3.6.7

Install

Grab a binary from the table:

	Windows	Linux	Mac classic (High Sierra or above)	Mac M1
Matlab	R2018b or later	R2018b or later	R2018b or later	R2023b or later (Apple Silicon) R2018b or later (Rosetta)
Octave	6.2.0 or later	6.2.0 or later	6.2.0 or later	6.2.0 or later
Python	pip install casadi (needs pip -V>=8.1)

For Matlab/Octave, unzip in your home directory and adapt the path:

addpath('<yourpath>/casadi-3.6.7-windows64-matlab2018b')

Check your installation:

Matlab/Octave	Python
import casadi.* x = MX.sym('x') disp(jacobian(sin(x),x))	from casadi import * x = MX.sym("x") print(jacobian(sin(x),x))

Get started with the example pack. Onboarding pointers have been gathered by the community at our wiki.

Troubleshooting

• KNITRO on linux crashes with a segmentation fault without LD_PRELOAD=<knitro_lin_path>/libiomp5.so.
• Callbacks with one argument are broken in Matlab CasADi

Release notes

Symbolic expressions

• Added SX/MX/DM operations #1595:
  • hypot(x,y) = sqrt(x*x+y*y)
  • log1p(x) = log(1+x)
  • expm1(x) = exp(x-1)
• Added operation remainder with the semantics of the C operation
• breaking AD rule of fmin/fmax` is now symmetric:
  jacobian(fmin(x,y),vertcat(x,y)) used to be [1 0] for x==y. Now yields [0.5 0.5].
• Added AD rules for mmin/mmax
• Added logsumexp which behaves like log(sum(exp(x))) but is numerically more accurate (and no overflow issues).
• breaking vertcat/vcat,horzcat/hcat, etc now return a DM type instead of a Sparsity type #2549
• breaking CasADi-Matlab mod has been renamed to rem, because its numerical behaviour is like the builtin-Matlab rem. The builtin-Matlab mod has no CasADi counterpart. CasADi-Python mod has been removed, because its numerical behaviour is not like numpy.mod. #2767. numpy.mod has no counterpart in CasADi; only fmod is equivalent.
• DAE index reduction support (Pantelides structural algorithm) See https://github.com/casadi/casadi/blob/3.6.0/docs/examples/python/dae_reduced_index.py
• Fixed flaw in codegen with MX if_else

Common subexpression elimination

• Added Common Subexpression Elimination #1540 for MX and SX.
  CasADi can now efficiently eliminate redundant computation by inspecting an expression graph and removing redundant nodes.

Before, CasADi internals would avoid introducing redundant nodes during operations on a given expression, but the user was responsible to avoid duplication when constructing that expression.

There is a function cse() that you may apply to expressions:

x = MX.sym('x')

# User responsibility
sx = sin(x)
y = sqrt(sx)+sx # MX(@1=sin(x), (sqrt(@1)+@1))

# cse
y = sqrt(sin(x))+sin(x) # MX((sqrt(sin(x))+sin(x)))
y = cse(y) # MX(@1=sin(x), (sqrt(@1)+@1))

There is a boolean option cse that may be used when constructing a Function:

x = MX.sym('x')

f = Function('f',[x],[sqrt(sin(x))+sin(x)],{"cse":True})
f.disp(True)

f:(i0)->(o0) MXFunction
Algorithm:
@0 = input[0][0]
@0 = sin(@0)
@1 = sqrt(@0)
@1 = (@1+@0)
output[0][0] = @1

The technique scales favorably for large graphs.

