diff --git a/fsrs4anki_optimizer.ipynb b/fsrs4anki_optimizer.ipynb
index b624b84..79a5157 100644
--- a/fsrs4anki_optimizer.ipynb
+++ b/fsrs4anki_optimizer.ipynb
@@ -5,9 +5,9 @@
       "cell_type": "markdown",
       "metadata": {},
       "source": [
-        "# FSRS4Anki v4.0.2 Optimizer\n",
+        "# FSRS4Anki v4.0.3 Optimizer\n",
         "\n",
-        "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/v4.0.2/fsrs4anki_optimizer.ipynb)\n",
+        "[![open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-spaced-repetition/fsrs4anki/blob/v4.0.3/fsrs4anki_optimizer.ipynb)\n",
         "\n",
         "↑ Click the above button to open the optimizer on Google Colab.\n",
         "\n",
@@ -50,7 +50,7 @@
         "\n",
         "filename = \"collection-2022-09-18@13-21-58.colpkg\"\n",
         "# If you upload deck file, replace it with your deck filename. E.g., ALL__Learning.apkg\n",
-        "# If you upload collection file, replace it with your colpgk filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
+        "# If you upload collection file, replace it with your colpkg filename. E.g., collection-2022-09-18@13-21-58.colpkg\n",
         "\n",
         "# Replace it with your timezone. I'm in China, so I use Asia/Shanghai.\n",
         "# You can find your timezone here: https://gist.github.com/heyalexej/8bf688fd67d7199be4a1682b3eec7568\n",
@@ -106,7 +106,7 @@
         }
       ],
       "source": [
-        "%pip install -q fsrs4anki_optimizer==4.0.2\n",
+        "%pip install -q fsrs4anki_optimizer==4.0.3\n",
         "# for local development\n",
         "# import os\n",
         "# import sys\n",
@@ -162,7 +162,7 @@
         {
           "data": {
             "application/vnd.jupyter.widget-view+json": {
-              "model_id": "c41ea9da400c454aaa5e5f05b3ce9ad5",
+              "model_id": "6b72474cfa8d455ca82bb998e0969207",
               "version_major": 2,
               "version_minor": 0
             },
@@ -183,7 +183,7 @@
         {
           "data": {
             "application/vnd.jupyter.widget-view+json": {
-              "model_id": "aa2c38f92a63447abef25a94cc76a5b7",
+              "model_id": "3695c998fddf4efc81a4c4e79247d7fd",
               "version_major": 2,
               "version_minor": 0
             },
@@ -280,7 +280,7 @@
         {
           "data": {
             "application/vnd.jupyter.widget-view+json": {
-              "model_id": "42b5ef7fa7e44edb8e9a0ead988de3bf",
+              "model_id": "872c7423a89c42009139d2f542224197",
               "version_major": 2,
               "version_minor": 0
             },
@@ -303,7 +303,7 @@
         {
           "data": {
             "application/vnd.jupyter.widget-view+json": {
-              "model_id": "6c40f000fbae4cf48786764b2c3434a9",
+              "model_id": "822fe528de9b43698c947d2b91035bc3",
               "version_major": 2,
               "version_minor": 0
             },
@@ -325,7 +325,7 @@
         {
           "data": {
             "application/vnd.jupyter.widget-view+json": {
-              "model_id": "ac26905ba66c4dfa864502471f060ffb",
+              "model_id": "a2d347bae3ca41b8afb30d318e7caee6",
               "version_major": 2,
               "version_minor": 0
             },
@@ -347,7 +347,7 @@
         {
           "data": {
             "application/vnd.jupyter.widget-view+json": {
-              "model_id": "8d5fdf443e554353bbaffd75c11271dd",
+              "model_id": "3e89e1b67d41424fab1291b8125401bd",
               "version_major": 2,
               "version_minor": 0
             },
@@ -369,7 +369,7 @@
         {
           "data": {
             "application/vnd.jupyter.widget-view+json": {
-              "model_id": "39c345d11d4e4521a2d99f3f2bb172d3",
+              "model_id": "0734fd18dbb5418ca23a03999baaaf5b",
               "version_major": 2,
               "version_minor": 0
             },
@@ -391,7 +391,7 @@
         {
           "data": {
             "application/vnd.jupyter.widget-view+json": {
-              "model_id": "cf1cdaae77134454b715149633919d30",
+              "model_id": "95dfe733a2e2473084090d49b8b46be2",
               "version_major": 2,
               "version_minor": 0
             },
@@ -412,61 +412,19 @@
         },
         {
           "data": {
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",
             "text/plain": [
-              "<Figure size 640x480 with 1 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 1 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 1 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 1 Axes>"
+              "[]"
             ]
           },
+          "execution_count": 4,
           "metadata": {},
-          "output_type": "display_data"
-        },
-        {
-          "data": {
-            "image/png": 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",
-            "text/plain": [
-              "<Figure size 640x480 with 1 Axes>"
-            ]
-          },
-          "metadata": {},
-          "output_type": "display_data"
+          "output_type": "execute_result"
         }
       ],
       "source": [
         "optimizer.define_model()\n",
         "optimizer.pretrain(verbose=False)\n",
-        "figs = optimizer.train(verbose=False)\n",
-        "for f in figs:\n",
-        "    f.show()"
+        "optimizer.train(verbose=False)"
       ]
     },
     {
@@ -496,12 +454,15 @@
           "name": "stdout",
           "output_type": "stream",
           "text": [
-            "[1.25, 1.72, 8.75, 16.53, 5.5432, 1.3275, 1.0602, 0.0071, 1.4928, 0.1338, 0.9143, 2.7053, 0.0118, 0.3176, 0.4736, 0.0, 2.1409]\n"
+            "[1.25, 1.72, 8.75, 16.53, 5.5432, 1.3275, 1.0602, 0.0071, 1.4928, 0.1338, 0.9143, 2.7053, 0.0118, 0.3176, 0.4736, 0.0, 2.1409]\n",
+            "\n",
+            "\u001b[91mNote\u001b[0m: These values should be used with FSRS scheduler v4.0.0 or above.\n"
           ]
         }
       ],
       "source": [
-        "print(optimizer.w)"
+        "print(optimizer.w)\n",
+        "print(\"\\n\\033[91mNote\\033[0m: These values should be used with FSRS scheduler v4.0.0 or above.\")"
       ]
     },
     {
@@ -679,7 +640,7 @@
         {
           "data": {
             "application/vnd.jupyter.widget-view+json": {
-              "model_id": "a5c5ecfcbf92498b98c92b9d825ad1fa",
+              "model_id": "06c1e449b7234f6eae1321101d405269",
