Merge pull request #96 from c-bata/suggest-float

Rename SuggestUniform to SuggestFloat.

README.md

@@ -44,8 +44,8 @@ import (
 // Define an objective function we want to minimize.
 func objective(trial goptuna.Trial) (float64, error) {
     // Define a search space of the input values.
-    x1, _ := trial.SuggestUniform("x1", -10, 10)
-    x2, _ := trial.SuggestUniform("x2", -10, 10)
+    x1, _ := trial.SuggestFloat("x1", -10, 10)
+    x2, _ := trial.SuggestFloat("x2", -10, 10)
 
     // Here is a two-dimensional quadratic function.
     // F(x1, x2) = (x1 - 2)^2 + (x2 + 5)^2

_examples/cmaes/main.go

@@ -9,8 +9,8 @@ import (
 )
 
 func objective(trial goptuna.Trial) (float64, error) {
-	x1, _ := trial.SuggestUniform("x1", -10, 10)
-	x2, _ := trial.SuggestUniform("x2", -10, 10)
+	x1, _ := trial.SuggestFloat("x1", -10, 10)
+	x2, _ := trial.SuggestFloat("x2", -10, 10)
 	return math.Pow(x1-2, 2) + math.Pow(x2+5, 2), nil
 }
 

_examples/concurrency/main.go

@@ -11,8 +11,8 @@ import (
 )
 
 func objective(trial goptuna.Trial) (float64, error) {
-	x1, _ := trial.SuggestUniform("x1", -10, 10)
-	x2, _ := trial.SuggestUniform("x2", -10, 10)
+	x1, _ := trial.SuggestFloat("x1", -10, 10)
+	x2, _ := trial.SuggestFloat("x2", -10, 10)
 	return math.Pow(x1-2, 2) + math.Pow(x2+5, 2), nil
 }
 

_examples/enqueue_trial/main.go

@@ -13,8 +13,8 @@ import (
 )
 
 func objective(trial goptuna.Trial) (float64, error) {
-	x1, _ := trial.SuggestUniform("x1", -10, 10)
-	x2, _ := trial.SuggestUniform("x2", -10, 10)
+	x1, _ := trial.SuggestFloat("x1", -10, 10)
+	x2, _ := trial.SuggestFloat("x2", -10, 10)
 	return math.Pow(x1-2, 2) + math.Pow(x2+5, 2), nil
 }
 

_examples/signalhandling/main.go

@@ -20,8 +20,8 @@ import (
 func objective(trial goptuna.Trial) (float64, error) {
 	ctx := trial.GetContext()
 
-	x1, _ := trial.SuggestUniform("x1", -10, 10)
-	x2, _ := trial.SuggestUniform("x2", -10, 10)
+	x1, _ := trial.SuggestFloat("x1", -10, 10)
+	x2, _ := trial.SuggestFloat("x2", -10, 10)
 
 	cmd := exec.CommandContext(ctx, "sleep", "1")
 	err := cmd.Run()

_examples/simple_rdb/main.go

@@ -14,8 +14,8 @@ import (
 )
 
 func objective(trial goptuna.Trial) (float64, error) {
-	x1, _ := trial.SuggestUniform("x1", -10, 10)
-	x2, _ := trial.SuggestUniform("x2", -10, 10)
+	x1, _ := trial.SuggestFloat("x1", -10, 10)
+	x2, _ := trial.SuggestFloat("x2", -10, 10)
 	return math.Pow(x1-2, 2) + math.Pow(x2+5, 2), nil
 }
 

_examples/simple_tpe/main.go

@@ -9,8 +9,8 @@ import (
 )
 
 func objective(trial goptuna.Trial) (float64, error) {
-	x1, _ := trial.SuggestUniform("x1", -10, 10)
-	x2, _ := trial.SuggestUniform("x2", -10, 10)
+	x1, _ := trial.SuggestFloat("x1", -10, 10)
+	x2, _ := trial.SuggestFloat("x2", -10, 10)
 	return math.Pow(x1-2, 2) + math.Pow(x2+5, 2), nil
 }
 

