Ipopt

(class from pyomo.contrib.solver.ipopt)

class pyomo.contrib.solver.ipopt.Ipopt(**kwds)[source]

Bases: SolverBase

__init__(**kwds)[source]

Methods

__init__(**kwds)

available([config])

Test if the solver is available on this system.

has_linear_solver(linear_solver)

is_persistent()

solve(model, **kwds)

Solve a model using Ipopt

version([config])

Attributes

CONFIG

name

Member Documentation

enum Availability(value)

Bases: IntEnum

Class to capture different statuses in which a solver can exist in order to record its availability for use.

as_integer_ratio()

Return integer ratio.

Return a pair of integers, whose ratio is exactly equal to the original int and with a positive denominator.

>>> (10).as_integer_ratio()
(10, 1)
>>> (-10).as_integer_ratio()
(-10, 1)
>>> (0).as_integer_ratio()
(0, 1)
bit_count()

Number of ones in the binary representation of the absolute value of self.

Also known as the population count.

>>> bin(13)
'0b1101'
>>> (13).bit_count()
3
bit_length()

Number of bits necessary to represent self in binary.

>>> bin(37)
'0b100101'
>>> (37).bit_length()
6
conjugate()

Returns self, the complex conjugate of any int.

classmethod from_bytes(bytes, byteorder='big', *, signed=False)

Return the integer represented by the given array of bytes.

bytes

Holds the array of bytes to convert. The argument must either support the buffer protocol or be an iterable object producing bytes. Bytes and bytearray are examples of built-in objects that support the buffer protocol.

byteorder

The byte order used to represent the integer. If byteorder is ‘big’, the most significant byte is at the beginning of the byte array. If byteorder is ‘little’, the most significant byte is at the end of the byte array. To request the native byte order of the host system, use sys.byteorder as the byte order value. Default is to use ‘big’.

signed

Indicates whether two’s complement is used to represent the integer.

to_bytes(length=1, byteorder='big', *, signed=False)

Return an array of bytes representing an integer.

length

Length of bytes object to use. An OverflowError is raised if the integer is not representable with the given number of bytes. Default is length 1.

byteorder

The byte order used to represent the integer. If byteorder is ‘big’, the most significant byte is at the beginning of the byte array. If byteorder is ‘little’, the most significant byte is at the end of the byte array. To request the native byte order of the host system, use sys.byteorder as the byte order value. Default is to use ‘big’.

signed

Determines whether two’s complement is used to represent the integer. If signed is False and a negative integer is given, an OverflowError is raised.

denominator

the denominator of a rational number in lowest terms

imag

the imaginary part of a complex number

numerator

the numerator of a rational number in lowest terms

real

the real part of a complex number

available(config=None)[source]

Test if the solver is available on this system.

Nominally, this will return True if the solver interface is valid and can be used to solve problems and False if it cannot.

Note that for licensed solvers there are a number of “levels” of available: depending on the license, the solver may be available with limitations on problem size or runtime (e.g., ‘demo’ vs. ‘community’ vs. ‘full’). In these cases, the solver may return a subclass of enum.IntEnum, with members that resolve to True if the solver is available (possibly with limitations). The Enum may also have multiple members that all resolve to False indicating the reason why the interface is not available (not found, bad license, unsupported version, etc).

Returns:

available – An enum that indicates “how available” the solver is. Note that the enum can be cast to bool, which will be True if the solver is runable at all and False otherwise.

Return type:

SolverBase.Availability

is_persistent() → bool
Returns:

is_persistent – True if the solver is a persistent solver.

Return type:

bool

solve(model, **kwds)[source]

Solve a model using Ipopt

Keyword Arguments:

  • tee (TextIO_or_Logger, default=False) – tee accepts bool, io.TextIOBase, or logging.Logger (or a list of these types). True is mapped to sys.stdout. The solver log will be printed to each of these streams / destinations.

  • working_dir (Path, optional) – The directory in which generated files should be saved. This replaces the keepfiles option.

  • load_solutions (Bool, default=True) – If True, the values of the primal variables will be loaded into the model.

  • raise_exception_on_nonoptimal_result (Bool, default=True) – If False, the solve method will continue processing even if the returned result is nonoptimal.

  • symbolic_solver_labels (Bool, default=False) – If True, the names given to the solver will reflect the names of the Pyomo components. Cannot be changed after set_instance is called.

  • timer (optional) – A timer object for recording relevant process timing data.

  • threads (NonNegativeInt, optional) – Number of threads to be used by a solver.

  • time_limit (NonNegativeFloat, optional) – Time limit applied to the solver (in seconds).

  • solver_options (dict, optional) – Options to pass to the solver.

  • executable (default=<pyomo.common.fileutils.ExecutableData object at 0x7f3061b29850>) – Preferred executable for ipopt. Defaults to searching the PATH for the first available ipopt.

  • writer_config (dict, optional) –

    nlwriter

    show_section_timing: bool, default=False

    Print timing after writing each section of the NL file

    skip_trivial_constraints: bool, default=True

    Skip writing constraints whose body is constant

    file_determinism: InEnum[~pyomo.repn.util.FileDeterminism], default=<FileDeterminism.ORDERED: 10>

    How much effort do we want to put into ensuring the NL file is written deterministically for a Pyomo model:

    • NONE (0) : None

    • ORDERED (10): rely on underlying component ordering (default)

    • SORT_INDICES (20) : sort keys of indexed components

    • SORT_SYMBOLS (30) : sort keys AND sort names (not declaration order)

    symbolic_solver_labels: bool, default=False

    Write the corresponding .row and .col files

    scale_model: bool, default=True

    If True, then the writer will output the model constraints and variables in ‘scaled space’ using the scaling from the ‘scaling_factor’ Suffix, if provided.

    export_nonlinear_variables: list, optional

    List of variables to ensure are in the NL file (even if they don’t appear in any constraints).

    row_order: optional

    List of constraints in the order that they should appear in the NL file. Note that this is only a suggestion, as the NL writer will move all nonlinear constraints before linear ones (preserving row_order within each group).

    column_order: optional

    List of variables in the order that they should appear in the NL file. Note that this is only a suggestion, as the NL writer will move all nonlinear variables before linear ones, and within nonlinear variables, variables appearing in both objectives and constraints before variables appearing only in constraints, which appear before variables appearing only in objectives. Within each group, continuous variables appear before discrete variables. In all cases, column_order is preserved within each group.

    export_defined_variables: bool, default=True

    If True, export Expression objects to the NL file as ‘defined variables’.

    linear_presolve: bool, default=True

    If True, we will perform a basic linear presolve by performing variable elimination (without fill-in).

version(config=None)[source]
Returns:

version – A tuple representing the version

Return type:

tuple

CONFIG = <pyomo.contrib.solver.ipopt.IpoptConfig object>