#!/usr/bin/env python3
# -----------------------------------------------------------------------------.
# Copyright (c) 2021-2023 DISDRODB developers
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 3 of the License, or
# (at your option) any later version.
#
# This program is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
# GNU General Public License for more details.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
# -----------------------------------------------------------------------------.
"""Implement DISDRODB L1 processing."""
import datetime
import logging
import os
import shutil
import time
from typing import Optional
import dask
import xarray as xr
from disdrodb.api.checks import check_station_inputs
from disdrodb.api.create_directories import (
create_logs_directory,
create_product_directory,
)
from disdrodb.api.io import find_files
from disdrodb.api.path import (
define_file_folder_path,
define_l1_filename,
)
from disdrodb.api.search import get_required_product
from disdrodb.configs import (
get_data_archive_dir,
get_folder_partitioning,
get_metadata_archive_dir,
get_product_options,
)
from disdrodb.l1.processing import generate_l1
from disdrodb.utils.decorators import delayed_if_parallel, single_threaded_if_parallel
# Logger
from disdrodb.utils.logger import (
close_logger,
create_logger_file,
create_product_logs,
log_error,
log_info,
)
from disdrodb.utils.writer import write_product
logger = logging.getLogger(__name__)
@delayed_if_parallel
@single_threaded_if_parallel
def _generate_l1(
filepath,
data_dir,
logs_dir,
campaign_name,
station_name,
# Processing options
force,
verbose,
parallel, # this is used only to initialize the correct logger !
):
"""Generate the L1 product from the DISRODB L0C netCDF file.
Parameters
----------
filepath : str
Path to the L0C netCDF file.
data_dir : str
Directory where the L1 netCDF file will be saved.
logs_dir : str
Directory where the log file will be saved.
campaign_name : str
Name of the campaign.
station_name : str
Name of the station.
force : bool
If True, overwrite existing files.
verbose : bool
Whether to verbose the processing.
Returns
-------
str
Path to the log file generated during processing.
Notes
-----
If an error occurs during processing, it is caught and logged,
but no error is raised to interrupt the execution.
"""
# -----------------------------------------------------------------.
# Define product name
product = "L1"
# Define folder partitioning
folder_partitioning = get_folder_partitioning()
# -----------------------------------------------------------------.
# Create file logger
filename = os.path.basename(filepath)
logger, logger_filepath = create_logger_file(
logs_dir=logs_dir,
filename=filename,
parallel=parallel,
)
##------------------------------------------------------------------------.
# Log start processing
msg = f"{product} processing of {filename} has started."
log_info(logger=logger, msg=msg, verbose=verbose)
success_flag = False
##------------------------------------------------------------------------.
# Retrieve L1 configurations
l1_options = get_product_options("L1").get("product_options")
##------------------------------------------------------------------------.
### Core computation
try:
# Open the raw netCDF
with xr.open_dataset(filepath, chunks=-1, decode_timedelta=False, cache=False) as ds:
ds = ds[["raw_drop_number"]].load()
# Produce L1 dataset
ds = generate_l1(ds=ds, **l1_options)
# Write L1 netCDF4 dataset
if ds["time"].size > 1:
# Define filepath
filename = define_l1_filename(ds, campaign_name=campaign_name, station_name=station_name)
folder_path = define_file_folder_path(ds, data_dir=data_dir, folder_partitioning=folder_partitioning)
filepath = os.path.join(folder_path, filename)
# Write to disk
write_product(ds, filepath=filepath, force=force)
##--------------------------------------------------------------------.
#### - Define logger file final directory
if folder_partitioning != "":
log_dst_dir = define_file_folder_path(ds, data_dir=logs_dir, folder_partitioning=folder_partitioning)
os.makedirs(log_dst_dir, exist_ok=True)
##--------------------------------------------------------------------.
# Clean environment
del ds
# Log end processing
msg = f"{product} processing of {filename} has ended."
log_info(logger=logger, msg=msg, verbose=verbose)
success_flag = True
##--------------------------------------------------------------------.
# Otherwise log the error
except Exception as e:
error_type = str(type(e).__name__)
msg = f"{error_type}: {e}"
log_error(logger, msg, verbose=verbose)
# Close the file logger
close_logger(logger)
# Move logger file to correct partitioning directory
if success_flag and folder_partitioning != "" and logger_filepath is not None:
# Move logger file to correct partitioning directory
dst_filepath = os.path.join(log_dst_dir, os.path.basename(logger_filepath))
shutil.move(logger_filepath, dst_filepath)
logger_filepath = dst_filepath
# Return the logger file path
return logger_filepath
[docs]
def run_l1_station(
# Station arguments
data_source,
campaign_name,
station_name,
# Processing options
force: bool = False,
verbose: bool = True,
parallel: bool = True,
debugging_mode: bool = False,
# DISDRODB root directories
data_archive_dir: Optional[str] = None,
metadata_archive_dir: Optional[str] = None,
):
"""
Run the L1 processing of a specific DISDRODB station when invoked from the terminal.
