minieigen documentation

Overview

Todo

Something concise here.

Examples

Todo

Some examples of what can be done with minieigen.

Naming conventions

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.

Documentation

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

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

__contains__((Vector2)arg2) → bool

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

__getitem__((tuple)arg2) → float

__getitem__( (AlignedBox2)arg1, (int)arg2) → Vector2

__init__() → None

__init__((AlignedBox2)other) → None

__init__((Vector2)min, (Vector2)max) → None

static __len__() → int [STATIC]
__repr__() → str
__setitem__((tuple)arg2, (float)arg3) → None

__setitem__( (AlignedBox2)arg1, (int)arg2, (Vector2)arg3) → None

__str__() → str
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

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

__contains__((Vector3)arg2) → bool

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

__getitem__((tuple)arg2) → float

__getitem__( (AlignedBox3)arg1, (int)arg2) → Vector3

__init__() → None

__init__((AlignedBox3)other) → None

__init__((Vector3)min, (Vector3)max) → None

static __len__() → int [STATIC]
__repr__() → str
__setitem__((tuple)arg2, (float)arg3) → None

__setitem__( (AlignedBox3)arg1, (int)arg2, (Vector3)arg3) → None

__str__() → str
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

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 [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)
__abs__() → float
__add__((Matrix3)arg2) → Matrix3
__div__((int)arg2) → Matrix3

__div__( (Matrix3)arg1, (float)arg2) → Matrix3

__eq__((Matrix3)arg2) → bool
__getitem__((int)arg2) → Vector3

__getitem__( (Matrix3)arg1, (tuple)arg2) → float

__iadd__((Matrix3)arg2) → Matrix3
__idiv__((int)arg2) → Matrix3

__idiv__( (Matrix3)arg1, (float)arg2) → Matrix3

__imul__((int)arg2) → Matrix3

__imul__( (Matrix3)arg1, (float)arg2) → Matrix3

__imul__( (Matrix3)arg1, (Matrix3)arg2) → Matrix3

__init__() → None

__init__((Quaternion)q) → None

__init__((Matrix3)other) → None

__init__((Vector3)diag) → object

__init__((float)m00, (float)m01, (float)m02, (float)m10, (float)m11, (float)m12, (float)m20, (float)m21, (float)m22) → object

__init__((Vector3)r0, (Vector3)r1, (Vector3)r2 [, (bool)cols=False]) → object

__isub__((Matrix3)arg2) → Matrix3
__itruediv__((int)arg2) → Matrix3

__itruediv__( (Matrix3)arg1, (float)arg2) → Matrix3

static __len__() → int [STATIC]
__mul__((int)arg2) → Matrix3

__mul__( (Matrix3)arg1, (float)arg2) → Matrix3

__mul__( (Matrix3)arg1, (Matrix3)arg2) → Matrix3

__mul__( (Matrix3)arg1, (Vector3)arg2) → Vector3

__ne__((Matrix3)arg2) → bool
__neg__() → Matrix3
__repr__() → str
__rmul__((int)arg2) → Matrix3

__rmul__( (Matrix3)arg1, (float)arg2) → Matrix3

__rmul__( (Matrix3)arg1, (Vector3)arg2) → Vector3

__setitem__((int)arg2, (Vector3)arg3) → None

__setitem__( (Matrix3)arg1, (tuple)arg2, (float)arg3) → None

__str__() → str
__sub__((Matrix3)arg2) → Matrix3
__truediv__((int)arg2) → Matrix3

__truediv__( (Matrix3)arg1, (float)arg2) → Matrix3

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.

isApprox((Matrix3)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

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.

maxCoeff() → float

Maximum value over all elements.

mean() → float

Mean value over all elements.

minCoeff() → float

Minimum 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.

prod() → float

Product of all elements.

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

/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 [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)
__abs__() → float
__add__((Matrix3c)arg2) → Matrix3c
__div__((int)arg2) → Matrix3c

__div__( (Matrix3c)arg1, (complex)arg2) → Matrix3c

__eq__((Matrix3c)arg2) → bool
__getitem__((int)arg2) → Vector3c

__getitem__( (Matrix3c)arg1, (tuple)arg2) → complex

__iadd__((Matrix3c)arg2) → Matrix3c
__idiv__((int)arg2) → Matrix3c

__idiv__( (Matrix3c)arg1, (complex)arg2) → Matrix3c

__imul__((int)arg2) → Matrix3c

__imul__( (Matrix3c)arg1, (complex)arg2) → Matrix3c

__imul__( (Matrix3c)arg1, (Matrix3c)arg2) → Matrix3c

__init__() → None

__init__((Matrix3c)other) → None

__init__((Vector3c)diag) → object

__init__((complex)m00, (complex)m01, (complex)m02, (complex)m10, (complex)m11, (complex)m12, (complex)m20, (complex)m21, (complex)m22) → object

