siconos.kernel.LagrangianLinearTIR (Python class)

class siconos.kernel.LagrangianLinearTIR(*args)[source]

Bases: siconos.kernel.LagrangianR

Lagrangian Linear Relation.

Lagrangian Relation with:

\(y= Cq + e + Fz\)

\(p = C^t \lambda\)

C is the only required input to built a LagrangianLinearTIR.

Generated class (swig), based on C++ header Program listing for file kernel/src/modelingTools/LagrangianLinearTIR.hpp.

Constructors

LagrangianLinearTIR()

Default constructor.

LagrangianLinearTIR(array_like (np.float64, 2D) C)

create the Relation from a set of data

Parameters:C – the matrix C
LagrangianLinearTIR(array_like (np.float64, 2D) C, array_like (np.float64, 2D) F, array_like (np.float64, 1D) e)

create the Relation from a set of data

Parameters:
  • C – the matrix C
  • F – the matrix F
  • e – the vector e
LagrangianLinearTIR(array_like (np.float64, 2D) C, array_like (np.float64, 1D) e)

create the Relation from a set of data

Parameters:
  • C – the matrix C
  • e – the vector e
C() -> array_like (np.float64, 2D)[source]

get C

Returns:pointer on a plugged matrix
D() -> array_like (np.float64, 2D)[source]

get D

Returns:pointer on a plugged matrix
F() -> array_like (np.float64, 2D)[source]

get F

Returns:pointer on a plugged matrix
checkSize(Interaction inter) → None[source]

initialize LagrangianLinearTIR specific operators.

Parameters:
  • inter – an Interaction using this relation check sizes of the relation specific operators.
  • inter – an Interaction using this relation
computeInput(double time, Interaction inter, int level=0) → None[source]

default function to compute r

Parameters:
  • time – not used
  • inter – the Interaction we want to update
  • level – the derivative of lambda we want to compute
computeJacg(double time, Interaction inter) → None[source]
computeJach(double time, Interaction inter) → None[source]

compute all the H Jacobian

Parameters:
  • time – the current time
  • inter – the interaction using this relation
computeOutput(double time, Interaction inter, int derivativeNumber=0) → None[source]

default function to compute y

Parameters:
  • time – not used
  • inter – the Interaction we want to update
  • derivativeNumber – the derivative of y we want to compute
display() → None[source]

get a pointer on matrix Jach[index]

Returns:a pointer on a SimpleMatrixprint the data to the screen
e() -> array_like (np.float64, 1D)[source]

get e

Returns:pointer on a plugged vector
isLinear() → bool[source]
Returns:true if the relation is linear.
setCPtr(array_like (np.float64, 2D) newPtr) → None[source]

set C to pointer newPtr

Parameters:newPtr – a SP to plugged matrix
setDPtr(array_like (np.float64, 2D) newPtr) → None[source]

set D to pointer newPtr

Parameters:newPtr – a SP to plugged matrix
setEPtr(array_like (np.float64, 1D) newPtr) → None[source]

set e to pointer newPtr

Parameters:newPtr – a SP to plugged vector
setFPtr(array_like (np.float64, 2D) newPtr) → None[source]

set F to pointer newPtr

Parameters:newPtr – a SP to plugged matrix