Vector Functions

SubModule Containing Vector and Scalar Function Types and Functions

class asset.VectorFunctions.Arguments

Bases: pybind11_object

Constant(*args, **kwargs)

Overloaded function.

1. Constant(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. Constant(self: asset.VectorFunctions.Arguments, arg0: float) -> asset.VectorFunctions.ScalarFunction

IRows(self: asset.VectorFunctions.Arguments) → int

ORows(self: asset.VectorFunctions.Arguments) → int

__add__(*args, **kwargs)

Overloaded function.

1. __add__(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. __add__(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Arguments) -> asset.VectorFunctions.VectorFunction

__array_ufunc__ = None

__call__(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

__getitem__(*args, **kwargs)

Overloaded function.

1. __getitem__(self: asset.VectorFunctions.Arguments, arg0: int) -> asset.VectorFunctions.Element

2. __getitem__(self: asset.VectorFunctions.Arguments, arg0: slice) -> asset.VectorFunctions.Segment

__init__(self: asset.VectorFunctions.Arguments, arg0: int) → None

__module__ = 'asset.VectorFunctions'

__mul__(*args, **kwargs)

Overloaded function.

1. __mul__(self: asset.VectorFunctions.Arguments, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __mul__(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

3. __mul__(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__neg__(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.VectorFunction

__radd__(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) → asset.VectorFunctions.VectorFunction

__rmul__(*args, **kwargs)

Overloaded function.

1. __rmul__(self: asset.VectorFunctions.Arguments, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __rmul__(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

3. __rmul__(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__rsub__(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) → asset.VectorFunctions.VectorFunction

__sub__(*args, **kwargs)

Overloaded function.

1. __sub__(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. __sub__(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Arguments) -> asset.VectorFunctions.VectorFunction

__truediv__(*args, **kwargs)

Overloaded function.

1. __truediv__(self: asset.VectorFunctions.Arguments, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __truediv__(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

3. __truediv__(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

4. __truediv__(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

adjointgradient(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

apply(*args, **kwargs)

Overloaded function.

1. apply(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. apply(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

coeff(self: asset.VectorFunctions.Arguments, arg0: int) → asset.VectorFunctions.Element

compute(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

compute_jacobian(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

computeall(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

cross(*args, **kwargs)

Overloaded function.

1. cross(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

2. cross(self: asset.VectorFunctions.Arguments, arg0: ASSET::Segment<-1, 3, -1>) -> asset.VectorFunctions.VectorFunction

3. cross(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

4. cross(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

5. cross(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Arguments) -> asset.VectorFunctions.VectorFunction

cubed_norm(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.ScalarFunction

cwiseProduct(*args, **kwargs)

Overloaded function.

1. cwiseProduct(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

2. cwiseProduct(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cwiseProduct(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Arguments) -> asset.VectorFunctions.VectorFunction

4. cwiseProduct(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

cwiseQuotient(*args, **kwargs)

Overloaded function.

1. cwiseQuotient(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

2. cwiseQuotient(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cwiseQuotient(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Arguments) -> asset.VectorFunctions.VectorFunction

4. cwiseQuotient(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

dot(*args, **kwargs)

Overloaded function.

1. dot(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.ScalarFunction

2. dot(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

3. dot(self: asset.VectorFunctions.Arguments, arg0: asset.VectorFunctions.Arguments) -> asset.VectorFunctions.ScalarFunction

4. dot(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.ScalarFunction

head(self: asset.VectorFunctions.Arguments, arg0: int) → asset.VectorFunctions.Segment

head2(self: asset.VectorFunctions.Arguments) → ASSET::Segment<-1, 2, -1>

head3(self: asset.VectorFunctions.Arguments) → ASSET::Segment<-1, 3, -1>

head_2(self: asset.VectorFunctions.Arguments) → ASSET::Segment<-1, 2, -1>

head_3(self: asset.VectorFunctions.Arguments) → ASSET::Segment<-1, 3, -1>

input_domain(self: asset.VectorFunctions.Arguments) → numpy.ndarray[numpy.int32[2, n]]

inverse_cubed_norm(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.ScalarFunction

inverse_four_norm(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.ScalarFunction

inverse_norm(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.ScalarFunction

inverse_squared_norm(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.ScalarFunction

is_linear(self: asset.VectorFunctions.Arguments) → bool

jacobian(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

name(self: asset.VectorFunctions.Arguments) → str

norm(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.ScalarFunction

normalized(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.VectorFunction

normalized_power2(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.VectorFunction

normalized_power3(*args, **kwargs)

Overloaded function.

1. normalized_power3(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. normalized_power3(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: float) -> asset.VectorFunctions.VectorFunction

3. normalized_power3(self: asset.VectorFunctions.Arguments) -> asset.VectorFunctions.VectorFunction

normalized_power4(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.VectorFunction

normalized_power5(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.VectorFunction

padded(self: asset.VectorFunctions.Arguments, arg0: int, arg1: int) → asset.VectorFunctions.VectorFunction

padded_lower(self: asset.VectorFunctions.Arguments, arg0: int) → asset.VectorFunctions.VectorFunction

padded_upper(self: asset.VectorFunctions.Arguments, arg0: int) → asset.VectorFunctions.VectorFunction

rpt(self: asset.VectorFunctions.Arguments, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

segment(self: asset.VectorFunctions.Arguments, arg0: int, arg1: int) → asset.VectorFunctions.Segment

segment2(self: asset.VectorFunctions.Arguments, arg0: int) → ASSET::Segment<-1, 2, -1>

segment3(self: asset.VectorFunctions.Arguments, arg0: int) → ASSET::Segment<-1, 3, -1>

segment_2(self: asset.VectorFunctions.Arguments, arg0: int) → ASSET::Segment<-1, 2, -1>

segment_3(self: asset.VectorFunctions.Arguments, arg0: int) → ASSET::Segment<-1, 3, -1>

squared_norm(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.ScalarFunction

sum(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.ScalarFunction

tail(self: asset.VectorFunctions.Arguments, arg0: int) → asset.VectorFunctions.Segment

tail2(self: asset.VectorFunctions.Arguments) → ASSET::Segment<-1, 2, -1>

tail3(self: asset.VectorFunctions.Arguments) → ASSET::Segment<-1, 3, -1>

tail_2(self: asset.VectorFunctions.Arguments) → ASSET::Segment<-1, 2, -1>

tail_3(self: asset.VectorFunctions.Arguments) → ASSET::Segment<-1, 3, -1>

tolist(*args, **kwargs)

Overloaded function.

1. tolist(self: asset.VectorFunctions.Arguments) -> list[asset.VectorFunctions.Element]

2. tolist(self: asset.VectorFunctions.Arguments, arg0: list[int]) -> list[asset.VectorFunctions.Element]

3. tolist(self: asset.VectorFunctions.Arguments, arg0: list[tuple[int, int]]) -> list[object]

vf(self: asset.VectorFunctions.Arguments) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.ColMatrix

Bases: pybind11_object

__add__(*args, **kwargs)

Overloaded function.

1. __add__(self: asset.VectorFunctions.ColMatrix, arg0: numpy.ndarray[numpy.float64[m, n]]) -> asset.VectorFunctions.ColMatrix

2. __add__(self: asset.VectorFunctions.ColMatrix, arg0: asset.VectorFunctions.ColMatrix) -> asset.VectorFunctions.ColMatrix

__array_ufunc__ = None

__init__(*args, **kwargs)

Overloaded function.

1. __init__(self: asset.VectorFunctions.ColMatrix, arg0: asset.VectorFunctions.VectorFunction, arg1: int, arg2: int) -> None

2. __init__(self: asset.VectorFunctions.ColMatrix, arg0: list[asset.VectorFunctions.VectorFunction]) -> None

__module__ = 'asset.VectorFunctions'

__mul__(*args, **kwargs)

Overloaded function.

1. __mul__(self: asset.VectorFunctions.ColMatrix, arg0: asset.VectorFunctions.ColMatrix) -> asset.VectorFunctions.ColMatrix

2. __mul__(self: asset.VectorFunctions.ColMatrix, arg0: ASSET::MatrixFunctionView<ASSET::GenericFunction<-1, -1>, -1, -1, 1>) -> asset.VectorFunctions.ColMatrix

3. __mul__(self: asset.VectorFunctions.ColMatrix, arg0: float) -> asset.VectorFunctions.ColMatrix

4. __mul__(self: asset.VectorFunctions.ColMatrix, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__radd__(self: asset.VectorFunctions.ColMatrix, arg0: numpy.ndarray[numpy.float64[m, n]]) → asset.VectorFunctions.ColMatrix

__rmul__(self: asset.VectorFunctions.ColMatrix, arg0: float) → asset.VectorFunctions.ColMatrix

inverse(self: asset.VectorFunctions.ColMatrix) → asset.VectorFunctions.ColMatrix

transpose(self: asset.VectorFunctions.ColMatrix) → ASSET::MatrixFunctionView<ASSET::GenericFunction<-1, -1>, -1, -1, 1>

vf(self: asset.VectorFunctions.ColMatrix) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.Comparative

Bases: pybind11_object

__init__(*args, **kwargs)

__module__ = 'asset.VectorFunctions'

compute(self: asset.VectorFunctions.Comparative, arg0: numpy.ndarray[numpy.float64[m, 1]]) → bool

max(*args, **kwargs)

Overloaded function.

1. max(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

2. max(self: float, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

3. max(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

4. max(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

5. max(self: numpy.ndarray[numpy.float64[m, 1]], arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

6. max(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

min(*args, **kwargs)

Overloaded function.

1. min(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

2. min(self: float, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

3. min(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

4. min(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

5. min(self: numpy.ndarray[numpy.float64[m, 1]], arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

6. min(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.Conditional

Bases: pybind11_object

__and__(self: asset.VectorFunctions.Conditional, arg0: asset.VectorFunctions.Conditional) → asset.VectorFunctions.Conditional

__init__(*args, **kwargs)

__module__ = 'asset.VectorFunctions'

__or__(self: asset.VectorFunctions.Conditional, arg0: asset.VectorFunctions.Conditional) → asset.VectorFunctions.Conditional

compute(self: asset.VectorFunctions.Conditional, arg0: numpy.ndarray[numpy.float64[m, 1]]) → bool

ifelse(*args, **kwargs)

Overloaded function.