Triangular solve triangular solve nodes in MX

MX how has atomic support for solving upper and lower triangular linear systems without allocating any linear solver instance. The operation handles the case with unity diagonal separately for efficiency and supports C code generation. To use the feature, call casadi.solve(A, b) (Python or MATLAB/Octave)

# Python
import casadi
A = casadi.MX.sym('A', casadi.Sparsity.upper(2))
b = casadi.MX.sym('b', 2)
x = casadi.solve(A, b)

// C++
casadi::MX A = casadi::MX::sym("A", casadi::Sparsity::upper(2));
casadi::MX b = casadi::MX::sym("b", 2);
casadi::MX x = solve(A, b);  // for argument-dependent lookup, alternatively casadi::MX::solve(A, b) for static function

Cf. #2688.

Function

• breaking SX/MX Function construction with free variables (i.e. symbols used in the output expressions that are not declared as inputs) now fails immediately unless the allow_free option is used.
• breaking SX/MX Function construction now fails if there are duplicates in input names or output names, unless the allow_duplicate_io_names option is used #2604.
• breaking Serialization: files saved with CasADi 3.5.5 will load in CasADi 3.6.0 (unittested), except for Functions that include a 'mumps' linear solver since serialization of this solver was deficient, and except for Functions that include an Integrator.
• breaking custom_jacobian semantics changed. The Function must now return individual blocks (Jacobian of an output w.r.t. to an input)
• breaking Changed API part for Jacobian sparsity (relevant for advanced use through external or Callback)

bool has_jac_sparsity(casadi_int oind, casadi_int iind) const override;
Sparsity get_jac_sparsity(casadi_int oind, casadi_int iind, bool symmetric) const override;

• Function.find_function Can be used to retrieve Functions in a hierarchy.
• Avoid truncation in printing #2452
• breaking: Function outputs that are not used (passed a null pointer internally) will be logged (dump_in option ) as nan instead of earlier 0. E.g. Ipopt nlp_grad_f has two outputs, f and grad_f_x. The f output is not used internally, so will be logged as nan.

Code-generation

• Function objects with an external call can now be codegenerated.
• mmin/mmax now support codegeneration

Solvers/plugins

• nlpsol/Opti.solver can now take an option 'detect_simple_bounds' (default False) that will promote general constraints to simple bounds (lbx/ubx).
• Added SPRAL linear solver for Ipopt
• Added QP solvers HPIPM, Proxqp, Highs
• CPLEX interface will dynamically load libcplex<CPLEX_VERSION>, where CPLEX_VERSION is read from environmental variables. Same strategy for Gurobi.
• SqpMethod Eigen-reflect/eigen-clip incorrect #2896

Generalized integrator support

The Integrator class, which solves initial-value problems in ODEs and DAEs has been thoroughly refactored. Changes include:

• The integrator class now has a much more mature support for returning the IVP solution at multiple time points. It can now be obtained by providing a time grid to the integrator constructor. Unlike before, this support should now work in combination with forward/adjoint sensitivity analysis (to any order) and sparsity pattern calculations. Cf. #2823.
• The integrator class now includes support for a piecewise constant control (u). The interface will keep track of changes to u and avoid integrating past such changes; for the Sundials (CVODES/IDAS) interfaces by setting a "stop time", for fixed step integrators by aligning the integration points with the grid points. Cf. #3025. Development versions of CasADi included support for this in a dedicated class, called Simulator, but this class has now been removed (breaking) and the functionality has been ported to the Integrator class.
  If you had code looking like cs.integrator('sim_function', 'cvodes', dae, tgrid, opts), you may replace it by cs.integrator('sim_function', 'cvodes', dae, 0, tgrid[1:], opts).
• The Integrator class now much better exploits the problem structure in the sensitivity calculations, especially adjoint (and forward-over-adjoint, adjoint-over-adjoint) sensitivity calculations. Cf. #2823, #3047. The sensitivity analysis relies to a much less extent on symbolic reformulations and instead uses calls to the Function class for derivat...

nightly-oct_compat3

Post 3.6.7

nightly-release-3.6.7

automated commit by docs target [skip ci]

nightly-se2

automated commit by docs target [skip ci]

nightly-oct_compat2

Issue #3831: relocatability fix for homebrew

nightly-graph_substitute

Issue #3831: relocatability fix for homebrew

nightly-se

issue #3807: return values of fatrop

3.6.6

Install

Grab a binary from the table:

