yade.minieigenHP module¶
When yade uses high-precision number as Real
type the usual (old):
from minieigen import *
has to be replaced with:
from yade.minieigenHP import *
This command ensures backward compatibility between both. It is then guaranteed that python uses the same number of decimal places as yade is using everywhere else.
Please note that used precision can be very arbitrary, because cpp_bin_float
or mpfr
take it as a compile-time argument. Hence such yade.minieigenHP
cannot be separately precompiled as a package.
Though it could be precompiled for some special types such as boost::multiprecision::float128
.
The RealHP<n>
higher precision vectors and matrices can be accessed in python by using the .HPn
module scope. For example:
import yade.minieigenHP as mne
mne.HP2.Vector3(1,2,3) # produces Vector3 using RealHP<2> precision
mne.Vector3(1,2,3) # without using HPn module scope it defaults to RealHP<1>
miniEigen is wrapper for a small part of the Eigen library. Refer to its documentation for details. All classes in this module support pickling.
- class yade._minieigenHP.AlignedBox2¶
Axis-aligned box object in 2d, defined by its minimum and maximum corners
- __init__((object)arg1) None ¶
__init__( (object)arg1, (AlignedBox2)other) -> None
__init__( (object)arg1, (Vector2)min, (Vector2)max) -> None
- clamp((AlignedBox2)arg1, (AlignedBox2)arg2) None ¶
- contains((AlignedBox2)arg1, (Vector2)arg2) bool ¶
contains( (AlignedBox2)arg1, (AlignedBox2)arg2) -> bool
- empty((AlignedBox2)arg1) bool ¶
- extend((AlignedBox2)arg1, (Vector2)arg2) None ¶
extend( (AlignedBox2)arg1, (AlignedBox2)arg2) -> None
- intersection((AlignedBox2)arg1, (AlignedBox2)arg2) AlignedBox2 ¶
- property max¶
- merged((AlignedBox2)arg1, (AlignedBox2)arg2) AlignedBox2 ¶
- property min¶
- volume((AlignedBox2)arg1) float ¶
- class yade._minieigenHP.AlignedBox3¶
Axis-aligned box object, defined by its minimum and maximum corners
- __init__((object)arg1) None ¶
__init__( (object)arg1, (AlignedBox3)other) -> None
__init__( (object)arg1, (Vector3)min, (Vector3)max) -> None
- clamp((AlignedBox3)arg1, (AlignedBox3)arg2) None ¶
- contains((AlignedBox3)arg1, (Vector3)arg2) bool ¶
contains( (AlignedBox3)arg1, (AlignedBox3)arg2) -> bool
- empty((AlignedBox3)arg1) bool ¶
- extend((AlignedBox3)arg1, (Vector3)arg2) None ¶
extend( (AlignedBox3)arg1, (AlignedBox3)arg2) -> None
- intersection((AlignedBox3)arg1, (AlignedBox3)arg2) AlignedBox3 ¶
- property max¶
- merged((AlignedBox3)arg1, (AlignedBox3)arg2) AlignedBox3 ¶
- property min¶
- volume((AlignedBox3)arg1) float ¶
- class yade._minieigenHP.HP1¶
- class AlignedBox2¶
Axis-aligned box object in 2d, defined by its minimum and maximum corners
- __init__((object)arg1) None ¶
__init__( (object)arg1, (AlignedBox2)other) -> None
__init__( (object)arg1, (Vector2)min, (Vector2)max) -> None
- clamp((AlignedBox2)arg1, (AlignedBox2)arg2) None ¶
- contains((AlignedBox2)arg1, (Vector2)arg2) bool ¶
contains( (AlignedBox2)arg1, (AlignedBox2)arg2) -> bool
- empty((AlignedBox2)arg1) bool ¶
- extend((AlignedBox2)arg1, (Vector2)arg2) None ¶
extend( (AlignedBox2)arg1, (AlignedBox2)arg2) -> None
- intersection((AlignedBox2)arg1, (AlignedBox2)arg2) AlignedBox2 ¶
- property max¶
- merged((AlignedBox2)arg1, (AlignedBox2)arg2) AlignedBox2 ¶
- property min¶
- volume((AlignedBox2)arg1) float ¶
- class AlignedBox3¶
Axis-aligned box object, defined by its minimum and maximum corners
- __init__((object)arg1) None ¶
__init__( (object)arg1, (AlignedBox3)other) -> None
__init__( (object)arg1, (Vector3)min, (Vector3)max) -> None
- clamp((AlignedBox3)arg1, (AlignedBox3)arg2) None ¶
- contains((AlignedBox3)arg1, (Vector3)arg2) bool ¶
contains( (AlignedBox3)arg1, (AlignedBox3)arg2) -> bool
- empty((AlignedBox3)arg1) bool ¶
- extend((AlignedBox3)arg1, (Vector3)arg2) None ¶
extend( (AlignedBox3)arg1, (AlignedBox3)arg2) -> None
- intersection((AlignedBox3)arg1, (AlignedBox3)arg2) AlignedBox3 ¶
- property max¶
- merged((AlignedBox3)arg1, (AlignedBox3)arg2) AlignedBox3 ¶
- property min¶
- volume((AlignedBox3)arg1) float ¶
- class Matrix3¶
3x3 float matrix.
Supported operations (
m
is a Matrix3,f
if a float/int,v
is a Vector3):-m
,m+m
,m+=m
,m-m
,m-=m
,m*f
,f*m
,m*=f
,m/f
,m/=f
,m*m
,m*=m
,m*v
,v*m
,m==m
,m!=m
.Static attributes:
Zero
,Ones
,Identity
.- Identity = Matrix3(1,0,0, 0,1,0, 0,0,1)¶
- Ones = Matrix3(1,1,1, 1,1,1, 1,1,1)¶
- static Random() Matrix3 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix3(0,0,0, 0,0,0, 0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Quaternion)q) -> None
__init__( (object)arg1, (Matrix3)other) -> None
__init__( (object)arg1, (Vector3)diag) -> object
__init__( (object)arg1, (float)m00, (float)m01, (float)m02, (float)m10, (float)m11, (float)m12, (float)m20, (float)m21, (float)m22) -> object
__init__( (object)arg1, (Vector3)r0, (Vector3)r1, (Vector3)r2 [, (bool)cols=False]) -> object
- col((Matrix3)arg1, (int)col) Vector3 : ¶
Return column as vector.
- cols((Matrix3)arg1) int : ¶
Number of columns.
- computeUnitaryPositive((Matrix3)arg1) tuple : ¶
Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).
- determinant((Matrix3)arg1) float : ¶
Return matrix determinant.
- diagonal((Matrix3)arg1) Vector3 : ¶
Return diagonal as vector.
- inverse((Matrix3)arg1) Matrix3 : ¶
Return inverted matrix.
- isApprox((Matrix3)arg1, (Matrix3)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- jacobiSVD((Matrix3)arg1) tuple : ¶
Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()
- maxAbsCoeff((Matrix3)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Matrix3)arg1) float : ¶
Maximum value over all elements.
- mean((Matrix3)arg1) float : ¶
Mean value over all elements.
- minCoeff((Matrix3)arg1) float : ¶
Minimum value over all elements.
- norm((Matrix3)arg1) float : ¶
Euclidean norm.
- normalize((Matrix3)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix3)arg1) Matrix3 : ¶
Return normalized copy of this object
- polarDecomposition((Matrix3)arg1) tuple : ¶
Alias for
computeUnitaryPositive
.
- prod((Matrix3)arg1) float : ¶
Product of all elements.
- pruned((Matrix3)arg1[, (float)absTol=1e-06]) Matrix3 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix3)arg1, (int)row) Vector3 : ¶
Return row as vector.
- rows((Matrix3)arg1) int : ¶
Number of rows.
- selfAdjointEigenDecomposition((Matrix3)arg1) tuple : ¶
Compute eigen (spectral) decomposition of symmetric matrix, returns (eigVecs,eigVals). eigVecs is orthogonal Matrix3 with columns ar normalized eigenvectors, eigVals is Vector3 with corresponding eigenvalues. self=eigVecs*diag(eigVals)*eigVecs.transpose().
- spectralDecomposition((Matrix3)arg1) tuple : ¶
Alias for
selfAdjointEigenDecomposition
.
- squaredNorm((Matrix3)arg1) float : ¶
Square of the Euclidean norm.
- sum((Matrix3)arg1) float : ¶
Sum of all elements.
- trace((Matrix3)arg1) float : ¶
Return sum of diagonal elements.
- transpose((Matrix3)arg1) Matrix3 : ¶
Return transposed matrix.
- class Matrix3c¶
/TODO/
- Identity = Matrix3c(1,0,0, 0,1,0, 0,0,1)¶
- Ones = Matrix3c(1,1,1, 1,1,1, 1,1,1)¶
- static Random() Matrix3c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix3c(0,0,0, 0,0,0, 0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Matrix3c)other) -> None
__init__( (object)arg1, (Vector3c)diag) -> object
__init__( (object)arg1, (complex)m00, (complex)m01, (complex)m02, (complex)m10, (complex)m11, (complex)m12, (complex)m20, (complex)m21, (complex)m22) -> object
__init__( (object)arg1, (Vector3c)r0, (Vector3c)r1, (Vector3c)r2 [, (bool)cols=False]) -> object
- col((Matrix3c)arg1, (int)col) Vector3c : ¶
Return column as vector.
- cols((Matrix3c)arg1) int : ¶
Number of columns.
- determinant((Matrix3c)arg1) complex : ¶
Return matrix determinant.
- diagonal((Matrix3c)arg1) Vector3c : ¶
Return diagonal as vector.
- inverse((Matrix3c)arg1) Matrix3c : ¶
Return inverted matrix.
- isApprox((Matrix3c)arg1, (Matrix3c)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Matrix3c)arg1) float : ¶
Maximum absolute value over all elements.
- mean((Matrix3c)arg1) complex : ¶
Mean value over all elements.
- norm((Matrix3c)arg1) float : ¶
Euclidean norm.
- normalize((Matrix3c)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix3c)arg1) Matrix3c : ¶
Return normalized copy of this object
- prod((Matrix3c)arg1) complex : ¶
Product of all elements.
- pruned((Matrix3c)arg1[, (float)absTol=1e-06]) Matrix3c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix3c)arg1, (int)row) Vector3c : ¶
Return row as vector.
- rows((Matrix3c)arg1) int : ¶
Number of rows.
- squaredNorm((Matrix3c)arg1) float : ¶
Square of the Euclidean norm.
- sum((Matrix3c)arg1) complex : ¶
Sum of all elements.
- trace((Matrix3c)arg1) complex : ¶
Return sum of diagonal elements.
- transpose((Matrix3c)arg1) Matrix3c : ¶
Return transposed matrix.
- class Matrix6¶
6x6 float matrix. Constructed from 4 3x3 sub-matrices, from 6xVector6 (rows).
Supported operations (
m
is a Matrix6,f
if a float/int,v
is a Vector6):-m
,m+m
,m+=m
,m-m
,m-=m
,m*f
,f*m
,m*=f
,m/f
,m/=f
,m*m
,m*=m
,m*v
,v*m
,m==m
,m!=m
.Static attributes:
Zero
,Ones
,Identity
.- Identity = Matrix6( (1,0,0,0,0,0), (0,1,0,0,0,0), (0,0,1,0,0,0), (0,0,0,1,0,0), (0,0,0,0,1,0), (0,0,0,0,0,1) )¶
- Ones = Matrix6( (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1) )¶
- static Random() Matrix6 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix6( (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0) )¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Matrix6)other) -> None
__init__( (object)arg1, (Vector6)diag) -> object
__init__( (object)arg1, (Matrix3)ul, (Matrix3)ur, (Matrix3)ll, (Matrix3)lr) -> object
__init__( (object)arg1, (Vector6)l0, (Vector6)l1, (Vector6)l2, (Vector6)l3, (Vector6)l4, (Vector6)l5 [, (bool)cols=False]) -> object
- col((Matrix6)arg1, (int)col) Vector6 : ¶
Return column as vector.
- cols((Matrix6)arg1) int : ¶
Number of columns.
- computeUnitaryPositive((Matrix6)arg1) tuple : ¶
Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).
- determinant((Matrix6)arg1) float : ¶
Return matrix determinant.
- diagonal((Matrix6)arg1) Vector6 : ¶
Return diagonal as vector.
- inverse((Matrix6)arg1) Matrix6 : ¶
Return inverted matrix.
- isApprox((Matrix6)arg1, (Matrix6)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- jacobiSVD((Matrix6)arg1) tuple : ¶
Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()
- ll((Matrix6)arg1) Matrix3 : ¶
Return lower-left 3x3 block
- lr((Matrix6)arg1) Matrix3 : ¶
Return lower-right 3x3 block
- maxAbsCoeff((Matrix6)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Matrix6)arg1) float : ¶
Maximum value over all elements.
- mean((Matrix6)arg1) float : ¶
Mean value over all elements.
- minCoeff((Matrix6)arg1) float : ¶
Minimum value over all elements.
- norm((Matrix6)arg1) float : ¶
Euclidean norm.
- normalize((Matrix6)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix6)arg1) Matrix6 : ¶
Return normalized copy of this object
- polarDecomposition((Matrix6)arg1) tuple : ¶
Alias for
computeUnitaryPositive
.
- prod((Matrix6)arg1) float : ¶
Product of all elements.
- pruned((Matrix6)arg1[, (float)absTol=1e-06]) Matrix6 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix6)arg1, (int)row) Vector6 : ¶
Return row as vector.
- rows((Matrix6)arg1) int : ¶
Number of rows.
- selfAdjointEigenDecomposition((Matrix6)arg1) tuple : ¶
Compute eigen (spectral) decomposition of symmetric matrix, returns (eigVecs,eigVals). eigVecs is orthogonal Matrix3 with columns ar normalized eigenvectors, eigVals is Vector3 with corresponding eigenvalues. self=eigVecs*diag(eigVals)*eigVecs.transpose().
- spectralDecomposition((Matrix6)arg1) tuple : ¶
Alias for
selfAdjointEigenDecomposition
.
- squaredNorm((Matrix6)arg1) float : ¶
Square of the Euclidean norm.
- sum((Matrix6)arg1) float : ¶
Sum of all elements.
- trace((Matrix6)arg1) float : ¶
Return sum of diagonal elements.
- transpose((Matrix6)arg1) Matrix6 : ¶
Return transposed matrix.
