pvlib.forecast.NDFD#

class pvlib.forecast.NDFD(**kwargs)[source]#

Deprecated since version 0.9.1: The NDFD class was deprecated in pvlib 0.9.1 and will be removed in a future release. For details, see https://pvlib-python.readthedocs.io/en/stable/user_guide/forecasts.html

Subclass of the ForecastModel class representing NDFD forecast model.

Model data corresponds to NWS CONUS CONDUIT forecasts.

Parameters: set_type (string, default 'best') – Type of model to pull data from.

dataframe_variables#

Common variables present in the final set of data.

Type: list

model#

Name of the UNIDATA forecast model.

Type: string

model_type#

UNIDATA category in which the model is located.

Type: string

variables#

Defines the variables to obtain from the weather model and how they should be renamed to common variable names.

Type: dict

units#

Dictionary containing the units of the standard variables and the model specific variables.

Type: dict

Methods

`__init__`(**kwargs)
`cloud_cover_to_ghi_linear`(cloud_cover, ghi_clear)	Convert cloud cover to GHI using a linear relationship.
`cloud_cover_to_irradiance`(cloud_cover[, how])	Convert cloud cover to irradiance.
`cloud_cover_to_irradiance_campbell_norman`(...)	Estimates irradiance from cloud cover in the following steps:
`cloud_cover_to_irradiance_clearsky_scaling`(...)	Estimates irradiance from cloud cover in the following steps:
`cloud_cover_to_transmittance_linear`(cloud_cover)	Convert cloud cover (percentage) to atmospheric transmittance using a linear model.
`connect_to_catalog`()
`get_data`(latitude, longitude, start, end[, ...])	Submits a query to the UNIDATA servers using Siphon NCSS and converts the netcdf data to a pandas DataFrame.
`get_processed_data`(args, *kwargs)	Get and process forecast data.
`gust_to_speed`(data[, scaling])	Computes standard wind speed from gust.
`isobaric_to_ambient_temperature`(data)	Calculates temperature from isobaric temperature.
`kelvin_to_celsius`(temperature)	Converts Kelvin to celsius.
`process_data`(data, **kwargs)	Defines the steps needed to convert raw forecast data into processed forecast data.
`rename`(data[, variables])	Renames the columns according the variable mapping.
`set_dataset`()	Retrieves the designated dataset, creates NCSS object, and creates a NCSS query object.
`set_location`(tz, latitude, longitude)	Sets the location for the query.
`set_query_latlon`()	Sets the NCSS query location latitude and longitude.
`set_query_time_range`(start, end)	param start Must be tz-localized.
`set_time`(time)	Converts time data into a pandas date object.
`uv_to_speed`(data)	Computes wind speed from wind components.

Attributes

`access_url_key`
`base_tds_url`
`catalog_url`
`data_format`
`units`

pvlib.forecast.HRRR_ESRL.uv_to_speed

pvlib.forecast.NDFD.__init__