               "version_major": 2,
               "version_minor": 0
             },
@@ -877,171 +838,171 @@
           "data": {
             "text/html": [
               "<style type=\"text/css\">\n",
-              "#T_21c79_row0_col0, #T_21c79_row0_col1, #T_21c79_row0_col2, #T_21c79_row0_col3, #T_21c79_row0_col4, #T_21c79_row0_col5, #T_21c79_row0_col6, #T_21c79_row1_col0, #T_21c79_row1_col1, #T_21c79_row1_col2, #T_21c79_row1_col3, #T_21c79_row1_col4, #T_21c79_row1_col6, #T_21c79_row2_col0, #T_21c79_row2_col1, #T_21c79_row2_col2, #T_21c79_row2_col3, #T_21c79_row2_col5, #T_21c79_row2_col6, #T_21c79_row3_col0, #T_21c79_row3_col1, #T_21c79_row3_col2, #T_21c79_row3_col3, #T_21c79_row3_col4, #T_21c79_row3_col6, #T_21c79_row4_col0, #T_21c79_row4_col1, #T_21c79_row4_col2, #T_21c79_row4_col3, #T_21c79_row4_col4, #T_21c79_row4_col6, #T_21c79_row5_col0, #T_21c79_row5_col1, #T_21c79_row5_col2, #T_21c79_row5_col3, #T_21c79_row5_col4, #T_21c79_row6_col0, #T_21c79_row6_col1, #T_21c79_row6_col2, #T_21c79_row6_col4, #T_21c79_row7_col0, #T_21c79_row7_col1, #T_21c79_row7_col2, #T_21c79_row8_col0, #T_21c79_row8_col1, #T_21c79_row8_col2, #T_21c79_row9_col0, #T_21c79_row9_col2, #T_21c79_row11_col2, #T_21c79_row12_col2, #T_21c79_row13_col0, #T_21c79_row13_col2, #T_21c79_row13_col6, #T_21c79_row13_col7, #T_21c79_row14_col0, #T_21c79_row14_col2, #T_21c79_row14_col6, #T_21c79_row14_col7, #T_21c79_row15_col0, #T_21c79_row15_col2, #T_21c79_row15_col5, #T_21c79_row15_col6, #T_21c79_row15_col7, #T_21c79_row16_col0, #T_21c79_row16_col2, #T_21c79_row16_col4, #T_21c79_row16_col5, #T_21c79_row16_col6, #T_21c79_row16_col7, #T_21c79_row17_col0, #T_21c79_row17_col2, #T_21c79_row17_col3, #T_21c79_row17_col4, #T_21c79_row17_col5, #T_21c79_row17_col6, #T_21c79_row17_col7 {\n",
+              "#T_d0fb6_row0_col0, #T_d0fb6_row0_col1, #T_d0fb6_row0_col2, #T_d0fb6_row0_col3, #T_d0fb6_row0_col4, #T_d0fb6_row0_col5, #T_d0fb6_row0_col6, #T_d0fb6_row1_col0, #T_d0fb6_row1_col1, #T_d0fb6_row1_col2, #T_d0fb6_row1_col3, #T_d0fb6_row1_col4, #T_d0fb6_row1_col6, #T_d0fb6_row2_col0, #T_d0fb6_row2_col1, #T_d0fb6_row2_col2, #T_d0fb6_row2_col3, #T_d0fb6_row2_col5, #T_d0fb6_row2_col6, #T_d0fb6_row3_col0, #T_d0fb6_row3_col1, #T_d0fb6_row3_col2, #T_d0fb6_row3_col3, #T_d0fb6_row3_col4, #T_d0fb6_row3_col6, #T_d0fb6_row4_col0, #T_d0fb6_row4_col1, #T_d0fb6_row4_col2, #T_d0fb6_row4_col3, #T_d0fb6_row4_col4, #T_d0fb6_row4_col6, #T_d0fb6_row5_col0, #T_d0fb6_row5_col1, #T_d0fb6_row5_col2, #T_d0fb6_row5_col3, #T_d0fb6_row5_col4, #T_d0fb6_row6_col0, #T_d0fb6_row6_col1, #T_d0fb6_row6_col2, #T_d0fb6_row6_col4, #T_d0fb6_row7_col0, #T_d0fb6_row7_col1, #T_d0fb6_row7_col2, #T_d0fb6_row8_col0, #T_d0fb6_row8_col1, #T_d0fb6_row8_col2, #T_d0fb6_row9_col0, #T_d0fb6_row9_col2, #T_d0fb6_row11_col2, #T_d0fb6_row12_col2, #T_d0fb6_row13_col0, #T_d0fb6_row13_col2, #T_d0fb6_row13_col6, #T_d0fb6_row13_col7, #T_d0fb6_row14_col0, #T_d0fb6_row14_col2, #T_d0fb6_row14_col6, #T_d0fb6_row14_col7, #T_d0fb6_row15_col0, #T_d0fb6_row15_col2, #T_d0fb6_row15_col5, #T_d0fb6_row15_col6, #T_d0fb6_row15_col7, #T_d0fb6_row16_col0, #T_d0fb6_row16_col2, #T_d0fb6_row16_col4, #T_d0fb6_row16_col5, #T_d0fb6_row16_col6, #T_d0fb6_row16_col7, #T_d0fb6_row17_col0, #T_d0fb6_row17_col2, #T_d0fb6_row17_col3, #T_d0fb6_row17_col4, #T_d0fb6_row17_col5, #T_d0fb6_row17_col6, #T_d0fb6_row17_col7 {\n",
               "  background-color: #000000;\n",
               "  color: #f1f1f1;\n",
               "}\n",
-              "#T_21c79_row0_col7 {\n",
+              "#T_d0fb6_row0_col7 {\n",
               "  background-color: #a5a5ff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row1_col5, #T_21c79_row8_col6, #T_21c79_row14_col4 {\n",
+              "#T_d0fb6_row1_col5, #T_d0fb6_row8_col6, #T_d0fb6_row14_col4 {\n",
               "  background-color: #ffe5e5;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row1_col7, #T_21c79_row14_col5, #T_21c79_row15_col3 {\n",
+              "#T_d0fb6_row1_col7, #T_d0fb6_row14_col5, #T_d0fb6_row15_col3 {\n",
               "  background-color: #b9b9ff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row2_col4, #T_21c79_row8_col5, #T_21c79_row12_col4 {\n",
+              "#T_d0fb6_row2_col4, #T_d0fb6_row8_col5, #T_d0fb6_row12_col4 {\n",
               "  background-color: #ffd1d1;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row2_col7 {\n",
+              "#T_d0fb6_row2_col7 {\n",
               "  background-color: #9d9dff;\n",
               "  color: #f1f1f1;\n",
               "}\n",
-              "#T_21c79_row3_col5 {\n",
+              "#T_d0fb6_row3_col5 {\n",
               "  background-color: #9191ff;\n",
               "  color: #f1f1f1;\n",
               "}\n",
-              "#T_21c79_row3_col7 {\n",
+              "#T_d0fb6_row3_col7 {\n",
               "  background-color: #d5d5ff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row4_col5, #T_21c79_row7_col5, #T_21c79_row8_col7, #T_21c79_row12_col6 {\n",
+              "#T_d0fb6_row4_col5, #T_d0fb6_row7_col5, #T_d0fb6_row8_col7, #T_d0fb6_row12_col6 {\n",
               "  background-color: #ffdddd;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row4_col7, #T_21c79_row12_col1 {\n",
+              "#T_d0fb6_row4_col7, #T_d0fb6_row12_col1 {\n",
               "  background-color: #e1e1ff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row5_col5, #T_21c79_row6_col7, #T_21c79_row8_col3, #T_21c79_row9_col3 {\n",
+              "#T_d0fb6_row5_col5, #T_d0fb6_row6_col7, #T_d0fb6_row8_col3, #T_d0fb6_row9_col3 {\n",
               "  background-color: #ededff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row5_col6, #T_21c79_row11_col5 {\n",
+              "#T_d0fb6_row5_col6, #T_d0fb6_row11_col5 {\n",
               "  background-color: #ffa9a9;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row5_col7, #T_21c79_row9_col1 {\n",
+              "#T_d0fb6_row5_col7, #T_d0fb6_row9_col1 {\n",
               "  background-color: #fff1f1;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row6_col3, #T_21c79_row6_col5, #T_21c79_row11_col0, #T_21c79_row11_col1 {\n",
+              "#T_d0fb6_row6_col3, #T_d0fb6_row6_col5, #T_d0fb6_row11_col0, #T_d0fb6_row11_col1 {\n",
               "  background-color: #e9e9ff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row6_col6, #T_21c79_row12_col3 {\n",