- ul((Matrix6)arg1) Matrix3 : ¶
Return upper-left 3x3 block
- ur((Matrix6)arg1) Matrix3 : ¶
Return upper-right 3x3 block
- class Matrix6c¶
/TODO/
- Identity = Matrix6c( (1,0,0,0,0,0), (0,1,0,0,0,0), (0,0,1,0,0,0), (0,0,0,1,0,0), (0,0,0,0,1,0), (0,0,0,0,0,1) )¶
- Ones = Matrix6c( (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1) )¶
- static Random() Matrix6c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix6c( (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0) )¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Matrix6c)other) -> None
__init__( (object)arg1, (Vector6c)diag) -> object
__init__( (object)arg1, (Matrix3c)ul, (Matrix3c)ur, (Matrix3c)ll, (Matrix3c)lr) -> object
__init__( (object)arg1, (Vector6c)l0, (Vector6c)l1, (Vector6c)l2, (Vector6c)l3, (Vector6c)l4, (Vector6c)l5 [, (bool)cols=False]) -> object
- col((Matrix6c)arg1, (int)col) Vector6c : ¶
Return column as vector.
- cols((Matrix6c)arg1) int : ¶
Number of columns.
- determinant((Matrix6c)arg1) complex : ¶
Return matrix determinant.
- diagonal((Matrix6c)arg1) Vector6c : ¶
Return diagonal as vector.
- inverse((Matrix6c)arg1) Matrix6c : ¶
Return inverted matrix.
- isApprox((Matrix6c)arg1, (Matrix6c)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- ll((Matrix6c)arg1) Matrix3c : ¶
Return lower-left 3x3 block
- lr((Matrix6c)arg1) Matrix3c : ¶
Return lower-right 3x3 block
- maxAbsCoeff((Matrix6c)arg1) float : ¶
Maximum absolute value over all elements.
- mean((Matrix6c)arg1) complex : ¶
Mean value over all elements.
- norm((Matrix6c)arg1) float : ¶
Euclidean norm.
- normalize((Matrix6c)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix6c)arg1) Matrix6c : ¶
Return normalized copy of this object
- prod((Matrix6c)arg1) complex : ¶
Product of all elements.
- pruned((Matrix6c)arg1[, (float)absTol=1e-06]) Matrix6c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix6c)arg1, (int)row) Vector6c : ¶
Return row as vector.
- rows((Matrix6c)arg1) int : ¶
Number of rows.
- squaredNorm((Matrix6c)arg1) float : ¶
Square of the Euclidean norm.
- sum((Matrix6c)arg1) complex : ¶
Sum of all elements.
- trace((Matrix6c)arg1) complex : ¶
Return sum of diagonal elements.
- transpose((Matrix6c)arg1) Matrix6c : ¶
Return transposed matrix.
- ul((Matrix6c)arg1) Matrix3c : ¶
Return upper-left 3x3 block
- ur((Matrix6c)arg1) Matrix3c : ¶
Return upper-right 3x3 block
- class MatrixX¶
XxX (dynamic-sized) float matrix. Constructed from list of rows (as VectorX).
Supported operations (
m
is a MatrixX,f
if a float/int,v
is a VectorX):-m
,m+m
,m+=m
,m-m
,m-=m
,m*f
,f*m
,m*=f
,m/f
,m/=f
,m*m
,m*=m
,m*v
,v*m
,m==m
,m!=m
.- static Identity((int)arg1, (int)rank) MatrixX : ¶
Create identity matrix with given rank (square).
- static Ones((int)rows, (int)cols) MatrixX : ¶
Create matrix of given dimensions where all elements are set to 1.
- static Random((int)rows, (int)cols) MatrixX : ¶
Create matrix with given dimensions where all elements are set to number between 0 and 1 (uniformly-distributed).
- static Zero((int)rows, (int)cols) MatrixX : ¶
Create zero matrix of given dimensions
- __init__((object)arg1) None ¶
__init__( (object)arg1, (MatrixX)other) -> None
__init__( (object)arg1, (VectorX)diag) -> object
__init__( (object)arg1 [, (VectorX)r0=VectorX() [, (VectorX)r1=VectorX() [, (VectorX)r2=VectorX() [, (VectorX)r3=VectorX() [, (VectorX)r4=VectorX() [, (VectorX)r5=VectorX() [, (VectorX)r6=VectorX() [, (VectorX)r7=VectorX() [, (VectorX)r8=VectorX() [, (VectorX)r9=VectorX() [, (bool)cols=False]]]]]]]]]]]) -> object
__init__( (object)arg1, (object)rows [, (bool)cols=False]) -> object
- col((MatrixX)arg1, (int)col) VectorX : ¶
Return column as vector.
- cols((MatrixX)arg1) int : ¶
Number of columns.
- computeUnitaryPositive((MatrixX)arg1) tuple : ¶
Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).
- determinant((MatrixX)arg1) float : ¶
Return matrix determinant.
- diagonal((MatrixX)arg1) VectorX : ¶
Return diagonal as vector.
- inverse((MatrixX)arg1) MatrixX : ¶
Return inverted matrix.
- isApprox((MatrixX)arg1, (MatrixX)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- jacobiSVD((MatrixX)arg1) tuple : ¶
Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()
- maxAbsCoeff((MatrixX)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((MatrixX)arg1) float : ¶
Maximum value over all elements.
- mean((MatrixX)arg1) float : ¶
Mean value over all elements.
- minCoeff((MatrixX)arg1) float : ¶
Minimum value over all elements.
- norm((MatrixX)arg1) float : ¶
Euclidean norm.
- normalize((MatrixX)arg1) None : ¶
Normalize this object in-place.
- normalized((MatrixX)arg1) MatrixX : ¶
Return normalized copy of this object
- polarDecomposition((MatrixX)arg1) tuple : ¶
Alias for
computeUnitaryPositive
.
- prod((MatrixX)arg1) float : ¶
Product of all elements.
- pruned((MatrixX)arg1[, (float)absTol=1e-06]) MatrixX : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((MatrixX)arg1, (int)rows, (int)cols) None : ¶
Change size of the matrix, keep values of elements which exist in the new matrix
- row((MatrixX)arg1, (int)row) VectorX : ¶
Return row as vector.
- rows((MatrixX)arg1) int : ¶
Number of rows.
- selfAdjointEigenDecomposition((MatrixX)arg1) tuple : ¶
Compute eigen (spectral) decomposition of symmetric matrix, returns (eigVecs,eigVals). eigVecs is orthogonal Matrix3 with columns ar normalized eigenvectors, eigVals is Vector3 with corresponding eigenvalues. self=eigVecs*diag(eigVals)*eigVecs.transpose().
- spectralDecomposition((MatrixX)arg1) tuple : ¶
Alias for
selfAdjointEigenDecomposition
.
- squaredNorm((MatrixX)arg1) float : ¶
Square of the Euclidean norm.
- sum((MatrixX)arg1) float : ¶
Sum of all elements.
- trace((MatrixX)arg1) float : ¶
Return sum of diagonal elements.
- transpose((MatrixX)arg1) MatrixX : ¶
Return transposed matrix.
- class MatrixXc¶
/TODO/
- static Identity((int)arg1, (int)rank) MatrixXc : ¶
Create identity matrix with given rank (square).
- static Ones((int)rows, (int)cols) MatrixXc : ¶
Create matrix of given dimensions where all elements are set to 1.
- static Random((int)rows, (int)cols) MatrixXc : ¶
Create matrix with given dimensions where all elements are set to number between 0 and 1 (uniformly-distributed).
- static Zero((int)rows, (int)cols) MatrixXc : ¶
Create zero matrix of given dimensions
- __init__((object)arg1) None ¶
__init__( (object)arg1, (MatrixXc)other) -> None
__init__( (object)arg1, (VectorXc)diag) -> object
__init__( (object)arg1 [, (VectorXc)r0=VectorXc() [, (VectorXc)r1=VectorXc() [, (VectorXc)r2=VectorXc() [, (VectorXc)r3=VectorXc() [, (VectorXc)r4=VectorXc() [, (VectorXc)r5=VectorXc() [, (VectorXc)r6=VectorXc() [, (VectorXc)r7=VectorXc() [, (VectorXc)r8=VectorXc() [, (VectorXc)r9=VectorXc() [, (bool)cols=False]]]]]]]]]]]) -> object
__init__( (object)arg1, (object)rows [, (bool)cols=False]) -> object
- col((MatrixXc)arg1, (int)col) VectorXc : ¶
Return column as vector.
- cols((MatrixXc)arg1) int : ¶
Number of columns.
- determinant((MatrixXc)arg1) complex : ¶
Return matrix determinant.
- diagonal((MatrixXc)arg1) VectorXc : ¶
Return diagonal as vector.
- inverse((MatrixXc)arg1) MatrixXc : ¶
Return inverted matrix.
- isApprox((MatrixXc)arg1, (MatrixXc)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((MatrixXc)arg1) float : ¶
Maximum absolute value over all elements.
- mean((MatrixXc)arg1) complex : ¶
Mean value over all elements.
- norm((MatrixXc)arg1) float : ¶
Euclidean norm.
- normalize((MatrixXc)arg1) None : ¶
Normalize this object in-place.
- normalized((MatrixXc)arg1) MatrixXc : ¶
Return normalized copy of this object
- prod((MatrixXc)arg1) complex : ¶
Product of all elements.
- pruned((MatrixXc)arg1[, (float)absTol=1e-06]) MatrixXc : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((MatrixXc)arg1, (int)rows, (int)cols) None : ¶
Change size of the matrix, keep values of elements which exist in the new matrix
- row((MatrixXc)arg1, (int)row) VectorXc : ¶
Return row as vector.
- rows((MatrixXc)arg1) int : ¶
Number of rows.
- squaredNorm((MatrixXc)arg1) float : ¶
Square of the Euclidean norm.
- sum((MatrixXc)arg1) complex : ¶
Sum of all elements.
- trace((MatrixXc)arg1) complex : ¶
Return sum of diagonal elements.
- transpose((MatrixXc)arg1) MatrixXc : ¶
Return transposed matrix.
- class Quaternion¶
Quaternion representing rotation.
Supported operations (
q
is a Quaternion,v
is a Vector3):q*q
(rotation composition),q*=q
,q*v
(rotatingv
byq
),q==q
,q!=q
.Static attributes:
Identity
.Note
Quaternion is represented as axis-angle when printed (e.g.
Identity
isQuaternion((1,0,0),0)
, and can also be constructed from the axis-angle representation. This is however different from the data stored inside, which can be accessed by indices[0]
(\(x\)),[1]
(\(y\)),[2]
(\(z\)),[3]
(\(w\)). To obtain axis-angle programatically, useQuaternion.toAxisAngle
which returns the tuple.- Identity = Quaternion((1,0,0),0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3)axis, (float)angle) -> object
__init__( (object)arg1, (float)angle, (Vector3)axis) -> object
__init__( (object)arg1, (Vector3)u, (Vector3)v) -> object
- __init__( (object)arg1, (float)w, (float)x, (float)y, (float)z) -> None :
Initialize from coefficients.
Note
The order of coefficients is w, x, y, z. The [] operator numbers them differently, 0…4 for x y z w!
__init__( (object)arg1, (Matrix3)rotMatrix) -> None
__init__( (object)arg1, (Quaternion)other) -> None
- angularDistance((Quaternion)arg1, (Quaternion)arg2) float ¶
- conjugate((Quaternion)arg1) Quaternion ¶
- inverse((Quaternion)arg1) Quaternion ¶
- norm((Quaternion)arg1) float ¶
- normalize((Quaternion)arg1) None ¶
- normalized((Quaternion)arg1) Quaternion ¶
- setFromTwoVectors((Quaternion)arg1, (Vector3)u, (Vector3)v) None ¶
- slerp((Quaternion)arg1, (float)t, (Quaternion)other) Quaternion ¶
- toAngleAxis((Quaternion)arg1) tuple ¶
- toAxisAngle((Quaternion)arg1) tuple ¶
- class Vector2¶
3-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector3):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 2 floats.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
.- Identity = Vector2(1,0)¶
- Ones = Vector2(1,1)¶
- static Random() Vector2 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector2(1,0)¶
- UnitY = Vector2(0,1)¶
- Zero = Vector2(0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector2)other) -> None
__init__( (object)arg1, (float)x, (float)y) -> None
- asDiagonal((Vector2)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector2)arg1) int : ¶
Number of columns.
- dot((Vector2)arg1, (Vector2)other) float : ¶
Dot product with other.
- isApprox((Vector2)arg1, (Vector2)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector2)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector2)arg1) float : ¶
Maximum value over all elements.
- mean((Vector2)arg1) float : ¶
Mean value over all elements.
- minCoeff((Vector2)arg1) float : ¶
Minimum value over all elements.
- norm((Vector2)arg1) float : ¶
Euclidean norm.
- normalize((Vector2)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector2)arg1) Vector2 : ¶
Return normalized copy of this object
- outer((Vector2)arg1, (Vector2)other) object : ¶
Outer product with other.
- prod((Vector2)arg1) float : ¶
Product of all elements.
- pruned((Vector2)arg1[, (float)absTol=1e-06]) Vector2 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector2)arg1) int : ¶
Number of rows.
- squaredNorm((Vector2)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector2)arg1) float : ¶
Sum of all elements.
- class Vector2c¶
/TODO/
- Identity = Vector2c(1,0)¶
- Ones = Vector2c(1,1)¶
- static Random() Vector2c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector2c(1,0)¶
- UnitY = Vector2c(0,1)¶
- Zero = Vector2c(0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector2c)other) -> None
__init__( (object)arg1, (complex)x, (complex)y) -> None
- asDiagonal((Vector2c)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector2c)arg1) int : ¶
Number of columns.
- dot((Vector2c)arg1, (Vector2c)other) complex : ¶
Dot product with other.
- isApprox((Vector2c)arg1, (Vector2c)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector2c)arg1) float : ¶
Maximum absolute value over all elements.
- mean((Vector2c)arg1) complex : ¶
Mean value over all elements.
- norm((Vector2c)arg1) float : ¶
Euclidean norm.
- normalize((Vector2c)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector2c)arg1) Vector2c : ¶
Return normalized copy of this object
- outer((Vector2c)arg1, (Vector2c)other) object : ¶
Outer product with other.
- prod((Vector2c)arg1) complex : ¶
Product of all elements.
- pruned((Vector2c)arg1[, (float)absTol=1e-06]) Vector2c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector2c)arg1) int : ¶
Number of rows.
- squaredNorm((Vector2c)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector2c)arg1) complex : ¶
Sum of all elements.
- class Vector2i¶
2-dimensional integer vector.
Supported operations (
i
if an int,v
is a Vector2i):-v
,v+v
,v+=v
,v-v
,v-=v
,v*i
,i*v
,v*=i
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 2 integers.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
.- Identity = Vector2i(1,0)¶
- Ones = Vector2i(1,1)¶
- static Random() Vector2i : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector2i(1,0)¶
- UnitY = Vector2i(0,1)¶
- Zero = Vector2i(0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector2i)other) -> None
__init__( (object)arg1, (int)x, (int)y) -> None
- asDiagonal((Vector2i)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector2i)arg1) int : ¶
Number of columns.
- dot((Vector2i)arg1, (Vector2i)other) int : ¶
Dot product with other.
- isApprox((Vector2i)arg1, (Vector2i)other[, (int)prec=0]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector2i)arg1) int : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector2i)arg1) int : ¶
Maximum value over all elements.
