Set L0A and L0B lowercase in remaining occurences

disdrodb/l0/check_configs.py

@@ -342,7 +342,7 @@ def check_raw_array(sensor_name: str) -> None:
             raise ValueError(f"Wrong chunksizes for {key} in l0b_encodings.yml for sensor {sensor_name}.")
 
     # Get chunksizes in l0b_encoding.yml and check that if len > 1, has dimension_order key in raw_data_format
-    list_attributes_L0B_encodings = [
+    list_attributes_l0b_encodings = [
         i
         for i in l0b_encodings.keys()
         if isinstance(l0b_encodings.get(i).get("chunksizes"), list) and len(l0b_encodings.get(i).get("chunksizes")) > 1
@@ -351,7 +351,7 @@ def check_raw_array(sensor_name: str) -> None:
         i for i in raw_data_format.keys() if raw_data_format.get(i).get("dimension_order") is not None
     ]
 
-    if not sorted(list_attributes_L0B_encodings) == sorted(list_attributes_from_raw_data_format):
+    if not sorted(list_attributes_l0b_encodings) == sorted(list_attributes_from_raw_data_format):
         raise ValueError(f"Chunksizes in l0b_encodings and raw_data_format for sensor {sensor_name} does not match.")
 
 

disdrodb/l0/io.py

@@ -206,7 +206,7 @@ def get_dataframe_min_max_time(df: pd.DataFrame):
     return (starting_time, ending_time)
 
 
-def get_L0A_dir(processed_dir: str, station_name: str) -> str:
+def get_l0a_dir(processed_dir: str, station_name: str) -> str:
     """Define L0A directory.
 
     Parameters
@@ -225,7 +225,7 @@ def get_L0A_dir(processed_dir: str, station_name: str) -> str:
     return dir_path
 
 
-def get_L0B_dir(processed_dir: str, station_name: str) -> str:
+def get_l0b_dir(processed_dir: str, station_name: str) -> str:
     """Define L0B directory.
 
     Parameters
@@ -244,7 +244,7 @@ def get_L0B_dir(processed_dir: str, station_name: str) -> str:
     return dir_path
 
 
-def get_L0A_fname(df, processed_dir, station_name: str) -> str:
+def get_l0a_fname(df, processed_dir, station_name: str) -> str:
     """Define L0A file name.
 
     Parameters
@@ -274,7 +274,7 @@ def get_L0A_fname(df, processed_dir, station_name: str) -> str:
     return fname
 
 
-def get_L0B_fname(ds, processed_dir, station_name: str) -> str:
+def get_l0b_fname(ds, processed_dir, station_name: str) -> str:
     """Define L0B file name.
 
     Parameters
@@ -304,7 +304,7 @@ def get_L0B_fname(ds, processed_dir, station_name: str) -> str:
     return fname
 
 
-def get_L0A_fpath(df: pd.DataFrame, processed_dir: str, station_name: str) -> str:
+def get_l0a_fpath(df: pd.DataFrame, processed_dir: str, station_name: str) -> str:
     """Define L0A file path.
 
     Parameters
@@ -321,13 +321,13 @@ def get_L0A_fpath(df: pd.DataFrame, processed_dir: str, station_name: str) -> st
     str
         L0A file path.
     """
-    fname = get_L0A_fname(df=df, processed_dir=processed_dir, station_name=station_name)
-    dir_path = get_L0A_dir(processed_dir=processed_dir, station_name=station_name)
+    fname = get_l0a_fname(df=df, processed_dir=processed_dir, station_name=station_name)
+    dir_path = get_l0a_dir(processed_dir=processed_dir, station_name=station_name)
     fpath = os.path.join(dir_path, fname)
     return fpath
 
 
-def get_L0B_fpath(ds: xr.Dataset, processed_dir: str, station_name: str, l0b_concat=False) -> str:
+def get_l0b_fpath(ds: xr.Dataset, processed_dir: str, station_name: str, l0b_concat=False) -> str:
     """Define L0B file path.
 
     Parameters
@@ -347,10 +347,10 @@ def get_L0B_fpath(ds: xr.Dataset, processed_dir: str, station_name: str, l0b_con
     str
         L0B file path.
     """
-    dir_path = get_L0B_dir(processed_dir, station_name)
+    dir_path = get_l0b_dir(processed_dir, station_name)
     if l0b_concat:
         dir_path = os.path.dirname(dir_path)
-    fname = get_L0B_fname(ds, processed_dir, station_name)
+    fname = get_l0b_fname(ds, processed_dir, station_name)
     fpath = os.path.join(dir_path, fname)
     return fpath
 
@@ -489,8 +489,8 @@ def get_l0a_file_list(processed_dir, station_name, debugging_mode):
         List of L0A file paths.
 
