chore: port functions support

This commit is contained in:
srikanthccv 2025-05-30 15:52:57 +05:30
parent c08d1bccaf
commit 2e9c66abdd
4 changed files with 1194 additions and 20 deletions

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@ -207,7 +207,7 @@ type SecondaryAggregation struct {
type Function struct {
// name of the function
Name string `json:"name"`
Name FunctionName `json:"name"`
// args is the arguments to the function
Args []struct {

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@ -1,27 +1,489 @@
package querybuildertypesv5
import "github.com/SigNoz/signoz/pkg/valuer"
import (
"math"
"sort"
"strconv"
"github.com/SigNoz/signoz/pkg/valuer"
)
type FunctionName struct {
valuer.String
}
var (
FunctionNameCutOffMin = FunctionName{valuer.NewString("cutOffMin")}
FunctionNameCutOffMax = FunctionName{valuer.NewString("cutOffMax")}
FunctionNameClampMin = FunctionName{valuer.NewString("clampMin")}
FunctionNameClampMax = FunctionName{valuer.NewString("clampMax")}
FunctionNameAbsolute = FunctionName{valuer.NewString("absolute")}
FunctionNameRunningDiff = FunctionName{valuer.NewString("runningDiff")}
FunctionNameLog2 = FunctionName{valuer.NewString("log2")}
FunctionNameLog10 = FunctionName{valuer.NewString("log10")}
FunctionNameCumSum = FunctionName{valuer.NewString("cumSum")}
FunctionNameEWMA3 = FunctionName{valuer.NewString("ewma3")}
FunctionNameEWMA5 = FunctionName{valuer.NewString("ewma5")}
FunctionNameEWMA7 = FunctionName{valuer.NewString("ewma7")}
FunctionNameMedian3 = FunctionName{valuer.NewString("median3")}
FunctionNameMedian5 = FunctionName{valuer.NewString("median5")}
FunctionNameMedian7 = FunctionName{valuer.NewString("median7")}
FunctionNameTimeShift = FunctionName{valuer.NewString("timeShift")}
FunctionNameAnomaly = FunctionName{valuer.NewString("anomaly")}
FunctionNameCutOffMin = FunctionName{valuer.NewString("cutoff_min")}
FunctionNameCutOffMax = FunctionName{valuer.NewString("cutoff_max")}
FunctionNameClampMin = FunctionName{valuer.NewString("clamp_min")}
FunctionNameClampMax = FunctionName{valuer.NewString("clamp_max")}
FunctionNameAbsolute = FunctionName{valuer.NewString("absolute")}
FunctionNameRunningDiff = FunctionName{valuer.NewString("running_diff")}
FunctionNameLog2 = FunctionName{valuer.NewString("log2")}
FunctionNameLog10 = FunctionName{valuer.NewString("log10")}
FunctionNameCumulativeSum = FunctionName{valuer.NewString("cumulative_sum")}
FunctionNameEWMA3 = FunctionName{valuer.NewString("ewma3")}
FunctionNameEWMA5 = FunctionName{valuer.NewString("ewma5")}
FunctionNameEWMA7 = FunctionName{valuer.NewString("ewma7")}
FunctionNameMedian3 = FunctionName{valuer.NewString("median3")}
FunctionNameMedian5 = FunctionName{valuer.NewString("median5")}
FunctionNameMedian7 = FunctionName{valuer.NewString("median7")}
FunctionNameTimeShift = FunctionName{valuer.NewString("time_shift")}
FunctionNameAnomaly = FunctionName{valuer.NewString("anomaly")}
)
// ApplyFunction applies the given function to the result data
func ApplyFunction(fn Function, result *Result) *Result {
// Extract the function name and arguments
name := fn.Name
args := fn.Args
switch name {
case FunctionNameCutOffMin, FunctionNameCutOffMax, FunctionNameClampMin, FunctionNameClampMax:
if len(args) == 0 {
return result
}
threshold, err := parseFloat64Arg(args[0].Value)
if err != nil {
return result
}
switch name {
case FunctionNameCutOffMin:
return funcCutOffMin(result, threshold)
case FunctionNameCutOffMax:
return funcCutOffMax(result, threshold)
case FunctionNameClampMin:
return funcClampMin(result, threshold)
case FunctionNameClampMax:
return funcClampMax(result, threshold)
}
case FunctionNameAbsolute:
return funcAbsolute(result)
case FunctionNameRunningDiff:
return funcRunningDiff(result)
case FunctionNameLog2:
return funcLog2(result)
case FunctionNameLog10:
return funcLog10(result)
case FunctionNameCumulativeSum:
return funcCumulativeSum(result)
case FunctionNameEWMA3, FunctionNameEWMA5, FunctionNameEWMA7:
alpha := getEWMAAlpha(name, args)
return funcEWMA(result, alpha)
case FunctionNameMedian3:
return funcMedian3(result)
case FunctionNameMedian5:
return funcMedian5(result)
case FunctionNameMedian7:
return funcMedian7(result)
case FunctionNameTimeShift:
if len(args) == 0 {
return result
}
shift, err := parseFloat64Arg(args[0].Value)
if err != nil {
return result
}
return funcTimeShift(result, shift)
case FunctionNameAnomaly:
// Placeholder for anomaly detection - would need more sophisticated implementation
return result
}
return result
}
// parseFloat64Arg parses a string argument to float64
func parseFloat64Arg(value string) (float64, error) {
return strconv.ParseFloat(value, 64)
}
// getEWMAAlpha calculates the alpha value for EWMA functions
func getEWMAAlpha(name FunctionName, args []struct {
Name string `json:"name,omitempty"`
Value string `json:"value"`
}) float64 {
// Try to get alpha from arguments first
if len(args) > 0 {
if alpha, err := parseFloat64Arg(args[0].Value); err == nil {
return alpha
}
}
// Default alpha values: alpha = 2 / (n + 1) where n is the window size
switch name {
case FunctionNameEWMA3:
return 0.5 // 2 / (3 + 1)
case FunctionNameEWMA5:
return 1.0 / 3.0 // 2 / (5 + 1)
case FunctionNameEWMA7:
return 0.25 // 2 / (7 + 1)
}
return 0.5 // default
}
// funcCutOffMin cuts off values below the threshold and replaces them with NaN
func funcCutOffMin(result *Result, threshold float64) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
for idx, point := range series.Values {
if point.Value < threshold {
point.Value = math.NaN()
}
series.Values[idx] = point
}
}
}
return result
}
// funcCutOffMax cuts off values above the threshold and replaces them with NaN
func funcCutOffMax(result *Result, threshold float64) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
for idx, point := range series.Values {
if point.Value > threshold {
point.Value = math.NaN()
}
series.Values[idx] = point
}
}
}
return result
}
// funcClampMin cuts off values below the threshold and replaces them with the threshold
func funcClampMin(result *Result, threshold float64) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
for idx, point := range series.Values {
if point.Value < threshold {
point.Value = threshold
}
series.Values[idx] = point
}
}
}
return result
}
// funcClampMax cuts off values above the threshold and replaces them with the threshold
func funcClampMax(result *Result, threshold float64) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
for idx, point := range series.Values {
if point.Value > threshold {
point.Value = threshold
}
series.Values[idx] = point
}
}
}
return result
}
// funcAbsolute returns the absolute value of each point
func funcAbsolute(result *Result) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
for idx, point := range series.Values {
point.Value = math.Abs(point.Value)
series.Values[idx] = point
}
}
}
return result
}
// funcRunningDiff returns the running difference of each point
func funcRunningDiff(result *Result) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
// iterate over the points in reverse order
for idx := len(series.Values) - 1; idx >= 0; idx-- {
if idx > 0 {
series.Values[idx].Value = series.Values[idx].Value - series.Values[idx-1].Value
}
}
// remove the first point
if len(series.Values) > 0 {
series.Values = series.Values[1:]
}
}
}
return result
}
// funcLog2 returns the log2 of each point
func funcLog2(result *Result) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
for idx, point := range series.Values {
point.Value = math.Log2(point.Value)
series.Values[idx] = point
}
}
}
return result
}
// funcLog10 returns the log10 of each point
func funcLog10(result *Result) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
for idx, point := range series.Values {
point.Value = math.Log10(point.Value)
series.Values[idx] = point
}
}
}
return result
}
// funcCumulativeSum returns the cumulative sum for each point in a series
func funcCumulativeSum(result *Result) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
var sum float64
for idx, point := range series.Values {
if !math.IsNaN(point.Value) {
sum += point.Value
}
point.Value = sum
series.Values[idx] = point
}
}
}
return result
}
// funcEWMA calculates the Exponentially Weighted Moving Average
func funcEWMA(result *Result, alpha float64) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
var ewma float64
var initialized bool
for i, point := range series.Values {
if !initialized {
if !math.IsNaN(point.Value) {
