minieigen documentation

Overview

Todo

Something concise here.

Examples

Todo

Some examples of what can be done with minieigen.

Naming conventions

• Classes are suffixed with number indicating size where it makes sense (it does not make sense for minieigen.Quaternion):
  • minieigen.Vector3 is a 3-vector (column vector);
  • minieigen.Matrix3 is a 3×3 matrix;
  • minieigen.AlignedBox3 is aligned box in 3d;
  • X indicates dynamic-sized types, such as minieigen.VectorX or minieigen.MatrixX.
• Scalar (element) type is suffixed at the end:
  • nothing is suffixed for floats (minieigen.Matrix3);
  • i indicates integers (minieigen.Matrix3i);
  • c indicates complex numbers (minieigen.Matrix3c).
• Methods are named as follows:
  • static methods are upper-case (as in c++), e.g. minieigen.Matrix3.Random;
    • nullary static methods are exposed as properties, if they return a constant (e.g. minieigen.Matrix3.Identity); if they don’t, they are exposed as methods (minieigen.Matrix3.Random); the idea is that the necessity to call the method (Matrix3.Random()) singifies that there is some computation going on, whereas constants behave like immutable singletons.
  • non-static methods are lower-case (as in c++), e.g. minieigen.Matrix3.inverse.
• Return types:
  • methods modifying the instance in-place return None (e.g. minieigen.Vector3.normalize); some methods in c++ (e.g. Quaternion::setFromTwoVectors) both modify the instance and return the reference to it, which we don’t want to do in Python (minieigen.Quaternion.setFromTwoVectors);
  • methods returning another object (e.g. minieigen.Vector3.normalized) do not modify the instance;
  • methods returning (non-const) references return by value in python

Limitations

• Type conversions (e.g. float to complex) are not supported.
• Methods returning references in c++ return values in Python (so e.g. Matrix3().diagonal()[2]=0 would zero the last diagonal element in c++ but not in Python).
• Many methods are not wrapped, though they are fairly easy to add.
• Conversion from 1-column MatrixX to VectorX is not automatic in places where the algebra requires it.
• Alignment of matrices is not supported (therefore Eigen cannot vectorize the code well); it might be a performance issue in some cases; c++ code interfacing with minieigen (in a way that c++ values can be set from Python) must compile with EIGEN_DONT_ALIGN, otherwise there might be crashes at runtime when vector instructions receive unaligned data. It seems that alignment is difficult to do with boost::python.
• Proper automatic tests are missing.

Links

• http://eigen.tuxfamily.org (Eigen itself)
• http://www.launchpad.net/minieigen (upstream repository, bug reports, answers)
• https://pypi.python.org/pypi/minieigen (Python package index page, used by easy_install)
• packages:
  • Debian
  • Ubuntu: distribution, PPA

Documentation

• Index
• Search Page

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 minieigen.AlignedBox2((object)arg1)

Axis-aligned box object in 2d, defined by its minimum and maximum corners

center() → Vector2

clamp((AlignedBox2)arg2) → None

contains((Vector2)arg2) → bool

contains( (AlignedBox2)arg1, (AlignedBox2)arg2) → bool

empty() → bool

extend((Vector2)arg2) → None

extend( (AlignedBox2)arg1, (AlignedBox2)arg2) → None

intersection((AlignedBox2)arg2) → AlignedBox2

max

merged((AlignedBox2)arg2) → AlignedBox2

min

sizes() → Vector2

volume() → float

class minieigen.AlignedBox3((object)arg1)

Axis-aligned box object, defined by its minimum and maximum corners

center() → Vector3

clamp((AlignedBox3)arg2) → None

contains((Vector3)arg2) → bool

contains( (AlignedBox3)arg1, (AlignedBox3)arg2) → bool

empty() → bool

extend((Vector3)arg2) → None

extend( (AlignedBox3)arg1, (AlignedBox3)arg2) → None

intersection((AlignedBox3)arg2) → AlignedBox3

max

merged((AlignedBox3)arg2) → AlignedBox3

min

sizes() → Vector3

volume() → float

class minieigen.Matrix3((object)arg1)

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)

Random() → Matrix3 [STATIC]

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)

col((int)col) → Vector3

Return column as vector.

cols() → int

Number of columns.

computeUnitaryPositive() → tuple

Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).

