diff --git a/.github/workflows/lint-and-test.yaml b/.github/workflows/lint-and-test.yaml
index 8855a15..ed31b1f 100644
--- a/.github/workflows/lint-and-test.yaml
+++ b/.github/workflows/lint-and-test.yaml
@@ -4,13 +4,20 @@ on:
   push:
     branches:
       - main
+    paths-ignore:
+      - 'examples/smarteole_example.ipynb'
   pull_request:
     branches:
       - main
+    paths-ignore:
+      - 'examples/smarteole_example.ipynb'
+  workflow_dispatch:
+
 
 permissions:
   contents: read
 
+
 jobs:
   lint-and-test:
     runs-on: ${{ matrix.os }}
@@ -37,14 +44,14 @@ jobs:
       run: |
         python -m venv .venv
         source .venv/bin/activate
-        pip install .[dev]
+        pip install .[all]
     - name: 'update dependencies'
       if: steps.cache-venv.outputs.cache-hit == 'true'
       run: |
         source .venv/bin/activate
-        pip install -U .[dev]
-    - name: "lint check & test"
+        pip install -U .[all]
+    - name: 'lint check & test'
       run: |
         source .venv/bin/activate
         poe lint-check
-        poe test
\ No newline at end of file
+        poe test
diff --git a/.github/workflows/smarteole_example.yaml b/.github/workflows/smarteole_example.yaml
new file mode 100644
index 0000000..e1b1113
--- /dev/null
+++ b/.github/workflows/smarteole_example.yaml
@@ -0,0 +1,71 @@
+name: Execute Smarteole Example notebook
+
+on:
+  push:
+    branches:
+      - main
+    paths-ignore:
+      - 'examples/smarteole_example.ipynb'
+  pull_request:
+  workflow_dispatch:
+
+
+permissions:
+  contents: write
+
+env:
+ BRANCH_NAME: ${{ github.head_ref || github.ref_name }}
+
+jobs:
+  lint-and-test:
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.x"]
+        os: [ubuntu-latest]
+    steps:
+    - uses: actions/checkout@v4
+      with:
+        ref: ${{ env.BRANCH_NAME }}
+    - name: "set up Python ${{ matrix.python-version }}"
+      uses: actions/setup-python@v5
+      with:
+        python-version: ${{ matrix.python-version }}
+    - uses: actions/cache@v4
+      id: cache-venv
+      with:
+        path: ./.venv/
+        key: ${{ matrix.python-version }}-venv-${{ hashFiles('**/pyproject.toml') }}
+        restore-keys: |
+          ${{ matrix.python-version }}-venv
+    - name: 'add examples to pyproject.toml as a module so notebook imports work in CI'
+      run: |
+        sed -i 's!\["wind_up\*"\]!\["wind_up\*", "examples"\]!' pyproject.toml
+    - name: 'create environment and install dependencies'
+      if: steps.cache-venv.outputs.cache-hit != 'true'
+      run: |
+        python -m venv .venv
+        source .venv/bin/activate
+        pip install .[all]
+    - name: 'update dependencies'
+      if: steps.cache-venv.outputs.cache-hit == 'true'
+      run: |
+        source .venv/bin/activate
+        pip install -U .[all]
+    - name: 'lint check & test'
+      run: |
+        source .venv/bin/activate
+        poe lint-check
+        poe test
+    - name: 'execute smarteole example notebook and push changes'
+      run: |
+        source .venv/bin/activate
+        poe smarteole-nb
+        git add -A
+        git config --local user.email "action@github.com"