_examples/trialnotify/main.go

@@ -11,8 +11,8 @@ import (
 )
 
 func objective(trial goptuna.Trial) (float64, error) {
-	x1, _ := trial.SuggestUniform("x1", -10, 10)
-	x2, _ := trial.SuggestUniform("x2", -10, 10)
+	x1, _ := trial.SuggestFloat("x1", -10, 10)
+	x2, _ := trial.SuggestFloat("x2", -10, 10)
 	return math.Pow(x1-2, 2) + math.Pow(x2+5, 2), nil
 }
 

sampler_test.go

@@ -208,22 +208,22 @@ func TestRelativeSampler(t *testing.T) {
 
 	// First trial cannot trigger relative sampler.
 	err = study.Optimize(func(trial goptuna.Trial) (f float64, e error) {
-		_, _ = trial.SuggestUniform("uniform", -10, 10)
-		_, _ = trial.SuggestLogUniform("log_uniform", 1e-10, 1e10)
+		_, _ = trial.SuggestFloat("uniform", -10, 10)
+		_, _ = trial.SuggestLogFloat("log_uniform", 1e-10, 1e10)
 		_, _ = trial.SuggestInt("int", -10, 10)
-		_, _ = trial.SuggestDiscreteUniform("discrete", -10, 10, 0.5)
+		_, _ = trial.SuggestDiscreteFloat("discrete", -10, 10, 0.5)
 		_, _ = trial.SuggestCategorical("categorical", []string{"choice1", "choice2", "choice3"})
 		return 0.0, nil
 	}, 1)
 
 	// Second trial call relative sampler.
 	err = study.Optimize(func(trial goptuna.Trial) (f float64, e error) {
-		uniformParam, _ := trial.SuggestUniform("uniform", -10, 10)
+		uniformParam, _ := trial.SuggestFloat("uniform", -10, 10)
 		if uniformParam != 3 {
 			t.Errorf("should be 3, but got %f", uniformParam)
 		}
 
-		logUniformParam, _ := trial.SuggestLogUniform("log_uniform", 1e-10, 1e10)
+		logUniformParam, _ := trial.SuggestLogFloat("log_uniform", 1e-10, 1e10)
 		if logUniformParam != 100 {
 			t.Errorf("should be 100, but got %f", logUniformParam)
 		}
@@ -233,7 +233,7 @@ func TestRelativeSampler(t *testing.T) {
 			t.Errorf("should be 7, but got %d", intParam)
 		}
 
-		discreteParam, _ := trial.SuggestDiscreteUniform("discrete", -10, 10, 0.5)
+		discreteParam, _ := trial.SuggestDiscreteFloat("discrete", -10, 10, 0.5)
 		if discreteParam != 5.5 {
 			t.Errorf("should be 5.5, but got %f", discreteParam)
 		}
@@ -274,8 +274,8 @@ func TestRelativeSampler_UnsupportedSearchSpace(t *testing.T) {
 
 	// First trial cannot trigger relative sampler.
 	err = study.Optimize(func(trial goptuna.Trial) (f float64, e error) {
-		_, _ = trial.SuggestUniform("x1", -10, 10)
-		_, _ = trial.SuggestLogUniform("x2", 1e-10, 1e10)
+		_, _ = trial.SuggestFloat("x1", -10, 10)
+		_, _ = trial.SuggestLogFloat("x2", 1e-10, 1e10)
 		return 0.0, nil
 	}, 1)
 	if err != nil {
@@ -285,11 +285,11 @@ func TestRelativeSampler_UnsupportedSearchSpace(t *testing.T) {
 
