Revert "remove early-stop tests"

This reverts commit e0af22e.

tests/test_early_stop.py

@@ -0,0 +1,337 @@
+import time
+import pytest
+import numpy as np
+from sklearn.datasets import load_breast_cancer
+from sklearn.model_selection import cross_val_score
+from sklearn.tree import DecisionTreeClassifier
+
+from hyperactive import Hyperactive
+from hyperactive.optimizers import (
+    RandomSearchOptimizer,
+    HillClimbingOptimizer,
+)
+
+
+def objective_function(para):
+    score = -para["x1"] * para["x1"]
+    return score
+
+
+search_space = {
+    "x1": list(np.arange(0, 100000, 0.1)),
+}
+
+
+def test_early_stop_0():
+    early_stopping = {
+        "n_iter_no_change": 5,
+        "tol_abs": 0.1,
+        "tol_rel": 0.1,
+    }
+
+    hyper = Hyperactive()
+    hyper.add_search(
+        objective_function,
+        search_space,
+        n_iter=1000,
+        initialize={"warm_start": [{"x1": 0}]},
+        early_stopping=early_stopping,
+    )
+    hyper.run()
+
+
+def test_early_stop_1():
+    early_stopping = {
+        "n_iter_no_change": 5,
+        "tol_abs": None,
+        "tol_rel": 5,
+    }
+
+    hyper = Hyperactive()
+    hyper.add_search(
+        objective_function,
+        search_space,
+        n_iter=1000,
+        initialize={"warm_start": [{"x1": 0}]},
+        early_stopping=early_stopping,
+    )
+    hyper.run()
+
+
+def test_early_stop_2():
+    early_stopping = {
+        "n_iter_no_change": 5,
+        "tol_abs": 0.1,
+        "tol_rel": None,
+    }
+
+    hyper = Hyperactive()
+    hyper.add_search(
+        objective_function,
+        search_space,
+        n_iter=1000,
+        initialize={"warm_start": [{"x1": 0}]},
+        early_stopping=early_stopping,
+    )
+    hyper.run()
+
+
+def test_early_stop_3():
+    def objective_function(para):
+        score = -para["x1"] * para["x1"]
+        return score
+
+    search_space = {
+        "x1": list(np.arange(0, 100, 0.1)),
+    }
+
+    n_iter_no_change = 5
+    early_stopping = {
+        "n_iter_no_change": n_iter_no_change,
+    }
+
+    hyper = Hyperactive()
+    hyper.add_search(
+        objective_function,
+        search_space,
+        n_iter=100000,
+        initialize={"warm_start": [{"x1": 0}]},
+        early_stopping=early_stopping,
+    )
+    hyper.run()
+
+    search_data = hyper.search_data(objective_function)
+    n_performed_iter = len(search_data)
+
+    print("\n n_performed_iter \n", n_performed_iter)
+    print("\n n_iter_no_change \n", n_iter_no_change)
+
+    assert n_performed_iter == (n_iter_no_change + 1)
+
+
+def test_early_stop_4():
+    def objective_function(para):
+        return para["x1"]
+
+    search_space = {
+        "x1": list(np.arange(0, 100, 0.1)),
+    }
+
+    n_iter_no_change = 5
+    early_stopping = {
+        "n_iter_no_change": 5,
+        "tol_abs": 0.1,
+        "tol_rel": None,
+    }
+
+    start1 = {"x1": 0}
+    start2 = {"x1": 0.1}
+    start3 = {"x1": 0.2}
+    start4 = {"x1": 0.3}
+    start5 = {"x1": 0.4}
+
+    warm_start_l = [
+        start1,
+        start1,
+        start1,
+        start1,
+        start1,
+        start2,
+        start2,
+        start2,
+        start3,
+        start3,
+        start3,
+        start4,
+        start4,
+        start4,
+        start5,
+        start5,
+        start5,
+    ]
+    n_iter = len(warm_start_l)
+
+    hyper = Hyperactive()
+    hyper.add_search(
+        objective_function,
+        search_space,
+        n_iter=n_iter,
+        initialize={"warm_start": warm_start_l},
+        early_stopping=early_stopping,
+    )
+    hyper.run()
+
+    search_data = hyper.search_data(objective_function)
+    n_performed_iter = len(search_data)
+
+    print("\n n_performed_iter \n", n_performed_iter)
