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cppad-20171217: A Package for Differentiation of C++ Algorithms
CppAD Download, Test, and Install Instructions
Using CMake to Configure CppAD
Including the ADOL-C Examples and Tests
Including the ColPack Sparsity Calculations
Including the Eigen Examples and Tests
Including the FADBAD Speed Tests
Including the cppad_ipopt Library and Tests
Including the Sacado Speed Tests
An Introduction by Example to Algorithmic Differentiation
Second Order Exponential Approximation
exp_2: Operation Sequence and Zero Order Forward Mode
exp_2: First Order Forward Mode
exp_2: First Order Reverse Mode
exp_2: Second Order Forward Mode
exp_2: Second Order Reverse Mode
An Epsilon Accurate Exponential Approximation
exp_eps: Operation Sequence and Zero Order Forward Sweep
exp_eps: First Order Forward Sweep
exp_eps: First Order Reverse Sweep
exp_eps: Second Order Forward Mode
exp_eps: Second Order Reverse Sweep
AD Objects
AD Constructors
AD Assignment Operator
Conversion and I/O of AD Objects
Convert From an AD Type to its Base Type
Convert From AD to Integer
AD Output Stream Operator
AD Output Stream Operator
Printing AD Values During Forward Mode
Convert an AD Variable to a Parameter
AD Valued Operations and Functions
AD Arithmetic Operators and Compound Assignments
AD Unary Plus Operator
AD Unary Minus Operator
AD Binary Arithmetic Operators
AD Compound Assignment Operators
The Unary Standard Math Functions
Inverse Sine Function: acos
Inverse Sine Function: asin
Inverse Tangent Function: atan
The Cosine Function: cos
The Hyperbolic Cosine Function: cosh
The Exponential Function: exp
The Exponential Function: log
The Base 10 Logarithm Function: log10
The Sine Function: sin
The Hyperbolic Sine Function: sinh
The Square Root Function: sqrt
The Tangent Function: tan
The Hyperbolic Tangent Function: tanh
AD Absolute Value Functions: abs, fabs
The Inverse Hyperbolic Cosine Function: acosh
The Inverse Hyperbolic Sine Function: asinh
The Inverse Hyperbolic Tangent Function: atanh
The Error Function
The Exponential Function Minus One: expm1
The Logarithm of One Plus Argument: log1p
The Sign: sign
The Binary Math Functions
AD Two Argument Inverse Tangent Function
The AD Power Function
Absolute Zero Multiplication
AD Conditional Expressions
Discrete AD Functions
Numeric Limits For an AD and Base Types
Atomic AD Functions
Checkpointing Functions
User Defined Atomic AD Functions
Atomic Forward Mode
Atomic Reverse Mode
Atomic Forward Jacobian Sparsity Patterns
Atomic Reverse Jacobian Sparsity Patterns
Atomic Forward Hessian Sparsity Patterns
Atomic Reverse Hessian Sparsity Patterns
Atomic Eigen Matrix Multiply: Example and Test
Atomic Eigen Matrix Inverse: Example and Test
Atomic Eigen Cholesky Factorization: Example and Test
User Atomic Matrix Multiply: Example and Test
Bool Valued Operations and Functions with AD Arguments
AD Binary Comparison Operators
Compare AD and Base Objects for Nearly Equal
AD Boolean Functions
Is an AD Object a Parameter or Variable
Check if Two Value are Identically Equal
AD Vectors that Record Index Operations
AD<Base> Requirements for a CppAD Base Type
Example AD Base Types That are not AD<OtherBase>
Enable use of AD<Base> where Base is Adolc's adouble Type
Enable use of AD<Base> where Base is std::complex<double>
ADFun Objects
Create an ADFun Object (Record an Operation Sequence)
Declare Independent Variables and Start Recording
Construct an ADFun Object and Stop Recording
Abort Recording of an Operation Sequence
ADFun Sequence Properties
First and Second Order Derivatives: Easy Drivers
Jacobian: Driver Routine
Hessian: Easy Driver
First Order Partial Derivative: Driver Routine
First Order Derivative: Driver Routine
Forward Mode Second Partial Derivative Driver
Reverse Mode Second Partial Derivative Driver
Forward Mode
Multiple Order Forward Mode
Multiple Directions Forward Mode
Comparison Changes Between Taping and Zero Order Forward
Controlling Taylor Coefficients Memory Allocation
Number of Variables that Can be Skipped
Reverse Mode
First Order Reverse Mode
Second Order Reverse Mode
Any Order Reverse Mode
Reverse Mode Using Subgraphs
Calculating Sparsity Patterns
Forward Mode Jacobian Sparsity Patterns
Jacobian Sparsity Pattern: Forward Mode
Reverse Mode Jacobian Sparsity Patterns
