didppy.FloatTable1D

class didppy.FloatTable1D

1-dimensional table of continuous constants.

t[x] returns an continuous expression referring to an item where t is FloatTable1D and x is ElementExpr, ElementVar, ElementResourceVar, or int. If x is SetExpr, SetVar, or SetConst, t[x] returns the sum of constants over x.

Examples

>>> import didppy as dp
>>> model = dp.Model()
>>> obj = model.add_object_type(number=2)
>>> table = model.add_float_table([2.5, 3.5])
>>> var = model.add_element_var(object_type=obj, target=1)
>>> table[var].eval(model.target_state, model)
3.5
>>> set_var = model.add_set_var(object_type=obj, target=[0, 1])
>>> table[set_var].eval(model.target_state, model)
6.0

Methods

`max`(i)	Takes the maximum of constants in a table over the set of indices.
`min`(i)	Takes the minimum of constants in a table over the set of indices.
`product`(i)	Takes the product of constants in a table over the set of indices.

max(i)

Takes the maximum of constants in a table over the set of indices.

Parameters:: set (SetExpr, SetVar, or SetConst) – Set of indices
Returns:: The maximum.
Return type:: FloatExpr

Examples

>>> import didppy as dp
>>> model = dp.Model()
>>> obj = model.add_object_type(number=2)
>>> table = model.add_float_table([2.5, 3.5])
>>> var = model.add_set_var(object_type=obj, target=[0, 1])
>>> table.max(var).eval(model.target_state, model)
3.5

min(i)

Takes the minimum of constants in a table over the set of indices.

Parameters:: set (SetExpr, SetVar, or SetConst) – Set of indices
Returns:: The minimum.
Return type:: FloatExpr

Examples

>>> import didppy as dp
>>> model = dp.Model()
>>> table = model.add_float_table([2.5, 3.5])
>>> obj = model.add_object_type(number=2)
>>> var = model.add_set_var(object_type=obj, target=[0, 1])
>>> table.min(var).eval(model.target_state, model)
2.5

product(i)

Takes the product of constants in a table over the set of indices.

Parameters:: set (SetExpr, SetVar, or SetConst) – Set of indices
Returns:: The product.
Return type:: FloatExpr

Examples

>>> import didppy as dp
>>> model = dp.Model()
>>> table = model.add_float_table([2.5, 3.5])
>>> obj = model.add_object_type(number=2)
>>> var = model.add_set_var(object_type=obj, target=[0, 1])
>>> table.product(var).eval(model.target_state, model)
8.75