 	// Second trial. RelativeSampler return ErrUnsupportedSearchSpace.
 	err = study.Optimize(func(trial goptuna.Trial) (f float64, e error) {
-		_, e = trial.SuggestUniform("x1", -10, 10)
+		_, e = trial.SuggestFloat("x1", -10, 10)
 		if e != nil {
 			t.Errorf("err should be nil, but got %s", e)
 		}
-		_, e = trial.SuggestLogUniform("x2", 1e-10, 1e10)
+		_, e = trial.SuggestLogFloat("x2", 1e-10, 1e10)
 		if e != nil {
 			t.Errorf("err should be nil, but got %s", e)
 		}
@@ -331,7 +331,7 @@ func TestIntersectionSearchSpace(t *testing.T) {
 
 				if err = study.Optimize(func(trial goptuna.Trial) (v float64, e error) {
 					x, _ := trial.SuggestInt("x", 0, 10)
-					y, _ := trial.SuggestUniform("y", -3, 3)
+					y, _ := trial.SuggestFloat("y", -3, 3)
 					return float64(x) + y, nil
 				}, 1); err != nil {
 					panic(err)
@@ -361,15 +361,15 @@ func TestIntersectionSearchSpace(t *testing.T) {
 				// First Trial
 				if err = study.Optimize(func(trial goptuna.Trial) (v float64, e error) {
 					x, _ := trial.SuggestInt("x", 0, 10)
-					y, _ := trial.SuggestUniform("y", -3, 3)
+					y, _ := trial.SuggestFloat("y", -3, 3)
 					return float64(x) + y, nil
 				}, 1); err != nil {
 					panic(err)
 				}
 
 				// Second Trial
 				if err = study.Optimize(func(trial goptuna.Trial) (v float64, e error) {
-					y, _ := trial.SuggestUniform("y", -3, 3)
+					y, _ := trial.SuggestFloat("y", -3, 3)
 					return y, nil
 				}, 1); err != nil {
 					panic(err)
@@ -395,28 +395,28 @@ func TestIntersectionSearchSpace(t *testing.T) {
 				// First Trial
 				if err = study.Optimize(func(trial goptuna.Trial) (v float64, e error) {
 					x, _ := trial.SuggestInt("x", 0, 10)
-					y, _ := trial.SuggestUniform("y", -3, 3)
+					y, _ := trial.SuggestFloat("y", -3, 3)
 					return float64(x) + y, nil
 				}, 1); err != nil {
 					panic(err)
 				}
 
 				// Second Trial
 				if err = study.Optimize(func(trial goptuna.Trial) (v float64, e error) {
-					y, _ := trial.SuggestUniform("y", -3, 3)
+					y, _ := trial.SuggestFloat("y", -3, 3)
 					return y, nil
 				}, 1); err != nil {
 					panic(err)
 				}
 
 				// Failed trial (ignore error)
 				_ = study.Optimize(func(trial goptuna.Trial) (v float64, e error) {
-					_, _ = trial.SuggestUniform("y", -3, 3)
+					_, _ = trial.SuggestFloat("y", -3, 3)
 					return 0.0, errors.New("something error")
 				}, 1)
 				// Pruned trial
 				if err = study.Optimize(func(trial goptuna.Trial) (v float64, e error) {
-					_, _ = trial.SuggestUniform("y", -3, 3)
+					_, _ = trial.SuggestFloat("y", -3, 3)
 					return 0.0, goptuna.ErrTrialPruned
 				}, 1); err != nil {
 					panic(err)

study_test.go

@@ -20,8 +20,8 @@ func ExampleStudy_Optimize() {
 	)
 
 	objective := func(trial goptuna.Trial) (float64, error) {
-		x1, _ := trial.SuggestUniform("x1", -10, 10)
-		x2, _ := trial.SuggestUniform("x2", -10, 10)
+		x1, _ := trial.SuggestFloat("x1", -10, 10)
+		x2, _ := trial.SuggestFloat("x2", -10, 10)
 		return math.Pow(x1-2, 2) + math.Pow(x2+5, 2), nil
 	}
 
