Fix docstring bugs (JCSDA-internal#151)

* fix bugs in transforms * data api * one line miss from last PR * utils * pycodestyle
EdwardSafford-NOAA · Aug 18, 2023 · 315d954 · 315d954
1 parent 2fd6d19
commit 315d954
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Showing 18 changed files with 130 additions and 101 deletions.
diff --git a/src/eva/data/cubed_sphere_restart.py b/src/eva/data/cubed_sphere_restart.py
@@ -28,7 +28,7 @@ def read_fms_tiles(files, variable, logger):
     Args:
         files (list): List of netCDF file paths.
         variable (str): Name of the variable to extract.
-        logger: Logger object for logging messages.
+        logger (Logger): Logger object for logging messages.
 
     Returns:
         np.ndarray: Combined variable array from input files.
@@ -77,7 +77,7 @@ def execute(self, dataset_config, data_collections, timing):
 
         Args:
             dataset_config (dict): Configuration dictionary for the dataset.
-            data_collections: Object for managing data collections.
+            data_collections (DataCollections): Object for managing data collections.
             timing: Timing object for tracking execution time.
         """
 

diff --git a/src/eva/data/gsi_obs_space.py b/src/eva/data/gsi_obs_space.py
@@ -80,7 +80,7 @@ def subset_channels(ds, channels, logger, add_channels_variable=False):
     Args:
         ds (Dataset): The xarray Dataset to subset.
         channels (list): List of channel numbers to keep.
-        logger: Logger instance for logging messages.
+        logger (Logger): Logger instance for logging messages.
         add_channels_variable (bool, optional): Whether to add 'channelNumber' variable. Default is
         False.
     """

diff --git a/src/eva/data/ioda_obs_space.py b/src/eva/data/ioda_obs_space.py
@@ -44,8 +44,10 @@ def subset_channels(ds, channels):
           the dataset, the function will perform the subset operation.
 
     Example:
-        # Subset the dataset 'data' to include only channels 1, 5 and 10:
-        subset_ds = subset_channels(data, [1, 5, 10])
+        ::
+
+                # Subset the dataset 'data' to include only channels 1, 5 and 10:
+                subset_ds = subset_channels(data, [1, 5, 10])
     """
 
     if 'Channel' in list(ds.dims):
@@ -97,14 +99,16 @@ class IodaObsSpace(EvaDatasetBase):
         - (Additional notes, if applicable)
 
     Example:
-        # Instantiate the class
-        ioda_instance = IodaObsSpace()
+        ::
+
+                # Instantiate the class
+                ioda_instance = IodaObsSpace()
 
-        # Execute data collection processing using IODA observation space
-        ioda_instance.execute(dataset_config, data_collections, timing)
+                # Execute data collection processing using IODA observation space
+                ioda_instance.execute(dataset_config, data_collections, timing)
 
-        # Generate a default configuration dictionary for IODA observation space
-        default_config = ioda_instance.generate_default_config(filenames, collection_name)
+                # Generate a default configuration dictionary for IODA observation space
+                default_config = ioda_instance.generate_default_config(filenames, collection_name)
     """
 
     def execute(self, dataset_config, data_collections, timing):
@@ -127,11 +131,13 @@ def execute(self, dataset_config, data_collections, timing):
             - This method operates on instance-specific attributes.
 
         Example:
-            # Instantiate the class
-            ioda_instance = IodaObsSpace()
+            ::
 
-            # Execute data collection processing using IODA observation space
-            ioda_instance.execute(dataset_config, data_collections, timing)
+                    # Instantiate the class
+                    ioda_instance = IodaObsSpace()
+
+                    # Execute data collection processing using IODA observation space
+                    ioda_instance.execute(dataset_config, data_collections, timing)
         """
 
         # Get channels for radiances
@@ -293,11 +299,14 @@ def generate_default_config(self, filenames, collection_name):
             - This method operates on instance-specific attributes.
 
         Example:
-            # Instantiate the class
-            ioda_instance = IodaObsSpace()
+            ::
+
+                    # Instantiate the class
+                    ioda_instance = IodaObsSpace()
 
-            # Generate a default configuration dictionary for IODA observation space
-            default_config = ioda_instance.generate_default_config(filenames, collection_name)
+                    # Generate a default configuration dictionary for IODA observation space
+                    default_config = ioda_instance.generate_default_config(filenames,
+                                                                           collection_name)
         """
 
         eva_dict = {'filenames': filenames,

diff --git a/src/eva/data/jedi_log.py b/src/eva/data/jedi_log.py
@@ -63,8 +63,8 @@ def execute(self, dataset_config, data_collections, timing):
 