1. ifelse(self: asset.VectorFunctions.Conditional, arg0: asset.VectorFunctions.ScalarFunction, arg1: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

2. ifelse(self: asset.VectorFunctions.Conditional, arg0: float, arg1: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

3. ifelse(self: asset.VectorFunctions.Conditional, arg0: asset.VectorFunctions.ScalarFunction, arg1: float) -> asset.VectorFunctions.ScalarFunction

4. ifelse(self: asset.VectorFunctions.Conditional, arg0: float, arg1: float) -> asset.VectorFunctions.ScalarFunction

5. ifelse(self: asset.VectorFunctions.Conditional, arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

6. ifelse(self: asset.VectorFunctions.Conditional, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

7. ifelse(self: asset.VectorFunctions.Conditional, arg0: asset.VectorFunctions.VectorFunction, arg1: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

8. ifelse(self: asset.VectorFunctions.Conditional, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.ConstantScalar

Bases: pybind11_object

IRows(self: asset.VectorFunctions.ConstantScalar) → int

ORows(self: asset.VectorFunctions.ConstantScalar) → int

__call__(self: asset.VectorFunctions.ConstantScalar, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, 1]]

__init__(self: asset.VectorFunctions.ConstantScalar, arg0: int, arg1: numpy.ndarray[numpy.float64[1, 1]]) → None

__module__ = 'asset.VectorFunctions'

adjointgradient(self: asset.VectorFunctions.ConstantScalar, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.ConstantScalar, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → numpy.ndarray[numpy.float64[m, n]]

compute(self: asset.VectorFunctions.ConstantScalar, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, 1]]

compute_jacobian(self: asset.VectorFunctions.ConstantScalar, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[1, 1]], numpy.ndarray[numpy.float64[1, n]]]

computeall(self: asset.VectorFunctions.ConstantScalar, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → tuple[numpy.ndarray[numpy.float64[1, 1]], numpy.ndarray[numpy.float64[1, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

input_domain(self: asset.VectorFunctions.ConstantScalar) → numpy.ndarray[numpy.int32[2, n]]

is_linear(self: asset.VectorFunctions.ConstantScalar) → bool

jacobian(self: asset.VectorFunctions.ConstantScalar, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, n]]

name(self: asset.VectorFunctions.ConstantScalar) → str

rpt(self: asset.VectorFunctions.ConstantScalar, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

sf(self: asset.VectorFunctions.ConstantScalar) → asset.VectorFunctions.ScalarFunction

vf(self: asset.VectorFunctions.ConstantScalar) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.ConstantVector

Bases: pybind11_object

IRows(self: asset.VectorFunctions.ConstantVector) → int

ORows(self: asset.VectorFunctions.ConstantVector) → int

__call__(self: asset.VectorFunctions.ConstantVector, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

__init__(self: asset.VectorFunctions.ConstantVector, arg0: int, arg1: numpy.ndarray[numpy.float64[m, 1]]) → None

__module__ = 'asset.VectorFunctions'

adjointgradient(self: asset.VectorFunctions.ConstantVector, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.ConstantVector, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

compute(self: asset.VectorFunctions.ConstantVector, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

compute_jacobian(self: asset.VectorFunctions.ConstantVector, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

computeall(self: asset.VectorFunctions.ConstantVector, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

input_domain(self: asset.VectorFunctions.ConstantVector) → numpy.ndarray[numpy.int32[2, n]]

is_linear(self: asset.VectorFunctions.ConstantVector) → bool

jacobian(self: asset.VectorFunctions.ConstantVector, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

name(self: asset.VectorFunctions.ConstantVector) → str

rpt(self: asset.VectorFunctions.ConstantVector, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

vf(self: asset.VectorFunctions.ConstantVector) → asset.VectorFunctions.VectorFunction

asset.VectorFunctions.DynamicStackTest(arg0: list[asset.VectorFunctions.VectorFunction]) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.Element

Bases: pybind11_object

IRows(self: asset.VectorFunctions.Element) → int

ORows(self: asset.VectorFunctions.Element) → int

__abs__(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

__add__(*args, **kwargs)

Overloaded function.

1. __add__(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

2. __add__(self: asset.VectorFunctions.Element, arg0: float) -> asset.VectorFunctions.ScalarFunction

3. __add__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

4. __add__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

__array_ufunc__ = None

__call__(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, 1]]

__ge__(*args, **kwargs)

Overloaded function.

1. __ge__(self: asset.VectorFunctions.Element, arg0: float) -> ASSET::GenericConditional<-1>

2. __ge__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> ASSET::GenericConditional<-1>

3. __ge__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.ScalarFunction) -> ASSET::GenericConditional<-1>

__getitem__(*args, **kwargs)

Overloaded function.

1. __getitem__(self: asset.VectorFunctions.Element, arg0: int) -> asset.VectorFunctions.Element

2. __getitem__(self: asset.VectorFunctions.Element, arg0: slice) -> asset.VectorFunctions.Segment

__gt__(*args, **kwargs)

Overloaded function.

1. __gt__(self: asset.VectorFunctions.Element, arg0: float) -> ASSET::GenericConditional<-1>

2. __gt__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> ASSET::GenericConditional<-1>

3. __gt__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.ScalarFunction) -> ASSET::GenericConditional<-1>

__init__(self: asset.VectorFunctions.Element, arg0: int, arg1: int, arg2: int) → None

__le__(*args, **kwargs)

Overloaded function.

1. __le__(self: asset.VectorFunctions.Element, arg0: float) -> ASSET::GenericConditional<-1>

2. __le__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> ASSET::GenericConditional<-1>

3. __le__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.ScalarFunction) -> ASSET::GenericConditional<-1>

__lt__(*args, **kwargs)

Overloaded function.

1. __lt__(self: asset.VectorFunctions.Element, arg0: float) -> ASSET::GenericConditional<-1>

2. __lt__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> ASSET::GenericConditional<-1>

3. __lt__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.ScalarFunction) -> ASSET::GenericConditional<-1>

__module__ = 'asset.VectorFunctions'

__mul__(*args, **kwargs)

Overloaded function.

1. __mul__(self: asset.VectorFunctions.Element, arg0: float) -> asset.VectorFunctions.ScalarFunction

2. __mul__(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

3. __mul__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

4. __mul__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

__neg__(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

__pow__(*args, **kwargs)

Overloaded function.

1. __pow__(self: asset.VectorFunctions.Element, arg0: float) -> asset.VectorFunctions.ScalarFunction

2. __pow__(self: asset.VectorFunctions.Element, arg0: int) -> asset.VectorFunctions.ScalarFunction

__radd__(*args, **kwargs)

Overloaded function.

1. __radd__(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

2. __radd__(self: asset.VectorFunctions.Element, arg0: float) -> asset.VectorFunctions.ScalarFunction

__rgt__(self: asset.VectorFunctions.Element, arg0: float) → ASSET::GenericConditional<-1>

__rlt__(self: asset.VectorFunctions.Element, arg0: float) → ASSET::GenericConditional<-1>

__rmul__(*args, **kwargs)

Overloaded function.

1. __rmul__(self: asset.VectorFunctions.Element, arg0: float) -> asset.VectorFunctions.ScalarFunction

2. __rmul__(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

__rsub__(*args, **kwargs)

Overloaded function.

1. __rsub__(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

2. __rsub__(self: asset.VectorFunctions.Element, arg0: float) -> asset.VectorFunctions.ScalarFunction

__rtruediv__(self: asset.VectorFunctions.Element, arg0: float) → asset.VectorFunctions.ScalarFunction

__sub__(*args, **kwargs)

Overloaded function.

1. __sub__(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

2. __sub__(self: asset.VectorFunctions.Element, arg0: float) -> asset.VectorFunctions.ScalarFunction

3. __sub__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

4. __sub__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

__truediv__(*args, **kwargs)

Overloaded function.

1. __truediv__(self: asset.VectorFunctions.Element, arg0: float) -> asset.VectorFunctions.ScalarFunction

2. __truediv__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

3. __truediv__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

4. __truediv__(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

adjointgradient(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → numpy.ndarray[numpy.float64[m, n]]

apply(*args, **kwargs)

Overloaded function.

1. apply(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. apply(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

arccos(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

arccosh(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

arcsin(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

arcsinh(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

arctan(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

arctanh(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

coeff(self: asset.VectorFunctions.Element, arg0: int) → asset.VectorFunctions.Element

compute(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, 1]]

compute_jacobian(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[1, 1]], numpy.ndarray[numpy.float64[1, n]]]

computeall(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → tuple[numpy.ndarray[numpy.float64[1, 1]], numpy.ndarray[numpy.float64[1, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

cos(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

cosh(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

cwiseProduct(*args, **kwargs)

Overloaded function.

1. cwiseProduct(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

2. cwiseProduct(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

cwiseQuotient(*args, **kwargs)

Overloaded function.

1. cwiseQuotient(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

2. cwiseQuotient(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

dot(*args, **kwargs)

Overloaded function.

1. dot(self: asset.VectorFunctions.Element, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

2. dot(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

exp(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

head(self: asset.VectorFunctions.Element, arg0: int) → asset.VectorFunctions.Segment

input_domain(self: asset.VectorFunctions.Element) → numpy.ndarray[numpy.int32[2, n]]

is_linear(self: asset.VectorFunctions.Element) → bool

jacobian(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, n]]

log(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

name(self: asset.VectorFunctions.Element) → str

padded(self: asset.VectorFunctions.Element, arg0: int, arg1: int) → asset.VectorFunctions.VectorFunction

padded_lower(self: asset.VectorFunctions.Element, arg0: int) → asset.VectorFunctions.VectorFunction

padded_upper(self: asset.VectorFunctions.Element, arg0: int) → asset.VectorFunctions.VectorFunction

pow(self: asset.VectorFunctions.Element, arg0: float) → asset.VectorFunctions.ScalarFunction

rpt(self: asset.VectorFunctions.Element, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

segment(self: asset.VectorFunctions.Element, arg0: int, arg1: int) → asset.VectorFunctions.Segment

sf(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

sign(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

sin(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

sinh(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

sqrt(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

squared(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

tail(self: asset.VectorFunctions.Element, arg0: int) → asset.VectorFunctions.Segment

tan(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

tanh(self: asset.VectorFunctions.Element) → asset.VectorFunctions.ScalarFunction

tolist(*args, **kwargs)

Overloaded function.

1. tolist(self: asset.VectorFunctions.Element) -> list[asset.VectorFunctions.Element]

2. tolist(self: asset.VectorFunctions.Element, arg0: list[int]) -> list[asset.VectorFunctions.Element]

3. tolist(self: asset.VectorFunctions.Element, arg0: list[tuple[int, int]]) -> list[object]

vf(self: asset.VectorFunctions.Element) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.IOScaled

Bases: pybind11_object

IRows(self: asset.VectorFunctions.IOScaled) → int

ORows(self: asset.VectorFunctions.IOScaled) → int

__call__(self: asset.VectorFunctions.IOScaled, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

__init__(self: asset.VectorFunctions.IOScaled, arg0: asset.VectorFunctions.VectorFunction, arg1: numpy.ndarray[numpy.float64[m, 1]], arg2: numpy.ndarray[numpy.float64[m, 1]]) → None

__module__ = 'asset.VectorFunctions'

adjointgradient(self: asset.VectorFunctions.IOScaled, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.IOScaled, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

compute(self: asset.VectorFunctions.IOScaled, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

compute_jacobian(self: asset.VectorFunctions.IOScaled, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

computeall(self: asset.VectorFunctions.IOScaled, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

input_domain(self: asset.VectorFunctions.IOScaled) → numpy.ndarray[numpy.int32[2, n]]

is_linear(self: asset.VectorFunctions.IOScaled) → bool

jacobian(self: asset.VectorFunctions.IOScaled, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

name(self: asset.VectorFunctions.IOScaled) → str

rpt(self: asset.VectorFunctions.IOScaled, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

vf(self: asset.VectorFunctions.IOScaled) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.InterpTable1D

Bases: pybind11_object

property ThrowOutOfBounds

property WarnOutOfBounds

__call__(*args, **kwargs)

Overloaded function.

1. __call__(self: asset.VectorFunctions.InterpTable1D, arg0: float) -> numpy.ndarray[numpy.float64[m, 1]]

2. __call__(self: asset.VectorFunctions.InterpTable1D, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> numpy.ndarray[numpy.float64[m, n]]

3. __call__(self: asset.VectorFunctions.InterpTable1D, arg0: asset.VectorFunctions.ScalarFunction) -> object

4. __call__(self: asset.VectorFunctions.InterpTable1D, arg0: asset.VectorFunctions.Element) -> object

__init__(*args, **kwargs)

Overloaded function.

1. __init__(self: asset.VectorFunctions.InterpTable1D, ts: numpy.ndarray[numpy.float64[m, 1]], Vs: numpy.ndarray[numpy.float64[m, 1]], axis: int = 0, kind: str = ‘cubic’) -> None

2. __init__(self: asset.VectorFunctions.InterpTable1D, ts: numpy.ndarray[numpy.float64[m, 1]], Vs: numpy.ndarray[numpy.float64[m, n]], axis: int = 0, kind: str = ‘cubic’) -> None

3. __init__(self: asset.VectorFunctions.InterpTable1D, Vts: list[numpy.ndarray[numpy.float64[m, 1]]], tvar: int = -1, kind: str = ‘cubic’) -> None

__module__ = 'asset.VectorFunctions'

interp(*args, **kwargs)

Overloaded function.

