.. currentmodule:: solarforecastarbiter
The data model.
.. autosummary:: :toctree: generated/ datamodel
There are two kinds of sites:
.. autosummary:: :toctree: generated/ datamodel.Site datamodel.SolarPowerPlant
The several model parameters are associated with the solar power plant site:
.. autosummary:: :toctree: generated/ datamodel.PVModelingParameters datamodel.FixedTiltModelingParameters datamodel.SingleAxisModelingParameters
The Observation and Forecast:
.. autosummary:: :toctree: generated/ datamodel.Observation datamodel.Forecast
Probabilistic forecasts:
.. autosummary:: :toctree: generated/ datamodel.ProbabilisticForecast datamodel.ProbabilisticForecastConstantValue
Event forecasts:
.. autosummary:: :toctree: generated/ datamodel.EventForecast
Aggregates:
.. autosummary:: :toctree: generated/ datamodel.AggregateObservation datamodel.Aggregate
Data validation toolkit filters for use with reports:
.. autosummary:: :toctree: generated/ datamodel.BaseFilter datamodel.QualityFlagFilter datamodel.TimeOfDayFilter datamodel.ValueFilter
Containers to associate forecasts and observations for use with reports:
.. autosummary:: :toctree: generated/ datamodel.ForecastObservation datamodel.ForecastAggregate datamodel.ProcessedForecastObservation
Report metrics and validation:
.. autosummary:: :toctree: generated/ datamodel.MetricResult datamodel.MetricValue datamodel.ValidationResult datamodel.PreprocessingResult datamodel.ReportMessage
Report plots:
.. autosummary:: :toctree: generated/ datamodel.RawReportPlots datamodel.ReportFigure
Reports:
.. autosummary:: :toctree: generated/ datamodel.ReportParameters datamodel.RawReport datamodel.Report
Cost:
.. autosummary:: :toctree: generated/ datamodel.ConstantCost datamodel.TimeOfDayCost datamodel.DatetimeCost datamodel.CostBand datamodel.ErrorBandCost datamodel.Cost
All :py:mod:`~solarforecastarbiter.datamodel` objects have from_dict and
to_dict methods:
.. autosummary:: :toctree: generated/ datamodel.BaseModel.from_dict datamodel.BaseModel.to_dict
The :py:mod:`~solarforecastarbiter.pvmodel` module contains functions closely associated with PV modeling.
.. autosummary:: :toctree: generated/ pvmodel
Several utility functions wrap pvlib functions:
.. autosummary:: :toctree: generated/ pvmodel.calculate_solar_position pvmodel.complete_irradiance_components pvmodel.calculate_clearsky
Three functions are useful for determining AOI, surface tilt, and surface azimuth. :py:func:`~pvmodel.aoi_func_factory` is helpful for standardizing the calculations for tracking and fixed systems. See :py:func:`~pvmodel.calculate_poa_effective`, for example.
.. autosummary:: :toctree: generated/ pvmodel.aoi_func_factory pvmodel.aoi_fixed pvmodel.aoi_tracking
.. autosummary:: :toctree: generated/ pvmodel.calculate_poa_effective_explicit pvmodel.calculate_poa_effective pvmodel.calculate_power pvmodel.irradiance_to_power
High-level functions for NWP and persistence forecasts.
.. autosummary:: :toctree: generated/ reference_forecasts.main.run_nwp reference_forecasts.main.run_persistence reference_forecasts.main.find_reference_nwp_forecasts reference_forecasts.main.process_nwp_forecast_groups reference_forecasts.main.make_latest_nwp_forecasts reference_forecasts.main.fill_nwp_forecast_gaps reference_forecasts.main.make_latest_persistence_forecasts reference_forecasts.main.make_latest_probabilistic_persistence_forecasts reference_forecasts.main.fill_persistence_forecasts_gaps reference_forecasts.main.fill_probabilistic_persistence_forecasts_gaps
.. autosummary:: :toctree: generated/ reference_forecasts.models.hrrr_subhourly_to_subhourly_instantaneous reference_forecasts.models.hrrr_subhourly_to_hourly_mean reference_forecasts.models.rap_ghi_to_instantaneous reference_forecasts.models.rap_cloud_cover_to_hourly_mean reference_forecasts.models.gfs_quarter_deg_3hour_to_hourly_mean reference_forecasts.models.gfs_quarter_deg_hourly_to_hourly_mean reference_forecasts.models.gfs_quarter_deg_to_hourly_mean reference_forecasts.models.nam_12km_hourly_to_hourly_instantaneous reference_forecasts.models.nam_12km_cloud_cover_to_hourly_mean
.. autosummary:: :toctree: generated/ reference_forecasts.models.gefs_half_deg_to_hourly_mean
Functions that process forecast data.
