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351 | class MonthlyRBStrategy(SavingStrategy):
"""Save PRBEM-standard data into one monthly file per interval.
The strategy supports NetCDF, CDF, HDF5, and MATLAB output through a format
dispatch table. Existing files can be appended by loading the current file,
replacing overlapping timestamps with the new data block, and atomically
rewriting the merged data.
"""
output_files: list[OutputFile]
dependency_dict: dict[InternalName, list[str]]
def __init__(
self,
base_data_path: str | Path,
mission: str,
satellite: str,
instrument: str,
mag_field: MagneticFieldLiteral,
data_standard: DataStandard[StandardName],
file_format: MFSFormats = "nc",
) -> None:
"""Initialize a monthly file saving strategy.
Parameters:
base_data_path (str | Path): Directory where monthly files are written.
mission (str): Mission name, used in file path and name generation.
satellite (str): Satellite name, used in file path and name generation.
instrument (str): Instrument name, used in file path and name generation.
mag_field (MagneticFieldLiteral): Magnetic field model name. Monthly files use one model.
file_format (MFSFormats): One of ``"nc"``, ``"cdf"``, ``"h5"``, or ``"mat"``.
A leading dot is also accepted.
data_standard (DataStandard): Instance of the data standard implementation.
Attributes:
output_files: List of output file configurations, with variable names
defined by ``_get_output_file_entries()``.
dependency_dict: Dictionary defining NetCDF dimension dependencies for
all variables in ``output_files``.
"""
self.base_data_path = Path(base_data_path)
self.mission = mission
self.satellite = satellite
self.instrument = instrument
self.mag_field = mag_field
self.data_standard = data_standard
self.file_format = ep.utils.normalize_file_format(file_format)
self.output_files = [
OutputFile("full", self._get_output_file_entries(), save_incomplete=True),
]
self._writers: dict[str, FileWriter] = {
".mat": ep.utils.write_mat_file,
".h5": ep.utils.write_h5_file,
".nc": ep.utils.write_netcdf_file,
".cdf": ep.utils.write_cdf_file,
}
self._loaders: dict[str, FileLoader] = {
".mat": ep.utils.load_mat_data,
".h5": ep.utils.load_h5_data,
".nc": ep.utils.load_netcdf_data,
".cdf": ep.utils.load_cdf_data,
}
def _get_output_file_entries(self) -> list[InternalName]:
"""Return the standard variable list plus user-defined custom variables."""
return [
"FEDU",
"Epoch",
"Alpha_Eq",
"Energy_FEDU",
"Alpha",
"B_Calc",
"B_Eq",
"InvK",
"InvMu",
"Position",
"PSD",
"R_Eq",
"MLT",
"L_m",
"L_star",
]
def _sanitize_dimension_name(self, variable_name: str) -> str:
"""Return a NetCDF-safe root dimension name derived from a variable path."""
return "".join(char if char.isalnum() else "_" for char in variable_name).strip("_") or "custom"
def _register_writer(self, extension: str, writer: FileWriter) -> None:
"""Register or replace the writer used for a file extension.
TODO: We may want to support user defined formats in the future, so this method could be extended to check.
"""
normalized = ep.utils.normalize_file_format(extension)
self._writers[normalized] = writer
def get_time_intervals_to_save(self, start_time: datetime | None, end_time: datetime | None) -> list[TimeInterval]:
"""Split the requested time range into full monthly intervals."""
time_intervals: list[TimeInterval] = []
if start_time is None or end_time is None:
msg = "start_time and end_time must be provided for MonthlyRBStrategy!"
raise ValueError(msg)
current_time = start_time.replace(day=1)
while current_time <= end_time:
year = current_time.year
month = current_time.month
eom_day = calendar.monthrange(year, month)[1]
month_start = datetime(year, month, 1, 0, 0, 0, tzinfo=timezone.utc)
month_end = datetime(year, month, eom_day, 23, 59, 59, tzinfo=timezone.utc)
time_intervals.append((month_start, month_end))
current_time = (
datetime(year + 1, 1, 1, tzinfo=timezone.utc)
if month == 12
else datetime(year, month + 1, 1, tzinfo=timezone.utc)
)
return time_intervals
def get_file_path_stem(self) -> Path:
return self.base_data_path / self.mission.upper() / self.satellite.lower()
def get_file_name_stem(self) -> str:
return self.satellite.lower() + "_" + self.instrument.lower()
def get_file_path(self, interval_start: datetime, interval_end: datetime, output_file: OutputFile) -> Path: # noqa: ARG002
"""Generate the monthly file path for the configured format."""
start_year_month_day = interval_start.strftime("%Y%m%d")
end_year_month_day = interval_end.strftime("%Y%m%d")
file_name = (
f"{self.get_file_name_stem()}_{start_year_month_day}to{end_year_month_day}_"
f"{self.mag_field}{self.file_format}"
)
return self.get_file_path_stem() / file_name
def standardize_variable(
self,
variable: Variable,
internal_name: InternalName,
*,
first_call_of_interval: bool,
) -> Variable:
"""Standardize a variable through the configured data standard."""
return self.data_standard.standardize_variable(
internal_name, variable, reset_consistency_check=first_call_of_interval
)
def save_single_file(self, file_path: Path, dict_to_save: SavedDataDict, *, append: bool = False) -> None:
"""Save one monthly file, optionally appending to an existing file."""
file_path.parent.mkdir(parents=True, exist_ok=True)
format_name = ep.utils.normalize_file_format(file_path.suffix)
writer = self._writers.get(format_name)
if writer is None:
msg = f"The '{format_name}' format is not implemented."
logger.error(msg)
raise NotImplementedError(msg)
if file_path.exists() and append:
logger.info(f"Appending and saving to existing file: {file_path.resolve()}")
self.append_data(file_path, dict_to_save)
return
logger.info(f"Saving file: {file_path.resolve()}")
writer(file_path, dict_to_save, self.data_standard)
def append_data(self, file_path: Path, data_dict_to_save: SavedDataDict) -> SavedDataDict:
"""Append data to any supported monthly file format.
