def from_flat(cls, data, copy=True, dtype=None, shape=None):
"""
Initializes object from flattened data.
If copy=False, it tries to recycle the flattened data whenever
possible. The caller is responsible for not sharing this data
with other mutable objects.
Note:
This function only normalizes an iterable data for final
consumption.
"""
if cls.__concrete__:
if dtype is None or dtype is cls.dtype:
new = object.__new__(cls)
new.flat = cls.__flat__(data, copy)
return new
elif cls.size is None:
raise TypeError('shapeless types cannot instantiate objects')
dtype = dtype or cls.dtype
if dtype is Any or dtype is None:
data = list(data)
dtype = _dtype(data)
T = cls.__origin__[cls.shape + (dtype, )]
return T.from_flat(data, copy=copy)
def from_flat(cls, data, copy=True, dtype=None, shape=None):
"""
Initializes object from flattened data.
If copy=False, it tries to recycle the flattened data whenever
possible. The caller is responsible for not sharing this data
with other mutable objects.
Note:
This function only normalizes an iterable data for final
consumption.
"""
if cls.__concrete__:
if dtype is None or dtype is cls.dtype:
new = object.__new__(cls)
new.flat = cls.__flat__(data, copy)
return new
elif cls.size is None:
raise TypeError('shapeless types cannot instantiate objects')
dtype = dtype or cls.dtype
if dtype is Any or dtype is None:
data = list(data)
dtype = _dtype(data)
T = cls.__origin__[cls.shape + (dtype,)]
return T.from_flat(data, copy=copy)
def __abstract_new__(cls, *args, dtype=None): # @NoSelf
"""
This function is called when user tries to instantiate an abstract
type. It just finds the proper concrete type and instantiate it.
"""
if dtype is None:
dtype = _dtype(args)
return cls[len(args), dtype](*args)
def __abstract_new__(cls, *args, dtype=None): # @NoSelf
"""
This function is called when user tries to instantiate an abstract
type. It just finds the proper concrete type and instantiate it.
"""
if dtype is None:
dtype = _dtype(args)
return cls[len(args), dtype](*args)
def __abstract_new__(cls, *args, shape=None, dtype=None):
"""
This function is called when user tries to instantiate an abstract
type. It just finds the proper concrete type and instantiate it.
"""
if dtype is None:
dtype = _dtype(args)
if shape is None:
shape = _shape(args)
return cls[shape + (dtype, )](*args)
def __abstract_new__(cls, *args, shape=None, dtype=None):
"""
This function is called when user tries to instantiate an abstract
type. It just finds the proper concrete type and instantiate it.
"""
if dtype is None:
dtype = _dtype(args)
if shape is None:
shape = _shape(args)
return cls[shape + (dtype,)](*args)
def from_diag(cls, diag):
"""
Create diagonal matrix from diagonal terms.
"""
N = len(diag)
data = [0] * (N * N)
for i in range(N):
data[N * i + i] = diag[i]
return cls.__origin__[N, N, _dtype(data)].from_flat(data, copy=False)
def __mul__(self, other):
if isinstance(other, (Vec, tuple, list)):
other = asvector(other)
return asvector([u.dot(other) for u in self.rows()])
elif isinstance(other, number):
return self.from_flat([x * other for x in self.flat], copy=False)
elif isinstance(other, Mat):
cols = list(other.cols())
rows = list(self.rows())
data = sum([[u.dot(v) for u in cols] for v in rows], [])
cls = self.__origin__[len(rows), len(cols), _dtype(data)]
return cls.from_flat(data, copy=False)
else:
return NotImplemented
def __mul__(self, other):
if isinstance(other, (Vec, tuple, list)):
other = asvector(other)
return asvector([u.dot(other) for u in self.rows()])
elif isinstance(other, number):
return self.from_flat([x * other for x in self.flat], copy=False)
elif isinstance(other, Mat):
cols = list(other.cols())
rows = list(self.rows())
data = sum([[u.dot(v) for u in cols] for v in rows], [])
cls = self.__origin__[len(rows), len(cols), _dtype(data)]
return cls.from_flat(data, copy=False)
else:
return NotImplemented
