def range(min, max, step=None):
""" Values between min and max by step.
If no value is provided, step is set to 1.
"""
if step is None:
return asmatrix(S.arange(min, max + 1))
else:
return asmatrix(S.arange(min, max + step, step))
def unit(r, c=None):
"""Identity matrix.
If r and c are numbers, it returns a (r, c) matrix,
r and c being converted to integers when needed.
If r is a (m, n) matrix, it returns an (m, n) matrix.
"""
try:
return asmatrix(N.eye(r, c))
except TypeError:
return asmatrix(N.eye(r.shape[0], r.shape[1]))
def eye(n,M=None, k=0, dtype=float):
"""
Return a matrix with ones on the diagonal and zeros elsewhere.
Parameters
----------
n : int
Number of rows in the output.
M : int, optional
Number of columns in the output, defaults to n.
k : int, optional
Index of the diagonal: 0 refers to the main diagonal,
a positive value refers to an upper diagonal,
and a negative value to a lower diagonal.
dtype : dtype, optional
Data-type of the returned matrix.
Returns
-------
I : matrix
A `n` x `M` matrix where all elements are equal to zero,
except for the k-th diagonal, whose values are equal to one.
See Also
--------
eye : Equivalent array function
matlib.identity : Square identity matrix
Notes
-----
For more detailed docuemtation, see the docstring of the equivalent
array function ``np.eye``.
"""
return asmatrix(np.eye(n,M,k,dtype))
def diag(ma):
"""Diagonal matrix with ma on the diagonal.
ma needs to be (1, k) or (k, 1).
"""
EXC._assertVectorOrScalar(asmatrix(ma))
ma = N.mat(ma)
return S.diagflat(ma)
def toeplitz(ma, cm=None):
"""
Symmetric Toeplitz matrix.
ma is a (k, 1) or (1, k) matrix.
The Toeplitz matrix is of dimension (cm, cm)
if cm is provided. Otherwise, it is (k, k)
"""
ma = asmatrix(ma)
EXC._assertVectorOrScalar(ma)
if type(cm) == None:
return asmatrix(L.basic.toeplitz(ma))
else:
m = ma.flatten()
if cm is None:
return asmatrix(L.basic.toeplitz(ma))
else:
if cm >= m.shape[1]:
n = cbind(zeros(N.mat(1), cm - m.shape[1]))
return asmatrix(L.basic.toeplitz(n))
else:
return asmatrix(L.basic.toeplitz(m[0:cm, 0:cm]))
def randn(*args):
if isinstance(args[0], tuple):
args = args[0]
return asmatrix(N.random.randn(*args))
def eye(n,M=None, k=0, dtype=float):
return asmatrix(N.eye(n,M,k,dtype))
height = 1
addon = N.resize(addon,[height, source.shape[1]])
else:
height = source.shape[0]
if len(addon) < len(source):
addon = N.resize(addon,[addon.shape[0], source.shape[1]])
elif len(source) < len(addon):
source = N.resize(source,[source.shape[0], addon.shape[1]])
source = N.concatenate((source,addon),0)
return source
##--------------------------------------------------------------------
## MAIN
##--------------------------------------------------------------------
if __name__ == "__main__":
x = asmatrix(N.random.normal(5,2,(4,1)))
d = diag(x)
print(x)
def randn(*args):
if isinstance(args[0], tuple):
args = args[0]
return asmatrix(np.random.randn(*args))
def eye(n, M=None, k=0, dtype=float):
return asmatrix(np.eye(n, M, k, dtype))
