WBTSdata API

WBTSdata.load_vel_files.create_Dataset(vel_dir, config=None)

Create a xr.Dataset from the velocity data files in the directory vel_dir.

Parameters:

• vel_dir (str) – The directory containing the velocity data files.

• config (dict(optional)) – The configuration dictionary.

Returns:

A xr.Dataset containing the velocity data.

Return type:

xr.Dataset

WBTSdata.load_vel_files.create_complete_Dataset(directory_list)

Create a xr.Dataset from the velocity data files in the list of directories directory_list.

Parameters:

directory_list (list) – A list of directories containing the velocity data files.

Returns:

A xr.Dataset containing the velocity data.

Return type:

xr.Dataset

WBTSdata.load_vel_files.create_coordinates(vel_dir)

Create a list of coordinates from the velocity data files in the directory vel_dir. Returns three lists of coordinates: avg_coordinates, start_coordinates, end_coordinates.

Parameters:

vel_dir (str) – The directory containing the velocity data files.

Returns:

A list of coordinates for the average, start, and end of the cast.

Return type:

list

WBTSdata.load_vel_files.load_vel_from_file(vel_dir)

Load the velocity data from the files in the directory vel_dir. Returns a list of pandas DataFrames.

Parameters:

vel_dir (str) – The directory containing the velocity data files.

Returns:

A list of pandas DataFrames containing the velocity data.

Return type:

list

WBTSdata.merge_datasets.create_CTD_Dataset_with_ADCPtimes(cal_dir, config=None)

Create a CTD dataset with the corresponding ADCP times.

Parameters:

• cal_dir (str) – The path to the directory containing the CTD calibration data

• config (dict(optional)) – The configuration dictionary

Returns:

ds – The dataset containing the CTD data with the corresponding ADCP times

Return type:

xarray.Dataset

WBTSdata.merge_datasets.create_coordinates_with_ADCPtimes(cal_dir, input_dir=None)

Create a list of coordinates for the CTD data with the corresponding ADCP times

Parameters:

• cal_dir (str) – The path to the directory containing the CTD calibration data

• input_dir (str) – The path to the directory containing the CTD data

Returns:

coordinates –

A list of lists, each list contains the following elements:

• Cast number

• Latitude

• Longitude

• Date and time of the ADCP data

• Time flag

Return type:

list

WBTSdata.merge_datasets.dir_list_ADCP(input_dir)

create a list with all the directories that contain the ADCP data

Parameters:

input_dir (str) – The path to the directory containing the ADCP data

Returns:

dir_list_ADCP – A list of strings, each string is a path to a directory containing ADCP data

Return type:

list

WBTSdata.merge_datasets.dir_list_CTD(input_dir)

create a list with all the directories that contain the CTD data

Parameters:

input_dir (str) – The path to the directory containing the CTD data

Returns:

dir_list_CTD – A list of strings, each string is a path to a directory containing CTD data

Return type:

list

WBTSdata.merge_datasets.merge_datasets(cal_dir, vel_dir, config=None)

Merge the CTD and ADCP datasets.

Parameters:

• cal_dir (str) – The path to the directory containing the CTD calibration data

• vel_dir (str) – The path to the directory containing the ADCP data

Returns:

ds_merge – The dataset containing the merged CTD and ADCP data.

Return type:

xarray.Dataset

WBTSdata.merge_datasets.merge_years(merge_dir)

Merge the datasets of different years into one dataset

Parameters:

merge_dir (str) – The path to the directory containing the merged datasets of different years

Returns:

ds_all – The dataset containing the merged data of all years

Return type:

xarray.Dataset

WBTSdata.convert.add_attributes(ds, config)

Add attributes to the variables in a dataset.

Parameters:

• (xarray.Dataset) (ds)

• (dict) (attr_dict)

Returns:

xarray.Dataset

Return type:

The dataset with added attributes.

