scipy.optimize (partial)

scipy-stubs/_typing.pyi

@@ -17,6 +17,7 @@ __all__ = [
     "AnyScalar",
     "AnyShape",
     "Array0D",
+    "Casting",
     "CorrelateMode",
     "NanPolicy",
     "Seed",
@@ -54,6 +55,7 @@ AnyShape: TypeAlias = op.CanIndex | Sequence[op.CanIndex]
 # numpy literals
 RNG: TypeAlias = np.random.Generator | np.random.RandomState
 Seed: TypeAlias = int | RNG
+Casting: TypeAlias = Literal["no", "equiv", "safe", "same_kind", "unsafe"]
 CorrelateMode: TypeAlias = Literal["valid", "same", "full"]
 
 # scipy literals

scipy-stubs/optimize/_constraints.pyi

@@ -1,19 +1,7 @@
-from scipy._typing import Untyped
-
-__all__ = (
-    "Bounds",
-    "LinearConstraint",
-    "NonlinearConstraint",
-    "PreparedConstraint",
-    "new_bounds_to_old",
-    "new_constraint_to_old",
-    "old_bound_to_new",
-    "old_constraint_to_new",
-    "strict_bounds",
-)
+from scipy._typing import Untyped, UntypedCallable
 
 class NonlinearConstraint:
-    fun: Untyped
+    fun: UntypedCallable
     lb: Untyped
     ub: Untyped
     finite_diff_rel_step: Untyped
@@ -23,40 +11,48 @@ class NonlinearConstraint:
     keep_feasible: Untyped
     def __init__(
         self,
-        fun,
-        lb,
-        ub,
+        /,
+        fun: UntypedCallable,
+        lb: Untyped,
+        ub: Untyped,
         jac: str = "2-point",
-        hess: Untyped | None = None,
+        hess: Untyped = ...,
         keep_feasible: bool = False,
         finite_diff_rel_step: Untyped | None = None,
         finite_diff_jac_sparsity: Untyped | None = None,
-    ): ...
+    ) -> None: ...
 
 class LinearConstraint:
     A: Untyped
     lb: Untyped
     ub: Untyped
     keep_feasible: Untyped
-    def __init__(self, A, lb=..., ub=..., keep_feasible: bool = False): ...
-    def residual(self, x) -> Untyped: ...
+    def __init__(self, /, A: Untyped, lb: Untyped = ..., ub: Untyped = ..., keep_feasible: bool = False) -> None: ...
+    def residual(self, /, x: Untyped) -> Untyped: ...
 
 class Bounds:
     lb: Untyped
     ub: Untyped
     keep_feasible: Untyped
-    def __init__(self, lb=..., ub=..., keep_feasible: bool = False): ...
-    def residual(self, x) -> Untyped: ...
+    def __init__(self, /, lb: Untyped = ..., ub: Untyped = ..., keep_feasible: bool = False) -> None: ...
+    def residual(self, /, x: Untyped) -> Untyped: ...
 
 class PreparedConstraint:
     fun: Untyped
     bounds: Untyped
     keep_feasible: Untyped
-    def __init__(self, constraint, x0, sparse_jacobian: Untyped | None = None, finite_diff_bounds=...): ...
-    def violation(self, x) -> Untyped: ...
+    def __init__(
+        self,
+        /,
+        constraint: Untyped,
+        x0: Untyped,
+        sparse_jacobian: Untyped | None = None,
+        finite_diff_bounds: Untyped = ...,
+    ) -> None: ...
+    def violation(self, x: Untyped) -> Untyped: ...
 
-def new_bounds_to_old(lb, ub, n) -> Untyped: ...
-def old_bound_to_new(bounds) -> Untyped: ...
-def strict_bounds(lb, ub, keep_feasible, n_vars) -> Untyped: ...
-def new_constraint_to_old(con, x0) -> Untyped: ...
-def old_constraint_to_new(ic, con) -> Untyped: ...
+def new_bounds_to_old(lb: Untyped, ub: Untyped, n: Untyped) -> Untyped: ...
+def old_bound_to_new(bounds: Untyped) -> Untyped: ...
+def strict_bounds(lb: Untyped, ub: Untyped, keep_feasible: Untyped, n_vars: Untyped) -> Untyped: ...
+def new_constraint_to_old(con: Untyped, x0: Untyped) -> Untyped: ...
+def old_constraint_to_new(ic: Untyped, con: Untyped) -> Untyped: ...

scipy-stubs/optimize/_group_columns.pyi

@@ -1,4 +1,9 @@
+from typing import Final
+from typing_extensions import LiteralString
+
 from scipy._typing import Untyped
 
-def group_dense(m, n, A) -> Untyped: ...
-def group_sparse(m, n, indices, indptr) -> Untyped: ...
+__pythran__: Final[tuple[LiteralString, LiteralString]]
+
+def group_dense(m: Untyped, n: Untyped, A: Untyped) -> Untyped: ...
+def group_sparse(m: Untyped, n: Untyped, indices: Untyped, indptr: Untyped) -> Untyped: ...

