pyValEIA.stats.tables

Functions to create tables of statistics.

Functions

`decision_table_sat`(states[, sats, sat_key, eia_type, ...])	Decision table summing hit/miss/corr-neg/false-pos states by satellite.
`style_df_table`(df_table, eia_type[, sat_names])	Style decision table.
`lss_table_sat`(model1, model2[, model1_name, ...])	Create table including the Liemohn Skill Scores 1-4.
`style_lss_table`(lss_df[, sat_names])	Style the LSS decision table.

Module Contents

pyValEIA.stats.tables.decision_table_sat(states, sats=None, sat_key='Sat', eia_type='eia', model_name='Model', const_name='Swarm')[source]

Decision table summing hit/miss/corr-neg/false-pos states by satellite.

Parameters:

statespd.DataFrame: DataFrame of model data including skill and local times built by multiday_states_report
satslist-like or NoneType: List of satellites specified by states[sat_key] to include in table, if None all will be included (default=None)
sat_keystr: Key in states to access the satellite separator (default=’Sat’)
eia_typestr: EIA state, e.g. ‘eia’, ‘peak’, etc., that declairs what is considered a hit.
model_namestr: Model name for decision table label (default=’Model’)
const_namestr: Satellite constellation name (default=’Swarm’)

Returns:

table_framepd.DataFrame: DataFrame in table format separated by satellite and event state (state, non-state). Index using: table_frame.loc[(

f’{const_name} {satellite}’, eia_type), (model_name, eia_type)]

pyValEIA.stats.tables.style_df_table(df_table, eia_type, sat_names=None)[source]

Style decision table.

Parameters:

df_tablepd.DataFrame: DataFrame created by decision_table_sat
eia_typestr: string designating which eia type is being reported
sat_nameslist-like or NoneType: List of satellite names in df_table or None to use Swarm defaults.

Returns:

styled_framepd.DataFrame: Styled DataFrame

Raises:

ValueError: For unknown constellation name

pyValEIA.stats.tables.lss_table_sat(model1, model2, model1_name='Model1', model2_name='Model2', sats=None, sat_key='Sat', const_name='Swarm')[source]

Create table including the Liemohn Skill Scores 1-4.

Parameters:

model1pd.DataFrame: DataFrame of 1st model data including skill and local times built by multiday_states_report
model2pd.DataFrame: DataFrame of 2nd model data including skill and local times built by multiday_states_report
model1_namestr: String of name of model1 (default=’Model1’)
model2_namestr: String of name for model2 (default=’Model2’)
satslist of strings kwarg: swarm satellites ‘A’, ‘B’, and ‘C’ as default can specify just 1 or 2
satslist-like or NoneType: List of satellites specified by states[sat_key] to include in table, if None all will be included (default=None)
sat_keystr: Key in model1 and model2 used to access the satellite separator (default=’Sat’)
const_namestr: Satellite constellation name (default=’Swarm’)

Returns:

lss_dfpd.DataFrame: DataFrame in table format separated by satellite and Liemohn skill score