1. interp(self: asset.VectorFunctions.InterpTable1D, arg0: float) -> numpy.ndarray[numpy.float64[m, 1]]

2. interp(self: asset.VectorFunctions.InterpTable1D, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> numpy.ndarray[numpy.float64[m, n]]

interp_deriv1(self: asset.VectorFunctions.InterpTable1D, arg0: float) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, 1]]]

interp_deriv2(self: asset.VectorFunctions.InterpTable1D, arg0: float) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, 1]]]

sf(self: asset.VectorFunctions.InterpTable1D) → asset.VectorFunctions.ScalarFunction

vf(self: asset.VectorFunctions.InterpTable1D) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.InterpTable2D

Bases: pybind11_object

property ThrowOutOfBounds

property WarnOutOfBounds

__call__(*args, **kwargs)

Overloaded function.

1. __call__(self: asset.VectorFunctions.InterpTable2D, arg0: float, arg1: float) -> float

2. __call__(self: asset.VectorFunctions.InterpTable2D, arg0: numpy.ndarray[numpy.float64[m, n]], arg1: numpy.ndarray[numpy.float64[m, n]]) -> numpy.ndarray[numpy.float64[m, n]]

3. __call__(self: asset.VectorFunctions.InterpTable2D, arg0: asset.VectorFunctions.ScalarFunction, arg1: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

4. __call__(self: asset.VectorFunctions.InterpTable2D, arg0: asset.VectorFunctions.Element, arg1: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

5. __call__(self: asset.VectorFunctions.InterpTable2D, arg0: asset.VectorFunctions.Segment2) -> asset.VectorFunctions.ScalarFunction

6. __call__(self: asset.VectorFunctions.InterpTable2D, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

__init__(self: asset.VectorFunctions.InterpTable2D, xs: numpy.ndarray[numpy.float64[m, 1]], ys: numpy.ndarray[numpy.float64[m, 1]], Z: numpy.ndarray[numpy.float64[m, n]], kind: str = 'cubic') → None

__module__ = 'asset.VectorFunctions'

find_elem(self: asset.VectorFunctions.InterpTable2D, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: float) → int

interp(*args, **kwargs)

Overloaded function.

1. interp(self: asset.VectorFunctions.InterpTable2D, arg0: float, arg1: float) -> float

2. interp(self: asset.VectorFunctions.InterpTable2D, arg0: numpy.ndarray[numpy.float64[m, n]], arg1: numpy.ndarray[numpy.float64[m, n]]) -> numpy.ndarray[numpy.float64[m, n]]

interp_deriv1(self: asset.VectorFunctions.InterpTable2D, arg0: float, arg1: float) → tuple[float, numpy.ndarray[numpy.float64[2, 1]]]

interp_deriv2(self: asset.VectorFunctions.InterpTable2D, arg0: float, arg1: float) → tuple[float, numpy.ndarray[numpy.float64[2, 1]], numpy.ndarray[numpy.float64[2, 2]]]

sf(self: asset.VectorFunctions.InterpTable2D) → asset.VectorFunctions.ScalarFunction

vf(self: asset.VectorFunctions.InterpTable2D) → asset.VectorFunctions.VectorFunction

asset.VectorFunctions.InterpTable2DSpeedTest(arg0: asset.VectorFunctions.ScalarFunction, arg1: float, arg2: float, arg3: float, arg4: float, arg5: int, arg6: bool) → float

class asset.VectorFunctions.InterpTable3D

Bases: pybind11_object

property ThrowOutOfBounds

property WarnOutOfBounds

__call__(*args, **kwargs)

Overloaded function.

1. __call__(self: asset.VectorFunctions.InterpTable3D, arg0: float, arg1: float, arg2: float) -> float

2. __call__(self: asset.VectorFunctions.InterpTable3D, arg0: asset.VectorFunctions.ScalarFunction, arg1: asset.VectorFunctions.ScalarFunction, arg2: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

3. __call__(self: asset.VectorFunctions.InterpTable3D, arg0: asset.VectorFunctions.Element, arg1: asset.VectorFunctions.Element, arg2: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

4. __call__(self: asset.VectorFunctions.InterpTable3D, arg0: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.ScalarFunction

5. __call__(self: asset.VectorFunctions.InterpTable3D, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

__init__(self: asset.VectorFunctions.InterpTable3D, xs: numpy.ndarray[numpy.float64[m, 1]], ys: numpy.ndarray[numpy.float64[m, 1]], zs: numpy.ndarray[numpy.float64[m, 1]], fs: numpy.ndarray[numpy.float64[?, ?, ?]], kind: str = 'cubic', cache: bool = False) → None

__module__ = 'asset.VectorFunctions'

interp(self: asset.VectorFunctions.InterpTable3D, arg0: float, arg1: float, arg2: float) → float

interp_deriv1(self: asset.VectorFunctions.InterpTable3D, arg0: float, arg1: float, arg2: float) → tuple[float, numpy.ndarray[numpy.float64[3, 1]]]

interp_deriv2(self: asset.VectorFunctions.InterpTable3D, arg0: float, arg1: float, arg2: float) → tuple[float, numpy.ndarray[numpy.float64[3, 1]], numpy.ndarray[numpy.float64[3, 3]]]

sf(self: asset.VectorFunctions.InterpTable3D) → asset.VectorFunctions.ScalarFunction

vf(self: asset.VectorFunctions.InterpTable3D) → asset.VectorFunctions.VectorFunction

asset.VectorFunctions.InterpTable3DSpeedTest(arg0: asset.VectorFunctions.ScalarFunction, arg1: float, arg2: float, arg3: float, arg4: float, arg5: float, arg6: float, arg7: int, arg8: bool) → float

class asset.VectorFunctions.InterpTable4D

Bases: pybind11_object

property ThrowOutOfBounds

property WarnOutOfBounds

__call__(*args, **kwargs)

Overloaded function.

1. __call__(self: asset.VectorFunctions.InterpTable4D, arg0: float, arg1: float, arg2: float, arg3: float) -> float

2. __call__(self: asset.VectorFunctions.InterpTable4D, arg0: asset.VectorFunctions.ScalarFunction, arg1: asset.VectorFunctions.ScalarFunction, arg2: asset.VectorFunctions.ScalarFunction, arg3: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

3. __call__(self: asset.VectorFunctions.InterpTable4D, arg0: asset.VectorFunctions.Element, arg1: asset.VectorFunctions.Element, arg2: asset.VectorFunctions.Element, arg3: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

4. __call__(self: asset.VectorFunctions.InterpTable4D, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.ScalarFunction

5. __call__(self: asset.VectorFunctions.InterpTable4D, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

__init__(self: asset.VectorFunctions.InterpTable4D, xs: numpy.ndarray[numpy.float64[m, 1]], ys: numpy.ndarray[numpy.float64[m, 1]], zs: numpy.ndarray[numpy.float64[m, 1]], ws: numpy.ndarray[numpy.float64[m, 1]], fs: numpy.ndarray[numpy.float64[?, ?, ?, ?]], kind: str = 'cubic', cache: bool = False) → None

__module__ = 'asset.VectorFunctions'

interp(self: asset.VectorFunctions.InterpTable4D, arg0: float, arg1: float, arg2: float, arg3: float) → float

interp_deriv1(self: asset.VectorFunctions.InterpTable4D, arg0: float, arg1: float, arg2: float, arg3: float) → tuple[float, numpy.ndarray[numpy.float64[4, 1]]]

interp_deriv2(self: asset.VectorFunctions.InterpTable4D, arg0: float, arg1: float, arg2: float, arg3: float) → tuple[float, numpy.ndarray[numpy.float64[4, 1]], numpy.ndarray[numpy.float64[4, 4]]]

sf(self: asset.VectorFunctions.InterpTable4D) → asset.VectorFunctions.ScalarFunction

vf(self: asset.VectorFunctions.InterpTable4D) → asset.VectorFunctions.VectorFunction

asset.VectorFunctions.InterpTable4DSpeedTest(arg0: asset.VectorFunctions.ScalarFunction, arg1: float, arg2: float, arg3: float, arg4: float, arg5: float, arg6: float, arg7: float, arg8: float, arg9: int, arg10: bool) → float

class asset.VectorFunctions.PyScalarFunction

Bases: pybind11_object

IRows(self: asset.VectorFunctions.PyScalarFunction) → int

ORows(self: asset.VectorFunctions.PyScalarFunction) → int

__call__(self: asset.VectorFunctions.PyScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, 1]]

__init__(self: asset.VectorFunctions.PyScalarFunction, IRows: int, Func: Callable[[numpy.ndarray[numpy.float64[m, 1]], detail::args_proxy], numpy.ndarray[numpy.float64[1, 1]]], Jstepsize: float = 1e-06, Hstepsize: float = 0.0001, args: tuple = ()) → None

__module__ = 'asset.VectorFunctions'

adjointgradient(self: asset.VectorFunctions.PyScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.PyScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → numpy.ndarray[numpy.float64[m, n]]

compute(self: asset.VectorFunctions.PyScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, 1]]

compute_jacobian(self: asset.VectorFunctions.PyScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[1, 1]], numpy.ndarray[numpy.float64[1, n]]]

computeall(self: asset.VectorFunctions.PyScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → tuple[numpy.ndarray[numpy.float64[1, 1]], numpy.ndarray[numpy.float64[1, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

input_domain(self: asset.VectorFunctions.PyScalarFunction) → numpy.ndarray[numpy.int32[2, n]]

is_linear(self: asset.VectorFunctions.PyScalarFunction) → bool

jacobian(self: asset.VectorFunctions.PyScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, n]]

name(self: asset.VectorFunctions.PyScalarFunction) → str

rpt(self: asset.VectorFunctions.PyScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

sf(self: asset.VectorFunctions.PyScalarFunction) → asset.VectorFunctions.ScalarFunction

vf(self: asset.VectorFunctions.PyScalarFunction) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.PyVectorFunction

Bases: pybind11_object

IRows(self: asset.VectorFunctions.PyVectorFunction) → int

ORows(self: asset.VectorFunctions.PyVectorFunction) → int

__call__(self: asset.VectorFunctions.PyVectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

__init__(self: asset.VectorFunctions.PyVectorFunction, IRows: int, ORows: int, Func: Callable[[numpy.ndarray[numpy.float64[m, 1]], detail::args_proxy], numpy.ndarray[numpy.float64[m, 1]]], Jstepsize: float = 1e-06, Hstepsize: float = 0.0001, args: tuple = ()) → None

__module__ = 'asset.VectorFunctions'

adjointgradient(self: asset.VectorFunctions.PyVectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.PyVectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

compute(self: asset.VectorFunctions.PyVectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

compute_jacobian(self: asset.VectorFunctions.PyVectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

computeall(self: asset.VectorFunctions.PyVectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

input_domain(self: asset.VectorFunctions.PyVectorFunction) → numpy.ndarray[numpy.int32[2, n]]

is_linear(self: asset.VectorFunctions.PyVectorFunction) → bool

jacobian(self: asset.VectorFunctions.PyVectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

name(self: asset.VectorFunctions.PyVectorFunction) → str

rpt(self: asset.VectorFunctions.PyVectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

vf(self: asset.VectorFunctions.PyVectorFunction) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.RowMatrix

Bases: pybind11_object

__add__(*args, **kwargs)

Overloaded function.