+        git config --local user.name "GitHub Action"
+        if git status | grep -q modified; then
+          git commit -m "Update smarteole example notebook"
+          git push
+        fi
diff --git a/examples/smarteole_example.ipynb b/examples/smarteole_example.ipynb
index 775d23c..b13cb35 100644
--- a/examples/smarteole_example.ipynb
+++ b/examples/smarteole_example.ipynb
@@ -20,6 +20,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:13:33.848463Z",
      "start_time": "2024-09-06T09:13:32.278143Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:06.693276Z",
+     "iopub.status.busy": "2024-11-18T11:36:06.693276Z",
+     "iopub.status.idle": "2024-11-18T11:36:08.113357Z",
+     "shell.execute_reply": "2024-11-18T11:36:08.113357Z"
     }
    },
    "outputs": [],
@@ -55,6 +61,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:13:33.853841Z",
      "start_time": "2024-09-06T09:13:33.849090Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:08.114937Z",
+     "iopub.status.busy": "2024-11-18T11:36:08.114937Z",
+     "iopub.status.idle": "2024-11-18T11:36:08.118114Z",
+     "shell.execute_reply": "2024-11-18T11:36:08.118114Z"
     }
    },
    "outputs": [],
@@ -96,6 +108,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:14:02.582769Z",
      "start_time": "2024-09-06T09:13:33.854832Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:08.119160Z",
+     "iopub.status.busy": "2024-11-18T11:36:08.119160Z",
+     "iopub.status.idle": "2024-11-18T11:36:21.886025Z",
+     "shell.execute_reply": "2024-11-18T11:36:21.886025Z"
     }
    },
    "outputs": [
@@ -111,6 +129,455 @@
      "metadata": {},
      "output_type": "display_data"
     },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "1 out of 144 MB downloaded\r",
+      "2 out of 144 MB downloaded\r",
+      "3 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "4 out of 144 MB downloaded\r",
+      "5 out of 144 MB downloaded\r",
+      "6 out of 144 MB downloaded\r",
+      "7 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "8 out of 144 MB downloaded\r",
+      "9 out of 144 MB downloaded\r",
+      "10 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "11 out of 144 MB downloaded\r",
+      "12 out of 144 MB downloaded\r",
+      "13 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "14 out of 144 MB downloaded\r",
+      "15 out of 144 MB downloaded\r",
+      "16 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "17 out of 144 MB downloaded\r",
+      "18 out of 144 MB downloaded\r",
+      "19 out of 144 MB downloaded\r",
+      "20 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "21 out of 144 MB downloaded\r",
+      "22 out of 144 MB downloaded\r",
+      "23 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "24 out of 144 MB downloaded\r",
+      "25 out of 144 MB downloaded\r",
+      "26 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "27 out of 144 MB downloaded\r",
+      "28 out of 144 MB downloaded\r",
+      "29 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "30 out of 144 MB downloaded\r",
+      "31 out of 144 MB downloaded\r",
+      "32 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "33 out of 144 MB downloaded\r",
