From ee10a8e9f365403c8f780bec39affaebaec01005 Mon Sep 17 00:00:00 2001
From: Wanrun Jiang <58099845+Vibsteamer@users.noreply.github.com>
Date: Thu, 24 Jul 2025 23:05:06 +0800
Subject: [PATCH 1/3] Update report_adaptive_lower.py

---
 dpgen2/exploration/report/report_adaptive_lower.py | 10 ++++++----
 1 file changed, 6 insertions(+), 4 deletions(-)

diff --git a/dpgen2/exploration/report/report_adaptive_lower.py b/dpgen2/exploration/report/report_adaptive_lower.py
index cd6087f2..33df129f 100644
--- a/dpgen2/exploration/report/report_adaptive_lower.py
+++ b/dpgen2/exploration/report/report_adaptive_lower.py
@@ -446,11 +446,13 @@ def _get_candidates_inv_pop_f(
         self.candi_picked = [(ii[0], ii[1]) for ii in self.candi]
         if max_nframes is not None and max_nframes < len(self.candi_picked):
             prob = self._choice_prob_inv_pop_f(self.candi_picked)
-            ret = random.choices(
-                self.candi_picked,
-                weights=prob,
-                k=max_nframes,
+            indices = np.random.choice(
+                len(self.candi_picked),
+                size=max_nframes,
+                replace=False,
+                p=prob / np.sum(prob)
             )
+            ret = [self.candi_picked[i] for i in indices]
         else:
             ret = self.candi_picked
         return ret

From 9f50df64df1258e5cdefd85de6fda380e1f419bd Mon Sep 17 00:00:00 2001
From: Wanrun Jiang <58099845+Vibsteamer@users.noreply.github.com>
Date: Thu, 24 Jul 2025 23:14:07 +0800
Subject: [PATCH 2/3] Update test_report_adaptive_lower.py

optimized for non-repeative sampling
---
 .../exploration/test_report_adaptive_lower.py | 28 ++++++++++---------
 1 file changed, 15 insertions(+), 13 deletions(-)

diff --git a/tests/exploration/test_report_adaptive_lower.py b/tests/exploration/test_report_adaptive_lower.py
index f5c13354..ccd7c046 100644
--- a/tests/exploration/test_report_adaptive_lower.py
+++ b/tests/exploration/test_report_adaptive_lower.py
@@ -198,30 +198,32 @@ def test_f_inv_pop(self):
         )
 
         def faked_choices(
-            candi,
-            weights=None,
-            k=0,
+            a,  #numb_candi
+            size=None,  #numb_select
+            replace=False, # non-repeative sampling
+            p=None,  # normalized prob
         ):
             # hist: 2bins, 0.1-0.4 5candi, 0.4-0.7 7candi
             # only return those with mdf 0.1-0.4
-            self.assertEqual(len(weights), 12)
-            self.assertEqual(len(candi), 12)
-            ret = []
-            for ii in range(len(candi)):
-                tidx, fidx = candi[ii]
+            candi = ter.candi_picked 
+            self.assertEqual(a, 12)
+            self.assertEqual(len(p), 12)
+            ret_indices = []
+            for ii in range(a):
+                tidx, fidx = candi[ii] 
                 this_mdf = md_f[tidx][fidx]
                 if this_mdf < 0.4:
-                    self.assertAlmostEqual(weights[ii], 1.0 / 5.0)
-                    ret.append(candi[ii])
+                    self.assertAlmostEqual(p[ii], 0.1)  # 1/5 / 2.0
+                    ret_indices.append(ii)
                 else:
-                    self.assertAlmostEqual(weights[ii], 1.0 / 7.0)
-            return ret
+                    self.assertAlmostEqual(p[ii], 1.0 / 14.0)  # 1/7 / 2.0
+            return ret_indices
 
         ter.record(model_devi)
         self.assertEqual(ter.candi, expected_cand)
         self.assertEqual(ter.accur, expected_accu)
         self.assertEqual(set(ter.failed), expected_fail)
-        with mock.patch("random.choices", faked_choices):
+        with mock.patch("numpy.random.choice", faked_choices):
             picked = ter.get_candidate_ids(11)
         self.assertFalse(ter.converged([]))
         self.assertEqual(len(picked), 2)

From f0e844d92e9d6905ce9bbf31d8f73cd9f5fcda9a Mon Sep 17 00:00:00 2001
From: "pre-commit-ci[bot]"
 <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Date: Thu, 24 Jul 2025 15:39:44 +0000
Subject: [PATCH 3/3] [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci
---
 dpgen2/exploration/report/report_adaptive_lower.py |  2 +-
 tests/exploration/test_report_adaptive_lower.py    | 10 +++++-----
 2 files changed, 6 insertions(+), 6 deletions(-)

diff --git a/dpgen2/exploration/report/report_adaptive_lower.py b/dpgen2/exploration/report/report_adaptive_lower.py
index 33df129f..cd2989f3 100644
--- a/dpgen2/exploration/report/report_adaptive_lower.py
+++ b/dpgen2/exploration/report/report_adaptive_lower.py
@@ -450,7 +450,7 @@ def _get_candidates_inv_pop_f(
                 len(self.candi_picked),
                 size=max_nframes,
                 replace=False,
-                p=prob / np.sum(prob)
+                p=prob / np.sum(prob),
             )
             ret = [self.candi_picked[i] for i in indices]
         else:
diff --git a/tests/exploration/test_report_adaptive_lower.py b/tests/exploration/test_report_adaptive_lower.py
index ccd7c046..b5f123ca 100644
--- a/tests/exploration/test_report_adaptive_lower.py
+++ b/tests/exploration/test_report_adaptive_lower.py
@@ -198,19 +198,19 @@ def test_f_inv_pop(self):
         )
 
         def faked_choices(
-            a,  #numb_candi
-            size=None,  #numb_select
-            replace=False, # non-repeative sampling
+            a,  # numb_candi
+            size=None,  # numb_select
+            replace=False,  # non-repeative sampling
             p=None,  # normalized prob
         ):
             # hist: 2bins, 0.1-0.4 5candi, 0.4-0.7 7candi
             # only return those with mdf 0.1-0.4
-            candi = ter.candi_picked 
+            candi = ter.candi_picked
             self.assertEqual(a, 12)
             self.assertEqual(len(p), 12)
             ret_indices = []
             for ii in range(a):
-                tidx, fidx = candi[ii] 
+                tidx, fidx = candi[ii]
                 this_mdf = md_f[tidx][fidx]
                 if this_mdf < 0.4:
                     self.assertAlmostEqual(p[ii], 0.1)  # 1/5 / 2.0