package/gonum
1
0
Fork 0
mirror of https://github.com/gonum/gonum.git synced 2025-10-21 14:19:35 +08:00
Code Issues Actions Packages Projects Releases Wiki Activity

Handle NaN inputs in CDF

Browse Source 
When sort.Float64sAreSorted is called, it panics on NaN inputs.

The way the code is written, there seems to be an intent that if the
input x contains a NaN, then the function should return a NaN.  I
switched the order of the conditional statements so that this became
possible.

I also modified the test cases so that cases with NaN could be
evaluated.
This commit is contained in:
Jonathan J Lawlor
2014-10-19 18:28:50 -04:00
parent c9b363350b
commit f510cbd899
2 changed files with 10 additions and 11 deletions
Download Patch File Download Diff File Expand all files Collapse all files

6
stat.go
View File

@@ -66,12 +66,12 @@ func CDF(q float64, c CumulantKind, x, weights []float64) float64 {
if weights != nil && len(x) != len(weights) { if weights != nil && len(x) != len(weights) {
panic("stat: slice length mismatch") panic("stat: slice length mismatch")
} }
if !sort.Float64sAreSorted(x) {
panic("x data are not sorted")
}
if floats.HasNaN(x) { if floats.HasNaN(x) {
return math.NaN() return math.NaN()
} }
if !sort.Float64sAreSorted(x) {
panic("x data are not sorted")
}
if q < x[0] { if q < x[0] {
return 0 return 0

15
stat_test.go
View File

@@ -755,6 +755,11 @@ func TestCDF(t *testing.T) {
weights: []float64{1, 1, 1, 1, 1}, weights: []float64{1, 1, 1, 1, 1},
ans: [][]float64{{0, 0, 0.2, 0.2, 0.4, 0.6, 0.6, 0.8, 1, 1}}, ans: [][]float64{{0, 0, 0.2, 0.2, 0.4, 0.6, 0.6, 0.8, 1, 1}},
}, },
{
q: []float64{0, 0.9, 1},
x: []float64{math.NaN()},
ans: [][]float64{{math.NaN(), math.NaN(), math.NaN()}},
},
} { } {
copyX := make([]float64, len(test.x)) copyX := make([]float64, len(test.x))
copy(copyX, test.x) copy(copyX, test.x)
@@ -766,13 +771,13 @@ func TestCDF(t *testing.T) {
for j, q := range test.q { for j, q := range test.q {
for k, kind := range cumulantKinds { for k, kind := range cumulantKinds {
v := CDF(q, kind, test.x, test.weights) v := CDF(q, kind, test.x, test.weights)
if !floats.Equal(copyX, test.x) { if !floats.Equal(copyX, test.x) && !math.IsNaN(v) {
t.Errorf("x changed for case %d kind %d percentile %v", i, k, q) t.Errorf("x changed for case %d kind %d percentile %v", i, k, q)
} }
if !floats.Equal(copyW, test.weights) { if !floats.Equal(copyW, test.weights) {
t.Errorf("x changed for case %d kind %d percentile %v", i, k, q) t.Errorf("x changed for case %d kind %d percentile %v", i, k, q)
} }
if v != test.ans[k][j] { if v != test.ans[k][j] && !(math.IsNaN(v) && math.IsNaN(test.ans[k][j])) {
t.Errorf("mismatch case %d kind %d percentile %v. Expected: %v, found: %v", i, k, q, test.ans[k][j], v) t.Errorf("mismatch case %d kind %d percentile %v. Expected: %v, found: %v", i, k, q, test.ans[k][j], v)
} }
} }
@@ -800,12 +805,6 @@ func TestCDF(t *testing.T) {
kind: Empirical, kind: Empirical,
x: []float64{3, 2, 1}, x: []float64{3, 2, 1},
}, },
{
name: "x has a NaN",
q: 1.5,
kind: Empirical,
x: []float64{1, 2, math.NaN()},
},
{ {
name: "unknown CumulantKind", name: "unknown CumulantKind",
q: 1.5, q: 1.5,