__init__((Vector3c)r0, (Vector3c)r1, (Vector3c)r2 [, (bool)cols=False]) → object

__isub__((Matrix3c)arg2) → Matrix3c
__itruediv__((int)arg2) → Matrix3c

__itruediv__( (Matrix3c)arg1, (complex)arg2) → Matrix3c

static __len__() → int [STATIC]
__mul__((int)arg2) → Matrix3c

__mul__( (Matrix3c)arg1, (complex)arg2) → Matrix3c

__mul__( (Matrix3c)arg1, (Matrix3c)arg2) → Matrix3c

__mul__( (Matrix3c)arg1, (Vector3c)arg2) → Vector3c

__ne__((Matrix3c)arg2) → bool
__neg__() → Matrix3c
__repr__() → str
__rmul__((int)arg2) → Matrix3c

__rmul__( (Matrix3c)arg1, (complex)arg2) → Matrix3c

__rmul__( (Matrix3c)arg1, (Vector3c)arg2) → Vector3c

__setitem__((int)arg2, (Vector3c)arg3) → None

__setitem__( (Matrix3c)arg1, (tuple)arg2, (complex)arg3) → None

__str__() → str
__sub__((Matrix3c)arg2) → Matrix3c
__truediv__((int)arg2) → Matrix3c

__truediv__( (Matrix3c)arg1, (complex)arg2) → Matrix3c

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.

isApprox((Matrix3c)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

mean() → complex

Mean value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Matrix3c

Return normalized copy of this object

prod() → complex

Product of all elements.

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

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 [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) )
__abs__() → float
__add__((Matrix6)arg2) → Matrix6
__div__((int)arg2) → Matrix6

__div__( (Matrix6)arg1, (float)arg2) → Matrix6

__eq__((Matrix6)arg2) → bool
__getitem__((int)arg2) → Vector6

__getitem__( (Matrix6)arg1, (tuple)arg2) → float

__iadd__((Matrix6)arg2) → Matrix6
__idiv__((int)arg2) → Matrix6

__idiv__( (Matrix6)arg1, (float)arg2) → Matrix6

__imul__((int)arg2) → Matrix6

__imul__( (Matrix6)arg1, (float)arg2) → Matrix6

__imul__( (Matrix6)arg1, (Matrix6)arg2) → Matrix6

__init__() → None

__init__((Matrix6)other) → None

__init__((Vector6)diag) → object

__init__((Matrix3)ul, (Matrix3)ur, (Matrix3)ll, (Matrix3)lr) → object

__init__((Vector6)l0, (Vector6)l1, (Vector6)l2, (Vector6)l3, (Vector6)l4, (Vector6)l5 [, (bool)cols=False]) → object

__isub__((Matrix6)arg2) → Matrix6
__itruediv__((int)arg2) → Matrix6

__itruediv__( (Matrix6)arg1, (float)arg2) → Matrix6

static __len__() → int [STATIC]
__mul__((int)arg2) → Matrix6

__mul__( (Matrix6)arg1, (float)arg2) → Matrix6

__mul__( (Matrix6)arg1, (Matrix6)arg2) → Matrix6

__mul__( (Matrix6)arg1, (Vector6)arg2) → Vector6

__ne__((Matrix6)arg2) → bool
__neg__() → Matrix6
__repr__() → str
__rmul__((int)arg2) → Matrix6

__rmul__( (Matrix6)arg1, (float)arg2) → Matrix6

__rmul__( (Matrix6)arg1, (Vector6)arg2) → Vector6

__setitem__((int)arg2, (Vector6)arg3) → None

__setitem__( (Matrix6)arg1, (tuple)arg2, (float)arg3) → None

__str__() → str
__sub__((Matrix6)arg2) → Matrix6
__truediv__((int)arg2) → Matrix6

__truediv__( (Matrix6)arg1, (float)arg2) → Matrix6

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.

isApprox((Matrix6)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

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.

maxCoeff() → float

Maximum value over all elements.

mean() → float

Mean value over all elements.

minCoeff() → float

Minimum 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.

prod() → float

Product of all elements.