     """
-    L0A_dir_path = get_L0A_dir(processed_dir, station_name)
-    filepaths = glob.glob(os.path.join(L0A_dir_path, "*.parquet"))
+    l0a_dir_path = get_l0a_dir(processed_dir, station_name)
+    filepaths = glob.glob(os.path.join(l0a_dir_path, "*.parquet"))
 
     n_files = len(filepaths)
 
@@ -501,7 +501,7 @@ def get_l0a_file_list(processed_dir, station_name, debugging_mode):
 
     # If no file available, raise error
     if n_files == 0:
-        msg = f"No L0A Apache Parquet file is available in {L0A_dir_path}. Run L0A processing first."
+        msg = f"No L0A Apache Parquet file is available in {l0a_dir_path}. Run L0A processing first."
         raise ValueError(msg)
 
     return filepaths
@@ -1036,7 +1036,7 @@ def create_directory_structure(processed_dir, product_level, station_name, force
 
 ####--------------------------------------------------------------------------.
 #### DISDRODB L0A Readers
-def _read_L0A(fpath: str, verbose: bool = False, debugging_mode: bool = False) -> pd.DataFrame:
+def _read_l0a(fpath: str, verbose: bool = False, debugging_mode: bool = False) -> pd.DataFrame:
     # Log
     msg = f" - Reading L0 Apache Parquet file at {fpath} started."
     log_info(logger, msg, verbose)
@@ -1050,7 +1050,7 @@ def _read_L0A(fpath: str, verbose: bool = False, debugging_mode: bool = False) -
     return df
 
 
-def read_L0A_dataframe(
+def read_l0a_dataframe(
     fpaths: Union[str, list],
     verbose: bool = False,
     debugging_mode: bool = False,
@@ -1093,7 +1093,7 @@ def read_L0A_dataframe(
         fpaths = fpaths[0:3]  # select first 3 fpaths
 
     # - Define the list of dataframe
-    list_df = [_read_L0A(fpath, verbose=verbose, debugging_mode=debugging_mode) for fpath in fpaths]
+    list_df = [_read_l0a(fpath, verbose=verbose, debugging_mode=debugging_mode) for fpath in fpaths]
     # - Concatenate dataframe
     df = concatenate_dataframe(list_df, verbose=verbose)
     # ---------------------------------------------------

disdrodb/l0/l0_processing.py

@@ -95,7 +95,7 @@ def _generate_l0a(
 ):
     """Generate L0A file from raw file."""
 
-    from disdrodb.l0.io import get_L0A_fpath
+    from disdrodb.l0.io import get_l0a_fpath
     from disdrodb.l0.l0a_processing import (
         process_raw_file,
         write_l0a,
@@ -145,7 +145,7 @@ def _generate_l0a(
 
         ##--------------------------------------------------------------------.
         #### - Write to Parquet
-        fpath = get_L0A_fpath(df=df, processed_dir=processed_dir, station_name=station_name)
+        fpath = get_l0a_fpath(df=df, processed_dir=processed_dir, station_name=station_name)
         write_l0a(df=df, fpath=fpath, force=force, verbose=verbose)
 
         ##--------------------------------------------------------------------.
@@ -178,7 +178,7 @@ def _generate_l0b(
     debugging_mode,
     parallel,
 ):
-    from disdrodb.l0.io import get_L0B_fpath, read_L0A_dataframe
+    from disdrodb.l0.io import get_l0b_fpath, read_l0a_dataframe
     from disdrodb.l0.l0b_processing import (
         create_l0b_from_l0a,
         write_l0b,
@@ -215,14 +215,14 @@ def _generate_l0b(
     ##------------------------------------------------------------------------.
     try:
         # Read L0A Apache Parquet file
-        df = read_L0A_dataframe(filepath, verbose=verbose, debugging_mode=debugging_mode)
+        df = read_l0a_dataframe(filepath, verbose=verbose, debugging_mode=debugging_mode)
         # -----------------------------------------------------------------.
         # Create xarray Dataset
         ds = create_l0b_from_l0a(df=df, attrs=attrs, verbose=verbose)
 
         # -----------------------------------------------------------------.
         # Write L0B netCDF4 dataset
-        fpath = get_L0B_fpath(ds, processed_dir, station_name)
+        fpath = get_l0b_fpath(ds, processed_dir, station_name)
         write_l0b(ds, fpath=fpath, force=force)
 
         ##--------------------------------------------------------------------.
@@ -256,7 +256,7 @@ def _generate_l0b_from_nc(
     verbose,
     parallel,
 ):
-    from disdrodb.l0.io import get_L0B_fpath
+    from disdrodb.l0.io import get_l0b_fpath
     from disdrodb.l0.l0b_nc_processing import process_raw_nc
     from disdrodb.l0.l0b_processing import write_l0b
 