The L1 routines just filter the raw drop spectrum and compute basic statistics.
The L1 routine expects as input L0C files where each file has a unique sample interval.
This function is intended to be called through the ``disdrodb_run_l1_station``
command-line interface.
Parameters
----------
data_source : str
The name of the institution (for campaigns spanning multiple countries) or
the name of the country (for campaigns or sensor networks within a single country).
Must be provided in UPPER CASE.
campaign_name : str
The name of the campaign. Must be provided in UPPER CASE.
station_name : str
The name of the station.
force : bool, optional
If ``True``, existing data in the destination directories will be overwritten.
If ``False`` (default), an error will be raised if data already exists in the destination directories.
verbose : bool, optional
If ``True`` (default), detailed processing information will be printed to the terminal.
If ``False``, less information will be displayed.
parallel : bool, optional
If ``True``, files will be processed in multiple processes simultaneously,
with each process using a single thread to avoid issues with the HDF/netCDF library.
If ``False`` (default), files will be processed sequentially in a single process,
and multi-threading will be automatically exploited to speed up I/O tasks.
debugging_mode : bool, optional
If ``True``, the amount of data processed will be reduced.
Only the first 3 files will be processed. The default value is ``False``.
data_archive_dir : str, optional
The base directory of DISDRODB, expected in the format ``<...>/DISDRODB``.
If not specified, the path specified in the DISDRODB active configuration will be used.
"""
# Define product
product = "L1"
# Define base directory
data_archive_dir = get_data_archive_dir(data_archive_dir)
# Retrieve DISDRODB Metadata Archive directory
metadata_archive_dir = get_metadata_archive_dir(metadata_archive_dir)
# Check valid data_source, campaign_name, and station_name
check_station_inputs(
metadata_archive_dir=metadata_archive_dir,
data_source=data_source,
campaign_name=campaign_name,
station_name=station_name,
)
# Define logs directory
logs_dir = create_logs_directory(
product=product,
data_archive_dir=data_archive_dir,
data_source=data_source,
campaign_name=campaign_name,
station_name=station_name,
)
# ------------------------------------------------------------------------.
# Start processing
if verbose:
t_i = time.time()
msg = f"{product} processing of station {station_name} has started."
log_info(logger=logger, msg=msg, verbose=verbose)
# ------------------------------------------------------------------------.
# Create directory structure
data_dir = create_product_directory(
data_archive_dir=data_archive_dir,
metadata_archive_dir=metadata_archive_dir,
data_source=data_source,
campaign_name=campaign_name,
station_name=station_name,
product=product,
force=force,
)
# -------------------------------------------------------------------------.
# List files to process
required_product = get_required_product(product)
flag_not_available_data = False
try:
filepaths = find_files(
data_archive_dir=data_archive_dir,
data_source=data_source,
campaign_name=campaign_name,
station_name=station_name,
product=required_product,
# Processing options
debugging_mode=debugging_mode,
)
except Exception as e:
print(str(e)) # Case where no file paths available
flag_not_available_data = True
# -------------------------------------------------------------------------.
# If no data available, print error message and return None
if flag_not_available_data:
msg = (
f"{product} processing of {data_source} {campaign_name} {station_name} "
+ f"has not been launched because of missing {required_product} data."
)
print(msg)
return
# -----------------------------------------------------------------.
# Generate L1 files
# - Loop over the L0 netCDF files and generate L1 files.
# - If parallel=True, it does that in parallel using dask.delayed
list_tasks = [
_generate_l1(
filepath=filepath,
data_dir=data_dir,
logs_dir=logs_dir,
campaign_name=campaign_name,
station_name=station_name,
# Processing options
force=force,
verbose=verbose,
parallel=parallel,
)
for filepath in filepaths
]
list_logs = dask.compute(*list_tasks) if parallel else list_tasks
# -----------------------------------------------------------------.
# Define L1 summary logs
create_product_logs(
product=product,
data_source=data_source,
campaign_name=campaign_name,
station_name=station_name,
data_archive_dir=data_archive_dir,
# Logs list
list_logs=list_logs,
)
# ---------------------------------------------------------------------.
# End L1 processing
if verbose:
timedelta_str = str(datetime.timedelta(seconds=round(time.time() - t_i)))
msg = f"{product} processing of station {station_name} completed in {timedelta_str}"
log_info(logger=logger, msg=msg, verbose=verbose)
####-------------------------------------------------------------------------------------------------------------------.