Existing data is loaded with the loader for ``file_path.suffix``, merged
by timestamp with the new dictionary, and written to a temporary file
before replacing the original file.
"""
if not file_path.exists():
msg = f"Cannot append: file does not exist: {file_path}"
raise FileNotFoundError(msg)
new_time = np.asarray(data_dict_to_save["Epoch"])
if int(new_time.shape[0]) == 0:
logger.info(f"No new time data to insert for {file_path.name}")
return data_dict_to_save
format_name = ep.utils.normalize_file_format(file_path.suffix)
loader = self._loaders.get(format_name)
writer = self._writers.get(format_name)
if loader is None or writer is None:
msg = f"Appending to '{format_name}' files is not supported by MonthlyRBStrategy."
logger.error(msg)
raise NotImplementedError(msg)
if format_name == ".nc":
self._validate_netcdf_appendable(file_path)
logger.info(f"Loading existing data from {file_path.name}")
existing_data = loader(file_path)
logger.info(f"Merging and sorting data for {file_path.name}")
merged_data = self._merge_and_sort_data(existing_data, data_dict_to_save)
with tempfile.NamedTemporaryFile(suffix=format_name, delete=False, dir=file_path.parent) as tmp_file:
tmp_path = Path(tmp_file.name)
try:
logger.info(f"Writing merged data to temporary file {tmp_path.name}")
writer(tmp_path, merged_data, self.data_standard)
logger.info(f"Replacing original file with merged data for {file_path.name}")
shutil.move(str(tmp_path), str(file_path))
logger.info(f"Successfully inserted data into {file_path.resolve()}")
return merged_data # noqa: TRY300
except Exception:
if tmp_path.exists():
tmp_path.unlink()
logger.exception("Failed to write merged data to temporary file")
raise
def _merge_and_sort_data(
self,
existing_data: dict[StandardName | Literal["metadata"], Any],
new_data: SavedDataDict,
) -> SavedDataDict:
"""Merge two dictionaries along the time axis, replacing duplicate times."""
def _normalize_1d(arr: np.ndarray) -> np.ndarray:
arr = np.asarray(arr)
if arr.ndim == 2 and arr.shape[1] == 1:
return arr.reshape(-1)
return arr
existing_data_internal: SavedDataDict = {}
for name, value in existing_data.items():
if name == "metadata":
existing_data_internal["metadata"] = value
else:
internal_name = self.data_standard.get_internal_name(name)
if internal_name is None:
msg = f"Could not find necessary internal name for variable: {name}"
raise ValueError(msg)
existing_data_internal[internal_name] = value
existing_time = _normalize_1d(existing_data_internal["Epoch"])
new_time = _normalize_1d(new_data["Epoch"])
mask_keep_existing = ~np.isin(existing_time, new_time)
insert_idx = int(np.searchsorted(existing_time, new_time[0]))
merged: SavedDataDict = {}
existing_metadata = existing_data_internal.get("metadata", {})
new_metadata = new_data.get("metadata", {})
if isinstance(existing_metadata, dict) and isinstance(new_metadata, dict):
merged["metadata"] = {**existing_metadata, **new_metadata}
elif "metadata" in new_data:
merged["metadata"] = new_metadata
elif "metadata" in existing_data_internal:
merged["metadata"] = existing_metadata
all_keys = set(existing_data_internal.keys()) | set(new_data.keys())
for key in all_keys:
if key == "metadata" or key.startswith("__"):
continue
if key not in existing_data_internal:
merged[key] = new_data[key]
continue
if key not in new_data:
merged[key] = existing_data_internal[key]
continue
v1 = _normalize_1d(np.asarray(existing_data_internal[key]))
v2 = _normalize_1d(np.asarray(new_data[key]))
if v1.ndim != v2.ndim:
msg = f"{key}: ndim mismatch {v1.shape} vs {v2.shape}"
logger.error(msg)
raise ValueError(msg)
if v1.ndim > 1 and v1.shape[1:] != v2.shape[1:]:
msg = f"{key}: shape mismatch {v1.shape} vs {v2.shape}"
logger.error(msg)
raise ValueError(msg)
v1_trunc = v1[mask_keep_existing]
merged_val = v2 if v1_trunc.size == 0 else np.insert(v1_trunc, insert_idx, v2, axis=0)
if key == "Epoch":
t = np.asarray(merged_val)
if len(np.unique(t)) != len(t):
msg = "Time values are not unique after merge for key 'time'"
logger.error(msg)
raise ValueError(msg)
merged[key] = merged_val
return merged
def _validate_netcdf_appendable(self, file_path: Path) -> None:
"""Validate that the existing NetCDF file has an unlimited time dimension."""
with nC.Dataset(file_path, "r", format="NETCDF4") as file:
time_dim = file.dimensions.get("Epoch")
if time_dim is None or not time_dim.isunlimited():
msg = (
"Cannot append: the existing NetCDF file does not have an "
"unlimited 'Epoch' dimension. Recreate the file with 'Epoch' "
"created as unlimited (None)."
)
raise ValueError(msg)
|