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

/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 [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) )
__abs__() → float
__add__((Matrix6c)arg2) → Matrix6c
__div__((int)arg2) → Matrix6c

__div__( (Matrix6c)arg1, (complex)arg2) → Matrix6c

__eq__((Matrix6c)arg2) → bool
__getitem__((int)arg2) → Vector6c

__getitem__( (Matrix6c)arg1, (tuple)arg2) → complex

__iadd__((Matrix6c)arg2) → Matrix6c
__idiv__((int)arg2) → Matrix6c

__idiv__( (Matrix6c)arg1, (complex)arg2) → Matrix6c

__imul__((int)arg2) → Matrix6c

__imul__( (Matrix6c)arg1, (complex)arg2) → Matrix6c

__imul__( (Matrix6c)arg1, (Matrix6c)arg2) → Matrix6c

__init__() → None

__init__((Matrix6c)other) → None

__init__((Vector6c)diag) → object

__init__((Matrix3c)ul, (Matrix3c)ur, (Matrix3c)ll, (Matrix3c)lr) → object

__init__((Vector6c)l0, (Vector6c)l1, (Vector6c)l2, (Vector6c)l3, (Vector6c)l4, (Vector6c)l5 [, (bool)cols=False]) → object

__isub__((Matrix6c)arg2) → Matrix6c
__itruediv__((int)arg2) → Matrix6c

__itruediv__( (Matrix6c)arg1, (complex)arg2) → Matrix6c

static __len__() → int [STATIC]
__mul__((int)arg2) → Matrix6c

__mul__( (Matrix6c)arg1, (complex)arg2) → Matrix6c

__mul__( (Matrix6c)arg1, (Matrix6c)arg2) → Matrix6c

__mul__( (Matrix6c)arg1, (Vector6c)arg2) → Vector6c

__ne__((Matrix6c)arg2) → bool
__neg__() → Matrix6c
__repr__() → str
__rmul__((int)arg2) → Matrix6c

__rmul__( (Matrix6c)arg1, (complex)arg2) → Matrix6c

__rmul__( (Matrix6c)arg1, (Vector6c)arg2) → Vector6c

__setitem__((int)arg2, (Vector6c)arg3) → None

__setitem__( (Matrix6c)arg1, (tuple)arg2, (complex)arg3) → None

__str__() → str
__sub__((Matrix6c)arg2) → Matrix6c
__truediv__((int)arg2) → Matrix6c

__truediv__( (Matrix6c)arg1, (complex)arg2) → Matrix6c

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.

isApprox((Matrix6c)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

ll() → Matrix3c

Return lower-left 3x3 block

lr() → Matrix3c

Return lower-right 3x3 block

maxAbsCoeff() → float

Maximum absolute value over all elements.

mean() → complex

Mean value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → Matrix6c

Return normalized copy of this object

prod() → complex

Product of all elements.

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

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 [STATIC]

Create identity matrix with given rank (square).

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

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

static 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).

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

Create zero matrix of given dimensions

__abs__() → float
__add__((MatrixX)arg2) → MatrixX
__div__((int)arg2) → MatrixX

__div__( (MatrixX)arg1, (float)arg2) → MatrixX

__eq__((MatrixX)arg2) → bool
__getitem__((int)arg2) → VectorX

__getitem__( (MatrixX)arg1, (tuple)arg2) → float

__iadd__((MatrixX)arg2) → MatrixX
__idiv__((int)arg2) → MatrixX

__idiv__( (MatrixX)arg1, (float)arg2) → MatrixX

__imul__((int)arg2) → MatrixX

__imul__( (MatrixX)arg1, (float)arg2) → MatrixX

__imul__( (MatrixX)arg1, (MatrixX)arg2) → MatrixX

__init__() → None

__init__((MatrixX)other) → None

__init__((VectorX)diag) → object

__init__( [, (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)rows [, (bool)cols=False]) → object

__isub__((MatrixX)arg2) → MatrixX
__itruediv__((int)arg2) → MatrixX

__itruediv__( (MatrixX)arg1, (float)arg2) → MatrixX

__len__() → int
__mul__((int)arg2) → MatrixX

__mul__( (MatrixX)arg1, (float)arg2) → MatrixX

__mul__( (MatrixX)arg1, (MatrixX)arg2) → MatrixX

__mul__( (MatrixX)arg1, (VectorX)arg2) → VectorX

__ne__((MatrixX)arg2) → bool
__neg__() → MatrixX
__repr__() → str
__rmul__((int)arg2) → MatrixX

__rmul__( (MatrixX)arg1, (float)arg2) → MatrixX

__rmul__( (MatrixX)arg1, (VectorX)arg2) → VectorX

__setitem__((int)arg2, (VectorX)arg3) → None

__setitem__( (MatrixX)arg1, (tuple)arg2, (float)arg3) → None

__str__() → str
__sub__((MatrixX)arg2) → MatrixX
__truediv__((int)arg2) → MatrixX

__truediv__( (MatrixX)arg1, (float)arg2) → MatrixX

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.

isApprox((MatrixX)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

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.

maxCoeff() → float

Maximum value over all elements.

mean() → float

Mean value over all elements.

minCoeff() → float

Minimum 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.

prod() → float

Product of all elements.

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

/TODO/

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

Create identity matrix with given rank (square).

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

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

static 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).