+              "#T_d0fb6_row6_col6, #T_d0fb6_row12_col3 {\n",
               "  background-color: #ffc9c9;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row7_col3, #T_21c79_row9_col4, #T_21c79_row10_col0, #T_21c79_row10_col3, #T_21c79_row12_col5 {\n",
+              "#T_d0fb6_row7_col3, #T_d0fb6_row9_col4, #T_d0fb6_row10_col0, #T_d0fb6_row10_col3, #T_d0fb6_row12_col5 {\n",
               "  background-color: #ffeded;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row7_col4, #T_21c79_row10_col4 {\n",
+              "#T_d0fb6_row7_col4, #T_d0fb6_row10_col4 {\n",
               "  background-color: #ffd9d9;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row7_col6 {\n",
+              "#T_d0fb6_row7_col6 {\n",
               "  background-color: #ff9595;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row7_col7, #T_21c79_row9_col7 {\n",
+              "#T_d0fb6_row7_col7, #T_d0fb6_row9_col7 {\n",
               "  background-color: #fff9f9;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row8_col4 {\n",
+              "#T_d0fb6_row8_col4 {\n",
               "  background-color: #ffbdbd;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row9_col5 {\n",
+              "#T_d0fb6_row9_col5 {\n",
               "  background-color: #ffb1b1;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row9_col6, #T_21c79_row10_col2, #T_21c79_row13_col3 {\n",
+              "#T_d0fb6_row9_col6, #T_d0fb6_row10_col2, #T_d0fb6_row13_col3 {\n",
               "  background-color: #ffe9e9;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row10_col1, #T_21c79_row11_col3 {\n",
+              "#T_d0fb6_row10_col1, #T_d0fb6_row11_col3 {\n",
               "  background-color: #fdfdff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row10_col5 {\n",
+              "#T_d0fb6_row10_col5 {\n",
               "  background-color: #ff7d7d;\n",
               "  color: #f1f1f1;\n",
               "}\n",
-              "#T_21c79_row10_col6 {\n",
+              "#T_d0fb6_row10_col6 {\n",
               "  background-color: #ffa5a5;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row10_col7, #T_21c79_row14_col1 {\n",
+              "#T_d0fb6_row10_col7, #T_d0fb6_row14_col1 {\n",
               "  background-color: #fffdfd;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row11_col4 {\n",
+              "#T_d0fb6_row11_col4 {\n",
               "  background-color: #ff8d8d;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row11_col6 {\n",
+              "#T_d0fb6_row11_col6 {\n",
               "  background-color: #ffb5b5;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row11_col7, #T_21c79_row13_col5 {\n",
+              "#T_d0fb6_row11_col7, #T_d0fb6_row13_col5 {\n",
               "  background-color: #ffc5c5;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row12_col0 {\n",
+              "#T_d0fb6_row12_col0 {\n",
               "  background-color: #c9c9ff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row12_col7 {\n",
+              "#T_d0fb6_row12_col7 {\n",
               "  background-color: #fff5f5;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row13_col1, #T_21c79_row17_col1 {\n",
+              "#T_d0fb6_row13_col1, #T_d0fb6_row17_col1 {\n",
               "  background-color: #e5e5ff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row13_col4 {\n",
+              "#T_d0fb6_row13_col4 {\n",
               "  background-color: #ffa1a1;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row14_col3 {\n",
+              "#T_d0fb6_row14_col3 {\n",
               "  background-color: #d1d1ff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row15_col1 {\n",
+              "#T_d0fb6_row15_col1 {\n",
               "  background-color: #ddddff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row15_col4 {\n",
+              "#T_d0fb6_row15_col4 {\n",
               "  background-color: #bdbdff;\n",
               "  color: #000000;\n",
               "}\n",
-              "#T_21c79_row16_col1 {\n",
+              "#T_d0fb6_row16_col1 {\n",
               "  background-color: #9999ff;\n",
               "  color: #f1f1f1;\n",
               "}\n",
-              "#T_21c79_row16_col3 {\n",
+              "#T_d0fb6_row16_col3 {\n",
               "  background-color: #adadff;\n",
               "  color: #000000;\n",
               "}\n",
               "</style>\n",
-              "<table id=\"T_21c79\">\n",
+              "<table id=\"T_d0fb6\">\n",
               "  <thead>\n",
               "    <tr>\n",
               "      <th class=\"index_name level0\" >d_bin</th>\n",
-              "      <th id=\"T_21c79_level0_col0\" class=\"col_heading level0 col0\" >3</th>\n",
-              "      <th id=\"T_21c79_level0_col1\" class=\"col_heading level0 col1\" >4</th>\n",
-              "      <th id=\"T_21c79_level0_col2\" class=\"col_heading level0 col2\" >5</th>\n",
-              "      <th id=\"T_21c79_level0_col3\" class=\"col_heading level0 col3\" >6</th>\n",
-              "      <th id=\"T_21c79_level0_col4\" class=\"col_heading level0 col4\" >7</th>\n",
-              "      <th id=\"T_21c79_level0_col5\" class=\"col_heading level0 col5\" >8</th>\n",
-              "      <th id=\"T_21c79_level0_col6\" class=\"col_heading level0 col6\" >9</th>\n",
-              "      <th id=\"T_21c79_level0_col7\" class=\"col_heading level0 col7\" >10</th>\n",
+              "      <th id=\"T_d0fb6_level0_col0\" class=\"col_heading level0 col0\" >3</th>\n",
+              "      <th id=\"T_d0fb6_level0_col1\" class=\"col_heading level0 col1\" >4</th>\n",
+              "      <th id=\"T_d0fb6_level0_col2\" class=\"col_heading level0 col2\" >5</th>\n",
+              "      <th id=\"T_d0fb6_level0_col3\" class=\"col_heading level0 col3\" >6</th>\n",
+              "      <th id=\"T_d0fb6_level0_col4\" class=\"col_heading level0 col4\" >7</th>\n",
+              "      <th id=\"T_d0fb6_level0_col5\" class=\"col_heading level0 col5\" >8</th>\n",
+              "      <th id=\"T_d0fb6_level0_col6\" class=\"col_heading level0 col6\" >9</th>\n",
+              "      <th id=\"T_d0fb6_level0_col7\" class=\"col_heading level0 col7\" >10</th>\n",
               "    </tr>\n",
               "    <tr>\n",
               "      <th class=\"index_name level0\" >s_bin</th>\n",
@@ -1057,208 +1018,208 @@
               "  </thead>\n",