WBTSdata.convert.assign_variable_attributes(ds, vocab_attrs={'CAST_NUMBER': {'long_name': 'Cast index', 'units': '1'}, 'DATETIME': {'URI': 'https://vocab.nerc.ac.uk/collection/P02/current/AYMD/', 'long_name': 'time of measurement', 'observation_type': 'measured', 'standard_name': 'time'}, 'DEPTH': {'accuracy': 1, 'comment': 'from science pressure and interpolated', 'long_name': 'glider depth', 'observation_type': 'calculated', 'platform': 'platform', 'positive': 'down', 'precision': 2, 'reference_datum': 'surface', 'resolution': 0.02, 'sensor': 'sensor_ctd', 'source': 'pressure', 'standard_name': 'depth', 'units': 'm', 'valid_max': 2000, 'valid_min': 0}, 'DOXY': {'URI': 'https://vocab.nerc.ac.uk/collection/P02/current/DOXY/', 'long_name': 'oxygen concentration', 'observation_type': 'calculated', 'standard_name': 'mole_concentration_of_dissolved_molecular_oxygen_in_sea_water', 'units': 'umol kg-1', 'valid_max': 425, 'valid_min': 0}, 'DYN_HEIGHT': {'URI': '', 'long_name': 'Dynamic height', 'observation_type': 'calculated', 'standard_name': 'sea_surface_height_above_geoid', 'units': 'cm', 'valid_max': 2, 'valid_min': -2}, 'ERROR_VELOCITY': {'URI': '', 'long_name': 'Error in water velocity', 'observation_type': 'measured', 'standard_name': 'error_sea_water_velocity', 'units': 'm s-1', 'valid_max': 2, 'valid_min': 0}, 'GA': {'long_name': '', 'observation_type': '', 'standard_name': '', 'units': 'gamma'}, 'GC_STRING': {'long_name': 'GC string', 'units': '1'}, 'LATITUDE': {'URI': 'https://vocab.nerc.ac.uk/collection/OG1/current/LAT/', 'axis': 'Y', 'coordinate_reference_frame': 'urn:ogc:crs:EPSG::4326', 'long_name': 'Latitude north', 'observation_type': 'measured', 'platform': 'platform', 'reference': 'WGS84', 'standard_name': 'latitude', 'units': 'degrees_north', 'valid_max': 90, 'valid_min': -90}, 'LONGITUDE': {'URI': 'https://vocab.nerc.ac.uk/collection/OG1/current/LON/', 'axis': 'X', 'coordinate_reference_frame': 'urn:ogc:crs:EPSG::4326', 'long_name': 'Longitude east', 'observation_type': 'measured', 'platform': 'platform', 'reference': 'WGS84', 'standard_name': 'longitude', 'units': 'degrees_east', 'valid_max': 180, 'valid_min': -180}, 'PRES': {'URI': 'https://vocab.nerc.ac.uk/collection/OG1/current/PRES', 'comment': 'ctd pressure sensor', 'long_name': 'Pressure (spatial coordinate) exerted by the water body by profiling pressure sensor and correction to read zero at sea level', 'observation_type': 'measured', 'positive': 'down', 'reference_datum': 'sea-surface', 'sensor': 'sensor_ctd', 'standard_name': 'sea_water_pressure', 'units': 'dbar', 'valid_max': 2000, 'valid_min': 0}, 'PSAL': {'URI': 'https://vocab.nerc.ac.uk/collection/OG1/current/PSAL/', 'comment': 'Practical salinity of the water body by CTD and computation using UNESCO 1983 algorithm', 'long_name': 'water salinity', 'observation_type': 'calculated', 'sensor': 'sensor_ctd', 'sources': 'CNDC, TEMP, PRES', 'standard_name': 'sea_water_practical_salinity', 'units': '1e-3', 'valid_max': 40, 'valid_min': 0}, 'TEMP': {'URI': 'https://vocab.nerc.ac.uk/collection/OG1/current/TEMP/', 'long_name': 'Temperature of the water body by CTD ', 'observation_type': 'measured', 'standard_name': 'sea_water_temperature', 'units': 'Celsius', 'valid_max': 42, 'valid_min': -5}, 'THETA': {'URI': 'https://vocab.nerc.ac.uk/collection/OG1/current/THETA/', 'long_name': 'Potential temperature of the water body by computation using UNESCO 1983 algorithm.', 'observation_type': 'calculated', 'sources': 'salinity temperature pressure', 'standard_name': 'sea_water_potential_temperature', 'units': 'Celsius', 'valid_max': 42, 'valid_min': -5}, 'TIME_FLAG': {'Value 0': 'Start time of the cast', 'Value 1': 'Start time of cast needs to be checked in Cruise report', 'Value 2': 'End time of cast', 'long_name': 'Time flag', 'units': '1'}, 'U_WATER_VELOCITY': {'URI': '', 'long_name': 'Eastward water velocity', 'observation_type': 'measured', 'standard_name': 'eastward_sea_water_velocity', 'units': 'm s-1', 'valid_max': 3, 'valid_min': -3}, 'V_WATER_VELOCITY': {'URI': '', 'long_name': 'Northward water velocity', 'observation_type': 'measured', 'standard_name': 'northward_sea_water_velocity', 'units': 'm s-1', 'valid_max': 3, 'valid_min': -3}}, unit_format={'cm_per_s': 'cm s-1', 'dbars': 'dbar', 'deg c': 'Celcius', 'dyn. cm': 'cm', 'gamma': 'gamma', 'meters': 'm', 'psu': 'psu', 'umol/kg': 'umol kg-1'})

Assigns variable attributes to a dataset where they are missing and reformats units according to the provided unit_format. Attributes that already exist in the dataset are not changed, except for unit reformatting.