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

Create zero matrix of given dimensions

__abs__() → float
__add__((MatrixXc)arg2) → MatrixXc
__div__((int)arg2) → MatrixXc

__div__( (MatrixXc)arg1, (complex)arg2) → MatrixXc

__eq__((MatrixXc)arg2) → bool
__getitem__((int)arg2) → VectorXc

__getitem__( (MatrixXc)arg1, (tuple)arg2) → complex

__iadd__((MatrixXc)arg2) → MatrixXc
__idiv__((int)arg2) → MatrixXc

__idiv__( (MatrixXc)arg1, (complex)arg2) → MatrixXc

__imul__((int)arg2) → MatrixXc

__imul__( (MatrixXc)arg1, (complex)arg2) → MatrixXc

__imul__( (MatrixXc)arg1, (MatrixXc)arg2) → MatrixXc

__init__() → None

__init__((MatrixXc)other) → None

__init__((VectorXc)diag) → object

__init__( [, (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)rows [, (bool)cols=False]) → object

__isub__((MatrixXc)arg2) → MatrixXc
__itruediv__((int)arg2) → MatrixXc

__itruediv__( (MatrixXc)arg1, (complex)arg2) → MatrixXc

__len__() → int
__mul__((int)arg2) → MatrixXc

__mul__( (MatrixXc)arg1, (complex)arg2) → MatrixXc

__mul__( (MatrixXc)arg1, (MatrixXc)arg2) → MatrixXc

__mul__( (MatrixXc)arg1, (VectorXc)arg2) → VectorXc

__ne__((MatrixXc)arg2) → bool
__neg__() → MatrixXc
__repr__() → str
__rmul__((int)arg2) → MatrixXc

__rmul__( (MatrixXc)arg1, (complex)arg2) → MatrixXc

__rmul__( (MatrixXc)arg1, (VectorXc)arg2) → VectorXc

__setitem__((int)arg2, (VectorXc)arg3) → None

__setitem__( (MatrixXc)arg1, (tuple)arg2, (complex)arg3) → None

__str__() → str
__sub__((MatrixXc)arg2) → MatrixXc
__truediv__((int)arg2) → MatrixXc

__truediv__( (MatrixXc)arg1, (complex)arg2) → MatrixXc

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.

isApprox((MatrixXc)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

mean() → complex

Mean value over all elements.

norm() → float

Euclidean norm.

normalize() → None

Normalize this object in-place.

normalized() → MatrixXc

Return normalized copy of this object

prod() → complex

Product of all elements.

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

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.

Note

Quaternion is represented as axis-angle when printed (e.g. Identity is Quaternion((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, use Quaternion.toAxisAngle which returns the tuple.

Identity = Quaternion((1,0,0),0)
Rotate((Vector3)v) → Vector3
__abs__() → float
__eq__((Quaternion)arg2) → bool
__getitem__((int)arg2) → float
__imul__((Quaternion)arg2) → object
__init__() → None

__init__((Vector3)axis, (float)angle) → object

__init__((float)angle, (Vector3)axis) → object

__init__((Vector3)u, (Vector3)v) → object

__init__((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__((Matrix3)rotMatrix) → None

__init__((Quaternion)other) → None

static __len__() → int [STATIC]
__mul__((Quaternion)arg2) → object

__mul__( (Quaternion)arg1, (Vector3)arg2) → object

__ne__((Quaternion)arg2) → bool
__repr__() → str
__setitem__((int)arg2, (float)arg3) → None
__str__() → str
__sub__((Quaternion)arg2) → VectorX
angularDistance((Quaternion)arg2) → float
conjugate() → Quaternion
inverse() → Quaternion
norm() → float
normalize() → None
normalized() → Quaternion
setFromTwoVectors((Vector3)u, (Vector3)v) → None
slerp((float)t, (Quaternion)other) → Quaternion
toAngleAxis() → tuple
toAxisAngle() → tuple
toRotationMatrix() → Matrix3
toRotationVector() → Vector3
class minieigen.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 [STATIC]

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

static Unit((int)arg1) → Vector2 [STATIC]
UnitX = Vector2(1,0)
UnitY = Vector2(0,1)
Zero = Vector2(0,0)
__abs__() → float
__add__((Vector2)arg2) → Vector2
__div__((int)arg2) → Vector2

__div__( (Vector2)arg1, (float)arg2) → Vector2

__eq__((Vector2)arg2) → bool
__getitem__((int)arg2) → float
__iadd__((Vector2)arg2) → Vector2
__idiv__((int)arg2) → Vector2

