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add new pv runvl model #158

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add new pv runvl model #158

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c7bbacf
add new pv runvl model
peterdudfield Dec 19, 2024
dccebf6
update conftest
peterdudfield Dec 19, 2024
f5572d5
update conftest
peterdudfield Dec 19, 2024
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6 changes: 6 additions & 0 deletions india_forecast_app/models/all_models.yaml
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Original file line number Diff line number Diff line change
Expand Up @@ -32,6 +32,12 @@ models:
version: d71104620f0b0bdd3eeb63cafecd2a49032ae0f7
client: ruvnl
asset_type: pv
- name: pvnet_india_ecmwf_mo_gfs
type: pvnet
id: openclimatefix/pvnet_india
version: 0561e737765df164b572fa506401995263c6401b
client: ruvnl
asset_type: pv
# Ad client solar
- name: pvnet_ad_sites
type: pvnet
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22 changes: 15 additions & 7 deletions tests/conftest.py
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Expand Up @@ -166,7 +166,7 @@ def generation_db_values(db_session, sites, init_timestamp):
def generation_db_values_only_wind(db_session, sites, init_timestamp):
"""Create some fake generations"""

n = 20*25 # 25 hours of readings
n = 20 * 25 # 25 hours of readings
start_times = [init_timestamp - dt.timedelta(minutes=x * 3) for x in range(n)]

# remove some of the most recent readings (to simulate missing timestamps)
Expand Down Expand Up @@ -361,12 +361,9 @@ def nwp_mo_global_data(tmp_path_factory, time_before_present):

# Load dataset which only contains coordinates, but no data
ds = xr.open_zarr(
f"{os.path.dirname(os.path.abspath(__file__))}/test_data/nwp-no-data_gfs.zarr"
f"{os.path.dirname(os.path.abspath(__file__))}/test_data/nwp-no-data.zarr"
)

# rename dimension init_time_utc to init_time
ds = ds.rename({"init_time_utc": "init_time"})

# Last t0 to at least 4 hours ago and floor to 3-hour interval
t0_datetime_utc = time_before_present(dt.timedelta(hours=0)).floor("3h")
t0_datetime_utc = t0_datetime_utc - dt.timedelta(hours=4)
Expand All @@ -389,10 +386,21 @@ def nwp_mo_global_data(tmp_path_factory, time_before_present):
ds[v].encoding.clear()

# change variables values to for MO global
ds.variable.values[0:3] = ["temperature_sl", "wind_u_component_10m", "wind_v_component_10m"]
ds.variable.values[0:10] = [
"temperature_sl",
"wind_u_component_10m",
"wind_v_component_10m",
"downward_shortwave_radiation_flux_gl",
"cloud_cover_high",
"cloud_cover_low",
"cloud_cover_medium",
"relative_humidity_sl",
"snow_depth_gl",
"visibility_sl",
]

# interpolate 3 hourly step to 1 hour steps
steps = pd.TimedeltaIndex(np.arange(49) * 3600 * 1e9, freq='infer')
steps = pd.TimedeltaIndex(np.arange(49) * 3600 * 1e9, freq="infer")
ds = ds.interp(step=steps, method="linear")

ds["mo_global"] = xr.DataArray(
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2 changes: 1 addition & 1 deletion tests/models/test_pydantic_models.py
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Expand Up @@ -5,7 +5,7 @@
def test_get_all_models():
"""Test for getting all models"""
models = get_all_models()
assert len(models.models) == 9
assert len(models.models) == 10


def test_get_all_models_client():
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