internal UnaryExpression(ExpressionType nodeType, Expression expression, Type type, MethodInfo method)
{
this._operand = expression;
this._method = method;
this._nodeType = nodeType;
this._type = type;
}
/// <summary>
/// Performs reverse-mode (adjoint) automatic differentiation
/// </summary>
/// <param name="builder"></param>
/// <param name="dependentVariable"></param>
/// <param name="independentVariables"></param>
public static void Differentiate(BlockExpressionBuilder builder,
out IList<Expression> derivativeExpressions,
VectorParameterExpression dependentVariable,
params VectorParameterExpression[] independentVariables)
{
if (independentVariables.Length == 0)
{
derivativeExpressions = null;
return;
}
var block = builder.ToBlock();
// change the numbering of variables; arguments first, then locals
List<int>[] jLookup;
Function[] f;
// we want a list of functions which can be unary or binary (in principle high order if it makes sense) and a look-up
// each function is associated with a parameter, which is either an argument or a local
// for each function index we return a list of the indices of the functions that reference the parameter
GetFunctions(block, out f, out jLookup);
int N = dependentVariable.Index;
bool[] derivativeRequired; int[] derivativeExpressionIndex;
IdentifyNeccesaryDerivatives(N, jLookup, independentVariables, out derivativeRequired, out derivativeExpressionIndex);
// the list of operations needed to calculate the derivatives (*all* derivatives)
derivativeExpressions = new Expression[independentVariables.Length];
var dxNdx = new Expression[N + 1];
dxNdx[N] = new ConstantExpression<double>(1.0);
for (int i = N - 1; i >= 0; i--)
{
if (!derivativeRequired[i]) continue;
// dxN / dxi
// need to find all operation indices j such that p(j) contains i
// that is, all functions that have xi as an argument (these must therefore have a higher index than i)
VectorParameterExpression total = new ConstantExpression<double>(0);
var xi = f[i].Parameter;
//need sum of dfj/dxi dXN/dxj
foreach (var j in jLookup[i])
{
var fj = f[j];
var dfjdxi = Differentiate(fj, xi, builder); // dfj/dxi
var dXNdxj = dxNdx[j]; // dXN/dxj
var product = builder.AddProductExpression(dfjdxi, dXNdxj);
total = builder.AddAdditionExpression(total, product);
}
dxNdx[i] = total;
int targetIndex = derivativeExpressionIndex[i];
if (targetIndex != -1) derivativeExpressions[targetIndex] = total;
}
}
internal AssignBinaryExpression(Expression left, Expression right)
: base(left, right)
{
}
private static void CheckTypes(Expression left, Expression right)
{
if (left.Type != right.Type) throw new ArgumentException("expressions Types mismatch");
}
public static BinaryExpression Multiply(Expression left, Expression right)
{
CheckTypes(left, right);
return new SimpleBinaryExpression(ExpressionType.Multiply, left, right, left.Type);
}
public static BinaryExpression MakeBinary(ExpressionType binaryType, Expression left, Expression right)
{
CheckTypes(left, right);
return new SimpleBinaryExpression(binaryType, left, right, left.Type);
}
public static BinaryExpression Divide(Expression left, Expression right)
{
CheckTypes(left, right);
return new SimpleBinaryExpression(ExpressionType.Divide, left, right, left.Type);
}
public static BinaryExpression Assign(Expression left, Expression right)
{
CheckTypes(left, right);
return new AssignBinaryExpression(left, right);
}
internal BinaryExpression(Expression left, Expression right)
{
_left = left;
_right = right;
}
/// <summary>
/// Differentiate the function with respect to the variable
/// </summary>
/// <param name="function"></param>
/// <param name="variable"></param>
/// <returns></returns>
private static Expression Differentiate(Function function, Expression variable, BlockExpressionBuilder builder)
{
// note that one of the function parameters is the variable
var expression = function.Expression;
if (expression is BinaryExpression)
{
BinaryExpression binaryExpression = expression as BinaryExpression;
if (expression.NodeType == ExpressionType.Multiply)
{
if (binaryExpression.Left == variable && binaryExpression.Right == variable)
{
return Expression.Multiply(new ConstantExpression<double>(2), variable);
}
if (binaryExpression.Left == variable) return binaryExpression.Right;
else if (binaryExpression.Right == variable) return binaryExpression.Left;
}
else if (expression.NodeType == ExpressionType.Add)
{
if (binaryExpression.Left == variable && binaryExpression.Right == variable)
{
return new ConstantExpression<double>(2);
}
else if (binaryExpression.Left == variable) return new ConstantExpression<double>(1);
else if (binaryExpression.Right == variable) return new ConstantExpression<double>(1);
}
else if (expression.NodeType == ExpressionType.Subtract)
{
if (binaryExpression.Left == variable && binaryExpression.Right == variable)
{
return new ConstantExpression<double>(0);
}
else if (binaryExpression.Left == variable) return new ConstantExpression<double>(1);
else if (binaryExpression.Right == variable) return new ConstantExpression<double>(-1);
}
else if (expression.NodeType == ExpressionType.Divide)
{
if (binaryExpression.Left == variable && binaryExpression.Right == variable) throw new NotImplementedException(); // should not happen
if (binaryExpression.Left == variable)
{
var right = binaryExpression.Right as ReferencingVectorParameterExpression<double>;
if (right.IsScalar) return builder.AddLocalAssignment<double>(1 / right.ScalarValue, new ScaleInverseExpression<double>(binaryExpression.Right as VectorParameterExpression, 1));
else return builder.AddLocalAssignment<double>(new ScaleInverseExpression<double>(binaryExpression.Right as VectorParameterExpression, 1));
}
else if (binaryExpression.Right == variable)
{
return builder.AddNegateDivideExpression(function.Parameter, binaryExpression.Right as VectorParameterExpression); // i.e. x/y => x/y * -1/y
}
}
}
if (expression is UnaryMathsExpression)
{
var unaryExpression = expression as UnaryMathsExpression;
if (unaryExpression.UnaryType == UnaryElementWiseOperation.ScaleOffset)
{
return new ConstantExpression<double>((unaryExpression as ScaleOffsetExpression<double>).Scale);
}
else if (unaryExpression.UnaryType == UnaryElementWiseOperation.Negate) return new ConstantExpression<double>(-1);
else if (unaryExpression.UnaryType == UnaryElementWiseOperation.ScaleInverse)
{
return builder.AddNegateDivideExpression(function.Parameter, unaryExpression.Operand); // i.e. x/y => x/y * -1/y
}
else if (unaryExpression.UnaryType == UnaryElementWiseOperation.Exp) return function.Parameter;
else if (unaryExpression.UnaryType == UnaryElementWiseOperation.Log) return builder.AddInverseExpression(unaryExpression.Operand);
else if (unaryExpression.UnaryType == UnaryElementWiseOperation.SquareRoot) return builder.AddHalfInverseSquareRootExpression(unaryExpression.Operand);
else if (unaryExpression.UnaryType == UnaryElementWiseOperation.CumulativeNormal) return builder.AddGaussian(unaryExpression.Operand);
else throw new NotImplementedException();
}
else throw new NotImplementedException();
}