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Save 0-deg predictions to different path #28

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Merged
dfulu merged 2 commits into from
Sep 8, 2025
Merged

Save 0-deg predictions to different path #28

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6f2ad69
light refactor
dfulu Sep 8, 2025
06f9824
remove scaling
dfulu Sep 8, 2025
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2 changes: 1 addition & 1 deletion pyproject.toml
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Original file line number Diff line number Diff line change
Expand Up @@ -25,7 +25,7 @@ dependencies = [
"hydra-core==1.3.2",
"loguru == 0.7.3",
"numpy==2.1.2",
"ocf-data-sampler==0.5.5",
"ocf-data-sampler==0.5.27",
"pandas==2.2.3",
"s3fs==2025.7.0",
"safetensors==0.5.2",
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21 changes: 10 additions & 11 deletions src/cloudcasting_app/app.py
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Expand Up @@ -19,7 +19,7 @@
from safetensors.torch import load_model
from loguru import logger

from cloudcasting_app.data import get_input_data, prepare_satellite_data, sat_path
from cloudcasting_app.data import SatelliteDownloader, sat_path, get_input_data

# Get package version
try:
Expand All @@ -28,8 +28,6 @@
__version__ = "v?"


xr.set_options(keep_attrs=True)

# ---------------------------------------------------------------------------

# Model will use GPU if available
Expand Down Expand Up @@ -62,7 +60,8 @@ def app(t0=None):
# ---------------------------------------------------------------------------
# 1. Prepare the input data
logger.info("Downloading satellite data")
prepare_satellite_data(t0)
satellite_downloader = SatelliteDownloader()
satellite_downloader.prepare_satellite_data(t0)

# ---------------------------------------------------------------------------
# 2. Load model
Expand Down Expand Up @@ -90,12 +89,8 @@ def app(t0=None):
# 3. Get inference inputs
logger.info("Preparing inputs")

# TODO check the spatial dimensions of this zarr
# Get inputs
ds = xr.open_zarr(sat_path)

# Reshape to (channel, time, height, width)
ds = ds.transpose("variable", "time", "y_geostationary", "x_geostationary")
ds = xr.open_zarr(sat_path).compute()

X = get_input_data(ds, t0)

Expand Down Expand Up @@ -130,8 +125,12 @@ def app(t0=None):
# Save predictions to the latest path and to path with timestring
out_dir = os.environ["OUTPUT_PREDICTION_DIRECTORY"]

latest_zarr_path = f"{out_dir}/latest.zarr"
t0_string_zarr_path = t0.strftime(f"{out_dir}/%Y-%m-%dT%H:%M.zarr")
if satellite_downloader.use_5_minute:
latest_zarr_path = f"{out_dir}/latest.zarr"
t0_string_zarr_path = t0.strftime(f"{out_dir}/%Y-%m-%dT%H:%M.zarr")
else:
latest_zarr_path = f"{out_dir}/latest_0-deg.zarr"
t0_string_zarr_path = t0.strftime(f"{out_dir}/%Y-%m-%dT%H:%M_0-deg.zarr")

fs = fsspec.open(out_dir).fs
for path in [latest_zarr_path, t0_string_zarr_path]:
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