ams.core.service.RampSub

class ams.core.service.RampSub(u: Callable, name: str = None, tex_name: str = None, unit: str = None, info: str = None, vtype: Type = None, rfun: Callable = None, rargs: dict = None, no_parse: bool = False, sparse: bool = False)

Build a substraction matrix for a 2D variable in the shape (nr, nr-1), where nr is the rows of the input.

This can be used for generator ramping constraints in multi-period optimization problems.

The subtraction matrix is constructed as follows: np.eye(nr, nc, k=-1) - np.eye(nr, nc, k=0).

Parameters:

uCallable

Input.

horizonCallable

Horizon reference.

namestr

Instance name.

tex_namestr

TeX name.

unitstr

Unit.

infostr

Description.

vtypeType

Variable type.

rfunCallable, optional

Function to apply to the output of fun.

rargsdict, optional

Keyword arguments to pass to rfun.

no_parse: bool, optional

True to skip parsing the service.

sparse: bool, optional

True to return output as scipy csr_matrix.

__init__(u: Callable, name: str = None, tex_name: str = None, unit: str = None, info: str = None, vtype: Type = None, rfun: Callable = None, rargs: dict = None, no_parse: bool = False, sparse: bool = False)

Methods

assign_memory(n)	Assign memory for self.v and set the array to zero.
evaluate(*args, **kwargs)
get_all_idxes()	Return all the indexes of this item.
get_idx()
get_names()	Return name in a list
parse(*args, **kwargs)
update()	Update the Parameter value.

Attributes

class_name	Return the class name
n	Return the count of values in self.v.
shape	Return the shape of the service.
size	Return the size.
v	Value of the service.
v0
v1