.. autosummary:: :toctree: generated/ reference_forecasts.forecast.cloud_cover_to_ghi_linear reference_forecasts.forecast.cloud_cover_to_irradiance_ghi_clear reference_forecasts.forecast.cloud_cover_to_irradiance reference_forecasts.forecast.resample reference_forecasts.forecast.reindex_fill_slice reference_forecasts.forecast.unmix_intervals reference_forecasts.forecast.sort_gefs_frame
.. autosummary:: :toctree: generated/ reference_forecasts.persistence.persistence_scalar reference_forecasts.persistence.persistence_interval reference_forecasts.persistence.persistence_scalar_index
.. autosummary:: :toctree: generated/ reference_forecasts.persistence.persistence_probabilistic reference_forecasts.persistence.persistence_probabilistic_timeofday
.. autosummary:: :toctree: generated/ io.fetch.arm.format_date io.fetch.arm.request_arm_file_list io.fetch.arm.list_arm_filenames io.fetch.arm.request_arm_file io.fetch.arm.retrieve_arm_dataset io.fetch.arm.extract_arm_variables io.fetch.arm.fetch_arm
.. autosummary:: :toctree: generated/ io.fetch.nwp.get_with_retries io.fetch.nwp.get_available_dirs io.fetch.nwp.check_next_inittime io.fetch.nwp.get_filename io.fetch.nwp.files_to_retrieve io.fetch.nwp.process_grib_to_netcdf io.fetch.nwp.optimize_netcdf io.fetch.nwp.sleep_until_inittime io.fetch.nwp.startup_find_next_runtime io.fetch.nwp.next_run_time io.fetch.nwp.run io.fetch.nwp.optimize_only io.fetch.nwp.check_wgrib2
.. autosummary:: :toctree: generated/ io.fetch.rtc.request_doe_rtc_data io.fetch.rtc.fetch_doe_rtc
.. autosummary:: :toctree: generated/ io.fetch.pvdaq.get_pvdaq_metadata io.fetch.pvdaq.get_pvdaq_data
.. autosummary:: :toctree: generated/ io.fetch.eia.get_eia_data
.. autosummary:: :toctree: generated/ io.fetch.bsrn.parse_bsrn io.fetch.bsrn.read_bsrn_from_nasa_larc io.fetch.bsrn.read_bsrn_month_from_nasa_larc
The following modules contain code for initializing the reference
database, wrappers for fetching data, functions for processing (e.g.
renaming and resampling) data, and wrapper functions for posting data.
The pure fetch functions are found in pvlib.iotools and in
solarforecastarbiter.io.fetch. See the source code for additional
files with site and observation metadata.
.. autosummary:: :toctree: generated/ io.reference_observations.common io.reference_observations.crn io.reference_observations.midc_config io.reference_observations.midc io.reference_observations.reference_data io.reference_observations.rtc io.reference_observations.solrad io.reference_observations.srml io.reference_observations.surfrad io.reference_observations.arm io.reference_observations.pvdaq io.reference_observations.eia io.reference_observations.bsrn io.reference_observations.pnnl
The following modules contain code for initializing the reference aggregates using Reference Observations that have already been created. Examples include average GHI and DNI at SURFRAD sites, and the total PV power in the Portland, OR area of UO SRML sites.
.. autosummary:: :toctree: generated/ io.reference_aggregates.generate_aggregate io.reference_aggregates.make_reference_aggregates
To pass API calls through a proxy server, set either the HTTP_PROXY or HTTPS_PROXY environment variable. If necessary, set a SSL certificate using the REQUESTS_CA_BUNDLE environment variable.
Get an API token.
.. autosummary:: :toctree: generated/ io.api.request_cli_access_token
Class for communicating with the Solar Forecast Arbiter API.