@@ -76,8 +76,8 @@ func ExampleStudy_EnqueueTrial() {
 	)
 
 	objective := func(trial goptuna.Trial) (float64, error) {
-		x1, _ := trial.SuggestUniform("x1", -10, 10)
-		x2, _ := trial.SuggestUniform("x2", -10, 10)
+		x1, _ := trial.SuggestFloat("x1", -10, 10)
+		x2, _ := trial.SuggestFloat("x2", -10, 10)
 		return math.Pow(x1-2, 2) + math.Pow(x2+5, 2), nil
 	}
 
@@ -108,8 +108,8 @@ func TestStudy_EnqueueTrial_WithUnfixedParameter(t *testing.T) {
 	)
 
 	objective := func(trial goptuna.Trial) (float64, error) {
-		x1, _ := trial.SuggestUniform("x1", -10, 10)
-		x2, _ := trial.SuggestUniform("x2", -10, 10)
+		x1, _ := trial.SuggestFloat("x1", -10, 10)
+		x2, _ := trial.SuggestFloat("x2", -10, 10)
 		return math.Pow(x1-2, 2) + math.Pow(x2+5, 2), nil
 	}
 

trial.go

@@ -167,7 +167,25 @@ func (t *Trial) Number() (int, error) {
 }
 
 // SuggestUniform suggests a value from a uniform distribution.
+// Deprecated: This method will be removed at v1.0.0. Please use SuggestFloat method.
 func (t *Trial) SuggestUniform(name string, low, high float64) (float64, error) {
+	return t.SuggestFloat(name, low, high)
+}
+
+// SuggestLogUniform suggests a value from a uniform distribution in the log domain.
+// Deprecated: This method will be removed at v1.0.0. Please use SuggestLogFloat method.
+func (t *Trial) SuggestLogUniform(name string, low, high float64) (float64, error) {
+	return t.SuggestLogFloat(name, low, high)
+}
+
+// SuggestDiscreteUniform suggests a value from a discrete uniform distribution.
+// Deprecated: This method will be removed at v1.0.0. Please use SuggestDiscreteFloat method.
+func (t *Trial) SuggestDiscreteUniform(name string, low, high, q float64) (float64, error) {
+	return t.SuggestDiscreteFloat(name, low, high, q)
+}
+
+// SuggestFloat suggests a value for the floating point parameter.
+func (t *Trial) SuggestFloat(name string, low, high float64) (float64, error) {
 	if low > high {
 		return 0, errors.New("'low' must be smaller than or equal to the 'high'")
 	}
@@ -176,15 +194,29 @@ func (t *Trial) SuggestUniform(name string, low, high float64) (float64, error)
 	})
 }
 
-// SuggestLogUniform suggests a value from a uniform distribution in the log domain.
-func (t *Trial) SuggestLogUniform(name string, low, high float64) (float64, error) {
+// SuggestLogFloat suggests a value for the log-scale floating point parameter.
+func (t *Trial) SuggestLogFloat(name string, low, high float64) (float64, error) {
 	if low > high {
 		return 0, errors.New("'low' must be smaller than or equal to the 'high'")
 	}
-	v, err := t.suggest(name, LogUniformDistribution{
+	return t.suggest(name, LogUniformDistribution{
 		High: high, Low: low,
 	})
-	return v, err
+}
+
+// SuggestDiscreteFloat suggests a value for the discrete floating point parameter.
+func (t *Trial) SuggestDiscreteFloat(name string, low, high, q float64) (float64, error) {
+	if low > high {
+		return 0, errors.New("'low' must be smaller than or equal to the 'high'")
+	}
+	d := DiscreteUniformDistribution{
+		High: high, Low: low, Q: q,
+	}
+	ir, err := t.suggest(name, d)
+	if err != nil {
+		return 0, err
+	}
+	return d.ToExternalRepr(ir).(float64), err
 }
 
 // SuggestInt suggests an integer parameter.
@@ -199,8 +231,8 @@ func (t *Trial) SuggestInt(name string, low, high int) (int, error) {
 	return d.ToExternalRepr(v).(int), err
 }
 