- mean((Vector2i)arg1) int : ¶
Mean value over all elements.
- minCoeff((Vector2i)arg1) int : ¶
Minimum value over all elements.
- outer((Vector2i)arg1, (Vector2i)other) object : ¶
Outer product with other.
- prod((Vector2i)arg1) int : ¶
Product of all elements.
- rows((Vector2i)arg1) int : ¶
Number of rows.
- sum((Vector2i)arg1) int : ¶
Sum of all elements.
- class Vector3¶
3-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector3):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
, plus operations withMatrix3
andQuaternion
.Implicit conversion from sequence (list, tuple, …) of 3 floats.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
,UnitZ
.- Identity = Vector3(1,0,0)¶
- Ones = Vector3(1,1,1)¶
- static Random() Vector3 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector3(1,0,0)¶
- UnitY = Vector3(0,1,0)¶
- UnitZ = Vector3(0,0,1)¶
- Zero = Vector3(0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3)other) -> None
__init__( (object)arg1 [, (float)x=0.0 [, (float)y=0.0 [, (float)z=0.0]]]) -> None
- asDiagonal((Vector3)arg1) Matrix3 : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector3)arg1) int : ¶
Number of columns.
- dot((Vector3)arg1, (Vector3)other) float : ¶
Dot product with other.
- isApprox((Vector3)arg1, (Vector3)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector3)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector3)arg1) float : ¶
Maximum value over all elements.
- mean((Vector3)arg1) float : ¶
Mean value over all elements.
- minCoeff((Vector3)arg1) float : ¶
Minimum value over all elements.
- norm((Vector3)arg1) float : ¶
Euclidean norm.
- normalize((Vector3)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector3)arg1) Vector3 : ¶
Return normalized copy of this object
- outer((Vector3)arg1, (Vector3)other) Matrix3 : ¶
Outer product with other.
- prod((Vector3)arg1) float : ¶
Product of all elements.
- pruned((Vector3)arg1[, (float)absTol=1e-06]) Vector3 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector3)arg1) int : ¶
Number of rows.
- squaredNorm((Vector3)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector3)arg1) float : ¶
Sum of all elements.
- class Vector3c¶
/TODO/
- Identity = Vector3c(1,0,0)¶
- Ones = Vector3c(1,1,1)¶
- static Random() Vector3c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector3c(1,0,0)¶
- UnitY = Vector3c(0,1,0)¶
- UnitZ = Vector3c(0,0,1)¶
- Zero = Vector3c(0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3c)other) -> None
__init__( (object)arg1 [, (complex)x=0j [, (complex)y=0j [, (complex)z=0j]]]) -> None
- asDiagonal((Vector3c)arg1) Matrix3c : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector3c)arg1) int : ¶
Number of columns.
- dot((Vector3c)arg1, (Vector3c)other) complex : ¶
Dot product with other.
- isApprox((Vector3c)arg1, (Vector3c)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector3c)arg1) float : ¶
Maximum absolute value over all elements.
- mean((Vector3c)arg1) complex : ¶
Mean value over all elements.
- norm((Vector3c)arg1) float : ¶
Euclidean norm.
- normalize((Vector3c)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector3c)arg1) Vector3c : ¶
Return normalized copy of this object
- outer((Vector3c)arg1, (Vector3c)other) Matrix3c : ¶
Outer product with other.
- prod((Vector3c)arg1) complex : ¶
Product of all elements.
- pruned((Vector3c)arg1[, (float)absTol=1e-06]) Vector3c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector3c)arg1) int : ¶
Number of rows.
- squaredNorm((Vector3c)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector3c)arg1) complex : ¶
Sum of all elements.
- class Vector3i¶
3-dimensional integer vector.
Supported operations (
i
if an int,v
is a Vector3i):-v
,v+v
,v+=v
,v-v
,v-=v
,v*i
,i*v
,v*=i
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 3 integers.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
,UnitZ
.- Identity = Vector3i(1,0,0)¶
- Ones = Vector3i(1,1,1)¶
- static Random() Vector3i : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector3i(1,0,0)¶
- UnitY = Vector3i(0,1,0)¶
- UnitZ = Vector3i(0,0,1)¶
- Zero = Vector3i(0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3i)other) -> None
__init__( (object)arg1 [, (int)x=0 [, (int)y=0 [, (int)z=0]]]) -> None
- asDiagonal((Vector3i)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector3i)arg1) int : ¶
Number of columns.
- dot((Vector3i)arg1, (Vector3i)other) int : ¶
Dot product with other.
- isApprox((Vector3i)arg1, (Vector3i)other[, (int)prec=0]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector3i)arg1) int : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector3i)arg1) int : ¶
Maximum value over all elements.
- mean((Vector3i)arg1) int : ¶
Mean value over all elements.
- minCoeff((Vector3i)arg1) int : ¶
Minimum value over all elements.
- outer((Vector3i)arg1, (Vector3i)other) object : ¶
Outer product with other.
- prod((Vector3i)arg1) int : ¶
Product of all elements.
- rows((Vector3i)arg1) int : ¶
Number of rows.
- sum((Vector3i)arg1) int : ¶
Sum of all elements.
- class Vector4¶
4-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector3):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 4 floats.
Static attributes:
Zero
,Ones
.- Identity = Vector4(1,0,0, 0)¶
- Ones = Vector4(1,1,1, 1)¶
- static Random() Vector4 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Vector4(0,0,0, 0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector4)other) -> None
__init__( (object)arg1, (float)v0, (float)v1, (float)v2, (float)v3) -> None
- asDiagonal((Vector4)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector4)arg1) int : ¶
Number of columns.
- dot((Vector4)arg1, (Vector4)other) float : ¶
Dot product with other.
- isApprox((Vector4)arg1, (Vector4)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector4)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector4)arg1) float : ¶
Maximum value over all elements.
- mean((Vector4)arg1) float : ¶
Mean value over all elements.
- minCoeff((Vector4)arg1) float : ¶
Minimum value over all elements.
- norm((Vector4)arg1) float : ¶
Euclidean norm.
- normalize((Vector4)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector4)arg1) Vector4 : ¶
Return normalized copy of this object
- outer((Vector4)arg1, (Vector4)other) object : ¶
Outer product with other.
- prod((Vector4)arg1) float : ¶
Product of all elements.
- pruned((Vector4)arg1[, (float)absTol=1e-06]) Vector4 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector4)arg1) int : ¶
Number of rows.
- squaredNorm((Vector4)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector4)arg1) float : ¶
Sum of all elements.
- class Vector6¶
6-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector6):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 6 floats.
Static attributes:
Zero
,Ones
.- Identity = Vector6(1,0,0, 0,0,0)¶
- Ones = Vector6(1,1,1, 1,1,1)¶
- static Random() Vector6 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Vector6(0,0,0, 0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector6)other) -> None
__init__( (object)arg1, (float)v0, (float)v1, (float)v2, (float)v3, (float)v4, (float)v5) -> object
__init__( (object)arg1, (Vector3)head, (Vector3)tail) -> object
- asDiagonal((Vector6)arg1) Matrix6 : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector6)arg1) int : ¶
Number of columns.
- dot((Vector6)arg1, (Vector6)other) float : ¶
Dot product with other.
- isApprox((Vector6)arg1, (Vector6)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector6)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector6)arg1) float : ¶
Maximum value over all elements.
- mean((Vector6)arg1) float : ¶
Mean value over all elements.
- minCoeff((Vector6)arg1) float : ¶
Minimum value over all elements.
- norm((Vector6)arg1) float : ¶
Euclidean norm.
- normalize((Vector6)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector6)arg1) Vector6 : ¶
Return normalized copy of this object
- outer((Vector6)arg1, (Vector6)other) Matrix6 : ¶
Outer product with other.
- prod((Vector6)arg1) float : ¶
Product of all elements.
- pruned((Vector6)arg1[, (float)absTol=1e-06]) Vector6 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector6)arg1) int : ¶
Number of rows.
- squaredNorm((Vector6)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector6)arg1) float : ¶
Sum of all elements.
- class Vector6c¶
/TODO/
- Identity = Vector6c(1,0,0, 0,0,0)¶
- Ones = Vector6c(1,1,1, 1,1,1)¶
- static Random() Vector6c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Vector6c(0,0,0, 0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector6c)other) -> None
__init__( (object)arg1, (complex)v0, (complex)v1, (complex)v2, (complex)v3, (complex)v4, (complex)v5) -> object
__init__( (object)arg1, (Vector3c)head, (Vector3c)tail) -> object
- asDiagonal((Vector6c)arg1) Matrix6c : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector6c)arg1) int : ¶
Number of columns.
- dot((Vector6c)arg1, (Vector6c)other) complex : ¶
Dot product with other.
- isApprox((Vector6c)arg1, (Vector6c)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector6c)arg1) float : ¶
Maximum absolute value over all elements.
- mean((Vector6c)arg1) complex : ¶
Mean value over all elements.
- norm((Vector6c)arg1) float : ¶
Euclidean norm.
- normalize((Vector6c)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector6c)arg1) Vector6c : ¶
Return normalized copy of this object
- outer((Vector6c)arg1, (Vector6c)other) Matrix6c : ¶
Outer product with other.
- prod((Vector6c)arg1) complex : ¶
Product of all elements.
- pruned((Vector6c)arg1[, (float)absTol=1e-06]) Vector6c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector6c)arg1) int : ¶
Number of rows.
- squaredNorm((Vector6c)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector6c)arg1) complex : ¶
Sum of all elements.
- class Vector6i¶
6-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector6):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 6 ints.
Static attributes:
Zero
,Ones
.- Identity = Vector6i(1,0,0, 0,0,0)¶
- Ones = Vector6i(1,1,1, 1,1,1)¶
- static Random() Vector6i : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Vector6i(0,0,0, 0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector6i)other) -> None
__init__( (object)arg1, (int)v0, (int)v1, (int)v2, (int)v3, (int)v4, (int)v5) -> object
__init__( (object)arg1, (Vector3i)head, (Vector3i)tail) -> object
- asDiagonal((Vector6i)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector6i)arg1) int : ¶
Number of columns.
- dot((Vector6i)arg1, (Vector6i)other) int : ¶
Dot product with other.
- isApprox((Vector6i)arg1, (Vector6i)other[, (int)prec=0]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector6i)arg1) int : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector6i)arg1) int : ¶
Maximum value over all elements.
- mean((Vector6i)arg1) int : ¶
Mean value over all elements.
- minCoeff((Vector6i)arg1) int : ¶
Minimum value over all elements.
- outer((Vector6i)arg1, (Vector6i)other) object : ¶
Outer product with other.
- prod((Vector6i)arg1) int : ¶
Product of all elements.
- rows((Vector6i)arg1) int : ¶
Number of rows.
- sum((Vector6i)arg1) int : ¶
Sum of all elements.
- class VectorX¶
Dynamic-sized float vector.
Supported operations (
f
if a float/int,v
is a VectorX):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of X floats.
- static Random((int)len) VectorX : ¶
Return vector of given length with all elements set to values between 0 and 1 randomly.
- __init__((object)arg1) None ¶
__init__( (object)arg1, (VectorX)other) -> None
__init__( (object)arg1, (object)vv) -> object
- asDiagonal((VectorX)arg1) MatrixX : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((VectorX)arg1) int : ¶
Number of columns.
- dot((VectorX)arg1, (VectorX)other) float : ¶
Dot product with other.
- isApprox((VectorX)arg1, (VectorX)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((VectorX)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((VectorX)arg1) float : ¶
Maximum value over all elements.
- mean((VectorX)arg1) float : ¶
Mean value over all elements.
- minCoeff((VectorX)arg1) float : ¶
Minimum value over all elements.
- norm((VectorX)arg1) float : ¶
Euclidean norm.
- normalize((VectorX)arg1) None : ¶
Normalize this object in-place.
- normalized((VectorX)arg1) VectorX : ¶
Return normalized copy of this object
- outer((VectorX)arg1, (VectorX)other) MatrixX : ¶
Outer product with other.
- prod((VectorX)arg1) float : ¶
Product of all elements.
- pruned((VectorX)arg1[, (float)absTol=1e-06]) VectorX : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((VectorX)arg1, (int)arg2) None ¶
- rows((VectorX)arg1) int : ¶
Number of rows.
- squaredNorm((VectorX)arg1) float : ¶
Square of the Euclidean norm.
- sum((VectorX)arg1) float : ¶
Sum of all elements.
- class VectorXc¶
/TODO/
- static Random((int)len) VectorXc : ¶
Return vector of given length with all elements set to values between 0 and 1 randomly.
- __init__((object)arg1) None ¶
__init__( (object)arg1, (VectorXc)other) -> None
__init__( (object)arg1, (object)vv) -> object
- asDiagonal((VectorXc)arg1) MatrixXc : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((VectorXc)arg1) int : ¶
Number of columns.
- dot((VectorXc)arg1, (VectorXc)other) complex : ¶
Dot product with other.
- isApprox((VectorXc)arg1, (VectorXc)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((VectorXc)arg1) float : ¶
Maximum absolute value over all elements.
- mean((VectorXc)arg1) complex : ¶
Mean value over all elements.
- norm((VectorXc)arg1) float : ¶
Euclidean norm.
- normalize((VectorXc)arg1) None : ¶
Normalize this object in-place.
- normalized((VectorXc)arg1) VectorXc : ¶
Return normalized copy of this object
- outer((VectorXc)arg1, (VectorXc)other) MatrixXc : ¶
Outer product with other.
- prod((VectorXc)arg1) complex : ¶
Product of all elements.
- pruned((VectorXc)arg1[, (float)absTol=1e-06]) VectorXc : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((VectorXc)arg1, (int)arg2) None ¶
- rows((VectorXc)arg1) int : ¶
Number of rows.
- squaredNorm((VectorXc)arg1) float : ¶
Square of the Euclidean norm.
- sum((VectorXc)arg1) complex : ¶
Sum of all elements.