+      "34 out of 144 MB downloaded\r",
+      "35 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "36 out of 144 MB downloaded\r",
+      "37 out of 144 MB downloaded\r",
+      "38 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "39 out of 144 MB downloaded\r",
+      "40 out of 144 MB downloaded\r",
+      "41 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "42 out of 144 MB downloaded\r",
+      "43 out of 144 MB downloaded\r",
+      "44 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "45 out of 144 MB downloaded\r",
+      "46 out of 144 MB downloaded\r",
+      "47 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "48 out of 144 MB downloaded\r",
+      "49 out of 144 MB downloaded\r",
+      "50 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "51 out of 144 MB downloaded\r",
+      "52 out of 144 MB downloaded\r",
+      "53 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "54 out of 144 MB downloaded\r",
+      "55 out of 144 MB downloaded\r",
+      "56 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "57 out of 144 MB downloaded\r",
+      "58 out of 144 MB downloaded\r",
+      "59 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "60 out of 144 MB downloaded\r",
+      "61 out of 144 MB downloaded\r",
+      "62 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "63 out of 144 MB downloaded\r",
+      "64 out of 144 MB downloaded\r",
+      "65 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "66 out of 144 MB downloaded\r",
+      "67 out of 144 MB downloaded\r",
+      "68 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "69 out of 144 MB downloaded\r",
+      "70 out of 144 MB downloaded\r",
+      "71 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "72 out of 144 MB downloaded\r",
+      "73 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "74 out of 144 MB downloaded\r",
+      "75 out of 144 MB downloaded\r",
+      "76 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "77 out of 144 MB downloaded\r",
+      "78 out of 144 MB downloaded\r",
+      "79 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "80 out of 144 MB downloaded\r",
+      "81 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "82 out of 144 MB downloaded\r",
+      "83 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "84 out of 144 MB downloaded\r",
+      "85 out of 144 MB downloaded\r",
+      "86 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "87 out of 144 MB downloaded\r",
+      "88 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "89 out of 144 MB downloaded\r",
+      "90 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "91 out of 144 MB downloaded\r",
+      "92 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "93 out of 144 MB downloaded\r",
+      "94 out of 144 MB downloaded\r",
+      "95 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "96 out of 144 MB downloaded\r",
+      "97 out of 144 MB downloaded\r",
+      "98 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "99 out of 144 MB downloaded\r",
+      "100 out of 144 MB downloaded\r",
+      "101 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "102 out of 144 MB downloaded\r",
