pydrake.multibody.math¶
Bindings for multibody math.
-
pydrake.multibody.math.
SpatialAcceleration
¶
-
template
pydrake.multibody.math.
SpatialAcceleration_
¶ Instantiations:
SpatialAcceleration_[float]
,SpatialAcceleration_[AutoDiffXd]
,SpatialAcceleration_[Expression]
-
class
SpatialAcceleration_[float]
¶ This class is used to represent a spatial acceleration that combines rotational (angular acceleration) and translational (linear acceleration) components. While a SpatialVelocity
V_XY
represents the motion of a “moving frame” Y measured with respect to a “measured-in” frame X, the SpatialAccelerationA_XY
represents the rate of change of this spatial velocityV_XY
in frame X. That is \(^XA^Y = \frac{^Xd}{dt}\,{^XV^Y}\) where \(\frac{^Xd}{dt}\) denotes the time derivative taken in frame X. That is, to compute an acceleration we need to specify in what frame the time derivative is taken, see [Mitiguy 2016, §6.1] for a more in depth discussion on this. Time derivatives can be taken in different frames, and they transform according to the “Transport Theorem”, which in Drake is implemented in drake::math::ConvertTimeDerivativeToOtherFrame(). In source code comments we writeA_XY = DtX(V_XY)
, whereDtX()
is the operator that takes the time derivative in the X frame. By convention, and unless otherwise stated, we assume that the frame in which the time derivative is taken is the “measured-in” frame, i.e. the time derivative used inA_XY
is in frame X by default (i.e. DtX()). To perform numerical computations, we need to specify an “expressed-in” frame E (which may be distinct from either X or Y), so that components can be expressed as real numbers. Only the vector values are stored in a SpatialAcceleration object; the frames must be understood from context and it is the responsibility of the user to keep track of them. That is best accomplished through disciplined notation. In source code we use monogram notation where capital A is used to designate a spatial acceleration quantity. The same monogram notation rules for SpatialVelocity are also used for SpatialAcceleration. That is, the spatial acceleration of a frame Y measured in X and expressed in E is denoted withA_XY_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.[Mitiguy 2016] Mitiguy, P., 2016. Advanced Dynamics & Motion Simulation.
-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialAcceleration_[float]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial acceleration are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial acceleration fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialAcceleration_[float], alpha: numpy.ndarray[numpy.float64[3, 1]], a: numpy.ndarray[numpy.float64[3, 1]]) -> None
SpatialAcceleration constructor from an angular acceleration
alpha
and a linear accelerationa
.- __init__(self: pydrake.multibody.math.SpatialAcceleration_[float], A: numpy.ndarray[numpy.float64[6, 1]]) -> None
SpatialAcceleration constructor from an Eigen expression that represents a six-dimensional vector. Under the hood, spatial accelerations are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 constitute the angular acceleration component while elements 3-5 constitute the translational acceleration. The argument
A
in this constructor is the concatenation of the rotational 3D component followed by the translational 3D component. This constructor will assert the size ofA
is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialAcceleration_[float]) → numpy.ndarray[numpy.float64[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialAcceleration_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialAcceleration_[float]) → pydrake.multibody.math.SpatialAcceleration_[float]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialAcceleration_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialAcceleration_[float]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
class
-
class
pydrake.multibody.math.
SpatialAcceleration_[AutoDiffXd]
¶ This class is used to represent a spatial acceleration that combines rotational (angular acceleration) and translational (linear acceleration) components. While a SpatialVelocity
V_XY
represents the motion of a “moving frame” Y measured with respect to a “measured-in” frame X, the SpatialAccelerationA_XY
represents the rate of change of this spatial velocityV_XY
in frame X. That is \(^XA^Y = \frac{^Xd}{dt}\,{^XV^Y}\) where \(\frac{^Xd}{dt}\) denotes the time derivative taken in frame X. That is, to compute an acceleration we need to specify in what frame the time derivative is taken, see [Mitiguy 2016, §6.1] for a more in depth discussion on this. Time derivatives can be taken in different frames, and they transform according to the “Transport Theorem”, which in Drake is implemented in drake::math::ConvertTimeDerivativeToOtherFrame(). In source code comments we writeA_XY = DtX(V_XY)
, whereDtX()
is the operator that takes the time derivative in the X frame. By convention, and unless otherwise stated, we assume that the frame in which the time derivative is taken is the “measured-in” frame, i.e. the time derivative used inA_XY
is in frame X by default (i.e. DtX()). To perform numerical computations, we need to specify an “expressed-in” frame E (which may be distinct from either X or Y), so that components can be expressed as real numbers. Only the vector values are stored in a SpatialAcceleration object; the frames must be understood from context and it is the responsibility of the user to keep track of them. That is best accomplished through disciplined notation. In source code we use monogram notation where capital A is used to designate a spatial acceleration quantity. The same monogram notation rules for SpatialVelocity are also used for SpatialAcceleration. That is, the spatial acceleration of a frame Y measured in X and expressed in E is denoted withA_XY_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.[Mitiguy 2016] Mitiguy, P., 2016. Advanced Dynamics & Motion Simulation.
-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialAcceleration_[AutoDiffXd]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial acceleration are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial acceleration fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialAcceleration_[AutoDiffXd], alpha: numpy.ndarray[object[3, 1]], a: numpy.ndarray[object[3, 1]]) -> None
SpatialAcceleration constructor from an angular acceleration
alpha
and a linear accelerationa
.- __init__(self: pydrake.multibody.math.SpatialAcceleration_[AutoDiffXd], A: numpy.ndarray[object[6, 1]]) -> None
SpatialAcceleration constructor from an Eigen expression that represents a six-dimensional vector. Under the hood, spatial accelerations are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 constitute the angular acceleration component while elements 3-5 constitute the translational acceleration. The argument
A
in this constructor is the concatenation of the rotational 3D component followed by the translational 3D component. This constructor will assert the size ofA
is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialAcceleration_[AutoDiffXd]) → numpy.ndarray[object[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialAcceleration_[AutoDiffXd]) → numpy.ndarray[object[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialAcceleration_[AutoDiffXd]) → pydrake.multibody.math.SpatialAcceleration_[AutoDiffXd]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialAcceleration_[AutoDiffXd]) → numpy.ndarray[object[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialAcceleration_[AutoDiffXd]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
class
pydrake.multibody.math.
SpatialAcceleration_[Expression]
¶ This class is used to represent a spatial acceleration that combines rotational (angular acceleration) and translational (linear acceleration) components. While a SpatialVelocity
V_XY
represents the motion of a “moving frame” Y measured with respect to a “measured-in” frame X, the SpatialAccelerationA_XY
represents the rate of change of this spatial velocityV_XY
in frame X. That is \(^XA^Y = \frac{^Xd}{dt}\,{^XV^Y}\) where \(\frac{^Xd}{dt}\) denotes the time derivative taken in frame X. That is, to compute an acceleration we need to specify in what frame the time derivative is taken, see [Mitiguy 2016, §6.1] for a more in depth discussion on this. Time derivatives can be taken in different frames, and they transform according to the “Transport Theorem”, which in Drake is implemented in drake::math::ConvertTimeDerivativeToOtherFrame(). In source code comments we writeA_XY = DtX(V_XY)
, whereDtX()
is the operator that takes the time derivative in the X frame. By convention, and unless otherwise stated, we assume that the frame in which the time derivative is taken is the “measured-in” frame, i.e. the time derivative used inA_XY
is in frame X by default (i.e. DtX()). To perform numerical computations, we need to specify an “expressed-in” frame E (which may be distinct from either X or Y), so that components can be expressed as real numbers. Only the vector values are stored in a SpatialAcceleration object; the frames must be understood from context and it is the responsibility of the user to keep track of them. That is best accomplished through disciplined notation. In source code we use monogram notation where capital A is used to designate a spatial acceleration quantity. The same monogram notation rules for SpatialVelocity are also used for SpatialAcceleration. That is, the spatial acceleration of a frame Y measured in X and expressed in E is denoted withA_XY_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.[Mitiguy 2016] Mitiguy, P., 2016. Advanced Dynamics & Motion Simulation.
-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialAcceleration_[Expression]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial acceleration are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial acceleration fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialAcceleration_[Expression], alpha: numpy.ndarray[object[3, 1]], a: numpy.ndarray[object[3, 1]]) -> None
SpatialAcceleration constructor from an angular acceleration
alpha
and a linear accelerationa
.- __init__(self: pydrake.multibody.math.SpatialAcceleration_[Expression], A: numpy.ndarray[object[6, 1]]) -> None
SpatialAcceleration constructor from an Eigen expression that represents a six-dimensional vector. Under the hood, spatial accelerations are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 constitute the angular acceleration component while elements 3-5 constitute the translational acceleration. The argument
A
in this constructor is the concatenation of the rotational 3D component followed by the translational 3D component. This constructor will assert the size ofA
is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialAcceleration_[Expression]) → numpy.ndarray[object[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialAcceleration_[Expression]) → numpy.ndarray[object[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialAcceleration_[Expression]) → pydrake.multibody.math.SpatialAcceleration_[Expression]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialAcceleration_[Expression]) → numpy.ndarray[object[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialAcceleration_[Expression]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
class
pydrake.multibody.math.
SpatialAcceleration_[float]
¶ This class is used to represent a spatial acceleration that combines rotational (angular acceleration) and translational (linear acceleration) components. While a SpatialVelocity
V_XY
represents the motion of a “moving frame” Y measured with respect to a “measured-in” frame X, the SpatialAccelerationA_XY
represents the rate of change of this spatial velocityV_XY
in frame X. That is \(^XA^Y = \frac{^Xd}{dt}\,{^XV^Y}\) where \(\frac{^Xd}{dt}\) denotes the time derivative taken in frame X. That is, to compute an acceleration we need to specify in what frame the time derivative is taken, see [Mitiguy 2016, §6.1] for a more in depth discussion on this. Time derivatives can be taken in different frames, and they transform according to the “Transport Theorem”, which in Drake is implemented in drake::math::ConvertTimeDerivativeToOtherFrame(). In source code comments we writeA_XY = DtX(V_XY)
, whereDtX()
is the operator that takes the time derivative in the X frame. By convention, and unless otherwise stated, we assume that the frame in which the time derivative is taken is the “measured-in” frame, i.e. the time derivative used inA_XY
is in frame X by default (i.e. DtX()). To perform numerical computations, we need to specify an “expressed-in” frame E (which may be distinct from either X or Y), so that components can be expressed as real numbers. Only the vector values are stored in a SpatialAcceleration object; the frames must be understood from context and it is the responsibility of the user to keep track of them. That is best accomplished through disciplined notation. In source code we use monogram notation where capital A is used to designate a spatial acceleration quantity. The same monogram notation rules for SpatialVelocity are also used for SpatialAcceleration. That is, the spatial acceleration of a frame Y measured in X and expressed in E is denoted withA_XY_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.[Mitiguy 2016] Mitiguy, P., 2016. Advanced Dynamics & Motion Simulation.
-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialAcceleration_[float]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial acceleration are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial acceleration fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialAcceleration_[float], alpha: numpy.ndarray[numpy.float64[3, 1]], a: numpy.ndarray[numpy.float64[3, 1]]) -> None
SpatialAcceleration constructor from an angular acceleration
alpha
and a linear accelerationa
.- __init__(self: pydrake.multibody.math.SpatialAcceleration_[float], A: numpy.ndarray[numpy.float64[6, 1]]) -> None
SpatialAcceleration constructor from an Eigen expression that represents a six-dimensional vector. Under the hood, spatial accelerations are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 constitute the angular acceleration component while elements 3-5 constitute the translational acceleration. The argument
A
in this constructor is the concatenation of the rotational 3D component followed by the translational 3D component. This constructor will assert the size ofA
is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialAcceleration_[float]) → numpy.ndarray[numpy.float64[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialAcceleration_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialAcceleration_[float]) → pydrake.multibody.math.SpatialAcceleration_[float]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialAcceleration_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialAcceleration_[float]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
pydrake.multibody.math.
SpatialForce
¶
-
template
pydrake.multibody.math.
SpatialForce_
¶ Instantiations:
SpatialForce_[float]
,SpatialForce_[AutoDiffXd]
,SpatialForce_[Expression]
-
class
SpatialForce_[float]
¶ This class is used to represent a spatial force (also called a wrench) that combines both rotational (torque) and translational force components. Spatial forces are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the torque component while elements 3-5 are the force component. Both vectors must be expressed in the same frame, and the translational force is applied to a particular point of a body, but neither the frame nor the point are stored with a SpatialForce object; they must be understood from context. It is the responsibility of the user to keep track of the application point and the expressed-in frame. That is best accomplished through disciplined notation. In source code we use monogram notation where capital F is used to designate a spatial force quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write a particular spatial force asF_Bp_E
where the_E
suffix indicates that the expressed-in frame is E. This symbol represents a torque applied to body B, and a force applied to point P on B, with both vectors expressed in E. Very often the application point will be the body originBo
; if no point is shown the origin is understood, soF_B_E
meansF_Bo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialForce_[float]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial force are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial force fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialForce_[float], tau: numpy.ndarray[numpy.float64[3, 1]], f: numpy.ndarray[numpy.float64[3, 1]]) -> None