         Args:
             dataset_config (dict): Configuration dictionary for the dataset.
-            data_collections: Object for managing data collections.
-            timing: Timing object for tracking execution time.
+            data_collections (DataCollections): Object for managing data collections.
+            timing (Timing): Timing object for tracking execution time.
         """
 
         # Get name of the log file to parse

diff --git a/src/eva/data/lat_lon.py b/src/eva/data/lat_lon.py
@@ -19,8 +19,8 @@ def execute(self, dataset_config, data_collections, timing):
 
         Args:
             dataset_config (dict): Configuration dictionary for the dataset.
-            data_collections: Object for managing data collections.
-            timing: Timing object for tracking execution time.
+            data_collections (DataCollections): Object for managing data collections.
+            timing (Timing): Timing object for tracking execution time.
         """
 
         # Filename to be read into this collection

diff --git a/src/eva/data/mon_data_space.py b/src/eva/data/mon_data_space.py
@@ -37,8 +37,8 @@ def execute(self, dataset_config, data_collections, timing):
 
         Args:
             dataset_config (dict): Configuration dictionary for the dataset.
-            data_collections: Object for managing data collections.
-            timing: Timing object for tracking execution time.
+            data_collections (DataCollections): Object for managing data collections.
+            timing (Timing): Timing object for tracking execution time.
         """
 
         # Set the collection name

diff --git a/src/eva/data/soca_restart.py b/src/eva/data/soca_restart.py
@@ -144,7 +144,7 @@ def read_soca(file, variable, logger):
     Args:
         file (str): Path to the SOCA data file.
         variable (str): Name of the variable to read.
-        logger: Logger for logging messages.
+        logger (Logger): Logger for logging messages.
 
     Returns:
         tuple: A tuple containing dimensions (list) and data (numpy.ndarray) for the specified

diff --git a/src/eva/plotting/emcpy/plot_tools/figure_driver.py b/src/eva/plotting/emcpy/plot_tools/figure_driver.py
@@ -30,7 +30,7 @@ def figure_driver(config, data_collections, timing, logger):
         config (dict): A dictionary containing the configuration for generating figures.
         data_collections (DataCollections): An instance of the DataCollections class containing
         input data.
-        timing: A timing instance to measure the execution time.
+        timing (Timing): A timing instance to measure the execution time.
         logger (Logger): An instance of the logger for logging messages.
 
     This function generates and saves multiple figures based on the provided configuration. It

diff --git a/src/eva/transforms/accept_where.py b/src/eva/transforms/accept_where.py
@@ -26,7 +26,7 @@ def accept_where(config, data_collections):
     Args:
         config (dict): A configuration dictionary containing transformation parameters.
         data_collections (DataCollections): An instance of the DataCollections class containing
-                                            input data.
+        input data.
 
     Returns:
         None
@@ -40,15 +40,17 @@ def accept_where(config, data_collections):
     The resulting filtered variables are added to the data collections.
 
     Example:
-        config = {
-            'collections': [...],
-            'groups': [...],
-            'variables': [...],
-            'new name': 'filtered_variable',
-            'starting field': 'original_variable',
-            'where': ['${collection}::${group}::${variable} >= 0.0']
-        }
-        accept_where(config, data_collections)
+        ::
+
+                config = {
+                    'collections': [...],
+                    'groups': [...],
+                    'variables': [...],
+                    'new name': 'filtered_variable',
+                    'starting field': 'original_variable',
+                    'where': ['${collection}::${group}::${variable} >= 0.0']
+                }
+                accept_where(config, data_collections)
     """
 
     # Create a logger
@@ -126,13 +128,14 @@ def generate_accept_where_config(new_name, starting_field, where, collection, va
     'for' dictionary to apply the transformation to the specified variables.
 
     Example:
-        new_name = 'filtered_variable'
-        starting_field = 'original_variable'
-        where = ['group1 >= 0', 'group2 < 10']
-        collection = 'my_collection'
-        var_list = ['variable1', 'variable2']
-        config = generate_accept_where_config(new_name, starting_field, where, collection,
-                                              var_list)
+        ::
+                new_name = 'filtered_variable'
+                starting_field = 'original_variable'
+                where = ['group1 >= 0', 'group2 < 10']
+                collection = 'my_collection'
+                var_list = ['variable1', 'variable2']
+                config = generate_accept_where_config(new_name, starting_field, where,
+                                                      collection, var_list)
     """
 
     # Update new_name

diff --git a/src/eva/transforms/arithmetic.py b/src/eva/transforms/arithmetic.py
@@ -40,7 +40,9 @@ def isfloat(a_string):
     floating-point number.
 
