Mappers

Various mapper implementations. Mappers are functions that map possible feature value’s to the interval [-1, 1]. In Creamas, they are used by individual agent’s to represent agent’s preferences over features values.

class creamas.mappers.BooleanMapper(mode='10')

Boolean mapper that has four different modes.

Depending on the mode, True and False are mapped either to 1, 0, or -1.

mode	True	False
‘10’	1.0	0.0
‘01’	0.0	1.0
‘1-1’	1.0	-1.0
‘-11’	-1.0	1.0

map(value)

Map given value to the interval [-1, 1].

This base implementation maps each value to itself, capping to [-1, 1].

Parameters

value – Value to map

Returns

Value mapped to the interval [-1, 1]

Rtype float

property mode

Mode of the mapper.

property value_set

Acceptable input types for the mapper.

class creamas.mappers.LinearMapper(lo, hi, mode='01')

Mapper that maps values in given interval linearly.

Can be used for features that return either ‘int’ or ‘float’ values.

Based on its mode, maps lo and hi to different end points and values between them to a straight line. Depending on the mode, lo and hi have following end points:

mode	lo	hi
‘10’	1.0	0.0
‘01’	0.0	1.0
‘1-1’	1.0	-1.0
‘-11’	-1.0	1.0

map(value)

Map given value to the interval [-1, 1].

This base implementation maps each value to itself, capping to [-1, 1].

Parameters

value – Value to map

Returns

Value mapped to the interval [-1, 1]

Rtype float

property mode

Mode of the mapper.

property value_set

Accepted value types, i.e. this mapper can be used for the features that return these types of values.

class creamas.mappers.DoubleLinearMapper(lo, mid, hi, mode='01')

Mapper that concatenates two linear mappers.

Can be used for features that return either ‘int’ or ‘float’ values.

First line is created from lo to mid and second line from mid to hi. Depending on the mode, lo, mid and hi are mapped to following end points.

mode	lo	mid	hi
‘10’	1.0	0.0	1.0
‘01’	0.0	1.0	0.0
‘1-1’	1.0	-1.0	1.0
‘-11’	-1.0	1.0	-1.0

map(value)

Map given value to the interval [-1, 1].

This base implementation maps each value to itself, capping to [-1, 1].

Parameters

value – Value to map

Returns

Value mapped to the interval [-1, 1]

Rtype float

property mode

Mode of the mapper.

property value_set

Accepted value types, i.e. this mapper can be used for the features that return these types of values.

class creamas.mappers.GaussianMapper(mean, std, mode='01')

Gaussian distribution mapper.

The mapped value is relative to given Gaussian distribution’s maximum point (pmax, evaluated at point loc) and the probability density function’s value at given evaluation point (pval).

The actual value calculation changes with the mode of the mapper:

mode	mapped value
‘10’	\(1.0 - (pval / pmax)\)
‘01’	\(pval / pmax\)
‘1-1’	\(1.0 - 2(pval / pmax)\)
‘-11’	\(-1.0 + 2(pval / pmax)\)

Parameters

• mean (float) – mean of the mapping distribution

• std (float) – standard deviation of the mapping distribution

• mode – mode of the mapper: ‘10’, ‘01’, ‘1-1’ or ‘-11’.

map(value)

Map given value to the interval [-1, 1].

This base implementation maps each value to itself, capping to [-1, 1].

Parameters

value – Value to map

Returns

Value mapped to the interval [-1, 1]

Rtype float

property mode

Mode of the mapper.

property value_set

Acceptable input types for the mapper.

class creamas.mappers.LogisticMapper(x0, k, mode='01')

Logistic function mapper.

The mapped value is relative to the logistic function’s value in the mapping point. Depending on the mode, some transformations (mirroring, shifting), might be applied to the mapped value.

Parameters

• x0 (float) – sigmoid’s midpoint

• k (float) – steepness of the curve

• mode – mode of the mapper: ‘10’, ‘01’, ‘1-1’ or ‘-11’.

map(value)

Map given value to the interval [-1, 1].

This base implementation maps each value to itself, capping to [-1, 1].

Parameters

value – Value to map

Returns

Value mapped to the interval [-1, 1]

Rtype float

property mode

Mode of the mapper.

property value_set

Acceptable input types for the mapper.