bsrn.dataset.BSRNDataset

class bsrn.dataset.BSRNDataset(*, station_code, year, month, lr0100, lr0300=None, lr4000=None, metadata_lrs=<factory>, station_name=None, lat=None, lon=None, elev=None, resolution=None)

One monthly BSRN dataset: station identity and minute data.

Typical enrichment on the cached data() frame is solpos(), then clear_sky(), then qc_test() (each mutates that frame in place and returns it). Optional qc_mask() sets failed irradiance to NaN and can drop flag columns. average() replaces the cache with a coarser time series from pretty_average().

Parameters:

• station_code (str) – Three-letter BSRN station code (must exist in BSRN_STATIONS).

• year (int) – Four-digit measurement year.

• month (int) – Measurement month (1–12).

• lr0100 (LR0100) – Validated LR0100 logical record (minute radiation and met data). This is the source of truth; data() is derived from it.

• lr0300 (LR0300 or None) – Validated LR0300 logical record (reflected / upward SW, LW, net radiation). Default None.

• lr4000 (LR4000 or None) – Validated LR4000 logical record (pyrgeometer minute data). Default None.

• metadata_lrs (dict) – Mapping for additional non-core logical records keyed by lr#### (for example 'lr0001'). Default empty dict.

• station_name (str or None) – Resolved from BSRN_STATIONS when omitted.

• lat (float or None) – Latitude (degrees); resolved from BSRN_STATIONS.

• lon (float or None) – Longitude (degrees); resolved from BSRN_STATIONS.

• elev (float or None) – Elevation (m above sea level); resolved from BSRN_STATIONS.

• resolution (int or None) – Temporal resolution in minutes (e.g. 1, 2, 3, 5). Defaults to 1.

Raises:

ValueError – If station_code is not in BSRN_STATIONS or month is outside 1–12.

__init__(**data)

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

self is explicitly positional-only to allow self as a field name.

Parameters:

data (Any)

Return type:

None

Methods

__init__(**data)	Create a new model by parsing and validating input data from keyword arguments.
average(freq[, alignment, aggfunc, ...])	Time-average the cached data() with explicit labeled windows.
clear_sky([model, mcclear_email])	Add clear-sky irradiance columns to the cached data() frame.
construct([_fields_set])
copy(*[, include, exclude, update, deep])	Returns a copy of the model.
data([include])	Minute-resolution DataFrame derived from lr0100.
dict(*[, include, exclude, by_alias, ...])
from_file(path[, include_lrs, strict])	Parse a BSRN .dat.gz station-to-archive file and return a fully validated BSRNDataset.
from_orm(obj)
get_lr(lr_code)	Return one logical record by code.
has_lr(lr_code)	Check whether one logical record exists on the dataset.
json(*[, include, exclude, by_alias, ...])
model_construct([_fields_set])	Creates a new instance of the Model class with validated data.
model_copy(*[, update, deep])	!!! abstract "Usage Documentation"
model_dump(*[, mode, include, exclude, ...])	!!! abstract "Usage Documentation"
model_dump_json(*[, indent, ensure_ascii, ...])	!!! abstract "Usage Documentation"
model_json_schema([by_alias, ref_template, ...])	Generates a JSON schema for a model class.
model_parametrized_name(params)	Compute the class name for parametrizations of generic classes.
model_post_init(context, /)	This function is meant to behave like a BaseModel method to initialize private attributes.
model_rebuild(*[, force, raise_errors, ...])	Try to rebuild the pydantic-core schema for the model.
model_validate(obj, *[, strict, extra, ...])	Validate a pydantic model instance.
model_validate_json(json_data, *[, strict, ...])	!!! abstract "Usage Documentation"
model_validate_strings(obj, *[, strict, ...])	Validate the given object with string data against the Pydantic model.
parse_file(path, *[, content_type, ...])
parse_obj(obj)
parse_raw(b, *[, content_type, encoding, ...])
qc_mask([flag_remove])	Set irradiance values to NaN where QC flags fail; optionally drop flag columns.
qc_test([tests])	Run QC tests and add flag columns to the cached data() frame.
schema([by_alias, ref_template])
schema_json(*[, by_alias, ref_template])
solpos()	Add solar position and extraterrestrial irradiance columns to the cached data() frame.
update_forward_refs(**localns)
validate(value)

Attributes

model_computed_fields
model_config	Configuration for the model, should be a dictionary conforming to [ConfigDict][pydantic.config.ConfigDict].
model_extra	Get extra fields set during validation.
model_fields
model_fields_set	Returns the set of fields that have been explicitly set on this model instance.
plot	Accessor for built-in plotting routines.
station_code
year
month
lr0100
lr0300
lr4000
metadata_lrs
station_name
lat
lon
elev
resolution