1. __add__(self: asset.VectorFunctions.RowMatrix, arg0: asset.VectorFunctions.RowMatrix) -> asset.VectorFunctions.RowMatrix

2. __add__(self: asset.VectorFunctions.RowMatrix, arg0: numpy.ndarray[numpy.float64[m, n]]) -> asset.VectorFunctions.RowMatrix

__array_ufunc__ = None

__init__(*args, **kwargs)

Overloaded function.

1. __init__(self: asset.VectorFunctions.RowMatrix, arg0: asset.VectorFunctions.VectorFunction, arg1: int, arg2: int) -> None

2. __init__(self: asset.VectorFunctions.RowMatrix, arg0: list[asset.VectorFunctions.VectorFunction]) -> None

__module__ = 'asset.VectorFunctions'

__mul__(*args, **kwargs)

Overloaded function.

1. __mul__(self: asset.VectorFunctions.RowMatrix, arg0: asset.VectorFunctions.ColMatrix) -> asset.VectorFunctions.ColMatrix

2. __mul__(self: asset.VectorFunctions.RowMatrix, arg0: asset.VectorFunctions.RowMatrix) -> asset.VectorFunctions.ColMatrix

3. __mul__(self: asset.VectorFunctions.RowMatrix, arg0: float) -> asset.VectorFunctions.RowMatrix

4. __mul__(self: asset.VectorFunctions.RowMatrix, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__radd__(self: asset.VectorFunctions.RowMatrix, arg0: numpy.ndarray[numpy.float64[m, n]]) → asset.VectorFunctions.RowMatrix

__rmul__(self: asset.VectorFunctions.RowMatrix, arg0: float) → asset.VectorFunctions.RowMatrix

inverse(self: asset.VectorFunctions.RowMatrix) → asset.VectorFunctions.RowMatrix

transpose(self: asset.VectorFunctions.RowMatrix) → asset.VectorFunctions.ColMatrix

vf(self: asset.VectorFunctions.RowMatrix) → asset.VectorFunctions.VectorFunction

asset.VectorFunctions.ScalarDynamicStackTest(arg0: list[asset.VectorFunctions.ScalarFunction]) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.ScalarFunction

Bases: pybind11_object

IRows(self: asset.VectorFunctions.ScalarFunction) → int

ORows(self: asset.VectorFunctions.ScalarFunction) → int

SpeedTest(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

SuperTest(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

__abs__(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

__add__(*args, **kwargs)

Overloaded function.

1. __add__(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

2. __add__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

3. __add__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

__array_ufunc__ = None

__call__(*args, **kwargs)

Overloaded function.

1. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> numpy.ndarray[numpy.float64[1, 1]]

2. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

3. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.ScalarFunction

4. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, -1, -1>) -> asset.VectorFunctions.ScalarFunction

5. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, 2, -1>) -> asset.VectorFunctions.ScalarFunction

6. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, 3, -1>) -> asset.VectorFunctions.ScalarFunction

7. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: list[asset.VectorFunctions.ScalarFunction]) -> asset.VectorFunctions.ScalarFunction

8. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: list[asset.VectorFunctions.VectorFunction]) -> asset.VectorFunctions.ScalarFunction

9. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.VectorFunction, *args) -> asset.VectorFunctions.ScalarFunction

10. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: float, *args) -> asset.VectorFunctions.ScalarFunction

11. __call__(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], *args) -> asset.VectorFunctions.ScalarFunction

__ge__(*args, **kwargs)

Overloaded function.

1. __ge__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> ASSET::GenericConditional<-1>

2. __ge__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> ASSET::GenericConditional<-1>

__getitem__(*args, **kwargs)

Overloaded function.

1. __getitem__(self: asset.VectorFunctions.ScalarFunction, arg0: int) -> asset.VectorFunctions.ScalarFunction

2. __getitem__(self: asset.VectorFunctions.ScalarFunction, arg0: slice) -> asset.VectorFunctions.VectorFunction

__gt__(*args, **kwargs)

Overloaded function.

1. __gt__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> ASSET::GenericConditional<-1>

2. __gt__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> ASSET::GenericConditional<-1>

__init__(*args, **kwargs)

Overloaded function.

1. __init__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> None

2. __init__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.Element) -> None

3. __init__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.PyScalarFunction) -> None

4. __init__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ConstantScalar) -> None

5. __init__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.OptimalControl.InterpFunction_1) -> None

__le__(*args, **kwargs)

Overloaded function.

1. __le__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> ASSET::GenericConditional<-1>

2. __le__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> ASSET::GenericConditional<-1>

__lt__(*args, **kwargs)

Overloaded function.

1. __lt__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> ASSET::GenericConditional<-1>

2. __lt__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> ASSET::GenericConditional<-1>

__module__ = 'asset.VectorFunctions'

__mul__(*args, **kwargs)

Overloaded function.

1. __mul__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

2. __mul__(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

3. __mul__(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.ScalarFunction

4. __mul__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

__neg__(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

__pow__(*args, **kwargs)

Overloaded function.

1. __pow__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

2. __pow__(self: asset.VectorFunctions.ScalarFunction, arg0: int) -> asset.VectorFunctions.ScalarFunction

__radd__(*args, **kwargs)

Overloaded function.

1. __radd__(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

2. __radd__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

__rgt__(self: asset.VectorFunctions.ScalarFunction, arg0: float) → ASSET::GenericConditional<-1>

__rlt__(self: asset.VectorFunctions.ScalarFunction, arg0: float) → ASSET::GenericConditional<-1>

__rmul__(*args, **kwargs)

Overloaded function.

1. __rmul__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

2. __rmul__(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

__rsub__(*args, **kwargs)

Overloaded function.

1. __rsub__(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

2. __rsub__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

__rtruediv__(self: asset.VectorFunctions.ScalarFunction, arg0: float) → asset.VectorFunctions.ScalarFunction

__sub__(*args, **kwargs)

Overloaded function.

1. __sub__(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

2. __sub__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

3. __sub__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

__truediv__(*args, **kwargs)

Overloaded function.

1. __truediv__(self: asset.VectorFunctions.ScalarFunction, arg0: float) -> asset.VectorFunctions.ScalarFunction

2. __truediv__(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.ScalarFunction

3. __truediv__(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.ScalarFunction

4. __truediv__(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

adjointgradient(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → numpy.ndarray[numpy.float64[m, n]]

apply(*args, **kwargs)

Overloaded function.

1. apply(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. apply(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

arccos(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

arccosh(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

arcsin(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

arcsinh(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

arctan(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

arctanh(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

coeff(self: asset.VectorFunctions.ScalarFunction, arg0: int) → asset.VectorFunctions.ScalarFunction

compute(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, 1]]

compute_jacobian(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[1, 1]], numpy.ndarray[numpy.float64[1, n]]]

computeall(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[1, 1]]) → tuple[numpy.ndarray[numpy.float64[1, 1]], numpy.ndarray[numpy.float64[1, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

cos(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

cosh(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

cwiseProduct(*args, **kwargs)

Overloaded function.

1. cwiseProduct(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

2. cwiseProduct(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

cwiseQuotient(*args, **kwargs)

Overloaded function.

1. cwiseQuotient(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

2. cwiseQuotient(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

dot(*args, **kwargs)

Overloaded function.

1. dot(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

2. dot(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[1, 1]]) -> asset.VectorFunctions.ScalarFunction

eval(*args, **kwargs)

Overloaded function.

1. eval(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.ScalarFunction

2. eval(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, -1, -1>) -> asset.VectorFunctions.ScalarFunction

3. eval(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, 2, -1>) -> asset.VectorFunctions.ScalarFunction

4. eval(self: asset.VectorFunctions.ScalarFunction, arg0: ASSET::Segment<-1, 3, -1>) -> asset.VectorFunctions.ScalarFunction

5. eval(self: asset.VectorFunctions.ScalarFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

6. eval(self: asset.VectorFunctions.ScalarFunction, arg0: int, arg1: numpy.ndarray[numpy.int32[m, 1]]) -> asset.VectorFunctions.ScalarFunction

exp(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

head(self: asset.VectorFunctions.ScalarFunction, arg0: int) → asset.VectorFunctions.VectorFunction

input_domain(self: asset.VectorFunctions.ScalarFunction) → numpy.ndarray[numpy.int32[2, n]]

is_linear(self: asset.VectorFunctions.ScalarFunction) → bool

jacobian(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[1, n]]

log(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

name(self: asset.VectorFunctions.ScalarFunction) → str

padded(self: asset.VectorFunctions.ScalarFunction, arg0: int, arg1: int) → asset.VectorFunctions.VectorFunction

padded_lower(self: asset.VectorFunctions.ScalarFunction, arg0: int) → asset.VectorFunctions.VectorFunction

padded_upper(self: asset.VectorFunctions.ScalarFunction, arg0: int) → asset.VectorFunctions.VectorFunction

pow(self: asset.VectorFunctions.ScalarFunction, arg0: float) → asset.VectorFunctions.ScalarFunction

rpt(self: asset.VectorFunctions.ScalarFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

segment(self: asset.VectorFunctions.ScalarFunction, arg0: int, arg1: int) → asset.VectorFunctions.VectorFunction

sf(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

sign(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

sin(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

sinh(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

sqrt(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

squared(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

tail(self: asset.VectorFunctions.ScalarFunction, arg0: int) → asset.VectorFunctions.VectorFunction

tan(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

tanh(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.ScalarFunction

vf(self: asset.VectorFunctions.ScalarFunction) → asset.VectorFunctions.VectorFunction

asset.VectorFunctions.ScalarRootFinder(*args, **kwargs)

Overloaded function.

1. ScalarRootFinder(arg0: asset.VectorFunctions.ScalarFunction, arg1: asset.VectorFunctions.ScalarFunction, arg2: int, arg3: float) -> asset.VectorFunctions.ScalarFunction

2. ScalarRootFinder(arg0: asset.VectorFunctions.ScalarFunction, arg1: int, arg2: float) -> asset.VectorFunctions.ScalarFunction

class asset.VectorFunctions.Segment

Bases: pybind11_object

IRows(self: asset.VectorFunctions.Segment) → int

ORows(self: asset.VectorFunctions.Segment) → int

__add__(*args, **kwargs)

Overloaded function.

1. __add__(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. __add__(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

3. __add__(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__array_ufunc__ = None

__call__(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

__getitem__(*args, **kwargs)

Overloaded function.

1. __getitem__(self: asset.VectorFunctions.Segment, arg0: int) -> ASSET::Segment<-1, 1, -1>

2. __getitem__(self: asset.VectorFunctions.Segment, arg0: slice) -> asset.VectorFunctions.Segment

__init__(self: asset.VectorFunctions.Segment, arg0: int, arg1: int, arg2: int) → None

__module__ = 'asset.VectorFunctions'

__mul__(*args, **kwargs)

Overloaded function.

1. __mul__(self: asset.VectorFunctions.Segment, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __mul__(self: asset.VectorFunctions.Segment, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

3. __mul__(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__neg__(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.VectorFunction

__radd__(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) → asset.VectorFunctions.VectorFunction

__rmul__(*args, **kwargs)

Overloaded function.

1. __rmul__(self: asset.VectorFunctions.Segment, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __rmul__(self: asset.VectorFunctions.Segment, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

3. __rmul__(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__rsub__(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) → asset.VectorFunctions.VectorFunction

__sub__(*args, **kwargs)

Overloaded function.

1. __sub__(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. __sub__(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

3. __sub__(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__truediv__(*args, **kwargs)

Overloaded function.

1. __truediv__(self: asset.VectorFunctions.Segment, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __truediv__(self: asset.VectorFunctions.Segment, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

3. __truediv__(self: asset.VectorFunctions.Segment, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

4. __truediv__(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

adjointgradient(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

apply(*args, **kwargs)

Overloaded function.