+      "103 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "104 out of 144 MB downloaded\r",
+      "105 out of 144 MB downloaded\r",
+      "106 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "107 out of 144 MB downloaded\r",
+      "108 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "109 out of 144 MB downloaded\r",
+      "110 out of 144 MB downloaded\r",
+      "111 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "112 out of 144 MB downloaded\r",
+      "113 out of 144 MB downloaded\r",
+      "114 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "115 out of 144 MB downloaded\r",
+      "116 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "117 out of 144 MB downloaded\r",
+      "118 out of 144 MB downloaded\r",
+      "119 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "120 out of 144 MB downloaded\r",
+      "121 out of 144 MB downloaded\r",
+      "122 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "123 out of 144 MB downloaded\r",
+      "124 out of 144 MB downloaded\r",
+      "125 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "126 out of 144 MB downloaded\r",
+      "127 out of 144 MB downloaded\r",
+      "128 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "129 out of 144 MB downloaded\r",
+      "130 out of 144 MB downloaded\r",
+      "131 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "132 out of 144 MB downloaded\r",
+      "133 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "134 out of 144 MB downloaded\r",
+      "135 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "136 out of 144 MB downloaded\r",
+      "137 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "138 out of 144 MB downloaded\r",
+      "139 out of 144 MB downloaded\r",
+      "140 out of 144 MB downloaded\r"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "141 out of 144 MB downloaded\r",
+      "142 out of 144 MB downloaded\r",
+      "143 out of 144 MB downloaded\r"
+     ]
+    },
     {
      "name": "stdout",
      "output_type": "stream",
@@ -141,6 +608,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:14:32.421318Z",
      "start_time": "2024-09-06T09:14:02.583774Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:21.888031Z",
+     "iopub.status.busy": "2024-11-18T11:36:21.888031Z",
+     "iopub.status.idle": "2024-11-18T11:36:21.948172Z",
+     "shell.execute_reply": "2024-11-18T11:36:21.948172Z"
     }
    },
    "outputs": [
@@ -343,6 +816,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:14:32.476398Z",
      "start_time": "2024-09-06T09:14:32.425931Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:21.950267Z",
+     "iopub.status.busy": "2024-11-18T11:36:21.950267Z",
+     "iopub.status.idle": "2024-11-18T11:36:21.957979Z",
+     "shell.execute_reply": "2024-11-18T11:36:21.957531Z"
     }
    },
    "outputs": [
@@ -463,6 +942,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:14:33.454729Z",
      "start_time": "2024-09-06T09:14:32.480395Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:21.959022Z",
+     "iopub.status.busy": "2024-11-18T11:36:21.959022Z",
+     "iopub.status.idle": "2024-11-18T11:36:21.966294Z",
