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rqthomas committed Jan 9, 2024
2 parents a2bb56c + f11351c commit 1341288
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4 changes: 2 additions & 2 deletions .github/workflows/combined.yaml
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# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
on:
schedule:
- cron: '0 5 * * *'
#schedule:
# - cron: '0 5 * * *'
workflow_dispatch:

name: submissions-score-dashboard-catalog
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10 changes: 2 additions & 8 deletions .github/workflows/drivers_stage1.yaml
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# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
on:
schedule:
- cron: '0 23 * * *'
- cron: '0 5 * * *'
workflow_dispatch:


Expand All @@ -29,16 +29,10 @@ jobs:
- name: Update GEFS
shell: Rscript {0}
run: |
source("drivers/download_stage1_psuedo.R")
source("drivers/download_stage1.R")
- name: Generate stage 2
shell: Rscript {0}
run: |
source("drivers/generate_stage2.R")
- name: Update Stage3
shell: Rscript {0}
run: |
source("drivers/update_stage3.R")
9 changes: 7 additions & 2 deletions .github/workflows/drivers_stage3.yaml
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@@ -1,8 +1,8 @@
# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
on:
#schedule:
# - cron: '0 13 * * *'
schedule:
- cron: '0 23 * * *'
workflow_dispatch:

name: gefs_osn_stage3
Expand All @@ -25,6 +25,11 @@ jobs:
install.packages("remotes")
remotes::install_github("eco4cast/gefs4cast")
- name: Download Pseudo
shell: Rscript {0}
run: |
source("drivers/download_psuedo.R")
- name: Update Stage3
shell: Rscript {0}
run: |
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Expand Up @@ -183,7 +183,7 @@
"interval": [
[
"2023-01-01T00:00:00Z",
"2024-01-18T00:00:00Z"
"2024-02-08T00:00:00Z"
]
]
}
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Expand Up @@ -120,6 +120,11 @@
"type": "application/json",
"href": "../../models/model_items/tg_bag_mlp.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/neon4cast_example.json"
},
{
"rel": "parent",
"type": "application/json",
Expand Down Expand Up @@ -163,7 +168,7 @@
"interval": [
[
"2023-01-01T00:00:00Z",
"2024-11-07T00:00:00Z"
"2024-11-28T00:00:00Z"
]
]
}
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Expand Up @@ -190,6 +190,16 @@
"type": "application/json",
"href": "../../models/model_items/tg_auto_adam.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/precip_mod.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/neon4cast_example.json"
},
{
"rel": "parent",
"type": "application/json",
Expand Down Expand Up @@ -233,7 +243,7 @@
"interval": [
[
"2023-01-01T00:00:00Z",
"2024-11-07T00:00:00Z"
"2024-11-28T00:00:00Z"
]
]
}
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2 changes: 1 addition & 1 deletion catalog/forecasts/Aquatics/collection.json
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Expand Up @@ -68,7 +68,7 @@
"interval": [
[
"2023-01-01T00:00:00Z",
"2024-12-02T00:00:00Z"
"2024-12-23T00:00:00Z"
]
]
}
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Expand Up @@ -128,7 +128,7 @@
"interval": [
[
"2023-01-02T00:00:00Z",
"2024-12-02T00:00:00Z"
"2024-12-23T00:00:00Z"
]
]
}
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Expand Up @@ -128,7 +128,7 @@
"interval": [
[
"2023-01-02T00:00:00Z",
"2024-12-02T00:00:00Z"
"2024-12-23T00:00:00Z"
]
]
}
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2 changes: 1 addition & 1 deletion catalog/forecasts/Beetles/collection.json
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Expand Up @@ -63,7 +63,7 @@
"interval": [
[
"2023-01-01T00:00:00Z",
"2024-12-02T00:00:00Z"
"2024-12-23T00:00:00Z"
]
]
}
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Expand Up @@ -95,6 +95,11 @@
"type": "application/json",
"href": "../../models/model_items/tg_randfor.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/PEG.json"
},
{
"rel": "parent",
"type": "application/json",
Expand Down Expand Up @@ -138,7 +143,7 @@
"interval": [
[
"2023-01-01T00:00:00Z",
"2024-01-18T00:00:00Z"
"2024-02-08T00:00:00Z"
]
]
}
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Expand Up @@ -110,6 +110,11 @@
"type": "application/json",
"href": "../../models/model_items/tg_auto_adam.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/PEG.json"
},
{
"rel": "parent",
"type": "application/json",