1. apply(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. apply(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

coeff(self: asset.VectorFunctions.Segment, arg0: int) → ASSET::Segment<-1, 1, -1>

compute(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

compute_jacobian(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

computeall(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

cross(*args, **kwargs)

Overloaded function.

1. cross(self: asset.VectorFunctions.Segment, arg0: ASSET::Segment<-1, 3, -1>) -> asset.VectorFunctions.VectorFunction

2. cross(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cross(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

4. cross(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

cubed_norm(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.ScalarFunction

cwiseProduct(*args, **kwargs)

Overloaded function.

1. cwiseProduct(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. cwiseProduct(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

3. cwiseProduct(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

cwiseQuotient(*args, **kwargs)

Overloaded function.

1. cwiseQuotient(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. cwiseQuotient(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

3. cwiseQuotient(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

dot(*args, **kwargs)

Overloaded function.

1. dot(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

2. dot(self: asset.VectorFunctions.Segment, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.ScalarFunction

3. dot(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.ScalarFunction

head(self: asset.VectorFunctions.Segment, arg0: int) → asset.VectorFunctions.Segment

head2(self: asset.VectorFunctions.Segment) → ASSET::Segment<-1, 2, -1>

head3(self: asset.VectorFunctions.Segment) → ASSET::Segment<-1, 3, -1>

head_2(self: asset.VectorFunctions.Segment) → ASSET::Segment<-1, 2, -1>

head_3(self: asset.VectorFunctions.Segment) → ASSET::Segment<-1, 3, -1>

input_domain(self: asset.VectorFunctions.Segment) → numpy.ndarray[numpy.int32[2, n]]

inverse_cubed_norm(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.ScalarFunction

inverse_four_norm(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.ScalarFunction

inverse_norm(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.ScalarFunction

inverse_squared_norm(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.ScalarFunction

is_linear(self: asset.VectorFunctions.Segment) → bool

jacobian(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

name(self: asset.VectorFunctions.Segment) → str

norm(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.ScalarFunction

normalized(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.VectorFunction

normalized_power2(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.VectorFunction

normalized_power3(*args, **kwargs)

Overloaded function.

1. normalized_power3(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. normalized_power3(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: float) -> asset.VectorFunctions.VectorFunction

3. normalized_power3(self: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

normalized_power4(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.VectorFunction

normalized_power5(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.VectorFunction

padded(self: asset.VectorFunctions.Segment, arg0: int, arg1: int) → asset.VectorFunctions.VectorFunction

padded_lower(self: asset.VectorFunctions.Segment, arg0: int) → asset.VectorFunctions.VectorFunction

padded_upper(self: asset.VectorFunctions.Segment, arg0: int) → asset.VectorFunctions.VectorFunction

rpt(self: asset.VectorFunctions.Segment, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

segment(self: asset.VectorFunctions.Segment, arg0: int, arg1: int) → asset.VectorFunctions.Segment

segment2(self: asset.VectorFunctions.Segment, arg0: int) → ASSET::Segment<-1, 2, -1>

segment3(self: asset.VectorFunctions.Segment, arg0: int) → ASSET::Segment<-1, 3, -1>

segment_2(self: asset.VectorFunctions.Segment, arg0: int) → ASSET::Segment<-1, 2, -1>

segment_3(self: asset.VectorFunctions.Segment, arg0: int) → ASSET::Segment<-1, 3, -1>

squared_norm(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.ScalarFunction

sum(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.ScalarFunction

tail(self: asset.VectorFunctions.Segment, arg0: int) → asset.VectorFunctions.Segment

tail2(self: asset.VectorFunctions.Segment) → ASSET::Segment<-1, 2, -1>

tail3(self: asset.VectorFunctions.Segment) → ASSET::Segment<-1, 3, -1>

tail_2(self: asset.VectorFunctions.Segment) → ASSET::Segment<-1, 2, -1>

tail_3(self: asset.VectorFunctions.Segment) → ASSET::Segment<-1, 3, -1>

tolist(*args, **kwargs)

Overloaded function.

1. tolist(self: asset.VectorFunctions.Segment) -> list[ASSET::Segment<-1, 1, -1>]

2. tolist(self: asset.VectorFunctions.Segment, arg0: list[int]) -> list[ASSET::Segment<-1, 1, -1>]

3. tolist(self: asset.VectorFunctions.Segment, arg0: list[tuple[int, int]]) -> list[object]

vf(self: asset.VectorFunctions.Segment) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.Segment2

Bases: pybind11_object

IRows(self: asset.VectorFunctions.Segment2) → int

ORows(self: asset.VectorFunctions.Segment2) → int

__add__(*args, **kwargs)

Overloaded function.

1. __add__(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[2, 1]]) -> asset.VectorFunctions.VectorFunction

2. __add__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Segment2) -> asset.VectorFunctions.VectorFunction

3. __add__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__array_ufunc__ = None

__call__(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[2, 1]]

__getitem__(*args, **kwargs)

Overloaded function.

1. __getitem__(self: asset.VectorFunctions.Segment2, arg0: int) -> asset.VectorFunctions.Element

2. __getitem__(self: asset.VectorFunctions.Segment2, arg0: slice) -> asset.VectorFunctions.Segment

__init__(self: asset.VectorFunctions.Segment2, arg0: int, arg1: int, arg2: int) → None

__module__ = 'asset.VectorFunctions'

__mul__(*args, **kwargs)

Overloaded function.

1. __mul__(self: asset.VectorFunctions.Segment2, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __mul__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

3. __mul__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__neg__(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.VectorFunction

__radd__(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[2, 1]]) → asset.VectorFunctions.VectorFunction

__rmul__(*args, **kwargs)

Overloaded function.

1. __rmul__(self: asset.VectorFunctions.Segment2, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __rmul__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

3. __rmul__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__rsub__(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[2, 1]]) → asset.VectorFunctions.VectorFunction

__sub__(*args, **kwargs)

Overloaded function.

1. __sub__(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[2, 1]]) -> asset.VectorFunctions.VectorFunction

2. __sub__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Segment2) -> asset.VectorFunctions.VectorFunction

3. __sub__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__truediv__(*args, **kwargs)

Overloaded function.

1. __truediv__(self: asset.VectorFunctions.Segment2, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __truediv__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

3. __truediv__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

4. __truediv__(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

adjointgradient(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[2, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[2, 1]]) → numpy.ndarray[numpy.float64[m, n]]

apply(*args, **kwargs)

Overloaded function.

1. apply(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. apply(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

coeff(self: asset.VectorFunctions.Segment2, arg0: int) → asset.VectorFunctions.Element

compute(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[2, 1]]

compute_jacobian(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[2, 1]], numpy.ndarray[numpy.float64[2, n]]]

computeall(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[2, 1]]) → tuple[numpy.ndarray[numpy.float64[2, 1]], numpy.ndarray[numpy.float64[2, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

cubed_norm(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.ScalarFunction

cwiseProduct(*args, **kwargs)

Overloaded function.

1. cwiseProduct(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

2. cwiseProduct(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cwiseProduct(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Segment2) -> asset.VectorFunctions.VectorFunction

4. cwiseProduct(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[2, 1]]) -> asset.VectorFunctions.VectorFunction

cwiseQuotient(*args, **kwargs)

Overloaded function.

1. cwiseQuotient(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

2. cwiseQuotient(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cwiseQuotient(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Segment2) -> asset.VectorFunctions.VectorFunction

4. cwiseQuotient(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[2, 1]]) -> asset.VectorFunctions.VectorFunction

dot(*args, **kwargs)

Overloaded function.

1. dot(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.ScalarFunction

2. dot(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

3. dot(self: asset.VectorFunctions.Segment2, arg0: asset.VectorFunctions.Segment2) -> asset.VectorFunctions.ScalarFunction

4. dot(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[2, 1]]) -> asset.VectorFunctions.ScalarFunction

head(self: asset.VectorFunctions.Segment2, arg0: int) → asset.VectorFunctions.Segment

input_domain(self: asset.VectorFunctions.Segment2) → numpy.ndarray[numpy.int32[2, n]]

inverse_cubed_norm(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.ScalarFunction

inverse_four_norm(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.ScalarFunction

inverse_norm(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.ScalarFunction

inverse_squared_norm(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.ScalarFunction

is_linear(self: asset.VectorFunctions.Segment2) → bool

jacobian(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[2, n]]

name(self: asset.VectorFunctions.Segment2) → str

norm(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.ScalarFunction

normalized(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.VectorFunction

normalized_power2(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.VectorFunction

normalized_power3(*args, **kwargs)

Overloaded function.

1. normalized_power3(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[2, 1]]) -> asset.VectorFunctions.VectorFunction

2. normalized_power3(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[2, 1]], arg1: float) -> asset.VectorFunctions.VectorFunction

3. normalized_power3(self: asset.VectorFunctions.Segment2) -> asset.VectorFunctions.VectorFunction

normalized_power4(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.VectorFunction

normalized_power5(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.VectorFunction

padded(self: asset.VectorFunctions.Segment2, arg0: int, arg1: int) → asset.VectorFunctions.VectorFunction

padded_lower(self: asset.VectorFunctions.Segment2, arg0: int) → asset.VectorFunctions.VectorFunction

padded_upper(self: asset.VectorFunctions.Segment2, arg0: int) → asset.VectorFunctions.VectorFunction

rpt(self: asset.VectorFunctions.Segment2, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

segment(self: asset.VectorFunctions.Segment2, arg0: int, arg1: int) → asset.VectorFunctions.Segment

squared_norm(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.ScalarFunction

sum(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.ScalarFunction

tail(self: asset.VectorFunctions.Segment2, arg0: int) → asset.VectorFunctions.Segment

tolist(*args, **kwargs)

Overloaded function.

1. tolist(self: asset.VectorFunctions.Segment2) -> list[asset.VectorFunctions.Element]

2. tolist(self: asset.VectorFunctions.Segment2, arg0: list[int]) -> list[asset.VectorFunctions.Element]

3. tolist(self: asset.VectorFunctions.Segment2, arg0: list[tuple[int, int]]) -> list[object]

vf(self: asset.VectorFunctions.Segment2) → asset.VectorFunctions.VectorFunction

class asset.VectorFunctions.Segment3

Bases: pybind11_object

IRows(self: asset.VectorFunctions.Segment3) → int

ORows(self: asset.VectorFunctions.Segment3) → int

__add__(*args, **kwargs)

Overloaded function.

1. __add__(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

2. __add__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.VectorFunction

3. __add__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__array_ufunc__ = None

__call__(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[3, 1]]

__getitem__(*args, **kwargs)

Overloaded function.

1. __getitem__(self: asset.VectorFunctions.Segment3, arg0: int) -> asset.VectorFunctions.Element

2. __getitem__(self: asset.VectorFunctions.Segment3, arg0: slice) -> asset.VectorFunctions.Segment

__init__(self: asset.VectorFunctions.Segment3, arg0: int, arg1: int, arg2: int) → None

__module__ = 'asset.VectorFunctions'

__mul__(*args, **kwargs)

Overloaded function.

1. __mul__(self: asset.VectorFunctions.Segment3, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __mul__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

3. __mul__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__neg__(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.VectorFunction

__radd__(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]]) → asset.VectorFunctions.VectorFunction

__rmul__(*args, **kwargs)

Overloaded function.

1. __rmul__(self: asset.VectorFunctions.Segment3, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __rmul__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

3. __rmul__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__rsub__(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]]) → asset.VectorFunctions.VectorFunction

__sub__(*args, **kwargs)

Overloaded function.

1. __sub__(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

2. __sub__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.VectorFunction

3. __sub__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__truediv__(*args, **kwargs)

Overloaded function.