+    print("\n n_iter_no_change \n", n_iter_no_change)
+
+    assert n_performed_iter == n_iter
+
+
+def test_early_stop_5():
+    def objective_function(para):
+        return para["x1"]
+
+    search_space = {
+        "x1": list(np.arange(0, 100, 0.01)),
+    }
+
+    n_iter_no_change = 5
+    early_stopping = {
+        "n_iter_no_change": n_iter_no_change,
+        "tol_abs": 0.1,
+        "tol_rel": None,
+    }
+
+    start1 = {"x1": 0}
+    start2 = {"x1": 0.09}
+    start3 = {"x1": 0.20}
+
+    warm_start_l = [
+        start1,
+        start1,
+        start1,
+        start1,
+        start1,
+        start2,
+        start2,
+        start2,
+        start3,
+        start3,
+        start3,
+    ]
+    n_iter = len(warm_start_l)
+
+    hyper = Hyperactive()
+    hyper.add_search(
+        objective_function,
+        search_space,
+        n_iter=n_iter,
+        initialize={"warm_start": warm_start_l},
+        early_stopping=early_stopping,
+    )
+    hyper.run()
+
+    search_data = hyper.search_data(objective_function)
+    n_performed_iter = len(search_data)
+
+    print("\n n_performed_iter \n", n_performed_iter)
+    print("\n n_iter_no_change \n", n_iter_no_change)
+
+    assert n_performed_iter == (n_iter_no_change + 1)
+
+
+def test_early_stop_6():
+    def objective_function(para):
+        return para["x1"]
+
+    search_space = {
+        "x1": list(np.arange(0, 100, 0.01)),
+    }
+
+    n_iter_no_change = 5
+    early_stopping = {
+        "n_iter_no_change": 5,
+        "tol_abs": None,
+        "tol_rel": 10,
+    }
+
+    start1 = {"x1": 1}
+    start2 = {"x1": 1.1}
+    start3 = {"x1": 1.22}
+    start4 = {"x1": 1.35}
+    start5 = {"x1": 1.48}
+
+    warm_start_l = [
+        start1,
+        start1,
+        start1,
+        start1,
+        start1,
+        start2,
+        start2,
+        start2,
+        start3,
+        start3,
+        start3,
+        start4,
+        start4,
+        start4,
+        start5,
+        start5,
+        start5,
+    ]
+    n_iter = len(warm_start_l)
+
+    hyper = Hyperactive()
+    hyper.add_search(
+        objective_function,
+        search_space,
+        n_iter=n_iter,
+        initialize={"warm_start": warm_start_l},
+        early_stopping=early_stopping,
+    )
+    hyper.run()
+
+    search_data = hyper.search_data(objective_function)
+    n_performed_iter = len(search_data)
+
+    print("\n n_performed_iter \n", n_performed_iter)
+    print("\n n_iter_no_change \n", n_iter_no_change)
+
+    assert n_performed_iter == n_iter
+
+
+def test_early_stop_7():
+    def objective_function(para):
+        return para["x1"]
+
+    search_space = {
+        "x1": list(np.arange(0, 100, 0.01)),
+    }
+
+    n_iter_no_change = 5
+    early_stopping = {
+        "n_iter_no_change": n_iter_no_change,
+        "tol_abs": None,
+        "tol_rel": 10,
+    }
+
+    start1 = {"x1": 1}
+    start2 = {"x1": 1.09}
+    start3 = {"x1": 1.20}
+
+    warm_start_l = [
+        start1,
+        start1,
+        start1,
+        start1,
+        start1,
+        start2,
+        start2,
+        start2,
+        start3,
+        start3,
+        start3,
+    ]
+    n_iter = len(warm_start_l)
+
+    hyper = Hyperactive()
+    hyper.add_search(
+        objective_function,
+        search_space,
+        n_iter=n_iter,
+        initialize={"warm_start": warm_start_l},
+        early_stopping=early_stopping,
+    )
+    hyper.run()
+
+    search_data = hyper.search_data(objective_function)
+    n_performed_iter = len(search_data)
+
+    print("\n n_performed_iter \n", n_performed_iter)
+    print("\n n_iter_no_change \n", n_iter_no_change)
+
+    assert n_performed_iter == (n_iter_no_change + 1)