     Example:
-        result = isfloat("3.14")
+        ::
+
+                result = isfloat("3.14")
     """
 
     try:
@@ -60,7 +62,7 @@ def arithmetic(config, data_collections):
     Args:
         config (dict): A configuration dictionary containing transformation parameters.
         data_collections (DataCollections): An instance of the DataCollections class containing
-                                            input data.
+        input data.
 
     Returns:
         None
@@ -71,14 +73,17 @@ def arithmetic(config, data_collections):
     resulting variables are added to the data collections.
 
     Example:
-        config = {
-            'collections': [...],
-            'groups': [...],
-            'variables': [...],
-            'new name': 'result_variable',
-            'equals': '(${collection}::${group}::${var1} + ${collection}::${group}::${var2}) / 2'
-        }
-        arithmetic(config, data_collections)
+        ::
+
+                config = {
+                    'collections': [...],
+                    'groups': [...],
+                    'variables': [...],
+                    'new name': 'result_variable',
+                    'equals': '(${collection}::${group}::${var1} + ${collection}::${group}::${var2})
+                               / 2'
+                }
+                arithmetic(config, data_collections)
     """
 
     # Create a logger
@@ -154,11 +159,13 @@ def generate_arithmetic_config(new_name, expression, collection, var_list):
     the transformation to the specified variables.
 
     Example:
-        new_name = 'result_variable'
-        expression = '(${group1} + ${group2}) / 2'
-        collection = 'my_collection'
-        var_list = ['variable1', 'variable2']
-        config = generate_arithmetic_config(new_name, expression, collection, var_list)
+        ::
+
+                new_name = 'result_variable'
+                expression = '(${group1} + ${group2}) / 2'
+                collection = 'my_collection'
+                var_list = ['variable1', 'variable2']
+                config = generate_arithmetic_config(new_name, expression, collection, var_list)
     """
 
     # Update new_name

diff --git a/src/eva/transforms/channel_stats.py b/src/eva/transforms/channel_stats.py
@@ -43,15 +43,17 @@ def channel_stats(config, data_collections):
     configuration. The resulting variables are added to the data collections.
 
     Example:
-        config = {
-            'collections': [...],
-            'groups': [...],
-            'variables': [...],
-            'variable_name': 'data_variable',
-            'statistic list': ['Mean', 'Std', 'Count'],
-            'statistic_dimension': 'Location'
-        }
-        channel_stats(config, data_collections)
+        ::
+
+                config = {
+                    'collections': [...],
+                    'groups': [...],
+                    'variables': [...],
+                    'variable_name': 'data_variable',
+                    'statistic list': ['Mean', 'Std', 'Count'],
+                    'statistic_dimension': 'Location'
+                }
+                channel_stats(config, data_collections)
     """
 
     # Create a logger

diff --git a/src/eva/transforms/select_time.py b/src/eva/transforms/select_time.py
@@ -32,7 +32,7 @@ def select_time(config, data_collections):
     Args:
         config (dict): A configuration dictionary containing transformation parameters.
         data_collections (DataCollections): An instance of the DataCollections class containing
-                                            input data.
+        input data.
 
     Returns:
         None
@@ -44,18 +44,20 @@ def select_time(config, data_collections):
     for a single time point. The resulting processed variables are added to the data collections.
 
     Example:
-        config = {
-            'collections': [...],
-            'groups': [...],
-            'variables': [...],
-            'new name': 'time_selected_variable',
-            'starting field': 'original_variable',
-            'cycle': 'YYYYMMDDHH',
-            # OR
-            'start cycle': 'YYYYMMDDHH',
-            'end cycle': 'YYYYMMDDHH'
-        }
-        select_time(config, data_collections)
+        ::
+
+                config = {
+                    'collections': [...],
+                    'groups': [...],
+                    'variables': [...],
+                    'new name': 'time_selected_variable',
+                    'starting field': 'original_variable',
+                    'cycle': 'YYYYMMDDHH',
+                    # OR
+                    'start cycle': 'YYYYMMDDHH',
+                    'end cycle': 'YYYYMMDDHH'
+                }
+                select_time(config, data_collections)
     """
 
     # Create a logger

diff --git a/src/eva/transforms/transform_driver.py b/src/eva/transforms/transform_driver.py
@@ -24,7 +24,7 @@ def transform_driver(config, data_collections, timing, logger):
     Args:
         config (dict): A configuration dictionary containing transformation parameters.
         data_collections (DataCollections): An instance of the DataCollections class containing
-                                            input data.
+        input data.
         timing (Timing): An instance of the Timing class for tracking execution times.
         logger (Logger): An instance of the logger for logging messages.