs.LambertConformal(central_longitude=crs_info.longitude_of_central_meridian, \n",
@@ -223,7 +247,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4cee13ba-487d-483e-a013-b65685137502",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"ds.crs"
@@ -233,7 +259,9 @@
"cell_type": "code",
"execution_count": null,
"id": "f7bc73db-7717-450e-9679-525f7be0c910",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"crs.to_proj4()"
@@ -260,7 +288,9 @@
"cell_type": "code",
"execution_count": null,
"id": "d46805e0-8e94-4ebe-aa01-d9a2d7051459",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out lat/lon bbox for data\n",
@@ -279,7 +309,9 @@
"cell_type": "code",
"execution_count": null,
"id": "f16fdb9e-7ed8-40fb-a4f1-9ecabdebc0a1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"XX, YY = np.meshgrid(ds[dim_names_dict['X']].data, ds[dim_names_dict['Y']].data)"
@@ -289,7 +321,9 @@
"cell_type": "code",
"execution_count": null,
"id": "074fc23c-f4d9-4427-80d3-fbf691e6d411",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"transformer = Transformer.from_crs(crs, \"EPSG:4326\", always_xy=True)\n",
@@ -300,7 +334,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5345c975-9fe3-48e1-a663-0275cdf275dc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(f'lower left coordinates (WGS84): {min(lon)}, {min(lat)}')\n",
@@ -311,7 +347,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e0a5a222-743d-403a-9411-2406374803cf",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a spatial extent object \n",
@@ -330,7 +368,9 @@
"cell_type": "code",
"execution_count": null,
"id": "41a84995-867c-4152-8c57-85e3758bbb77",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out first and last timestamps\n",
@@ -351,7 +391,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1e37c4-5348-46ad-abc9-e005b5d6c02b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"collection_extent = pystac.Extent(spatial=spatial_extent, temporal=temporal_extent)"
@@ -369,7 +411,9 @@
"cell_type": "code",
"execution_count": null,
"id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# define folder location where your STAC catalog json file is\n",
@@ -382,7 +426,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7e96811b-95ae-406a-9728-55fc429d4e1f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -411,7 +457,9 @@
"cell_type": "code",
"execution_count": null,
"id": "094832af-d22b-4359-b0f6-cf687acce5cc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"asset_id = \"zarr-s3-osn\"\n",
@@ -453,7 +501,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fc00946d-2880-491d-9b3b-3aeeb4414d6c",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# instantiate extention on collection\n",
@@ -481,7 +531,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ea452f62-5644-49b6-8a4e-7dc4f649fd1a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# print out crs information in dataset\n",
@@ -492,7 +544,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1d05ff-8e43-44a7-8343-178b112c4ad6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # the datacube extension can accept reference_system information as a numerical EPSG code, \n",
@@ -530,7 +584,9 @@
"cell_type": "code",
"execution_count": null,
"id": "82f1e9bd-52ee-46f5-9e95-c2359d95fcf3",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"#time_step = pd.Timedelta(get_step(ds, dim_names_dict['T'], time_dim=True)).isoformat()\n",
@@ -542,7 +598,9 @@
"cell_type": "code",
"execution_count": null,
"id": "64be65b2-de20-447a-a9c2-bd8eca3e440e",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for time steps:\n",
@@ -555,7 +613,9 @@
"cell_type": "code",
"execution_count": null,
"id": "bc8dff39-2a2e-44a0-9b30-987107c2d1e2",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps, cont:\n",
@@ -579,7 +639,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a8ba7695-ca45-4db2-bd46-c465f4e37eff",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"x_step = stac_helpers.get_step(ds, dim_names_dict['X'])\n",
@@ -593,7 +655,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for spatial steps:\n",
@@ -608,7 +672,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8d0b5a2d-dc58-4ad6-b890-859ce6bb08de",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -632,7 +698,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7405583b-ecb9-44b0-8815-048e42e55a42",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"y_step = stac_helpers.get_step(ds, dim_names_dict['Y'])\n",
@@ -646,7 +714,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for spatial steps:\n",
@@ -661,7 +731,9 @@
"cell_type": "code",
"execution_count": null,
"id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -688,7 +760,9 @@
"cell_type": "code",
"execution_count": null,
"id": "acd45d3c-7845-47e6-9b7d-e35627a7ca9a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"dims = list(ds.dims)\n",
@@ -699,7 +773,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5a443497-67a9-4dce-a8e9-b08d31a88223",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a dictionary of datacube dimensions you would like to assign to this dataset\n",
