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Import MemoizeJac from scipy.optimize._optimize. #183

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Feb 13, 2023
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Import MemoizeJac from scipy.optimize._optimize. #183

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11 changes: 6 additions & 5 deletions cyipopt/scipy_interface.py
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Original file line number Diff line number Diff line change
Expand Up @@ -28,9 +28,10 @@
from scipy.optimize import Result
OptimizeResult = Result
try:
from scipy.optimize import MemoizeJac
# MemoizeJac has been made a private class, see
# https://github.com/scipy/scipy/issues/17572
from scipy.optimize._optimize import MemoizeJac
except ImportError:
# The optimize.optimize namespace is being deprecated
from scipy.optimize.optimize import MemoizeJac
try:
from scipy.sparse import coo_array
Expand Down Expand Up @@ -67,18 +68,18 @@ class IpoptProblemWrapper(object):
constraints : {Constraint, dict} or List of {Constraint, dict}, optional
See https://docs.scipy.org/doc/scipy/reference/generated/scipy.optimize.minimize.html
for more information. Note that the jacobian of each constraint
corresponds to the `'jac'` key and must be a callable function
corresponds to the `'jac'` key and must be a callable function
with signature ``jac(x) -> {ndarray, coo_array}``. If the constraint's
value of `'jac'` is a boolean and True, the constraint function `fun`
is expected to return a tuple `(con_val, con_jac)` consisting of the
is expected to return a tuple `(con_val, con_jac)` consisting of the
evaluated constraint `con_val` and the evaluated jacobian `con_jac`.
eps : float, optional
Epsilon used in finite differences.
con_dims : array_like, optional
Dimensions p_1, ..., p_m of the m constraint functions
g_1, ..., g_m : R^n -> R^(p_i).
sparse_jacs: array_like, optional
If sparse_jacs[i] = True, the i-th constraint's jacobian is sparse.
If sparse_jacs[i] = True, the i-th constraint's jacobian is sparse.
Otherwise, the i-th constraint jacobian is assumed to be dense.
jac_nnz_row: array_like, optional
The row indices of the nonzero elements in the stacked
Expand Down