determinant() → float

Return matrix determinant.

diagonal() → Vector3

Return diagonal as vector.

inverse() → Matrix3

Return inverted matrix.

jacobiSVD() → tuple

Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()

maxAbsCoeff() → float

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Matrix3

Return normalized copy of this object

polarDecomposition() → tuple

Alias for computeUnitaryPositive.

pruned([(float)absTol=1e-06]) → Matrix3

Zero all elements which are greater than absTol. Negative zeros are not pruned.

row((int)row) → Vector3

Return row as vector.

rows() → int

Number of rows.

selfAdjointEigenDecomposition() → 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() → tuple

Alias for selfAdjointEigenDecomposition.

squaredNorm() → float

Square of the Euclidean norm.

sum() → float

Sum of all elements.

svd() → tuple

Alias for jacobiSVD.

trace() → float

Return sum of diagonal elements.

transpose() → Matrix3

Return transposed matrix.

class minieigen.Matrix3c((object)arg1)

/TODO/

Identity = Matrix3c(1,0,0, 0,1,0, 0,0,1)

Ones = Matrix3c(1,1,1, 1,1,1, 1,1,1)

Random() → Matrix3c [STATIC]

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)

col((int)col) → Vector3c

Return column as vector.

cols() → int

Number of columns.

determinant() → complex

Return matrix determinant.

diagonal() → Vector3c

Return diagonal as vector.

inverse() → Matrix3c

Return inverted matrix.

maxAbsCoeff() → complex

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Matrix3c

Return normalized copy of this object

pruned([(float)absTol=1e-06]) → Matrix3c

Zero all elements which are greater than absTol. Negative zeros are not pruned.

row((int)row) → Vector3c

Return row as vector.

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → complex

Sum of all elements.

trace() → complex

Return sum of diagonal elements.

transpose() → Matrix3c

Return transposed matrix.

class minieigen.Matrix6((object)arg1)

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) )

Random() → Matrix6 [STATIC]

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) )

col((int)col) → Vector6

Return column as vector.

cols() → int

Number of columns.

computeUnitaryPositive() → tuple

Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).

determinant() → float

Return matrix determinant.

diagonal() → Vector6

Return diagonal as vector.

inverse() → Matrix6

Return inverted matrix.

jacobiSVD() → tuple

Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()

ll() → Matrix3

Return lower-left 3x3 block

lr() → Matrix3

Return lower-right 3x3 block

maxAbsCoeff() → float

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Matrix6

Return normalized copy of this object

polarDecomposition() → tuple

Alias for computeUnitaryPositive.

pruned([(float)absTol=1e-06]) → Matrix6

Zero all elements which are greater than absTol. Negative zeros are not pruned.

row((int)row) → Vector6

Return row as vector.

rows() → int

Number of rows.

selfAdjointEigenDecomposition() → 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() → tuple

Alias for selfAdjointEigenDecomposition.

squaredNorm() → float

Square of the Euclidean norm.

sum() → float

Sum of all elements.

svd() → tuple

Alias for jacobiSVD.

trace() → float

Return sum of diagonal elements.

transpose() → Matrix6

Return transposed matrix.

ul() → Matrix3

Return upper-left 3x3 block

ur() → Matrix3

Return upper-right 3x3 block

class minieigen.Matrix6c((object)arg1)

/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) )

Random() → Matrix6c [STATIC]

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) )

col((int)col) → Vector6c

Return column as vector.

cols() → int

Number of columns.

determinant() → complex

Return matrix determinant.

diagonal() → Vector6c

Return diagonal as vector.

inverse() → Matrix6c

Return inverted matrix.

ll() → Matrix3c

Return lower-left 3x3 block

lr() → Matrix3c

Return lower-right 3x3 block

maxAbsCoeff() → complex

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Matrix6c

Return normalized copy of this object

pruned([(float)absTol=1e-06]) → Matrix6c

Zero all elements which are greater than absTol. Negative zeros are not pruned.

row((int)row) → Vector6c

Return row as vector.

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → complex

Sum of all elements.

trace() → complex

Return sum of diagonal elements.

transpose() → Matrix6c

Return transposed matrix.

ul() → Matrix3c

Return upper-left 3x3 block

ur() → Matrix3c

Return upper-right 3x3 block

class minieigen.MatrixX((object)arg1)

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.