SpatialForce constructor from a torque
tau
and a forcef
.- __init__(self: pydrake.multibody.math.SpatialForce_[float], F: numpy.ndarray[numpy.float64[6, 1]]) -> None
SpatialForce constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of F is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialForce_[float]) → numpy.ndarray[numpy.float64[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialForce_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialForce_[float]) → pydrake.multibody.math.SpatialForce_[float]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialForce_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialForce_[float]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
class
-
class
pydrake.multibody.math.
SpatialForce_[AutoDiffXd]
¶ This class is used to represent a spatial force (also called a wrench) that combines both rotational (torque) and translational force components. Spatial forces are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the torque component while elements 3-5 are the force component. Both vectors must be expressed in the same frame, and the translational force is applied to a particular point of a body, but neither the frame nor the point are stored with a SpatialForce object; they must be understood from context. It is the responsibility of the user to keep track of the application point and the expressed-in frame. That is best accomplished through disciplined notation. In source code we use monogram notation where capital F is used to designate a spatial force quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write a particular spatial force asF_Bp_E
where the_E
suffix indicates that the expressed-in frame is E. This symbol represents a torque applied to body B, and a force applied to point P on B, with both vectors expressed in E. Very often the application point will be the body originBo
; if no point is shown the origin is understood, soF_B_E
meansF_Bo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialForce_[AutoDiffXd]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial force are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial force fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialForce_[AutoDiffXd], tau: numpy.ndarray[object[3, 1]], f: numpy.ndarray[object[3, 1]]) -> None
SpatialForce constructor from a torque
tau
and a forcef
.- __init__(self: pydrake.multibody.math.SpatialForce_[AutoDiffXd], F: numpy.ndarray[object[6, 1]]) -> None
SpatialForce constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of F is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialForce_[AutoDiffXd]) → numpy.ndarray[object[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialForce_[AutoDiffXd]) → numpy.ndarray[object[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialForce_[AutoDiffXd]) → pydrake.multibody.math.SpatialForce_[AutoDiffXd]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialForce_[AutoDiffXd]) → numpy.ndarray[object[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialForce_[AutoDiffXd]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
class
pydrake.multibody.math.
SpatialForce_[Expression]
¶ This class is used to represent a spatial force (also called a wrench) that combines both rotational (torque) and translational force components. Spatial forces are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the torque component while elements 3-5 are the force component. Both vectors must be expressed in the same frame, and the translational force is applied to a particular point of a body, but neither the frame nor the point are stored with a SpatialForce object; they must be understood from context. It is the responsibility of the user to keep track of the application point and the expressed-in frame. That is best accomplished through disciplined notation. In source code we use monogram notation where capital F is used to designate a spatial force quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write a particular spatial force asF_Bp_E
where the_E
suffix indicates that the expressed-in frame is E. This symbol represents a torque applied to body B, and a force applied to point P on B, with both vectors expressed in E. Very often the application point will be the body originBo
; if no point is shown the origin is understood, soF_B_E
meansF_Bo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialForce_[Expression]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial force are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial force fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialForce_[Expression], tau: numpy.ndarray[object[3, 1]], f: numpy.ndarray[object[3, 1]]) -> None
SpatialForce constructor from a torque
tau
and a forcef
.- __init__(self: pydrake.multibody.math.SpatialForce_[Expression], F: numpy.ndarray[object[6, 1]]) -> None
SpatialForce constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of F is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialForce_[Expression]) → numpy.ndarray[object[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialForce_[Expression]) → numpy.ndarray[object[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialForce_[Expression]) → pydrake.multibody.math.SpatialForce_[Expression]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialForce_[Expression]) → numpy.ndarray[object[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialForce_[Expression]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
class
pydrake.multibody.math.
SpatialForce_[float]
¶ This class is used to represent a spatial force (also called a wrench) that combines both rotational (torque) and translational force components. Spatial forces are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the torque component while elements 3-5 are the force component. Both vectors must be expressed in the same frame, and the translational force is applied to a particular point of a body, but neither the frame nor the point are stored with a SpatialForce object; they must be understood from context. It is the responsibility of the user to keep track of the application point and the expressed-in frame. That is best accomplished through disciplined notation. In source code we use monogram notation where capital F is used to designate a spatial force quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write a particular spatial force asF_Bp_E
where the_E
suffix indicates that the expressed-in frame is E. This symbol represents a torque applied to body B, and a force applied to point P on B, with both vectors expressed in E. Very often the application point will be the body originBo
; if no point is shown the origin is understood, soF_B_E
meansF_Bo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialForce_[float]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial force are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial force fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialForce_[float], tau: numpy.ndarray[numpy.float64[3, 1]], f: numpy.ndarray[numpy.float64[3, 1]]) -> None
SpatialForce constructor from a torque
tau
and a forcef
.- __init__(self: pydrake.multibody.math.SpatialForce_[float], F: numpy.ndarray[numpy.float64[6, 1]]) -> None
SpatialForce constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of F is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialForce_[float]) → numpy.ndarray[numpy.float64[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialForce_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialForce_[float]) → pydrake.multibody.math.SpatialForce_[float]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialForce_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialForce_[float]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
pydrake.multibody.math.
SpatialMomentum
¶
-
template
pydrake.multibody.math.
SpatialMomentum_
¶ Instantiations:
SpatialMomentum_[float]
,SpatialMomentum_[AutoDiffXd]
,SpatialMomentum_[Expression]
-
class
SpatialMomentum_[float]
¶ This class is used to represent the spatial momentum of a particle, system of particles or body (whether rigid or soft.) The linear momentum
l_NS
of a system of particles S in a reference frame N is defined by:l_NS = ∑l_NQi = ∑mᵢv_NQi
where
mᵢ
andv_NQi
are the mass and linear velocity (in frame N) of the i-th particle in the system, respectively. Their productl_NQi = mᵢv_NQi
is the linear momentum of the i-th particle in the N reference frame. The angular momentumh_NSp
of a system of particles S in a reference frame N about an arbitrary point P is defined by:h_NSp = ∑ p_PQi x l_NQi
where
p_PQi
is the position vector from point P to the i-th particle positionQi
. The definitions above extend to a continuum of particles as:h_NSp = ∫p_PQ(r) x v_NQ(r) ρ(r)d³r l_NS = ∫v_NQ(r) ρ(r)d³r
where
ρ(r)
is the density of the body at each material locationr
. In particular, the continuum version above also applies to rigid bodies.Spatial momenta are elements of F⁶ (see [Featherstone 2008]) that combine both rotational (angular momentum) and translational (linear momentum) components. Spatial momenta are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the angular momentum component while elements 3-5 are the linear momentum component. As with any other spatial vector, both vector components must be expressed in the same frame.
Neither the expressed-in frame nor the about-point are stored with a SpatialMomentum object; they must be understood from context. It is the responsibility of the user to keep track of the about-point and the expressed-in frame. That is best accomplished through disciplined notation. In source code we use monogram notation where L is used to designate a spatial momentum quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write as \([^NL^{S/B_P}]_E\), which appears in code asL_NBp_E
, the spatial momentum of a body B in a reference frame N, about a point P and, expressed in frame E. Very often the about-point will be the body originBo
; if no point is shown the origin is understood, thusL_NB_E
meansL_NBo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.- [Featherstone 2008] Featherstone, R., 2008. Rigid body dynamics
- algorithms. Springer.
-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[float]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial momentum are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial momentum fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[float], h: numpy.ndarray[numpy.float64[3, 1]], l: numpy.ndarray[numpy.float64[3, 1]]) -> None
SpatialMomentum constructor from an angular momentum h and a linear momentum l.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[float], L: numpy.ndarray[numpy.float64[6, 1]]) -> None
SpatialMomentum constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of L is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialMomentum_[float]) → numpy.ndarray[numpy.float64[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialMomentum_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialMomentum_[float]) → pydrake.multibody.math.SpatialMomentum_[float]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialMomentum_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialMomentum_[float]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
class
-
class
pydrake.multibody.math.
SpatialMomentum_[AutoDiffXd]
¶ This class is used to represent the spatial momentum of a particle, system of particles or body (whether rigid or soft.) The linear momentum
l_NS
of a system of particles S in a reference frame N is defined by:l_NS = ∑l_NQi = ∑mᵢv_NQi
where
mᵢ
andv_NQi
are the mass and linear velocity (in frame N) of the i-th particle in the system, respectively. Their productl_NQi = mᵢv_NQi
is the linear momentum of the i-th particle in the N reference frame. The angular momentumh_NSp
of a system of particles S in a reference frame N about an arbitrary point P is defined by:h_NSp = ∑ p_PQi x l_NQi
where
p_PQi
is the position vector from point P to the i-th particle positionQi
. The definitions above extend to a continuum of particles as:h_NSp = ∫p_PQ(r) x v_NQ(r) ρ(r)d³r l_NS = ∫v_NQ(r) ρ(r)d³r
where
ρ(r)
is the density of the body at each material locationr
. In particular, the continuum version above also applies to rigid bodies.Spatial momenta are elements of F⁶ (see [Featherstone 2008]) that combine both rotational (angular momentum) and translational (linear momentum) components. Spatial momenta are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the angular momentum component while elements 3-5 are the linear momentum component. As with any other spatial vector, both vector components must be expressed in the same frame.
Neither the expressed-in frame nor the about-point are stored with a SpatialMomentum object; they must be understood from context. It is the responsibility of the user to keep track of the about-point and the expressed-in frame. That is best accomplished through disciplined notation. In source code we use monogram notation where L is used to designate a spatial momentum quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write as \([^NL^{S/B_P}]_E\), which appears in code asL_NBp_E
, the spatial momentum of a body B in a reference frame N, about a point P and, expressed in frame E. Very often the about-point will be the body originBo
; if no point is shown the origin is understood, thusL_NB_E
meansL_NBo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.- [Featherstone 2008] Featherstone, R., 2008. Rigid body dynamics
- algorithms. Springer.
-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[AutoDiffXd]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial momentum are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial momentum fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[AutoDiffXd], h: numpy.ndarray[object[3, 1]], l: numpy.ndarray[object[3, 1]]) -> None
SpatialMomentum constructor from an angular momentum h and a linear momentum l.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[AutoDiffXd], L: numpy.ndarray[object[6, 1]]) -> None
SpatialMomentum constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of L is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialMomentum_[AutoDiffXd]) → numpy.ndarray[object[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialMomentum_[AutoDiffXd]) → numpy.ndarray[object[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialMomentum_[AutoDiffXd]) → pydrake.multibody.math.SpatialMomentum_[AutoDiffXd]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialMomentum_[AutoDiffXd]) → numpy.ndarray[object[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialMomentum_[AutoDiffXd]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
class
pydrake.multibody.math.
SpatialMomentum_[Expression]
¶ This class is used to represent the spatial momentum of a particle, system of particles or body (whether rigid or soft.) The linear momentum
l_NS
of a system of particles S in a reference frame N is defined by:l_NS = ∑l_NQi = ∑mᵢv_NQi
where
mᵢ
andv_NQi
are the mass and linear velocity (in frame N) of the i-th particle in the system, respectively. Their productl_NQi = mᵢv_NQi
is the linear momentum of the i-th particle in the N reference frame. The angular momentumh_NSp
of a system of particles S in a reference frame N about an arbitrary point P is defined by:h_NSp = ∑ p_PQi x l_NQi
where
p_PQi
is the position vector from point P to the i-th particle positionQi
. The definitions above extend to a continuum of particles as:h_NSp = ∫p_PQ(r) x v_NQ(r) ρ(r)d³r l_NS = ∫v_NQ(r) ρ(r)d³r
where
ρ(r)
is the density of the body at each material locationr
. In particular, the continuum version above also applies to rigid bodies.Spatial momenta are elements of F⁶ (see [Featherstone 2008]) that combine both rotational (angular momentum) and translational (linear momentum) components. Spatial momenta are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the angular momentum component while elements 3-5 are the linear momentum component. As with any other spatial vector, both vector components must be expressed in the same frame.
Neither the expressed-in frame nor the about-point are stored with a SpatialMomentum object; they must be understood from context. It is the responsibility of the user to keep track of the about-point and the expressed-in frame. That is best accomplished through disciplined notation. In source code we use monogram notation where L is used to designate a spatial momentum quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write as \([^NL^{S/B_P}]_E\), which appears in code asL_NBp_E
, the spatial momentum of a body B in a reference frame N, about a point P and, expressed in frame E. Very often the about-point will be the body originBo