// Initialize EWMA with the first non-NaN value
ewma = point.Value
initialized = true
}
// Continue until the EWMA is initialized
continue
}
if !math.IsNaN(point.Value) {
// Update EWMA with the current value
ewma = alpha*point.Value + (1-alpha)*ewma
}
// Set the EWMA value for the current point
series.Values[i].Value = ewma
}
}
}
return result
}
// funcMedian3 returns the median of 3 points for each point in a series
func funcMedian3(result *Result) *Result {
return funcMedianN(result, 3)
}
// funcMedian5 returns the median of 5 points for each point in a series
func funcMedian5(result *Result) *Result {
return funcMedianN(result, 5)
}
// funcMedian7 returns the median of 7 points for each point in a series
func funcMedian7(result *Result) *Result {
return funcMedianN(result, 7)
}
// funcMedianN returns the median of N points for each point in a series
func funcMedianN(result *Result, n int) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
halfWindow := n / 2
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
medianValues := make([]*TimeSeriesValue, 0)
for i := halfWindow; i < len(series.Values)-halfWindow; i++ {
values := make([]float64, 0, n)
// Add non-NaN values to the slice
for j := -halfWindow; j <= halfWindow; j++ {
if !math.IsNaN(series.Values[i+j].Value) {
values = append(values, series.Values[i+j].Value)
}
}
// Create a new point with median value
newPoint := &TimeSeriesValue{
Timestamp: series.Values[i].Timestamp,
}
// Handle the case where there are not enough values to calculate a median
if len(values) == 0 {
newPoint.Value = math.NaN()
} else {
newPoint.Value = median(values)
}
medianValues = append(medianValues, newPoint)
}
// Replace the series values with median values
// Keep the original edge points unchanged
for i := halfWindow; i < len(series.Values)-halfWindow; i++ {
series.Values[i] = medianValues[i-halfWindow]
}
}
}
return result
}
// median calculates the median of a slice of float64 values
func median(values []float64) float64 {
if len(values) == 0 {
return math.NaN()
}
sort.Float64s(values)
medianIndex := len(values) / 2
if len(values)%2 == 0 {
return (values[medianIndex-1] + values[medianIndex]) / 2
}
return values[medianIndex]
}
// funcTimeShift shifts all timestamps by the given amount (in seconds)
func funcTimeShift(result *Result, shift float64) *Result {
if result.Type != RequestTypeTimeSeries {
return result
}
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok {
return result
}
shiftMs := int64(shift * 1000) // Convert seconds to milliseconds
for _, aggregation := range timeSeriesData.Aggregations {
for _, series := range aggregation.Series {
for idx, point := range series.Values {
series.Values[idx].Timestamp = point.Timestamp + shiftMs
}
}
}
return result
}
// ApplyFunctions applies a list of functions sequentially to the result
func ApplyFunctions(functions []Function, result *Result) *Result {
for _, fn := range functions {
result = ApplyFunction(fn, result)
}
return result
}

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@ -0,0 +1,712 @@
package querybuildertypesv5
import (
"math"
"testing"
)
// Helper function to create test time series data
func createTestTimeSeriesData(values []float64) *Result {
timeSeriesValues := make([]*TimeSeriesValue, len(values))
for i, val := range values {
timeSeriesValues[i] = &TimeSeriesValue{
Timestamp: int64(i + 1),
Value: val,
}
}
series := &TimeSeries{
Values: timeSeriesValues,
}
aggregation := &AggregationBucket{
Index: 0,
Alias: "test",
Series: []*TimeSeries{series},
}
timeSeriesData := &TimeSeriesData{
QueryName: "test",
Aggregations: []*AggregationBucket{aggregation},
}
return &Result{
Type: RequestTypeTimeSeries,
Value: timeSeriesData,
}
}
// Helper function to extract values from result for comparison
func extractValues(result *Result) []float64 {
timeSeriesData, ok := result.Value.(*TimeSeriesData)
if !ok || len(timeSeriesData.Aggregations) == 0 || len(timeSeriesData.Aggregations[0].Series) == 0 {
return nil
}
series := timeSeriesData.Aggregations[0].Series[0]
values := make([]float64, len(series.Values))
for i, point := range series.Values {
values[i] = point.Value
}
return values
}
func TestFuncCutOffMin(t *testing.T) {
tests := []struct {
name string