1. __truediv__(self: asset.VectorFunctions.Segment3, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __truediv__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

3. __truediv__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

4. __truediv__(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

adjointgradient(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[3, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[3, 1]]) → numpy.ndarray[numpy.float64[m, n]]

apply(*args, **kwargs)

Overloaded function.

1. apply(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. apply(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

coeff(self: asset.VectorFunctions.Segment3, arg0: int) → asset.VectorFunctions.Element

compute(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[3, 1]]

compute_jacobian(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[3, 1]], numpy.ndarray[numpy.float64[3, n]]]

computeall(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[3, 1]]) → tuple[numpy.ndarray[numpy.float64[3, 1]], numpy.ndarray[numpy.float64[3, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

cross(*args, **kwargs)

Overloaded function.

1. cross(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

2. cross(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cross(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

4. cross(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.VectorFunction

cubed_norm(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.ScalarFunction

cwiseProduct(*args, **kwargs)

Overloaded function.

1. cwiseProduct(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

2. cwiseProduct(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cwiseProduct(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.VectorFunction

4. cwiseProduct(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

cwiseQuotient(*args, **kwargs)

Overloaded function.

1. cwiseQuotient(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

2. cwiseQuotient(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cwiseQuotient(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.VectorFunction

4. cwiseQuotient(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

dot(*args, **kwargs)

Overloaded function.

1. dot(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment) -> asset.VectorFunctions.ScalarFunction

2. dot(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

3. dot(self: asset.VectorFunctions.Segment3, arg0: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.ScalarFunction

4. dot(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.ScalarFunction

head(self: asset.VectorFunctions.Segment3, arg0: int) → asset.VectorFunctions.Segment

head2(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.Segment2

head_2(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.Segment2

input_domain(self: asset.VectorFunctions.Segment3) → numpy.ndarray[numpy.int32[2, n]]

inverse_cubed_norm(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.ScalarFunction

inverse_four_norm(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.ScalarFunction

inverse_norm(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.ScalarFunction

inverse_squared_norm(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.ScalarFunction

is_linear(self: asset.VectorFunctions.Segment3) → bool

jacobian(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[3, n]]

name(self: asset.VectorFunctions.Segment3) → str

norm(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.ScalarFunction

normalized(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.VectorFunction

normalized_power2(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.VectorFunction

normalized_power3(*args, **kwargs)

Overloaded function.

1. normalized_power3(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

2. normalized_power3(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[3, 1]], arg1: float) -> asset.VectorFunctions.VectorFunction

3. normalized_power3(self: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.VectorFunction

normalized_power4(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.VectorFunction

normalized_power5(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.VectorFunction

padded(self: asset.VectorFunctions.Segment3, arg0: int, arg1: int) → asset.VectorFunctions.VectorFunction

padded_lower(self: asset.VectorFunctions.Segment3, arg0: int) → asset.VectorFunctions.VectorFunction

padded_upper(self: asset.VectorFunctions.Segment3, arg0: int) → asset.VectorFunctions.VectorFunction

rpt(self: asset.VectorFunctions.Segment3, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

segment(self: asset.VectorFunctions.Segment3, arg0: int, arg1: int) → asset.VectorFunctions.Segment

segment2(self: asset.VectorFunctions.Segment3, arg0: int) → asset.VectorFunctions.Segment2

segment_2(self: asset.VectorFunctions.Segment3, arg0: int) → asset.VectorFunctions.Segment2

squared_norm(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.ScalarFunction

sum(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.ScalarFunction

tail(self: asset.VectorFunctions.Segment3, arg0: int) → asset.VectorFunctions.Segment

tail2(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.Segment2

tail_2(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.Segment2

tolist(*args, **kwargs)

Overloaded function.

1. tolist(self: asset.VectorFunctions.Segment3) -> list[asset.VectorFunctions.Element]

2. tolist(self: asset.VectorFunctions.Segment3, arg0: list[int]) -> list[asset.VectorFunctions.Element]

3. tolist(self: asset.VectorFunctions.Segment3, arg0: list[tuple[int, int]]) -> list[object]

vf(self: asset.VectorFunctions.Segment3) → asset.VectorFunctions.VectorFunction

asset.VectorFunctions.Stack(*args, **kwargs)

Overloaded function.

1. Stack(arg0: list[asset.VectorFunctions.ScalarFunction]) -> asset.VectorFunctions.VectorFunction

2. Stack(arg0: list[asset.VectorFunctions.VectorFunction]) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.StackScalar(arg0: list[asset.VectorFunctions.ScalarFunction]) → asset.VectorFunctions.VectorFunction

asset.VectorFunctions.Sum(*args, **kwargs)

Overloaded function.

1. Sum(arg0: list[asset.VectorFunctions.ScalarFunction]) -> asset.VectorFunctions.ScalarFunction

2. Sum(arg0: list[asset.VectorFunctions.VectorFunction]) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.SumElems(*args, **kwargs)

Overloaded function.

1. SumElems(arg0: list[asset.VectorFunctions.Element]) -> asset.VectorFunctions.ScalarFunction

2. SumElems(arg0: list[asset.VectorFunctions.Element], arg1: list[float]) -> asset.VectorFunctions.ScalarFunction

asset.VectorFunctions.SumScalar(arg0: list[asset.VectorFunctions.ScalarFunction]) → asset.VectorFunctions.ScalarFunction

class asset.VectorFunctions.VectorFunction

Bases: pybind11_object

IRows(self: asset.VectorFunctions.VectorFunction) → int

ORows(self: asset.VectorFunctions.VectorFunction) → int

SpeedTest(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

SuperTest(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

__add__(*args, **kwargs)

Overloaded function.

1. __add__(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. __add__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__array_ufunc__ = None

__call__(*args, **kwargs)

Overloaded function.

1. __call__(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> numpy.ndarray[numpy.float64[m, 1]]

2. __call__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. __call__(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

4. __call__(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, -1, -1>) -> asset.VectorFunctions.VectorFunction

5. __call__(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 2, -1>) -> asset.VectorFunctions.VectorFunction

6. __call__(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 3, -1>) -> asset.VectorFunctions.VectorFunction

7. __call__(self: asset.VectorFunctions.VectorFunction, arg0: list[asset.VectorFunctions.ScalarFunction]) -> asset.VectorFunctions.VectorFunction

8. __call__(self: asset.VectorFunctions.VectorFunction, arg0: list[asset.VectorFunctions.VectorFunction]) -> asset.VectorFunctions.VectorFunction

9. __call__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction, *args) -> asset.VectorFunctions.VectorFunction

10. __call__(self: asset.VectorFunctions.VectorFunction, arg0: float, *args) -> asset.VectorFunctions.VectorFunction

11. __call__(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], *args) -> asset.VectorFunctions.VectorFunction

__getitem__(*args, **kwargs)

Overloaded function.

1. __getitem__(self: asset.VectorFunctions.VectorFunction, arg0: int) -> asset.VectorFunctions.ScalarFunction

2. __getitem__(self: asset.VectorFunctions.VectorFunction, arg0: slice) -> asset.VectorFunctions.VectorFunction

__init__(*args, **kwargs)

Overloaded function.

1. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> None

2. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.ScalarFunction) -> None

3. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.Segment) -> None

4. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.Element) -> None

5. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.Arguments) -> None

6. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.Segment2) -> None

7. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.Segment3) -> None

8. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.PyVectorFunction) -> None

9. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.PyScalarFunction) -> None

10. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.ConstantVector) -> None

11. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.ConstantScalar) -> None

12. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.IOScaled) -> None

13. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.InterpFunction) -> None

14. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.InterpFunction_1) -> None

15. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.InterpFunction_3) -> None

16. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.InterpFunction_6) -> None

17. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_x.ode) -> None

18. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_x.integrator) -> None

19. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_x_u.ode) -> None

20. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_x_u.integrator) -> None

21. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_x_u_p.ode) -> None

22. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_x_u_p.integrator) -> None

23. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_6_3.ode) -> None

24. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_6_3.integrator) -> None

25. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_7_3.ode) -> None

26. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_7_3.integrator) -> None

27. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_2_1.ode) -> None

28. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_2_1.integrator) -> None

29. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_6.ode) -> None

30. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_6.integrator) -> None

31. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_4.ode) -> None

32. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.OptimalControl.ode_4.integrator) -> None

33. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.Astro.Kepler.ode) -> None

34. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.Astro.Kepler.integrator) -> None

35. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.Astro.Kepler.KeplerPropagator) -> None

36. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.Astro.ModifiedToCartesian) -> None

37. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.Astro.CartesianToClassic) -> None

38. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.Extensions.cpp_cr3bp_ad) -> None

39. __init__(self: asset.VectorFunctions.VectorFunction, arg0: asset.Extensions.ModifiedDynamicsAD) -> None

__module__ = 'asset.VectorFunctions'

__mul__(*args, **kwargs)

Overloaded function.

1. __mul__(self: asset.VectorFunctions.VectorFunction, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __mul__(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

3. __mul__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__neg__(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

__radd__(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → asset.VectorFunctions.VectorFunction

__rmul__(*args, **kwargs)

Overloaded function.

1. __rmul__(self: asset.VectorFunctions.VectorFunction, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __rmul__(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

3. __rmul__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

__rsub__(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → asset.VectorFunctions.VectorFunction

__sub__(*args, **kwargs)

Overloaded function.

1. __sub__(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. __sub__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

__truediv__(*args, **kwargs)

Overloaded function.

1. __truediv__(self: asset.VectorFunctions.VectorFunction, arg0: float) -> asset.VectorFunctions.VectorFunction

2. __truediv__(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

3. __truediv__(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

4. __truediv__(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

adjointgradient(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

adjointhessian(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

apply(*args, **kwargs)

Overloaded function.

1. apply(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. apply(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

coeff(self: asset.VectorFunctions.VectorFunction, arg0: int) → asset.VectorFunctions.ScalarFunction

compute(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, 1]]

compute_jacobian(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

computeall(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: numpy.ndarray[numpy.float64[m, 1]]) → tuple[numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]], numpy.ndarray[numpy.float64[m, 1]], numpy.ndarray[numpy.float64[m, n]]]

cross(*args, **kwargs)

Overloaded function.

1. cross(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, -1, -1>) -> asset.VectorFunctions.VectorFunction

2. cross(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 3, -1>) -> asset.VectorFunctions.VectorFunction

3. cross(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

4. cross(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

cubed_norm(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.ScalarFunction

cwiseProduct(*args, **kwargs)

Overloaded function.

1. cwiseProduct(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, -1, -1>) -> asset.VectorFunctions.VectorFunction

2. cwiseProduct(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cwiseProduct(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

cwiseQuotient(*args, **kwargs)

Overloaded function.

1. cwiseQuotient(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, -1, -1>) -> asset.VectorFunctions.VectorFunction

2. cwiseQuotient(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. cwiseQuotient(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

dot(*args, **kwargs)

Overloaded function.

1. dot(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, -1, -1>) -> asset.VectorFunctions.ScalarFunction

2. dot(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.ScalarFunction

3. dot(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.ScalarFunction

eval(*args, **kwargs)

Overloaded function.