; if no point is shown the origin is understood, thusL_NB_E
meansL_NBo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.- [Featherstone 2008] Featherstone, R., 2008. Rigid body dynamics
- algorithms. Springer.
-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[Expression]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial momentum are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial momentum fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[Expression], h: numpy.ndarray[object[3, 1]], l: numpy.ndarray[object[3, 1]]) -> None
SpatialMomentum constructor from an angular momentum h and a linear momentum l.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[Expression], L: numpy.ndarray[object[6, 1]]) -> None
SpatialMomentum constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of L is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialMomentum_[Expression]) → numpy.ndarray[object[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialMomentum_[Expression]) → numpy.ndarray[object[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialMomentum_[Expression]) → pydrake.multibody.math.SpatialMomentum_[Expression]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialMomentum_[Expression]) → numpy.ndarray[object[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialMomentum_[Expression]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
class
pydrake.multibody.math.
SpatialMomentum_[float]
¶ This class is used to represent the spatial momentum of a particle, system of particles or body (whether rigid or soft.) The linear momentum
l_NS
of a system of particles S in a reference frame N is defined by:l_NS = ∑l_NQi = ∑mᵢv_NQi
where
mᵢ
andv_NQi
are the mass and linear velocity (in frame N) of the i-th particle in the system, respectively. Their productl_NQi = mᵢv_NQi
is the linear momentum of the i-th particle in the N reference frame. The angular momentumh_NSp
of a system of particles S in a reference frame N about an arbitrary point P is defined by:h_NSp = ∑ p_PQi x l_NQi
where
p_PQi
is the position vector from point P to the i-th particle positionQi
. The definitions above extend to a continuum of particles as:h_NSp = ∫p_PQ(r) x v_NQ(r) ρ(r)d³r l_NS = ∫v_NQ(r) ρ(r)d³r
where
ρ(r)
is the density of the body at each material locationr
. In particular, the continuum version above also applies to rigid bodies.Spatial momenta are elements of F⁶ (see [Featherstone 2008]) that combine both rotational (angular momentum) and translational (linear momentum) components. Spatial momenta are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the angular momentum component while elements 3-5 are the linear momentum component. As with any other spatial vector, both vector components must be expressed in the same frame.
Neither the expressed-in frame nor the about-point are stored with a SpatialMomentum object; they must be understood from context. It is the responsibility of the user to keep track of the about-point and the expressed-in frame. That is best accomplished through disciplined notation. In source code we use monogram notation where L is used to designate a spatial momentum quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write as \([^NL^{S/B_P}]_E\), which appears in code asL_NBp_E
, the spatial momentum of a body B in a reference frame N, about a point P and, expressed in frame E. Very often the about-point will be the body originBo
; if no point is shown the origin is understood, thusL_NB_E
meansL_NBo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.- [Featherstone 2008] Featherstone, R., 2008. Rigid body dynamics
- algorithms. Springer.
-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[float]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial momentum are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial momentum fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[float], h: numpy.ndarray[numpy.float64[3, 1]], l: numpy.ndarray[numpy.float64[3, 1]]) -> None
SpatialMomentum constructor from an angular momentum h and a linear momentum l.
- __init__(self: pydrake.multibody.math.SpatialMomentum_[float], L: numpy.ndarray[numpy.float64[6, 1]]) -> None
SpatialMomentum constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of L is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialMomentum_[float]) → numpy.ndarray[numpy.float64[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialMomentum_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialMomentum_[float]) → pydrake.multibody.math.SpatialMomentum_[float]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialMomentum_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialMomentum_[float]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
pydrake.multibody.math.
SpatialVelocity
¶
-
template
pydrake.multibody.math.
SpatialVelocity_
¶ Instantiations:
SpatialVelocity_[float]
,SpatialVelocity_[AutoDiffXd]
,SpatialVelocity_[Expression]
-
class
SpatialVelocity_[float]
¶ This class is used to represent a spatial velocity (also called a twist) that combines rotational (angular) and translational (linear) velocity components. Spatial velocities are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the angular velocity component while elements 3-5 are the translational velocity. Spatial velocities represent the motion of a “moving frame” B measured with respect to a “measured-in” frame A. In addition, the two contained vectors must be expressed in the same “expressed-in” frame E, which may be distinct from either A or B. Finally, while angular velocity is identical for any frame fixed to a rigid body, translational velocity refers to a particular point. Only the vector values are stored in a SpatialVelocity object; the three frames and the point must be understood from context. It is the responsibility of the user to keep track of them. That is best accomplished through disciplined notation. In source code we use monogram notation where capital V is used to designate a spatial velocity quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write a particular spatial velocity asV_ABp_E
where the_E
suffix indicates that the expressed-in frame is E. This symbol represents the angular velocity of frame B in frame A, and the translational velocity of point P in A, where P is fixed to frame B, with both vectors expressed in E. Very often the point of interest will be the body originBo
; if no point is shown the origin is understood, soV_AB_E
meansV_ABo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialVelocity_[float]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial velocity are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial velocity fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialVelocity_[float], w: numpy.ndarray[numpy.float64[3, 1]], v: numpy.ndarray[numpy.float64[3, 1]]) -> None
SpatialVelocity constructor from an angular velocity
w
and a linear velocityv
.- __init__(self: pydrake.multibody.math.SpatialVelocity_[float], V: numpy.ndarray[numpy.float64[6, 1]]) -> None
SpatialVelocity constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of V is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialVelocity_[float]) → numpy.ndarray[numpy.float64[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialVelocity_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialVelocity_[float]) → pydrake.multibody.math.SpatialVelocity_[float]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialVelocity_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialVelocity_[float]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
class
-
class
pydrake.multibody.math.
SpatialVelocity_[AutoDiffXd]
¶ This class is used to represent a spatial velocity (also called a twist) that combines rotational (angular) and translational (linear) velocity components. Spatial velocities are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the angular velocity component while elements 3-5 are the translational velocity. Spatial velocities represent the motion of a “moving frame” B measured with respect to a “measured-in” frame A. In addition, the two contained vectors must be expressed in the same “expressed-in” frame E, which may be distinct from either A or B. Finally, while angular velocity is identical for any frame fixed to a rigid body, translational velocity refers to a particular point. Only the vector values are stored in a SpatialVelocity object; the three frames and the point must be understood from context. It is the responsibility of the user to keep track of them. That is best accomplished through disciplined notation. In source code we use monogram notation where capital V is used to designate a spatial velocity quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write a particular spatial velocity asV_ABp_E
where the_E
suffix indicates that the expressed-in frame is E. This symbol represents the angular velocity of frame B in frame A, and the translational velocity of point P in A, where P is fixed to frame B, with both vectors expressed in E. Very often the point of interest will be the body originBo
; if no point is shown the origin is understood, soV_AB_E
meansV_ABo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialVelocity_[AutoDiffXd]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial velocity are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial velocity fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialVelocity_[AutoDiffXd], w: numpy.ndarray[object[3, 1]], v: numpy.ndarray[object[3, 1]]) -> None
SpatialVelocity constructor from an angular velocity
w
and a linear velocityv
.- __init__(self: pydrake.multibody.math.SpatialVelocity_[AutoDiffXd], V: numpy.ndarray[object[6, 1]]) -> None
SpatialVelocity constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of V is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialVelocity_[AutoDiffXd]) → numpy.ndarray[object[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialVelocity_[AutoDiffXd]) → numpy.ndarray[object[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialVelocity_[AutoDiffXd]) → pydrake.multibody.math.SpatialVelocity_[AutoDiffXd]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialVelocity_[AutoDiffXd]) → numpy.ndarray[object[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialVelocity_[AutoDiffXd]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
class
pydrake.multibody.math.
SpatialVelocity_[Expression]
¶ This class is used to represent a spatial velocity (also called a twist) that combines rotational (angular) and translational (linear) velocity components. Spatial velocities are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the angular velocity component while elements 3-5 are the translational velocity. Spatial velocities represent the motion of a “moving frame” B measured with respect to a “measured-in” frame A. In addition, the two contained vectors must be expressed in the same “expressed-in” frame E, which may be distinct from either A or B. Finally, while angular velocity is identical for any frame fixed to a rigid body, translational velocity refers to a particular point. Only the vector values are stored in a SpatialVelocity object; the three frames and the point must be understood from context. It is the responsibility of the user to keep track of them. That is best accomplished through disciplined notation. In source code we use monogram notation where capital V is used to designate a spatial velocity quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write a particular spatial velocity asV_ABp_E
where the_E
suffix indicates that the expressed-in frame is E. This symbol represents the angular velocity of frame B in frame A, and the translational velocity of point P in A, where P is fixed to frame B, with both vectors expressed in E. Very often the point of interest will be the body originBo
; if no point is shown the origin is understood, soV_AB_E
meansV_ABo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialVelocity_[Expression]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial velocity are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial velocity fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialVelocity_[Expression], w: numpy.ndarray[object[3, 1]], v: numpy.ndarray[object[3, 1]]) -> None
SpatialVelocity constructor from an angular velocity
w
and a linear velocityv
.- __init__(self: pydrake.multibody.math.SpatialVelocity_[Expression], V: numpy.ndarray[object[6, 1]]) -> None
SpatialVelocity constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of V is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialVelocity_[Expression]) → numpy.ndarray[object[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialVelocity_[Expression]) → numpy.ndarray[object[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialVelocity_[Expression]) → pydrake.multibody.math.SpatialVelocity_[Expression]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialVelocity_[Expression]) → numpy.ndarray[object[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialVelocity_[Expression]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-
-
class
pydrake.multibody.math.
SpatialVelocity_[float]
¶ This class is used to represent a spatial velocity (also called a twist) that combines rotational (angular) and translational (linear) velocity components. Spatial velocities are 6-element quantities that are pairs of ordinary 3-vectors. Elements 0-2 are the angular velocity component while elements 3-5 are the translational velocity. Spatial velocities represent the motion of a “moving frame” B measured with respect to a “measured-in” frame A. In addition, the two contained vectors must be expressed in the same “expressed-in” frame E, which may be distinct from either A or B. Finally, while angular velocity is identical for any frame fixed to a rigid body, translational velocity refers to a particular point. Only the vector values are stored in a SpatialVelocity object; the three frames and the point must be understood from context. It is the responsibility of the user to keep track of them. That is best accomplished through disciplined notation. In source code we use monogram notation where capital V is used to designate a spatial velocity quantity. We write a point P fixed to body (or frame) B as \(B_P\) which appears in code and comments as
Bp
. Then we write a particular spatial velocity asV_ABp_E
where the_E
suffix indicates that the expressed-in frame is E. This symbol represents the angular velocity of frame B in frame A, and the translational velocity of point P in A, where P is fixed to frame B, with both vectors expressed in E. Very often the point of interest will be the body originBo
; if no point is shown the origin is understood, soV_AB_E
meansV_ABo_E
. For a more detailed introduction on spatial vectors and the monogram notation please refer to section multibody_spatial_vectors.-
__init__
(*args, **kwargs)¶ Overloaded function.
- __init__(self: pydrake.multibody.math.SpatialVelocity_[float]) -> None
Default constructor. In Release builds the elements of the newly constructed spatial velocity are left uninitialized resulting in a zero cost operation. However in Debug builds those entries are set to NaN so that operations using this uninitialized spatial velocity fail fast, allowing fast bug detection.
- __init__(self: pydrake.multibody.math.SpatialVelocity_[float], w: numpy.ndarray[numpy.float64[3, 1]], v: numpy.ndarray[numpy.float64[3, 1]]) -> None
SpatialVelocity constructor from an angular velocity
w
and a linear velocityv
.- __init__(self: pydrake.multibody.math.SpatialVelocity_[float], V: numpy.ndarray[numpy.float64[6, 1]]) -> None
SpatialVelocity constructor from an Eigen expression that represents a six-dimensional vector. This constructor will assert the size of V is six (6) at compile-time for fixed sized Eigen expressions and at run-time for dynamic sized Eigen expressions.
-
get_coeffs
(self: pydrake.multibody.math.SpatialVelocity_[float]) → numpy.ndarray[numpy.float64[6, 1]]¶ Returns a constant reference to the underlying storage.
-
rotational
(self: pydrake.multibody.math.SpatialVelocity_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the rotational component of this spatial vector.
-
SetZero
(self: pydrake.multibody.math.SpatialVelocity_[float]) → pydrake.multibody.math.SpatialVelocity_[float]¶ Sets both rotational and translational components of
this
SpatialVector to zero.
-
translational
(self: pydrake.multibody.math.SpatialVelocity_[float]) → numpy.ndarray[numpy.float64[3, 1]]¶ Const access to the translational component of this spatial vector.
-
static
Zero
() → pydrake.multibody.math.SpatialVelocity_[float]¶ Factory to create a zero SpatialVector, i.e. rotational and translational components are both zero.
-