@@ -720,7 +796,9 @@
"cell_type": "code",
"execution_count": null,
"id": "15db7bae-e387-4377-852b-5f864c67ee69",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# make sure you added all the right dims\n",
@@ -739,7 +817,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e9272931-fc0b-4f2a-9546-283033e9cde8",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# drop metpy_crs coordinate we have added\n",
@@ -762,7 +842,7 @@
"vars_dict={}\n",
"for v in vars:\n",
" unit = stac_helpers.get_unit(ds, v)\n",
- " var_type = stac_helpers.get_var_type(ds, v)\n",
+ " var_type = stac_helpers.get_var_type(ds, v, crs_var)\n",
" long_name = stac_helpers.get_long_name(ds, v)\n",
" vars_dict[v] = pystac.extensions.datacube.Variable({'dimensions':list(ds[v].dims), 'type': var_type, 'description': long_name, 'unit': unit})"
]
@@ -779,7 +859,9 @@
"cell_type": "code",
"execution_count": null,
"id": "10141fd4-91d6-491d-878b-02653720891d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# add dimesions and variables to collection extension\n",
@@ -812,7 +894,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4b75791b-6b2d-40be-b7c6-330a60888fb5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
diff --git a/workflows/archive/TTU_2019_rcp45_time_slices_create_collection_from_zarr.ipynb b/workflows/archive/TTU_2019_rcp45_time_slices_create_collection_from_zarr.ipynb
index f76a3fd5..2574cca9 100644
--- a/workflows/archive/TTU_2019_rcp45_time_slices_create_collection_from_zarr.ipynb
+++ b/workflows/archive/TTU_2019_rcp45_time_slices_create_collection_from_zarr.ipynb
@@ -19,7 +19,9 @@
"cell_type": "code",
"execution_count": null,
"id": "201e0945-de55-45ff-b095-c2af009a4e62",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"import pystac\n",
@@ -55,7 +57,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4572c6fa-c1da-4809-95e4-deea2119d5e6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection - should match name of zarr dataset\n",
@@ -130,7 +134,9 @@
"cell_type": "code",
"execution_count": null,
"id": "708f2cf5-79ab-49af-8067-de31d0d13ee6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# open and view zarr dataset\n",
@@ -154,7 +160,9 @@
"cell_type": "code",
"execution_count": null,
"id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# description of STAC collection\n",
@@ -166,7 +174,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a77517ef-a9cc-4b8c-9132-229580e192b1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# license for dataset\n",
@@ -186,7 +196,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ab91268f-7200-4cb1-979a-c7d75531d2c0",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# dims_auto_extract = ['X', 'Y', 'T']\n",
@@ -205,15 +217,29 @@
"## Get crs info"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "0f27113b-6488-4dad-961b-0ecb695bcd08",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "crs_var = 'crs'"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
"id": "b03d52f3-1367-4255-a561-52ee4fc9e92d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# use pyproj to automatically extract crs info\n",
- "crs = pyproj.CRS.from_cf(ds.crs.attrs)\n",
+ "crs = pyproj.CRS.from_cf(ds[crs_var].attrs)\n",
"\n",
"# alternatively, create the appropriate cartopy projection\n",
"# crs = ccrs.LambertConformal(central_longitude=crs_info.longitude_of_central_meridian, \n",
@@ -242,7 +268,9 @@
"cell_type": "code",
"execution_count": null,
"id": "d46805e0-8e94-4ebe-aa01-d9a2d7051459",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out lat/lon bbox for data\n",
@@ -261,7 +289,9 @@
"cell_type": "code",
"execution_count": null,
"id": "61dd5559-3284-4fc1-af8c-0db7258b7a18",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"XX, YY = np.meshgrid(ds[dim_names_dict['X']].data, ds[dim_names_dict['Y']].data)"
@@ -271,7 +301,9 @@
"cell_type": "code",
"execution_count": null,
"id": "05af4c5e-1e6c-4589-b6f2-2e2fc1123b29",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"transformer = Transformer.from_crs(crs, \"EPSG:4326\", always_xy=True)\n",
@@ -282,7 +314,9 @@
"cell_type": "code",
"execution_count": null,
"id": "3377c99a-434a-4e72-a997-644b495e5d95",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(f'lower left coordinates (WGS84): {min(lon)}, {min(lat)}')\n",
@@ -293,7 +327,9 @@
"cell_type": "code",
"execution_count": null,
"id": "48d6f450-5833-44e4-a11d-6906aa3b2283",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a spatial extent object \n",
@@ -312,7 +348,9 @@
"cell_type": "code",
"execution_count": null,
"id": "41a84995-867c-4152-8c57-85e3758bbb77",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out first and last timestamps\n",
@@ -332,7 +370,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1e37c4-5348-46ad-abc9-e005b5d6c02b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"collection_extent = pystac.Extent(spatial=spatial_extent, temporal=temporal_extent)"
@@ -352,7 +392,9 @@
"cell_type": "code",
"execution_count": null,