- vectorize = False¶
- class yade._minieigenHP.HP2¶
- class AlignedBox2¶
Axis-aligned box object in 2d, defined by its minimum and maximum corners
- __init__((object)arg1) None ¶
__init__( (object)arg1, (AlignedBox2)other) -> None
__init__( (object)arg1, (Vector2)min, (Vector2)max) -> None
- clamp((AlignedBox2)arg1, (AlignedBox2)arg2) None ¶
- contains((AlignedBox2)arg1, (Vector2)arg2) bool ¶
contains( (AlignedBox2)arg1, (AlignedBox2)arg2) -> bool
- empty((AlignedBox2)arg1) bool ¶
- extend((AlignedBox2)arg1, (Vector2)arg2) None ¶
extend( (AlignedBox2)arg1, (AlignedBox2)arg2) -> None
- intersection((AlignedBox2)arg1, (AlignedBox2)arg2) AlignedBox2 ¶
- property max¶
- merged((AlignedBox2)arg1, (AlignedBox2)arg2) AlignedBox2 ¶
- property min¶
- volume((AlignedBox2)arg1) object ¶
- class AlignedBox3¶
Axis-aligned box object, defined by its minimum and maximum corners
- __init__((object)arg1) None ¶
__init__( (object)arg1, (AlignedBox3)other) -> None
__init__( (object)arg1, (Vector3)min, (Vector3)max) -> None
- clamp((AlignedBox3)arg1, (AlignedBox3)arg2) None ¶
- contains((AlignedBox3)arg1, (Vector3)arg2) bool ¶
contains( (AlignedBox3)arg1, (AlignedBox3)arg2) -> bool
- empty((AlignedBox3)arg1) bool ¶
- extend((AlignedBox3)arg1, (Vector3)arg2) None ¶
extend( (AlignedBox3)arg1, (AlignedBox3)arg2) -> None
- intersection((AlignedBox3)arg1, (AlignedBox3)arg2) AlignedBox3 ¶
- property max¶
- merged((AlignedBox3)arg1, (AlignedBox3)arg2) AlignedBox3 ¶
- property min¶
- volume((AlignedBox3)arg1) object ¶
- class Matrix3¶
3x3 float matrix.
Supported operations (
m
is a Matrix3,f
if a float/int,v
is a Vector3):-m
,m+m
,m+=m
,m-m
,m-=m
,m*f
,f*m
,m*=f
,m/f
,m/=f
,m*m
,m*=m
,m*v
,v*m
,m==m
,m!=m
.Static attributes:
Zero
,Ones
,Identity
.- Identity = Matrix3("1","0","0", "0","1","0", "0","0","1")¶
- Ones = Matrix3("1","1","1", "1","1","1", "1","1","1")¶
- static Random() Matrix3 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix3("0","0","0", "0","0","0", "0","0","0")¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Quaternion)q) -> None
__init__( (object)arg1, (Matrix3)other) -> None
__init__( (object)arg1, (Vector3)diag) -> object
__init__( (object)arg1, (object)m00, (object)m01, (object)m02, (object)m10, (object)m11, (object)m12, (object)m20, (object)m21, (object)m22) -> object
__init__( (object)arg1, (Vector3)r0, (Vector3)r1, (Vector3)r2 [, (bool)cols=False]) -> object
- col((Matrix3)arg1, (int)col) Vector3 : ¶
Return column as vector.
- cols((Matrix3)arg1) int : ¶
Number of columns.
- computeUnitaryPositive((Matrix3)arg1) tuple : ¶
Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).
- determinant((Matrix3)arg1) object : ¶
Return matrix determinant.
- diagonal((Matrix3)arg1) Vector3 : ¶
Return diagonal as vector.
- inverse((Matrix3)arg1) Matrix3 : ¶
Return inverted matrix.
- isApprox((Matrix3)arg1, (Matrix3)other[, (object)prec=mpf('3.842735439305961757e-31')]) bool : ¶
Approximate comparison with precision prec.
- jacobiSVD((Matrix3)arg1) tuple : ¶
Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()
- maxAbsCoeff((Matrix3)arg1) object : ¶
Maximum absolute value over all elements.
- maxCoeff((Matrix3)arg1) object : ¶
Maximum value over all elements.
- mean((Matrix3)arg1) object : ¶
Mean value over all elements.
- minCoeff((Matrix3)arg1) object : ¶
Minimum value over all elements.
- norm((Matrix3)arg1) object : ¶
Euclidean norm.
- normalize((Matrix3)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix3)arg1) Matrix3 : ¶
Return normalized copy of this object
- polarDecomposition((Matrix3)arg1) tuple : ¶
Alias for
computeUnitaryPositive
.
- prod((Matrix3)arg1) object : ¶
Product of all elements.
- pruned((Matrix3)arg1[, (float)absTol=1e-06]) Matrix3 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix3)arg1, (int)row) Vector3 : ¶
Return row as vector.
- rows((Matrix3)arg1) int : ¶
Number of rows.
- selfAdjointEigenDecomposition((Matrix3)arg1) tuple : ¶
Compute eigen (spectral) decomposition of symmetric matrix, returns (eigVecs,eigVals). eigVecs is orthogonal Matrix3 with columns ar normalized eigenvectors, eigVals is Vector3 with corresponding eigenvalues. self=eigVecs*diag(eigVals)*eigVecs.transpose().
- spectralDecomposition((Matrix3)arg1) tuple : ¶
Alias for
selfAdjointEigenDecomposition
.
- squaredNorm((Matrix3)arg1) object : ¶
Square of the Euclidean norm.
- sum((Matrix3)arg1) object : ¶
Sum of all elements.
- trace((Matrix3)arg1) object : ¶
Return sum of diagonal elements.
- transpose((Matrix3)arg1) Matrix3 : ¶
Return transposed matrix.
- class Matrix3c¶
/TODO/
- Identity = Matrix3c(mpc("1","0"),mpc("0","0"),mpc("0","0"), mpc("0","0"),mpc("1","0"),mpc("0","0"), mpc("0","0"),mpc("0","0"),mpc("1","0"))¶
- Ones = Matrix3c(mpc("1","0"),mpc("1","0"),mpc("1","0"), mpc("1","0"),mpc("1","0"),mpc("1","0"), mpc("1","0"),mpc("1","0"),mpc("1","0"))¶
- static Random() Matrix3c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix3c(mpc("0","0"),mpc("0","0"),mpc("0","0"), mpc("0","0"),mpc("0","0"),mpc("0","0"), mpc("0","0"),mpc("0","0"),mpc("0","0"))¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Matrix3c)other) -> None
__init__( (object)arg1, (Vector3c)diag) -> object
__init__( (object)arg1, (object)m00, (object)m01, (object)m02, (object)m10, (object)m11, (object)m12, (object)m20, (object)m21, (object)m22) -> object
__init__( (object)arg1, (Vector3c)r0, (Vector3c)r1, (Vector3c)r2 [, (bool)cols=False]) -> object
- col((Matrix3c)arg1, (int)col) Vector3c : ¶
Return column as vector.
- cols((Matrix3c)arg1) int : ¶
Number of columns.
- determinant((Matrix3c)arg1) object : ¶
Return matrix determinant.
- diagonal((Matrix3c)arg1) Vector3c : ¶
Return diagonal as vector.
- inverse((Matrix3c)arg1) Matrix3c : ¶
Return inverted matrix.
- isApprox((Matrix3c)arg1, (Matrix3c)other[, (object)prec=mpc(real='3.842735439305961757e-31', imag='0.0')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Matrix3c)arg1) object : ¶
Maximum absolute value over all elements.
- mean((Matrix3c)arg1) object : ¶
Mean value over all elements.
- norm((Matrix3c)arg1) object : ¶
Euclidean norm.
- normalize((Matrix3c)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix3c)arg1) Matrix3c : ¶
Return normalized copy of this object
- prod((Matrix3c)arg1) object : ¶
Product of all elements.
- pruned((Matrix3c)arg1[, (float)absTol=1e-06]) Matrix3c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix3c)arg1, (int)row) Vector3c : ¶
Return row as vector.
- rows((Matrix3c)arg1) int : ¶
Number of rows.
- squaredNorm((Matrix3c)arg1) object : ¶
Square of the Euclidean norm.
- sum((Matrix3c)arg1) object : ¶
Sum of all elements.
- trace((Matrix3c)arg1) object : ¶
Return sum of diagonal elements.
- transpose((Matrix3c)arg1) Matrix3c : ¶
Return transposed matrix.
- class Matrix6¶
6x6 float matrix. Constructed from 4 3x3 sub-matrices, from 6xVector6 (rows).
Supported operations (
m
is a Matrix6,f
if a float/int,v
is a Vector6):-m
,m+m
,m+=m
,m-m
,m-=m
,m*f
,f*m
,m*=f
,m/f
,m/=f
,m*m
,m*=m
,m*v
,v*m
,m==m
,m!=m
.Static attributes:
Zero
,Ones
,Identity
.- Identity = Matrix6( ("1","0","0","0","0","0"), ("0","1","0","0","0","0"), ("0","0","1","0","0","0"), ("0","0","0","1","0","0"), ("0","0","0","0","1","0"), ("0","0","0","0","0","1") )¶
- Ones = Matrix6( ("1","1","1","1","1","1"), ("1","1","1","1","1","1"), ("1","1","1","1","1","1"), ("1","1","1","1","1","1"), ("1","1","1","1","1","1"), ("1","1","1","1","1","1") )¶
- static Random() Matrix6 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix6( ("0","0","0","0","0","0"), ("0","0","0","0","0","0"), ("0","0","0","0","0","0"), ("0","0","0","0","0","0"), ("0","0","0","0","0","0"), ("0","0","0","0","0","0") )¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Matrix6)other) -> None
__init__( (object)arg1, (Vector6)diag) -> object
__init__( (object)arg1, (Matrix3)ul, (Matrix3)ur, (Matrix3)ll, (Matrix3)lr) -> object
__init__( (object)arg1, (Vector6)l0, (Vector6)l1, (Vector6)l2, (Vector6)l3, (Vector6)l4, (Vector6)l5 [, (bool)cols=False]) -> object
- col((Matrix6)arg1, (int)col) Vector6 : ¶
Return column as vector.
- cols((Matrix6)arg1) int : ¶
Number of columns.
- computeUnitaryPositive((Matrix6)arg1) tuple : ¶
Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).
- determinant((Matrix6)arg1) object : ¶
Return matrix determinant.
- diagonal((Matrix6)arg1) Vector6 : ¶
Return diagonal as vector.
- inverse((Matrix6)arg1) Matrix6 : ¶
Return inverted matrix.
- isApprox((Matrix6)arg1, (Matrix6)other[, (object)prec=mpf('3.842735439305961757e-31')]) bool : ¶
Approximate comparison with precision prec.
- jacobiSVD((Matrix6)arg1) tuple : ¶
Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()
- ll((Matrix6)arg1) Matrix3 : ¶
Return lower-left 3x3 block
- lr((Matrix6)arg1) Matrix3 : ¶
Return lower-right 3x3 block
- maxAbsCoeff((Matrix6)arg1) object : ¶
Maximum absolute value over all elements.
- maxCoeff((Matrix6)arg1) object : ¶
Maximum value over all elements.
- mean((Matrix6)arg1) object : ¶
Mean value over all elements.
- minCoeff((Matrix6)arg1) object : ¶
Minimum value over all elements.
- norm((Matrix6)arg1) object : ¶
Euclidean norm.
- normalize((Matrix6)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix6)arg1) Matrix6 : ¶
Return normalized copy of this object
- polarDecomposition((Matrix6)arg1) tuple : ¶
Alias for
computeUnitaryPositive
.
- prod((Matrix6)arg1) object : ¶
Product of all elements.
- pruned((Matrix6)arg1[, (float)absTol=1e-06]) Matrix6 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix6)arg1, (int)row) Vector6 : ¶
Return row as vector.
- rows((Matrix6)arg1) int : ¶
Number of rows.
- selfAdjointEigenDecomposition((Matrix6)arg1) tuple : ¶
Compute eigen (spectral) decomposition of symmetric matrix, returns (eigVecs,eigVals). eigVecs is orthogonal Matrix3 with columns ar normalized eigenvectors, eigVals is Vector3 with corresponding eigenvalues. self=eigVecs*diag(eigVals)*eigVecs.transpose().
- spectralDecomposition((Matrix6)arg1) tuple : ¶
Alias for
selfAdjointEigenDecomposition
.
- squaredNorm((Matrix6)arg1) object : ¶
Square of the Euclidean norm.
- sum((Matrix6)arg1) object : ¶
Sum of all elements.
- trace((Matrix6)arg1) object : ¶
Return sum of diagonal elements.
- transpose((Matrix6)arg1) Matrix6 : ¶
Return transposed matrix.
- ul((Matrix6)arg1) Matrix3 : ¶
Return upper-left 3x3 block
- ur((Matrix6)arg1) Matrix3 : ¶
Return upper-right 3x3 block
- class Matrix6c¶
/TODO/
- Identity = Matrix6c( (mpc("1","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0")), (mpc("0","0"),mpc("1","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0")), (mpc("0","0"),mpc("0","0"),mpc("1","0"),mpc("0","0"),mpc("0","0"),mpc("0","0")), (mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("1","0"),mpc("0","0"),mpc("0","0")), (mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("1","0"),mpc("0","0")), (mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("1","0")) )¶
- Ones = Matrix6c( (mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0")), (mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0")), (mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0")), (mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0")), (mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0")), (mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0"),mpc("1","0")) )¶
- static Random() Matrix6c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix6c( (mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0")), (mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0")), (mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0")), (mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0")), (mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0")), (mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0"),mpc("0","0")) )¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Matrix6c)other) -> None
__init__( (object)arg1, (Vector6c)diag) -> object
__init__( (object)arg1, (Matrix3c)ul, (Matrix3c)ur, (Matrix3c)ll, (Matrix3c)lr) -> object
__init__( (object)arg1, (Vector6c)l0, (Vector6c)l1, (Vector6c)l2, (Vector6c)l3, (Vector6c)l4, (Vector6c)l5 [, (bool)cols=False]) -> object
- col((Matrix6c)arg1, (int)col) Vector6c : ¶
Return column as vector.
- cols((Matrix6c)arg1) int : ¶
Number of columns.
- determinant((Matrix6c)arg1) object : ¶
Return matrix determinant.
- diagonal((Matrix6c)arg1) Vector6c : ¶
Return diagonal as vector.
- inverse((Matrix6c)arg1) Matrix6c : ¶
Return inverted matrix.
- isApprox((Matrix6c)arg1, (Matrix6c)other[, (object)prec=mpc(real='3.842735439305961757e-31', imag='0.0')]) bool : ¶
Approximate comparison with precision prec.
- ll((Matrix6c)arg1) Matrix3c : ¶
Return lower-left 3x3 block
- lr((Matrix6c)arg1) Matrix3c : ¶
Return lower-right 3x3 block
- maxAbsCoeff((Matrix6c)arg1) object : ¶
Maximum absolute value over all elements.
- mean((Matrix6c)arg1) object : ¶
Mean value over all elements.
- norm((Matrix6c)arg1) object : ¶
Euclidean norm.
- normalize((Matrix6c)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix6c)arg1) Matrix6c : ¶
Return normalized copy of this object
- prod((Matrix6c)arg1) object : ¶
Product of all elements.
- pruned((Matrix6c)arg1[, (float)absTol=1e-06]) Matrix6c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix6c)arg1, (int)row) Vector6c : ¶
Return row as vector.
- rows((Matrix6c)arg1) int : ¶
Number of rows.
- squaredNorm((Matrix6c)arg1) object : ¶
Square of the Euclidean norm.
- sum((Matrix6c)arg1) object : ¶
Sum of all elements.
- trace((Matrix6c)arg1) object : ¶
Return sum of diagonal elements.