The two most commonly grown are the highly regarded arabica, and the less sophisticated but stronger and more hardy robusta. Once ripe, coffee berries are picked, processed, and dried. Dried coffee seeds (referred to as beans) are roasted to varying degrees, depending on the desired flavor. Roasted beans are ground and brewed with near boiling water to produce coffee as a beverage.
Coffee is one of the most popular drinks in the world.
Coffee is slightly acidic and can have a stimulating effect on humans because of its caffeine content.


beats solo 2 magenta
Beats Solo2 headphones have a wide range of dynamic sound for a more immersive, emotional listening experience
beats solo 2 blood orange
Beats Solo2 headphones have a wide range of dynamic sound for a more immersive, emotional listening experience
beats solo 2 olive green
Beats Solo2 headphones have a wide range of dynamic sound for a more immersive, emotional listening experience


@* * Copyright 2023 HM Revenue & Customs * * Licensed under the Apache License, Version 2.0 (the "License"); * you may not use this file except in compliance with the License. * You may obtain a copy of the License at * * http://www.apache.org/licenses/LICENSE-2.0 * * Unless required by applicable law or agreed to in writing, software * distributed under the License is distributed on an "AS IS" BASIS, * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. * See the License for the specific language governing permissions and * limitations under the License. *@ @this() @(form: Form[_], id: String, fields: Html )(implicit messages: Messages)


