PyLandUsePlugin.GKGenerationAttractionScenario

class GKGenerationAttractionScenario

The scenario of a trip for Generation/Attraction models.

Details

Requires a time period, one or more than one trip purpose and, optionally, the transportation modes.

It requires also a data group used to select what variables will be used in the calculation. The group allows the selection of Current or Future data (any data by socio-economical scenario).

Inheritance diagram of PyLandUsePlugin.GKGenerationAttractionScenario

Synopsis

Methods

Note

This documentation may contain snippets that were automatically translated from C++ to Python. We always welcome contributions to the snippet translation. If you see an issue with the translation, you can also let us know by creating a ticket on https:/bugreports.qt.io/projects/PYSIDE

__init__()
addMode(mode)
Parameters:

modeGKTransportationMode

Adds a mode.

addPurpose(purpose)
Parameters:

purposeGKTripPurpose

Adds a purpose.

aggregatingModes()
Return type:

bool

Returns whether the algorithm should aggregate mode data

getAverageCarOwnership()
Return type:

float

The average car ownership factor.

getCAModelFunction()
Return type:

GKFunctionCost

Get the Car availability Model Function

getCarModeCA()
Return type:

GKTransportationMode

Get the mode considered car for the CA/NCA split

getDataGroup()
Return type:

GKGenerationAttractionDataSet

The data group to consider.

getDisaggregateModes()
Return type:

.list of GKTransportationMode

get disaggregate modes belonging to aggregate mode

getElasticityCarOwnership()
Return type:

float

The elasticity factor.

getInfluenceCO()
Return type:

int

Gets the transportation mode to be influenced by car ownership

getModes()
Return type:

.list of GKTransportationMode

Modes to consider, including transit and walking. Can be empty.

getPurposes()
Return type:

.list of GKTripPurpose

Purposes to consider.

getStoreOutput()
Return type:

bool

Gets whether the Generation Attraction outputs are set to be stored in the database.

getSubAreasBalancing()
Return type:

GKGroupingType

getTimePeriod()
Return type:

GKTimePeriod

The time period to consider.

removeMode(mode)
Parameters:

modeGKTransportationMode

Removes a mode.

removePurpose(purpose)
Parameters:

purposeGKTripPurpose

Removes a purpose.

setAggregateModes(iAggregate)
Parameters:

iAggregate – bool

Configures the algorithm to aggregate mode data

setAverageCarOwnership(_factor)
Parameters:

_factor – float

The average car ownership factor.

setCAModelFunction(iFunction)
Parameters:

iFunctionGKFunctionCost

Set the Car availability Model Function

setCarModeCA(iMode)
Parameters:

iModeGKTransportationMode

Set the mode considered car for the CA/NCA split

setDataGroup(dataGroup)
Parameters:

dataGroupGKGenerationAttractionDataSet

The data group to consider.

setDisaggregateModes(iModes)
Parameters:

iModes – .list of GKTransportationMode

Set disaggregate modes belonging to aggregate mode

setElasticityCarOwnership(_factor)
Parameters:

_factor – float

The elasticity factor.

setInfluenceCO(iMode)
Parameters:

iMode – int

Sets the transportation mode to be influenced by car ownership

setModes(aModes)
Parameters:

aModes – .list of GKTransportationMode

Modes to consider, including transit and walking. Can be empty.

setPurposes(purposes)
Parameters:

purposes – .list of GKTripPurpose

Purposes to consider.

setStoreOutput(iValue)
Parameters:

iValue – bool

Sets the Generation Attraction outputs to be stored in the database or not.

setSubAreasBalancing(iGroupingType)
Parameters:

iGroupingTypeGKGroupingType

setTimePeriod(period)
Parameters:

periodGKTimePeriod

The time period to consider.

setUseCA(_state)
Parameters:

_state – bool

Sets if Car Availability operations must be performed.

usingCA()
Return type:

bool

return true if Car Availability operations are requested, false if not.