Parameters:

• (xarray.Dataset) (ds)

• (dict) (unit_str_format)

• (dict)

Returns:

• xarray.Dataset (The dataset with updated attributes.)

• attr_warnings (set) (A set containing warning messages for attribute mismatches.)

WBTSdata.convert.attr_cruise(ds, config)

Generate a dictionary of attributes for a cruise based on the given dataset and configuration.

Parameters:

• ds (xarray.Dataset) – The dataset containing the cruise data.

• config (dict) – The configuration dictionary.

Returns:

A dictionary containing the cruise attributes.

Return type:

dict

WBTSdata.convert.process_dataset(ds, config)

Process a dataset by renaming dimensions and variables, assigning attributes, and adding attributes.

Parameters:

• (xarray.Dataset) (ds)

• (dict) (config)

Returns:

xarray.Dataset

Return type:

The processed dataset.

WBTSdata.convert.rename_dimensions(ds, rename_dict={})

Renames dimensions in the dataset based on the provided dictionary for OG1.

Parameters:

• (xarray.Dataset) (ds)

• (dict) (rename_dict)

Returns:

xarray.Dataset

Return type:

The dataset with renamed dimensions.

WBTSdata.convert.rename_variables(ds, rename_dict={'CAST': 'CAST_NUMBER', 'error_velocity': 'ERROR_VELOCITY', 'ga': 'GA', 'gc_string': 'GC_STRING', 'ht': 'DYN_HEIGHT', 'latitude': 'LATITUDE', 'longitude': 'LONGITUDE', 'ox': 'DOXY', 'pr': 'PRES', 'sa': 'PSAL', 'te': 'TEMP', 'th': 'THETA', 'u_water_velocity_component': 'U_WATER_VELOCITY', 'v_water_velocity_component': 'V_WATER_VELOCITY', 'z_depth': 'DEPTH'})

Renames variables in the dataset based on the provided dictionary for OG1.

Parameters:

• (xarray.Dataset) (ds)

• (dict) (rename_dict)

Returns:

xarray.Dataset

Return type:

The dataset with renamed variables.

WBTSdata.tools.convert_units(ds, preferred_units=['m s-1', 'dbar', 'Celsius', 'psu', 'umol kg-1', 'gamma', 'm'], unit_conversion={'cm': {'factor': 0.01, 'units_name': 'm'}, 'cm s-1': {'factor': 0.01, 'units_name': 'm s-1'}, 'cm/s': {'factor': 0.01, 'units_name': 'm/s'}, 'cm_per_s': {'factor': 0.01, 'units_name': 'm s-1'}, 'dyn. cm': {'factor': 1, 'units_name': 'cm'}, 'meters': {'factor': 1, 'units_name': 'm'}})

Convert the units of variables in an xarray Dataset to preferred units. This is useful, for instance, to convert cm/s to m/s.

Parameters:

• (xarray.Dataset) (ds)

• (list) (preferred_units)

• (dict) (unit_conversion)

• string (Each key is a unit) –

  • ‘factor’: The factor to multiply the variable by to convert it.

  • ’units_name’: The new unit name after conversion.

• with (and each value is a dictionary) –

  • ‘factor’: The factor to multiply the variable by to convert it.

  • ’units_name’: The new unit name after conversion.

Returns:

xarray.Dataset

Return type:

The dataset with converted units.

WBTSdata.tools.get_config()

Get the configuration settings from a YAML file.

Returns:

dict

Return type:

The configuration settings.

WBTSdata.plotters.plot_cast_over_time(ds_all)

Plot the cast over time for the given dataset. The dataset should contain the following variables: - DATETIME: The datetime of the cast - LONGITUDE: The longitude of the cast - GC_STRING: The gc_string of the cast

Parameters:

ds_all (xarray.Dataset) – The dataset containing the data to plot.

Returns:

fig, ax – The figure and axes of the plot.

Return type:

matplotlib.figure.Figure, matplotlib.axes.Axes