def norm2diff_id_matrix(mvma, a, solveb, solvetransb, b,
rows: int, cols: int) -> float:
cmvma = libkrylov.CFuncMvmT(mvma)
ca = a.as_voidp()
csolveb = libkrylov.CFuncPrcdT(solveb)
csolvetransb = libkrylov.CFuncPrcdT(solvetransb)
cb = b.as_voidp()
return libkrylov.norm2diff_id_pre_matrix(cmvma, ca, csolveb, csolvetransb,
cb, rows, cols)
def norm2diff_pre_matrix(mvma, a, evalb, evaltransb, b,
rows: int, cols: int) -> float:
cmvma = libkrylov.CFuncMvmT(mvma)
ca = a.as_voidp()
cevalb = libkrylov.CFuncPrcdT(evalb)
cevaltransb = libkrylov.CFuncPrcdT(evaltransb)
cb = b.as_voidp()
return libkrylov.norm2diff_pre_matrix(cmvma, ca, cevalb, cevaltransb, cb,
rows, cols)
def step_uzawa(solve_a11, matrix_a11, mvm_a21, matrix_a21, b1: 'vec.AVector',
b2: 'vec.AVector', x1: 'vec.AVector', x2: 'vec.AVector',
r2: 'vec.AVector', p2: 'vec.AVector', a1: 'vec.AVector',
s2: 'vec.AVector'):
csolvea11 = libkrylov.CFuncPrcdT(solve_a11)
cmatrixa11 = matrix_a11.as_voidp()
cmvma21 = libkrylov.CFuncMvmT(mvm_a21)
cmatrixa21 = matrix_a21.as_voidp()
libkrylov.step_uzawa(csolvea11, cmatrixa11, cmvma21, cmatrixa21,
b1, b2, x1, x2, r2, p2, a1, s2)
def step_puzawa(solve_a11, matrix_a11, mvm_a21, matrix_a21, prcd, pdata,
b1: 'vec.AVector', b2: 'vec.AVector', x1: 'vec.AVector',
x2: 'vec.AVector', r2: 'vec.AVector', q2: 'vec.AVector',
p2: 'vec.AVector', a1: 'vec.AVector', s2: 'vec.AVector'):
csolvea11 = libkrylov.CFuncPrcdT(solve_a11)
cmatrixa11 = matrix_a11.as_voidp()
cmvma21 = libkrylov.CFuncMvmT(mvm_a21)
cmatrixa21 = matrix_a21.as_voidp()
cprcd = libkrylov.CFuncPrcdT(prcd)
cpdata = cast(pdata, c_void_p)
libkrylov.step_puzawa(csolvea11, cmatrixa11, cmvma21, cmatrixa21, cprcd,
cpdata, b1, b2, x1, x2, r2, q2, p2, a1, s2)
def norm2_matrix(mvm, a, rows: int, cols: int) -> float:
cmvm = libkrylov.CFuncMvmT(mvm)
ca = cast(a, c_void_p)
return libkrylov.norm2_matrix(cmvm, ca, rows, cols)
def norm2diff_matrix(mvma, a, mvmb, b, rows: int, cols: int) -> float:
cmvma = libkrylov.CFuncMvmT(mvma)
ca = a.as_voidp()
cmvmb = libkrylov.CFuncMvmT(mvmb)
cb = b.as_voidp()
return libkrylov.norm2diff_matrix(cmvma, ca, cmvmb, cb, rows, cols)