@@ -298,7 +298,7 @@ def _generate_l0b_from_nc(
         )
         # -----------------------------------------------------------------.
         # Write L0B netCDF4 dataset
-        fpath = get_L0B_fpath(ds, processed_dir, station_name)
+        fpath = get_l0b_fpath(ds, processed_dir, station_name)
         write_l0b(ds, fpath=fpath, force=force)
 
         ##--------------------------------------------------------------------.

disdrodb/l0/l0b_nc_concat.py

@@ -19,7 +19,7 @@
 import logging
 import os
 
-from disdrodb.l0.io import get_L0B_dir, get_L0B_fpath
+from disdrodb.l0.io import get_l0b_dir, get_l0b_fpath
 from disdrodb.utils.logger import (
     close_logger,
     create_file_logger,
@@ -53,19 +53,19 @@ def _concatenate_netcdf_files(processed_dir, station_name, remove=False, verbose
 
     # -------------------------------------------------------------------------.
     # Retrieve L0B files
-    L0B_dir_path = get_L0B_dir(processed_dir, station_name)
-    file_list = sorted(glob.glob(os.path.join(L0B_dir_path, "*.nc")))
+    l0b_dir_path = get_l0b_dir(processed_dir, station_name)
+    file_list = sorted(glob.glob(os.path.join(l0b_dir_path, "*.nc")))
 
     # -------------------------------------------------------------------------.
     # Check there are at least two files
     n_files = len(file_list)
     if n_files == 0:
-        msg = f"No L0B file is available for concatenation in {L0B_dir_path}."
+        msg = f"No L0B file is available for concatenation in {l0b_dir_path}."
         log_error(logger=logger, msg=msg, verbose=False)
         raise ValueError(msg)
 
     if n_files == 1:
-        msg = f"Only a single file is available for concatenation in {L0B_dir_path}."
+        msg = f"Only a single file is available for concatenation in {l0b_dir_path}."
         log_warning(logger=logger, msg=msg, verbose=verbose)
         raise ValueError(msg)
 
@@ -75,7 +75,7 @@ def _concatenate_netcdf_files(processed_dir, station_name, remove=False, verbose
 
     # -------------------------------------------------------------------------.
     # Define the filepath of the concatenated L0B netCDF
-    single_nc_fpath = get_L0B_fpath(ds, processed_dir, station_name, l0b_concat=True)
+    single_nc_fpath = get_l0b_fpath(ds, processed_dir, station_name, l0b_concat=True)
     force = True  # TODO add as argument
     write_l0b(ds, fpath=single_nc_fpath, force=force)
 

disdrodb/l0/l0b_processing.py

@@ -148,7 +148,7 @@ def format_string_array(string: str, n_values: int) -> np.array:
         # Replace "-9.999" with 0
         values = np.char.replace(values, "-9.999", "0")
         # Cast values to float type
-        # --> Note: the disk encoding is specified in the L0B_encodings.yml
+        # --> Note: the disk encoding is specified in the l0b_encodings.yml
         values = values.astype(float)
     return values
 

disdrodb/l0/standards.py

@@ -798,7 +798,7 @@ def get_l0a_encodings_dict(sensor_name: str) -> dict:
         L0A encodings
     """
 
-    # - L0A_encodings currently specify only the dtype. This could be expanded in the future.
+    # - l0a_encodings.yml currently specify only the dtype. This could be expanded in the future.
     d = read_config_yml(sensor_name=sensor_name, filename="l0a_encodings.yml")
     return d
 

disdrodb/tests/test_l0/test_config_files.py

@@ -25,7 +25,7 @@ def check_list_length(cls, value):
             return value
 
 
-class L0B_encodings_2n_level(BaseModel):
+class l0b_encodings_2n_level(BaseModel):
     dtype: str
     zlib: bool
     complevel: int
@@ -306,13 +306,13 @@ def test_yaml_format_basic_config_files(yaml_file_path: str) -> None:
     assert is_string_list(list_of_fisrt_level_values)
 
 
-# Test the fotmat and content of the L0B_encodings.yml file
+# Test the fotmat and content of the l0b_encodings.yml file
 list_of_yaml_file_paths = list_files(CONFIG_FOLDER, "l0b_encodings.yml")
 
 
 @pytest.mark.parametrize("yaml_file_path", list_of_yaml_file_paths)
-def test_L0B_encodings_format(yaml_file_path: str) -> None:
-    """test the L0B_encodings.yml file format
+def test_l0b_encodings_format(yaml_file_path: str) -> None:
+    """test the l0b_encodings.yml file format
 
     Parameters
     ----------
@@ -330,4 +330,4 @@ def test_L0B_encodings_format(yaml_file_path: str) -> None:
 