"id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# define folder location where your STAC catalog json file is\n",
@@ -365,7 +407,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7e96811b-95ae-406a-9728-55fc429d4e1f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -394,7 +438,9 @@
"cell_type": "code",
"execution_count": null,
"id": "094832af-d22b-4359-b0f6-cf687acce5cc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"asset_id = \"zarr-s3-osn\"\n",
@@ -436,7 +482,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fc00946d-2880-491d-9b3b-3aeeb4414d6c",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# instantiate extention on collection\n",
@@ -455,7 +503,9 @@
"cell_type": "code",
"execution_count": null,
"id": "120a4914-3302-44a5-a282-0308ac84f040",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# list out dataset dimensions\n",
@@ -469,7 +519,9 @@
"cell_type": "code",
"execution_count": null,
"id": "00a18a29-fb9a-4b56-8009-493122997b16",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# get x, y bounds for extent of those dimensions (required)\n",
@@ -490,7 +542,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ea452f62-5644-49b6-8a4e-7dc4f649fd1a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# print out crs information in dataset\n",
@@ -501,7 +555,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1d05ff-8e43-44a7-8343-178b112c4ad6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # create the appropriate cartopy projection\n",
@@ -542,7 +598,9 @@
"cell_type": "code",
"execution_count": null,
"id": "82f1e9bd-52ee-46f5-9e95-c2359d95fcf3",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"#time_step = pd.Timedelta(get_step(ds, dim_names_dict['T'], time_dim=True)).isoformat()\n",
@@ -554,7 +612,9 @@
"cell_type": "code",
"execution_count": null,
"id": "64be65b2-de20-447a-a9c2-bd8eca3e440e",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps: get all step values and locations\n",
@@ -565,7 +625,9 @@
"cell_type": "code",
"execution_count": null,
"id": "bc8dff39-2a2e-44a0-9b30-987107c2d1e2",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps, cont:\n",
@@ -587,7 +649,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a8ba7695-ca45-4db2-bd46-c465f4e37eff",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"x_step = stac_helpers.get_step(ds, dim_names_dict['X'])\n",
@@ -598,7 +662,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps: get all step values and locations\n",
@@ -611,7 +677,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8d0b5a2d-dc58-4ad6-b890-859ce6bb08de",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -633,7 +701,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7405583b-ecb9-44b0-8815-048e42e55a42",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"y_step = stac_helpers.get_step(ds, dim_names_dict['Y'])\n",
@@ -644,7 +714,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps: get all step values and locations\n",
@@ -657,7 +729,9 @@
"cell_type": "code",
"execution_count": null,
"id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -683,7 +757,9 @@
"cell_type": "code",
"execution_count": null,
"id": "acd45d3c-7845-47e6-9b7d-e35627a7ca9a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(dims)"
@@ -693,7 +769,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5a443497-67a9-4dce-a8e9-b08d31a88223",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a dictionary of datacube dimensions you would like to assign to this dataset\n",
@@ -723,7 +801,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e9272931-fc0b-4f2a-9546-283033e9cde8",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# drop metpy_crs coordinate we have added\n",
@@ -746,7 +826,7 @@
"vars_dict={}\n",
"for v in vars:\n",
" unit = stac_helpers.get_unit(ds, v)\n",
- " var_type = stac_helpers.get_var_type(ds, v)\n",
+ " var_type = stac_helpers.get_var_type(ds, v, crs_var)\n",
" long_name = stac_helpers.get_long_name(ds, v)\n",
" vars_dict[v] = pystac.extensions.datacube.Variable({'dimensions':list(ds[v].dims), 'type': var_type, 'description': long_name, 'unit': unit})"
]
@@ -763,7 +843,9 @@
"cell_type": "code",
"execution_count": null,
"id": "10141fd4-91d6-491d-878b-02653720891d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# add dimesions and variables to collection extension\n",
@@ -796,7 +878,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4b75791b-6b2d-40be-b7c6-330a60888fb5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
diff --git a/workflows/archive/TTU_2019_rcp85_gridded_annual_create_collection_from_zarr.ipynb b/workflows/archive/TTU_2019_rcp85_gridded_annual_create_collection_from_zarr.ipynb
index e67eff8e..0f5332dc 100644
--- a/workflows/archive/TTU_2019_rcp85_gridded_annual_create_collection_from_zarr.ipynb
+++ b/workflows/archive/TTU_2019_rcp85_gridded_annual_create_collection_from_zarr.ipynb
@@ -19,7 +19,9 @@
"cell_type": "code",
"execution_count": null,
"id": "201e0945-de55-45ff-b095-c2af009a4e62",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"import pystac\n",
