Mercurial > gemma
view pkg/common/nashsutcliffe.go @ 5095:e21cbb9768a2
Prevent duplicate fairway areas
In principal, there can be only one or no fairway area at each point
on the map. Since polygons from real data will often be topologically
inexact, just disallow equal geometries. This will also help to
avoid importing duplicates with concurrent imports, once the history
of fairway dimensions will be preserved.
author | Tom Gottfried <tom@intevation.de> |
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date | Wed, 25 Mar 2020 18:10:02 +0100 |
parents | 8c5df0f3562e |
children | 6270951dda28 |
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// This is Free Software under GNU Affero General Public License v >= 3.0 // without warranty, see README.md and license for details. // // SPDX-License-Identifier: AGPL-3.0-or-later // License-Filename: LICENSES/AGPL-3.0.txt // // Copyright (C) 2019 by via donau // – Österreichische Wasserstraßen-Gesellschaft mbH // Software engineering by Intevation GmbH // // Author(s): // * Sascha L. Teichmann <sascha.teichmann@intevation.de> package common import ( "fmt" "time" ) type ( // TimedValue is a tuple of a point in time and an associated value. TimedValue struct { When time.Time Value float64 } // TimedValues is a slice of TimedValue tuples. TimedValues []TimedValue ) func epsEquals(a, b time.Time) bool { d := a.Sub(b) return -10*time.Millisecond < d && d < 10*time.Millisecond } // Find scans to the tuples and compares the time with an // epsilon of ten micro seconds. If they are equals the associated // value is returned. The return bool flags indicated if the // search was successful. func (mvs TimedValues) Find(when time.Time) (float64, bool) { for i := range mvs { if epsEquals(when, mvs[i].When) { return mvs[i].Value, true } } return 0, false } // NashSutcliffe calculates the Nash-Sutcliffe coefficent for // given predicted and observed values. // See // https://en.wikipedia.org/wiki/Nash%E2%80%93Sutcliffe_model_efficiency_coefficient // for details. // The function panics if predicted and observed are of different lengths. func NashSutcliffe(predicted, observed []float64) float64 { if len(predicted) != len(observed) { panic(fmt.Sprintf( "NashSutcliffe: predicted and observed len differ: %d != %d", len(predicted), len(observed))) } if len(observed) == 0 { return 0 } var mo float64 for _, v := range observed { mo += v } mo /= float64(len(observed)) var num, denom float64 for i, o := range observed { d1 := predicted[i] - o num += d1 * d1 d2 := o - mo denom += d2 * d2 } return 1 - num/denom }