Jacobian Sparsity Pattern: Reverse Mode
Reverse Mode Hessian Sparsity Patterns
Hessian Sparsity Pattern: Reverse Mode
Forward Mode Hessian Sparsity Patterns
Hessian Sparsity Pattern: Forward Mode
Subgraph Dependency Sparsity Patterns
Calculating Sparse Derivatives
Computing Sparse Jacobians
Sparse Jacobian
Computing Sparse Hessians
Sparse Hessian
Compute Sparse Jacobians Using Subgraphs
Optimize an ADFun Object Tape
Abs-normal Representation of Non-Smooth Functions
Create An Abs-normal Representation of a Function
abs_normal: Evaluate First Order Approximation
abs_normal: Solve a Linear Program Using Simplex Method
abs_normal: Solve a Linear Program With Box Constraints
abs_normal: Minimize a Linear Abs-normal Approximation
Non-Smooth Optimization Using Abs-normal Linear Approximations
Solve a Quadratic Program Using Interior Point Method
abs_normal: Solve a Quadratic Program With Box Constraints
abs_normal: Minimize a Linear Abs-normal Approximation
Non-Smooth Optimization Using Abs-normal Quadratic Approximations
Check an ADFun Sequence of Operations
Check an ADFun Object For Nan Results
Using CppAD in a Multi-Threading Environment
Run Multi-Threading Examples and Speed Tests
Multi-Threading Harmonic Summation Example / Test
Multi-Threading User Atomic Example / Test
Multi-Threaded Newton Method Example / Test
Specifications for A Team of AD Threads
Some General Purpose Utilities
Replacing the CppAD Error Handler
Determine if Two Values Are Nearly Equal
Run One Speed Test and Return Results
Run One Speed Test and Print Results
Determine Amount of Time to Execute a Test
Returns Elapsed Number of Seconds
Definition of a Numeric Type
Check NumericType Class Concept
Definition of a Simple Vector
Check Simple Vector Concept
Obtain Nan or Determine if a Value is Nan
The Integer Power Function
Evaluate a Polynomial or its Derivative
Compute Determinants and Solve Equations by LU Factorization
Compute Determinant and Solve Linear Equations
LU Factorization of A Square Matrix
Invert an LU Factored Equation
One DimensionalRomberg Integration
Multi-dimensional Romberg Integration
An Embedded 4th and 5th Order Runge-Kutta ODE Solver
A 3rd and 4th Order Rosenbrock ODE Solver
An Error Controller for ODE Solvers
An Arbitrary Order Gear Method
An Error Controller for Gear's Ode Solvers
The CppAD::vector Template Class
A Fast Multi-Threading Memory Allocator
Returns Indices that Sort a Vector
Convert Certain Types to a String
Union of Standard Sets
Row and Column Index Sparsity Patterns
Sparse Matrix Row, Column, Value Representation
Use Ipopt to Solve a Nonlinear Programming Problem
Examples
General Examples
Enable Use of Eigen Linear Algebra Package with CppAD
Using Multiple Levels of AD
Utility Routines used by CppAD Examples
Lu Factor and Solve with Recorded Pivoting
Speed Test an Operator Overloading AD Package
Running the Speed Test Program
Speed Testing Utilities
Determinant Using Expansion by Lu Factorization
Determinant of a Minor
Determinant Using Expansion by Minors
Check Determinant of 3 by 3 matrix
Check Gradient of Determinant of 3 by 3 matrix
Sum Elements of a Matrix Times Itself
Evaluate a Function Defined in Terms of an ODE
Evaluate a Function That Has a Sparse Jacobian
Evaluate a Function That Has a Sparse Hessian
Simulate a [0,1] Uniform Random Variate
Speed Test of Functions in Double
Speed Test of Derivatives Using Adolc
Speed Test Derivatives Using CppAD
Speed Test Derivatives Using Fadbad
Speed Test Derivatives Using Sacado
Appendix
The Theory of Derivative Calculations
The Theory of Forward Mode
The Theory of Reverse Mode
Changes and Additions to CppAD
CppAD Deprecated API Features
Routines That Track Use of New and Delete
A Quick OpenMP Memory Allocator Used by CppAD
Nonlinear Programming Using the CppAD Interface to Ipopt
Example Simultaneous Solution of Forward and Inverse Problem
An ODE Inverse Problem Example
ODE Fitting Using Simple Representation
ODE Fitting Using Fast Representation
User Defined Atomic AD Functions
Old Matrix Multiply as a User Atomic Operation: Example and Test
zdouble: An AD Base Type With Absolute Zero
Compare Speed of C and C++
Some Numerical AD Utilities
Computing Jacobian and Hessian of Bender's Reduced Objective
Jacobian and Hessian of Optimal Values
LU Factorization of A Square Matrix and Stability Calculation