In Go, you can partition a slice of float64 values by using a custom function that determines the criteria for partitioning. Typically, you might want to split the slice into two slices: one containing values that meet the condition and another with values that do not.
Here's a basic example of how to partition a slice of float64s based on whether the values are above or below a specified threshold.
package main
import (
"fmt"
)
func partition(slice []float64, threshold float64) ([]float64, []float64) {
less := []float64{}
greater := []float64{}
for _, value := range slice {
if value < threshold {
less = append(less, value)
} else {
greater = append(greater, value)
}
}
return less, greater
}
func main() {
values := []float64{1.2, 3.4, 2.2, 5.6, 4.3}
threshold := 3.0
less, greater := partition(values, threshold)
fmt.Println("Less than threshold:", less)
fmt.Println("Greater than or equal to threshold:", greater)
}
How do I avoid rehashing overhead with std::set in multithreaded code?
How do I find elements with custom comparators with std::set for embedded targets?
How do I erase elements while iterating with std::set for embedded targets?
How do I provide stable iteration order with std::unordered_map for large datasets?
How do I reserve capacity ahead of time with std::unordered_map for large datasets?
How do I erase elements while iterating with std::unordered_map in multithreaded code?
How do I provide stable iteration order with std::map for embedded targets?
How do I provide stable iteration order with std::map in multithreaded code?
How do I avoid rehashing overhead with std::map in performance-sensitive code?
How do I merge two containers efficiently with std::map for embedded targets?