- transpose((Matrix6c)arg1) Matrix6c : ¶
Return transposed matrix.
- ul((Matrix6c)arg1) Matrix3c : ¶
Return upper-left 3x3 block
- ur((Matrix6c)arg1) Matrix3c : ¶
Return upper-right 3x3 block
- class MatrixX¶
XxX (dynamic-sized) float matrix. Constructed from list of rows (as VectorX).
Supported operations (
m
is a MatrixX,f
if a float/int,v
is a VectorX):-m
,m+m
,m+=m
,m-m
,m-=m
,m*f
,f*m
,m*=f
,m/f
,m/=f
,m*m
,m*=m
,m*v
,v*m
,m==m
,m!=m
.- static Identity((int)arg1, (int)rank) MatrixX : ¶
Create identity matrix with given rank (square).
- static Ones((int)rows, (int)cols) MatrixX : ¶
Create matrix of given dimensions where all elements are set to 1.
- static Random((int)rows, (int)cols) MatrixX : ¶
Create matrix with given dimensions where all elements are set to number between 0 and 1 (uniformly-distributed).
- static Zero((int)rows, (int)cols) MatrixX : ¶
Create zero matrix of given dimensions
- __init__((object)arg1) None ¶
__init__( (object)arg1, (MatrixX)other) -> None
__init__( (object)arg1, (VectorX)diag) -> object
__init__( (object)arg1 [, (VectorX)r0=VectorX() [, (VectorX)r1=VectorX() [, (VectorX)r2=VectorX() [, (VectorX)r3=VectorX() [, (VectorX)r4=VectorX() [, (VectorX)r5=VectorX() [, (VectorX)r6=VectorX() [, (VectorX)r7=VectorX() [, (VectorX)r8=VectorX() [, (VectorX)r9=VectorX() [, (bool)cols=False]]]]]]]]]]]) -> object
__init__( (object)arg1, (object)rows [, (bool)cols=False]) -> object
- col((MatrixX)arg1, (int)col) VectorX : ¶
Return column as vector.
- cols((MatrixX)arg1) int : ¶
Number of columns.
- computeUnitaryPositive((MatrixX)arg1) tuple : ¶
Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).
- determinant((MatrixX)arg1) object : ¶
Return matrix determinant.
- diagonal((MatrixX)arg1) VectorX : ¶
Return diagonal as vector.
- inverse((MatrixX)arg1) MatrixX : ¶
Return inverted matrix.
- isApprox((MatrixX)arg1, (MatrixX)other[, (object)prec=mpf('3.842735439305961757e-31')]) bool : ¶
Approximate comparison with precision prec.
- jacobiSVD((MatrixX)arg1) tuple : ¶
Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()
- maxAbsCoeff((MatrixX)arg1) object : ¶
Maximum absolute value over all elements.
- maxCoeff((MatrixX)arg1) object : ¶
Maximum value over all elements.
- mean((MatrixX)arg1) object : ¶
Mean value over all elements.
- minCoeff((MatrixX)arg1) object : ¶
Minimum value over all elements.
- norm((MatrixX)arg1) object : ¶
Euclidean norm.
- normalize((MatrixX)arg1) None : ¶
Normalize this object in-place.
- normalized((MatrixX)arg1) MatrixX : ¶
Return normalized copy of this object
- polarDecomposition((MatrixX)arg1) tuple : ¶
Alias for
computeUnitaryPositive
.
- prod((MatrixX)arg1) object : ¶
Product of all elements.
- pruned((MatrixX)arg1[, (float)absTol=1e-06]) MatrixX : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((MatrixX)arg1, (int)rows, (int)cols) None : ¶
Change size of the matrix, keep values of elements which exist in the new matrix
- row((MatrixX)arg1, (int)row) VectorX : ¶
Return row as vector.
- rows((MatrixX)arg1) int : ¶
Number of rows.
- selfAdjointEigenDecomposition((MatrixX)arg1) tuple : ¶
Compute eigen (spectral) decomposition of symmetric matrix, returns (eigVecs,eigVals). eigVecs is orthogonal Matrix3 with columns ar normalized eigenvectors, eigVals is Vector3 with corresponding eigenvalues. self=eigVecs*diag(eigVals)*eigVecs.transpose().
- spectralDecomposition((MatrixX)arg1) tuple : ¶
Alias for
selfAdjointEigenDecomposition
.
- squaredNorm((MatrixX)arg1) object : ¶
Square of the Euclidean norm.
- sum((MatrixX)arg1) object : ¶
Sum of all elements.
- trace((MatrixX)arg1) object : ¶
Return sum of diagonal elements.
- transpose((MatrixX)arg1) MatrixX : ¶
Return transposed matrix.
- class MatrixXc¶
/TODO/
- static Identity((int)arg1, (int)rank) MatrixXc : ¶
Create identity matrix with given rank (square).
- static Ones((int)rows, (int)cols) MatrixXc : ¶
Create matrix of given dimensions where all elements are set to 1.
- static Random((int)rows, (int)cols) MatrixXc : ¶
Create matrix with given dimensions where all elements are set to number between 0 and 1 (uniformly-distributed).
- static Zero((int)rows, (int)cols) MatrixXc : ¶
Create zero matrix of given dimensions
- __init__((object)arg1) None ¶
__init__( (object)arg1, (MatrixXc)other) -> None
__init__( (object)arg1, (VectorXc)diag) -> object
__init__( (object)arg1 [, (VectorXc)r0=VectorXc() [, (VectorXc)r1=VectorXc() [, (VectorXc)r2=VectorXc() [, (VectorXc)r3=VectorXc() [, (VectorXc)r4=VectorXc() [, (VectorXc)r5=VectorXc() [, (VectorXc)r6=VectorXc() [, (VectorXc)r7=VectorXc() [, (VectorXc)r8=VectorXc() [, (VectorXc)r9=VectorXc() [, (bool)cols=False]]]]]]]]]]]) -> object
__init__( (object)arg1, (object)rows [, (bool)cols=False]) -> object
- col((MatrixXc)arg1, (int)col) VectorXc : ¶
Return column as vector.
- cols((MatrixXc)arg1) int : ¶
Number of columns.
- determinant((MatrixXc)arg1) object : ¶
Return matrix determinant.
- diagonal((MatrixXc)arg1) VectorXc : ¶
Return diagonal as vector.
- inverse((MatrixXc)arg1) MatrixXc : ¶
Return inverted matrix.
- isApprox((MatrixXc)arg1, (MatrixXc)other[, (object)prec=mpc(real='3.842735439305961757e-31', imag='0.0')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((MatrixXc)arg1) object : ¶
Maximum absolute value over all elements.
- mean((MatrixXc)arg1) object : ¶
Mean value over all elements.
- norm((MatrixXc)arg1) object : ¶
Euclidean norm.
- normalize((MatrixXc)arg1) None : ¶
Normalize this object in-place.
- normalized((MatrixXc)arg1) MatrixXc : ¶
Return normalized copy of this object
- prod((MatrixXc)arg1) object : ¶
Product of all elements.
- pruned((MatrixXc)arg1[, (float)absTol=1e-06]) MatrixXc : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((MatrixXc)arg1, (int)rows, (int)cols) None : ¶
Change size of the matrix, keep values of elements which exist in the new matrix
- row((MatrixXc)arg1, (int)row) VectorXc : ¶
Return row as vector.
- rows((MatrixXc)arg1) int : ¶
Number of rows.
- squaredNorm((MatrixXc)arg1) object : ¶
Square of the Euclidean norm.
- sum((MatrixXc)arg1) object : ¶
Sum of all elements.
- trace((MatrixXc)arg1) object : ¶
Return sum of diagonal elements.
- transpose((MatrixXc)arg1) MatrixXc : ¶
Return transposed matrix.
- class Quaternion¶
Quaternion representing rotation.
Supported operations (
q
is a Quaternion,v
is a Vector3):q*q
(rotation composition),q*=q
,q*v
(rotatingv
byq
),q==q
,q!=q
.Static attributes:
Identity
.Note
Quaternion is represented as axis-angle when printed (e.g.
Identity
isQuaternion((1,0,0),0)
, and can also be constructed from the axis-angle representation. This is however different from the data stored inside, which can be accessed by indices[0]
(\(x\)),[1]
(\(y\)),[2]
(\(z\)),[3]
(\(w\)). To obtain axis-angle programatically, useQuaternion.toAxisAngle
which returns the tuple.- Identity = Quaternion(("1","0","0"),"0")¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3)axis, (object)angle) -> object
__init__( (object)arg1, (object)angle, (Vector3)axis) -> object
__init__( (object)arg1, (Vector3)u, (Vector3)v) -> object
- __init__( (object)arg1, (object)w, (object)x, (object)y, (object)z) -> None :
Initialize from coefficients.
Note
The order of coefficients is w, x, y, z. The [] operator numbers them differently, 0…4 for x y z w!
__init__( (object)arg1, (Matrix3)rotMatrix) -> None
__init__( (object)arg1, (Quaternion)other) -> None
- angularDistance((Quaternion)arg1, (Quaternion)arg2) object ¶
- conjugate((Quaternion)arg1) Quaternion ¶
- inverse((Quaternion)arg1) Quaternion ¶
- norm((Quaternion)arg1) object ¶
- normalize((Quaternion)arg1) None ¶
- normalized((Quaternion)arg1) Quaternion ¶
- setFromTwoVectors((Quaternion)arg1, (Vector3)u, (Vector3)v) None ¶
- slerp((Quaternion)arg1, (object)t, (Quaternion)other) Quaternion ¶
- toAngleAxis((Quaternion)arg1) tuple ¶
- toAxisAngle((Quaternion)arg1) tuple ¶
- class Vector2¶
3-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector3):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 2 floats.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
.- Identity = Vector2("1","0")¶
- Ones = Vector2("1","1")¶
- static Random() Vector2 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector2("1","0")¶
- UnitY = Vector2("0","1")¶
- Zero = Vector2("0","0")¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector2)other) -> None
__init__( (object)arg1, (object)x, (object)y) -> None
- asDiagonal((Vector2)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector2)arg1) int : ¶
Number of columns.
- dot((Vector2)arg1, (Vector2)other) object : ¶
Dot product with other.
- isApprox((Vector2)arg1, (Vector2)other[, (object)prec=mpf('3.842735439305961757e-31')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector2)arg1) object : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector2)arg1) object : ¶
Maximum value over all elements.
- mean((Vector2)arg1) object : ¶
Mean value over all elements.
- minCoeff((Vector2)arg1) object : ¶
Minimum value over all elements.
- norm((Vector2)arg1) object : ¶
Euclidean norm.
- normalize((Vector2)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector2)arg1) Vector2 : ¶
Return normalized copy of this object
- outer((Vector2)arg1, (Vector2)other) object : ¶
Outer product with other.
- prod((Vector2)arg1) object : ¶
Product of all elements.
- pruned((Vector2)arg1[, (float)absTol=1e-06]) Vector2 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector2)arg1) int : ¶
Number of rows.
- squaredNorm((Vector2)arg1) object : ¶
Square of the Euclidean norm.
- sum((Vector2)arg1) object : ¶
Sum of all elements.
- class Vector2c¶
/TODO/
- Identity = Vector2c(mpc("1","0"),mpc("0","0"))¶
- Ones = Vector2c(mpc("1","0"),mpc("1","0"))¶
- static Random() Vector2c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector2c(mpc("1","0"),mpc("0","0"))¶
- UnitY = Vector2c(mpc("0","0"),mpc("1","0"))¶
- Zero = Vector2c(mpc("0","0"),mpc("0","0"))¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector2c)other) -> None
__init__( (object)arg1, (object)x, (object)y) -> None
- asDiagonal((Vector2c)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector2c)arg1) int : ¶
Number of columns.
- dot((Vector2c)arg1, (Vector2c)other) object : ¶
Dot product with other.
- isApprox((Vector2c)arg1, (Vector2c)other[, (object)prec=mpc(real='3.842735439305961757e-31', imag='0.0')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector2c)arg1) object : ¶
Maximum absolute value over all elements.
- mean((Vector2c)arg1) object : ¶
Mean value over all elements.
- norm((Vector2c)arg1) object : ¶
Euclidean norm.
- normalize((Vector2c)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector2c)arg1) Vector2c : ¶
Return normalized copy of this object
- outer((Vector2c)arg1, (Vector2c)other) object : ¶
Outer product with other.
- prod((Vector2c)arg1) object : ¶
Product of all elements.
- pruned((Vector2c)arg1[, (float)absTol=1e-06]) Vector2c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector2c)arg1) int : ¶
Number of rows.
- squaredNorm((Vector2c)arg1) object : ¶
Square of the Euclidean norm.
- sum((Vector2c)arg1) object : ¶
Sum of all elements.
- class Vector2i¶
2-dimensional integer vector.
Supported operations (
i
if an int,v
is a Vector2i):-v
,v+v
,v+=v
,v-v
,v-=v
,v*i
,i*v
,v*=i
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 2 integers.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
.- Identity = Vector2i(1,0)¶
- Ones = Vector2i(1,1)¶
- static Random() Vector2i : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector2i(1,0)¶
- UnitY = Vector2i(0,1)¶
- Zero = Vector2i(0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector2i)other) -> None
__init__( (object)arg1, (int)x, (int)y) -> None
- asDiagonal((Vector2i)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector2i)arg1) int : ¶
Number of columns.
- dot((Vector2i)arg1, (Vector2i)other) int : ¶
Dot product with other.
- isApprox((Vector2i)arg1, (Vector2i)other[, (int)prec=0]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector2i)arg1) int : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector2i)arg1) int : ¶
Maximum value over all elements.
- mean((Vector2i)arg1) int : ¶
Mean value over all elements.
- minCoeff((Vector2i)arg1) int : ¶
Minimum value over all elements.
- outer((Vector2i)arg1, (Vector2i)other) object : ¶
Outer product with other.
- prod((Vector2i)arg1) int : ¶
Product of all elements.
- rows((Vector2i)arg1) int : ¶
Number of rows.
- sum((Vector2i)arg1) int : ¶
Sum of all elements.
- class Vector3¶
3-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector3):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
, plus operations withMatrix3
andQuaternion
.Implicit conversion from sequence (list, tuple, …) of 3 floats.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
,UnitZ
.- Identity = Vector3("1","0","0")¶
- Ones = Vector3("1","1","1")¶
- static Random() Vector3 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector3("1","0","0")¶
- UnitY = Vector3("0","1","0")¶
- UnitZ = Vector3("0","0","1")¶
- Zero = Vector3("0","0","0")¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3)other) -> None
__init__( (object)arg1 [, (object)x=mpf(‘0.0’) [, (object)y=mpf(‘0.0’) [, (object)z=mpf(‘0.0’)]]]) -> None
- asDiagonal((Vector3)arg1) Matrix3 : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector3)arg1) int : ¶
Number of columns.