1. eval(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 1, -1>) -> asset.VectorFunctions.VectorFunction

2. eval(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, -1, -1>) -> asset.VectorFunctions.VectorFunction

3. eval(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 2, -1>) -> asset.VectorFunctions.VectorFunction

4. eval(self: asset.VectorFunctions.VectorFunction, arg0: ASSET::Segment<-1, 3, -1>) -> asset.VectorFunctions.VectorFunction

5. eval(self: asset.VectorFunctions.VectorFunction, arg0: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

6. eval(self: asset.VectorFunctions.VectorFunction, arg0: int, arg1: numpy.ndarray[numpy.int32[m, 1]]) -> asset.VectorFunctions.VectorFunction

head(self: asset.VectorFunctions.VectorFunction, arg0: int) → asset.VectorFunctions.VectorFunction

head2(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

head3(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

head_2(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

head_3(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

input_domain(self: asset.VectorFunctions.VectorFunction) → numpy.ndarray[numpy.int32[2, n]]

inverse_cubed_norm(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.ScalarFunction

inverse_four_norm(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.ScalarFunction

inverse_norm(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.ScalarFunction

inverse_squared_norm(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.ScalarFunction

is_linear(self: asset.VectorFunctions.VectorFunction) → bool

jacobian(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) → numpy.ndarray[numpy.float64[m, n]]

name(self: asset.VectorFunctions.VectorFunction) → str

norm(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.ScalarFunction

normalized(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

normalized_power2(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

normalized_power3(*args, **kwargs)

Overloaded function.

1. normalized_power3(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

2. normalized_power3(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: float) -> asset.VectorFunctions.VectorFunction

3. normalized_power3(self: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

normalized_power4(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

normalized_power5(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

padded(self: asset.VectorFunctions.VectorFunction, arg0: int, arg1: int) → asset.VectorFunctions.VectorFunction

padded_lower(self: asset.VectorFunctions.VectorFunction, arg0: int) → asset.VectorFunctions.VectorFunction

padded_upper(self: asset.VectorFunctions.VectorFunction, arg0: int) → asset.VectorFunctions.VectorFunction

rpt(self: asset.VectorFunctions.VectorFunction, arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: int) → None

segment(self: asset.VectorFunctions.VectorFunction, arg0: int, arg1: int) → asset.VectorFunctions.VectorFunction

segment2(self: asset.VectorFunctions.VectorFunction, arg0: int) → asset.VectorFunctions.VectorFunction

segment3(self: asset.VectorFunctions.VectorFunction, arg0: int) → asset.VectorFunctions.VectorFunction

segment_2(self: asset.VectorFunctions.VectorFunction, arg0: int) → asset.VectorFunctions.VectorFunction

segment_3(self: asset.VectorFunctions.VectorFunction, arg0: int) → asset.VectorFunctions.VectorFunction

squared_norm(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.ScalarFunction

sum(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.ScalarFunction

tail(self: asset.VectorFunctions.VectorFunction, arg0: int) → asset.VectorFunctions.VectorFunction

tail2(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

tail3(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

tail_2(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

tail_3(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

vf(self: asset.VectorFunctions.VectorFunction) → asset.VectorFunctions.VectorFunction

asset.VectorFunctions.abs(*args, **kwargs)

Overloaded function.

1. abs(arg0: asset.VectorFunctions.Element) -> object

2. abs(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.arccos(*args, **kwargs)

Overloaded function.

1. arccos(arg0: asset.VectorFunctions.Element) -> object

2. arccos(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.arccosh(*args, **kwargs)

Overloaded function.

1. arccosh(arg0: asset.VectorFunctions.Element) -> object

2. arccosh(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.arcsin(*args, **kwargs)

Overloaded function.

1. arcsin(arg0: asset.VectorFunctions.Element) -> object

2. arcsin(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.arcsinh(*args, **kwargs)

Overloaded function.

1. arcsinh(arg0: asset.VectorFunctions.Element) -> object

2. arcsinh(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.arctan(*args, **kwargs)

Overloaded function.

1. arctan(arg0: asset.VectorFunctions.Element) -> object

2. arctan(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.arctan2(*args, **kwargs)

Overloaded function.

1. arctan2(arg0: asset.VectorFunctions.ScalarFunction, arg1: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

2. arctan2(arg0: asset.VectorFunctions.Element, arg1: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

3. arctan2(arg0: asset.VectorFunctions.Element, arg1: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

4. arctan2(arg0: asset.VectorFunctions.ScalarFunction, arg1: asset.VectorFunctions.Element) -> asset.VectorFunctions.ScalarFunction

asset.VectorFunctions.arctanh(*args, **kwargs)

Overloaded function.

1. arctanh(arg0: asset.VectorFunctions.Element) -> object

2. arctanh(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.cos(*args, **kwargs)

Overloaded function.

1. cos(arg0: asset.VectorFunctions.Element) -> object

2. cos(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.cosh(*args, **kwargs)

Overloaded function.

1. cosh(arg0: asset.VectorFunctions.Element) -> object

2. cosh(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.cross(*args, **kwargs)

Overloaded function.

1. cross(arg0: asset.VectorFunctions.Segment3, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

2. cross(arg0: asset.VectorFunctions.Segment, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

3. cross(arg0: asset.VectorFunctions.VectorFunction, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

4. cross(arg0: numpy.ndarray[numpy.float64[3, 1]], arg1: asset.VectorFunctions.Segment3) -> object

5. cross(arg0: numpy.ndarray[numpy.float64[3, 1]], arg1: asset.VectorFunctions.Segment) -> object

6. cross(arg0: numpy.ndarray[numpy.float64[3, 1]], arg1: asset.VectorFunctions.VectorFunction) -> object

7. cross(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.Segment3) -> object

8. cross(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.Segment) -> object

9. cross(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.VectorFunction) -> object

10. cross(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment) -> object

11. cross(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment3) -> object

12. cross(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.VectorFunction) -> object

13. cross(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment3) -> object

14. cross(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment) -> object

15. cross(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.cubed_norm(*args, **kwargs)

Overloaded function.

1. cubed_norm(arg0: asset.VectorFunctions.Arguments) -> object

2. cubed_norm(arg0: asset.VectorFunctions.Segment) -> object

3. cubed_norm(arg0: asset.VectorFunctions.Segment2) -> object

4. cubed_norm(arg0: asset.VectorFunctions.Segment3) -> object

5. cubed_norm(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.cwiseProduct(*args, **kwargs)

Overloaded function.

1. cwiseProduct(arg0: asset.VectorFunctions.Segment2, arg1: numpy.ndarray[numpy.float64[2, 1]]) -> object

2. cwiseProduct(arg0: asset.VectorFunctions.Segment3, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

3. cwiseProduct(arg0: asset.VectorFunctions.Segment, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

4. cwiseProduct(arg0: asset.VectorFunctions.VectorFunction, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

5. cwiseProduct(arg0: numpy.ndarray[numpy.float64[2, 1]], arg1: asset.VectorFunctions.Segment2) -> object

6. cwiseProduct(arg0: numpy.ndarray[numpy.float64[3, 1]], arg1: asset.VectorFunctions.Segment3) -> object

7. cwiseProduct(arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: asset.VectorFunctions.Segment) -> object

8. cwiseProduct(arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: asset.VectorFunctions.VectorFunction) -> object

9. cwiseProduct(arg0: asset.VectorFunctions.Segment2, arg1: asset.VectorFunctions.Segment2) -> object

10. cwiseProduct(arg0: asset.VectorFunctions.Segment2, arg1: asset.VectorFunctions.Segment) -> object

11. cwiseProduct(arg0: asset.VectorFunctions.Segment2, arg1: asset.VectorFunctions.VectorFunction) -> object

12. cwiseProduct(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.Segment3) -> object

13. cwiseProduct(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.Segment) -> object

14. cwiseProduct(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.VectorFunction) -> object

15. cwiseProduct(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment) -> object

16. cwiseProduct(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment2) -> object

17. cwiseProduct(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment3) -> object

18. cwiseProduct(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.VectorFunction) -> object

19. cwiseProduct(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment2) -> object

20. cwiseProduct(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment3) -> object

21. cwiseProduct(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment) -> object

22. cwiseProduct(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.cwiseQuotient(*args, **kwargs)

Overloaded function.

1. cwiseQuotient(arg0: asset.VectorFunctions.Segment2, arg1: numpy.ndarray[numpy.float64[2, 1]]) -> object

2. cwiseQuotient(arg0: asset.VectorFunctions.Segment3, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

3. cwiseQuotient(arg0: asset.VectorFunctions.Segment, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

4. cwiseQuotient(arg0: asset.VectorFunctions.VectorFunction, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

5. cwiseQuotient(arg0: numpy.ndarray[numpy.float64[2, 1]], arg1: asset.VectorFunctions.Segment2) -> object

6. cwiseQuotient(arg0: numpy.ndarray[numpy.float64[3, 1]], arg1: asset.VectorFunctions.Segment3) -> object

7. cwiseQuotient(arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: asset.VectorFunctions.Segment) -> object

8. cwiseQuotient(arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: asset.VectorFunctions.VectorFunction) -> object

9. cwiseQuotient(arg0: asset.VectorFunctions.Segment2, arg1: asset.VectorFunctions.Segment2) -> object

10. cwiseQuotient(arg0: asset.VectorFunctions.Segment2, arg1: asset.VectorFunctions.Segment) -> object

11. cwiseQuotient(arg0: asset.VectorFunctions.Segment2, arg1: asset.VectorFunctions.VectorFunction) -> object

12. cwiseQuotient(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.Segment3) -> object

13. cwiseQuotient(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.Segment) -> object

14. cwiseQuotient(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.VectorFunction) -> object

15. cwiseQuotient(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment) -> object

16. cwiseQuotient(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment2) -> object

17. cwiseQuotient(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment3) -> object

18. cwiseQuotient(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.VectorFunction) -> object

19. cwiseQuotient(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment2) -> object

20. cwiseQuotient(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment3) -> object

21. cwiseQuotient(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment) -> object

22. cwiseQuotient(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.divtest(*args, **kwargs)

Overloaded function.

1. divtest(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.VectorFunction

2. divtest(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Element) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.dot(*args, **kwargs)

Overloaded function.

1. dot(arg0: asset.VectorFunctions.Segment2, arg1: numpy.ndarray[numpy.float64[2, 1]]) -> object

2. dot(arg0: asset.VectorFunctions.Segment3, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

3. dot(arg0: asset.VectorFunctions.Segment, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

4. dot(arg0: asset.VectorFunctions.VectorFunction, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> object

5. dot(arg0: numpy.ndarray[numpy.float64[2, 1]], arg1: asset.VectorFunctions.Segment2) -> object

6. dot(arg0: numpy.ndarray[numpy.float64[3, 1]], arg1: asset.VectorFunctions.Segment3) -> object

7. dot(arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: asset.VectorFunctions.Segment) -> object

8. dot(arg0: numpy.ndarray[numpy.float64[m, 1]], arg1: asset.VectorFunctions.VectorFunction) -> object

9. dot(arg0: asset.VectorFunctions.Segment2, arg1: asset.VectorFunctions.Segment2) -> object

10. dot(arg0: asset.VectorFunctions.Segment2, arg1: asset.VectorFunctions.Segment) -> object

11. dot(arg0: asset.VectorFunctions.Segment2, arg1: asset.VectorFunctions.VectorFunction) -> object

12. dot(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.Segment3) -> object

13. dot(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.Segment) -> object

14. dot(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.VectorFunction) -> object

15. dot(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment) -> object

16. dot(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment2) -> object

17. dot(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment3) -> object

18. dot(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.VectorFunction) -> object

19. dot(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment2) -> object

20. dot(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment3) -> object

21. dot(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment) -> object

22. dot(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.doublecross(*args, **kwargs)

Overloaded function.

1. doublecross(arg0: asset.VectorFunctions.Segment3, arg1: asset.VectorFunctions.Segment3, arg2: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.VectorFunction

2. doublecross(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.VectorFunction, arg2: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.exp(*args, **kwargs)

Overloaded function.

1. exp(arg0: asset.VectorFunctions.Element) -> object

2. exp(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.ifelse(*args, **kwargs)

Overloaded function.