               "  <tbody>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row0\" class=\"row_heading level0 row0\" >0.710000</th>\n",
-              "      <td id=\"T_21c79_row0_col0\" class=\"data row0 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row0_col1\" class=\"data row0 col1\" ></td>\n",
-              "      <td id=\"T_21c79_row0_col2\" class=\"data row0 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row0_col3\" class=\"data row0 col3\" ></td>\n",
-              "      <td id=\"T_21c79_row0_col4\" class=\"data row0 col4\" ></td>\n",
-              "      <td id=\"T_21c79_row0_col5\" class=\"data row0 col5\" ></td>\n",
-              "      <td id=\"T_21c79_row0_col6\" class=\"data row0 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row0_col7\" class=\"data row0 col7\" >-3.45%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row0\" class=\"row_heading level0 row0\" >0.710000</th>\n",
+              "      <td id=\"T_d0fb6_row0_col0\" class=\"data row0 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row0_col1\" class=\"data row0 col1\" ></td>\n",
+              "      <td id=\"T_d0fb6_row0_col2\" class=\"data row0 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row0_col3\" class=\"data row0 col3\" ></td>\n",
+              "      <td id=\"T_d0fb6_row0_col4\" class=\"data row0 col4\" ></td>\n",
+              "      <td id=\"T_d0fb6_row0_col5\" class=\"data row0 col5\" ></td>\n",
+              "      <td id=\"T_d0fb6_row0_col6\" class=\"data row0 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row0_col7\" class=\"data row0 col7\" >-3.45%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row1\" class=\"row_heading level0 row1\" >1.000000</th>\n",
-              "      <td id=\"T_21c79_row1_col0\" class=\"data row1 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row1_col1\" class=\"data row1 col1\" ></td>\n",
-              "      <td id=\"T_21c79_row1_col2\" class=\"data row1 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row1_col3\" class=\"data row1 col3\" ></td>\n",
-              "      <td id=\"T_21c79_row1_col4\" class=\"data row1 col4\" ></td>\n",
-              "      <td id=\"T_21c79_row1_col5\" class=\"data row1 col5\" >0.99%</td>\n",
-              "      <td id=\"T_21c79_row1_col6\" class=\"data row1 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row1_col7\" class=\"data row1 col7\" >-2.80%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row1\" class=\"row_heading level0 row1\" >1.000000</th>\n",
+              "      <td id=\"T_d0fb6_row1_col0\" class=\"data row1 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row1_col1\" class=\"data row1 col1\" ></td>\n",
+              "      <td id=\"T_d0fb6_row1_col2\" class=\"data row1 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row1_col3\" class=\"data row1 col3\" ></td>\n",
+              "      <td id=\"T_d0fb6_row1_col4\" class=\"data row1 col4\" ></td>\n",
+              "      <td id=\"T_d0fb6_row1_col5\" class=\"data row1 col5\" >0.99%</td>\n",
+              "      <td id=\"T_d0fb6_row1_col6\" class=\"data row1 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row1_col7\" class=\"data row1 col7\" >-2.80%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row2\" class=\"row_heading level0 row2\" >1.400000</th>\n",
-              "      <td id=\"T_21c79_row2_col0\" class=\"data row2 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row2_col1\" class=\"data row2 col1\" ></td>\n",
-              "      <td id=\"T_21c79_row2_col2\" class=\"data row2 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row2_col3\" class=\"data row2 col3\" ></td>\n",
-              "      <td id=\"T_21c79_row2_col4\" class=\"data row2 col4\" >1.78%</td>\n",
-              "      <td id=\"T_21c79_row2_col5\" class=\"data row2 col5\" ></td>\n",
-              "      <td id=\"T_21c79_row2_col6\" class=\"data row2 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row2_col7\" class=\"data row2 col7\" >-3.86%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row2\" class=\"row_heading level0 row2\" >1.400000</th>\n",
+              "      <td id=\"T_d0fb6_row2_col0\" class=\"data row2 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row2_col1\" class=\"data row2 col1\" ></td>\n",
+              "      <td id=\"T_d0fb6_row2_col2\" class=\"data row2 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row2_col3\" class=\"data row2 col3\" ></td>\n",
+              "      <td id=\"T_d0fb6_row2_col4\" class=\"data row2 col4\" >1.78%</td>\n",
+              "      <td id=\"T_d0fb6_row2_col5\" class=\"data row2 col5\" ></td>\n",
+              "      <td id=\"T_d0fb6_row2_col6\" class=\"data row2 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row2_col7\" class=\"data row2 col7\" >-3.86%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row3\" class=\"row_heading level0 row3\" >1.960000</th>\n",
-              "      <td id=\"T_21c79_row3_col0\" class=\"data row3 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row3_col1\" class=\"data row3 col1\" ></td>\n",
-              "      <td id=\"T_21c79_row3_col2\" class=\"data row3 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row3_col3\" class=\"data row3 col3\" ></td>\n",
-              "      <td id=\"T_21c79_row3_col4\" class=\"data row3 col4\" ></td>\n",
-              "      <td id=\"T_21c79_row3_col5\" class=\"data row3 col5\" >-4.24%</td>\n",
-              "      <td id=\"T_21c79_row3_col6\" class=\"data row3 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row3_col7\" class=\"data row3 col7\" >-1.57%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row3\" class=\"row_heading level0 row3\" >1.960000</th>\n",
+              "      <td id=\"T_d0fb6_row3_col0\" class=\"data row3 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row3_col1\" class=\"data row3 col1\" ></td>\n",
+              "      <td id=\"T_d0fb6_row3_col2\" class=\"data row3 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row3_col3\" class=\"data row3 col3\" ></td>\n",
+              "      <td id=\"T_d0fb6_row3_col4\" class=\"data row3 col4\" ></td>\n",
+              "      <td id=\"T_d0fb6_row3_col5\" class=\"data row3 col5\" >-4.24%</td>\n",
+              "      <td id=\"T_d0fb6_row3_col6\" class=\"data row3 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row3_col7\" class=\"data row3 col7\" >-1.57%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row4\" class=\"row_heading level0 row4\" >2.740000</th>\n",