.. autosummary:: :toctree: generated/ io.api.APISession io.api.APISession.request io.api.APISession.get_user_info
Sites
.. autosummary:: :toctree: generated/ io.api.APISession.get_site io.api.APISession.list_sites io.api.APISession.list_sites_in_zone io.api.APISession.create_site
Observations
.. autosummary:: :toctree: generated/ io.api.APISession.get_observation io.api.APISession.list_observations io.api.APISession.create_observation io.api.APISession.get_observation_values io.api.APISession.post_observation_values io.api.APISession.get_observation_time_range io.api.APISession.get_observation_values_not_flagged io.api.APISession.get_observation_value_gaps
Forecasts
.. autosummary:: :toctree: generated/ io.api.APISession.get_forecast io.api.APISession.list_forecasts io.api.APISession.create_forecast io.api.APISession.get_forecast_values io.api.APISession.post_forecast_values io.api.APISession.get_forecast_time_range io.api.APISession.get_forecast_value_gaps
Probabilistic Forecasts
.. autosummary:: :toctree: generated/ io.api.APISession.get_probabilistic_forecast io.api.APISession.list_probabilistic_forecasts io.api.APISession.create_probabilistic_forecast io.api.APISession.get_probabilistic_forecast_values io.api.APISession.get_probabilistic_forecast_value_gaps io.api.APISession.get_probabilistic_forecast_constant_value io.api.APISession.get_probabilistic_forecast_constant_value_values io.api.APISession.post_probabilistic_forecast_constant_value_values io.api.APISession.get_probabilistic_forecast_constant_value_time_range io.api.APISession.get_probabilistic_forecast_constant_value_value_gaps
Aggregates
.. autosummary:: :toctree: generated/ io.api.APISession.get_aggregate io.api.APISession.list_aggregates io.api.APISession.create_aggregate io.api.APISession.get_aggregate_values
Reports
.. autosummary:: :toctree: generated/ io.api.APISession.process_report_dict io.api.APISession.get_report io.api.APISession.list_reports io.api.APISession.create_report io.api.APISession.post_raw_report_processed_data io.api.APISession.get_raw_report_processed_data io.api.APISession.post_raw_report io.api.APISession.update_report_status
Climate Zones
.. autosummary:: :toctree: generated/ io.api.APISession.list_sites_in_zone io.api.APISession.search_climatezones
Convenience method for unifying API for getting time series values for observations, forecasts, aggregates, and probabilistic forecasts:
.. autosummary:: :toctree: generated/ io.api.APISession.get_values io.api.APISession.chunk_value_requests io.api.APISession.get_value_gaps
Utility functions for data IO.
.. autosummary:: :toctree: generated/ io.utils.observation_df_to_json_payload io.utils.forecast_object_to_json io.utils.json_payload_to_observation_df io.utils.json_payload_to_forecast_series io.utils.adjust_start_end_for_interval_label io.utils.adjust_timeseries_for_interval_label io.utils.ensure_timestamps io.utils.serialize_timeseries io.utils.deserialize_timeseries io.utils.load_report_values io.utils.mock_raw_report_endpoints
Entry points for calculating metrics for :py:class:`~solarforecastarbiter.datamodel.Forecast` and :py:class:`~solarforecastarbiter.datamodel.Observation`:
.. autosummary:: :toctree: generated/ metrics.calculator.calculate_metrics metrics.calculator.calculate_deterministic_metrics metrics.calculator.calculate_probabilistic_metrics metrics.calculator.calculate_event_metrics metrics.calculator.calculate_all_summary_statistics metrics.calculator.calculate_summary_statistics
Functions for preparing the timeseries data before calculating metrics:
.. autosummary:: :toctree: generated/ metrics.preprocessing.check_reference_forecast_consistency metrics.preprocessing.apply_fill metrics.preprocessing.filter_resample metrics.preprocessing.align metrics.preprocessing.process_forecast_observations
Functions to compute forecast deterministic performance metrics:
.. autosummary:: :toctree: generated/ metrics.deterministic.mean_absolute metrics.deterministic.mean_bias metrics.deterministic.root_mean_square metrics.deterministic.normalized_mean_absolute metrics.deterministic.normalized_mean_bias metrics.deterministic.normalized_root_mean_square metrics.deterministic.centered_root_mean_square metrics.deterministic.mean_absolute_percentage metrics.deterministic.forecast_skill metrics.deterministic.pearson_correlation_coeff metrics.deterministic.coeff_determination metrics.deterministic.relative_euclidean_distance metrics.deterministic.kolmogorov_smirnov_integral metrics.deterministic.over metrics.deterministic.combined_performance_index
Functions to compute costs:
.. autosummary:: :toctree: generated/ metrics.deterministic.constant_cost metrics.deterministic.time_of_day_cost metrics.deterministic.datetime_cost metrics.deterministic.error_band_cost metrics.deterministic.cost
Functions to compute errors and deadbands:
.. autosummary:: :toctree: generated/ metrics.deterministic.deadband_mask metrics.deterministic.error metrics.deterministic.error_deadband
Functions to compute forecast probabilistic performance metrics:
.. autosummary::
:toctree: generated/
metrics.probabilistic.brier_score
metrics.probabilistic.brier_skill_score
metrics.probabilistic.quantile_score
metrics.probabilistic.quantile_skill_score
metrics.probabilistic.brier_decomposition
metrics.probabilistic.reliability
metrics.probabilistic.resolution
metrics.probabilistic.uncertainty
metrics.probabilistic.sharpness
metrics.probabilistic.continuous_ranked_probability_score
metrics.probabilistic.crps_skill_score
Functions to compute deterministic event forecast performance metrics:
.. autosummary::
:toctree: generated/
metrics.event.probability_of_detection
metrics.event.false_alarm_ratio
metrics.event.probability_of_false_detection
metrics.event.critical_success_index
metrics.event.event_bias
metrics.event.event_accuracy
Functions to compute the report.
