From 77430af92a865f69ff2da727fe28fedb60529c11 Mon Sep 17 00:00:00 2001
From: amsnyder <asnyder@usgs.gov>
Date: Tue, 16 Jan 2024 11:01:05 -0600
Subject: [PATCH] add spatial step exploration to examples
---
..._collection_from_zarr_conus404-daily.ipynb | 82 ++++++++++++++++++-
...create_item_from_zarr_conus404-daily.ipynb | 82 ++++++++++++++++++-
2 files changed, 160 insertions(+), 4 deletions(-)
diff --git a/workflows/examples/create_collection_from_zarr_conus404-daily.ipynb b/workflows/examples/create_collection_from_zarr_conus404-daily.ipynb
index b79125ad..120e4947 100644
--- a/workflows/examples/create_collection_from_zarr_conus404-daily.ipynb
+++ b/workflows/examples/create_collection_from_zarr_conus404-daily.ipynb
@@ -553,6 +553,14 @@
"#### user review needed - looks at the steps pulled out and make sure they make sense"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "9e2bbcc5-e45a-4b8c-9d60-601f345e8134",
+ "metadata": {},
+ "source": [
+ "**Time**"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
@@ -560,7 +568,7 @@
"metadata": {},
"outputs": [],
"source": [
- "time_step = get_step(ds, dim_names_dict['T'])\n",
+ "time_step = pd.Timedelta(get_step(ds, dim_names_dict['T'])).isoformat()\n",
"print(f'time step: {time_step}')"
]
},
@@ -589,6 +597,14 @@
"# ds.isel(time=slice(ix-1,ix+3)).time"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "9aa6c8ff-8d9b-40a7-a281-39b502bd5a3d",
+ "metadata": {},
+ "source": [
+ "**X/lon**"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
@@ -600,6 +616,41 @@
"print(f'x step: {x_step}')"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "fac4c9f2-a952-4c7f-aa32-862957372d6f",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# # debugging for spatial steps: get all step values and locations\n",
+ "# x_dim=dim_names_dict['X']\n",
+ "# x_step = get_step(ds, x_dim, debug=True, step_ix=1)\n",
+ "# print(f'\\nx dim name (for next cell): {x_dim}')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "8d0b5a2d-dc58-4ad6-b890-859ce6bb08de",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# # debugging for spatial steps, cont:\n",
+ "# # please choose one of the index locations printed above\n",
+ "# # this will print the time steps adjacent to it\n",
+ "# ix = 5\n",
+ "# ds.isel(x=slice(ix-1,ix+3)).x"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "21b5cca4-8bb4-498d-ae6b-6b8545fffe56",
+ "metadata": {},
+ "source": [
+ "**Y/lat**"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
@@ -611,6 +662,33 @@
"print(f'y step: {y_step}')"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ece0fe37-b54c-4721-aa9b-33d2998d191b",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# # debugging for spatial steps: get all step values and locations\n",
+ "# y_dim=dim_names_dict['Y']\n",
+ "# y_step = get_step(ds, y_dim, debug=True, step_ix=1)\n",
+ "# print(f'\\nx dim name (for next cell): {x_dim}')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "abdafb8f-5217-4b82-91b6-eec8183c9128",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# # debugging for spatial steps, cont:\n",
+ "# # please choose one of the index locations printed above\n",
+ "# # this will print the time steps adjacent to it\n",
+ "# ix = 5\n",
+ "# ds.isel(y=slice(ix-1,ix+3)).y"
+ ]
+ },
{
"cell_type": "markdown",
"id": "00a5e041-081d-428d-ac2e-75d16de205e6",
@@ -648,7 +726,7 @@
"\n",
"# we do not recommend including redundant dimensions (do not include x,y if you have lon,lat)\n",
"# note that the extent of each dimension should be pulled from the dataset\n",
- "dims_dict = {dim_names_dict['T']: pystac.extensions.datacube.Dimension({'type': 'temporal', 'description': get_long_name(ds, dim_names_dict['T']), 'extent': [temporal_extent_lower.strftime('%Y-%m-%dT%XZ'), temporal_extent_upper.strftime('%Y-%m-%dT%XZ')], 'step': pd.Timedelta(time_step).isoformat()}),\n",
+ "dims_dict = {dim_names_dict['T']: pystac.extensions.datacube.Dimension({'type': 'temporal', 'description': get_long_name(ds, dim_names_dict['T']), 'extent': [temporal_extent_lower.strftime('%Y-%m-%dT%XZ'), temporal_extent_upper.strftime('%Y-%m-%dT%XZ')], 'step':time_step}),\n",
" dim_names_dict['X']: pystac.extensions.datacube.Dimension({'type': 'spatial', 'axis': 'x', 'description': get_long_name(ds, dim_names_dict['X']), 'extent': [xy_bounds[0], xy_bounds[2]], 'step': x_step, 'reference_system': projjson}),\n",
" dim_names_dict['Y']: pystac.extensions.datacube.Dimension({'type': 'spatial', 'axis': 'y', 'description': get_long_name(ds, dim_names_dict['Y']), 'extent': [xy_bounds[1], xy_bounds[3]], 'step': y_step, 'reference_system': projjson}),\n",