Climbing to the top of Africa is an incomparable experience. Mount Kilimanjaro was declared a world heritage site by UNESCO in 1989. This mountain is one of the largest volcanoes in the world, which has been idle for centuries. Mount Killimanjaro standing at 5,895m (19.341″”) is the tallest mountain in Africa and the highest free standing summit in the world. The extraordinary fact about this gigantic natural monument is that it has multiple routes therefore allowing everyone to summit, whether they have had mountaineering experience or not.
Afri-raha Tours offers the best possible expeditions to the majestic Kilimanjaro. In addition to traditional routes, we also offer unique and undiscovered trails such as Shira, Machame or Umbwe where you will climb by a team of guides and porters which was seleted by the best specialists on the field. Climbing groups are accompanied by competent assistant guides, all of which are certified as first responders in wild rescue and cardio-vascular resuscitation by the most notorious associations and schools of the world.Their combined experience from hundreds of ascents gives this company a solid foundation, in part because they continue to educate all Afri-raha staff on a quarterly basis to ensure uncompromising security and your unforgettable experience. Our experienced team will be able to encourage you and help you reach this summit where the 360 ° panoramatic view is the trully a breathtaking experience.
Afri-raha Tours makes every effort to make your dream come true. We are prepared and experienced to accompany you to the top of Africa. At the end of each day, the Afri-raha Tanzania Tours team will set up camp in a selected location, including the tent that serves as dining room, with tables and chairs. You will find that despite the rustic limitations of the place, we are able to offer you high quality services, and a very pleasant and soothing gastronomic experience. The luxurious itineraries of these expeditions (If you choose them) will add extra comfort to the severity of this great challenge. In fact, we have put everything in order to offer you the best of what Tanzania can offer you.
Good equipment is extremely important to the success, enjoyment, comfort and safety of your climb. We suggest that you only bring the essentials because excessive packing is a problem for you as well as for the team of porters who accompany you. Your travel bag should be limited to 15kg. Please consult the list of the following items to take with you. Feel free to contact us if you have questions or just for advice.
We simply offer the best that nature has to show. Mount Kilimanjaro is Africa’s peak, and is in a unique environment in the world. The weather conditions are very variable, as much from one point to another of the tracks, from dawn to dawn. Despite the fact that it is difficult to predict the weather, our expertise allows us to recommend certain equipment and clothing to maximize your comfort. The temperature above 2,500 m / 8,000 ‘varies between 15 ° C and 25 ° C (60 ° F and 80 ° F), while at night the mercury dives below 0 ° C (32 ° F) .

