github.com/jingcheng-WU/gonum@v0.9.1-0.20210323123734-f1a2a11a8f7b/stat/spatial/spatial_areal_example_test.go (about)

     1  // Copyright ©2017 The Gonum Authors. All rights reserved.
     2  // Use of this source code is governed by a BSD-style
     3  // license that can be found in the LICENSE file.
     4  
     5  package spatial_test
     6  
     7  import (
     8  	"fmt"
     9  	"math"
    10  
    11  	"github.com/jingcheng-WU/gonum/floats"
    12  	"github.com/jingcheng-WU/gonum/mat"
    13  	"github.com/jingcheng-WU/gonum/stat/spatial"
    14  )
    15  
    16  // Euclid is a mat.Matrix whose elements refects the Euclidean
    17  // distance between a series of unit-separated points strided
    18  // to be arranged in an x by y grid.
    19  type Euclid struct{ x, y int }
    20  
    21  func (e Euclid) Dims() (r, c int) { return e.x * e.y, e.x * e.y }
    22  func (e Euclid) At(i, j int) float64 {
    23  	d := e.x * e.y
    24  	if i < 0 || d <= i || j < 0 || d <= j {
    25  		panic("bounds error")
    26  	}
    27  	if i == j {
    28  		return 0
    29  	}
    30  	x := float64(j%e.x - i%e.x)
    31  	y := float64(j/e.x - i/e.x)
    32  	return 1 / math.Hypot(x, y)
    33  }
    34  func (e Euclid) T() mat.Matrix { return mat.Transpose{Matrix: e} }
    35  
    36  func ExampleGlobalMoransI_areal() {
    37  	locality := Euclid{10, 10}
    38  
    39  	data1 := []float64{
    40  		1, 0, 0, 1, 0, 0, 1, 0, 0, 0,
    41  		0, 1, 1, 0, 0, 1, 0, 0, 0, 0,
    42  		1, 0, 0, 1, 0, 0, 0, 0, 1, 0,
    43  		0, 0, 1, 0, 1, 0, 1, 0, 0, 0,
    44  		1, 0, 0, 0, 0, 0, 0, 1, 0, 0,
    45  		0, 0, 0, 0, 1, 0, 0, 0, 0, 0,
    46  		0, 0, 1, 0, 0, 0, 1, 0, 1, 0,
    47  		1, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    48  		0, 0, 1, 0, 1, 0, 1, 0, 0, 0,
    49  		1, 0, 0, 0, 0, 0, 0, 0, 1, 0,
    50  	}
    51  	i1, _, z1 := spatial.GlobalMoransI(data1, nil, locality)
    52  
    53  	data2 := []float64{
    54  		0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    55  		0, 0, 0, 0, 0, 0, 0, 0, 0, 0,
    56  		0, 0, 0, 1, 1, 0, 0, 0, 0, 0,
    57  		0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
    58  		0, 0, 1, 1, 1, 1, 0, 0, 0, 0,
    59  		0, 0, 0, 1, 1, 1, 0, 0, 0, 0,
    60  		0, 0, 0, 0, 1, 0, 0, 0, 1, 0,
    61  		0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
    62  		0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
    63  		0, 0, 0, 0, 0, 0, 0, 1, 1, 1,
    64  	}
    65  	i2, _, z2 := spatial.GlobalMoransI(data2, nil, locality)
    66  
    67  	fmt.Printf("%v scattered points Moran's I=%.4v z-score=%.4v\n", floats.Sum(data1), i1, z1)
    68  	fmt.Printf("%v clustered points Moran's I=%.4v z-score=%.4v\n", floats.Sum(data2), i2, z2)
    69  
    70  	// Output:
    71  	//
    72  	// 24 scattered points Moran's I=-0.02999 z-score=-1.913
    73  	// 24 clustered points Moran's I=0.09922 z-score=10.52
    74  }