" 'bottom_top_stag': pystac.extensions.datacube.Dimension({'type': 'spatial', 'axis': 'z', 'description': get_long_name(ds, 'bottom_top_stag')}),\n",
diff --git a/workflows/examples/create_item_from_zarr_conus404-daily.ipynb b/workflows/examples/create_item_from_zarr_conus404-daily.ipynb
index 3713cca8..c8d3f29b 100644
--- a/workflows/examples/create_item_from_zarr_conus404-daily.ipynb
+++ b/workflows/examples/create_item_from_zarr_conus404-daily.ipynb
@@ -563,6 +563,14 @@
"#### user review needed - looks at the steps pulled out and make sure they make sense"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "18b8950f-030f-4f78-b9ac-799dc9263cb6",
+ "metadata": {},
+ "source": [
+ "**Time**"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
@@ -570,7 +578,7 @@
"metadata": {},
"outputs": [],
"source": [
- "time_step = get_step(ds, dim_names_dict['T'])\n",
+ "time_step = pd.Timedelta(get_step(ds, dim_names_dict['T'])).isoformat()\n",
"print(f'time step: {time_step}')"
]
},
@@ -599,6 +607,14 @@
"# ds.isel(time=slice(ix-1,ix+3)).time"
]
},
+ {
+ "cell_type": "markdown",
+ "id": "c2898abe-ca26-4587-bc6d-531268547266",
+ "metadata": {},
+ "source": [
+ "**X/lon**"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
@@ -610,6 +626,41 @@
"print(f'x step: {x_step}')"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "2f29a57d-2203-4f49-9dea-c04c1362d685",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# # debugging for spatial steps: get all step values and locations\n",
+ "# x_dim=dim_names_dict['X']\n",
+ "# x_step = get_step(ds, x_dim, debug=True, step_ix=1)\n",
+ "# print(f'\\nx dim name (for next cell): {x_dim}')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "448714dd-4f57-4e74-99bc-c3b3de400231",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# # debugging for spatial steps, cont:\n",
+ "# # please choose one of the index locations printed above\n",
+ "# # this will print the time steps adjacent to it\n",
+ "# ix = 5\n",
+ "# ds.isel(x=slice(ix-1,ix+3)).x"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "id": "b40ef6ce-8830-4465-a960-f31357ac73ad",
+ "metadata": {},
+ "source": [
+ "**Y/lat**"
+ ]
+ },
{
"cell_type": "code",
"execution_count": null,
@@ -621,6 +672,33 @@
"print(f'y step: {y_step}')"
]
},
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "15975722-2f96-4a39-b904-c99cdf2921c3",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# # debugging for spatial steps: get all step values and locations\n",
+ "# y_dim=dim_names_dict['Y']\n",
+ "# y_step = get_step(ds, y_dim, debug=True, step_ix=1)\n",
+ "# print(f'\\nx dim name (for next cell): {x_dim}')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "142e62f0-412c-4e9b-a117-205c5a2c08af",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# # debugging for spatial steps, cont:\n",
+ "# # please choose one of the index locations printed above\n",
+ "# # this will print the time steps adjacent to it\n",
+ "# ix = 5\n",
+ "# ds.isel(y=slice(ix-1,ix+3)).y"
+ ]
+ },
{
"cell_type": "markdown",
"id": "00a5e041-081d-428d-ac2e-75d16de205e6",
@@ -658,7 +736,7 @@
"\n",
"# we do not recommend including redundant dimensions (do not include x,y if you have lon,lat)\n",
"# note that the extent of each dimension should be pulled from the dataset\n",
- "dims_dict = {dim_names_dict['T']: pystac.extensions.datacube.Dimension({'type': 'temporal', 'description': get_long_name(ds, dim_names_dict['T']), 'extent': [temporal_extent_lower.strftime('%Y-%m-%dT%XZ'), temporal_extent_upper.strftime('%Y-%m-%dT%XZ')], 'step': pd.Timedelta(time_step).isoformat()}),\n",
+ "dims_dict = {dim_names_dict['T']: pystac.extensions.datacube.Dimension({'type': 'temporal', 'description': get_long_name(ds, dim_names_dict['T']), 'extent': [temporal_extent_lower.strftime('%Y-%m-%dT%XZ'), temporal_extent_upper.strftime('%Y-%m-%dT%XZ')], 'step': time_step}),\n",
" dim_names_dict['X']: pystac.extensions.datacube.Dimension({'type': 'spatial', 'axis': 'x', 'description': get_long_name(ds, dim_names_dict['X']), 'extent': [xy_bounds[0], xy_bounds[2]], 'step': x_step, 'reference_system': projjson}),\n",
" dim_names_dict['Y']: pystac.extensions.datacube.Dimension({'type': 'spatial', 'axis': 'y', 'description': get_long_name(ds, dim_names_dict['Y']), 'extent': [xy_bounds[1], xy_bounds[3]], 'step': y_step, 'reference_system': projjson}),\n",
" 'bottom_top_stag': pystac.extensions.datacube.Dimension({'type': 'spatial', 'axis': 'z', 'description': get_long_name(ds, 'bottom_top_stag')}),\n",
--
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