-              "      <td id=\"T_21c79_row4_col0\" class=\"data row4 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row4_col1\" class=\"data row4 col1\" ></td>\n",
-              "      <td id=\"T_21c79_row4_col2\" class=\"data row4 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row4_col3\" class=\"data row4 col3\" ></td>\n",
-              "      <td id=\"T_21c79_row4_col4\" class=\"data row4 col4\" ></td>\n",
-              "      <td id=\"T_21c79_row4_col5\" class=\"data row4 col5\" >1.28%</td>\n",
-              "      <td id=\"T_21c79_row4_col6\" class=\"data row4 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row4_col7\" class=\"data row4 col7\" >-1.25%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row4\" class=\"row_heading level0 row4\" >2.740000</th>\n",
+              "      <td id=\"T_d0fb6_row4_col0\" class=\"data row4 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row4_col1\" class=\"data row4 col1\" ></td>\n",
+              "      <td id=\"T_d0fb6_row4_col2\" class=\"data row4 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row4_col3\" class=\"data row4 col3\" ></td>\n",
+              "      <td id=\"T_d0fb6_row4_col4\" class=\"data row4 col4\" ></td>\n",
+              "      <td id=\"T_d0fb6_row4_col5\" class=\"data row4 col5\" >1.28%</td>\n",
+              "      <td id=\"T_d0fb6_row4_col6\" class=\"data row4 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row4_col7\" class=\"data row4 col7\" >-1.25%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row5\" class=\"row_heading level0 row5\" >3.840000</th>\n",
-              "      <td id=\"T_21c79_row5_col0\" class=\"data row5 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row5_col1\" class=\"data row5 col1\" ></td>\n",
-              "      <td id=\"T_21c79_row5_col2\" class=\"data row5 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row5_col3\" class=\"data row5 col3\" ></td>\n",
-              "      <td id=\"T_21c79_row5_col4\" class=\"data row5 col4\" ></td>\n",
-              "      <td id=\"T_21c79_row5_col5\" class=\"data row5 col5\" >-0.64%</td>\n",
-              "      <td id=\"T_21c79_row5_col6\" class=\"data row5 col6\" >3.39%</td>\n",
-              "      <td id=\"T_21c79_row5_col7\" class=\"data row5 col7\" >0.61%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row5\" class=\"row_heading level0 row5\" >3.840000</th>\n",
+              "      <td id=\"T_d0fb6_row5_col0\" class=\"data row5 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row5_col1\" class=\"data row5 col1\" ></td>\n",
+              "      <td id=\"T_d0fb6_row5_col2\" class=\"data row5 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row5_col3\" class=\"data row5 col3\" ></td>\n",
+              "      <td id=\"T_d0fb6_row5_col4\" class=\"data row5 col4\" ></td>\n",
+              "      <td id=\"T_d0fb6_row5_col5\" class=\"data row5 col5\" >-0.64%</td>\n",
+              "      <td id=\"T_d0fb6_row5_col6\" class=\"data row5 col6\" >3.39%</td>\n",
+              "      <td id=\"T_d0fb6_row5_col7\" class=\"data row5 col7\" >0.61%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row6\" class=\"row_heading level0 row6\" >5.380000</th>\n",
-              "      <td id=\"T_21c79_row6_col0\" class=\"data row6 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row6_col1\" class=\"data row6 col1\" ></td>\n",
-              "      <td id=\"T_21c79_row6_col2\" class=\"data row6 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row6_col3\" class=\"data row6 col3\" >-0.80%</td>\n",
-              "      <td id=\"T_21c79_row6_col4\" class=\"data row6 col4\" ></td>\n",
-              "      <td id=\"T_21c79_row6_col5\" class=\"data row6 col5\" >-0.87%</td>\n",
-              "      <td id=\"T_21c79_row6_col6\" class=\"data row6 col6\" >2.15%</td>\n",
-              "      <td id=\"T_21c79_row6_col7\" class=\"data row6 col7\" >-0.69%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row6\" class=\"row_heading level0 row6\" >5.380000</th>\n",
+              "      <td id=\"T_d0fb6_row6_col0\" class=\"data row6 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row6_col1\" class=\"data row6 col1\" ></td>\n",
+              "      <td id=\"T_d0fb6_row6_col2\" class=\"data row6 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row6_col3\" class=\"data row6 col3\" >-0.80%</td>\n",
+              "      <td id=\"T_d0fb6_row6_col4\" class=\"data row6 col4\" ></td>\n",
+              "      <td id=\"T_d0fb6_row6_col5\" class=\"data row6 col5\" >-0.87%</td>\n",
+              "      <td id=\"T_d0fb6_row6_col6\" class=\"data row6 col6\" >2.15%</td>\n",
+              "      <td id=\"T_d0fb6_row6_col7\" class=\"data row6 col7\" >-0.69%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row7\" class=\"row_heading level0 row7\" >7.530000</th>\n",
-              "      <td id=\"T_21c79_row7_col0\" class=\"data row7 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row7_col1\" class=\"data row7 col1\" ></td>\n",
-              "      <td id=\"T_21c79_row7_col2\" class=\"data row7 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row7_col3\" class=\"data row7 col3\" >0.71%</td>\n",
-              "      <td id=\"T_21c79_row7_col4\" class=\"data row7 col4\" >1.51%</td>\n",
-              "      <td id=\"T_21c79_row7_col5\" class=\"data row7 col5\" >1.34%</td>\n",
-              "      <td id=\"T_21c79_row7_col6\" class=\"data row7 col6\" >4.08%</td>\n",
-              "      <td id=\"T_21c79_row7_col7\" class=\"data row7 col7\" >0.17%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row7\" class=\"row_heading level0 row7\" >7.530000</th>\n",
+              "      <td id=\"T_d0fb6_row7_col0\" class=\"data row7 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row7_col1\" class=\"data row7 col1\" ></td>\n",
+              "      <td id=\"T_d0fb6_row7_col2\" class=\"data row7 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row7_col3\" class=\"data row7 col3\" >0.71%</td>\n",
+              "      <td id=\"T_d0fb6_row7_col4\" class=\"data row7 col4\" >1.51%</td>\n",
+              "      <td id=\"T_d0fb6_row7_col5\" class=\"data row7 col5\" >1.34%</td>\n",
+              "      <td id=\"T_d0fb6_row7_col6\" class=\"data row7 col6\" >4.08%</td>\n",