Identity((int)arg1, (int)rank) → MatrixX [STATIC]

Create identity matrix with given rank (square).

Ones((int)rows, (int)cols) → MatrixX [STATIC]

Create matrix of given dimensions where all elements are set to 1.

Random((int)rows, (int)cols) → MatrixX [STATIC]

Create matrix with given dimensions where all elements are set to number between 0 and 1 (uniformly-distributed).

Zero((int)rows, (int)cols) → MatrixX [STATIC]

Create zero matrix of given dimensions

col((int)col) → VectorX

Return column as vector.

cols() → int

Number of columns.

computeUnitaryPositive() → tuple

Compute polar decomposition (unitary matrix U and positive semi-definite symmetric matrix P such that self=U*P).

determinant() → float

Return matrix determinant.

diagonal() → VectorX

Return diagonal as vector.

inverse() → MatrixX

Return inverted matrix.

jacobiSVD() → tuple

Compute SVD decomposition of square matrix, retuns (U,S,V) such that self=U*S*V.transpose()

maxAbsCoeff() → float

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → MatrixX

Return normalized copy of this object

polarDecomposition() → tuple

Alias for computeUnitaryPositive.

pruned([(float)absTol=1e-06]) → MatrixX

Zero all elements which are greater than absTol. Negative zeros are not pruned.

resize((int)rows, (int)cols) → None

Change size of the matrix, keep values of elements which exist in the new matrix

row((int)row) → VectorX

Return row as vector.

rows() → int

Number of rows.

selfAdjointEigenDecomposition() → 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() → tuple

Alias for selfAdjointEigenDecomposition.

squaredNorm() → float

Square of the Euclidean norm.

sum() → float

Sum of all elements.

svd() → tuple

Alias for jacobiSVD.

trace() → float

Return sum of diagonal elements.

transpose() → MatrixX

Return transposed matrix.

class minieigen.MatrixXc((object)arg1)

/TODO/

Identity((int)arg1, (int)rank) → MatrixXc [STATIC]

Create identity matrix with given rank (square).

Ones((int)rows, (int)cols) → MatrixXc [STATIC]

Create matrix of given dimensions where all elements are set to 1.

Random((int)rows, (int)cols) → MatrixXc [STATIC]

Create matrix with given dimensions where all elements are set to number between 0 and 1 (uniformly-distributed).

Zero((int)rows, (int)cols) → MatrixXc [STATIC]

Create zero matrix of given dimensions

col((int)col) → VectorXc

Return column as vector.

cols() → int

Number of columns.

determinant() → complex

Return matrix determinant.

diagonal() → VectorXc

Return diagonal as vector.

inverse() → MatrixXc

Return inverted matrix.

maxAbsCoeff() → complex

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → MatrixXc

Return normalized copy of this object

pruned([(float)absTol=1e-06]) → MatrixXc

Zero all elements which are greater than absTol. Negative zeros are not pruned.

resize((int)rows, (int)cols) → None

Change size of the matrix, keep values of elements which exist in the new matrix

row((int)row) → VectorXc

Return row as vector.

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → complex

Sum of all elements.

trace() → complex

Return sum of diagonal elements.

transpose() → MatrixXc

Return transposed matrix.

class minieigen.Quaternion((object)arg1)

Quaternion representing rotation.

Supported operations (q is a Quaternion, v is a Vector3): q*q (rotation composition), q*=q, q*v (rotating v by q), q==q, q!=q.

Static attributes: Identity.

Identity = Quaternion((1,0,0),0)

Rotate((Vector3)v) → Vector3

conjugate() → Quaternion

inverse() → Quaternion

norm() → float

normalize() → None

normalized() → Quaternion

setFromTwoVectors((Vector3)u, (Vector3)v) → None

toAngleAxis() → tuple

toAxisAngle() → tuple

toRotationMatrix() → Matrix3

toRotationVector() → Vector3

class minieigen.Vector2((object)arg1)

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)

Random() → Vector2 [STATIC]

Return an object where all elements are randomly set to values between 0 and 1.

Unit((int)arg1) → Vector2 [STATIC]

UnitX = Vector2(1,0)

UnitY = Vector2(0,1)

Zero = Vector2(0,0)

asDiagonal() → object

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((Vector2)other) → float

Dot product with other.

maxAbsCoeff() → float

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Vector2

Return normalized copy of this object

outer((Vector2)other) → object

Outer product with other.

pruned([(float)absTol=1e-06]) → Vector2

Zero all elements which are greater than absTol. Negative zeros are not pruned.