1. ifelse(arg0: ASSET::GenericConditional<-1>, arg1: asset.VectorFunctions.ScalarFunction, arg2: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

2. ifelse(arg0: ASSET::GenericConditional<-1>, arg1: float, arg2: asset.VectorFunctions.ScalarFunction) -> asset.VectorFunctions.ScalarFunction

3. ifelse(arg0: ASSET::GenericConditional<-1>, arg1: asset.VectorFunctions.ScalarFunction, arg2: float) -> asset.VectorFunctions.ScalarFunction

4. ifelse(arg0: ASSET::GenericConditional<-1>, arg1: float, arg2: float) -> asset.VectorFunctions.ScalarFunction

5. ifelse(arg0: ASSET::GenericConditional<-1>, arg1: asset.VectorFunctions.VectorFunction, arg2: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

6. ifelse(arg0: ASSET::GenericConditional<-1>, arg1: numpy.ndarray[numpy.float64[m, 1]], arg2: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

7. ifelse(arg0: ASSET::GenericConditional<-1>, arg1: asset.VectorFunctions.VectorFunction, arg2: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

8. ifelse(arg0: ASSET::GenericConditional<-1>, arg1: numpy.ndarray[numpy.float64[m, 1]], arg2: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.inverse_cubed_norm(*args, **kwargs)

Overloaded function.

1. inverse_cubed_norm(arg0: asset.VectorFunctions.Arguments) -> object

2. inverse_cubed_norm(arg0: asset.VectorFunctions.Segment) -> object

3. inverse_cubed_norm(arg0: asset.VectorFunctions.Segment2) -> object

4. inverse_cubed_norm(arg0: asset.VectorFunctions.Segment3) -> object

5. inverse_cubed_norm(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.inverse_four_norm(*args, **kwargs)

Overloaded function.

1. inverse_four_norm(arg0: asset.VectorFunctions.Arguments) -> object

2. inverse_four_norm(arg0: asset.VectorFunctions.Segment) -> object

3. inverse_four_norm(arg0: asset.VectorFunctions.Segment2) -> object

4. inverse_four_norm(arg0: asset.VectorFunctions.Segment3) -> object

5. inverse_four_norm(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.inverse_norm(*args, **kwargs)

Overloaded function.

1. inverse_norm(arg0: asset.VectorFunctions.Arguments) -> object

2. inverse_norm(arg0: asset.VectorFunctions.Segment) -> object

3. inverse_norm(arg0: asset.VectorFunctions.Segment2) -> object

4. inverse_norm(arg0: asset.VectorFunctions.Segment3) -> object

5. inverse_norm(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.inverse_squared_norm(*args, **kwargs)

Overloaded function.

1. inverse_squared_norm(arg0: asset.VectorFunctions.Arguments) -> object

2. inverse_squared_norm(arg0: asset.VectorFunctions.Segment) -> object

3. inverse_squared_norm(arg0: asset.VectorFunctions.Segment2) -> object

4. inverse_squared_norm(arg0: asset.VectorFunctions.Segment3) -> object

5. inverse_squared_norm(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.log(*args, **kwargs)

Overloaded function.

1. log(arg0: asset.VectorFunctions.Element) -> object

2. log(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.matmul(*args, **kwargs)

Overloaded function.

1. matmul(arg0: asset.VectorFunctions.ColMatrix, arg1: asset.VectorFunctions.ColMatrix) -> asset.VectorFunctions.ColMatrix

2. matmul(arg0: asset.VectorFunctions.ColMatrix, arg1: asset.VectorFunctions.RowMatrix) -> asset.VectorFunctions.ColMatrix

3. matmul(arg0: asset.VectorFunctions.ColMatrix, arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

4. matmul(arg0: asset.VectorFunctions.ColMatrix, arg1: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

5. matmul(arg0: asset.VectorFunctions.RowMatrix, arg1: asset.VectorFunctions.ColMatrix) -> asset.VectorFunctions.ColMatrix

6. matmul(arg0: asset.VectorFunctions.RowMatrix, arg1: asset.VectorFunctions.RowMatrix) -> asset.VectorFunctions.ColMatrix

7. matmul(arg0: asset.VectorFunctions.RowMatrix, arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

8. matmul(arg0: asset.VectorFunctions.RowMatrix, arg1: numpy.ndarray[numpy.float64[m, 1]]) -> asset.VectorFunctions.VectorFunction

9. matmul(arg0: numpy.ndarray[numpy.float64[2, 2]], arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

10. matmul(arg0: numpy.ndarray[numpy.float64[3, 3]], arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

11. matmul(arg0: numpy.ndarray[numpy.float64[m, n]], arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.norm(*args, **kwargs)

Overloaded function.

1. norm(arg0: asset.VectorFunctions.Arguments) -> object

2. norm(arg0: asset.VectorFunctions.Segment) -> object

3. norm(arg0: asset.VectorFunctions.Segment2) -> object

4. norm(arg0: asset.VectorFunctions.Segment3) -> object

5. norm(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.normalize(*args, **kwargs)

Overloaded function.

1. normalize(arg0: numpy.ndarray[numpy.float64[m, 1]]) -> numpy.ndarray[numpy.float64[m, 1]]

2. normalize(arg0: asset.VectorFunctions.Arguments) -> object

3. normalize(arg0: asset.VectorFunctions.Segment) -> object

4. normalize(arg0: asset.VectorFunctions.Segment2) -> object

5. normalize(arg0: asset.VectorFunctions.Segment3) -> object

6. normalize(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.normalized(*args, **kwargs)

Overloaded function.

1. normalized(arg0: numpy.ndarray[numpy.float64[m, 1]]) -> numpy.ndarray[numpy.float64[m, 1]]

2. normalized(arg0: asset.VectorFunctions.Arguments) -> object

3. normalized(arg0: asset.VectorFunctions.Segment) -> object

4. normalized(arg0: asset.VectorFunctions.Segment2) -> object

5. normalized(arg0: asset.VectorFunctions.Segment3) -> object

6. normalized(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.normalized_power2(*args, **kwargs)

Overloaded function.

1. normalized_power2(arg0: asset.VectorFunctions.Arguments) -> object

2. normalized_power2(arg0: asset.VectorFunctions.Segment) -> object

3. normalized_power2(arg0: asset.VectorFunctions.Segment2) -> object

4. normalized_power2(arg0: asset.VectorFunctions.Segment3) -> object

5. normalized_power2(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.normalized_power3(*args, **kwargs)

Overloaded function.

1. normalized_power3(arg0: asset.VectorFunctions.Arguments) -> object

2. normalized_power3(arg0: asset.VectorFunctions.Segment) -> object

3. normalized_power3(arg0: asset.VectorFunctions.Segment2) -> object

4. normalized_power3(arg0: asset.VectorFunctions.Segment3) -> object

5. normalized_power3(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.normalized_power4(*args, **kwargs)

Overloaded function.

1. normalized_power4(arg0: asset.VectorFunctions.Arguments) -> object

2. normalized_power4(arg0: asset.VectorFunctions.Segment) -> object

3. normalized_power4(arg0: asset.VectorFunctions.Segment2) -> object

4. normalized_power4(arg0: asset.VectorFunctions.Segment3) -> object

5. normalized_power4(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.normalized_power5(*args, **kwargs)

Overloaded function.

1. normalized_power5(arg0: asset.VectorFunctions.Arguments) -> object

2. normalized_power5(arg0: asset.VectorFunctions.Segment) -> object

3. normalized_power5(arg0: asset.VectorFunctions.Segment2) -> object

4. normalized_power5(arg0: asset.VectorFunctions.Segment3) -> object

5. normalized_power5(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.pow(*args, **kwargs)

Overloaded function.

1. pow(arg0: asset.VectorFunctions.Element) -> object

2. pow(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.quatProduct(*args, **kwargs)

Overloaded function.

1. quatProduct(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

2. quatProduct(arg0: asset.VectorFunctions.Segment, arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

3. quatProduct(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

4. quatProduct(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.quatRotate(*args, **kwargs)

Overloaded function.

1. quatRotate(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.VectorFunction) -> asset.VectorFunctions.VectorFunction

2. quatRotate(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment3) -> asset.VectorFunctions.VectorFunction

3. quatRotate(arg0: asset.VectorFunctions.VectorFunction, arg1: asset.VectorFunctions.Segment) -> asset.VectorFunctions.VectorFunction

4. quatRotate(arg0: asset.VectorFunctions.VectorFunction, arg1: numpy.ndarray[numpy.float64[3, 1]]) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.sign(*args, **kwargs)

Overloaded function.

1. sign(arg0: asset.VectorFunctions.Element) -> object

2. sign(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.sin(*args, **kwargs)

Overloaded function.

1. sin(arg0: asset.VectorFunctions.Element) -> object

2. sin(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.sinh(*args, **kwargs)

Overloaded function.

1. sinh(arg0: asset.VectorFunctions.Element) -> object

2. sinh(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.sqrt(*args, **kwargs)

Overloaded function.

1. sqrt(arg0: asset.VectorFunctions.Element) -> object

2. sqrt(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.squared(*args, **kwargs)

Overloaded function.

1. squared(arg0: asset.VectorFunctions.Element) -> object

2. squared(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.squared_norm(*args, **kwargs)

Overloaded function.

1. squared_norm(arg0: asset.VectorFunctions.Arguments) -> object

2. squared_norm(arg0: asset.VectorFunctions.Segment) -> object

3. squared_norm(arg0: asset.VectorFunctions.Segment2) -> object

4. squared_norm(arg0: asset.VectorFunctions.Segment3) -> object

5. squared_norm(arg0: asset.VectorFunctions.VectorFunction) -> object

asset.VectorFunctions.stack(*args, **kwargs)

Overloaded function.

1. stack(arg0: list[asset.VectorFunctions.ScalarFunction]) -> asset.VectorFunctions.VectorFunction

2. stack(arg0: list[asset.VectorFunctions.VectorFunction]) -> asset.VectorFunctions.VectorFunction

3. stack(arg0: asset.VectorFunctions.VectorFunction, *args) -> asset.VectorFunctions.VectorFunction

4. stack(arg0: float, *args) -> asset.VectorFunctions.VectorFunction

5. stack(arg0: numpy.ndarray[numpy.float64[m, 1]], *args) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.stack_scalar(*args, **kwargs)

Overloaded function.

1. stack_scalar(arg0: list[asset.VectorFunctions.ScalarFunction]) -> asset.VectorFunctions.VectorFunction

2. stack_scalar(arg0: asset.VectorFunctions.ScalarFunction, *args) -> asset.VectorFunctions.VectorFunction

3. stack_scalar(arg0: float, *args) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.sum(*args, **kwargs)

Overloaded function.

1. sum(arg0: list[asset.VectorFunctions.ScalarFunction]) -> asset.VectorFunctions.ScalarFunction

2. sum(arg0: list[asset.VectorFunctions.VectorFunction]) -> asset.VectorFunctions.VectorFunction

3. sum(arg0: asset.VectorFunctions.ScalarFunction, *args) -> asset.VectorFunctions.ScalarFunction

4. sum(arg0: float, *args) -> asset.VectorFunctions.ScalarFunction

5. sum(arg0: asset.VectorFunctions.VectorFunction, *args) -> asset.VectorFunctions.VectorFunction

6. sum(arg0: numpy.ndarray[numpy.float64[m, 1]], *args) -> asset.VectorFunctions.VectorFunction

asset.VectorFunctions.tan(*args, **kwargs)

Overloaded function.

1. tan(arg0: asset.VectorFunctions.Element) -> object

2. tan(arg0: asset.VectorFunctions.ScalarFunction) -> object

asset.VectorFunctions.tanh(*args, **kwargs)

Overloaded function.

1. tanh(arg0: asset.VectorFunctions.Element) -> object

2. tanh(arg0: asset.VectorFunctions.ScalarFunction) -> object