__idiv__( (Vector2)arg1, (float)arg2) → Vector2

__imul__((int)arg2) → Vector2

__imul__( (Vector2)arg1, (float)arg2) → Vector2

__init__() → None

__init__((Vector2)other) → None

__init__((float)x, (float)y) → None

__isub__((Vector2)arg2) → Vector2
__itruediv__((int)arg2) → Vector2

__itruediv__( (Vector2)arg1, (float)arg2) → Vector2

static __len__() → int [STATIC]
__mul__((int)arg2) → Vector2

__mul__( (Vector2)arg1, (float)arg2) → Vector2

__ne__((Vector2)arg2) → bool
__neg__() → Vector2
__repr__() → str
__rmul__((int)arg2) → Vector2

__rmul__( (Vector2)arg1, (float)arg2) → Vector2

__setitem__((int)arg2, (float)arg3) → None
__str__() → str
__sub__((Vector2)arg2) → Vector2
__truediv__((int)arg2) → Vector2

__truediv__( (Vector2)arg1, (float)arg2) → Vector2

asDiagonal() → object

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((Vector2)other) → float

Dot product with other.

isApprox((Vector2)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

maxCoeff() → float

Maximum value over all elements.

mean() → float

Mean value over all elements.

minCoeff() → float

Minimum 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.

prod() → float

Product of all elements.

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

/TODO/

Identity = Vector2c(1,0)
Ones = Vector2c(1,1)
static Random() → Vector2c [STATIC]

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

static Unit((int)arg1) → Vector2c [STATIC]
UnitX = Vector2c(1,0)
UnitY = Vector2c(0,1)
Zero = Vector2c(0,0)
__abs__() → float
__add__((Vector2c)arg2) → Vector2c
__div__((int)arg2) → Vector2c

__div__( (Vector2c)arg1, (complex)arg2) → Vector2c

__eq__((Vector2c)arg2) → bool
__getitem__((int)arg2) → complex
__iadd__((Vector2c)arg2) → Vector2c
__idiv__((int)arg2) → Vector2c

__idiv__( (Vector2c)arg1, (complex)arg2) → Vector2c

__imul__((int)arg2) → Vector2c

__imul__( (Vector2c)arg1, (complex)arg2) → Vector2c

__init__() → None

__init__((Vector2c)other) → None

__init__((complex)x, (complex)y) → None

__isub__((Vector2c)arg2) → Vector2c
__itruediv__((int)arg2) → Vector2c

__itruediv__( (Vector2c)arg1, (complex)arg2) → Vector2c

static __len__() → int [STATIC]
__mul__((int)arg2) → Vector2c

__mul__( (Vector2c)arg1, (complex)arg2) → Vector2c

__ne__((Vector2c)arg2) → bool
__neg__() → Vector2c
__repr__() → str
__rmul__((int)arg2) → Vector2c

__rmul__( (Vector2c)arg1, (complex)arg2) → Vector2c

__setitem__((int)arg2, (complex)arg3) → None
__str__() → str
__sub__((Vector2c)arg2) → Vector2c
__truediv__((int)arg2) → Vector2c

__truediv__( (Vector2c)arg1, (complex)arg2) → Vector2c

asDiagonal() → object

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((Vector2c)other) → complex

Dot product with other.

isApprox((Vector2c)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

mean() → complex

Mean 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.

prod() → complex

Product of all elements.

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

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 [STATIC]

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

static Unit((int)arg1) → Vector2i [STATIC]
UnitX = Vector2i(1,0)
UnitY = Vector2i(0,1)
Zero = Vector2i(0,0)
__add__((Vector2i)arg2) → Vector2i
__eq__((Vector2i)arg2) → bool
__getitem__((int)arg2) → int
__iadd__((Vector2i)arg2) → Vector2i
__imul__((int)arg2) → Vector2i
__init__() → None

__init__((Vector2i)other) → None

__init__((int)x, (int)y) → None

__isub__((Vector2i)arg2) → Vector2i
static __len__() → int [STATIC]
__mul__((int)arg2) → Vector2i
__ne__((Vector2i)arg2) → bool
__neg__() → Vector2i
__repr__() → str
__rmul__((int)arg2) → Vector2i
__setitem__((int)arg2, (int)arg3) → None
__str__() → str
__sub__((Vector2i)arg2) → Vector2i
asDiagonal() → object

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((Vector2i)other) → int

Dot product with other.

isApprox((Vector2i)other[, (int)prec=0]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → int

Maximum absolute value over all elements.

maxCoeff() → int

Maximum value over all elements.

mean() → int

Mean value over all elements.

minCoeff() → int

Minimum value over all elements.

outer((Vector2i)other) → object

Outer product with other.

prod() → int

Product of all elements.

rows() → int

Number of rows.

sum() → int

Sum of all elements.

class minieigen.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 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)
static Random() → Vector3 [STATIC]

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

static 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)
__abs__() → float
__add__((Vector3)arg2) → Vector3
__div__((int)arg2) → Vector3