	Windows	Linux	Mac classic (High Sierra or above)	Mac M1
Matlab	R2018b or later	R2018b or later	R2018b or later	R2020b or later (normal Matlab) R2018b or later (Open Beta/M1)
Octave	6.2.0 or later	6.2.0 or later	6.2.0 or later	6.2.0 or later
Python	pip install casadi (needs pip -V>=8.1)

For Matlab/Octave, unzip in your home directory and adapt the path:

addpath('<yourpath>/casadi-3.6.6-windows64-matlab2018b')

Check your installation:

Matlab/Octave	Python
import casadi.* x = MX.sym('x') disp(jacobian(sin(x),x))	from casadi import * x = MX.sym("x") print(jacobian(sin(x),x))

Get started with the example pack. Onboarding pointers have been gathered by the community at our wiki.

Troubleshooting

• KNITRO on linux crashes with a segmentation fault without LD_PRELOAD=<knitro_lin_path>/libiomp5.so.
• Callbacks with one argument are broken in Matlab CasADi

Release notes

Symbolic expressions

• Added SX/MX/DM operations #1595:
  • hypot(x,y) = sqrt(x*x+y*y)
  • log1p(x) = log(1+x)
  • expm1(x) = exp(x-1)
• Added operation remainder with the semantics of the C operation
• breaking AD rule of fmin/fmax` is now symmetric:
  jacobian(fmin(x,y),vertcat(x,y)) used to be [1 0] for x==y. Now yields [0.5 0.5].
• Added AD rules for mmin/mmax
• Added logsumexp which behaves like log(sum(exp(x))) but is numerically more accurate (and no overflow issues).
• breaking vertcat/vcat,horzcat/hcat, etc now return a DM type instead of a Sparsity type #2549
• breaking CasADi-Matlab mod has been renamed to rem, because its numerical behaviour is like the builtin-Matlab rem. The builtin-Matlab mod has no CasADi counterpart. CasADi-Python mod has been removed, because its numerical behaviour is not like numpy.mod. #2767. numpy.mod has no counterpart in CasADi; only fmod is equivalent.
• DAE index reduction support (Pantelides structural algorithm) See https://github.com/casadi/casadi/blob/3.6.0/docs/examples/python/dae_reduced_index.py
• Fixed flaw in codegen with MX if_else

Common subexpression elimination

• Added Common Subexpression Elimination #1540 for MX and SX.
  CasADi can now efficiently eliminate redundant computation by inspecting an expression graph and removing redundant nodes.

Before, CasADi internals would avoid introducing redundant nodes during operations on a given expression, but the user was responsible to avoid duplication when constructing that expression.

There is a function cse() that you may apply to expressions:

x = MX.sym('x')

# User responsibility
sx = sin(x)
y = sqrt(sx)+sx # MX(@1=sin(x), (sqrt(@1)+@1))

# cse
y = sqrt(sin(x))+sin(x) # MX((sqrt(sin(x))+sin(x)))
y = cse(y) # MX(@1=sin(x), (sqrt(@1)+@1))

There is a boolean option cse that may be used when constructing a Function:

x = MX.sym('x')

f = Function('f',[x],[sqrt(sin(x))+sin(x)],{"cse":True})
f.disp(True)

f:(i0)->(o0) MXFunction
Algorithm:
@0 = input[0][0]
@0 = sin(@0)
@1 = sqrt(@0)
@1 = (@1+@0)
output[0][0] = @1

The technique scales favorably for large graphs.