@@ -55,7 +57,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4425c28a-50af-4cd6-ba99-7be2068833bd",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection - should match name of zarr dataset\n",
@@ -130,7 +134,9 @@
"cell_type": "code",
"execution_count": null,
"id": "708f2cf5-79ab-49af-8067-de31d0d13ee6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# open and view zarr dataset\n",
@@ -152,7 +158,9 @@
"cell_type": "code",
"execution_count": null,
"id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# description of STAC collection\n",
@@ -164,7 +172,9 @@
"cell_type": "code",
"execution_count": null,
"id": "aa7ef52b-d89a-4d76-81a5-149bc95c32f5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# license for dataset\n",
@@ -184,7 +194,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ab91268f-7200-4cb1-979a-c7d75531d2c0",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# dims_auto_extract = ['X', 'Y', 'T']\n",
@@ -203,15 +215,29 @@
"## Get crs info"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "262f0882-9182-4470-a15a-4849b83ce3a9",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "crs_var = 'crs'"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
"id": "b03d52f3-1367-4255-a561-52ee4fc9e92d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# use pyproj to automatically extract crs info\n",
- "crs = pyproj.CRS.from_cf(ds.crs.attrs)\n",
+ "crs = pyproj.CRS.from_cf(ds[crs_var].attrs)\n",
"\n",
"# alternatively, create the appropriate cartopy projection\n",
"# crs = ccrs.LambertConformal(central_longitude=crs_info.longitude_of_central_meridian, \n",
@@ -240,7 +266,9 @@
"cell_type": "code",
"execution_count": null,
"id": "d46805e0-8e94-4ebe-aa01-d9a2d7051459",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out lat/lon bbox for data\n",
@@ -259,7 +287,9 @@
"cell_type": "code",
"execution_count": null,
"id": "f91e6693-e4be-4cb5-86d3-7386db1c0188",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"XX, YY = np.meshgrid(ds[dim_names_dict['X']].data, ds[dim_names_dict['Y']].data)"
@@ -269,7 +299,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8544a97d-62ea-4b26-9e8a-5d1663d3e632",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"transformer = Transformer.from_crs(crs, \"EPSG:4326\", always_xy=True)\n",
@@ -280,7 +312,9 @@
"cell_type": "code",
"execution_count": null,
"id": "2bafc4d4-0401-4a2b-a025-2aa86bc5a15a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(f'lower left coordinates (WGS84): {min(lon)}, {min(lat)}')\n",
@@ -291,7 +325,9 @@
"cell_type": "code",
"execution_count": null,
"id": "37fb3eb8-bc62-4179-9b70-6a17575e8f84",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a spatial extent object \n",
@@ -310,7 +346,9 @@
"cell_type": "code",
"execution_count": null,
"id": "41a84995-867c-4152-8c57-85e3758bbb77",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out first and last timestamps\n",
@@ -330,7 +368,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1e37c4-5348-46ad-abc9-e005b5d6c02b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"collection_extent = pystac.Extent(spatial=spatial_extent, temporal=temporal_extent)"
@@ -350,7 +390,9 @@
"cell_type": "code",
"execution_count": null,
"id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# define folder location where your STAC catalog json file is\n",
@@ -363,7 +405,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7e96811b-95ae-406a-9728-55fc429d4e1f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -392,7 +436,9 @@
"cell_type": "code",
"execution_count": null,
"id": "094832af-d22b-4359-b0f6-cf687acce5cc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"asset_id = \"zarr-s3-osn\"\n",
@@ -434,7 +480,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fc00946d-2880-491d-9b3b-3aeeb4414d6c",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# instantiate extention on collection\n",
@@ -453,7 +501,9 @@
"cell_type": "code",
"execution_count": null,
"id": "120a4914-3302-44a5-a282-0308ac84f040",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# list out dataset dimensions\n",
@@ -467,7 +517,9 @@
"cell_type": "code",
"execution_count": null,
"id": "00a18a29-fb9a-4b56-8009-493122997b16",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# get x, y bounds for extent of those dimensions (required)\n",
@@ -488,7 +540,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ea452f62-5644-49b6-8a4e-7dc4f649fd1a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# print out crs information in dataset\n",
@@ -499,7 +553,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1d05ff-8e43-44a7-8343-178b112c4ad6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # create the appropriate cartopy projection\n",
@@ -540,7 +596,9 @@
"cell_type": "code",
"execution_count": null,
"id": "82f1e9bd-52ee-46f5-9e95-c2359d95fcf3",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"#time_step = pd.Timedelta(get_step(ds, dim_names_dict['T'], time_dim=True)).isoformat()\n",
@@ -552,7 +610,9 @@
"cell_type": "code",
