Fix on test notebook for input change in jit function and change in bootstrap

Also remove prange function from numba

Author: Jacobluke-

dabest/_stats_tools/confint_2group_diff.py

@@ -125,7 +125,7 @@ def bootstrap_indices(is_paired, x0_len, x1_len, resamples, random_seed):
     np.random.seed(random_seed)
     indices = np.empty((resamples, x0_len if is_paired else x0_len + x1_len), dtype=np.int64)
 
-    for i in prange(resamples):
+    for i in range(resamples):
         if is_paired:
             indices[i, :x0_len] = np.random.choice(x0_len, x0_len)
         else:  
@@ -170,7 +170,7 @@ def delta2_bootstrap_loop(x1, x2, x3, x4, resamples, pooled_sd, rng_seed, is_pai
 
 
     # Bootstrapping
-    for i in prange(resamples):
+    for i in range(resamples):
         # Paired or unpaired resampling
         if is_paired:
             indices_1 = np.random.choice(len(x1),len(x1))

nbs/API/confint_2group_diff.ipynb

@@ -181,7 +181,7 @@
     "    np.random.seed(random_seed)\n",
     "    indices = np.empty((resamples, x0_len if is_paired else x0_len + x1_len), dtype=np.int64)\n",
     "    \n",
-    "    for i in prange(resamples):\n",
+    "    for i in range(resamples):\n",
     "        if is_paired:\n",
     "            indices[i, :x0_len] = np.random.choice(x0_len, x0_len)\n",
     "        else:  \n",
@@ -226,7 +226,7 @@
     "    \n",
     "\n",
     "    # Bootstrapping\n",
-    "    for i in prange(resamples):\n",
+    "    for i in range(resamples):\n",
     "        # Paired or unpaired resampling\n",
     "        if is_paired:\n",
     "            indices_1 = np.random.choice(len(x1),len(x1))\n",

nbs/tests/test_01_effsizes_pvals.ipynb

@@ -192,7 +192,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "hedges_g = effsize.hedges_g(paired_wellbeing.pre, paired_wellbeing.post,\n",
+    "hedges_g = effsize.hedges_g(np.array(paired_wellbeing.pre), np.array(paired_wellbeing.post),\n",
     "                            is_paired=\"baseline\")\n",
     "assert np.round(hedges_g, 2) == pytest.approx(0.33)"
    ]
@@ -212,7 +212,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "cohens_h = effsize.cohens_h(smoke.low, smoke.high)\n",
+    "cohens_h = effsize.cohens_h(np.array(smoke.low), np.array(smoke.high))\n",
     "assert np.round(cohens_h, 2) == pytest.approx(0.17)"
    ]
   },
@@ -231,10 +231,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "likert_delta = effsize.cliffs_delta(likert_treatment, likert_control)\n",
+    "likert_delta = effsize.cliffs_delta(np.array(likert_treatment), np.array(likert_control))\n",
     "assert likert_delta == pytest.approx(-0.25)\n",
     "\n",
-    "scores_delta = effsize.cliffs_delta(b_scores, a_scores)\n",
+    "scores_delta = effsize.cliffs_delta(np.array(b_scores), np.array(a_scores))\n",
     "assert scores_delta == pytest.approx(0.65)"
    ]
   },

nbs/tests/test_02_edge_cases.ipynb

@@ -49,7 +49,7 @@
     "random_seed=12345\n",
     "\n",
     "# rng = RandomState(MT19937(random_seed))\n",
-    "rng = RandomState(PCG64(12345))\n",
+    "rng = RandomState(PCG64(random_seed))\n",
     "# rng = np.random.default_rng(seed=random_seed)\n",
     "\n",
     "df = pd.DataFrame(\n",
@@ -63,19 +63,10 @@
     "            idx=['Group 1', 'Group 2'])\n",
     "\n",
     "md = test.mean_diff.results\n",
-    "\n",
     "assert md.difference[0] == pytest.approx(-0.0322, abs=1e-4)\n",
-    "assert md.bca_low[0]    == pytest.approx(-0.2279, abs=1e-4)\n",
-    "assert md.bca_high[0]   == pytest.approx(0.1613, abs=1e-4)"
+    "assert md.bca_low[0]    == pytest.approx(-0.2268, abs=1e-4)\n",
+    "assert md.bca_high[0]   == pytest.approx(0.1524, abs=1e-4)"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "afc96b46",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {

nbs/tests/test_04_repeated_measures_effsizes_pvals.ipynb

@@ -324,6 +324,10 @@
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,

nbs/tests/test_99_confidence_intervals.ipynb

@@ -55,8 +55,9 @@
     "             paired=\"baseline\", id_col=\"subject_id\")\n",
     "paired_mean_diff = ex_bp.mean_diff.results\n",
     "\n",
-    "assert pytest.approx(3.875) == paired_mean_diff.bca_low[0]\n",
-    "assert pytest.approx(9.5) == paired_mean_diff.bca_high[0]"
+    "\n",
+    "assert pytest.approx(3.625) == paired_mean_diff.bca_low[0]\n",
+    "assert pytest.approx(9.125) == paired_mean_diff.bca_high[0]"
    ]
   },
   {
@@ -198,21 +199,17 @@
     "assert error_count_median_diff  <= max_errors\n",
     "assert error_count_cliffs_delta <= max_errors\n"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "9da1b76d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
    "display_name": "python3",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.8"
   }
  },
  "nbformat": 4,