- dot((Vector3)arg1, (Vector3)other) object : ¶
Dot product with other.
- isApprox((Vector3)arg1, (Vector3)other[, (object)prec=mpf('3.842735439305961757e-31')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector3)arg1) object : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector3)arg1) object : ¶
Maximum value over all elements.
- mean((Vector3)arg1) object : ¶
Mean value over all elements.
- minCoeff((Vector3)arg1) object : ¶
Minimum value over all elements.
- norm((Vector3)arg1) object : ¶
Euclidean norm.
- normalize((Vector3)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector3)arg1) Vector3 : ¶
Return normalized copy of this object
- outer((Vector3)arg1, (Vector3)other) Matrix3 : ¶
Outer product with other.
- prod((Vector3)arg1) object : ¶
Product of all elements.
- pruned((Vector3)arg1[, (float)absTol=1e-06]) Vector3 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector3)arg1) int : ¶
Number of rows.
- squaredNorm((Vector3)arg1) object : ¶
Square of the Euclidean norm.
- sum((Vector3)arg1) object : ¶
Sum of all elements.
- class Vector3c¶
/TODO/
- Identity = Vector3c(mpc("1","0"),mpc("0","0"),mpc("0","0"))¶
- Ones = Vector3c(mpc("1","0"),mpc("1","0"),mpc("1","0"))¶
- static Random() Vector3c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector3c(mpc("1","0"),mpc("0","0"),mpc("0","0"))¶
- UnitY = Vector3c(mpc("0","0"),mpc("1","0"),mpc("0","0"))¶
- UnitZ = Vector3c(mpc("0","0"),mpc("0","0"),mpc("1","0"))¶
- Zero = Vector3c(mpc("0","0"),mpc("0","0"),mpc("0","0"))¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3c)other) -> None
__init__( (object)arg1 [, (object)x=mpc(real=’0.0’, imag=’0.0’) [, (object)y=mpc(real=’0.0’, imag=’0.0’) [, (object)z=mpc(real=’0.0’, imag=’0.0’)]]]) -> None
- asDiagonal((Vector3c)arg1) Matrix3c : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector3c)arg1) int : ¶
Number of columns.
- dot((Vector3c)arg1, (Vector3c)other) object : ¶
Dot product with other.
- isApprox((Vector3c)arg1, (Vector3c)other[, (object)prec=mpc(real='3.842735439305961757e-31', imag='0.0')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector3c)arg1) object : ¶
Maximum absolute value over all elements.
- mean((Vector3c)arg1) object : ¶
Mean value over all elements.
- norm((Vector3c)arg1) object : ¶
Euclidean norm.
- normalize((Vector3c)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector3c)arg1) Vector3c : ¶
Return normalized copy of this object
- outer((Vector3c)arg1, (Vector3c)other) Matrix3c : ¶
Outer product with other.
- prod((Vector3c)arg1) object : ¶
Product of all elements.
- pruned((Vector3c)arg1[, (float)absTol=1e-06]) Vector3c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector3c)arg1) int : ¶
Number of rows.
- squaredNorm((Vector3c)arg1) object : ¶
Square of the Euclidean norm.
- sum((Vector3c)arg1) object : ¶
Sum of all elements.
- class Vector3i¶
3-dimensional integer vector.
Supported operations (
i
if an int,v
is a Vector3i):-v
,v+v
,v+=v
,v-v
,v-=v
,v*i
,i*v
,v*=i
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 3 integers.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
,UnitZ
.- Identity = Vector3i(1,0,0)¶
- Ones = Vector3i(1,1,1)¶
- static Random() Vector3i : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector3i(1,0,0)¶
- UnitY = Vector3i(0,1,0)¶
- UnitZ = Vector3i(0,0,1)¶
- Zero = Vector3i(0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3i)other) -> None
__init__( (object)arg1 [, (int)x=0 [, (int)y=0 [, (int)z=0]]]) -> None
- asDiagonal((Vector3i)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector3i)arg1) int : ¶
Number of columns.
- dot((Vector3i)arg1, (Vector3i)other) int : ¶
Dot product with other.
- isApprox((Vector3i)arg1, (Vector3i)other[, (int)prec=0]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector3i)arg1) int : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector3i)arg1) int : ¶
Maximum value over all elements.
- mean((Vector3i)arg1) int : ¶
Mean value over all elements.
- minCoeff((Vector3i)arg1) int : ¶
Minimum value over all elements.
- outer((Vector3i)arg1, (Vector3i)other) object : ¶
Outer product with other.
- prod((Vector3i)arg1) int : ¶
Product of all elements.
- rows((Vector3i)arg1) int : ¶
Number of rows.
- sum((Vector3i)arg1) int : ¶
Sum of all elements.
- class Vector4¶
4-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector3):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 4 floats.
Static attributes:
Zero
,Ones
.- Identity = Vector4("1","0","0", "0")¶
- Ones = Vector4("1","1","1", "1")¶
- static Random() Vector4 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Vector4("0","0","0", "0")¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector4)other) -> None
__init__( (object)arg1, (object)v0, (object)v1, (object)v2, (object)v3) -> None
- asDiagonal((Vector4)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector4)arg1) int : ¶
Number of columns.
- dot((Vector4)arg1, (Vector4)other) object : ¶
Dot product with other.
- isApprox((Vector4)arg1, (Vector4)other[, (object)prec=mpf('3.842735439305961757e-31')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector4)arg1) object : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector4)arg1) object : ¶
Maximum value over all elements.
- mean((Vector4)arg1) object : ¶
Mean value over all elements.
- minCoeff((Vector4)arg1) object : ¶
Minimum value over all elements.
- norm((Vector4)arg1) object : ¶
Euclidean norm.
- normalize((Vector4)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector4)arg1) Vector4 : ¶
Return normalized copy of this object
- outer((Vector4)arg1, (Vector4)other) object : ¶
Outer product with other.
- prod((Vector4)arg1) object : ¶
Product of all elements.
- pruned((Vector4)arg1[, (float)absTol=1e-06]) Vector4 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector4)arg1) int : ¶
Number of rows.
- squaredNorm((Vector4)arg1) object : ¶
Square of the Euclidean norm.
- sum((Vector4)arg1) object : ¶
Sum of all elements.
- class Vector6¶
6-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector6):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 6 floats.
Static attributes:
Zero
,Ones
.- Identity = Vector6("1","0","0", "0","0","0")¶
- Ones = Vector6("1","1","1", "1","1","1")¶
- static Random() Vector6 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Vector6("0","0","0", "0","0","0")¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector6)other) -> None
__init__( (object)arg1, (object)v0, (object)v1, (object)v2, (object)v3, (object)v4, (object)v5) -> object
__init__( (object)arg1, (Vector3)head, (Vector3)tail) -> object
- asDiagonal((Vector6)arg1) Matrix6 : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector6)arg1) int : ¶
Number of columns.
- dot((Vector6)arg1, (Vector6)other) object : ¶
Dot product with other.
- isApprox((Vector6)arg1, (Vector6)other[, (object)prec=mpf('3.842735439305961757e-31')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector6)arg1) object : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector6)arg1) object : ¶
Maximum value over all elements.
- mean((Vector6)arg1) object : ¶
Mean value over all elements.
- minCoeff((Vector6)arg1) object : ¶
Minimum value over all elements.
- norm((Vector6)arg1) object : ¶
Euclidean norm.
- normalize((Vector6)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector6)arg1) Vector6 : ¶
Return normalized copy of this object
- outer((Vector6)arg1, (Vector6)other) Matrix6 : ¶
Outer product with other.
- prod((Vector6)arg1) object : ¶
Product of all elements.
- pruned((Vector6)arg1[, (float)absTol=1e-06]) Vector6 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector6)arg1) int : ¶
Number of rows.
- squaredNorm((Vector6)arg1) object : ¶
Square of the Euclidean norm.
- sum((Vector6)arg1) object : ¶
Sum of all elements.
- class Vector6c¶
/TODO/
- Identity = Vector6c(mpc("1","0"),mpc("0","0"),mpc("0","0"), mpc("0","0"),mpc("0","0"),mpc("0","0"))¶
- Ones = Vector6c(mpc("1","0"),mpc("1","0"),mpc("1","0"), mpc("1","0"),mpc("1","0"),mpc("1","0"))¶
- static Random() Vector6c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Vector6c(mpc("0","0"),mpc("0","0"),mpc("0","0"), mpc("0","0"),mpc("0","0"),mpc("0","0"))¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector6c)other) -> None
__init__( (object)arg1, (object)v0, (object)v1, (object)v2, (object)v3, (object)v4, (object)v5) -> object
__init__( (object)arg1, (Vector3c)head, (Vector3c)tail) -> object
- asDiagonal((Vector6c)arg1) Matrix6c : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector6c)arg1) int : ¶
Number of columns.
- dot((Vector6c)arg1, (Vector6c)other) object : ¶
Dot product with other.
- isApprox((Vector6c)arg1, (Vector6c)other[, (object)prec=mpc(real='3.842735439305961757e-31', imag='0.0')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector6c)arg1) object : ¶
Maximum absolute value over all elements.
- mean((Vector6c)arg1) object : ¶
Mean value over all elements.
- norm((Vector6c)arg1) object : ¶
Euclidean norm.
- normalize((Vector6c)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector6c)arg1) Vector6c : ¶
Return normalized copy of this object
- outer((Vector6c)arg1, (Vector6c)other) Matrix6c : ¶
Outer product with other.
- prod((Vector6c)arg1) object : ¶
Product of all elements.
- pruned((Vector6c)arg1[, (float)absTol=1e-06]) Vector6c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector6c)arg1) int : ¶
Number of rows.
- squaredNorm((Vector6c)arg1) object : ¶
Square of the Euclidean norm.
- sum((Vector6c)arg1) object : ¶
Sum of all elements.
- class Vector6i¶
6-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector6):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 6 ints.
Static attributes:
Zero
,Ones
.- Identity = Vector6i(1,0,0, 0,0,0)¶
- Ones = Vector6i(1,1,1, 1,1,1)¶
- static Random() Vector6i : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Vector6i(0,0,0, 0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector6i)other) -> None
__init__( (object)arg1, (int)v0, (int)v1, (int)v2, (int)v3, (int)v4, (int)v5) -> object
__init__( (object)arg1, (Vector3i)head, (Vector3i)tail) -> object
- asDiagonal((Vector6i)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector6i)arg1) int : ¶
Number of columns.
- dot((Vector6i)arg1, (Vector6i)other) int : ¶
Dot product with other.
- isApprox((Vector6i)arg1, (Vector6i)other[, (int)prec=0]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector6i)arg1) int : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector6i)arg1) int : ¶
Maximum value over all elements.
- mean((Vector6i)arg1) int : ¶
Mean value over all elements.
- minCoeff((Vector6i)arg1) int : ¶
Minimum value over all elements.
- outer((Vector6i)arg1, (Vector6i)other) object : ¶
Outer product with other.
- prod((Vector6i)arg1) int : ¶
Product of all elements.
- rows((Vector6i)arg1) int : ¶
Number of rows.
- sum((Vector6i)arg1) int : ¶
Sum of all elements.
- class VectorX¶
Dynamic-sized float vector.
Supported operations (
f
if a float/int,v
is a VectorX):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of X floats.
- static Random((int)len) VectorX : ¶
Return vector of given length with all elements set to values between 0 and 1 randomly.
- __init__((object)arg1) None ¶
__init__( (object)arg1, (VectorX)other) -> None
__init__( (object)arg1, (object)vv) -> object
- asDiagonal((VectorX)arg1) MatrixX : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((VectorX)arg1) int : ¶
Number of columns.
- dot((VectorX)arg1, (VectorX)other) object : ¶
Dot product with other.
- isApprox((VectorX)arg1, (VectorX)other[, (object)prec=mpf('3.842735439305961757e-31')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((VectorX)arg1) object : ¶
Maximum absolute value over all elements.
- maxCoeff((VectorX)arg1) object : ¶
Maximum value over all elements.
- mean((VectorX)arg1) object : ¶
Mean value over all elements.
- minCoeff((VectorX)arg1) object : ¶
Minimum value over all elements.
- norm((VectorX)arg1) object : ¶
Euclidean norm.
- normalize((VectorX)arg1) None : ¶
Normalize this object in-place.
- normalized((VectorX)arg1) VectorX : ¶
Return normalized copy of this object
- outer((VectorX)arg1, (VectorX)other) MatrixX : ¶
Outer product with other.
- prod((VectorX)arg1) object : ¶
Product of all elements.
- pruned((VectorX)arg1[, (float)absTol=1e-06]) VectorX : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((VectorX)arg1, (int)arg2) None ¶
- rows((VectorX)arg1) int : ¶
Number of rows.
- squaredNorm((VectorX)arg1) object : ¶
Square of the Euclidean norm.
- sum((VectorX)arg1) object : ¶
Sum of all elements.
- class VectorXc¶
/TODO/
- static Random((int)len) VectorXc : ¶
Return vector of given length with all elements set to values between 0 and 1 randomly.
- __init__((object)arg1) None ¶
__init__( (object)arg1, (VectorXc)other) -> None
__init__( (object)arg1, (object)vv) -> object
- asDiagonal((VectorXc)arg1) MatrixXc : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((VectorXc)arg1) int : ¶
Number of columns.
- dot((VectorXc)arg1, (VectorXc)other) object : ¶
Dot product with other.
- isApprox((VectorXc)arg1, (VectorXc)other[, (object)prec=mpc(real='3.842735439305961757e-31', imag='0.0')]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((VectorXc)arg1) object : ¶
Maximum absolute value over all elements.
- mean((VectorXc)arg1) object : ¶
Mean value over all elements.
- norm((VectorXc)arg1) object : ¶
Euclidean norm.
- normalize((VectorXc)arg1) None : ¶
Normalize this object in-place.
- normalized((VectorXc)arg1) VectorXc : ¶
Return normalized copy of this object
- outer((VectorXc)arg1, (VectorXc)other) MatrixXc : ¶
Outer product with other.
- prod((VectorXc)arg1) object : ¶
Product of all elements.
- pruned((VectorXc)arg1[, (float)absTol=1e-06]) VectorXc : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((VectorXc)arg1, (int)arg2) None ¶
- rows((VectorXc)arg1) int : ¶
Number of rows.
- squaredNorm((VectorXc)arg1) object : ¶
Square of the Euclidean norm.
- sum((VectorXc)arg1) object : ¶
Sum of all elements.
- vectorize = False¶
- class yade._minieigenHP.Matrix3¶
3x3 float matrix.