+     "shell.execute_reply": "2024-11-18T11:36:21.966294Z"
     }
    },
    "outputs": [
@@ -572,6 +1057,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:14:33.485569Z",
      "start_time": "2024-09-06T09:14:33.455967Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:21.968346Z",
+     "iopub.status.busy": "2024-11-18T11:36:21.967335Z",
+     "iopub.status.idle": "2024-11-18T11:36:21.985480Z",
+     "shell.execute_reply": "2024-11-18T11:36:21.985480Z"
     }
    },
    "outputs": [
@@ -682,6 +1173,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:14:33.515513Z",
      "start_time": "2024-09-06T09:14:33.486526Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:21.987485Z",
+     "iopub.status.busy": "2024-11-18T11:36:21.987485Z",
+     "iopub.status.idle": "2024-11-18T11:36:21.997316Z",
+     "shell.execute_reply": "2024-11-18T11:36:21.997316Z"
     }
    },
    "outputs": [
@@ -791,6 +1288,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:14:33.553187Z",
      "start_time": "2024-09-06T09:14:33.516556Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:21.998858Z",
+     "iopub.status.busy": "2024-11-18T11:36:21.998858Z",
+     "iopub.status.idle": "2024-11-18T11:36:22.009611Z",
+     "shell.execute_reply": "2024-11-18T11:36:22.009611Z"
     }
    },
    "outputs": [
@@ -1055,6 +1558,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:14:33.569760Z",
      "start_time": "2024-09-06T09:14:33.554184Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:22.011633Z",
+     "iopub.status.busy": "2024-11-18T11:36:22.010635Z",
+     "iopub.status.idle": "2024-11-18T11:36:22.016701Z",
+     "shell.execute_reply": "2024-11-18T11:36:22.016701Z"
     }
    },
    "outputs": [
@@ -1133,6 +1642,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:15:06.937771Z",
      "start_time": "2024-09-06T09:14:33.570875Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:22.018706Z",
+     "iopub.status.busy": "2024-11-18T11:36:22.018706Z",
+     "iopub.status.idle": "2024-11-18T11:36:34.561843Z",
+     "shell.execute_reply": "2024-11-18T11:36:34.561843Z"
     }
    },
    "outputs": [
@@ -1275,7 +1790,7 @@
     {
      "data": {
       "text/markdown": [
-       "filter_stuck_data set 0 rows [0.0%] to NA"
+       "filter_stuck_data set 7443 rows [7.6%] to NA"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -1940,6 +2455,12 @@
     "ExecuteTime": {
      "end_time": "2024-09-06T09:17:25.661612Z",
      "start_time": "2024-09-06T09:15:06.938774Z"
+    },
+    "execution": {
+     "iopub.execute_input": "2024-11-18T11:36:34.563813Z",
+     "iopub.status.busy": "2024-11-18T11:36:34.563813Z",
+     "iopub.status.idle": "2024-11-18T11:38:03.146215Z",
+     "shell.execute_reply": "2024-11-18T11:38:03.146215Z"
     }
    },
    "outputs": [
@@ -2573,7 +3094,7 @@
     },
     {
      "data": {
