def __abstract_new__(cls, matrix, vector):
data, N, M = flatten(matrix)
if N != M:
raise ValueError('expected an square matrix')
M += 1
for i, x in enumerate(vector):
data.insert((i + 1) * M - 1, x)
T = cls[N, dtype(data)]
return T.from_flat(data)
def __abstract_new__(cls, matrix, vector):
data, N, M = flatten(matrix)
if N != M:
raise ValueError("expected an square matrix")
M += 1
for i, x in enumerate(vector):
data.insert((i + 1) * M - 1, x)
T = cls[N, dtype(data)]
return T.from_flat(data)
def from_rows(cls, rows, dtype=None):
"""
Build matrix from a sequence of row vectors.
"""
data, M, N = flatten(rows, 2)
if (M, N) != cls.shape:
if cls.size is None:
return cls[M, N, cls.dtype].from_flat(data, dtype)
msg = ('data shape %s is not consistent with matrix type %s' %
((M, N), cls.shape))
raise ValueError(msg)
return cls.from_flat(data, dtype=dtype)
def from_rows(cls, rows, dtype=None):
"""
Build matrix from a sequence of row vectors.
"""
data, M, N = flatten(rows, 2)
if (M, N) != cls.shape:
if cls.size is None:
return cls[M, N, cls.dtype].from_flat(data, dtype)
msg = ('data shape %s is not consistent with matrix type %s' %
((M, N), cls.shape))
raise ValueError(msg)
return cls.from_flat(data, dtype=dtype)
def from_cols(cls, cols, dtype=None):
"""
Build matrix from a sequence of column vectors.
"""
dataT, N, M = flatten(cols, 2)
data = dataT[:]
for i in range(M):
data[i * N:i * N + N] = dataT[i::M]
if (M, N) != cls.shape:
if cls.size is None:
return cls[M, N, cls.dtype].from_flat(data, dtype)
msg = ('data shape %s is not consistent with matrix type %s' %
((M, N), cls.shape))
raise ValueError(msg)
return cls.from_flat(data, dtype=dtype)
def from_cols(cls, cols, dtype=None):
"""
Build matrix from a sequence of column vectors.
"""
dataT, N, M = flatten(cols, 2)
data = dataT[:]
for i in range(M):
data[i * N:i * N + N] = dataT[i::M]
if (M, N) != cls.shape:
if cls.size is None:
return cls[M, N, cls.dtype].from_flat(data, dtype)
msg = ('data shape %s is not consistent with matrix type %s' %
((M, N), cls.shape))
raise ValueError(msg)
return cls.from_flat(data, dtype=dtype)
def __abstract_new__(cls, *args, dtype=None):
flat, nrows, ncols = flatten(args, 2)
return cls[nrows, ncols].from_flat(flat)
def __init__(self, *args):
flat, N, M = flatten(args, 2)
self.flat = self.__flat__(flat, copy=False)
if N != self.nrows or M != self.ncols:
raise ValueError('data has an invalid shape: %s' % repr((N, M)))
def __abstract_new__(cls, *args, dtype=None):
flat, nrows, ncols = flatten(args, 2)
return cls[nrows, ncols].from_flat(flat)
def __init__(self, *args):
flat, N, M = flatten(args, 2)
self.flat = self.__flat__(flat, copy=False)
if N != self.nrows or M != self.ncols:
raise ValueError('data has an invalid shape: %s' % repr((N, M)))
def test_flatten():
assert flatten([1, 2]) == ([1, 2], 2)
assert flatten([[1, 2]]) == ([1, 2], 1, 2)
assert flatten([[1], [2]]) == ([1, 2], 2, 1)
assert flatten([[1, 2], [3, 4], [5, 6]]) == ([1, 2, 3, 4, 5, 6], 3, 2)