values []float64
threshold float64
want []float64
}{
{
name: "test funcCutOffMin",
values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
threshold: 0.3,
want: []float64{0.5, 0.4, 0.3, math.NaN(), math.NaN()},
},
{
name: "test funcCutOffMin with threshold 0",
values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
threshold: 0,
want: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcCutOffMin(result, tt.threshold)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("funcCutOffMin() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if math.IsNaN(tt.want[i]) {
if !math.IsNaN(got[i]) {
t.Errorf("funcCutOffMin() at index %d = %v, want %v", i, got[i], tt.want[i])
}
} else {
if got[i] != tt.want[i] {
t.Errorf("funcCutOffMin() at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
}
})
}
}
func TestFuncCutOffMax(t *testing.T) {
tests := []struct {
name string
values []float64
threshold float64
want []float64
}{
{
name: "test funcCutOffMax",
values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
threshold: 0.3,
want: []float64{math.NaN(), math.NaN(), 0.3, 0.2, 0.1},
},
{
name: "test funcCutOffMax with threshold 0",
values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
threshold: 0,
want: []float64{math.NaN(), math.NaN(), math.NaN(), math.NaN(), math.NaN()},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcCutOffMax(result, tt.threshold)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("funcCutOffMax() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if math.IsNaN(tt.want[i]) {
if !math.IsNaN(got[i]) {
t.Errorf("funcCutOffMax() at index %d = %v, want %v", i, got[i], tt.want[i])
}
} else {
if got[i] != tt.want[i] {
t.Errorf("funcCutOffMax() at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
}
})
}
}
func TestCutOffMinCumSum(t *testing.T) {
tests := []struct {
name string
values []float64
threshold float64
want []float64
}{
{
name: "test funcCutOffMin followed by funcCumulativeSum",
values: []float64{0.5, 0.2, 0.1, 0.4, 0.3},
threshold: 0.3,
want: []float64{0.5, 0.5, 0.5, 0.9, 1.2},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcCutOffMin(result, tt.threshold)
newResult = funcCumulativeSum(newResult)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("CutOffMin+CumSum got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if math.IsNaN(tt.want[i]) {
if !math.IsNaN(got[i]) {
t.Errorf("CutOffMin+CumSum at index %d = %v, want %v", i, got[i], tt.want[i])
}
} else {
if got[i] != tt.want[i] {
t.Errorf("CutOffMin+CumSum at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
}
})
}
}
func TestFuncMedian3(t *testing.T) {
tests := []struct {
name string
values []float64
want []float64
}{
{
name: "Values",
values: []float64{5, 3, 8, 2, 7},
want: []float64{5, 5, 3, 7, 7}, // edge values unchanged, middle values are median of 3
},
{
name: "NaNHandling",
values: []float64{math.NaN(), 3, math.NaN(), 7, 9},
want: []float64{math.NaN(), 3, 5, 8, 9}, // median of available values
},
{
name: "UniformValues",
values: []float64{7, 7, 7, 7, 7},
want: []float64{7, 7, 7, 7, 7},
},
{
name: "SingleValueSeries",
values: []float64{9},
want: []float64{9},
},
{
name: "EmptySeries",
values: []float64{},
want: []float64{},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
got := funcMedian3(result)
gotValues := extractValues(got)
if len(gotValues) != len(tt.want) {
t.Errorf("funcMedian3() got length %d, want length %d", len(gotValues), len(tt.want))
return
}
for i := range gotValues {
if math.IsNaN(tt.want[i]) {
if !math.IsNaN(gotValues[i]) {
t.Errorf("funcMedian3() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
}
} else {
if gotValues[i] != tt.want[i] {
t.Errorf("funcMedian3() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
}
}
}
})
}
}
func TestFuncMedian5(t *testing.T) {
tests := []struct {
name string
values []float64
want []float64
}{
{
name: "Values",
values: []float64{5, 3, 8, 2, 7, 9, 1, 4, 6, 10},
want: []float64{5, 3, 5, 7, 7, 4, 6, 6, 6, 10}, // edge values unchanged
},
{
name: "NaNHandling",
values: []float64{math.NaN(), 3, math.NaN(), 7, 9, 1, 4, 6, 10, 2},
want: []float64{math.NaN(), 3, 7, 5, 5.5, 6, 6, 4, 10, 2}, // median of available values
},
{
name: "UniformValues",
values: []float64{7, 7, 7, 7, 7},