Supported operations (
m
is a Matrix3,f
if a float/int,v
is a Vector3):-m
,m+m
,m+=m
,m-m
,m-=m
,m*f
,f*m
,m*=f
,m/f
,m/=f
,m*m
,m*=m
,m*v
,v*m
,m==m
,m!=m
.Static attributes:
Zero
,Ones
,Identity
.- Identity = Matrix3(1,0,0, 0,1,0, 0,0,1)¶
- Ones = Matrix3(1,1,1, 1,1,1, 1,1,1)¶
- static Random() Matrix3 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix3(0,0,0, 0,0,0, 0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Quaternion)q) -> None
__init__( (object)arg1, (Matrix3)other) -> None
__init__( (object)arg1, (Vector3)diag) -> object
__init__( (object)arg1, (float)m00, (float)m01, (float)m02, (float)m10, (float)m11, (float)m12, (float)m20, (float)m21, (float)m22) -> object
__init__( (object)arg1, (Vector3)r0, (Vector3)r1, (Vector3)r2 [, (bool)cols=False]) -> object
- col((Matrix3)arg1, (int)col) Vector3 : ¶
Return column as vector.
- cols((Matrix3)arg1) int : ¶
Number of columns.
- computeUnitaryPositive((Matrix3)arg1) tuple : ¶
Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).
- determinant((Matrix3)arg1) float : ¶
Return matrix determinant.
- diagonal((Matrix3)arg1) Vector3 : ¶
Return diagonal as vector.
- inverse((Matrix3)arg1) Matrix3 : ¶
Return inverted matrix.
- isApprox((Matrix3)arg1, (Matrix3)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- jacobiSVD((Matrix3)arg1) tuple : ¶
Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()
- maxAbsCoeff((Matrix3)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Matrix3)arg1) float : ¶
Maximum value over all elements.
- mean((Matrix3)arg1) float : ¶
Mean value over all elements.
- minCoeff((Matrix3)arg1) float : ¶
Minimum value over all elements.
- norm((Matrix3)arg1) float : ¶
Euclidean norm.
- normalize((Matrix3)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix3)arg1) Matrix3 : ¶
Return normalized copy of this object
- polarDecomposition((Matrix3)arg1) tuple : ¶
Alias for
computeUnitaryPositive
.
- prod((Matrix3)arg1) float : ¶
Product of all elements.
- pruned((Matrix3)arg1[, (float)absTol=1e-06]) Matrix3 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix3)arg1, (int)row) Vector3 : ¶
Return row as vector.
- rows((Matrix3)arg1) int : ¶
Number of rows.
- selfAdjointEigenDecomposition((Matrix3)arg1) tuple : ¶
Compute eigen (spectral) decomposition of symmetric matrix, returns (eigVecs,eigVals). eigVecs is orthogonal Matrix3 with columns ar normalized eigenvectors, eigVals is Vector3 with corresponding eigenvalues. self=eigVecs*diag(eigVals)*eigVecs.transpose().
- spectralDecomposition((Matrix3)arg1) tuple : ¶
Alias for
selfAdjointEigenDecomposition
.
- squaredNorm((Matrix3)arg1) float : ¶
Square of the Euclidean norm.
- sum((Matrix3)arg1) float : ¶
Sum of all elements.
- trace((Matrix3)arg1) float : ¶
Return sum of diagonal elements.
- transpose((Matrix3)arg1) Matrix3 : ¶
Return transposed matrix.
- class yade._minieigenHP.Matrix3c¶
/TODO/
- Identity = Matrix3c(1,0,0, 0,1,0, 0,0,1)¶
- Ones = Matrix3c(1,1,1, 1,1,1, 1,1,1)¶
- static Random() Matrix3c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix3c(0,0,0, 0,0,0, 0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Matrix3c)other) -> None
__init__( (object)arg1, (Vector3c)diag) -> object
__init__( (object)arg1, (complex)m00, (complex)m01, (complex)m02, (complex)m10, (complex)m11, (complex)m12, (complex)m20, (complex)m21, (complex)m22) -> object
__init__( (object)arg1, (Vector3c)r0, (Vector3c)r1, (Vector3c)r2 [, (bool)cols=False]) -> object
- col((Matrix3c)arg1, (int)col) Vector3c : ¶
Return column as vector.
- cols((Matrix3c)arg1) int : ¶
Number of columns.
- determinant((Matrix3c)arg1) complex : ¶
Return matrix determinant.
- diagonal((Matrix3c)arg1) Vector3c : ¶
Return diagonal as vector.
- inverse((Matrix3c)arg1) Matrix3c : ¶
Return inverted matrix.
- isApprox((Matrix3c)arg1, (Matrix3c)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Matrix3c)arg1) float : ¶
Maximum absolute value over all elements.
- mean((Matrix3c)arg1) complex : ¶
Mean value over all elements.
- norm((Matrix3c)arg1) float : ¶
Euclidean norm.
- normalize((Matrix3c)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix3c)arg1) Matrix3c : ¶
Return normalized copy of this object
- prod((Matrix3c)arg1) complex : ¶
Product of all elements.
- pruned((Matrix3c)arg1[, (float)absTol=1e-06]) Matrix3c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix3c)arg1, (int)row) Vector3c : ¶
Return row as vector.
- rows((Matrix3c)arg1) int : ¶
Number of rows.
- squaredNorm((Matrix3c)arg1) float : ¶
Square of the Euclidean norm.
- sum((Matrix3c)arg1) complex : ¶
Sum of all elements.
- trace((Matrix3c)arg1) complex : ¶
Return sum of diagonal elements.
- transpose((Matrix3c)arg1) Matrix3c : ¶
Return transposed matrix.
- class yade._minieigenHP.Matrix6¶
6x6 float matrix. Constructed from 4 3x3 sub-matrices, from 6xVector6 (rows).
Supported operations (
m
is a Matrix6,f
if a float/int,v
is a Vector6):-m
,m+m
,m+=m
,m-m
,m-=m
,m*f
,f*m
,m*=f
,m/f
,m/=f
,m*m
,m*=m
,m*v
,v*m
,m==m
,m!=m
.Static attributes:
Zero
,Ones
,Identity
.- Identity = Matrix6( (1,0,0,0,0,0), (0,1,0,0,0,0), (0,0,1,0,0,0), (0,0,0,1,0,0), (0,0,0,0,1,0), (0,0,0,0,0,1) )¶
- Ones = Matrix6( (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1) )¶
- static Random() Matrix6 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix6( (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0) )¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Matrix6)other) -> None
__init__( (object)arg1, (Vector6)diag) -> object
__init__( (object)arg1, (Matrix3)ul, (Matrix3)ur, (Matrix3)ll, (Matrix3)lr) -> object
__init__( (object)arg1, (Vector6)l0, (Vector6)l1, (Vector6)l2, (Vector6)l3, (Vector6)l4, (Vector6)l5 [, (bool)cols=False]) -> object
- col((Matrix6)arg1, (int)col) Vector6 : ¶
Return column as vector.
- cols((Matrix6)arg1) int : ¶
Number of columns.
- computeUnitaryPositive((Matrix6)arg1) tuple : ¶
Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).
- determinant((Matrix6)arg1) float : ¶
Return matrix determinant.
- diagonal((Matrix6)arg1) Vector6 : ¶
Return diagonal as vector.
- inverse((Matrix6)arg1) Matrix6 : ¶
Return inverted matrix.
- isApprox((Matrix6)arg1, (Matrix6)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- jacobiSVD((Matrix6)arg1) tuple : ¶
Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()
- ll((Matrix6)arg1) Matrix3 : ¶
Return lower-left 3x3 block
- lr((Matrix6)arg1) Matrix3 : ¶
Return lower-right 3x3 block
- maxAbsCoeff((Matrix6)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Matrix6)arg1) float : ¶
Maximum value over all elements.
- mean((Matrix6)arg1) float : ¶
Mean value over all elements.
- minCoeff((Matrix6)arg1) float : ¶
Minimum value over all elements.
- norm((Matrix6)arg1) float : ¶
Euclidean norm.
- normalize((Matrix6)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix6)arg1) Matrix6 : ¶
Return normalized copy of this object
- polarDecomposition((Matrix6)arg1) tuple : ¶
Alias for
computeUnitaryPositive
.
- prod((Matrix6)arg1) float : ¶
Product of all elements.
- pruned((Matrix6)arg1[, (float)absTol=1e-06]) Matrix6 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix6)arg1, (int)row) Vector6 : ¶
Return row as vector.
- rows((Matrix6)arg1) int : ¶
Number of rows.
- selfAdjointEigenDecomposition((Matrix6)arg1) tuple : ¶
Compute eigen (spectral) decomposition of symmetric matrix, returns (eigVecs,eigVals). eigVecs is orthogonal Matrix3 with columns ar normalized eigenvectors, eigVals is Vector3 with corresponding eigenvalues. self=eigVecs*diag(eigVals)*eigVecs.transpose().
- spectralDecomposition((Matrix6)arg1) tuple : ¶
Alias for
selfAdjointEigenDecomposition
.
- squaredNorm((Matrix6)arg1) float : ¶
Square of the Euclidean norm.
- sum((Matrix6)arg1) float : ¶
Sum of all elements.
- trace((Matrix6)arg1) float : ¶
Return sum of diagonal elements.
- transpose((Matrix6)arg1) Matrix6 : ¶
Return transposed matrix.
- ul((Matrix6)arg1) Matrix3 : ¶
Return upper-left 3x3 block
- ur((Matrix6)arg1) Matrix3 : ¶
Return upper-right 3x3 block
- class yade._minieigenHP.Matrix6c¶
/TODO/
- Identity = Matrix6c( (1,0,0,0,0,0), (0,1,0,0,0,0), (0,0,1,0,0,0), (0,0,0,1,0,0), (0,0,0,0,1,0), (0,0,0,0,0,1) )¶
- Ones = Matrix6c( (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1), (1,1,1,1,1,1) )¶
- static Random() Matrix6c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- Zero = Matrix6c( (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0), (0,0,0,0,0,0) )¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Matrix6c)other) -> None
__init__( (object)arg1, (Vector6c)diag) -> object
__init__( (object)arg1, (Matrix3c)ul, (Matrix3c)ur, (Matrix3c)ll, (Matrix3c)lr) -> object
__init__( (object)arg1, (Vector6c)l0, (Vector6c)l1, (Vector6c)l2, (Vector6c)l3, (Vector6c)l4, (Vector6c)l5 [, (bool)cols=False]) -> object
- col((Matrix6c)arg1, (int)col) Vector6c : ¶
Return column as vector.
- cols((Matrix6c)arg1) int : ¶
Number of columns.
- determinant((Matrix6c)arg1) complex : ¶
Return matrix determinant.
- diagonal((Matrix6c)arg1) Vector6c : ¶
Return diagonal as vector.
- inverse((Matrix6c)arg1) Matrix6c : ¶
Return inverted matrix.
- isApprox((Matrix6c)arg1, (Matrix6c)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- ll((Matrix6c)arg1) Matrix3c : ¶
Return lower-left 3x3 block
- lr((Matrix6c)arg1) Matrix3c : ¶
Return lower-right 3x3 block
- maxAbsCoeff((Matrix6c)arg1) float : ¶
Maximum absolute value over all elements.
- mean((Matrix6c)arg1) complex : ¶
Mean value over all elements.
- norm((Matrix6c)arg1) float : ¶
Euclidean norm.
- normalize((Matrix6c)arg1) None : ¶
Normalize this object in-place.
- normalized((Matrix6c)arg1) Matrix6c : ¶
Return normalized copy of this object
- prod((Matrix6c)arg1) complex : ¶
Product of all elements.
- pruned((Matrix6c)arg1[, (float)absTol=1e-06]) Matrix6c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- row((Matrix6c)arg1, (int)row) Vector6c : ¶
Return row as vector.
- rows((Matrix6c)arg1) int : ¶
Number of rows.
- squaredNorm((Matrix6c)arg1) float : ¶
Square of the Euclidean norm.
- sum((Matrix6c)arg1) complex : ¶
Sum of all elements.
- trace((Matrix6c)arg1) complex : ¶
Return sum of diagonal elements.
- transpose((Matrix6c)arg1) Matrix6c : ¶
Return transposed matrix.
- ul((Matrix6c)arg1) Matrix3c : ¶
Return upper-left 3x3 block
- ur((Matrix6c)arg1) Matrix3c : ¶
Return upper-right 3x3 block
- class yade._minieigenHP.MatrixX¶
XxX (dynamic-sized) float matrix. Constructed from list of rows (as VectorX).
Supported operations (
m
is a MatrixX,f
if a float/int,v
is a VectorX):-m
,m+m
,m+=m
,m-m
,m-=m
,m*f
,f*m
,m*=f
,m/f
,m/=f
,m*m
,m*=m
,m*v
,v*m
,m==m
,m!=m
.- static Identity((int)arg1, (int)rank) MatrixX : ¶
Create identity matrix with given rank (square).
- static Ones((int)rows, (int)cols) MatrixX : ¶
Create matrix of given dimensions where all elements are set to 1.
- static Random((int)rows, (int)cols) MatrixX : ¶
Create matrix with given dimensions where all elements are set to number between 0 and 1 (uniformly-distributed).
- static Zero((int)rows, (int)cols) MatrixX : ¶
Create zero matrix of given dimensions
- __init__((object)arg1) None ¶
__init__( (object)arg1, (MatrixX)other) -> None
__init__( (object)arg1, (VectorX)diag) -> object
__init__( (object)arg1 [, (VectorX)r0=VectorX() [, (VectorX)r1=VectorX() [, (VectorX)r2=VectorX() [, (VectorX)r3=VectorX() [, (VectorX)r4=VectorX() [, (VectorX)r5=VectorX() [, (VectorX)r6=VectorX() [, (VectorX)r7=VectorX() [, (VectorX)r8=VectorX() [, (VectorX)r9=VectorX() [, (bool)cols=False]]]]]]]]]]]) -> object
__init__( (object)arg1, (object)rows [, (bool)cols=False]) -> object
- col((MatrixX)arg1, (int)col) VectorX : ¶
Return column as vector.
- cols((MatrixX)arg1) int : ¶
Number of columns.
- computeUnitaryPositive((MatrixX)arg1) tuple : ¶
Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).
- determinant((MatrixX)arg1) float : ¶
Return matrix determinant.
- diagonal((MatrixX)arg1) VectorX : ¶
Return diagonal as vector.
- inverse((MatrixX)arg1) MatrixX : ¶
Return inverted matrix.
- isApprox((MatrixX)arg1, (MatrixX)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- jacobiSVD((MatrixX)arg1) tuple : ¶
Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()
- maxAbsCoeff((MatrixX)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((MatrixX)arg1) float : ¶
Maximum value over all elements.
- mean((MatrixX)arg1) float : ¶
Mean value over all elements.
- minCoeff((MatrixX)arg1) float : ¶
Minimum value over all elements.
- norm((MatrixX)arg1) float : ¶
Euclidean norm.
- normalize((MatrixX)arg1) None : ¶
Normalize this object in-place.
- normalized((MatrixX)arg1) MatrixX : ¶
Return normalized copy of this object
- polarDecomposition((MatrixX)arg1) tuple : ¶
Alias for
computeUnitaryPositive
.
