Drop () from FuncName() in comments

cg.go

@@ -40,7 +40,7 @@ type CGVariant interface {
 //  - The angle between the gradients at two consecutive iterations ∇f_k and
 //    ∇f_{k+1} is too large.
 //  - The direction d_{k+1} is not a descent direction.
-//  - β_k given by CGVariant.Beta() is equal to zero.
+//  - β_k returned from CGVariant.Beta is equal to zero.
 //
 // The line search for CG must yield step sizes that satisfy the strong Wolfe
 // conditions at every iteration, otherwise the generated search direction

functions/minsurf_test.go

@@ -32,8 +32,8 @@ func TestMinimalSurface(t *testing.T) {
 		}
 
 		// Test that the gradient at the minimum is small enough.
-		// In some sense this test is not completely correct because ExactX()
-		// is the exact solution to the continuous problem projected on the
+		// In some sense this test is not completely correct because ExactX
+		// returns the exact solution to the continuous problem projected on the
 		// grid, not the exact solution to the discrete problem which we are
 		// solving. This is the reason why a relatively loose tolerance 1e-4
 		// must be used.

interfaces.go

@@ -31,19 +31,19 @@ package optimize
 type Method interface {
 	// Init initializes the method based on the initial data in loc, updates it
 	// and returns the first operation to be carried out by the caller.
-	// The initial location must be valid as specified by Needs().
+	// The initial location must be valid as specified by Needs.
 	Init(loc *Location) (Operation, error)
 
 	// Iterate retrieves data from loc, performs one iteration of the method,
 	// updates loc and returns the next operation.
 	// TODO(vladimir-ch): When decided, say something whether the contents of
-	// Location is preserved between calls to Iterate().
+	// Location is preserved between calls to Iterate.
 	Iterate(loc *Location) (Operation, error)
 
 	// Needs specifies information about the objective function needed by the
 	// optimizer beyond just the function value. The information is used
 	// internally for initialization and must match evaluation types returned
-	// by Init() and Iterate() during the optimization process.
+	// by Init and Iterate during the optimization process.
 	Needs() struct {
 		Gradient bool
 		Hessian  bool
@@ -52,7 +52,7 @@ type Method interface {
 
 // Statuser can report the status and any error. It is intended for methods as
 // an additional error reporting mechanism apart from the errors returned from
-// Init() and Iterate().
+// Init and Iterate.
 type Statuser interface {
 	Status() (Status, error)
 }

linesearch.go

@@ -22,13 +22,13 @@ type LinesearchMethod struct {
 	dir []float64 // Search direction for the current iteration.
 
 	first     bool // Indicator of the first iteration.
-	nextMajor bool // Indicates that MajorIteration must be requested at the next call to Iterate().
+	nextMajor bool // Indicates that MajorIteration must be requested at the next call to Iterate.
 
 	loc  Location  // Storage for intermediate locations.
 	eval Operation // Indicator of valid fields in loc.
 
-	lastStep float64   // Step taken from x in the previous call to Iterate().
-	lastOp   Operation // Operation returned from the previous call to Iterate().
+	lastStep float64   // Step taken from x in the previous call to Iterate.
+	lastOp   Operation // Operation returned from the previous call to Iterate.
 }
 
 func (ls *LinesearchMethod) Init(loc *Location) (Operation, error) {
@@ -60,7 +60,7 @@ func (ls *LinesearchMethod) Iterate(loc *Location) (Operation, error) {
 	switch ls.lastOp {
 	case NoOperation:
 		// TODO(vladimir-ch): We have previously returned with an error and
-		// Init() was not called. What to do? What about ls's internal state?
+		// Init was not called. What to do? What about ls's internal state?
 
 	case MajorIteration:
 		// We previously requested MajorIteration but since we're here, the

local.go

@@ -21,7 +21,7 @@ import (
 // routines that evaluate the objective function, gradient, and other
 // quantities related to the problem. The objective function, p.Func, must not
 // be nil. The optimization method used may require other fields to be non-nil
-// as specified by method.Needs(). Local will panic if these are not met. The
+// as specified by method.Needs. Local will panic if these are not met. The
 // method can be determined automatically from the supplied problem which is
 // described below.
 //
@@ -34,7 +34,7 @@ import (
 // problem dimension.
 //
 // The third argument contains the settings for the minimization. It is here that
-// gradient tolerance, etc. are specified. The DefaultSettings() function
+// gradient tolerance, etc. are specified. The DefaultSettings function
 // can be called for a Settings struct with the default values initialized.
 // If settings == nil, the default settings are used. See the documentation
 // for the Settings structure for more information. The optimization Method used
@@ -50,8 +50,8 @@ import (
 // in the method will be populated with default values. The methods are also
 // designed such that they can be reused in future calls to Local.
 //
-// If method implements Statuser, method.Status() is called before every call
-// to method.Iterate(). If the returned Status is not NotTerminated or the
+// If method implements Statuser, method.Status is called before every call
+// to method.Iterate. If the returned Status is not NotTerminated or the
 // error is non-nil, the optimization run is terminated.
 //
 // Local returns a Result struct and any error that occurred. See the
@@ -151,7 +151,7 @@ func minimize(p *Problem, method Method, settings *Settings, stats *Stats, optLo
 	}
 
 	for {
-		// Sequentially call method.Iterate(), performing the operations it has
+		// Sequentially call method.Iterate, performing the operations it has
 		// requested, until convergence.
 
 		switch op {
@@ -311,7 +311,7 @@ func getStartingLocation(p *Problem, method Method, initX []float64, stats *Stat
 // checkConvergence returns NotTerminated if the Location does not satisfy the
 // convergence criteria given by settings. Otherwise a corresponding status is
 // returned.
-// Unlike checkLimits, it is called by Local() only at MajorIterations.
+// Unlike checkLimits, checkConvergence is called by Local only at MajorIterations.
 func checkConvergence(loc *Location, settings *Settings) Status {
 	if loc.Gradient != nil {
 		norm := floats.Norm(loc.Gradient, math.Inf(1))
@@ -333,7 +333,7 @@ func checkConvergence(loc *Location, settings *Settings) Status {
 
 // checkLimits returns NotTerminated status if the various limits given by
 // settings has not been reached. Otherwise it returns a corresponding status.
-// Unlike checkConvergence(), it is called by Local() at _every_ iteration.
+// Unlike checkConvergence, checkLimits is called by Local at _every_ iteration.
 func checkLimits(loc *Location, stats *Stats, settings *Settings) Status {
 	// Check the objective function value for negative infinity because it
 	// could break the linesearches and -inf is the best we can do anyway.

termination.go

@@ -107,7 +107,7 @@ var statuses = []struct {
 // calls to NewStatus are not thread safe.
 //
 // NewStatus takes in three arguments, the string that should be output from
-// Status.String(), a boolean if the status indicates early optimization conclusion,
+// Status.String, a boolean if the status indicates early optimization conclusion,
 // and the error to return from Err (if any).
 func NewStatus(name string, early bool, err error) Status {
 	statuses = append(statuses, struct {

types.go

@@ -98,9 +98,9 @@ type Result struct {
 // Stats contains the statistics of the run.
 type Stats struct {
 	MajorIterations int           // Total number of major iterations
-	FuncEvaluations int           // Number of evaluations of Func()
-	GradEvaluations int           // Number of evaluations of Grad()
-	HessEvaluations int           // Number of evaluations of Hess()
+	FuncEvaluations int           // Number of evaluations of Func
+	GradEvaluations int           // Number of evaluations of Grad
+	HessEvaluations int           // Number of evaluations of Hess
 	Runtime         time.Duration // Total runtime of the optimization
 }
 
@@ -154,7 +154,7 @@ func (p Problem) satisfies(method Method) error {
 
 // Settings represents settings of the optimization run. It contains initial
 // settings, convergence information, and Recorder information. In general, users
-// should use DefaultSettings() rather than constructing a Settings literal.
+// should use DefaultSettings rather than constructing a Settings literal.
 //
 // If UseInitData is true, InitialValue, InitialGradient and InitialHessian
 // specify function information at the initial location.
@@ -208,21 +208,21 @@ type Settings struct {
 
 	// FuncEvaluations is the maximum allowed number of function evaluations.
 	// FunctionEvaluationLimit status is returned if the total number of calls
-	// to Func() equals or exceeds this number.
+	// to Func equals or exceeds this number.
 	// If it equals zero, this setting has no effect.
 	// The default value is 0.
 	FuncEvaluations int
 
 	// GradEvaluations is the maximum allowed number of gradient evaluations.
 	// GradientEvaluationLimit status is returned if the total number of calls
-	// to Grad() equals or exceeds this number.
+	// to Grad equals or exceeds this number.
 	// If it equals zero, this setting has no effect.
 	// The default value is 0.
 	GradEvaluations int
 
 	// HessEvaluations is the maximum allowed number of Hessian evaluations.
 	// HessianEvaluationLimit status is returned if the total number of calls
-	// to Hess() equals or exceeds this number.
+	// to Hess equals or exceeds this number.
 	// If it equals zero, this setting has no effect.
 	// The default value is 0.
 	HessEvaluations int

unconstrained_test.go

@@ -31,7 +31,7 @@ type unconstrainedTest struct {
 	// the default value of 20 will be used.
 	fIter int
 	// long indicates that the test takes long time to finish and will be
-	// excluded if testing.Short() is true.
+	// excluded if testing.Short returns true.
 	long bool
 }
 
@@ -995,15 +995,15 @@ func newVariablyDimensioned(dim int, gradTol float64) unconstrainedTest {
 
 func TestLocal(t *testing.T) {
 	var tests []unconstrainedTest
-	// Mix of functions with and without Grad() method.
+	// Mix of functions with and without Grad method.
 	tests = append(tests, gradFreeTests...)
 	tests = append(tests, gradientDescentTests...)
 	testLocal(t, gradientDescentTests, nil)
 }
 
 func TestNelderMead(t *testing.T) {
 	var tests []unconstrainedTest
-	// Mix of functions with and without Grad() method.
+	// Mix of functions with and without Grad method.
 	tests = append(tests, gradFreeTests...)
 	tests = append(tests, gradientDescentTests...)
 	testLocal(t, tests, &NelderMead{})