-// SuggestIntWithStep suggests an integer parameter.
-func (t *Trial) SuggestIntWithStep(name string, low, high, step int) (int, error) {
+// SuggestStepInt suggests a step-interval integer parameter.
+func (t *Trial) SuggestStepInt(name string, low, high, step int) (int, error) {
 	if low > high {
 		return 0, errors.New("'low' must be smaller than or equal to the 'high'")
 	}
@@ -214,21 +246,6 @@ func (t *Trial) SuggestIntWithStep(name string, low, high, step int) (int, error
 	return d.ToExternalRepr(v).(int), err
 }
 
-// SuggestDiscreteUniform suggests a value from a discrete uniform distribution.
-func (t *Trial) SuggestDiscreteUniform(name string, low, high, q float64) (float64, error) {
-	if low > high {
-		return 0, errors.New("'low' must be smaller than or equal to the 'high'")
-	}
-	d := DiscreteUniformDistribution{
-		High: high, Low: low, Q: q,
-	}
-	ir, err := t.suggest(name, d)
-	if err != nil {
-		return 0, err
-	}
-	return d.ToExternalRepr(ir).(float64), err
-}
-
 // SuggestCategorical suggests an categorical parameter.
 func (t *Trial) SuggestCategorical(name string, choices []string) (string, error) {
 	if len(choices) == 0 {

trial_test.go

@@ -17,7 +17,7 @@ func TestTrial_Suggest(t *testing.T) {
 			name: "SuggestUniform",
 			objective: func(trial goptuna.Trial) (float64, error) {
 				// low is larger than high
-				x1, err := trial.SuggestUniform("x", -10, 10)
+				x1, err := trial.SuggestFloat("x", -10, 10)
 				if err != nil {
 					return -1, err
 				}
@@ -29,7 +29,7 @@ func TestTrial_Suggest(t *testing.T) {
 			name: "SuggestUniform: low is larger than high",
 			objective: func(trial goptuna.Trial) (float64, error) {
 				// low is larger than high
-				x1, err := trial.SuggestUniform("x", 10, -10)
+				x1, err := trial.SuggestFloat("x", 10, -10)
 				if err != nil {
 					return -1, err
 				}
@@ -40,7 +40,7 @@ func TestTrial_Suggest(t *testing.T) {
 		{
 			name: "SuggestLogUniform",
 			objective: func(trial goptuna.Trial) (float64, error) {
-				x1, err := trial.SuggestLogUniform("x", 1e5, 1e10)
+				x1, err := trial.SuggestLogFloat("x", 1e5, 1e10)
 				if err != nil {
 					return -1, err
 				}
@@ -51,7 +51,7 @@ func TestTrial_Suggest(t *testing.T) {
 		{
 			name: "SuggestLogUniform: low is larger than high",
 			objective: func(trial goptuna.Trial) (float64, error) {
-				x1, err := trial.SuggestLogUniform("x", 1e10, 1e5)
+				x1, err := trial.SuggestLogFloat("x", 1e10, 1e5)
 				if err != nil {
 					return -1, err
 				}
@@ -62,7 +62,7 @@ func TestTrial_Suggest(t *testing.T) {
 		{
 			name: "SuggestDiscreteUniform",
 			objective: func(trial goptuna.Trial) (float64, error) {
-				x1, err := trial.SuggestDiscreteUniform("x", -10, 10, 0.5)
+				x1, err := trial.SuggestDiscreteFloat("x", -10, 10, 0.5)
 				if err != nil {
 					return -1, err
 				}
@@ -73,7 +73,7 @@ func TestTrial_Suggest(t *testing.T) {
 		{
 			name: "SuggestDiscreteUniform: low is larger than high",
 			objective: func(trial goptuna.Trial) (float64, error) {
-				x1, err := trial.SuggestDiscreteUniform("x", 10, -10, 0.5)
+				x1, err := trial.SuggestDiscreteFloat("x", 10, -10, 0.5)
 				if err != nil {
 					return -1, err
 				}