"execution_count": null,
"id": "64be65b2-de20-447a-a9c2-bd8eca3e440e",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps: get all step values and locations\n",
@@ -563,7 +623,9 @@
"cell_type": "code",
"execution_count": null,
"id": "bc8dff39-2a2e-44a0-9b30-987107c2d1e2",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps, cont:\n",
@@ -585,7 +647,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a8ba7695-ca45-4db2-bd46-c465f4e37eff",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"x_step = stac_helpers.get_step(ds, dim_names_dict['X'])\n",
@@ -596,7 +660,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps: get all step values and locations\n",
@@ -609,7 +675,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8d0b5a2d-dc58-4ad6-b890-859ce6bb08de",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -631,7 +699,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7405583b-ecb9-44b0-8815-048e42e55a42",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"y_step = stac_helpers.get_step(ds, dim_names_dict['Y'])\n",
@@ -642,7 +712,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps: get all step values and locations\n",
@@ -655,7 +727,9 @@
"cell_type": "code",
"execution_count": null,
"id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -681,7 +755,9 @@
"cell_type": "code",
"execution_count": null,
"id": "acd45d3c-7845-47e6-9b7d-e35627a7ca9a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(dims)"
@@ -691,7 +767,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5a443497-67a9-4dce-a8e9-b08d31a88223",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a dictionary of datacube dimensions you would like to assign to this dataset\n",
@@ -721,7 +799,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e9272931-fc0b-4f2a-9546-283033e9cde8",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# drop metpy_crs coordinate we have added\n",
@@ -744,7 +824,7 @@
"vars_dict={}\n",
"for v in vars:\n",
" unit = stac_helpers.get_unit(ds, v)\n",
- " var_type = stac_helpers.get_var_type(ds, v)\n",
+ " var_type = stac_helpers.get_var_type(ds, v, crs_var)\n",
" long_name = stac_helpers.get_long_name(ds, v)\n",
" vars_dict[v] = pystac.extensions.datacube.Variable({'dimensions':list(ds[v].dims), 'type': var_type, 'description': long_name, 'unit': unit})"
]
@@ -761,7 +841,9 @@
"cell_type": "code",
"execution_count": null,
"id": "10141fd4-91d6-491d-878b-02653720891d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# add dimesions and variables to collection extension\n",
@@ -794,7 +876,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4b75791b-6b2d-40be-b7c6-330a60888fb5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
diff --git a/workflows/archive/TTU_2019_rcp85_station_data_create_collection_from_zarr.ipynb b/workflows/archive/TTU_2019_rcp85_station_data_create_collection_from_zarr.ipynb
index ac1d9963..22aa185e 100644
--- a/workflows/archive/TTU_2019_rcp85_station_data_create_collection_from_zarr.ipynb
+++ b/workflows/archive/TTU_2019_rcp85_station_data_create_collection_from_zarr.ipynb
@@ -19,7 +19,9 @@
"cell_type": "code",
"execution_count": null,
"id": "201e0945-de55-45ff-b095-c2af009a4e62",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"import pystac\n",
@@ -55,7 +57,9 @@
"cell_type": "code",
"execution_count": null,
"id": "15ee060d-3127-4024-a1ad-6aa0648667e1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection - should match name of zarr dataset\n",
@@ -128,7 +132,9 @@
"cell_type": "code",
"execution_count": null,
"id": "708f2cf5-79ab-49af-8067-de31d0d13ee6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# open and view zarr dataset\n",
@@ -150,7 +156,9 @@
"cell_type": "code",
"execution_count": null,
"id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# description of STAC collection\n",
@@ -175,7 +183,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ab91268f-7200-4cb1-979a-c7d75531d2c0",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# dims_auto_extract = ['X', 'Y', 'T']\n",
@@ -195,15 +205,29 @@
"If there is no crs info that can be automatically extracted from the dataset with pyproj, you will need to manually identify the crs and create a crs object. This reference list of cartopy projections may be a helpful resource: https://scitools.org.uk/cartopy/docs/latest/reference/projections.html"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "aa8f1511-909c-422f-9be7-1d5c9a7e8054",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "crs_var = 'crs'"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
"id": "b03d52f3-1367-4255-a561-52ee4fc9e92d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# use pyproj to automatically extract crs info\n",
- "crs = pyproj.CRS.from_cf(ds.crs.attrs)\n",
+ "crs = pyproj.CRS.from_cf(ds[crs_var].attrs)\n",
"\n",
"# alternatively, create the appropriate cartopy projection\n",
"# crs = ccrs.LambertConformal(central_longitude=crs_info.longitude_of_central_meridian, \n",