+              "      <td id=\"T_d0fb6_row7_col7\" class=\"data row7 col7\" >0.17%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row8\" class=\"row_heading level0 row8\" >10.540000</th>\n",
-              "      <td id=\"T_21c79_row8_col0\" class=\"data row8 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row8_col1\" class=\"data row8 col1\" ></td>\n",
-              "      <td id=\"T_21c79_row8_col2\" class=\"data row8 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row8_col3\" class=\"data row8 col3\" >-0.68%</td>\n",
-              "      <td id=\"T_21c79_row8_col4\" class=\"data row8 col4\" >2.50%</td>\n",
-              "      <td id=\"T_21c79_row8_col5\" class=\"data row8 col5\" >1.84%</td>\n",
-              "      <td id=\"T_21c79_row8_col6\" class=\"data row8 col6\" >0.97%</td>\n",
-              "      <td id=\"T_21c79_row8_col7\" class=\"data row8 col7\" >1.39%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row8\" class=\"row_heading level0 row8\" >10.540000</th>\n",
+              "      <td id=\"T_d0fb6_row8_col0\" class=\"data row8 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row8_col1\" class=\"data row8 col1\" ></td>\n",
+              "      <td id=\"T_d0fb6_row8_col2\" class=\"data row8 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row8_col3\" class=\"data row8 col3\" >-0.68%</td>\n",
+              "      <td id=\"T_d0fb6_row8_col4\" class=\"data row8 col4\" >2.50%</td>\n",
+              "      <td id=\"T_d0fb6_row8_col5\" class=\"data row8 col5\" >1.84%</td>\n",
+              "      <td id=\"T_d0fb6_row8_col6\" class=\"data row8 col6\" >0.97%</td>\n",
+              "      <td id=\"T_d0fb6_row8_col7\" class=\"data row8 col7\" >1.39%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row9\" class=\"row_heading level0 row9\" >14.760000</th>\n",
-              "      <td id=\"T_21c79_row9_col0\" class=\"data row9 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row9_col1\" class=\"data row9 col1\" >0.47%</td>\n",
-              "      <td id=\"T_21c79_row9_col2\" class=\"data row9 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row9_col3\" class=\"data row9 col3\" >-0.68%</td>\n",
-              "      <td id=\"T_21c79_row9_col4\" class=\"data row9 col4\" >0.63%</td>\n",
-              "      <td id=\"T_21c79_row9_col5\" class=\"data row9 col5\" >3.05%</td>\n",
-              "      <td id=\"T_21c79_row9_col6\" class=\"data row9 col6\" >0.87%</td>\n",
-              "      <td id=\"T_21c79_row9_col7\" class=\"data row9 col7\" >0.17%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row9\" class=\"row_heading level0 row9\" >14.760000</th>\n",
+              "      <td id=\"T_d0fb6_row9_col0\" class=\"data row9 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row9_col1\" class=\"data row9 col1\" >0.47%</td>\n",
+              "      <td id=\"T_d0fb6_row9_col2\" class=\"data row9 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row9_col3\" class=\"data row9 col3\" >-0.68%</td>\n",
+              "      <td id=\"T_d0fb6_row9_col4\" class=\"data row9 col4\" >0.63%</td>\n",
+              "      <td id=\"T_d0fb6_row9_col5\" class=\"data row9 col5\" >3.05%</td>\n",
+              "      <td id=\"T_d0fb6_row9_col6\" class=\"data row9 col6\" >0.87%</td>\n",
+              "      <td id=\"T_d0fb6_row9_col7\" class=\"data row9 col7\" >0.17%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row10\" class=\"row_heading level0 row10\" >20.660000</th>\n",
-              "      <td id=\"T_21c79_row10_col0\" class=\"data row10 col0\" >0.71%</td>\n",
-              "      <td id=\"T_21c79_row10_col1\" class=\"data row10 col1\" >-0.01%</td>\n",
-              "      <td id=\"T_21c79_row10_col2\" class=\"data row10 col2\" >0.93%</td>\n",
-              "      <td id=\"T_21c79_row10_col3\" class=\"data row10 col3\" >0.69%</td>\n",
-              "      <td id=\"T_21c79_row10_col4\" class=\"data row10 col4\" >1.55%</td>\n",
-              "      <td id=\"T_21c79_row10_col5\" class=\"data row10 col5\" >5.15%</td>\n",
-              "      <td id=\"T_21c79_row10_col6\" class=\"data row10 col6\" >3.54%</td>\n",
-              "      <td id=\"T_21c79_row10_col7\" class=\"data row10 col7\" >0.11%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row10\" class=\"row_heading level0 row10\" >20.660000</th>\n",
+              "      <td id=\"T_d0fb6_row10_col0\" class=\"data row10 col0\" >0.71%</td>\n",
+              "      <td id=\"T_d0fb6_row10_col1\" class=\"data row10 col1\" >-0.01%</td>\n",
+              "      <td id=\"T_d0fb6_row10_col2\" class=\"data row10 col2\" >0.93%</td>\n",
+              "      <td id=\"T_d0fb6_row10_col3\" class=\"data row10 col3\" >0.69%</td>\n",
+              "      <td id=\"T_d0fb6_row10_col4\" class=\"data row10 col4\" >1.55%</td>\n",
+              "      <td id=\"T_d0fb6_row10_col5\" class=\"data row10 col5\" >5.15%</td>\n",
+              "      <td id=\"T_d0fb6_row10_col6\" class=\"data row10 col6\" >3.54%</td>\n",
+              "      <td id=\"T_d0fb6_row10_col7\" class=\"data row10 col7\" >0.11%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row11\" class=\"row_heading level0 row11\" >28.930000</th>\n",
-              "      <td id=\"T_21c79_row11_col0\" class=\"data row11 col0\" >-0.86%</td>\n",
-              "      <td id=\"T_21c79_row11_col1\" class=\"data row11 col1\" >-0.79%</td>\n",
-              "      <td id=\"T_21c79_row11_col2\" class=\"data row11 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row11_col3\" class=\"data row11 col3\" >-0.08%</td>\n",
-              "      <td id=\"T_21c79_row11_col4\" class=\"data row11 col4\" >4.42%</td>\n",
-              "      <td id=\"T_21c79_row11_col5\" class=\"data row11 col5\" >3.37%</td>\n",
-              "      <td id=\"T_21c79_row11_col6\" class=\"data row11 col6\" >2.87%</td>\n",
-              "      <td id=\"T_21c79_row11_col7\" class=\"data row11 col7\" >2.19%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row11\" class=\"row_heading level0 row11\" >28.930000</th>\n",
+              "      <td id=\"T_d0fb6_row11_col0\" class=\"data row11 col0\" >-0.86%</td>\n",
+              "      <td id=\"T_d0fb6_row11_col1\" class=\"data row11 col1\" >-0.79%</td>\n",
+              "      <td id=\"T_d0fb6_row11_col2\" class=\"data row11 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row11_col3\" class=\"data row11 col3\" >-0.08%</td>\n",