scipy-stubs/optimize/_hessian_update_strategy.pyi

@@ -1,32 +1,40 @@
-from scipy._typing import Untyped
-from scipy.linalg import get_blas_funcs as get_blas_funcs, issymmetric as issymmetric
+from typing import Final, Literal
+
+from scipy._typing import Untyped, UntypedArray
+
+__all__ = ["BFGS", "SR1", "HessianUpdateStrategy"]
 
 class HessianUpdateStrategy:
-    def initialize(self, n, approx_type): ...
-    def update(self, delta_x, delta_grad): ...
-    def dot(self, p): ...
-    def get_matrix(self): ...
+    def initialize(self, /, n: int, approx_type: Literal["hess", "inv_hess"]) -> None: ...
+    def update(self, /, delta_x: UntypedArray, delta_grad: UntypedArray) -> None: ...
+    def dot(self, /, p: Untyped) -> UntypedArray: ...
+    def get_matrix(self, /) -> UntypedArray: ...
 
 class FullHessianUpdateStrategy(HessianUpdateStrategy):
     init_scale: Untyped
     first_iteration: Untyped
     approx_type: Untyped
     B: Untyped
     H: Untyped
-    def __init__(self, init_scale: str = "auto"): ...
     n: Untyped
-    def initialize(self, n, approx_type): ...
-    def update(self, delta_x, delta_grad): ...
-    def dot(self, p) -> Untyped: ...
-    def get_matrix(self) -> Untyped: ...
+    def __init__(self, /, init_scale: Literal["auto"] | float | UntypedArray = "auto") -> None: ...
 
 class BFGS(FullHessianUpdateStrategy):
-    min_curvature: Untyped
-    exception_strategy: Untyped
+    min_curvature: Final[float]
+    exception_strategy: Final[Literal["skip_update", "damp_update"]]
     def __init__(
-        self, exception_strategy: str = "skip_update", min_curvature: Untyped | None = None, init_scale: str = "auto"
-    ): ...
+        self,
+        /,
+        exception_strategy: Literal["skip_update", "damp_update"] = "skip_update",
+        min_curvature: float | None = None,
+        init_scale: Literal["auto"] | float | UntypedArray = "auto",
+    ) -> None: ...
 
 class SR1(FullHessianUpdateStrategy):
-    min_denominator: Untyped
-    def __init__(self, min_denominator: float = 1e-08, init_scale: str = "auto"): ...
+    min_denominator: Final[float]
+    def __init__(
+        self,
+        /,
+        min_denominator: float = 1e-08,
+        init_scale: Literal["auto"] | float | UntypedArray = "auto",
+    ) -> None: ...

scipy-stubs/optimize/_lbfgsb_py.pyi

@@ -1,7 +1,5 @@
 from scipy._typing import Untyped
-from scipy.sparse.linalg import LinearOperator as LinearOperator
-from ._constraints import old_bound_to_new as old_bound_to_new
-from ._optimize import MemoizeJac as MemoizeJac, OptimizeResult as OptimizeResult
+from scipy.sparse.linalg import LinearOperator
 
 def fmin_l_bfgs_b(
     func,

scipy-stubs/optimize/_linesearch.pyi

@@ -1,26 +1,34 @@
-from scipy._typing import Untyped
-from ._dcsrch import DCSRCH as DCSRCH
+from scipy._typing import Untyped, UntypedCallable
+
+__all__ = [
+    "LineSearchWarning",
+    "line_search_armijo",
+    "line_search_wolfe1",
+    "line_search_wolfe2",
+    "scalar_search_wolfe1",
+    "scalar_search_wolfe2",
+]
 
 class LineSearchWarning(RuntimeWarning): ...
 
 def line_search_wolfe1(
-    f,
-    fprime,
-    xk,
-    pk,
+    f: UntypedCallable,
+    fprime: Untyped,
+    xk: Untyped,
+    pk: Untyped,
     gfk: Untyped | None = None,
     old_fval: Untyped | None = None,
     old_old_fval: Untyped | None = None,
-    args=(),
+    args: Untyped = (),
     c1: float = 0.0001,
     c2: float = 0.9,
     amax: int = 50,
     amin: float = 1e-08,
     xtol: float = 1e-14,
 ) -> Untyped: ...
 def scalar_search_wolfe1(
-    phi,
-    derphi,
+    phi: Untyped,
+    derphi: Untyped,
     phi0: Untyped | None = None,
     old_phi0: Untyped | None = None,
     derphi0: Untyped | None = None,
@@ -34,23 +42,23 @@ def scalar_search_wolfe1(
 line_search = line_search_wolfe1
 