__div__( (Vector3)arg1, (float)arg2) → Vector3

__eq__((Vector3)arg2) → bool
__getitem__((int)arg2) → float
__iadd__((Vector3)arg2) → Vector3
__idiv__((int)arg2) → Vector3

__idiv__( (Vector3)arg1, (float)arg2) → Vector3

__imul__((int)arg2) → Vector3

__imul__( (Vector3)arg1, (float)arg2) → Vector3

__init__() → None

__init__((Vector3)other) → None

__init__((float)x, (float)y, (float)z) → None

__isub__((Vector3)arg2) → Vector3
__itruediv__((int)arg2) → Vector3

__itruediv__( (Vector3)arg1, (float)arg2) → Vector3

static __len__() → int [STATIC]
__mul__((int)arg2) → Vector3

__mul__( (Vector3)arg1, (float)arg2) → Vector3

__ne__((Vector3)arg2) → bool
__neg__() → Vector3
__repr__() → str
__rmul__((int)arg2) → Vector3

__rmul__( (Vector3)arg1, (float)arg2) → Vector3

__setitem__((int)arg2, (float)arg3) → None
__str__() → str
__sub__((Vector3)arg2) → Vector3
__truediv__((int)arg2) → Vector3

__truediv__( (Vector3)arg1, (float)arg2) → Vector3

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.

isApprox((Vector3)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

maxCoeff() → float

Maximum value over all elements.

mean() → float

Mean value over all elements.

minCoeff() → float

Minimum 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.

prod() → float

Product of all elements.

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

/TODO/

Identity = Vector3c(1,0,0)
Ones = Vector3c(1,1,1)
static Random() → Vector3c [STATIC]

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

static 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)
__abs__() → float
__add__((Vector3c)arg2) → Vector3c
__div__((int)arg2) → Vector3c

__div__( (Vector3c)arg1, (complex)arg2) → Vector3c

__eq__((Vector3c)arg2) → bool
__getitem__((int)arg2) → complex
__iadd__((Vector3c)arg2) → Vector3c
__idiv__((int)arg2) → Vector3c

__idiv__( (Vector3c)arg1, (complex)arg2) → Vector3c

__imul__((int)arg2) → Vector3c

__imul__( (Vector3c)arg1, (complex)arg2) → Vector3c

__init__() → None

__init__((Vector3c)other) → None

__init__((complex)x, (complex)y, (complex)z) → None

__isub__((Vector3c)arg2) → Vector3c
__itruediv__((int)arg2) → Vector3c

__itruediv__( (Vector3c)arg1, (complex)arg2) → Vector3c

static __len__() → int [STATIC]
__mul__((int)arg2) → Vector3c

__mul__( (Vector3c)arg1, (complex)arg2) → Vector3c

__ne__((Vector3c)arg2) → bool
__neg__() → Vector3c
__repr__() → str
__rmul__((int)arg2) → Vector3c

__rmul__( (Vector3c)arg1, (complex)arg2) → Vector3c

__setitem__((int)arg2, (complex)arg3) → None
__str__() → str
__sub__((Vector3c)arg2) → Vector3c
__truediv__((int)arg2) → Vector3c

__truediv__( (Vector3c)arg1, (complex)arg2) → Vector3c

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.

isApprox((Vector3c)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

mean() → complex

Mean 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.

prod() → complex

Product of all elements.

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

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 [STATIC]

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

static 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)
__add__((Vector3i)arg2) → Vector3i
__eq__((Vector3i)arg2) → bool
__getitem__((int)arg2) → int
__iadd__((Vector3i)arg2) → Vector3i
__imul__((int)arg2) → Vector3i
__init__() → None

__init__((Vector3i)other) → None

__init__((int)x, (int)y, (int)z) → None

__isub__((Vector3i)arg2) → Vector3i
static __len__() → int [STATIC]
__mul__((int)arg2) → Vector3i
__ne__((Vector3i)arg2) → bool
__neg__() → Vector3i
__repr__() → str
__rmul__((int)arg2) → Vector3i
__setitem__((int)arg2, (int)arg3) → None
__str__() → str
__sub__((Vector3i)arg2) → Vector3i
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.

isApprox((Vector3i)other[, (int)prec=0]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → int

Maximum absolute value over all elements.

maxCoeff() → int

Maximum value over all elements.

mean() → int

Mean value over all elements.

minCoeff() → int

Minimum value over all elements.

outer((Vector3i)other) → object

Outer product with other.

prod() → int

Product of all elements.