-      "image/png": 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WLarff//dPtalSxcdOXJEGzZssM9/69atDocyb/SzXaZMGfn4+GTJ9dNPP+mhhx5SSEiIgoODFR4erscff1zS/18/mdmuze7l5aWYmBiHsRvZNrAur+tPAhQePj4+ql27tmrXrq3bb79dPXv21Keffprtv9br1q2r2NhYDRw4UAkJCTnugch09YnvXbt21dy5c+Xp6elwXo0klS5dWpIcCoR0Za9aWFjYdf8iKmzLc7XDhw/rhx9+UO/evbM9dy83V+99kK6c72Oz2bRkyRJ5enpmmb5IkSI3NP+b0blzZ61fv17PP/+8qlevriJFiigjI0OtWrVyKF21atWSn5+fvv/+e0VFRalEiRK6/fbb1bBhQ02ZMkUpKSn64Ycf7OcCZsrcK5fT7VnWrFljP58qU3brQlKu9x3Mq8xl+uijjxQREZHl+av3+Fyra9eumjp1qoKCgtSlS5ccbxOTkZGhu+66S+PGjcv2+cjISElXClGzZs1UqVIljRs3TpGRkfLx8dE333yj8ePHZym9+bleMuX2D6FM999/vwICAvTJJ5+ofv36+uSTT+Th4aFOnTrZp7nRz/a1PxuSdPbsWTVu3FjBwcEaMWKEYmNj5efnp23btunFF1+8qfsv5nXbwNoodnBbmVeo/fnnnzlO8+ijj+q1115T5cqVVb169Vzn5+vrq4cfflgffvihEhMT9emnn+q+++7L8hdkzZo1JUl//PGHw3hqaqpOnjyp8PDwm1ga1y3P1ebNmydjzA0fhs1ObGysjDEqV65crod+88uZM2e0cuVKDR8+XEOHDrWPZ+7VupqPj4/9SsOoqCj7IcGGDRsqJSVFc+bMUWJiosOFE5l7Q7t06aKHH344yzz79++vOXPmZCl21xMdHa2MjAwlJCSoQoUK9vEDBw5c97WxsbGSrlxdndNNrXPStWtXDR06VH/++ac++uijXN9j586datasWa5F6csvv1RKSoq++OILh71xzj4cGBsbq2XLlun06dM57rXLXKf79+9X5cqV7eOJiYk6e/asoqOj7WOBgYFq166dPv30U40bN04LFixQw4YN7f+gy3zPW/1sr169WqdOndLnn3/u8LlKSEjIkl26sv2v/ixdvnxZhw4dUtWqVR1y5WXbwNo4FItCb9WqVdn+qz3zvJmKFSvm+NqnnnpKr776qt5+++08vddjjz2mtLQ09enTRydOnMi24DRp0sR+DtWlS5fs47Nnz1Z6erqaN2/uVstztblz5yoqKsrhPLKb1aFDB3l6emr48OFZltcY43DLkfyQuSfl2veeMGFCttM3bNhQGzdu1KpVq+zFrnjx4qpcubLGjBljnybTwoULdfHiRcXHx+vhhx/O8qddu3b67LPPbvg2E5m3r5kyZYrD+LXfSpLTa4ODg/XGG29ke6ub3G6gHRsbqwkTJmjUqFGqU6dOjtN17txZf/zxh2bMmJHlub/++st+nmJ26//cuXOaNWvWdZfjRnTs2FHGmCxXFl/93m3atJGUddtn7tm69urfLl266OjRo/rPf/6jnTt3Zrmi1Bmf7ezWT2pqapbtXqtWLYWFhWnGjBkO33wzZ86cLEcH8rptYG3ssUOh169fPyUnJ+uhhx5SpUqVlJqaqvXr12vBggWKiYnJ9qTkTNHR0Xm+J5okNW7cWGXLltXixYtzvN2Hr6+v3nzzTXXv3l2NGjVSt27ddPjwYU2cOFENGza87q06CtvyZNqzZ4927dqll156ySn/2o+NjdVrr72ml19+WYcOHVL79u0VFBSkhIQELVy4UL1799Zzzz13y++Tk+DgYDVq1Ehjx45VWlqaypQpo+XLl2fZI5KpYcOGev3113XkyBGHAteoUSO99957iomJUdmyZe3jc+bMUVhYmOrXr5/t/B544AHNmDFDX3/99Q3dNqZmzZrq2LGjJkyYoFOnTumee+7RmjVr9Ouvv0rK/XBicHCwpk6dqm7duqlGjRp65JFHFB4ersOHD+vrr7/Wvffeq3fffTfH1w8YMOC6+bp166ZPPvlEzzzzjFatWqV7771X6enp+uWXX/TJJ59o2bJlqlWrllq0aCEfHx/df//96tOnjy5cuKAZM2aoRIkSue6VvlFNmzZVt27d9M4772j//v32w+w//PCDmjZtqr59+6patWrq3r27pk+fbj8EumnTJn3wwQdq3759lr2qbdq0UVBQkJ577jl5enqqY8eODs8747Ndv359hYaGqnv37urfv79sNps++uijLEXRx8dHw4YNU79+/XTfffepc+fOOnTokGbPnq3Y2FiHz0Netw0sriAvwQVuxpIlS0yvXr1MpUqVTJEiRYyPj48pX7686devX7bf1NC2bdtc55fd7UGu9vzzzxtJ173dx7x580y1atWMr6+vKVmypOnbt69JSkpy2+XJvBXKrl27rrsMV7verUo+++wz06BBAxMYGGgCAwNNpUqVTHx8vMMtV271difGXLmtxB133OEw9r///c889NBDpmjRoiYkJMR06tTJHD16NMttQ4wxJikpyXh6epqgoCBz+fJl+/jHH39sJJlu3brZxxITE42Xl5fD2LWSk5NNQECAeeihh3Jdxuy+PeLixYsmPj7eFCtWzBQpUsS0b9/e7Nu3z0gyo0ePzvW1xhizatUq07JlSxMSEmL8/PxMbGys6dGjh9myZYt9mryuc2XzzROpqalmzJgx5o477jC+vr4mNDTU1KxZ0wwfPtycO3fOPt0XX3xhqlatavz8/ExMTIwZM2aMmTlzZpbMOX3OGzdu7HA7j5xcvnzZvPnmm6ZSpUrGx8fHhIeHm9atW5utW7fap0lLSzPDhw835cqVM97e3iYyMtK8/PLL9tuKXOuxxx4zkkxcXFyO75uXz3Z2n8tM69atM/fcc4/x9/c3pUuXtt/6SJJZtWqVw7TvvPOOiY6ONr6+vqZOnTpm3bp1pmbNmqZVq1YO0+V128C6bMY48cxUAEC+2LFjh+6++259/PHHTjkHEu4tIyND4eHh6tChQ7aHXvH3xTl2AFDI/PXXX1nGJkyYIA8PjyzffAHru3TpUpZDtB9++KFOnz6d5SvFAM6xA1DoXLhwwX4j6JyEh4fneIsMdzd27Fht3bpVTZs2lZeXl5YsWaIlS5aod+/e3LLib+jHH3/UoEGD1KlTJ4WFhWnbtm16//33deeddzrchgWQJA7FAih0hg0blu1VjldLSEjIcoNWq1ixYoWGDx+uvXv36sKFC4qKilK3bt30r3/9K9d70cGaDh06pP79+2vTpk3227q0adNGo0ePVokSJVwdD4UMxQ5AofPbb79d96ukGjRoID8/vwJKBADugWIHAABgEVw8AQAAYBGWP1kjIyNDR48eVVBQEF+xAgAA3I4xRufPn1fp0qVz/B7nTJYvdkePHuUqMgAA4PaOHDni8A042bF8sQsKCpJ0ZWUEBwe7OM2NSUtL0/Lly9WiRQt5e3u7