Expand Down Expand Up @@ -153,7 +158,7 @@
"interval": [
[
"2023-01-01T00:00:00Z",
"2024-01-18T00:00:00Z"
"2024-02-08T00:00:00Z"
]
]
}
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2 changes: 1 addition & 1 deletion catalog/forecasts/Phenology/collection.json
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Expand Up @@ -63,7 +63,7 @@
"interval": [
[
"2023-01-01T00:00:00Z",
"2024-12-02T00:00:00Z"
"2024-12-23T00:00:00Z"
]
]
}
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@@ -1,6 +1,6 @@
{
"id": "abundance_weekly",
"description": "This page includes all models for the abundance_weekly variable.",
"id": "30min_Net_ecosystem_exchange",
"description": "This page includes all models for the 30min_Net_ecosystem_exchange variable.",
"stac_version": "1.0.0",
"license": "CC0-1.0",
"stac_extensions": [
Expand All @@ -13,67 +13,7 @@
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_humidity_lm_all_sites.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_precip_lm_all_sites.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_temp_lm.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_humidity_lm.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_precip_lm.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_randfor.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_lasso.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_temp_lm_all_sites.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_arima.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_tbats.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_randfor_all_sites.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_ets.json"
},
{
"rel": "item",
"type": "application/json",
"href": "../../models/model_items/tg_lasso_all_sites.json"
"href": "../../models/model_items/climatology.json"
},
{
"rel": "parent",
Expand All @@ -96,34 +36,29 @@
},
{
"rel": "about",
"href": "www.neon4cast.org",
"href": "https://projects.ecoforecast.org/neon4cast-docs/",
"type": "text/html",
"title": "NEON Ecological Forecasting Challenge Documentation"
},
{
"rel": "describedby",
"href": "www.neon4cast.org",
"title": "NEON Ecological Forecasting Challenge Documentation",
"href": "https://projects.ecoforecast.org/neon4cast-docs/",
"title": "NEON Forecast Challenge Dashboard",
"type": "text/html"
}
],
"title": "abundance_weekly",
"title": "30min_Net_ecosystem_exchange",
"extent": {
"spatial": {
"bbox": [
[
-156.6194,
71.2824,
-66.7987,
71.2824
]
[-156.6194, 17.9696, -66.8687, 71.2824]
]
},
"temporal": {
"interval": [
[
"2021-05-17T00:00:00Z",
"2024-10-28T00:00:00Z"
"2023-11-14T00:00:00Z",
"2024-01-09T00:00:00Z"
]
]
}
Expand Down Expand Up @@ -192,13 +127,21 @@
],
"assets": {
"data": {
"href": "s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=abundance?endpoint_override=sdsc.osn.xsede.org",
"href": "\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=PT30M/variable=nee?endpoint_override=sdsc.osn.xsede.org\"",
"type": "application/x-parquet",
"title": "Database Access",
"roles": [
"data"
],
"description": "Use `arrow` for remote access to the database. This R code will return results for the NEON Ecological Forecasting Aquatics theme.\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=P1W/variable=abundance?endpoint_override=sdsc.osn.xsede.org)\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
"description": "Use `arrow` for remote access to the database. This R code will return results for forecasts of the variable by the specific model .\n\n### R\n\n```{r}\n# Use code below\n\nall_results <- arrow::open_dataset(\"s3://anonymous@bio230014-bucket01/challenges/forecasts/parquet/project_id=neon4cast/duration=PT30M/variable=nee?endpoint_override=sdsc.osn.xsede.org\")\ndf <- all_results |> dplyr::collect()\n\n```\n \n\nYou can use dplyr operations before calling `dplyr::collect()` to `summarise`, `select` columns, and/or `filter` rows prior to pulling the data into a local `data.frame`. Reducing the data that is pulled locally will speed up the data download speed and reduce your memory usage.\n\n\n"
},
"thumbnail": {
"href": "pending",
"type": "image/JPEG",
"roles": [
"thumbnail"
],
"title": "pending"
}
}
}
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Expand Up @@ -58,7 +58,7 @@
"interval": [
[
"2023-11-14T00:00:00Z",
"2023-12-24T00:00:00Z"
"2024-01-09T00:00:00Z"
]
]
}
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