Travel bag, identified (for your regular clothes, this bag will be left at the hotel).
Backpack from 24L to 32L (1,500 cu³ to 2000 cu³), max. 5kg, identified.
Normal underwear (from 4 to 7, suggested synthetic materials because it is lighter, easier to wash and faster to dry).
Lightweight clothing – long-sleeved top and sticky stockings (suggested synthetic materials, polyester, wool or synthetic).
Turtleneck or long-sleeved shirt
Long sleeve sweater
Long sleeved or wool synthetic vest.
Warm synthetic coat (padded 10-12oz or 15-20oz).
Waterproof windproof Gore-tex jacket that breathes properly
Resistant and waterproof poncho to protect the backpack and photographic equipment
Hiking pants (light, loose and preferably dark).
Overpants (synthetic, velvet or light wool, loose and preferably dark).
Gore-tex rain / wind pants.
Walking shorts (preferably synthetic)
Wide-brimmed sunhat (preferably ones with under-chin laces to cope with strong wind) and sunscreen.
Hood with facial protection (synthetic or wool).
Scarf (as sunscreen and sponge for sweat).
Waterproof mittens.
Silk gloves
Thermal bottom (synthetic or wool).
Synthetic sports socks (for the tropical portion of the expedition).
Synthetic stockings
Hiking boots (preferably rigid, leather and waterproof).
Shoes / sneakers (for the camp)
Leggings (to keep your feet free from dust)
Partition sleeping bag (4 seasons or certified -20 ° C).
Inflatable mattress
Tipping is optional, but it is well accepted by the team as an appreciation of the service you have received to your level of quality and satisfaction. It should be given at the end of the trip only.
Here’s a suggestion of what the customer usually gives, but this is not a mandatory or limited standard.
For the driver-guide, $ 5 - 15 USD per person per day. If you also want to give to other people, such as local guides, we suggest $ 10- 15 USD per person per day. Porter in hotels $ 0.5 - 1 USD per luggage and $ 1 to $ 2 in the tip box of the hotel.
There is no obligation on your part.
The best way to prepare for high mountianeering is to climb high altitudes. Although it’s hard for most people, remember that for high altitude climbs, the longer you take to climb the better it is for your well being. Whether for a hike 2,000″” up the local hill or climbing great mountains, just hiking is effective. This will also allow you to get used to your backpack and your hiking boots.
Running and cycling are also very good activities to prepare you for mountiaineering and they allow you to be outside so you can test your equipment. Excercising in gyms and training rooms is also good but it is better to exercise in the open air. Do endurance training and not strength training, your endurance is what that will be tested most. An adequate training regimen is to maintain 80% of your maximum heart rate (220 minus your age) for an hour, three to four days a week. Remember that high altitude mountaineering requires acclimatization and a strong mind is as important as the strength of the body. If you are fit enough and choose a climbing route that allows a lot of time to acclimatize, you have the formula for success.
Remember, it is not only about the altitude but also your attitude that will help you succeed on your climb.
When en route to the summit, if you feel breathless, stop and breathe until you feel better. Once your heart rate is back to normal, you can continue.  If you feel bad, you have headaches, nausea, extreme tiredness or loss of appetite, you may have to go down or stay where you are. In any case, your guide is there to help you and do not hesitate to tell him about your condition.
Above all, do not worry about being abandoned on the mountain. Do not be afraid to stop and adjust to your breathing and walking pace instead of wanting to follow others who have a higher endurance. Drink plenty of water throughout the day, between 3L to 5L. Above all, walk at your own pace, this is the key to success for a successful ascent.
Our guides, assistants and porters are specially trained to keep an eye on you and react at the first sign of discomfort. Trust them and listen to their advice. If they advise you to stop for a while, listen to them and do not force your physical limit. They are experienced and know exactly how to react to the challenges you might face.


ROSS is an acronym for Rensselaer's Optimistic Simulation System. It is a parallel discrete-event simulator that executes on shared-memory multiprocessor systems. ROSS is geared for running large-scale simulation models (i.e., 100K to even 1 million object models). The synchronization mechanism is based on Time Warp. Time Warp is an optimistic synchronization mechanism develop by Jefferson and Sowizral [10, 11] used in the parallelization of discrete-event simulation. The distributed simulator consists of a collection of logical processes or LPs, each modeling a distinct component of the system being modeled, e.g., a server in a queuing network. LPs communicate by exchanging timestamped event messages, e.g., denoting the arrival of a new job at that server. The Time Warp mechanism uses a detection-and-recovery protocol to synchronize the computation. Any time an LP determines that it has processed events out of timestamp order, it "rolls back" those events, and re-executes them. For a detailed discussion of Time Warp as well as other parallel simulation protocols we refer the reader to [8] ROSS was modeled after a Time Warp simulator called GTW or Georgia Tech Time Warp[7]. ROSS helped to demonstrate that Time Warp simulators can be run efficiently both in terms of speed and memory usage relative to a high-performance sequential simulator. To achieve high parallel performance, ROSS uses a technique call Reverse Computation. Here, the roll back mechanism in the optimistic simulator is realized not by classic state-saving, but by literally allowing to the greatest possible extent events to be reverse. Thus, as models are developed for parallel execution, both the forward and reverse execution code must be written. Currently, both are done by hand. We are investigating automatic methods that are able to generate the reverse execution code using only the forward execution code as input. For more information on ROSS and Reverse Computation we refer the interested reader to [4, 5]. Both of these text are provided as additional reading in the ROSS distribution.
Copyright (c) 2013, Rensselaer Polytechnic Institute All rights reserved.
Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met:
Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer.
Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution.
Neither the name of Rensselaer Polytechnic Institute nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.