@@ -223,7 +247,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4cee13ba-487d-483e-a013-b65685137502",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"ds.crs"
@@ -233,7 +259,9 @@
"cell_type": "code",
"execution_count": null,
"id": "f7bc73db-7717-450e-9679-525f7be0c910",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"crs.to_proj4()"
@@ -260,7 +288,9 @@
"cell_type": "code",
"execution_count": null,
"id": "d46805e0-8e94-4ebe-aa01-d9a2d7051459",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out lat/lon bbox for data\n",
@@ -279,7 +309,9 @@
"cell_type": "code",
"execution_count": null,
"id": "f16fdb9e-7ed8-40fb-a4f1-9ecabdebc0a1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"XX, YY = np.meshgrid(ds[dim_names_dict['X']].data, ds[dim_names_dict['Y']].data)"
@@ -289,7 +321,9 @@
"cell_type": "code",
"execution_count": null,
"id": "074fc23c-f4d9-4427-80d3-fbf691e6d411",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"transformer = Transformer.from_crs(crs, \"EPSG:4326\", always_xy=True)\n",
@@ -300,7 +334,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5345c975-9fe3-48e1-a663-0275cdf275dc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(f'lower left coordinates (WGS84): {min(lon)}, {min(lat)}')\n",
@@ -311,7 +347,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e0a5a222-743d-403a-9411-2406374803cf",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a spatial extent object \n",
@@ -330,7 +368,9 @@
"cell_type": "code",
"execution_count": null,
"id": "41a84995-867c-4152-8c57-85e3758bbb77",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out first and last timestamps\n",
@@ -351,7 +391,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1e37c4-5348-46ad-abc9-e005b5d6c02b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"collection_extent = pystac.Extent(spatial=spatial_extent, temporal=temporal_extent)"
@@ -369,7 +411,9 @@
"cell_type": "code",
"execution_count": null,
"id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# define folder location where your STAC catalog json file is\n",
@@ -382,7 +426,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7e96811b-95ae-406a-9728-55fc429d4e1f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -411,7 +457,9 @@
"cell_type": "code",
"execution_count": null,
"id": "094832af-d22b-4359-b0f6-cf687acce5cc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"asset_id = \"zarr-s3-osn\"\n",
@@ -453,7 +501,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fc00946d-2880-491d-9b3b-3aeeb4414d6c",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# instantiate extention on collection\n",
@@ -481,7 +531,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ea452f62-5644-49b6-8a4e-7dc4f649fd1a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# print out crs information in dataset\n",
@@ -492,7 +544,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1d05ff-8e43-44a7-8343-178b112c4ad6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # the datacube extension can accept reference_system information as a numerical EPSG code, \n",
@@ -530,7 +584,9 @@
"cell_type": "code",
"execution_count": null,
"id": "82f1e9bd-52ee-46f5-9e95-c2359d95fcf3",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"#time_step = pd.Timedelta(get_step(ds, dim_names_dict['T'], time_dim=True)).isoformat()\n",
@@ -542,7 +598,9 @@
"cell_type": "code",
"execution_count": null,
"id": "64be65b2-de20-447a-a9c2-bd8eca3e440e",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for time steps:\n",
@@ -555,7 +613,9 @@
"cell_type": "code",
"execution_count": null,
"id": "bc8dff39-2a2e-44a0-9b30-987107c2d1e2",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps, cont:\n",
@@ -579,7 +639,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a8ba7695-ca45-4db2-bd46-c465f4e37eff",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"x_step = stac_helpers.get_step(ds, dim_names_dict['X'])\n",
@@ -593,7 +655,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for spatial steps:\n",
@@ -608,7 +672,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8d0b5a2d-dc58-4ad6-b890-859ce6bb08de",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -632,7 +698,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7405583b-ecb9-44b0-8815-048e42e55a42",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"y_step = stac_helpers.get_step(ds, dim_names_dict['Y'])\n",
@@ -646,7 +714,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # optional debugging for spatial steps:\n",
@@ -661,7 +731,9 @@
"cell_type": "code",
"execution_count": null,
"id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -688,7 +760,9 @@
"cell_type": "code",
"execution_count": null,
"id": "acd45d3c-7845-47e6-9b7d-e35627a7ca9a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"dims = list(ds.dims)\n",
@@ -699,7 +773,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5a443497-67a9-4dce-a8e9-b08d31a88223",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a dictionary of datacube dimensions you would like to assign to this dataset\n",
@@ -720,7 +796,9 @@
"cell_type": "code",
"execution_count": null,