+              "      <td id=\"T_d0fb6_row11_col4\" class=\"data row11 col4\" >4.42%</td>\n",
+              "      <td id=\"T_d0fb6_row11_col5\" class=\"data row11 col5\" >3.37%</td>\n",
+              "      <td id=\"T_d0fb6_row11_col6\" class=\"data row11 col6\" >2.87%</td>\n",
+              "      <td id=\"T_d0fb6_row11_col7\" class=\"data row11 col7\" >2.19%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row12\" class=\"row_heading level0 row12\" >40.500000</th>\n",
-              "      <td id=\"T_21c79_row12_col0\" class=\"data row12 col0\" >-2.14%</td>\n",
-              "      <td id=\"T_21c79_row12_col1\" class=\"data row12 col1\" >-1.22%</td>\n",
-              "      <td id=\"T_21c79_row12_col2\" class=\"data row12 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row12_col3\" class=\"data row12 col3\" >2.18%</td>\n",
-              "      <td id=\"T_21c79_row12_col4\" class=\"data row12 col4\" >1.81%</td>\n",
-              "      <td id=\"T_21c79_row12_col5\" class=\"data row12 col5\" >0.72%</td>\n",
-              "      <td id=\"T_21c79_row12_col6\" class=\"data row12 col6\" >1.27%</td>\n",
-              "      <td id=\"T_21c79_row12_col7\" class=\"data row12 col7\" >0.37%</td>\n",
+              "      <th id=\"T_d0fb6_level0_row12\" class=\"row_heading level0 row12\" >40.500000</th>\n",
+              "      <td id=\"T_d0fb6_row12_col0\" class=\"data row12 col0\" >-2.14%</td>\n",
+              "      <td id=\"T_d0fb6_row12_col1\" class=\"data row12 col1\" >-1.22%</td>\n",
+              "      <td id=\"T_d0fb6_row12_col2\" class=\"data row12 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row12_col3\" class=\"data row12 col3\" >2.18%</td>\n",
+              "      <td id=\"T_d0fb6_row12_col4\" class=\"data row12 col4\" >1.81%</td>\n",
+              "      <td id=\"T_d0fb6_row12_col5\" class=\"data row12 col5\" >0.72%</td>\n",
+              "      <td id=\"T_d0fb6_row12_col6\" class=\"data row12 col6\" >1.27%</td>\n",
+              "      <td id=\"T_d0fb6_row12_col7\" class=\"data row12 col7\" >0.37%</td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row13\" class=\"row_heading level0 row13\" >56.690000</th>\n",
-              "      <td id=\"T_21c79_row13_col0\" class=\"data row13 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row13_col1\" class=\"data row13 col1\" >-0.99%</td>\n",
-              "      <td id=\"T_21c79_row13_col2\" class=\"data row13 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row13_col3\" class=\"data row13 col3\" >0.79%</td>\n",
-              "      <td id=\"T_21c79_row13_col4\" class=\"data row13 col4\" >3.63%</td>\n",
-              "      <td id=\"T_21c79_row13_col5\" class=\"data row13 col5\" >2.26%</td>\n",
-              "      <td id=\"T_21c79_row13_col6\" class=\"data row13 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row13_col7\" class=\"data row13 col7\" ></td>\n",
+              "      <th id=\"T_d0fb6_level0_row13\" class=\"row_heading level0 row13\" >56.690000</th>\n",
+              "      <td id=\"T_d0fb6_row13_col0\" class=\"data row13 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row13_col1\" class=\"data row13 col1\" >-0.99%</td>\n",
+              "      <td id=\"T_d0fb6_row13_col2\" class=\"data row13 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row13_col3\" class=\"data row13 col3\" >0.79%</td>\n",
+              "      <td id=\"T_d0fb6_row13_col4\" class=\"data row13 col4\" >3.63%</td>\n",
+              "      <td id=\"T_d0fb6_row13_col5\" class=\"data row13 col5\" >2.26%</td>\n",
+              "      <td id=\"T_d0fb6_row13_col6\" class=\"data row13 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row13_col7\" class=\"data row13 col7\" ></td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row14\" class=\"row_heading level0 row14\" >79.370000</th>\n",
-              "      <td id=\"T_21c79_row14_col0\" class=\"data row14 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row14_col1\" class=\"data row14 col1\" >0.06%</td>\n",
-              "      <td id=\"T_21c79_row14_col2\" class=\"data row14 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row14_col3\" class=\"data row14 col3\" >-1.74%</td>\n",
-              "      <td id=\"T_21c79_row14_col4\" class=\"data row14 col4\" >1.02%</td>\n",
-              "      <td id=\"T_21c79_row14_col5\" class=\"data row14 col5\" >-2.67%</td>\n",
-              "      <td id=\"T_21c79_row14_col6\" class=\"data row14 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row14_col7\" class=\"data row14 col7\" ></td>\n",
+              "      <th id=\"T_d0fb6_level0_row14\" class=\"row_heading level0 row14\" >79.370000</th>\n",
+              "      <td id=\"T_d0fb6_row14_col0\" class=\"data row14 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row14_col1\" class=\"data row14 col1\" >0.06%</td>\n",
+              "      <td id=\"T_d0fb6_row14_col2\" class=\"data row14 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row14_col3\" class=\"data row14 col3\" >-1.74%</td>\n",
+              "      <td id=\"T_d0fb6_row14_col4\" class=\"data row14 col4\" >1.02%</td>\n",
+              "      <td id=\"T_d0fb6_row14_col5\" class=\"data row14 col5\" >-2.67%</td>\n",
+              "      <td id=\"T_d0fb6_row14_col6\" class=\"data row14 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row14_col7\" class=\"data row14 col7\" ></td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row15\" class=\"row_heading level0 row15\" >111.120000</th>\n",
-              "      <td id=\"T_21c79_row15_col0\" class=\"data row15 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row15_col1\" class=\"data row15 col1\" >-1.38%</td>\n",
-              "      <td id=\"T_21c79_row15_col2\" class=\"data row15 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row15_col3\" class=\"data row15 col3\" >-2.72%</td>\n",
-              "      <td id=\"T_21c79_row15_col4\" class=\"data row15 col4\" >-2.53%</td>\n",
-              "      <td id=\"T_21c79_row15_col5\" class=\"data row15 col5\" ></td>\n",
-              "      <td id=\"T_21c79_row15_col6\" class=\"data row15 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row15_col7\" class=\"data row15 col7\" ></td>\n",
+              "      <th id=\"T_d0fb6_level0_row15\" class=\"row_heading level0 row15\" >111.120000</th>\n",
