Source code for pyomo.contrib.pynumero.linalg.ma27

#  ___________________________________________________________________________
#  Pyomo: Python Optimization Modeling Objects
#  Copyright 2017 National Technology and Engineering Solutions of Sandia, LLC
#  Under the terms of Contract DE-NA0003525 with National Technology and
#  Engineering Solutions of Sandia, LLC, the U.S. Government retains certain
#  rights in this software.
#  This software is distributed under the 3-clause BSD License.
#  ___________________________________________________________________________
from pyomo.common.fileutils import find_library
from pyomo.contrib.pynumero.linalg.utils import (validate_index,
        validate_value, _NotSet)
import numpy.ctypeslib as npct
import numpy as np
import ctypes 
import os

[docs]class MA27Interface(object): libname = _NotSet
[docs] @classmethod def available(cls): if cls.libname is _NotSet: cls.libname = find_library('pynumero_MA27') if cls.libname is None: return False return os.path.exists(cls.libname)
def __init__(self, iw_factor=None, a_factor=None): if not MA27Interface.available(): raise RuntimeError( 'Could not find pynumero_MA27 library.') self.iw_factor = iw_factor self.a_factor = a_factor self._dim_cached = None self.lib = ctypes.cdll.LoadLibrary(self.libname) array_1d_double = npct.ndpointer(dtype=np.double, ndim=1, flags='CONTIGUOUS') array_2d_double = npct.ndpointer(dtype=np.double, ndim=2, flags='CONTIGUOUS') array_1d_int = npct.ndpointer(dtype=np.intc, ndim=1, flags='CONTIGUOUS') # Declare arg and res types of functions: # Do I need to specify that this function takes no argument? self.lib.new_MA27_struct.restype = ctypes.c_void_p self.lib.free_MA27_struct.argtypes = [ctypes.c_void_p] self.lib.set_icntl.argtypes = [ctypes.c_void_p, ctypes.c_int, ctypes.c_int] # Do I need to specify that this function returns nothing? self.lib.get_icntl.argtypes = [ctypes.c_void_p, ctypes.c_int] self.lib.get_icntl.restype = ctypes.c_int self.lib.set_cntl.argtypes = [ctypes.c_void_p, ctypes.c_int, ctypes.c_double] self.lib.get_cntl.argtypes = [ctypes.c_void_p, ctypes.c_int] self.lib.get_cntl.restype = ctypes.c_double self.lib.get_info.argtypes = [ctypes.c_void_p, ctypes.c_int] self.lib.get_info.restype = ctypes.c_int self.lib.alloc_iw_a.argtypes = [ctypes.c_void_p, ctypes.c_int] self.lib.alloc_iw_b.argtypes = [ctypes.c_void_p, ctypes.c_int] self.lib.alloc_a.argtypes = [ctypes.c_void_p, ctypes.c_int] self.lib.do_symbolic_factorization.argtypes = [ctypes.c_void_p, ctypes.c_int, ctypes.c_int, array_1d_int, array_1d_int] self.lib.do_numeric_factorization.argtypes = [ctypes.c_void_p, ctypes.c_int, ctypes.c_int, array_1d_int, array_1d_int, array_1d_double] self.lib.do_backsolve.argtypes = [ctypes.c_void_p, ctypes.c_int, array_1d_double] self.icntl_len = 30 self.cntl_len = 5 self.info_len = 20 self._ma27 = self.lib.new_MA27_struct() def __del__(self): self.lib.free_MA27_struct(self._ma27)
[docs] def set_icntl(self, i, val): validate_index(i, self.icntl_len, 'ICNTL') validate_value(i, int, 'ICNTL') # NOTE: Use the FORTRAN indexing (same as documentation) to # set and access info/cntl arrays from Python, whereas C # functions use C indexing. Maybe this is too confusing. self.lib.set_icntl(self._ma27, i-1, val)
[docs] def get_icntl(self, i): validate_index(i, self.icntl_len, 'ICNTL') return self.lib.get_icntl(self._ma27, i-1)
[docs] def set_cntl(self, i, val): validate_index(i, self.cntl_len, 'CNTL') validate_value(val, float, 'CNTL') self.lib.set_cntl(self._ma27, i-1, val)
[docs] def get_cntl(self, i): validate_index(i, self.cntl_len, 'CNTL') return self.lib.get_cntl(self._ma27, i-1)
[docs] def get_info(self, i): validate_index(i, self.info_len, 'INFO') return self.lib.get_info(self._ma27, i-1)
[docs] def do_symbolic_factorization(self, dim, irn, icn): irn = irn.astype(np.intc, casting='safe', copy=True) icn = icn.astype(np.intc, casting='safe', copy=True) ne = irn.size self._dim_cached = dim assert ne == icn.size, 'Dimension mismatch in row and column arrays' if self.iw_factor is not None: min_size = 2*ne + 3*dim + 1 self.lib.alloc_iw_a(self._ma27, int(self.iw_factor*min_size)) self.lib.do_symbolic_factorization(self._ma27, dim, ne, irn, icn) return self.get_info(1)
[docs] def do_numeric_factorization(self, irn, icn, dim, entries): irn = irn.astype(np.intc, casting='safe', copy=True) icn = icn.astype(np.intc, casting='safe', copy=True) ent = entries.astype(np.double, casting='safe', copy=True) ne = ent.size assert dim == self._dim_cached,\ ('Dimension mismatch between symbolic and numeric factorization.' 'Please re-run symbolic factorization with the correct ' 'dimension.') if self.a_factor is not None: min_size = self.get_info(5) self.lib.alloc_a(self._ma27, int(self.a_factor*min_size)) if self.iw_factor is not None: min_size = self.get_info(6) self.lib.alloc_iw_b(self._ma27, int(self.iw_factor*min_size)) self.lib.do_numeric_factorization(self._ma27, dim, ne, irn, icn, ent) return self.get_info(1)
[docs] def do_backsolve(self, rhs): rhs = rhs.astype(np.double, casting='safe', copy=True) rhs_dim = rhs.size assert rhs_dim == self._dim_cached,\ 'Dimension mismatch in right hand side. Please correct.' self.lib.do_backsolve(self._ma27, rhs_dim, rhs) return rhs