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → float

Sum of all elements.

class minieigen.Vector2c((object)arg1)

/TODO/

Identity = Vector2c(1,0)

Ones = Vector2c(1,1)

Random() → Vector2c [STATIC]

Return an object where all elements are randomly set to values between 0 and 1.

Unit((int)arg1) → Vector2c [STATIC]

UnitX = Vector2c(1,0)

UnitY = Vector2c(0,1)

Zero = Vector2c(0,0)

asDiagonal() → object

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((Vector2c)other) → complex

Dot product with other.

maxAbsCoeff() → complex

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Vector2c

Return normalized copy of this object

outer((Vector2c)other) → object

Outer product with other.

pruned([(float)absTol=1e-06]) → Vector2c

Zero all elements which are greater than absTol. Negative zeros are not pruned.

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → complex

Sum of all elements.

class minieigen.Vector2i((object)arg1)

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)

Random() → Vector2i [STATIC]

Return an object where all elements are randomly set to values between 0 and 1.

Unit((int)arg1) → Vector2i [STATIC]

UnitX = Vector2i(1,0)

UnitY = Vector2i(0,1)

Zero = Vector2i(0,0)

asDiagonal() → object

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((Vector2i)other) → int

Dot product with other.

maxAbsCoeff() → int

Maximum absolute value over all elements.

outer((Vector2i)other) → object

Outer product with other.

rows() → int

Number of rows.

sum() → int

Sum of all elements.

class minieigen.Vector3((object)arg1)

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 with Matrix3 and Quaternion.

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)

Random() → Vector3 [STATIC]

Return an object where all elements are randomly set to values between 0 and 1.

Unit((int)arg1) → Vector3 [STATIC]

UnitX = Vector3(1,0,0)

UnitY = Vector3(0,1,0)

UnitZ = Vector3(0,0,1)

Zero = Vector3(0,0,0)

asDiagonal() → Matrix3

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

cross((Vector3)arg2) → Vector3

dot((Vector3)other) → float

Dot product with other.

maxAbsCoeff() → float

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Vector3

Return normalized copy of this object

outer((Vector3)other) → Matrix3

Outer product with other.

pruned([(float)absTol=1e-06]) → Vector3

Zero all elements which are greater than absTol. Negative zeros are not pruned.

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → float

Sum of all elements.

xy() → Vector2

xz() → Vector2

yx() → Vector2

yz() → Vector2

zx() → Vector2

zy() → Vector2

class minieigen.Vector3c((object)arg1)

/TODO/

Identity = Vector3c(1,0,0)

Ones = Vector3c(1,1,1)

Random() → Vector3c [STATIC]

Return an object where all elements are randomly set to values between 0 and 1.

Unit((int)arg1) → Vector3c [STATIC]

UnitX = Vector3c(1,0,0)

UnitY = Vector3c(0,1,0)

UnitZ = Vector3c(0,0,1)

Zero = Vector3c(0,0,0)

asDiagonal() → Matrix3c

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

cross((Vector3c)arg2) → Vector3c

dot((Vector3c)other) → complex

Dot product with other.

maxAbsCoeff() → complex

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Vector3c

Return normalized copy of this object

outer((Vector3c)other) → Matrix3c

Outer product with other.

pruned([(float)absTol=1e-06]) → Vector3c

Zero all elements which are greater than absTol. Negative zeros are not pruned.

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → complex

Sum of all elements.

xy() → Vector2c

xz() → Vector2c

yx() → Vector2c

yz() → Vector2c

zx() → Vector2c

zy() → Vector2c

class minieigen.Vector3i((object)arg1)

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)

Random() → Vector3i [STATIC]

Return an object where all elements are randomly set to values between 0 and 1.