+              "      <td id=\"T_d0fb6_row15_col0\" class=\"data row15 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row15_col1\" class=\"data row15 col1\" >-1.38%</td>\n",
+              "      <td id=\"T_d0fb6_row15_col2\" class=\"data row15 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row15_col3\" class=\"data row15 col3\" >-2.72%</td>\n",
+              "      <td id=\"T_d0fb6_row15_col4\" class=\"data row15 col4\" >-2.53%</td>\n",
+              "      <td id=\"T_d0fb6_row15_col5\" class=\"data row15 col5\" ></td>\n",
+              "      <td id=\"T_d0fb6_row15_col6\" class=\"data row15 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row15_col7\" class=\"data row15 col7\" ></td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row16\" class=\"row_heading level0 row16\" >155.570000</th>\n",
-              "      <td id=\"T_21c79_row16_col0\" class=\"data row16 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row16_col1\" class=\"data row16 col1\" >-3.93%</td>\n",
-              "      <td id=\"T_21c79_row16_col2\" class=\"data row16 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row16_col3\" class=\"data row16 col3\" >-3.21%</td>\n",
-              "      <td id=\"T_21c79_row16_col4\" class=\"data row16 col4\" ></td>\n",
-              "      <td id=\"T_21c79_row16_col5\" class=\"data row16 col5\" ></td>\n",
-              "      <td id=\"T_21c79_row16_col6\" class=\"data row16 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row16_col7\" class=\"data row16 col7\" ></td>\n",
+              "      <th id=\"T_d0fb6_level0_row16\" class=\"row_heading level0 row16\" >155.570000</th>\n",
+              "      <td id=\"T_d0fb6_row16_col0\" class=\"data row16 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row16_col1\" class=\"data row16 col1\" >-3.93%</td>\n",
+              "      <td id=\"T_d0fb6_row16_col2\" class=\"data row16 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row16_col3\" class=\"data row16 col3\" >-3.21%</td>\n",
+              "      <td id=\"T_d0fb6_row16_col4\" class=\"data row16 col4\" ></td>\n",
+              "      <td id=\"T_d0fb6_row16_col5\" class=\"data row16 col5\" ></td>\n",
+              "      <td id=\"T_d0fb6_row16_col6\" class=\"data row16 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row16_col7\" class=\"data row16 col7\" ></td>\n",
               "    </tr>\n",
               "    <tr>\n",
-              "      <th id=\"T_21c79_level0_row17\" class=\"row_heading level0 row17\" >217.800000</th>\n",
-              "      <td id=\"T_21c79_row17_col0\" class=\"data row17 col0\" ></td>\n",
-              "      <td id=\"T_21c79_row17_col1\" class=\"data row17 col1\" >-1.00%</td>\n",
-              "      <td id=\"T_21c79_row17_col2\" class=\"data row17 col2\" ></td>\n",
-              "      <td id=\"T_21c79_row17_col3\" class=\"data row17 col3\" ></td>\n",
-              "      <td id=\"T_21c79_row17_col4\" class=\"data row17 col4\" ></td>\n",
-              "      <td id=\"T_21c79_row17_col5\" class=\"data row17 col5\" ></td>\n",
-              "      <td id=\"T_21c79_row17_col6\" class=\"data row17 col6\" ></td>\n",
-              "      <td id=\"T_21c79_row17_col7\" class=\"data row17 col7\" ></td>\n",
+              "      <th id=\"T_d0fb6_level0_row17\" class=\"row_heading level0 row17\" >217.800000</th>\n",
+              "      <td id=\"T_d0fb6_row17_col0\" class=\"data row17 col0\" ></td>\n",
+              "      <td id=\"T_d0fb6_row17_col1\" class=\"data row17 col1\" >-1.00%</td>\n",
+              "      <td id=\"T_d0fb6_row17_col2\" class=\"data row17 col2\" ></td>\n",
+              "      <td id=\"T_d0fb6_row17_col3\" class=\"data row17 col3\" ></td>\n",
+              "      <td id=\"T_d0fb6_row17_col4\" class=\"data row17 col4\" ></td>\n",
+              "      <td id=\"T_d0fb6_row17_col5\" class=\"data row17 col5\" ></td>\n",
+              "      <td id=\"T_d0fb6_row17_col6\" class=\"data row17 col6\" ></td>\n",
+              "      <td id=\"T_d0fb6_row17_col7\" class=\"data row17 col7\" ></td>\n",
               "    </tr>\n",
               "  </tbody>\n",
               "</table>\n"
             ],
             "text/plain": [
-              "<pandas.io.formats.style.Styler at 0x2ca512220>"
+              "<pandas.io.formats.style.Styler at 0x2d481de80>"
             ]
           },
           "execution_count": 12,
diff --git a/package/fsrs4anki_optimizer/fsrs4anki_optimizer.py b/package/fsrs4anki_optimizer/fsrs4anki_optimizer.py
index 5ce0c5e..800ea05 100644
--- a/package/fsrs4anki_optimizer/fsrs4anki_optimizer.py
+++ b/package/fsrs4anki_optimizer/fsrs4anki_optimizer.py
@@ -512,6 +512,11 @@ def pretrain(self, verbose=True):
 
         if len(rating_stability) < 2:
             raise Exception("Not enough data for pretraining!")
+        elif len(rating_stability) == 4:
+            for rating, stability in rating_stability.items():
+                self.init_w[rating-1] = round(stability, 2)
+            tqdm.write(f"Pretrain finished!")
+            return
 
         def S0_rating_curve(rating, a, b, c):
             return np.exp(a + b * rating) + c
@@ -576,11 +581,13 @@ def train(self, lr: float = 4e-2, n_epoch: int = 5, n_splits: int = 5, batch_siz
                 test_set = self.dataset.iloc[test_index].copy()
                 trainer = Trainer(train_set, test_set, self.init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)
                 w.append(trainer.train(verbose=verbose))
-                plots.append(trainer.plot())
+                if verbose:
+                    plots.append(trainer.plot())
         else:
             trainer = Trainer(self.dataset, self.dataset, self.init_w, n_epoch=n_epoch, lr=lr, batch_size=batch_size)
             w.append(trainer.train(verbose=verbose))
-            plots.append(trainer.plot())
+            if verbose:
+                plots.append(trainer.plot())
 
         w = np.array(w)
         avg_w = np.round(np.mean(w, axis=0), 4)
diff --git a/package/pyproject.toml b/package/pyproject.toml
index ad7e30f..4741f28 100644
--- a/package/pyproject.toml
+++ b/package/pyproject.toml
@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "fsrs4anki_optimizer"
-version = "4.0.2"
+version = "4.0.3"
 readme = "README.md"
 dependencies = [
     "matplotlib>=3.7.0",