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5f94b77a39
* #7 Added ABS * #7 Added ACOS * #7 Added ASIN * #7 Added ATAN * #7 Added ATAN2 * #7 Added AVERAGE * #7 Added CEIL * #7 Added COS * #7 Added DEGREES * #7 Added EXP * #7 Added EXP2 * #7 Added FLOOR * #7 Added LOG * #7 Added LOG2 * #7 Added LOG10 * #7 Added MAX * #7 Added MEDIAN * #7 Added MIN * #7 Added PERCENTILE * #7 Added PI * #7 Added POW * #7 Added RADIANS * #7 Added RAND * #7 Added RANGE * #7 Added ROUND * #7 Added SIN * #7 Added SQRT * #7 Added TAN * #7 Added SUM * #7 Added STDDEV_POPULATION * #7 Added STDDEV_SAMPLE, VARIANCE_POPULATION, VARIANCE_SAMPLE
40 lines
834 B
Go
40 lines
834 B
Go
package math
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import (
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"github.com/MontFerret/ferret/pkg/runtime/core"
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"github.com/MontFerret/ferret/pkg/runtime/values"
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"math"
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)
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func variance(input *values.Array, sample values.Int) (values.Float, error) {
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if input.Length() == 0 {
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return values.NewFloat(math.NaN()), nil
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}
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m, _ := mean(input)
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var err error
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var variance values.Float
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input.ForEach(func(value core.Value, idx int) bool {
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err = core.ValidateType(value, core.IntType, core.FloatType)
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if err != nil {
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return false
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}
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n := values.Float(toFloat(value))
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variance += (n - m) * (n - m)
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return true
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})
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// When getting the mean of the squared differences
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// "sample" will allow us to know if it's a sample
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// or population and wether to subtract by one or not
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l := values.Float(input.Length() - (1 * sample))
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return variance / l, nil
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}
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