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import os
import tempfile
import pytest
import torch
import numpy as np
import pandas as pd
import xarray as xr
from pvnet.data import DataModule, SiteDataModule
@pytest.fixture
def temp_pt_sample_dir():
"""Create temporary directory with synthetic PT samples"""
with tempfile.TemporaryDirectory() as tmpdirname:
# Create train and val directories
os.makedirs(f"{tmpdirname}/train", exist_ok=True)
os.makedirs(f"{tmpdirname}/val", exist_ok=True)
# Generate and save synthetic samples
for i in range(5):
sample = {
"gsp": torch.rand(21),
"gsp_time_utc": torch.tensor(list(range(21))),
"gsp_nominal_capacity_mwp": torch.tensor(100.0),
"gsp_id": 12
}
torch.save(sample, f"{tmpdirname}/train/{i:08d}.pt")
torch.save(sample, f"{tmpdirname}/val/{i:08d}.pt")
yield tmpdirname
@pytest.fixture
def temp_nc_sample_dir():
"""Create temporary directory with synthetic NC site samples"""
with tempfile.TemporaryDirectory() as tmpdirname:
# Create train and val directories
os.makedirs(f"{tmpdirname}/train", exist_ok=True)
os.makedirs(f"{tmpdirname}/val", exist_ok=True)
# Create config file
config_path = f"{tmpdirname}/data_configuration.yaml"
with open(config_path, "w") as f:
f.write(f"sample_dir: {tmpdirname}\n")
# Generate and save synthetic site samples
for i in range(5):
site_time = pd.date_range("2023-01-01", periods=10, freq="15min")
ds = xr.Dataset(
data_vars={
"site": (["site__time_utc"], np.random.rand(10)),
},
coords={
"site__time_utc": site_time,
"site__site_id": np.int32(i % 3 + 1),
"site__latitude": 52.5,
"site__longitude": -1.5,
"site__capacity_kwp": 10000.0,
}
)
ds.to_netcdf(f"{tmpdirname}/train/{i:08d}.nc", mode="w", engine="h5netcdf")
ds.to_netcdf(f"{tmpdirname}/val/{i:08d}.nc", mode="w", engine="h5netcdf")
yield tmpdirname
def test_init(temp_pt_sample_dir):
"""Test DataModule initialization"""
dm = DataModule(
configuration=None,
sample_dir=temp_pt_sample_dir,
batch_size=2,
num_workers=0,
prefetch_factor=None,
train_period=[None, None],
val_period=[None, None],
)
# Verify datamodule initialisation
assert dm is not None
assert hasattr(dm, "train_dataloader")
def test_iter(temp_pt_sample_dir):
"""Test iteration through DataModule"""
dm = DataModule(
configuration=None,
sample_dir=temp_pt_sample_dir,
batch_size=2,
num_workers=0,
prefetch_factor=None,
train_period=[None, None],
val_period=[None, None],
)
# Verify existing keys
batch = next(iter(dm.train_dataloader()))
assert batch is not None
assert "gsp" in batch
def test_iter_multiprocessing(temp_pt_sample_dir):
"""Test DataModule with multiple workers"""
dm = DataModule(
configuration=None,
sample_dir=temp_pt_sample_dir,
batch_size=1,
num_workers=2,
prefetch_factor=1,
train_period=[None, None],
val_period=[None, None],
)
served_batches = 0
for batch in dm.train_dataloader():
served_batches += 1
if served_batches == 2:
break
# Batch verification
assert served_batches == 2
def test_site_init_sample_dir(temp_nc_sample_dir):
"""Test SiteDataModule initialization with sample dir"""
dm = SiteDataModule(
configuration=None,
sample_dir=temp_nc_sample_dir,
batch_size=2,
num_workers=0,
prefetch_factor=None,
train_period=[None, None],
val_period=[None, None],
)
# Verify datamodule initialisation
assert dm is not None
assert hasattr(dm, "train_dataloader")
def test_site_init_config(temp_nc_sample_dir):
"""Test SiteDataModule initialization with config file"""
config_path = f"{temp_nc_sample_dir}/data_configuration.yaml"
dm = SiteDataModule(
configuration=config_path,
batch_size=2,
num_workers=0,
prefetch_factor=None,
train_period=[None, None],
val_period=[None, None],
sample_dir=None,
)
# Verify datamodule initialisation w/ config
assert dm is not None
assert hasattr(dm, "train_dataloader")
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