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depend on meanas instad of fdfd_tools

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This commit is contained in:
Jan Petykiewicz 2021-07-11 17:07:46 -07:00
parent 792b161753
commit 5861767a00
1 changed files with 8 additions and 8 deletions
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8
opencl_fdfd/csr.py
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@ -6,7 +6,7 @@ CSRMatrix sparse matrix representation.
The FDFD solver (fdfd_cg_solver()) solves an FDFD problem by
creating a sparse matrix representing the problem (using
fdfd_tools) and then passing it to cg(), which performs a
meanas) and then passing it to cg(), which performs a
conjugate gradient solve.
cg() is capable of solving arbitrary sparse matrices which
@ -23,7 +23,7 @@ from numpy.linalg import norm
import pyopencl
import pyopencl.array
import fdfd_tools.solvers
import meanas.fdfd.solvers
from . import ops
@ -158,7 +158,7 @@ def fdfd_cg_solver(solver_opts: Dict[str, Any] = None,
Conjugate gradient FDFD solver using CSR sparse matrices, mainly for
testing and development since it's much slower than the solver in main.py.
Calls fdfd_tools.solvers.generic(**fdfd_args,
Calls meanas.fdfd.solvers.generic(**fdfd_args,
matrix_solver=opencl_fdfd.csr.cg,
matrix_solver_opts=solver_opts)
@ -172,7 +172,7 @@ def fdfd_cg_solver(solver_opts: Dict[str, Any] = None,
if solver_opts is None:
solver_opts = dict()
x = fdfd_tools.solvers.generic(matrix_solver=cg,
x = meanas.fdfd.solvers.generic(matrix_solver=cg,
matrix_solver_opts=solver_opts,
**fdfd_args)