pymel.core.datatypes.Matrix¶

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class Matrix(*args, **kwargs)¶

A 4x4 transformation matrix based on api Matrix

>>> from pymel.all import *
>>> import pymel.core.datatypes as dt
>>>
>>> i = dt.Matrix()
>>> print i.formated()
[[1.0, 0.0, 0.0, 0.0],
 [0.0, 1.0, 0.0, 0.0],
 [0.0, 0.0, 1.0, 0.0],
 [0.0, 0.0, 0.0, 1.0]]

>>> v = dt.Matrix(1, 2, 3)
>>> print v.formated()
[[1.0, 2.0, 3.0, 0.0],
 [1.0, 2.0, 3.0, 0.0],
 [1.0, 2.0, 3.0, 0.0],
 [1.0, 2.0, 3.0, 0.0]]

__add__(other)¶

m.__add__(v) <==> m+v Returns the result of the addition of m and v if v is convertible to a MatrixN (element-wise addition), adds v to every component of m if v is a scalar

__delitem__(index)¶

Cannot delete from a class with a fixed shape

__eq__(other)¶

m.__eq__(v) <==> m == v Equivalence test

__getitem__(index)¶

m.__getitem__(index) <==> m[index] Get component index value from self. index can be a single numeric value or slice, thus one or more rows will be returned, or a row,column tuple of numeric values / slices

__iadd__(other)¶

m.__iadd__(v) <==> m += v In place addition of m and v, see __add__

__imul__(other)¶

m.__imul__(n) <==> m *= n Valid for Matrix * Matrix multiplication, in place multiplication of MatrixN m by MatrixN n

__isub__(other)¶

m.__isub__(v) <==> m -= v In place substraction of m and v, see __sub__

__iter__(*args, **kwargs)¶

Iterate on the Matrix rows

__len__()¶

Number of components in the Matrix instance

__melobject__()¶

Special method for returning a mel-friendly representation. In this case, a flat list of 16 values

__mul__(other)¶

m.__mul__(x) <==> m*x If x is a MatrixN, __mul__ is mapped to matrix multiplication m*x, if x is a VectorN, to MatrixN by VectorN multiplication. Otherwise, returns the result of the element wise multiplication of m and x if x is convertible to Array, multiplies every component of b by x if x is a single numeric value

__ne__(other)¶

m.__ne__(v) <==> m != v Equivalence test

__neg__()¶

m.__neg__() <==> -m The unary minus operator. Negates the value of each of the components of m

__radd__(other)¶

m.__radd__(v) <==> v+m Returns the result of the addition of m and v if v is convertible to a MatrixN (element-wise addition), adds v to every component of m if v is a scalar

__rmul__(other)¶

m.__rmul__(x) <==> x*m If x is a MatrixN, __rmul__ is mapped to matrix multiplication x*m, if x is a VectorN (or Vector or Point or Color), to transformation, ie VectorN by MatrixN multiplication. Otherwise, returns the result of the element wise multiplication of m and x if x is convertible to Array, multiplies every component of m by x if x is a single numeric value

__rsub__(other)¶

m.__rsub__(v) <==> v-m Returns the result of the substraction of m from v if v is convertible to a MatrixN (element-wise substration), replace every component c of m by v-c if v is a scalar

__setitem__(index, value)¶

m.__setitem__(index, value) <==> m[index] = value Set value of component index on self index can be a single numeric value or slice, thus one or more rows will be returned, or a row,column tuple of numeric values / slices

__sub__(other)¶

m.__sub__(v) <==> m-v Returns the result of the substraction of v from m if v is convertible to a MatrixN (element-wise substration), substract v to every component of m if v is a scalar

a00¶

a01¶

a02¶

a03¶

a10¶

a11¶

a12¶

a13¶

a20¶

a21¶

a22¶

a23¶

a30¶

a31¶

a32¶

a33¶

adjoint()¶

Returns the adjoint (adjugate) Matrix

apicls¶

alias of MMatrix

asMatrix(percent=None)¶

The matrix representation for this Matrix/TransformationMatrix/Quaternion/EulerRotation instance

assign(value)¶

blend(other, weight=0.5)¶

Returns a 0.0-1.0 scalar weight blend between self and other Matrix, blend mixes Matrix as transformation matrices

cnames = ('a00', 'a01', 'a02', 'a03', 'a10', 'a11', 'a12', 'a13', 'a20', 'a21', 'a22', 'a23', 'a30', 'a31', 'a32', 'a33')¶

data¶

The Matrix/FloatMatrix/TransformationMatrix/Quaternion/EulerRotation data

det()¶

Returns the determinant of this Matrix instance

det3x3()¶

Returns the determinant of the upper left 3x3 submatrix of this Matrix instance, it’s the same as doing det(m[0:3, 0:3])

det4x4()¶

Returns the 4x4 determinant of this Matrix instance

get()¶

Wrap the Matrix api get method

homogenize()¶

Returns a homogenized version of the Matrix

identity = Matrix([[1.0, 0.0, 0.0, 0.0], [0.0, 1.0, 0.0, 0.0], [0.0, 0.0, 1.0, 0.0], [0.0, 0.0, 0.0, 1.0]])¶

inverse()¶

Returns the inverse Matrix

isEquivalent(other, tol=1e-10)¶

Returns true if both arguments considered as Matrix are equal within the specified tolerance

isSingular()¶

Returns True if the given Matrix is singular

matrix¶

The Matrix representation for this Matrix/TransformationMatrix/Quaternion/EulerRotation instance

ndim = 2¶

rotate¶

The rotation expressed in this Matrix, in transform space

scale¶

The scale expressed in this Matrix, in transform space

setToIdentity()¶

m.setToIdentity() <==> m = a * b Sets MatrixN to the identity matrix

setToProduct(left, right)¶

m.setToProduct(a, b) <==> m = a * b Sets MatrixN to the result of the product of MatrixN a and MatrixN b

shape = (4, 4)¶

size = 16¶

translate¶

The translation expressed in this Matrix, in transform space

transpose()¶

Returns the transposed Matrix

weighted(weight)¶

Returns a 0.0-1.0 scalar weighted blend between identity and self