want: []float64{7, 7, 7, 7, 7},
},
{
name: "SingleValueSeries",
values: []float64{9},
want: []float64{9},
},
{
name: "EmptySeries",
values: []float64{},
want: []float64{},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
got := funcMedian5(result)
gotValues := extractValues(got)
if len(gotValues) != len(tt.want) {
t.Errorf("funcMedian5() got length %d, want length %d", len(gotValues), len(tt.want))
return
}
for i := range gotValues {
if math.IsNaN(tt.want[i]) {
if !math.IsNaN(gotValues[i]) {
t.Errorf("funcMedian5() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
}
} else {
if gotValues[i] != tt.want[i] {
t.Errorf("funcMedian5() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
}
}
}
})
}
}
func TestFuncRunningDiff(t *testing.T) {
tests := []struct {
name string
values []float64
want []float64
}{
{
name: "test funcRunningDiff",
values: []float64{1, 2, 3},
want: []float64{1, 1}, // diff removes first element
},
{
name: "test funcRunningDiff with start number as 8",
values: []float64{8, 8, 8},
want: []float64{0, 0},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
got := funcRunningDiff(result)
gotValues := extractValues(got)
if len(gotValues) != len(tt.want) {
t.Errorf("funcRunningDiff() got length %d, want length %d", len(gotValues), len(tt.want))
return
}
for i := range gotValues {
if gotValues[i] != tt.want[i] {
t.Errorf("funcRunningDiff() at index %d = %v, want %v", i, gotValues[i], tt.want[i])
}
}
})
}
}
func TestFuncClampMin(t *testing.T) {
tests := []struct {
name string
values []float64
threshold float64
want []float64
}{
{
name: "test funcClampMin",
values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
threshold: 0.3,
want: []float64{0.5, 0.4, 0.3, 0.3, 0.3},
},
{
name: "test funcClampMin with threshold 0",
values: []float64{-0.5, -0.4, 0.3, 0.2, 0.1},
threshold: 0,
want: []float64{0, 0, 0.3, 0.2, 0.1},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcClampMin(result, tt.threshold)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("funcClampMin() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if got[i] != tt.want[i] {
t.Errorf("funcClampMin() at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
})
}
}
func TestFuncClampMax(t *testing.T) {
tests := []struct {
name string
values []float64
threshold float64
want []float64
}{
{
name: "test funcClampMax",
values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
threshold: 0.3,
want: []float64{0.3, 0.3, 0.3, 0.2, 0.1},
},
{
name: "test funcClampMax with threshold 1.0",
values: []float64{2.5, 0.4, 1.3, 0.2, 0.1},
threshold: 1.0,
want: []float64{1.0, 0.4, 1.0, 0.2, 0.1},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcClampMax(result, tt.threshold)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("funcClampMax() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if got[i] != tt.want[i] {
t.Errorf("funcClampMax() at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
})
}
}
func TestFuncAbsolute(t *testing.T) {
tests := []struct {
name string
values []float64
want []float64
}{
{
name: "test funcAbsolute",
values: []float64{-0.5, 0.4, -0.3, 0.2, -0.1},
want: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
},
{
name: "test funcAbsolute with all positive",
values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
want: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcAbsolute(result)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("funcAbsolute() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if got[i] != tt.want[i] {
t.Errorf("funcAbsolute() at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
})
}
}
func TestFuncLog2(t *testing.T) {
tests := []struct {
name string
values []float64
want []float64
}{
{
name: "test funcLog2",
values: []float64{1, 2, 4, 8, 16},
want: []float64{0, 1, 2, 3, 4},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcLog2(result)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("funcLog2() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if math.Abs(got[i]-tt.want[i]) > 1e-10 {
t.Errorf("funcLog2() at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
})
}
}
func TestFuncLog10(t *testing.T) {
tests := []struct {
name string
values []float64
want []float64
}{
{
name: "test funcLog10",
values: []float64{1, 10, 100, 1000},
