Instruments#

This module implements UATAQ instruments as classes.

Each instrument class is a subclass of the Instrument abstract base class and implements methods for reading and parsing data files.

The Instrument class provides a common interface for all instrument classes and defines abstract methods that must be implemented by each subclass.

class lair.uataq.instruments.Instrument(SID: str, name: str, loggers: dict, config: dict)[source]#

Bases: object

Abstract base class for instrument objects.

Attributes

model	(str) Model of the instrument.
SID	(str) Site ID where the instrument is installed.
name	(str) Name of the instrument.
groups	(list[str]) Research groups that operate the instrument.
loggers	(set[str]) Loggers used by the research groups to record data.
config	(dict) Configuration settings for the instrument.

Methods

get_files(group: str, lvl: str) -> list[str]	Get list of file paths for a given level.
read_data(group: str, lvl: str, time_range: TimeRange, num_processes: int, file_pattern: str) -> pd.DataFrame	Read and parse group data files for the given level and time range using multiple processes.

__init__(SID: str, name: str, loggers: dict, config: dict)[source]#

Initialize the Instrument object.

Parameters:

SIDstr: Site ID where the instrument is installed.
namestr: Name of the instrument.
loggersdict: Dictionary of loggers used by different research groups.
configdict: Configuration settings for the instrument.

get_highest_lvl(group: str) → str[source]#

Get the highest data level for the instrument.

Parameters:

groupstr: The research group whose data to retrieve.

Returns:

str: The highest data level.

get_files(group: str, lvl: str) → list[str][source]#

Get list of file paths for a given level.

Parameters:

groupstr: The research group whose data to retrieve.
lvlstr: The level of the data to retrieve.

Returns:

list[str]: A list of file paths.

get_datafiles(group: str, lvl: str, time_range: TimeRange, pattern: str | None = None) → list[DataFile][source]#

Get data files for the given level and time range from the groupspace.

Parameters:

groupstr: The research group whose data to retrieve.
lvlstr: The level of the data to retrieve.
time_rangeTimeRange: The time range of the data to retrieve.
patternstr: A string pattern to filter the file paths.

Returns:

list[DataFile]: A list of data files.

standardize_data(group: str, data: DataFrame) → DataFrame[source]#

Manipulate the data to a standard format between research groups, renaming columns, converting units, mapping values, etc. as needed.

Parameters:

groupstr: The research group whose data to standardize.
datapandas.DataFrame: The data to standardize.

Returns:

pandas.DataFrame: The standardized data.

Read and parse data files for the given level and time range, using multiple processes if specified.

Parameters:

groupstr: The research group whose data to read.
lvlstr: The level of the data to read.
time_rangestr | list[Union[str, dt.datetime, None]] | tuple[Union[str, dt.datetime, None], Union[str, dt.datetime, None]] | slice | None: The time range to read data. Default is None which reads all available data.
num_processesint | ‘max’: The number of processes to use for parallelization.
file_patternstr: A string pattern to filter the file paths.

Returns:

pandas.DataFrame: A concatenated DataFrame containing the parsed data from files.

lair.uataq.instruments.configure_instrument(SID: str, name: str, config: dict, loggers: dict | None = None) → Instrument[source]#

Configure an instrument object based on the given configuration settings.

Parameters:

SIDstr: Site ID where the instrument is installed.
namestr: Name of the instrument.
configdict: Configuration settings for the instrument.
loggersdict, optional: Dictionary of loggers used by different research groups.

Returns:

Instrument: An instrument object configured with the given settings.

Raises:

ValueError: If the instrument model is not found in the catalog.
ValueError: If no loggers are found for the instrument at the site.

class lair.uataq.instruments.InstrumentEnsemble(SID: str, configs: dict, loggers: dict | None = None)[source]#

Bases: object

Container for an ensemble of instruments at a site.

Attributes

SID	(str) Site ID of the ensemble.
configs	(dict[str, dict]) Dictionary of configuration settings for each instrument.
names	(list[str]) List of instrument names in the ensemble.
loggers	(set[str]) Set of loggers used by the research groups.
groups	(set[str]) Set of research groups that operate the instruments.
pollutants	(set[str]) Set of pollutants measured by the instruments.

__init__(SID: str, configs: dict, loggers: dict | None = None)[source]#

Initialize the InstrumentEnsemble object.

Parameters:

SIDstr: Site ID of the ensemble.
configsdict[instrument, config]: Dictionary of configuration settings for each instrument.
loggersdict[group, logger], optional: Dictionary of loggers used by different research groups.

class lair.uataq.instruments.SensorMixin[source]#

Bases: object

Mixin for instrument objects that measure a pollutant.

Attributes:: pollutants (tuple): Tuple of pollutants measured by the instrument.

class lair.uataq.instruments.BB_205(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.BB_405(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.CR1000(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument

class lair.uataq.instruments.GPS(SID: str, name: str, loggers: dict, config: dict)[source]#

Bases: Instrument

Read and parse data files for the given level and time range, using multiple processes if specified.

Parameters:

groupstr: The research group whose data to read.
lvlstr: The level of the data to read.
time_rangestr | list[Union[str, dt.datetime, None]] | tuple[Union[str, dt.datetime, None], Union[str, dt.datetime, None]] | slice | None: The time range to read data. Default is None which reads all available data.
num_processesint | ‘max’: The number of processes to use for parallelization.
file_patternstr: A string pattern to filter the file paths.

Returns:

pandas.DataFrame: A concatenated DataFrame containing the parsed data from files.

class lair.uataq.instruments.LGR_NO2(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.LGR_UGGA(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.Licor_6262(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.Licor_7000(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Licor_6262

class lair.uataq.instruments.Magee_AE33(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.MetOne_ES405(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.MetOne_ES642(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.Teledyne_T200(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.Teledyne_T300(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.Teledyne_T400(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.Teledyne_T500u(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

class lair.uataq.instruments.Teom_1400ab(SID: str, name: str, loggers: dict, config: dict)[source]#: Bases: Instrument, SensorMixin

lair.uataq.instruments.catalog: dict[str, Type[Instrument]] = {'2b_205': <class 'lair.uataq.instruments.BB_205'>, '2b_405': <class 'lair.uataq.instruments.BB_405'>, 'cr1000': <class 'lair.uataq.instruments.CR1000'>, 'gps': <class 'lair.uataq.instruments.GPS'>, 'lgr_no2': <class 'lair.uataq.instruments.LGR_NO2'>, 'lgr_ugga': <class 'lair.uataq.instruments.LGR_UGGA'>, 'licor_6262': <class 'lair.uataq.instruments.Licor_6262'>, 'licor_7000': <class 'lair.uataq.instruments.Licor_7000'>, 'magee_ae33': <class 'lair.uataq.instruments.Magee_AE33'>, 'metone_es405': <class 'lair.uataq.instruments.MetOne_ES405'>, 'metone_es642': <class 'lair.uataq.instruments.MetOne_ES642'>, 'teledyne_t200': <class 'lair.uataq.instruments.Teledyne_T200'>, 'teledyne_t300': <class 'lair.uataq.instruments.Teledyne_T300'>, 'teledyne_t400': <class 'lair.uataq.instruments.Teledyne_T400'>, 'teledyne_t500u': <class 'lair.uataq.instruments.Teledyne_T500u'>, 'teom_1400ab': <class 'lair.uataq.instruments.Teom_1400ab'>}#: Instrument catalog