.. autosummary:: :toctree: generated/ reports.main.compute_report reports.main.get_data_for_report reports.main.create_raw_report_from_data
Functions for generating Plotly report metric figures.
.. autosummary:: :toctree: generated/ reports.figures.plotly_figures.construct_metrics_dataframe reports.figures.plotly_figures.construct_timeseries_dataframe reports.figures.plotly_figures.bar reports.figures.plotly_figures.bar_subdivisions reports.figures.plotly_figures.output_svg reports.figures.plotly_figures.raw_report_plots reports.figures.plotly_figures.timeseries_plots reports.figures.plotly_figures.timeseries reports.figures.plotly_figures.scatter
Functions for generating Bokeh plots.
.. autosummary:: :toctree: generated/ reports.figures.bokeh_figures.construct_timeseries_cds reports.figures.bokeh_figures.construct_metrics_cds reports.figures.bokeh_figures.timeseries reports.figures.bokeh_figures.scatter reports.figures.bokeh_figures.bar reports.figures.bokeh_figures.bar_subdivisions reports.figures.bokeh_figures.output_svg reports.figures.bokeh_figures.raw_report_plots reports.figures.bokeh_figures.timeseries_plots
Functions to generate output (HTML, PDF) for reports
.. autosummary:: :toctree: generated/ reports.template.render_html reports.template.get_template_and_kwargs reports.template.render_pdf
Functions to perform validation.
.. autosummary:: :toctree: generated/ validation.validator.check_ghi_limits_QCRad validation.validator.check_dhi_limits_QCRad validation.validator.check_dni_limits_QCRad validation.validator.check_irradiance_limits_QCRad validation.validator.check_irradiance_consistency_QCRad validation.validator.check_temperature_limits validation.validator.check_wind_limits validation.validator.check_rh_limits validation.validator.check_ac_power_limits validation.validator.check_dc_power_limits validation.validator.check_ghi_clearsky validation.validator.check_poa_clearsky validation.validator.check_day_night validation.validator.check_day_night_interval validation.validator.check_timestamp_spacing validation.validator.detect_stale_values validation.validator.detect_interpolation validation.validator.detect_levels validation.validator.detect_clipping validation.validator.detect_clearsky_ghi validation.validator.stale_interpolated_window
Perform a sequence of validation steps. Used by the API to initiate validation.
.. autosummary:: :toctree: generated/ validation.tasks.validate_ghi validation.tasks.validate_dni validation.tasks.validate_dhi validation.tasks.validate_poa_global validation.tasks.validate_dc_power validation.tasks.validate_ac_power validation.tasks.validate_defaults validation.tasks.validate_air_temperature validation.tasks.validate_wind_speed validation.tasks.validate_relative_humidity validation.tasks.validate_daily_ghi validation.tasks.validate_daily_dc_power validation.tasks.validate_daily_ac_power validation.tasks.validate_daily_defaults validation.tasks.apply_immediate_validation validation.tasks.apply_daily_validation validation.tasks.apply_validation
Functions to handle the translation of validation results and database storage.
.. autosummary:: :toctree: generated/ validation.quality_mapping.convert_bool_flags_to_flag_mask validation.quality_mapping.mask_flags validation.quality_mapping.has_data_been_validated validation.quality_mapping.get_version validation.quality_mapping.check_if_single_value_flagged validation.quality_mapping.which_data_is_ok validation.quality_mapping.check_for_all_descriptions validation.quality_mapping.convert_mask_into_dataframe validation.quality_mapping.convert_flag_frame_to_strings validation.quality_mapping.check_if_series_flagged
Time series plotting.
.. autosummary:: :toctree: generated/ plotting.timeseries.build_figure_title plotting.timeseries.make_quality_bars plotting.timeseries.add_hover_tool plotting.timeseries.make_basic_timeseries plotting.timeseries.generate_forecast_figure plotting.timeseries.generate_observation_figure plotting.timeseries.generate_probabilistic_forecast_figure
Utility functions for plotting.
.. autosummary:: :toctree: generated/ plotting.utils.format_variable_name plotting.utils.align_index plotting.utils.line_or_step
Generic utility functions.
.. autosummary:: :toctree: generated/ utils.compute_aggregate utils.sha256_pandas_object_hash utils.generate_continuous_chunks utils.merge_ranges