sailor.assetcentral.indicators

Indicators module can be used to retrieve Indicator information from AssetCentral.

Classes are provided for individual Indicators as well as groups of Indicators (IndicatorSet). Note that the indicators here represent ‘materialized’ indicators, i.e. indicators attached to an equipment. Hence they contain information on indicator_group and template used to attach it to the equipment. Currently there is no support for unrealized ‘Indicator Templates’.

class sailor.assetcentral.indicators.AggregatedIndicator(ac_json, aggregation_function)

Bases: Indicator

An extension of the AssetCentral Indicator object that additionally holds aggregation information.

classmethod get_available_properties()

Return the available properties for this class.

property id

Return the ID of the object.

class sailor.assetcentral.indicators.AggregatedIndicatorSet(elements)

Bases: IndicatorSet

Class representing a group of AggregatedIndicators.

as_df(columns=None)

Return all information on the objects stored in the MasterDataEntitySet as a pandas dataframe.

columns can be specified to select the columns (and their order) for the DataFrame.

Parameters

columns (Optional[Iterable[str]]) –

filter(**kwargs)

Select a subset of the collection based on named filter criteria for the attributes of the elements.

All keyword arguments are concatenated as filters with OR operator, i.e., only one of the supplied filters must match for an entity to be selected.

Returns a new AssetcentralEntitySet object.

Return type

MasterDataEntitySet

plot_distribution(by=None, fill=None, dropna=False)

Plot the distribution of elements of a MasterDataEntitySet based on their properties.

This effectively creates a histogram with the number of elements per group on the y-axis, and the group (given by the by parameter) on the x-axis. Additionally, the fill colour of the bar can be used to distinguish a second dimension.

class sailor.assetcentral.indicators.Indicator(ac_json)

Bases: AssetcentralEntity

AssetCentral Indicator Object.

Parameters

ac_json (dict) –

classmethod get_available_properties()

Return the available properties for this class.

property id

Return the ID of the object.

class sailor.assetcentral.indicators.IndicatorSet(elements)

Bases: AssetcentralEntitySet

Class representing a group of Indicators.

as_df(columns=None)

Return all information on the objects stored in the MasterDataEntitySet as a pandas dataframe.

columns can be specified to select the columns (and their order) for the DataFrame.

Parameters

columns (Optional[Iterable[str]]) –

filter(**kwargs)

Select a subset of the collection based on named filter criteria for the attributes of the elements.

All keyword arguments are concatenated as filters with OR operator, i.e., only one of the supplied filters must match for an entity to be selected.

Returns a new AssetcentralEntitySet object.

Return type

MasterDataEntitySet

plot_distribution(by=None, fill=None, dropna=False)

Plot the distribution of elements of a MasterDataEntitySet based on their properties.

This effectively creates a histogram with the number of elements per group on the y-axis, and the group (given by the by parameter) on the x-axis. Additionally, the fill colour of the bar can be used to distinguish a second dimension.

class sailor.assetcentral.indicators.SystemAggregatedIndicator(ac_json, aggregation_function, hierarchy_position)

Bases: AggregatedIndicator

An extension of the AssetCentral Indicator object that additionally holds aggregation and hierarchy position information.

classmethod get_available_properties()

Return the available properties for this class.

property id

Return the ID of the object.

class sailor.assetcentral.indicators.SystemAggregatedIndicatorSet(elements)

Bases: IndicatorSet

Class representing a group of SystemAggregatedIndicators.

as_df(columns=None)

Return all information on the objects stored in the MasterDataEntitySet as a pandas dataframe.

columns can be specified to select the columns (and their order) for the DataFrame.

Parameters

columns (Optional[Iterable[str]]) –

filter(**kwargs)

Select a subset of the collection based on named filter criteria for the attributes of the elements.

All keyword arguments are concatenated as filters with OR operator, i.e., only one of the supplied filters must match for an entity to be selected.

Returns a new AssetcentralEntitySet object.

Return type

MasterDataEntitySet

plot_distribution(by=None, fill=None, dropna=False)

Plot the distribution of elements of a MasterDataEntitySet based on their properties.

This effectively creates a histogram with the number of elements per group on the y-axis, and the group (given by the by parameter) on the x-axis. Additionally, the fill colour of the bar can be used to distinguish a second dimension.

class sailor.assetcentral.indicators.SystemIndicator(ac_json, hierarchy_position)

Bases: Indicator

An extension of the AssetCentral Indicator object that additionally holds hierarchy position information.

classmethod get_available_properties()

Return the available properties for this class.

property id

Return the ID of the object.

class sailor.assetcentral.indicators.SystemIndicatorSet(elements)

Bases: IndicatorSet

Class representing a group of SystemIndicators.

as_df(columns=None)

Return all information on the objects stored in the MasterDataEntitySet as a pandas dataframe.

columns can be specified to select the columns (and their order) for the DataFrame.

Parameters

columns (Optional[Iterable[str]]) –

filter(**kwargs)

Select a subset of the collection based on named filter criteria for the attributes of the elements.

All keyword arguments are concatenated as filters with OR operator, i.e., only one of the supplied filters must match for an entity to be selected.

Returns a new AssetcentralEntitySet object.

Return type

MasterDataEntitySet

plot_distribution(by=None, fill=None, dropna=False)

Plot the distribution of elements of a MasterDataEntitySet based on their properties.

This effectively creates a histogram with the number of elements per group on the y-axis, and the group (given by the by parameter) on the x-axis. Additionally, the fill colour of the bar can be used to distinguish a second dimension.