diff --git a/.github/workflows/cd.yml b/.github/workflows/cd.yml
index 226a0c0..9ac0213 100644
--- a/.github/workflows/cd.yml
+++ b/.github/workflows/cd.yml
@@ -50,7 +50,7 @@ jobs:
path: dist
- name: Generate artifact attestation for sdist and wheel
- uses: actions/attest-build-provenance@v1.4.3
+ uses: actions/attest-build-provenance@v1.4.4
with:
subject-path: "dist/*"
diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml
index badd57a..505b086 100644
--- a/.github/workflows/ci.yml
+++ b/.github/workflows/ci.yml
@@ -1,6 +1,8 @@
name: CI
on:
+ schedule:
+ - cron: 0 0 * * *
workflow_dispatch:
pull_request:
push:
diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
index cf0abb4..b3a0484 100644
--- a/.pre-commit-config.yaml
+++ b/.pre-commit-config.yaml
@@ -15,6 +15,7 @@ repos:
rev: "v4.6.0"
hooks:
- id: check-added-large-files
+ args: ["--maxkb=1000"]
- id: check-case-conflict
- id: check-merge-conflict
- id: check-symlinks
diff --git a/docs/api.rst b/docs/api.rst
index 520d9f1..b86119a 100644
--- a/docs/api.rst
+++ b/docs/api.rst
@@ -43,3 +43,16 @@ Datasets
general.Dataset
maxar.open_browse
maxar.plot_browse
+
+
+IO
+--
+
+.. currentmodule:: coincident.io
+
+.. autosummary::
+ :toctree: generated/
+
+ sliderule.subset_gedi02a
+ sliderule.subset_atl06
+ sliderule.sample_3dep
diff --git a/docs/conf.py b/docs/conf.py
index 7007742..aafffbd 100644
--- a/docs/conf.py
+++ b/docs/conf.py
@@ -88,3 +88,4 @@
always_document_param_types = True
# autodoc_typehints = "none"
nb_execution_mode = "auto" # off, on
+nb_execution_excludepatterns = ["sliderule.ipynb"]
diff --git a/docs/examples/index.md b/docs/examples/index.md
index 1f95832..6f8f952 100644
--- a/docs/examples/index.md
+++ b/docs/examples/index.md
@@ -8,4 +8,5 @@ This section contains Jupyter Notebooks with narrative workflows using the
quickstart
cascading_search
+sliderule
```
diff --git a/docs/examples/sliderule.ipynb b/docs/examples/sliderule.ipynb
new file mode 100644
index 0000000..b076944
--- /dev/null
+++ b/docs/examples/sliderule.ipynb
@@ -0,0 +1,483 @@
+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Sliderule data I/O\n",
+ "\n",
+ "This notebook will highlight analyzing various coincident elevation measurements. We will find regions with and use sliderule to retrieve ICESat-2 and GEDI point elevation measurements.\n",
+ "\n",
+ "```{note}\n",
+ "Keep in mind, these measurements are from different sensor types, close in time, but not at exactly the same time. All measurements also have uncertainties, so we do not expect perfect agreement.\n",
+ "```"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import coincident\n",
+ "import matplotlib.pyplot as plt\n",
+ "\n",
+ "# For testing\n",
+ "# sliderule.init(url='slideruleearth.io', verbose=True)\n",
+ "\n",
+ "%matplotlib inline"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Identify a primary dataset\n",
+ "\n",
+ "Start by loading a full resolution polygon of a 3DEP LiDAR workunit which has a known start_datetime and end_datatime:"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
\n",
+ "\n",
+ "
\n",
+ " \n",
+ " \n",
+ " | \n",
+ " workunit | \n",
+ " workunit_id | \n",
+ " project | \n",
+ " project_id | \n",
+ " start_datetime | \n",
+ " end_datetime | \n",
+ " ql | \n",
+ " spec | \n",
+ " p_method | \n",
+ " dem_gsd_meters | \n",
+ " ... | \n",
+ " seamless_category | \n",
+ " seamless_reason | \n",
+ " lpc_link | \n",
+ " sourcedem_link | \n",
+ " metadata_link | \n",
+ " geometry | \n",
+ " collection | \n",
+ " datetime | \n",
+ " dayofyear | \n",
