Creating scalars and matrices

Creating scalars and matrices#

Creating a matrix, and converting from compatible data types#

CtxEigen.MatT(x=None, y=None, eigen=False)#

Creates a real or complex matrix of the data type corresponding to the context.

Creating a matrix of zeros#

CtxEigen.MatZeros(n, m, complex=False, eigen=False)#

Creates a \(n \times m\) matrix of the indicated type and sets all entries to zero.

>>> from xlcalcnet import *
>>> ctx.dps = 15; n = 4; m = 4
>>> matA = ctx.mat_zeros(n, m, eigen=True)
>>> matA.show("matA, mat_zeros(n, m) :")
matA, mat_zeros(n, m) :
 0,  0,  0,  0,
 0,  0,  0,  0,
 0,  0,  0,  0,
 0,  0,  0,  0,

Creating a matrix of ones#

CtxEigen.MatOnes(n, m, complex=False, eigen=False)#

Creates a \(n \times m\) matrix of the indicated type and sets all entries to one.

>>> from xlcalcnet import *
>>> ctx.dps = 15; n = 4; m = 4
>>> matA = ctx.mat_ones(n, m)
>>> matA.show("matA, mat_ones(n, m) :")
matA, mat_ones(n, m) :
 1,  1,  1,  1,
 1,  1,  1,  1,
 1,  1,  1,  1,
 1,  1,  1,  1,

Creating an identity matrix#

CtxEigen.MatIdentity(n, m, complex=False, eigen=False)#

Creates a \(n \times m\) identity matrix of the indicated type.

>>> from xlcalcnet import *
>>> ctx.dps = 15; n = 4; m = 4
>>> matA = ctx.mat_identity(n, m)
>>> matA.show("matA, mat_identity(n, m) :")
matA, mat_identity(n, m) :
 1,  0,  0,  0,
 0,  1,  0,  0,
 0,  0,  1,  0,
 0,  0,  0,  1,

Creating a matrix with linearly increasing values#

CtxEigen.MatLinspace(n, m, x, complex=False, eigen=False)#

Creates a \(n \times m\) matrix of the indicated type and sets all entries to incresing values \(x\).

>>> from xlcalcnet import *
>>> ctx.dps = 15; n = 4; m = 4
>>> matA = ctx.mat_fill_linear(n, m)
>>> matA.show("matA, mat_fill_linear(n) :")
matA, mat_fill_linear(n) :
 0,  0,  0,  0,
 0,  0,  0,  0,
 0,  0,  0,  0,
 0,  0,  0,  0,

Creating a general random matrix#

CtxEigen.MatRandom(n, m, complex=False, eigen=False)#

Creates a \(n \times m\) matrix of the indicated type and sets all entries to random values.

>>> from xlcalcnet import *
>>> ctx.dps = 15; n = 4; m = 4
>>> matA = ctx.mat_random(n, m)
>>> matA.show("matA, mat_random(n, m) :")
matA, mat_random(n, m) :
 0.35029145176550,  0.17410809656056,  0.30399487289041,  0.14731284524064,
 0.89596240119633,  0.85894344920194,  0.014984588152715,  0.16589861751152,
 0.82284005249184,  0.71050141911069,  0.091402935880612,  0.98852504043703,
 0.74660481582080,  0.51353495895260,  0.36445204016236,  0.44569231238746,

Creating a symmetric random matrix#

CtxEigen.MatRandomSymmetric(n, complex=False, eigen=False)#

Creates a \(n \times n\) symmetric matrix of the indicated type and sets all entries to random values.

>>> from xlcalcnet import *
>>> ctx.dps = 15; n = 4; m = 4
>>> matA = ctx.mat_random_sym(n)
>>> matA.show("matA, mat_random_sym(n) :")
matA, mat_random_sym(n) :
 0.23816644795068,  0.53633228553118,  0.17514572588275,  0.43491927854244,
 0.53633228553118,  1.1423688467055,  1.2648091067232,  1.2148503067110,
 0.17514572588275,  1.2648091067232,  0.90157780693990,  1.1354411450545,
 0.43491927854244,  1.2148503067110,  1.1354411450545,  1.6052125614185,

Creating a self-adjoint random matrix#

CtxEigen.MatRandomHermitian(n, complex=False, eigen=False)#

Creates a \(n \times n\) hermitian matrix of the indicated type and sets all entries to random values.

>>> from xlcalcnet import *
>>> ctx.dps = 15; n = 4; m = 4
>>> matA = ctx.mat_random_sa(n)
>>> matA.show("matA, mat_random_sa(n) :")
matA, mat_random_sym(n) :
 0.23816644795068,  0.53633228553118,  0.17514572588275,  0.43491927854244,
 0.53633228553118,  1.1423688467055,  1.2648091067232,  1.2148503067110,
 0.17514572588275,  1.2648091067232,  0.90157780693990,  1.1354411450545,
 0.43491927854244,  1.2148503067110,  1.1354411450545,  1.6052125614185,

Creating a positive definite self-adjoint matrix#

CtxEigen.MatRandomPosDefinite(n, complex=False, eigen=False)#

Creates a \(n \times n\) positive definite random matrix of the indicated type.

>>> from xlcalcnet import *
>>> ctx.dps = 15; n = 4; m = 4
>>> matA = ctx.mat_random_sa_posdef(n)
>>> matA.show("matA, mat_random_sa_posdef(n)")
matA, mat_random_sa_posdef(n)
 1.6144949159812,  0.37328104299787,  0.64671931578811,  1.0725029543798,
 0.37328104299787,  0.23220359390837,  0.27432857744706,  0.35913470470614,
 0.64671931578811,  0.27432857744706,  0.55785829596540,  0.52838216584663,
 1.0725029543798,  0.35913470470614,  0.52838216584663,  1.4188647561723,
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