- prod((MatrixX)arg1) float : ¶
Product of all elements.
- pruned((MatrixX)arg1[, (float)absTol=1e-06]) MatrixX : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((MatrixX)arg1, (int)rows, (int)cols) None : ¶
Change size of the matrix, keep values of elements which exist in the new matrix
- row((MatrixX)arg1, (int)row) VectorX : ¶
Return row as vector.
- rows((MatrixX)arg1) int : ¶
Number of rows.
- selfAdjointEigenDecomposition((MatrixX)arg1) tuple : ¶
Compute eigen (spectral) decomposition of symmetric matrix, returns (eigVecs,eigVals). eigVecs is orthogonal Matrix3 with columns ar normalized eigenvectors, eigVals is Vector3 with corresponding eigenvalues. self=eigVecs*diag(eigVals)*eigVecs.transpose().
- spectralDecomposition((MatrixX)arg1) tuple : ¶
Alias for
selfAdjointEigenDecomposition
.
- squaredNorm((MatrixX)arg1) float : ¶
Square of the Euclidean norm.
- sum((MatrixX)arg1) float : ¶
Sum of all elements.
- trace((MatrixX)arg1) float : ¶
Return sum of diagonal elements.
- transpose((MatrixX)arg1) MatrixX : ¶
Return transposed matrix.
- class yade._minieigenHP.MatrixXc¶
/TODO/
- static Identity((int)arg1, (int)rank) MatrixXc : ¶
Create identity matrix with given rank (square).
- static Ones((int)rows, (int)cols) MatrixXc : ¶
Create matrix of given dimensions where all elements are set to 1.
- static Random((int)rows, (int)cols) MatrixXc : ¶
Create matrix with given dimensions where all elements are set to number between 0 and 1 (uniformly-distributed).
- static Zero((int)rows, (int)cols) MatrixXc : ¶
Create zero matrix of given dimensions
- __init__((object)arg1) None ¶
__init__( (object)arg1, (MatrixXc)other) -> None
__init__( (object)arg1, (VectorXc)diag) -> object
__init__( (object)arg1 [, (VectorXc)r0=VectorXc() [, (VectorXc)r1=VectorXc() [, (VectorXc)r2=VectorXc() [, (VectorXc)r3=VectorXc() [, (VectorXc)r4=VectorXc() [, (VectorXc)r5=VectorXc() [, (VectorXc)r6=VectorXc() [, (VectorXc)r7=VectorXc() [, (VectorXc)r8=VectorXc() [, (VectorXc)r9=VectorXc() [, (bool)cols=False]]]]]]]]]]]) -> object
__init__( (object)arg1, (object)rows [, (bool)cols=False]) -> object
- col((MatrixXc)arg1, (int)col) VectorXc : ¶
Return column as vector.
- cols((MatrixXc)arg1) int : ¶
Number of columns.
- determinant((MatrixXc)arg1) complex : ¶
Return matrix determinant.
- diagonal((MatrixXc)arg1) VectorXc : ¶
Return diagonal as vector.
- inverse((MatrixXc)arg1) MatrixXc : ¶
Return inverted matrix.
- isApprox((MatrixXc)arg1, (MatrixXc)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((MatrixXc)arg1) float : ¶
Maximum absolute value over all elements.
- mean((MatrixXc)arg1) complex : ¶
Mean value over all elements.
- norm((MatrixXc)arg1) float : ¶
Euclidean norm.
- normalize((MatrixXc)arg1) None : ¶
Normalize this object in-place.
- normalized((MatrixXc)arg1) MatrixXc : ¶
Return normalized copy of this object
- prod((MatrixXc)arg1) complex : ¶
Product of all elements.
- pruned((MatrixXc)arg1[, (float)absTol=1e-06]) MatrixXc : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- resize((MatrixXc)arg1, (int)rows, (int)cols) None : ¶
Change size of the matrix, keep values of elements which exist in the new matrix
- row((MatrixXc)arg1, (int)row) VectorXc : ¶
Return row as vector.
- rows((MatrixXc)arg1) int : ¶
Number of rows.
- squaredNorm((MatrixXc)arg1) float : ¶
Square of the Euclidean norm.
- sum((MatrixXc)arg1) complex : ¶
Sum of all elements.
- trace((MatrixXc)arg1) complex : ¶
Return sum of diagonal elements.
- transpose((MatrixXc)arg1) MatrixXc : ¶
Return transposed matrix.
- class yade._minieigenHP.Quaternion¶
Quaternion representing rotation.
Supported operations (
q
is a Quaternion,v
is a Vector3):q*q
(rotation composition),q*=q
,q*v
(rotatingv
byq
),q==q
,q!=q
.Static attributes:
Identity
.Note
Quaternion is represented as axis-angle when printed (e.g.
Identity
isQuaternion((1,0,0),0)
, and can also be constructed from the axis-angle representation. This is however different from the data stored inside, which can be accessed by indices[0]
(\(x\)),[1]
(\(y\)),[2]
(\(z\)),[3]
(\(w\)). To obtain axis-angle programatically, useQuaternion.toAxisAngle
which returns the tuple.- Identity = Quaternion((1,0,0),0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3)axis, (float)angle) -> object
__init__( (object)arg1, (float)angle, (Vector3)axis) -> object
__init__( (object)arg1, (Vector3)u, (Vector3)v) -> object
- __init__( (object)arg1, (float)w, (float)x, (float)y, (float)z) -> None :
Initialize from coefficients.
Note
The order of coefficients is w, x, y, z. The [] operator numbers them differently, 0…4 for x y z w!
__init__( (object)arg1, (Matrix3)rotMatrix) -> None
__init__( (object)arg1, (Quaternion)other) -> None
- angularDistance((Quaternion)arg1, (Quaternion)arg2) float ¶
- conjugate((Quaternion)arg1) Quaternion ¶
- inverse((Quaternion)arg1) Quaternion ¶
- norm((Quaternion)arg1) float ¶
- normalize((Quaternion)arg1) None ¶
- normalized((Quaternion)arg1) Quaternion ¶
- setFromTwoVectors((Quaternion)arg1, (Vector3)u, (Vector3)v) None ¶
- slerp((Quaternion)arg1, (float)t, (Quaternion)other) Quaternion ¶
- toAngleAxis((Quaternion)arg1) tuple ¶
- toAxisAngle((Quaternion)arg1) tuple ¶
- class yade._minieigenHP.Vector2¶
3-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector3):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 2 floats.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
.- Identity = Vector2(1,0)¶
- Ones = Vector2(1,1)¶
- static Random() Vector2 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector2(1,0)¶
- UnitY = Vector2(0,1)¶
- Zero = Vector2(0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector2)other) -> None
__init__( (object)arg1, (float)x, (float)y) -> None
- asDiagonal((Vector2)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector2)arg1) int : ¶
Number of columns.
- dot((Vector2)arg1, (Vector2)other) float : ¶
Dot product with other.
- isApprox((Vector2)arg1, (Vector2)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector2)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector2)arg1) float : ¶
Maximum value over all elements.
- mean((Vector2)arg1) float : ¶
Mean value over all elements.
- minCoeff((Vector2)arg1) float : ¶
Minimum value over all elements.
- norm((Vector2)arg1) float : ¶
Euclidean norm.
- normalize((Vector2)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector2)arg1) Vector2 : ¶
Return normalized copy of this object
- outer((Vector2)arg1, (Vector2)other) object : ¶
Outer product with other.
- prod((Vector2)arg1) float : ¶
Product of all elements.
- pruned((Vector2)arg1[, (float)absTol=1e-06]) Vector2 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector2)arg1) int : ¶
Number of rows.
- squaredNorm((Vector2)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector2)arg1) float : ¶
Sum of all elements.
- class yade._minieigenHP.Vector2c¶
/TODO/
- Identity = Vector2c(1,0)¶
- Ones = Vector2c(1,1)¶
- static Random() Vector2c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector2c(1,0)¶
- UnitY = Vector2c(0,1)¶
- Zero = Vector2c(0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector2c)other) -> None
__init__( (object)arg1, (complex)x, (complex)y) -> None
- asDiagonal((Vector2c)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector2c)arg1) int : ¶
Number of columns.
- dot((Vector2c)arg1, (Vector2c)other) complex : ¶
Dot product with other.
- isApprox((Vector2c)arg1, (Vector2c)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector2c)arg1) float : ¶
Maximum absolute value over all elements.
- mean((Vector2c)arg1) complex : ¶
Mean value over all elements.
- norm((Vector2c)arg1) float : ¶
Euclidean norm.
- normalize((Vector2c)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector2c)arg1) Vector2c : ¶
Return normalized copy of this object
- outer((Vector2c)arg1, (Vector2c)other) object : ¶
Outer product with other.
- prod((Vector2c)arg1) complex : ¶
Product of all elements.
- pruned((Vector2c)arg1[, (float)absTol=1e-06]) Vector2c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector2c)arg1) int : ¶
Number of rows.
- squaredNorm((Vector2c)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector2c)arg1) complex : ¶
Sum of all elements.
- class yade._minieigenHP.Vector2i¶
2-dimensional integer vector.
Supported operations (
i
if an int,v
is a Vector2i):-v
,v+v
,v+=v
,v-v
,v-=v
,v*i
,i*v
,v*=i
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 2 integers.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
.- Identity = Vector2i(1,0)¶
- Ones = Vector2i(1,1)¶
- static Random() Vector2i : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector2i(1,0)¶
- UnitY = Vector2i(0,1)¶
- Zero = Vector2i(0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector2i)other) -> None
__init__( (object)arg1, (int)x, (int)y) -> None
- asDiagonal((Vector2i)arg1) object : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector2i)arg1) int : ¶
Number of columns.
- dot((Vector2i)arg1, (Vector2i)other) int : ¶
Dot product with other.
- isApprox((Vector2i)arg1, (Vector2i)other[, (int)prec=0]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector2i)arg1) int : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector2i)arg1) int : ¶
Maximum value over all elements.
- mean((Vector2i)arg1) int : ¶
Mean value over all elements.
- minCoeff((Vector2i)arg1) int : ¶
Minimum value over all elements.
- outer((Vector2i)arg1, (Vector2i)other) object : ¶
Outer product with other.
- prod((Vector2i)arg1) int : ¶
Product of all elements.
- rows((Vector2i)arg1) int : ¶
Number of rows.
- sum((Vector2i)arg1) int : ¶
Sum of all elements.
- class yade._minieigenHP.Vector3¶
3-dimensional float vector.
Supported operations (
f
if a float/int,v
is a Vector3):-v
,v+v
,v+=v
,v-v
,v-=v
,v*f
,f*v
,v*=f
,v/f
,v/=f
,v==v
,v!=v
, plus operations withMatrix3
andQuaternion
.Implicit conversion from sequence (list, tuple, …) of 3 floats.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
,UnitZ
.- Identity = Vector3(1,0,0)¶
- Ones = Vector3(1,1,1)¶
- static Random() Vector3 : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector3(1,0,0)¶
- UnitY = Vector3(0,1,0)¶
- UnitZ = Vector3(0,0,1)¶
- Zero = Vector3(0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3)other) -> None
__init__( (object)arg1 [, (float)x=0.0 [, (float)y=0.0 [, (float)z=0.0]]]) -> None
- asDiagonal((Vector3)arg1) Matrix3 : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector3)arg1) int : ¶
Number of columns.
- dot((Vector3)arg1, (Vector3)other) float : ¶
Dot product with other.
- isApprox((Vector3)arg1, (Vector3)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector3)arg1) float : ¶
Maximum absolute value over all elements.
- maxCoeff((Vector3)arg1) float : ¶
Maximum value over all elements.
- mean((Vector3)arg1) float : ¶
Mean value over all elements.
- minCoeff((Vector3)arg1) float : ¶
Minimum value over all elements.
- norm((Vector3)arg1) float : ¶
Euclidean norm.
- normalize((Vector3)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector3)arg1) Vector3 : ¶
Return normalized copy of this object
- outer((Vector3)arg1, (Vector3)other) Matrix3 : ¶
Outer product with other.
- prod((Vector3)arg1) float : ¶
Product of all elements.
- pruned((Vector3)arg1[, (float)absTol=1e-06]) Vector3 : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector3)arg1) int : ¶
Number of rows.
- squaredNorm((Vector3)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector3)arg1) float : ¶
Sum of all elements.
- class yade._minieigenHP.Vector3c¶
/TODO/
- Identity = Vector3c(1,0,0)¶
- Ones = Vector3c(1,1,1)¶
- static Random() Vector3c : ¶
Return an object where all elements are randomly set to values between 0 and 1.
- UnitX = Vector3c(1,0,0)¶
- UnitY = Vector3c(0,1,0)¶
- UnitZ = Vector3c(0,0,1)¶
- Zero = Vector3c(0,0,0)¶
- __init__((object)arg1) None ¶
__init__( (object)arg1, (Vector3c)other) -> None
__init__( (object)arg1 [, (complex)x=0j [, (complex)y=0j [, (complex)z=0j]]]) -> None
- asDiagonal((Vector3c)arg1) Matrix3c : ¶
Return diagonal matrix with this vector on the diagonal.
- cols((Vector3c)arg1) int : ¶
Number of columns.
- dot((Vector3c)arg1, (Vector3c)other) complex : ¶
Dot product with other.
- isApprox((Vector3c)arg1, (Vector3c)other[, (float)prec=1e-12]) bool : ¶
Approximate comparison with precision prec.
- maxAbsCoeff((Vector3c)arg1) float : ¶
Maximum absolute value over all elements.
- mean((Vector3c)arg1) complex : ¶
Mean value over all elements.
- norm((Vector3c)arg1) float : ¶
Euclidean norm.
- normalize((Vector3c)arg1) None : ¶
Normalize this object in-place.
- normalized((Vector3c)arg1) Vector3c : ¶
Return normalized copy of this object
- outer((Vector3c)arg1, (Vector3c)other) Matrix3c : ¶
Outer product with other.
- prod((Vector3c)arg1) complex : ¶
Product of all elements.
- pruned((Vector3c)arg1[, (float)absTol=1e-06]) Vector3c : ¶
Zero all elements which are greater than absTol. Negative zeros are not pruned.
- rows((Vector3c)arg1) int : ¶
Number of rows.
- squaredNorm((Vector3c)arg1) float : ¶
Square of the Euclidean norm.
- sum((Vector3c)arg1) complex : ¶
Sum of all elements.
- class yade._minieigenHP.Vector3i¶
3-dimensional integer vector.
Supported operations (
i
if an int,v
is a Vector3i):-v
,v+v
,v+=v
,v-v
,v-=v
,v*i
,i*v
,v*=i
,v==v
,v!=v
.Implicit conversion from sequence (list, tuple, …) of 3 integers.
Static attributes:
Zero
,Ones
,UnitX
,UnitY
,UnitZ
.- Identity = Vector3i(1,0,0)¶
- Ones = Vector3i(1,1,1)¶