want: []float64{0, 1, 2, 3},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcLog10(result)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("funcLog10() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if math.Abs(got[i]-tt.want[i]) > 1e-10 {
t.Errorf("funcLog10() at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
})
}
}
func TestFuncCumSum(t *testing.T) {
tests := []struct {
name string
values []float64
want []float64
}{
{
name: "test funcCumSum",
values: []float64{1, 2, 3, 4, 5},
want: []float64{1, 3, 6, 10, 15},
},
{
name: "test funcCumSum with NaN",
values: []float64{1, math.NaN(), 3, 4, 5},
want: []float64{1, 1, 4, 8, 13}, // NaN is ignored
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcCumulativeSum(result)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("funcCumSum() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if got[i] != tt.want[i] {
t.Errorf("funcCumSum() at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
})
}
}
func TestFuncTimeShift(t *testing.T) {
tests := []struct {
name string
values []float64
shift float64
want []int64 // expected timestamps
}{
{
name: "test funcTimeShift positive",
values: []float64{1, 2, 3},
shift: 5.0, // 5 seconds
want: []int64{6000, 7000, 8000}, // original timestamps (1,2,3) + 5000ms
},
{
name: "test funcTimeShift negative",
values: []float64{1, 2, 3},
shift: -2.0, // -2 seconds
want: []int64{-1000, 0, 1000}, // original timestamps (1,2,3) - 2000ms
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := funcTimeShift(result, tt.shift)
timeSeriesData, ok := newResult.Value.(*TimeSeriesData)
if !ok {
t.Errorf("funcTimeShift() failed to get time series data")
return
}
series := timeSeriesData.Aggregations[0].Series[0]
got := make([]int64, len(series.Values))
for i, point := range series.Values {
got[i] = point.Timestamp
}
if len(got) != len(tt.want) {
t.Errorf("funcTimeShift() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if got[i] != tt.want[i] {
t.Errorf("funcTimeShift() at index %d timestamp = %v, want %v", i, got[i], tt.want[i])
}
}
})
}
}
func TestApplyFunction(t *testing.T) {
tests := []struct {
name string
function Function
values []float64
want []float64
}{
{
name: "cutOffMin function",
function: Function{
Name: FunctionNameCutOffMin,
Args: []struct {
Name string `json:"name,omitempty"`
Value string `json:"value"`
}{
{Value: "0.3"},
},
},
values: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
want: []float64{0.5, 0.4, 0.3, math.NaN(), math.NaN()},
},
{
name: "absolute function",
function: Function{
Name: FunctionNameAbsolute,
},
values: []float64{-0.5, 0.4, -0.3, 0.2, -0.1},
want: []float64{0.5, 0.4, 0.3, 0.2, 0.1},
},
}
for _, tt := range tests {
t.Run(tt.name, func(t *testing.T) {
result := createTestTimeSeriesData(tt.values)
newResult := ApplyFunction(tt.function, result)
got := extractValues(newResult)
if len(got) != len(tt.want) {
t.Errorf("ApplyFunction() got length %d, want length %d", len(got), len(tt.want))
return
}
for i := range got {
if math.IsNaN(tt.want[i]) {
if !math.IsNaN(got[i]) {
t.Errorf("ApplyFunction() at index %d = %v, want %v", i, got[i], tt.want[i])
}
} else {
if got[i] != tt.want[i] {
t.Errorf("ApplyFunction() at index %d = %v, want %v", i, got[i], tt.want[i])
}
}
}
})
}
}
func TestApplyFunctions(t *testing.T) {
functions := []Function{
{
Name: FunctionNameCutOffMin,
Args: []struct {
Name string `json:"name,omitempty"`
Value string `json:"value"`
}{
{Value: "0.3"},
},
},
{
Name: FunctionNameCumulativeSum,
},
}
values := []float64{0.5, 0.2, 0.1, 0.4, 0.3}
want := []float64{0.5, 0.5, 0.5, 0.9, 1.2}
result := createTestTimeSeriesData(values)
newResult := ApplyFunctions(functions, result)
got := extractValues(newResult)
if len(got) != len(want) {
t.Errorf("ApplyFunctions() got length %d, want length %d", len(got), len(want))
return
}
for i := range got {
if got[i] != want[i] {
t.Errorf("ApplyFunctions() at index %d = %v, want %v", i, got[i], want[i])
}
}
}

View File

@ -249,7 +249,7 @@ func TestQueryRangeRequest_UnmarshalJSON(t *testing.T) {
Name: "error_rate",
Expression: "A / B * 100",
Functions: []Function{{
Name: "absolute",
Name: FunctionNameAbsolute,
Args: []struct {
Name string `json:"name,omitempty"`
Value string `json:"value"`