Triangular solve triangular solve nodes in MX

MX how has atomic support for solving upper and lower triangular linear systems without allocating any linear solver instance. The operation handles the case with unity diagonal separately for efficiency and supports C code generation. To use the feature, call casadi.solve(A, b) (Python or MATLAB/Octave)

# Python
import casadi
A = casadi.MX.sym('A', casadi.Sparsity.upper(2))
b = casadi.MX.sym('b', 2)
x = casadi.solve(A, b)

// C++
casadi::MX A = casadi::MX::sym("A", casadi::Sparsity::upper(2));
casadi::MX b = casadi::MX::sym("b", 2);
casadi::MX x = solve(A, b);  // for argument-dependent lookup, alternatively casadi::MX::solve(A, b) for static function

Cf. #2688.

Function

• breaking SX/MX Function construction with free variables (i.e. symbols used in the output expressions that are not declared as inputs) now fails immediately unless the allow_free option is used.
• breaking SX/MX Function construction now fails if there are duplicates in input names or output names, unless the allow_duplicate_io_names option is used #2604.
• breaking Serialization: files saved with CasADi 3.5.5 will load in CasADi 3.6.0 (unittested), except for Functions that include a 'mumps' linear solver since serialization of this solver was deficient, and except for Functions that include an Integrator.
• breaking custom_jacobian semantics changed. The Function must now return individual blocks (Jacobian of an output w.r.t. to an input)
• breaking Changed API part for Jacobian sparsity (relevant for advanced use through external or Callback)

bool has_jac_sparsity(casadi_int oind, casadi_int iind) const override;
Sparsity get_jac_sparsity(casadi_int oind, casadi_int iind, bool symmetric) const override;

• Function.find_function Can be used to retrieve Functions in a hierarchy.
• Avoid truncation in printing #2452
• breaking: Function outputs that are not used (passed a null pointer internally) will be logged (dump_in option ) as nan instead of earlier 0. E.g. Ipopt nlp_grad_f has two outputs, f and grad_f_x. The f output is not used internally, so will be logged as nan.

Code-generation

• Function objects with an external call can now be codegenerated.
• mmin/mmax now support codegeneration

Solvers/plugins

• nlpsol/Opti.solver can now take an option 'detect_simple_bounds' (default False) that will promote general constraints to simple bounds (lbx/ubx).
• Added SPRAL linear solver for Ipopt
• Added QP solvers HPIPM, Proxqp, Highs
• CPLEX interface will dynamically load libcplex<CPLEX_VERSION>, where CPLEX_VERSION is read from environmental variables. Same strategy for Gurobi.
• SqpMethod Eigen-reflect/eigen-clip incorrect #2896

Generalized integrator support

The Integrator class, which solves initial-value problems in ODEs and DAEs has been thoroughly refactored. Changes include:

• The integrator class now has a much more mature support for returning the IVP solution at multiple time points. It can now be obtained by providing a time grid to the integrator constructor. Unlike before, this support should now work in combination with forward/adjoint sensitivity analysis (to any order) and sparsity pattern calculations. Cf. #2823.
• The integrator class now includes support for a piecewise constant control (u). The interface will keep track of changes to u and avoid integrating past such changes; for the Sundials (CVODES/IDAS) interfaces by setting a "stop time", for fixed step integrators by aligning the integration points with the grid points. Cf. #3025. Development versions of CasADi included support for this in a dedicated class, called Simulator, but this class has now been removed (breaking) and the functionality has been ported to the Integrator class.
  If you had code looking like cs.integrator('sim_function', 'cvodes', dae, tgrid, opts), you may replace it by cs.integrator('sim_function', 'cvodes', dae, 0, tgrid[1:], opts).
• The Integrator class now much better exploits the problem structure in the sensitivity calculations, especially adjoint (and forward-over-adjoint, adjoint-over-adjoint) sensitivity calculations. Cf. #2823, #3047. The sensitivity analysis relies to a much less extent on...

nightly-plugin_madnlp2

automated commit by docs target [skip ci]

nightly-basemodelica

Adding bfgs to sqpmethod codegen