- onActivityResult(int, int, Intent) - Method in class com.cmput301w18t07.taskasker.AddTaskActivity
-
Purpose:
After inserting a photo checks the size and sets it to the task.
- onActivityResult(int, int, Intent) - Method in class com.cmput301w18t07.taskasker.LoginActivity
-
Purpose:
When an new account activity sends back a result set the username edit text to the new username
- onActivityResult(int, int, Intent) - Method in class com.cmput301w18t07.taskasker.MainActivity
-
Purpose:
after activity do certain action
- onActivityResult(int, int, Intent) - Method in class com.cmput301w18t07.taskasker.MyTaskDetailsActivity
-
Purpose:
After accept bid activity change the details of the task.
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.AcceptBidActivity
-
Purpose:
Sets the view when Accept Bid activity is started.
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.AddTaskActivity
-
Purpose:
Sets the view when Add task activity is started.
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.BidOnTaskActivity
-
Purpose:
Sets up the view when the add a bid activity is started
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.EditProfileActivity
-
Purpose:
Sets the view when edit profile activity is started.
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.EditTask
-
Purpose:
Sets up the view when the edit task activity is started
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.LoginActivity
-
Purpose:
Sets the view when login activity is started.
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.MainActivity
-
Purpose:
Called when the activity is first created.
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.MapActivity
-
Purpose:
Sets the initial view for the activity
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.MyTaskDetailsActivity
-
Purpose:
Sets up the view when the task details activity is started
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.NewAccountActivity
-
Purpose:
Sets up the view when the new account activity is started
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.ProfileActivity
-
Purpose:
Sets up the view when the profile activity is started
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.SearchActivity
-
Purpose:
Sets the view when Search activity is started.
- onCreate(Bundle) - Method in class com.cmput301w18t07.taskasker.TaskDetailsActivity
-
Purpose:
Sets up the view when the task details activity is started
- onMapReady(GoogleMap) - Method in class com.cmput301w18t07.taskasker.MapActivity
-
Purpose:
Sets the marker on the map
- onResume() - Method in class com.cmput301w18t07.taskasker.LoginActivity
-
Purpose:
When going back to login make sure progress bar is gone
- onResume() - Method in class com.cmput301w18t07.taskasker.MainActivity
-
Purpose:
When main activity is resumed update the task lists.
- onResume() - Method in class com.cmput301w18t07.taskasker.SearchActivity
-
Purpose:
When the search is resumed reset the task list to all open tasks


If you own property within the Prairie Fields subdivision, then you are a member of PF HOA. When you purchased your property in Prairie Fields, you automatically became a member of the PF HOA.
According to www.planersweb.com, an active HOA helps to ensure a neighborhood will remain physically attractive over many years, thus maintaining and often enhancing property values.
Nearly all newer neighborhoods in the Champaign-Urbana area have a Homeowners Association (HOA) to assist in maintaining the grounds around the neighborhood and to help maintain the quality of the development over many years.
The PF HOA was incorporated in 1996 by the developer of Prairie Fields subdivision. From 1996 to 2008, the developer performed and paid for all services of the HOA. Starting in 2009, the developer transitioned the association to a resident run, resident funded HOA, and in the fall of 2009 the residents of Prairie Fields elected a Board of Directors (BOD).
See the Board page.
To volunteer for any committee, attend a committee meeting or email<EMAIL_ADDRESS>Or, email<EMAIL_ADDRESS>to volunteer for the Neighborhood Events committee or to help with one of the HOA events.
The largest budgeted expense is the mowing, fertilizing, and weed control of the grounds around the neighborhood that we maintain- a total of more than 12 acres of grass, trees, berms, ditches, and two detention basins. The budget also includes liability insurance, printing, copying, postage, power bills for the subdivision sign, etc. Just under half of the budget is set aside for capital improvements, which include the costs of repairing HOA owned storm drain tiles and HOA owned sidewalks when repairs are needed, and money for possible capital improvements. You can view the approved budget by going to the board meeting minutes page and clicking on the “financials” link next to the annual meeting date. Monthly statements are available upon request.
Current capital improvements include Prairie Fields signs at the entrances to the subdivision and replacing a portion of the HOA-owned concrete sidewalk at Indigo and Tomaras drainage backs up into the neighbor's lawns. The BOD will weigh the costs and benefits of these and other improvements to determine if they are necessary and/or desirable, and if they can be completed without raising annual dues or jeopardizing our ability to complete required maintenance.
You can review the approved budget by going to the board meeting minutes page and clicking on the “financials” link next to the annual meeting date. That page will pull up a file of the actual budget and descriptions of each of the budget categories.
If you are selling your home in Prairie Fields and need a closing letter, statement of accounts, or other closing documents related to HOA dues, click here to email our accountant.
Prairie Fields is regulated by covenants. There are different covenants for each phase of the Prairie Fields development. Each set of covenants includes a map, showing the location of the properties which that set of covenants applies. Also on the website is the Prairie Fields Homeowners Association Bylaws, adopted in 2008.
Actually, your covenants list covenant enforcement as the responsibility of a developer related committee. The Board of Directors is working to change enforcement so that it is controlled by the Homeowners Association, and a committee will ultimately establish enforcement procedures.
Because each phase of the subdivision has different covenants, the Board of Directors has a committee evaluating consolidating the different covenants into one set which would apply to all homes in PF. The consolidated covenants would have to be approved by 75% of the residents of each phase of PF, which won’t be easy. Email<EMAIL_ADDRESS>to volunteer for the Covenant Consolidation Committee.
The Prairie Fields HOA does not regulate any of these items. The US Supreme Court has ruled that homeowners associations cannot restrict reasonably sized antenna or satallites. However, the Village of Savoy does have restrictions on both Solar Panels and Windmills. Windmills generally must be positioned so that they do not fall onto a neighbor’s property. The Village of Savoy also has restrictions about height of windmills. Also, the FAA regulates airspace within the flight approach to Willard Airport. Contact Dan Davies at the Village of Savoy for more information.
For large purchases, the BOD solicits a minimum of 3 bids. The BOD evaluates bids on the basis of best overall value.
The HOA asks that you keep sidewalks clean and safe, especially for the children walking to school. However, neither the HOA nor the Village of Savoy has any snow removal ordinances.
The street lights in Prairie Fields are owned and maintained by Ameren, and the Village of Savoy “rents” them. Please contact Brett Maue, the Public Works Director/Village Engineer, and he will send a maintenance request to Ameren.
Only if you wish to plant in the right-of-way, which is between the street and sidewalk. In that case, you will need approval from the Village of Savoy Arborist. The Village, if funds are available, can reimburse the property owner for half of the total cost of purchase and installation of the tree up to $100.00 for each tree installed through the Village Right-of-Way Tree Cost Share Program.
If a vehicle is left unattended on the street for more than 7 days it may be towed by the Village of Savoy according to ordinance 8.20.070. Please contact Savoy Building Inspector/Code Enforcement officer, Gary Zinn, for more information.