"id": "910cf68e-5d1d-43f9-baad-b8b5709dcbd7",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"dims_dict.keys()"
@@ -730,7 +808,9 @@
"cell_type": "code",
"execution_count": null,
"id": "74cac855-7570-42d6-a8a6-5d233bc06ad7",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"list(dims_dict.keys()) == dims"
@@ -740,7 +820,9 @@
"cell_type": "code",
"execution_count": null,
"id": "3d7d8551-13e2-4ec7-9f9c-b578d9780d66",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# make sure you added all the right dims\n",
@@ -759,7 +841,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e9272931-fc0b-4f2a-9546-283033e9cde8",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# drop metpy_crs coordinate we have added\n",
@@ -782,7 +866,7 @@
"vars_dict={}\n",
"for v in vars:\n",
" unit = stac_helpers.get_unit(ds, v)\n",
- " var_type = stac_helpers.get_var_type(ds, v)\n",
+ " var_type = stac_helpers.get_var_type(ds, v, crs_var)\n",
" long_name = stac_helpers.get_long_name(ds, v)\n",
" vars_dict[v] = pystac.extensions.datacube.Variable({'dimensions':list(ds[v].dims), 'type': var_type, 'description': long_name, 'unit': unit})"
]
@@ -799,7 +883,9 @@
"cell_type": "code",
"execution_count": null,
"id": "10141fd4-91d6-491d-878b-02653720891d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# add dimesions and variables to collection extension\n",
@@ -832,7 +918,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4b75791b-6b2d-40be-b7c6-330a60888fb5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
diff --git a/workflows/archive/TTU_2019_rcp85_time_slices_create_collection_from_zarr.ipynb b/workflows/archive/TTU_2019_rcp85_time_slices_create_collection_from_zarr.ipynb
index 61d2f9d9..e0730e35 100644
--- a/workflows/archive/TTU_2019_rcp85_time_slices_create_collection_from_zarr.ipynb
+++ b/workflows/archive/TTU_2019_rcp85_time_slices_create_collection_from_zarr.ipynb
@@ -19,7 +19,9 @@
"cell_type": "code",
"execution_count": null,
"id": "201e0945-de55-45ff-b095-c2af009a4e62",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"import pystac\n",
@@ -55,7 +57,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a1e7b195-3e56-408a-b16b-52d79888728a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# name for STAC collection - should match name of zarr dataset\n",
@@ -130,7 +134,9 @@
"cell_type": "code",
"execution_count": null,
"id": "708f2cf5-79ab-49af-8067-de31d0d13ee6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# open and view zarr dataset\n",
@@ -152,7 +158,9 @@
"cell_type": "code",
"execution_count": null,
"id": "482d204d-b5b6-40e5-ac42-55b459be1097",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# description of STAC collection\n",
@@ -186,7 +194,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ab91268f-7200-4cb1-979a-c7d75531d2c0",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# dims_auto_extract = ['X', 'Y', 'T']\n",
@@ -205,15 +215,29 @@
"## Get crs info"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "c2b5a003-a382-4887-8ca1-e51c54e9050b",
+ "metadata": {
+ "tags": []
+ },
+ "outputs": [],
+ "source": [
+ "crs_var = 'crs'"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
"id": "b03d52f3-1367-4255-a561-52ee4fc9e92d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# use pyproj to automatically extract crs info\n",
- "crs = pyproj.CRS.from_cf(ds.crs.attrs)\n",
+ "crs = pyproj.CRS.from_cf(ds[crs_var].attrs)\n",
"\n",
"# alternatively, create the appropriate cartopy projection\n",
"# crs = ccrs.LambertConformal(central_longitude=crs_info.longitude_of_central_meridian, \n",
@@ -242,7 +266,9 @@
"cell_type": "code",
"execution_count": null,
"id": "d46805e0-8e94-4ebe-aa01-d9a2d7051459",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out lat/lon bbox for data\n",
@@ -261,7 +287,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e9ed6ff9-8ac0-4e8b-8641-9314f2d5e4e1",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"XX, YY = np.meshgrid(ds[dim_names_dict['X']].data, ds[dim_names_dict['Y']].data)"
@@ -271,7 +299,9 @@
"cell_type": "code",
"execution_count": null,
"id": "797e274f-a9e6-4aa5-a9d9-070dada92a4f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"transformer = Transformer.from_crs(crs, \"EPSG:4326\", always_xy=True)\n",
@@ -282,7 +312,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1806104c-50b4-4266-a8dc-a0c67f554634",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(f'lower left coordinates (WGS84): {min(lon)}, {min(lat)}')\n",
@@ -293,7 +325,9 @@
"cell_type": "code",
"execution_count": null,
"id": "18551939-abab-4cac-bc94-c6feb523fd4f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a spatial extent object \n",
@@ -312,7 +346,9 @@
"cell_type": "code",
"execution_count": null,
"id": "41a84995-867c-4152-8c57-85e3758bbb77",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# pull out first and last timestamps\n",
@@ -332,7 +368,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1e37c4-5348-46ad-abc9-e005b5d6c02b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"collection_extent = pystac.Extent(spatial=spatial_extent, temporal=temporal_extent)"