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

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 [STATIC]

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

static Unit((int)arg1) → Vector6 [STATIC]
Zero = Vector6(0,0,0, 0,0,0)
__abs__() → float
__add__((Vector6)arg2) → Vector6
__div__((int)arg2) → Vector6

__div__( (Vector6)arg1, (float)arg2) → Vector6

__eq__((Vector6)arg2) → bool
__getitem__((int)arg2) → float
__iadd__((Vector6)arg2) → Vector6
__idiv__((int)arg2) → Vector6

__idiv__( (Vector6)arg1, (float)arg2) → Vector6

__imul__((int)arg2) → Vector6

__imul__( (Vector6)arg1, (float)arg2) → Vector6

__init__() → None

__init__((Vector6)other) → None

__init__((float)v0, (float)v1, (float)v2, (float)v3, (float)v4, (float)v5) → object

__init__((Vector3)head, (Vector3)tail) → object

__isub__((Vector6)arg2) → Vector6
__itruediv__((int)arg2) → Vector6

__itruediv__( (Vector6)arg1, (float)arg2) → Vector6

static __len__() → int [STATIC]
__mul__((int)arg2) → Vector6

__mul__( (Vector6)arg1, (float)arg2) → Vector6

__ne__((Vector6)arg2) → bool
__neg__() → Vector6
__repr__() → str
__rmul__((int)arg2) → Vector6

__rmul__( (Vector6)arg1, (float)arg2) → Vector6

__setitem__((int)arg2, (float)arg3) → None
__str__() → str
__sub__((Vector6)arg2) → Vector6
__truediv__((int)arg2) → Vector6

__truediv__( (Vector6)arg1, (float)arg2) → Vector6

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
isApprox((Vector6)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

maxCoeff() → float

Maximum value over all elements.

mean() → float

Mean value over all elements.

minCoeff() → float

Minimum 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.

prod() → float

Product of all elements.

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

/TODO/

Identity = Vector6c(1,0,0, 0,0,0)
Ones = Vector6c(1,1,1, 1,1,1)
static Random() → Vector6c [STATIC]

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

static Unit((int)arg1) → Vector6c [STATIC]
Zero = Vector6c(0,0,0, 0,0,0)
__abs__() → float
__add__((Vector6c)arg2) → Vector6c
__div__((int)arg2) → Vector6c

__div__( (Vector6c)arg1, (complex)arg2) → Vector6c

__eq__((Vector6c)arg2) → bool
__getitem__((int)arg2) → complex
__iadd__((Vector6c)arg2) → Vector6c
__idiv__((int)arg2) → Vector6c

__idiv__( (Vector6c)arg1, (complex)arg2) → Vector6c

__imul__((int)arg2) → Vector6c

__imul__( (Vector6c)arg1, (complex)arg2) → Vector6c

__init__() → None

__init__((Vector6c)other) → None

__init__((complex)v0, (complex)v1, (complex)v2, (complex)v3, (complex)v4, (complex)v5) → object

__init__((Vector3c)head, (Vector3c)tail) → object

__isub__((Vector6c)arg2) → Vector6c
__itruediv__((int)arg2) → Vector6c

__itruediv__( (Vector6c)arg1, (complex)arg2) → Vector6c

static __len__() → int [STATIC]
__mul__((int)arg2) → Vector6c

__mul__( (Vector6c)arg1, (complex)arg2) → Vector6c

__ne__((Vector6c)arg2) → bool
__neg__() → Vector6c
__repr__() → str
__rmul__((int)arg2) → Vector6c

__rmul__( (Vector6c)arg1, (complex)arg2) → Vector6c

__setitem__((int)arg2, (complex)arg3) → None
__str__() → str
__sub__((Vector6c)arg2) → Vector6c
__truediv__((int)arg2) → Vector6c

__truediv__( (Vector6c)arg1, (complex)arg2) → Vector6c

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
isApprox((Vector6c)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

mean() → complex

Mean 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.

prod() → complex

Product of all elements.

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

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)
static Random() → Vector6i [STATIC]

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

static Unit((int)arg1) → Vector6i [STATIC]
Zero = Vector6i(0,0,0, 0,0,0)
__add__((Vector6i)arg2) → Vector6i
__eq__((Vector6i)arg2) → bool
__getitem__((int)arg2) → int
__iadd__((Vector6i)arg2) → Vector6i
__imul__((int)arg2) → Vector6i
__init__() → None

__init__((Vector6i)other) → None

__init__((int)v0, (int)v1, (int)v2, (int)v3, (int)v4, (int)v5) → object

__init__((Vector3i)head, (Vector3i)tail) → object

__isub__((Vector6i)arg2) → Vector6i
static __len__() → int [STATIC]
__mul__((int)arg2) → Vector6i
__ne__((Vector6i)arg2) → bool
__neg__() → Vector6i
__repr__() → str
__rmul__((int)arg2) → Vector6i
__setitem__((int)arg2, (int)arg3) → None
__str__() → str
__sub__((Vector6i)arg2) → Vector6i
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
isApprox((Vector6i)other[, (int)prec=0]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → int

