def __init__(self, ops, nproc=1, dtype=None):
self.ops = ops
nops = np.zeros(len(self.ops), dtype=int)
for iop, oper in enumerate(ops):
if not isinstance(oper, (LinearOperator, spLinearOperator)):
self.ops[iop] = MatrixMult(oper, dtype=oper.dtype)
nops[iop] = self.ops[iop].shape[0]
self.nops = int(nops.sum())
mops = [oper.shape[1] for oper in self.ops]
if len(set(mops)) > 1:
raise ValueError("operators have different number of columns")
self.mops = int(mops[0])
self.nnops = np.insert(np.cumsum(nops), 0, 0)
# create pool for multiprocessing
self._nproc = nproc
self.pool = None
if self.nproc > 1:
self.pool = mp.Pool(processes=nproc)
self.shape = (self.nops, self.mops)
if dtype is None:
self.dtype = _get_dtype(self.ops)
else:
self.dtype = np.dtype(dtype)
self.explicit = False
self.clinear = all(
[getattr(oper, "clinear", True) for oper in self.ops])
def __init__(self, ops, nproc=1, dtype=None):
self.ops = ops
mops = np.zeros(len(ops), dtype=np.int)
nops = np.zeros(len(ops), dtype=np.int)
for iop, oper in enumerate(ops):
if not isinstance(oper, (LinearOperator, spLinearOperator)):
self.ops[iop] = MatrixMult(oper, dtype=oper.dtype)
nops[iop] = self.ops[iop].shape[0]
mops[iop] = self.ops[iop].shape[1]
self.nops = int(nops.sum())
self.mops = int(mops.sum())
self.nnops = np.insert(np.cumsum(nops), 0, 0)
self.mmops = np.insert(np.cumsum(mops), 0, 0)
# create pool for multiprocessing
self._nproc = nproc
self.pool = None
if self.nproc > 1:
self.pool = mp.Pool(processes=nproc)
self.shape = (self.nops, self.mops)
if dtype is None:
self.dtype = _get_dtype(ops)
else:
self.dtype = np.dtype(dtype)
self.explicit = False
self.clinear = all(
[getattr(oper, 'clinear', True) for oper in self.ops])
def __init__(self, ops, dtype='float64'):
self.ops = ops
mops = np.zeros(len(ops), dtype=np.int)
for iop, op in enumerate(ops):
mops[iop] = op.shape[1]
self.mops = mops.sum()
self.nops = ops[0].shape[0]
self.mmops = np.insert(np.cumsum(mops), 0, 0)
self.shape = (self.nops, self.mops)
if dtype is None:
self.dtype = _get_dtype(ops)
else:
self.dtype = np.dtype(dtype)
self.explicit = False
def __init__(self, ops, dtype=None):
self.ops = ops
mops = np.zeros(len(ops), dtype=np.int)
for iop, oper in enumerate(ops):
if not isinstance(oper, (LinearOperator, spLinearOperator)):
self.ops[iop] = MatrixMult(oper, dtype=oper.dtype)
mops[iop] = self.ops[iop].shape[1]
self.mops = int(mops.sum())
nops = [oper.shape[0] for oper in self.ops]
if len(set(nops)) > 1:
raise ValueError('operators have different number of rows')
self.nops = int(nops[0])
self.mmops = np.insert(np.cumsum(mops), 0, 0)
self.shape = (self.nops, self.mops)
if dtype is None:
self.dtype = _get_dtype(self.ops)
else:
self.dtype = np.dtype(dtype)
self.explicit = False
def __init__(self, ops, dtype=None):
self.ops = ops
mops = np.zeros(len(ops), dtype=np.int)
nops = np.zeros(len(ops), dtype=np.int)
for iop, oper in enumerate(ops):
if not isinstance(oper, (LinearOperator, spLinearOperator)):
self.ops[iop] = MatrixMult(oper, dtype=oper.dtype)
nops[iop] = self.ops[iop].shape[0]
mops[iop] = self.ops[iop].shape[1]
self.nops = int(nops.sum())
self.mops = int(mops.sum())
self.nnops = np.insert(np.cumsum(nops), 0, 0)
self.mmops = np.insert(np.cumsum(mops), 0, 0)
self.shape = (self.nops, self.mops)
if dtype is None:
self.dtype = _get_dtype(ops)
else:
self.dtype = np.dtype(dtype)
self.explicit = False
def __init__(self, ops, chunks=None, compute=(False, False),
todask=(False, False), usedelayed=False, dtype=None):
self.ops = ops
nops = np.zeros(len(ops), dtype=np.int)
for iop, oper in enumerate(ops):
nops[iop] = oper.shape[0]
self.nops = nops.sum()
self.mops = ops[0].shape[1]
self.nnops = np.insert(np.cumsum(nops), 0, 0)
self.shape = (self.nops, self.mops)
if dtype is None:
self.dtype = _get_dtype(ops)
else:
self.dtype = np.dtype(dtype)
self.chunks = (self.nops, self.mops) if chunks is None else chunks
self.compute = compute
self.todask = todask
self.usedelayed = usedelayed
if self.usedelayed:
self.todask = (False, False)
self.Op = None
self.explicit = False