 def line_search_wolfe2(
-    f,
-    myfprime,
-    xk,
-    pk,
+    f: UntypedCallable,
+    myfprime: Untyped,
+    xk: Untyped,
+    pk: Untyped,
     gfk: Untyped | None = None,
     old_fval: Untyped | None = None,
     old_old_fval: Untyped | None = None,
-    args=(),
+    args: Untyped = (),
     c1: float = 0.0001,
     c2: float = 0.9,
     amax: Untyped | None = None,
     extra_condition: Untyped | None = None,
     maxiter: int = 10,
 ) -> Untyped: ...
 def scalar_search_wolfe2(
-    phi,
-    derphi,
+    phi: Untyped,
+    derphi: Untyped,
     phi0: Untyped | None = None,
     old_phi0: Untyped | None = None,
     derphi0: Untyped | None = None,
@@ -60,6 +68,31 @@ def scalar_search_wolfe2(
     extra_condition: Untyped | None = None,
     maxiter: int = 10,
 ) -> Untyped: ...
-def line_search_armijo(f, xk, pk, gfk, old_fval, args=(), c1: float = 0.0001, alpha0: int = 1) -> Untyped: ...
-def line_search_BFGS(f, xk, pk, gfk, old_fval, args=(), c1: float = 0.0001, alpha0: int = 1) -> Untyped: ...
-def scalar_search_armijo(phi, phi0, derphi0, c1: float = 0.0001, alpha0: int = 1, amin: int = 0) -> Untyped: ...
+def line_search_armijo(
+    f: UntypedCallable,
+    xk: Untyped,
+    pk: Untyped,
+    gfk: Untyped,
+    old_fval: Untyped,
+    args: Untyped = (),
+    c1: float = 0.0001,
+    alpha0: int = 1,
+) -> Untyped: ...
+def line_search_BFGS(
+    f: UntypedCallable,
+    xk: Untyped,
+    pk: Untyped,
+    gfk: Untyped,
+    old_fval: Untyped,
+    args: Untyped = (),
+    c1: float = 0.0001,
+    alpha0: int = 1,
+) -> Untyped: ...
+def scalar_search_armijo(
+    phi: Untyped,
+    phi0: Untyped,
+    derphi0: Untyped,
+    c1: float = 0.0001,
+    alpha0: int = 1,
+    amin: int = 0,
+) -> Untyped: ...

scipy-stubs/optimize/_linprog.pyi

@@ -1,21 +1,30 @@
-from scipy._typing import Untyped
-from ._optimize import OptimizeResult as OptimizeResult, OptimizeWarning as OptimizeWarning
+from collections.abc import Callable, Mapping, Sequence
+from typing import Final
 
-__docformat__: str
-LINPROG_METHODS: Untyped
+import numpy.typing as npt
+from ._optimize import OptimizeResult
+from ._typing import Bound, MethodLinprog
 
-def linprog_verbose_callback(res) -> Untyped: ...
-def linprog_terse_callback(res): ...
+__all__ = ["linprog", "linprog_terse_callback", "linprog_verbose_callback"]
+
+__docformat__: Final[str] = ...
+LINPROG_METHODS: Final[Sequence[MethodLinprog]] = ...
+
+def linprog_verbose_callback(res: OptimizeResult) -> None: ...
+def linprog_terse_callback(res: OptimizeResult) -> None: ...
+
+# TODO: Tighen these array-like types
 def linprog(
-    c,
-    A_ub: Untyped | None = None,
-    b_ub: Untyped | None = None,
-    A_eq: Untyped | None = None,
-    b_eq: Untyped | None = None,
-    bounds=(0, None),
-    method: str = "highs",
-    callback: Untyped | None = None,
-    options: Untyped | None = None,
-    x0: Untyped | None = None,
-    integrality: Untyped | None = None,
-) -> Untyped: ...
+    c: npt.ArrayLike,
+    A_ub: npt.ArrayLike | None = None,
+    b_ub: npt.ArrayLike | None = None,
+    A_eq: npt.ArrayLike | None = None,
+    b_eq: npt.ArrayLike | None = None,
+    bounds: Bound = (0, None),
+    method: MethodLinprog = "highs",
+    callback: Callable[[OptimizeResult], None] | None = None,
+    # TODO: `TypedDict`
+    options: Mapping[str, object] | None = None,
+    x0: npt.ArrayLike | None = None,
+    integrality: npt.ArrayLike | None = None,
+) -> OptimizeResult: ...

scipy-stubs/optimize/_linprog_highs.pyi

@@ -0,0 +1 @@
+# nothing to see here

scipy-stubs/optimize/_linprog_ip.pyi

@@ -1,5 +1,2 @@
-from scipy.linalg import LinAlgError as LinAlgError
-from ._optimize import OptimizeResult as OptimizeResult, OptimizeWarning as OptimizeWarning
-
 has_umfpack: bool
 has_cholmod: bool

scipy-stubs/optimize/_linprog_rs.pyi

@@ -0,0 +1 @@
+# nothing to see here

scipy-stubs/optimize/_linprog_simplex.pyi

@@ -1 +1 @@
-from ._optimize import OptimizeResult as OptimizeResult, OptimizeWarning as OptimizeWarning
+# nothing to see here