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- // Copyright 2023 The casbin Authors. All Rights Reserved.
- //
- // Licensed under the Apache License, Version 2.0 (the "License");
- // you may not use this file except in compliance with the License.
- // You may obtain a copy of the License at
- //
- // http://www.apache.org/licenses/LICENSE-2.0
- //
- // Unless required by applicable law or agreed to in writing, software
- // distributed under the License is distributed on an "AS IS" BASIS,
- // WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
- // See the License for the specific language governing permissions and
- // limitations under the License.
-
- package object
-
- import "math"
-
- func dot(vec1, vec2 []float32) float32 {
- if len(vec1) != len(vec2) {
- panic("Vector lengths do not match")
- }
-
- dotProduct := float32(0.0)
- for i := range vec1 {
- dotProduct += vec1[i] * vec2[i]
- }
- return dotProduct
- }
-
- func norm(vec []float32) float32 {
- normSquared := float32(0.0)
- for _, val := range vec {
- normSquared += val * val
- }
- return float32(math.Sqrt(float64(normSquared)))
- }
-
- func cosineSimilarity(vec1, vec2 []float32, vec1Norm float32) float32 {
- dotProduct := dot(vec1, vec2)
- vec2Norm := norm(vec2)
- if vec2Norm == 0 {
- return 0.0
- }
- return dotProduct / (vec1Norm * vec2Norm)
- }
-
- func getNearestVectorIndex(target []float32, vectors [][]float32) int {
- targetNorm := norm(target)
-
- var res int
- max := float32(-1.0)
- for i, vector := range vectors {
- similarity := cosineSimilarity(target, vector, targetNorm)
- if similarity > max {
- max = similarity
- res = i
- }
- }
- return res
- }
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