@@ -352,7 +390,9 @@
"cell_type": "code",
"execution_count": null,
"id": "adf6c59d-58cd-48b1-a5fd-3bb205a3ef56",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# define folder location where your STAC catalog json file is\n",
@@ -365,7 +405,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7e96811b-95ae-406a-9728-55fc429d4e1f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
@@ -394,7 +436,9 @@
"cell_type": "code",
"execution_count": null,
"id": "094832af-d22b-4359-b0f6-cf687acce5cc",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"asset_id = \"zarr-s3-osn\"\n",
@@ -436,7 +480,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fc00946d-2880-491d-9b3b-3aeeb4414d6c",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# instantiate extention on collection\n",
@@ -455,7 +501,9 @@
"cell_type": "code",
"execution_count": null,
"id": "120a4914-3302-44a5-a282-0308ac84f040",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# list out dataset dimensions\n",
@@ -469,7 +517,9 @@
"cell_type": "code",
"execution_count": null,
"id": "00a18a29-fb9a-4b56-8009-493122997b16",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# get x, y bounds for extent of those dimensions (required)\n",
@@ -490,7 +540,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ea452f62-5644-49b6-8a4e-7dc4f649fd1a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# print out crs information in dataset\n",
@@ -501,7 +553,9 @@
"cell_type": "code",
"execution_count": null,
"id": "1b1d05ff-8e43-44a7-8343-178b112c4ad6",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # create the appropriate cartopy projection\n",
@@ -542,7 +596,9 @@
"cell_type": "code",
"execution_count": null,
"id": "82f1e9bd-52ee-46f5-9e95-c2359d95fcf3",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"#time_step = pd.Timedelta(get_step(ds, dim_names_dict['T'], time_dim=True)).isoformat()\n",
@@ -554,7 +610,9 @@
"cell_type": "code",
"execution_count": null,
"id": "64be65b2-de20-447a-a9c2-bd8eca3e440e",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps: get all step values and locations\n",
@@ -565,7 +623,9 @@
"cell_type": "code",
"execution_count": null,
"id": "bc8dff39-2a2e-44a0-9b30-987107c2d1e2",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for time steps, cont:\n",
@@ -587,7 +647,9 @@
"cell_type": "code",
"execution_count": null,
"id": "a8ba7695-ca45-4db2-bd46-c465f4e37eff",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"x_step = stac_helpers.get_step(ds, dim_names_dict['X'])\n",
@@ -598,7 +660,9 @@
"cell_type": "code",
"execution_count": null,
"id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps: get all step values and locations\n",
@@ -611,7 +675,9 @@
"cell_type": "code",
"execution_count": null,
"id": "8d0b5a2d-dc58-4ad6-b890-859ce6bb08de",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -633,7 +699,9 @@
"cell_type": "code",
"execution_count": null,
"id": "7405583b-ecb9-44b0-8815-048e42e55a42",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"y_step = stac_helpers.get_step(ds, dim_names_dict['Y'])\n",
@@ -644,7 +712,9 @@
"cell_type": "code",
"execution_count": null,
"id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps: get all step values and locations\n",
@@ -657,7 +727,9 @@
"cell_type": "code",
"execution_count": null,
"id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# # debugging for spatial steps, cont:\n",
@@ -683,7 +755,9 @@
"cell_type": "code",
"execution_count": null,
"id": "acd45d3c-7845-47e6-9b7d-e35627a7ca9a",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"print(dims)"
@@ -693,7 +767,9 @@
"cell_type": "code",
"execution_count": null,
"id": "5a443497-67a9-4dce-a8e9-b08d31a88223",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# create a dictionary of datacube dimensions you would like to assign to this dataset\n",
@@ -723,7 +799,9 @@
"cell_type": "code",
"execution_count": null,
"id": "e9272931-fc0b-4f2a-9546-283033e9cde8",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# drop metpy_crs coordinate we have added\n",
@@ -746,7 +824,7 @@
"vars_dict={}\n",
"for v in vars:\n",
" unit = stac_helpers.get_unit(ds, v)\n",
- " var_type = stac_helpers.get_var_type(ds, v)\n",
+ " var_type = stac_helpers.get_var_type(ds, v, crs_var)\n",
" long_name = stac_helpers.get_long_name(ds, v)\n",
" vars_dict[v] = pystac.extensions.datacube.Variable({'dimensions':list(ds[v].dims), 'type': var_type, 'description': long_name, 'unit': unit})"
]
@@ -763,7 +841,9 @@
"cell_type": "code",
"execution_count": null,
"id": "10141fd4-91d6-491d-878b-02653720891d",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"# add dimesions and variables to collection extension\n",
@@ -796,7 +876,9 @@
"cell_type": "code",
"execution_count": null,
"id": "4b75791b-6b2d-40be-b7c6-330a60888fb5",
- "metadata": {},
+ "metadata": {
+ "tags": []
+ },
"outputs": [],
"source": [
"if catalog.get_child(collection_id):\n",
--
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