     # check that the second level of the dictionary match the schema
     for value in data.values():
-        assert validate_schema_pytest(value, L0B_encodings_2n_level)
+        assert validate_schema_pytest(value, l0b_encodings_2n_level)

disdrodb/tests/test_l0/test_io.py

@@ -245,9 +245,9 @@ def test_get_dataset_min_max_time():
 
 
 @pytest.mark.parametrize("path_process_dir", [PATH_PROCESS_DIR_WINDOWS, PATH_PROCESS_DIR_LINUX])
-def test_get_L0A_dir(path_process_dir):
+def test_get_l0a_dir(path_process_dir):
     res = (
-        io.get_L0A_dir(path_process_dir, "STATION_NAME")
+        io.get_l0a_dir(path_process_dir, "STATION_NAME")
         .replace(path_process_dir, "")
         .replace("\\", "")
         .replace("/", "")
@@ -256,17 +256,17 @@ def test_get_L0A_dir(path_process_dir):
 
 
 @pytest.mark.parametrize("path_process_dir", [PATH_PROCESS_DIR_WINDOWS, PATH_PROCESS_DIR_LINUX])
-def test_get_L0B_dir(path_process_dir):
+def test_get_l0b_dir(path_process_dir):
     res = (
-        io.get_L0B_dir(path_process_dir, "STATION_NAME")
+        io.get_l0b_dir(path_process_dir, "STATION_NAME")
         .replace(path_process_dir, "")
         .replace("\\", "")
         .replace("/", "")
     )
     assert res == "L0BSTATION_NAME"
 
 
-def test_get_L0A_fpath():
+def test_get_l0a_fpath():
     """
     Test the naming and the path of the L0A file
     Note that this test needs "/pytest_files/test_folders_files_structure/DISDRODB/Processed/DATA_SOURCE/CAMPAIGN_NAME/
@@ -297,7 +297,7 @@ def test_get_L0A_fpath():
     df = pd.DataFrame({"time": pd.date_range(start=start_date, end=end_date)})
 
     # Test the function
-    res = io.get_L0A_fpath(df, path_campaign_name, station_name)
+    res = io.get_l0a_fpath(df, path_campaign_name, station_name)
 
     # Define expected results
     expected_name = (
@@ -307,7 +307,7 @@ def test_get_L0A_fpath():
     assert res == expected_path
 
 
-def test_get_L0B_fpath():
+def test_get_l0b_fpath():
     """
     Test the naming and the path of the L0B file
     Note that this test needs "/pytest_files/test_folders_files_structure/DISDRODB/Processed/DATA_SOURCE/CAMPAIGN_NAME/
@@ -344,7 +344,7 @@ def test_get_L0B_fpath():
     )
 
     # Test the function
-    res = io.get_L0B_fpath(ds, path_campaign_name, station_name)
+    res = io.get_l0b_fpath(ds, path_campaign_name, station_name)
 
     # Define expected results
     expected_name = f"L0B.{campaign_name.upper()}.{station_name}.s{start_date_str}.e{end_date_str}.{PRODUCT_VERSION}.nc"
@@ -610,7 +610,7 @@ def test_copy_station_metadata():
 ####--------------------------------------------------------------------------.
 
 
-def test__read_L0A():
+def test__read_l0a():
     # create dummy dataframe
     data = [{"a": "1", "b": "2"}, {"a": "2", "b": "2", "c": "3"}]
     df = pd.DataFrame(data)
@@ -624,12 +624,12 @@ def test__read_L0A():
     df.to_parquet(path_parquet_file, compression="gzip")
 
     # read written parquet file
-    df_written = io._read_L0A(path_parquet_file, False)
+    df_written = io._read_l0a(path_parquet_file, False)
 
     assert df.equals(df_written)
 
 
-def test_read_L0A_dataframe():
+def test_read_l0a_dataframe():
     list_of_parquet_file_paths = list()
 
     for i in [0, 1]:
@@ -659,7 +659,7 @@ def test_read_L0A_dataframe():
     df_concatenate = df_concatenate.sort_values(by="time")
 
     # read written parquet files
-    df_written = io.read_L0A_dataframe(list_of_parquet_file_paths, False)
+    df_written = io.read_l0a_dataframe(list_of_parquet_file_paths, False)
 
     # Create lists
     df_concatenate_list = df_concatenate.values.tolist()

disdrodb/tests/test_l0/test_l0a_processing.py

@@ -561,7 +561,7 @@ def test_write_l0a():
     l0a_processing.write_l0a(df, path_parquet_file, True, False)
 
     # Read parquet file
-    df_written = io.read_L0A_dataframe([path_parquet_file], False)
+    df_written = io.read_l0a_dataframe([path_parquet_file], False)
 
     # Check if parquet file are similar
     is_equal = df.equals(df_written)