Before Change
Test siamese singletask model overfits tiny data.
np.random.seed(123)
tf.set_random_seed(123)
g = tf.Graph()
sess = tf.Session(graph=g)
n_tasks = 1
n_feat = 75
max_depth = 4
n_pos = 6
n_neg = 4
test_batch_size = 10
n_train_trials = 80
support_batch_size = n_pos + n_neg
// Load mini log-solubility dataset.
featurizer = dc.feat.ConvMolFeaturizer()
tasks = ["outcome"]
input_file = os.path.join(self.current_dir, "example_classification.csv")
loader = dc.data.CSVLoader(
tasks=tasks, smiles_field="smiles", featurizer=featurizer)
dataset = loader.featurize(input_file)
classification_metric = dc.metrics.Metric(dc.metrics.accuracy_score)
with g.as_default():
support_model = dc.nn.SequentialSupportGraph(n_feat)
// Add layers
// output will be (n_atoms, 64)
support_model.add(dc.nn.GraphConv(64, activation="relu"))
// Need to add batch-norm separately to test/support due to differing
// shapes.
// output will be (n_atoms, 64)
support_model.add_test(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
// output will be (n_atoms, 64)
support_model.add_support(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
support_model.add(dc.nn.GraphPool())
support_model.add_test(dc.nn.GraphGather(test_batch_size))
support_model.add_support(dc.nn.GraphGather(support_batch_size))
with self.test_session() as sess:
model = dc.models.SupportGraphClassifier(
sess, support_model, test_batch_size=test_batch_size,
support_batch_size=support_batch_size, learning_rate=1e-3)
// Fit trained model. Dataset has 6 positives and 4 negatives, so set
// n_pos/n_neg accordingly.
model.fit(dataset, n_episodes_per_epoch=n_train_trials, n_pos=n_pos,
n_neg=n_neg)
model.save()
// Eval model on train. Dataset has 6 positives and 4 negatives, so set
// n_pos/n_neg accordingly. Note that support is *not* excluded (so we
// can measure model has memorized support). Replacement is turned off to
// ensure that support contains full training set. This checks that the
// model has mastered memorization of provided support.
scores, _ = model.evaluate(dataset, classification_metric, n_trials=5,
n_pos=n_pos, n_neg=n_neg,
exclude_support=False)
// Measure performance on 0-th task.
assert scores[0] > .9
def test_attn_lstm_singletask_classification_overfit(self):
Test attn lstm singletask overfits tiny data.
np.random.seed(123)
tf.set_random_seed(123)
After Change
classification_metric = dc.metrics.Metric(dc.metrics.accuracy_score)
support_model = dc.nn.SequentialSupportGraph(n_feat)
// Add layers
// output will be (n_atoms, 64)
support_model.add(dc.nn.GraphConv(64, n_feat, activation="relu"))
// Need to add batch-norm separately to test/support due to differing
// shapes.
// output will be (n_atoms, 64)
support_model.add_test(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
// output will be (n_atoms, 64)
support_model.add_support(dc.nn.BatchNormalization(epsilon=1e-5, mode=1))
support_model.add(dc.nn.GraphPool())
support_model.add_test(dc.nn.GraphGather(test_batch_size))
support_model.add_support(dc.nn.GraphGather(support_batch_size))
model = dc.models.SupportGraphClassifier(
support_model,
test_batch_size=test_batch_size,
support_batch_size=support_batch_size,
learning_rate=1e-3)
// Fit trained model. Dataset has 6 positives and 4 negatives, so set
// n_pos/n_neg accordingly.
model.fit(
dataset, n_episodes_per_epoch=n_train_trials, n_pos=n_pos, n_neg=n_neg)
model.save()
// Eval model on train. Dataset has 6 positives and 4 negatives, so set
// n_pos/n_neg accordingly. Note that support is *not* excluded (so we
// can measure model has memorized support). Replacement is turned off to
// ensure that support contains full training set. This checks that the
// model has mastered memorization of provided support.
scores, _ = model.evaluate(
dataset,
classification_metric,
n_trials=5,
n_pos=n_pos,
n_neg=n_neg,
exclude_support=False)
////////////////////////////////////////////////////////////////////////////////////////////////////////// DEBUG
// TODO(rbharath): Check if something went wrong here...
// Measure performance on 0-th task.


I’m A Celebrity viewers beg Holly Willoughby to return as host
She hosted the show last year with Dec Donnelly
by Rebecca CarterViewers of I'm A Celebrity are begging Holly Willoughby to return as host.
The This Morning presenter host the show last year alongside Dec Donnelly as Ant McPartlin took a break from the spotlight following his drink-drive arrest earlier that year.
She was an instant hit with fans and made ratings soar, but it was only a one-off stint.
Read more: Bookies predict Jacqueline Jossa will win this year's I'm A Celebrity
Ant returned to this year's series with Dec and many viewers were over the moon.
However, some have admitted they preferred the show when Holly was hosting and have shared their thoughts on Twitter.
One person said: "I’m saying it. Holly was better last year with Dec than Ant & Dec this year."
Another wrote: "I love #ImACeleb although I do have to mute it when #antanddec are on. Bring back Holly!"
A third added: "Normally a big fan of Ant and Dec on Celebrity but I really miss Holly, @hollywills at least she had compassion."
However, others weren't thrilled that Ant and Dec are back together.
 I loved Holly but #ImACeleb just isn't I'm a celeb with out them together."
Another wrote: "I love Holly and she did great but... Ant and Dec together are just another level aren't they."
Read more: I'm A Celebrity: Roman Kemp's impressions of Ant and Dec steal the show
Last year's launch episode drew in 11.6 million in the overnight ratings.
It was the most-watched launch since 2013.
Leave us a comment on our Facebook page @EntertainmentDailyFix and let us know what you think of this story.


Welcome to cipher day!
Write a program that can encrypt texts with an alphabetical caesar cipher.
This cipher can ignore numbers, symbols, and whitespace.
For extra credit, add a "decrypt" function to your program!


ITZY confirmed to perform at the 'Melon Music Awards 2019'
by beansssRookie girl group ITZY has just been announced as the second performing artist to attend this year's 'Melon Music Awards 2019'!
So far, the upcoming 'MMA 2019' has only revealed two performing artists of this year's ceremony - BTS and ITZY. The 'MMA 2019' is coming up very soon this November 30 at 7 PM KST at the Gocheok Sky Dome in Seoul, airing live worldwide.
Which other K-Pop artists do you want to see performing at the 'MMA 2019'?


Editor Demo
-
Sometimes, we don't want the compilation to be done each
time a key is pressed, use the compile on demand for that.
The value
compile-on-demand
is a parameter of the
directive, and can be modified dynamically by the user in the UI.
-
In some contexts, the "hot compilation" doesn't work fine
(angular directives for example).
In such a case, the user can use the jsFiddle option which
will open the editor content in jsFiddle.
Use the
js-fiddle
parameter to display it or not
by default, it can still be modified dynamically by the user
<p id="theParagraph">
I am a paragraph which is not loaded when the
javascript compiles
</p>
document.getElementById('theParagraph').innerText='modified';


Tutorials
We encourage everyone to learn the process on working with repositories. Please feel free to look at our tutorials!
-
Cloning a Repository
-
Pulling a Branch
-
Committing and Pushing
We encourage everyone to learn the process on working with repositories. Please feel free to look at our tutorials!


Each paragraph tag has the "commentable-section" class, making it a section which can be commented on after you've
initialized a new SideComments object and pointed it at the parent element, which is "#commentable-container" for
this demo.
Clicking on the markers on the right will show the SideComments. Sections without any comments only show their
marker on hover.
This is the default theme that comes with SideComments.js. You can easily theme SideComments to your liking by not
including "default-theme.css" and just styling it all yourself.
SideComments.js In Action
Each paragraph tag has the "commentable-section" class, making it a section which can be commented on after you've initialized a new SideComments object and pointed it at the parent element, which is "#commentable-container" for this demo.
Clicking on the markers on the right will show the SideComments. Sections without any comments only show their marker on hover.
This is the default theme that comes with SideComments.js. You can easily theme SideComments to your liking by not including "default-theme.css" and just styling it all yourself.


“France still produces abominable sulphurous State-made matches (the manufacture of matches being a State monopoly). The label designs are sometimes poor and the colouring crude… One of the earliest German labels, issued in 1835, illustrates, by drawing, how to ignite the match by rubbing it on the box. Even the most ignorant person knew how to light a match, and the label appears a very futile one.”—A J Cruse, Matchbox Labels Of The World, With a History of Fire-Making Appliances from Primitive Man to the Modern Match, together with a History of the World's Labels (1946).
Further opinionated matchbox label observations are likely to follow, so watch this space. Many thanks to Ed Baxter.


This old English lullaby, also known as "The Riddle Song," is from the album
"JOAN BAEZ in San Francisco" which was recorded when she was 17years old.
It's a clumsy recording
with uneven volume, yet her rendition of the song is the most beautiful and haunting version you'll
ever hear.
Anyone who wants to know more about Joan Baez should read her candid 1987 autobiography
titled, "And A Voice To Sing With."
I gave my love a cherry which had no stone
I gave my love a chicken which had no bone
I gave my love a story which had no end
I gave my love a baby with no cryin'
How can there be a cherry which has no stone?
How can there be a chicken which has no bone?
How can there be a story which has no end?
How can there be a baby she's no cryin'?


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You can look at our many prideful awards and prices that we have won since the begining of Rocket Elevators.
AWARDSLooking for an upgrade for your residence? Or simply looking to add one or two of our elevators to your building, Well my friend you've come to the right place.
READ MORERunning a business is tough, you don't have time to worry about your building not looking profesional enough, don't worry we have you're back.
READ MOREThis is the Staff behind every projects of Rocket Elevators
For any questions towards our product or how we proceed.
Address:418-725 Boulevard Lebourgneuf, Quebec, Canada Phone: (581) LEARNTOCODE Email: info@codeboxx.bizz