+ " duration | \n",
+ "
\n",
+ " \n",
+ " \n",
+ " \n",
+ " 0 | \n",
+ " CO_WestCentral_2019 | \n",
+ " 175984 | \n",
+ " CO_WestCentral_2019_A19 | \n",
+ " 175987 | \n",
+ " 2019-08-21 | \n",
+ " 2019-09-19 | \n",
+ " QL 2 | \n",
+ " USGS Lidar Base Specification 1.3 | \n",
+ " linear-mode lidar | \n",
+ " 1.0 | \n",
+ " ... | \n",
+ " Meets | \n",
+ " Meets 3DEP seamless DEM requirements | \n",
+ " https://rockyweb.usgs.gov/vdelivery/Datasets/S... | \n",
+ " http://prd-tnm.s3.amazonaws.com/index.html?pre... | \n",
+ " http://prd-tnm.s3.amazonaws.com/index.html?pre... | \n",
+ " MULTIPOLYGON (((-106.13571 38.4146, -106.1702 ... | \n",
+ " 3DEP | \n",
+ " 2019-09-04 12:00:00 | \n",
+ " 247 | \n",
+ " 29 | \n",
+ "
\n",
+ " \n",
+ "
\n",
+ "
1 rows × 33 columns
\n",
+ "
"
+ ],
+ "text/plain": [
+ " workunit workunit_id project project_id \\\n",
+ "0 CO_WestCentral_2019 175984 CO_WestCentral_2019_A19 175987 \n",
+ "\n",
+ " start_datetime end_datetime ql spec \\\n",
+ "0 2019-08-21 2019-09-19 QL 2 USGS Lidar Base Specification 1.3 \n",
+ "\n",
+ " p_method dem_gsd_meters ... seamless_category \\\n",
+ "0 linear-mode lidar 1.0 ... Meets \n",
+ "\n",
+ " seamless_reason \\\n",
+ "0 Meets 3DEP seamless DEM requirements \n",
+ "\n",
+ " lpc_link \\\n",
+ "0 https://rockyweb.usgs.gov/vdelivery/Datasets/S... \n",
+ "\n",
+ " sourcedem_link \\\n",
+ "0 http://prd-tnm.s3.amazonaws.com/index.html?pre... \n",
+ "\n",
+ " metadata_link \\\n",
+ "0 http://prd-tnm.s3.amazonaws.com/index.html?pre... \n",
+ "\n",
+ " geometry collection \\\n",
+ "0 MULTIPOLYGON (((-106.13571 38.4146, -106.1702 ... 3DEP \n",
+ "\n",
+ " datetime dayofyear duration \n",
+ "0 2019-09-04 12:00:00 247 29 \n",
+ "\n",
+ "[1 rows x 33 columns]"
+ ]
+ },
+ "execution_count": 2,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "workunit = \"CO_WestCentral_2019\"\n",
+ "df_wesm = coincident.search.wesm.read_wesm_csv()\n",
+ "gf_lidar = coincident.search.wesm.load_by_fid(\n",
+ " df_wesm[df_wesm.workunit == workunit].index\n",
+ ")\n",
+ "gf_lidar"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Search secondary datasets\n",
+ "\n",
+ "Provide a list that will be searched in order. The list contains tuples of dataset aliases and the temporal pad in days to search before the primary dataset start and end dates"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "ICESat2(alias='icesat-2', has_stac_api=True, collections=['ATL06_006'], search='https://cmr.earthdata.nasa.gov/stac/NSIDC_ECS', start='2018-10-13', end=None, type='altimeter', provider='nasa', stac_kwargs={'limit': 1000})\n"
+ ]
+ }
+ ],
+ "source": [
+ "# For more control, modify the dataset object being searched\n",
+ "# For example, search for ATL06 instead of default ATL03\n",
+ "is2 = coincident.datasets.nasa.ICESat2()\n",
+ "is2.collections = [\"ATL06_006\"]\n",
+ "print(is2)"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "secondary_datasets = [\n",
+ " (\"gedi\", 40), # +/- 40 days from lidar\n",
+ " (is2, 60), # +/- 60 days from lidar\n",
+ "]\n",
+ "\n",
+ "gf_gedi, gf_is2 = coincident.search.cascading_search(\n",
+ " gf_lidar,\n",
+ " secondary_datasets,\n",
+ " min_overlap_area=30, # km^2\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Get ICESat-2 ATL06 Data\n",
+ "\n",
+ "We've identified 7 granules of icesat-2 data to examine, but there is no need to work with the entire granule, which spans a huge geographic extent. Instead we'll retrive a subset of elevation values in the area of interest for each granule."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ "