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73 lines
2.4 KiB
Go
73 lines
2.4 KiB
Go
// Copyright ©2014 The Gonum Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package optimize
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import (
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"errors"
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"fmt"
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"math"
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)
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var (
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// ErrZeroDimensional signifies an optimization was called with an input of length 0.
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ErrZeroDimensional = errors.New("optimize: zero dimensional input")
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// ErrLinesearcherFailure signifies that a Linesearcher has iterated too
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// many times. This may occur if the gradient tolerance is set too low.
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ErrLinesearcherFailure = errors.New("linesearch: failed to converge")
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// ErrNonDescentDirection signifies that LinesearchMethod has received a
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// search direction from a NextDirectioner in which the function is not
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// decreasing.
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ErrNonDescentDirection = errors.New("linesearch: non-descent search direction")
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// ErrNoProgress signifies that LinesearchMethod cannot make further
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// progress because there is no change in location after Linesearcher step
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// due to floating-point arithmetic.
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ErrNoProgress = errors.New("linesearch: no change in location after Linesearcher step")
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// ErrLinesearcherBound signifies that a Linesearcher reached a step that
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// lies out of allowed bounds.
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ErrLinesearcherBound = errors.New("linesearch: step out of bounds")
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)
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// ErrFunc is returned when an initial function value is invalid. The error
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// state may be either +Inf or NaN. ErrFunc satisfies the error interface.
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type ErrFunc float64
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func (err ErrFunc) Error() string {
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switch {
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case math.IsInf(float64(err), 1):
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return "optimize: initial function value is infinite"
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case math.IsNaN(float64(err)):
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return "optimize: initial function value is NaN"
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default:
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panic("optimize: bad ErrFunc")
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}
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}
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// ErrGrad is returned when an initial gradient is invalid. The error gradient
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// may be either ±Inf or NaN. ErrGrad satisfies the error interface.
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type ErrGrad struct {
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Grad float64 // Grad is the invalid gradient value.
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Index int // Index is the position at which the invalid gradient was found.
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}
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func (err ErrGrad) Error() string {
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switch {
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case math.IsInf(err.Grad, 0):
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return fmt.Sprintf("optimize: initial gradient is infinite at position %d", err.Index)
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case math.IsNaN(err.Grad):
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return fmt.Sprintf("optimize: initial gradient is NaN at position %d", err.Index)
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default:
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panic("optimize: bad ErrGrad")
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}
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}
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// List of shared panic strings
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var (
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badProblem = "optimize: objective function is undefined"
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)
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