def _create_J_with_numba(Ybus, V, pvpq, pq, createJ, pvpq_lookup, npv, npq):
Ibus = zeros(len(V), dtype=complex128)
# create Jacobian from fast calc of dS_dV
dVm_x, dVa_x = dSbus_dV_numba_sparse(Ybus.data, Ybus.indptr, Ybus.indices,
V, V / abs(V), Ibus)
# data in J, space preallocated is bigger than acutal Jx -> will be reduced later on
Jx = empty(len(dVm_x) * 4, dtype=float64)
# row pointer, dimension = pvpq.shape[0] + pq.shape[0] + 1
Jp = zeros(pvpq.shape[0] + pq.shape[0] + 1, dtype=int32)
# indices, same with the preallocated space (see Jx)
Jj = empty(len(dVm_x) * 4, dtype=int32)
# fill Jx, Jj and Jp
createJ(dVm_x, dVa_x, Ybus.indptr, Ybus.indices, pvpq_lookup, pvpq, pq, Jx,
Jj, Jp)
# resize before generating the scipy sparse matrix
Jx.resize(Jp[-1], refcheck=False)
Jj.resize(Jp[-1], refcheck=False)
# generate scipy sparse matrix
dimJ = npv + npq + npq
J = sparse((Jx, Jj, Jp), shape=(dimJ, dimJ))
return J
def ones(shape, typecode='l', savespace=0, dtype=None):
"""ones(shape, dtype=int) returns an array of the given
dimensions which is initialized to all ones.
"""
dtype = convtypecode(typecode, dtype)
a = mu.empty(shape, dtype)
a.fill(1)
return a
def AC_jacobian(Ybus, V, pvpq, pq, pvpq_lookup, npv, npq):
"""
Create the AC Jacobian function with no embedded controls
:param Ybus: Ybus matrix in CSC format
:param V: Voltages vector
:param pvpq: array of pv|pq bus indices
:param pq: array of pq indices
:param pvpq_lookup: array of pv|pq lookup indices
:param npv: number of pv buses
:param npq: number of pq buses
:return: Jacobian Matrix in CSR format
"""
Ibus = zeros(len(V), dtype=complex128)
# create Jacobian from fast calc of dS_dV
dS_dVm, dS_dVa = deriv.dSbus_dV_numba_sparse_csr(Ybus.data, Ybus.indptr,
Ybus.indices, V,
V / abs(V), Ibus)
# data in J, space pre-allocated is bigger than actual Jx -> will be reduced later on
Jx = empty(len(dS_dVm) * 4, dtype=float64)
# row pointer, dimension = pvpq.shape[0] + pq.shape[0] + 1
Jp = zeros(pvpq.shape[0] + pq.shape[0] + 1, dtype=int32)
# indices, same with the pre-allocated space (see Jx)
Jj = empty(len(dS_dVm) * 4, dtype=int32)
# fill Jx, Jj and Jp in CSR order
if len(pvpq) == len(pq):
create_J_no_pv(dS_dVm, dS_dVa, Ybus.indptr, Ybus.indices, pvpq_lookup,
pvpq, Jx, Jj, Jp)
else:
create_J(dS_dVm, dS_dVa, Ybus.indptr, Ybus.indices, pvpq_lookup, pvpq,
pq, Jx, Jj, Jp)
# resize before generating the scipy sparse matrix
Jx.resize(Jp[-1], refcheck=False)
Jj.resize(Jp[-1], refcheck=False)
# generate scipy sparse matrix
nj = npv + npq + npq
return csr_matrix((Jx, Jj, Jp), shape=(nj, nj))
_types.StringType, _types.UnicodeType, _types.BufferType]
ScalarType.extend(_sctype2char_dict.keys())
ScalarType = tuple(ScalarType)
for key in _sctype2char_dict.keys():
cast[key] = lambda x, k=key : array(x, copy=False).astype(k)
_unicodesize = array('u','U1').itemsize
# Create the typestring lookup dictionary
_typestr = _typedict()
for key in _sctype2char_dict.keys():
if issubclass(key, allTypes['flexible']):
_typestr[key] = _sctype2char_dict[key]
else:
_typestr[key] = empty((1,),key).dtype.str[1:]
# Make sure all typestrings are in sctypeDict
for key, val in _typestr.items():
if val not in sctypeDict:
sctypeDict[val] = key
# Add additional strings to the sctypeDict
_toadd = ['int', 'float', 'complex', 'bool', 'object', 'string', ('str', allTypes['string_']),
'unicode', 'object', ('a', allTypes['string_'])]
for name in _toadd:
if isinstance(name, tuple):
sctypeDict[name[0]] = name[1]
else:
except AttributeError:
# Py3K
ScalarType = [int, float, complex, int, bool, bytes, str, memoryview]
ScalarType.extend(_sctype2char_dict.keys())
ScalarType = tuple(ScalarType)
for key in _sctype2char_dict.keys():
cast[key] = lambda x, k=key : array(x, copy=False).astype(k)
# Create the typestring lookup dictionary
_typestr = _typedict()
for key in _sctype2char_dict.keys():
if issubclass(key, allTypes['flexible']):
_typestr[key] = _sctype2char_dict[key]
else:
_typestr[key] = empty((1,), key).dtype.str[1:]
# Make sure all typestrings are in sctypeDict
for key, val in _typestr.items():
if val not in sctypeDict:
sctypeDict[val] = key
# Add additional strings to the sctypeDict
if sys.version_info[0] >= 3:
_toadd = ['int', 'float', 'complex', 'bool', 'object',
'str', 'bytes', 'object', ('a', allTypes['bytes_'])]
else:
_toadd = ['int', 'float', 'complex', 'bool', 'object', 'string',
('str', allTypes['string_']),
'unicode', 'object', ('a', allTypes['string_'])]
def empty(shape, typecode='l', dtype=None):
dtype = convtypecode(typecode, dtype)
return mu.empty(shape, dtype)