Maximum absolute value over all elements.

maxCoeff() → int

Maximum value over all elements.

mean() → int

Mean value over all elements.

minCoeff() → int

Minimum value over all elements.

outer((Vector6i)other) → object

Outer product with other.

prod() → int

Product of all elements.

rows() → int

Number of rows.

sum() → int

Sum of all elements.

tail() → Vector3i
class minieigen.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 Ones((int)arg1) → VectorX [STATIC]
static Random((int)len) → VectorX [STATIC]

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

static Unit((int)arg1, (int)arg2) → VectorX [STATIC]
static Zero((int)arg1) → VectorX [STATIC]
__abs__() → float
__add__((VectorX)arg2) → VectorX
__div__((int)arg2) → VectorX

__div__( (VectorX)arg1, (float)arg2) → VectorX

__eq__((VectorX)arg2) → bool
__getitem__((int)arg2) → float
__iadd__((VectorX)arg2) → VectorX
__idiv__((int)arg2) → VectorX

__idiv__( (VectorX)arg1, (float)arg2) → VectorX

__imul__((int)arg2) → VectorX

__imul__( (VectorX)arg1, (float)arg2) → VectorX

__init__() → None

__init__((VectorX)other) → None

__init__((object)vv) → object

__isub__((VectorX)arg2) → VectorX
__itruediv__((int)arg2) → VectorX

__itruediv__( (VectorX)arg1, (float)arg2) → VectorX

__len__() → int
__mul__((int)arg2) → VectorX

__mul__( (VectorX)arg1, (float)arg2) → VectorX

__ne__((VectorX)arg2) → bool
__neg__() → VectorX
__repr__() → str
__rmul__((int)arg2) → VectorX

__rmul__( (VectorX)arg1, (float)arg2) → VectorX

__setitem__((int)arg2, (float)arg3) → None
__str__() → str
__sub__((VectorX)arg2) → VectorX
__truediv__((int)arg2) → VectorX

__truediv__( (VectorX)arg1, (float)arg2) → VectorX

asDiagonal() → MatrixX

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((VectorX)other) → float

Dot product with other.

isApprox((VectorX)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

maxCoeff() → float

Maximum value over all elements.

mean() → float

Mean value over all elements.

minCoeff() → float

Minimum 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.

prod() → float

Product of all elements.

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

/TODO/

static Ones((int)arg1) → VectorXc [STATIC]
static Random((int)len) → VectorXc [STATIC]

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

static Unit((int)arg1, (int)arg2) → VectorXc [STATIC]
static Zero((int)arg1) → VectorXc [STATIC]
__abs__() → float
__add__((VectorXc)arg2) → VectorXc
__div__((int)arg2) → VectorXc

__div__( (VectorXc)arg1, (complex)arg2) → VectorXc

__eq__((VectorXc)arg2) → bool
__getitem__((int)arg2) → complex
__iadd__((VectorXc)arg2) → VectorXc
__idiv__((int)arg2) → VectorXc

__idiv__( (VectorXc)arg1, (complex)arg2) → VectorXc

__imul__((int)arg2) → VectorXc

__imul__( (VectorXc)arg1, (complex)arg2) → VectorXc

__init__() → None

__init__((VectorXc)other) → None

__init__((object)vv) → object

__isub__((VectorXc)arg2) → VectorXc
__itruediv__((int)arg2) → VectorXc

__itruediv__( (VectorXc)arg1, (complex)arg2) → VectorXc

__len__() → int
__mul__((int)arg2) → VectorXc

__mul__( (VectorXc)arg1, (complex)arg2) → VectorXc

__ne__((VectorXc)arg2) → bool
__neg__() → VectorXc
__repr__() → str
__rmul__((int)arg2) → VectorXc

__rmul__( (VectorXc)arg1, (complex)arg2) → VectorXc

__setitem__((int)arg2, (complex)arg3) → None
__str__() → str
__sub__((VectorXc)arg2) → VectorXc
__truediv__((int)arg2) → VectorXc

__truediv__( (VectorXc)arg1, (complex)arg2) → VectorXc

asDiagonal() → MatrixXc

Return diagonal matrix with this vector on the diagonal.

cols() → int

Number of columns.

dot((VectorXc)other) → complex

Dot product with other.

isApprox((VectorXc)other[, (float)prec=1e-12]) → bool

Approximate comparison with precision prec.

maxAbsCoeff() → float

Maximum absolute value over all elements.

mean() → complex

Mean 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.

prod() → complex

Product of all elements.

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.

minieigen.float2str((float)f[, (int)pad=0]) → str

Return the shortest string representation of f which will is equal to f when converted back to float. This function is only useful in Python prior to 3.0; starting from that version, standard string conversion does just that.