Unit((int)arg1) → Vector3i [STATIC]

UnitX = Vector3i(1,0,0)

UnitY = Vector3i(0,1,0)

UnitZ = Vector3i(0,0,1)

Zero = Vector3i(0,0,0)

asDiagonal() → object

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

cross((Vector3i)arg2) → Vector3i

dot((Vector3i)other) → int

Dot product with other.

maxAbsCoeff() → int

Maximum absolute value over all elements.

outer((Vector3i)other) → object

Outer product with other.

rows() → int

Number of rows.

sum() → int

Sum of all elements.

xy() → Vector2i

xz() → Vector2i

yx() → Vector2i

yz() → Vector2i

zx() → Vector2i

zy() → Vector2i

class minieigen.Vector6((object)arg1)

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)

Random() → Vector6 [STATIC]

Return an object where all elements are randomly set to values between 0 and 1.

Unit((int)arg1) → Vector6 [STATIC]

Zero = Vector6(0,0,0, 0,0,0)

asDiagonal() → Matrix6

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((Vector6)other) → float

Dot product with other.

head() → Vector3

maxAbsCoeff() → float

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Vector6

Return normalized copy of this object

outer((Vector6)other) → Matrix6

Outer product with other.

pruned([(float)absTol=1e-06]) → Vector6

Zero all elements which are greater than absTol. Negative zeros are not pruned.

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → float

Sum of all elements.

tail() → Vector3

class minieigen.Vector6c((object)arg1)

/TODO/

Identity = Vector6c(1,0,0, 0,0,0)

Ones = Vector6c(1,1,1, 1,1,1)

Random() → Vector6c [STATIC]

Return an object where all elements are randomly set to values between 0 and 1.

Unit((int)arg1) → Vector6c [STATIC]

Zero = Vector6c(0,0,0, 0,0,0)

asDiagonal() → Matrix6c

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((Vector6c)other) → complex

Dot product with other.

head() → Vector3c

maxAbsCoeff() → complex

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Vector6c

Return normalized copy of this object

outer((Vector6c)other) → Matrix6c

Outer product with other.

pruned([(float)absTol=1e-06]) → Vector6c

Zero all elements which are greater than absTol. Negative zeros are not pruned.

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → complex

Sum of all elements.

tail() → Vector3c

class minieigen.Vector6i((object)arg1)

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 = Vector6i(1,0,0, 0,0,0)

Ones = Vector6i(1,1,1, 1,1,1)

Random() → Vector6i [STATIC]

Return an object where all elements are randomly set to values between 0 and 1.

Unit((int)arg1) → Vector6i [STATIC]

Zero = Vector6i(0,0,0, 0,0,0)

asDiagonal() → object

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((Vector6i)other) → int

Dot product with other.

head() → Vector3i

maxAbsCoeff() → int

Maximum absolute value over all elements.

outer((Vector6i)other) → object

Outer product with other.

rows() → int

Number of rows.

sum() → int

Sum of all elements.

tail() → Vector3i

class minieigen.VectorX((object)arg1)

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.

Ones((int)arg1) → VectorX [STATIC]

Random((int)len) → VectorX [STATIC]

Return vector of given length with all elements set to values between 0 and 1 randomly.

Unit((int)arg1, (int)arg2) → VectorX [STATIC]

Zero((int)arg1) → VectorX [STATIC]

asDiagonal() → MatrixX

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((VectorX)other) → float

Dot product with other.

maxAbsCoeff() → float

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → VectorX

Return normalized copy of this object

outer((VectorX)other) → MatrixX

Outer product with other.

pruned([(float)absTol=1e-06]) → VectorX

Zero all elements which are greater than absTol. Negative zeros are not pruned.

resize((int)arg2) → None

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → float

Sum of all elements.

class minieigen.VectorXc((object)arg1)

/TODO/

Ones((int)arg1) → VectorXc [STATIC]

Random((int)len) → VectorXc [STATIC]

Return vector of given length with all elements set to values between 0 and 1 randomly.

Unit((int)arg1, (int)arg2) → VectorXc [STATIC]

Zero((int)arg1) → VectorXc [STATIC]

asDiagonal() → MatrixXc

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((VectorXc)other) → complex

Dot product with other.

maxAbsCoeff() → complex

Maximum absolute value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → VectorXc

Return normalized copy of this object

outer((VectorXc)other) → MatrixXc

Outer product with other.

pruned([(float)absTol=1e-06]) → VectorXc

Zero all elements which are greater than absTol. Negative zeros are not pruned.

resize((int)arg2) → None

rows() → int

Number of rows.

squaredNorm() → float

Square of the Euclidean norm.

sum() → complex

Sum of all elements.