From 0e217a4b283decfd04ba9b7bc564bccf4c29991a Mon Sep 17 00:00:00 2001
From: schroeder5 <s.schroeder@fz-juelich.de>
Date: Mon, 3 Jun 2024 21:57:31 +0000
Subject: [PATCH] do the ML downscaling for the whole forecast length of the
numerical simulation
---
src/pages/dashboard.py | 3 ++-
1 file changed, 2 insertions(+), 1 deletion(-)
diff --git a/src/pages/dashboard.py b/src/pages/dashboard.py
index 168ad1d..2247057 100644
--- a/src/pages/dashboard.py
+++ b/src/pages/dashboard.py
@@ -1333,6 +1333,7 @@ def ml_downscaling_output_download(download_button, job_dict, plot_dict):
iscen = job_props['emis_scen']
iscen = iscen if (iscen) else 0
fc_length = job_props['forecast_length']
+ forecast_hours = fc_length * 24
out_filenames = get_filenames(jobnr, year, month, day, iscen, fc_length)
downscaling_fn = out_filenames["downscaling_filename"].format(variable=variable)
downscaling_filename = str(DATA_PATH.joinpath(f'{downscaling_fn}'))
@@ -1344,7 +1345,7 @@ def ml_downscaling_output_download(download_button, job_dict, plot_dict):
credentials = uc_credentials.UsernamePassword(UNICORE_USER, UNICORE_PASSWORD)
client = uc_client.Client(credentials, base_url)
job_description = {'Executable': f"/p/project/cjicg21/{UNICORE_USER}/downscaling_destine_de370c/HPC_batch_scripts/inference_destine_test_{variable}.sh",
- 'Arguments': [ f"{jobnr.upper()}/CTM/", year, month, day ] }
+ 'Arguments': [ f"{jobnr.upper()}/CTM/", year, month, day, str(forecast_hours) ] }
job = client.new_job(job_description)
# wait for the job to finish:
while str(job.status) != 'JobStatus.SUCCESSFUL':
--
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