Ok6O3CWnRNb84C45JbLmB3fJKZE1P7hLTsm9sl4rKSlJkZGR9k6TG8sXu8zDr8HBwW5Z7AICAhQcHFyoP4TuklMia35wl5wSWfODu+SUyJof3CWn5F5Zc5KXU8q4eAIAAMAiKHYAAAAWQbEDAACwCMufYwcAAApWenq60tLSXB3DQVpamry8vHTp0iWlp6e7Oo4Db29vp333NcUOAAA4hTFGx44d09mzZ10dJQtjjCIiInTkyJFCeV/bokWLKiIi4pazUewAAIBTZJa6EiVKKCAgoFAVqIyMDF24cEFFihS57k1+C5IxRsnJyTp+/LgkqVSpUrc0P4odAAC4Zenp6fZSFxYW5uo4WWRkZCg1NVV+fn6FqthJkr+/vyTp+PHjKlGixC0dli1cSwYAANxS5jl1AQEBLk7injLX262em0ixAwAATlOYDr+6E2etN4odAACARVDsAAAALIKLJwAAQL6KeenrAnuvQ6PbFth7FUbssQMAALgBqampro6QI4odAAD4W2vSpIn69u2rvn37KiQkRMWLF9eQIUNkjJEkxcTEaOTIkXriiScUHBys3r17S5LWrl2rhg0byt/fX5GRkerfv78uXrzoykWh2AEAAHzwwQfy8vLSpk2bNHHiRI0bN07/+c9/7M+/9dZbqlatmrZv364hQ4bo4MGDatWqlTp27Khdu3ZpwYIFWrt2rfr27evCpeAcOwAAAEVGRmr8+PGy2WyqWLGidu/erfHjx+vpp5+WJN1333365z//aZ/+qaee0mOPPaaBAwdKkipUqKB33nlHjRs31tSpU+Xn5+eKxaDYAcDfyqpRzp2f8ZBUSfphnGTLcO68m77s3PkBubjnnnsc7iVXr149vf3220pPT5ck1apVy2H6nTt3ateuXZozZ459zBijjIwMJSQkqHLlygUT/BoUOwAAgOsIDAx0eHzhwgX16dNH/fv3zzJtVFRUQcXKgmIHAAD+9jZu3Ojw+Mcff1SFChVy/N7WGjVqaO/evSpfvnxBxMszLp4AAAB/e4cPH9bgwYO1b98+zZs3T5MmTdKAAQNynP7FF1/U+vXr1bdvX+3YsUP79+/X4sWLuXgCAFBwJqz81anzs3l4KaZmJU1ZfUAm47JT5z2wqVNnB+TqiSee0F9//aU6derI09NTAwYMsN/WJDtVq1bVmjVr9K9//UsNGzaUMUaxsbHq0qVLAabOimIHAADylTt8G4S3t7cmTJigqVOnZnnu0KFD2b6mdu3aWr58eT4nuzEcigUAALAIih0AAIBFcCgWAAD8ra1evdrVEZyGPXYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgE97EDAAD5a9Wognuvpi8X3HvlwerVq9W0aVOdOXNGRYsWzff3Y48dAACARVDsAADA31qTJk3Ut29f9e3bVyEhISpevLiGDBkiY4wk6cyZM3riiScUGhqqgIAAtW7dWvv377e//vfff9f999+v0NBQBQYG6o477tA333yjQ4cOqWnTppKk0NBQ2Ww29ejRI1+XhWIHAAD+9j744AN5eXlp06ZNmjhxosaNG6f//Oc/kqQePXpoy5Yt+uKLL7RhwwYZY9SmTRulpaVJkuLj45WSkqLvv/9eu3fv1pgxY1SkSBFFRkbqs88+kyTt27dPf/75pyZOnJivy8E5dgAA4G8vMjJS48ePl81mU8WKFbV7926NHz9eTZo00RdffKF169apfv36kqQ5c+YoMjJSixYtUqdOnXT48GF17NhRd911lyTptttus8+3WLFikqQSJUpwjh0AAEBBuOeee2Sz2eyP69Wrp/3792vv3r3y8vJS3bp17c+FhYWpYsWK+vnnnyVJ/fv312uvvaZ7771Xr776qnbt2lXg+TNR7AAAAG7BU089pd9++03dunXT7t27VatWLU2aNMklWSh2AADgb2/jxo0Oj3/88UdVqFBBVapU0eXLlx2eP3XqlPbt26cqVarYxyIjI/XMM8/o888/1z//+U/NmDFDkuTj4yNJSk9PL4CloNgBAADo8OHDGjx4sPbt26d58+Zp0qRJGjBggCpUqKAHH3xQTz/9tNauXaudO3fq8ccfV5kyZfTggw9KkgYOHKhly5YpISFB27Zt06pVq1S5cmVJUnR0tGw2m7766iudOHFCFy5cyNfloNgBAIC/vSeeeEJ//fWX6tSpo/j4eA0YMEC9e/eWJM2aNUs1a9ZUu3btVK9ePRlj9M0338jb21vSlb1x8fHxqly5slq1aqXbb79dU6ZMkSSVKVNGw4cP10svvaSSJUuqb9+++bocXBULAADyVyH7NojseHt7a8KECZo6dWqW50JDQ/Xhhx/m+NrrnU83ZMgQDRky5JYz5gV77AAAACyCYgcAAGARHIoFAAB/a6tXr3Z1BKdhjx0AAIBFUOwAAAAsgmIHAACcJiMjw9UR3JKz1hvn2AEAgFvm4+MjDw8PHT16VOHh4fLx8XH47lVXy8jIUGpqqi5duiQPj8KzX8sYo9TUVJ04cUIeHh72b6q4WRQ7AABwyzw8PFSuXDn9+eefOnr0qKvjZGGM0V9//SV/f/9CVTgzBQQEKCoq6pZLJ8UOAAA4hY+Pj6KionT58uUC+27UvEpLS9P333+vRo0a2b8xorDw9PSUl5eXUwonxQ4AADiNzWaTt7d3oSxPly9flp+fX6HL5kyF5yAzAAAAbgnFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAswqXFLj09XUOGDFG5cuXk7++v2NhYjRw5UsYY+zTGGA0dOlSlSpWSv7+/4uLitH//fhemBgAAKJxcWuzGjBmjqVOn6t1339XPP/+sMWPGaOzYsZo0aZJ9mrFjx+qdd97RtGnTtHHjRgUGBqply5a6dOmSC5MDAAAUPl6ufPP169frwQcfVNu2bSVJMTExmjdvnjZt2iTpyt66CRMm6N///rcefPBBSdKHH36okiVLatGiRXrkkUdclh0AAKCwcekeu/r162vlypX69ddfJUk7d+7U2rVr1bp1a0lSQkKCjh07pri4OPtrQkJCVLduXW3YsMElmQEAAAorl+6xe+mll5SUlKRKlSrJ09NT6enpev311/XYY49Jko4dOyZJKlmypMPrSpYsaX/uWikpKUpJSbE/TkpKkiSlpaUpLS0tPxYj32TmLey53SWnRNb84C45JbJKks3Dub/2M+fn7PlKzl92tr/zuUtOyb2yXutGMtvM1VcqFLD58+fr+eef15tvvqk77rhDO3bs0MCBAzVu3Dh1795d69ev17333qujR4+qVKlS9td17txZNptNCxYsyDLPYcOGafjw4VnG586dq4CAgHxdHgAAAGdLTk5W165dde7cOQUHB+c6rUuLXWRkpF566SXFx8fbx1577TV9/PHH+uWXX/Tbb78pNjZW27dvV/Xq1e3TNG7cWNWrV9fEiROzzDO7PXaRkZE6efLkdVdGYZOWlqYVK1aoefPm8vb2dnWcHLlLToms+cFdckpklaQpI5912rykK3vqou9upd+3L5XJuOzUeT87ZIpT58f2dz53ySm5V9ZrJSUlqXjx4nkqdi49FJucnCwPD8fT/Dw9PZWRkSFJKleunCIiIrRy5Up7sUtKStLGjRv1j3/8I9t5+vr6ytfXN8u4t7e3223ITO6S3V1ySmTND+6SU/p7Z3V2+bp6vs6ed35to7/z9s8v7pJTcq+smW4kr0uL3f3336/XX39dUVFRuuOOO7R9+3aNGzdOvXr1kiTZbDYNHDhQr732mipUqKBy5cppyJAhKl26tNq3b+/K6AAAAIWOS4vdpEmTNGTIED377LM6fvy4SpcurT59+mjo0KH2aV544QVdvHhRvXv31tmzZ9WgQQMtXbpUfn5+LkwOAABQ+Li02AUFBWnChAmaMGFCjtPYbDaNGDFCI0aMKLhgAAAAbojvigUAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAswuXF7o8//tDjjz+usLAw+fv766677tKWLVvszxtjNHToUJUqVUr+/v6Ki4vT/v37XZgYAACgcHJpsTtz5ozuvfdeeXt7a8mSJdq7d6/efvtthYaG2qcZO3as3nnnHU2bNk0bN25UYGCgWrZsqUuXLrkwOQAAQOHj5co3HzNmjCIjIzVr1iz7WLly5ez/b4zRhAkT9O9//1sPPvigJOnDDz9UyZIltWjRIj3yyCMFnhkAAKCwcmmx++KLL9SyZUt16tRJa9asUZkyZfTss8/q6aefliQlJCTo2LFjiouLs78mJCREdevW1YYNG7ItdikpKUpJSbE/TkpKkiSlpaUpLS0tn5fIuTLzFvbc7pJTImt+cJecElklyebh3F/7mfNz9nwl5y8729/53CWn5F5Zr3UjmW3GGJOPWXLl5+cnSRo8eLA6deqkzZs3a8CAAZo2bZq6d++u9evX695779XRo0dVqlQp++s6d+4sm82mBQsWZJnnsGHDNHz48Czjc+fOVUBAQP4tDAAAQD5ITk5W165dde7cOQUHB+c6rUuLnY+Pj2rVqqX169fbx/r376/Nmzdrw4YNN1XssttjFxkZqZMnT153ZRQ2aWlpWrFihZo3by5vb29Xx8mRu+SUyJof3CWnRFZJmjLyWafNS7qypy767lb6fftSmYzLTp33s0OmOHV+bH/nc5eckntlvVZSUpKKFy+ep2Ln0kOxpUqVUpUqVRzGKleurM8++0ySFBERIUlKTEx0KHaJiYmqXr16tvP09fWVr69vlnFvb2+325CZ3CW7u+SUyJof3CWn9PfO6uzydfV8nT3v/NpGf+ftn1/cJafkXlkz3Uhel14Ve++992rfvn0OY7/++quio6MlXbmQIiIiQitXrrQ/n5SUpI0bN6pevXoFmhUAAKCwc+keu0GDBql+/fp644031LlzZ23atEnTp0/X9OnTJUk2m00DBw7Ua6+9pgoVKqhcuXIaMmSISpcurfbt27syOgAAQKHj0mJXu3ZtLVy4UC+//LJGjBihcuXKacKECXrsscfs07zwwgu6ePGievfurbNnz6pBgwZaunSp/cILAAAAXOHSYidJ7dq1U7t27XJ83mazacSIERoxYkQBpgIAAHA/Lv9KMQAAADgHxQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFiEU4pdenq6duzYoTNnzjhjdgAAALgJN1XsBg4cqPfff1/SlVLXuHFj1ahRQ5GRkVq9erUz8wEAACCPbqrY/fe//1W1atUkSV9++aUSEhL0yy+/aNCgQfrXv/7l1IAAAADIm5sqdidPnlRERIQk6ZtvvlGnTp10++23q1evXtq9e7dTAwIAACBvbqrYlSxZUnv37lV6erqWLl2q5s2bS5KSk5Pl6enp1IAAAADIG6+beVHPnj3VuXNnlSpVSjabTXFxcZKkjRs3qlKlSk4NCAAAgLy5qWI3bNgw3XXXXTp8+LA6deokX19fSZKnp6deeuklpwYEAABA3txwsUtLS1OrVq00bdo0dezY0eG57t27Oy0YAAAAbswNn2Pn7e2tXbt25UcWAAAA3IKbunji8ccft9/HDgAAAIXDTZ1jd/nyZc2cOVPffvutatasqcDAQIfnx40b55RwAAAAyLubKnZ79uxRjRo1JEm//vqrw3M2m+3WUwEAAOCG3VSxW7VqlbNzAAAA4Bbd1Dl2AAAAKHxuao9d06ZNcz3k+t133910IAAAANycmyp21atXd3iclpamHTt2aM+ePdzLDgAAwEVuqtiNHz8+2/Fhw4bpwoULtxQIAAAAN8ep59g9/vjjmjlzpjNnCQAAgDxyarHbsGGD/Pz8nDlLAAAA5NFNHYrt0KGDw2NjjP78809t2bJFQ4YMcUowAAAA3JibKnYhISEOjz08PFSxYkWNGDFCLVq0cEowAAAA3JibKnazZs1ydg4AAADcopsqdpm2bt2qn3/+WZJ0xx136O6773ZKKAAAANy4myp2x48f1yOPPKLVq1eraNGikqSzZ8+qadOmmj9/vsLDw52ZEQAAAHlwU1fF9uvXT+fPn9dPP/2k06dP6/Tp09qzZ4+SkpLUv39/Z2cEAABAHtzUHrulS5fq22+/VeXKle1jVapU0eTJk7l4AgAAwEVuao9dRkaGvL29s4x7e3srIyPjlkMBAADgxt1Usbvvvvs0YMAAHT161D72xx9/aNCgQWrWrJnTwgEAACDvbqrYvfvuu0pKSlJMTIxiY2MVGxurmJgYJSUladKkSc7OCAAAgDy4qXPsIiMjtW3bNq1cudJ+u5PKlSsrLi7OqeEAAACQdzd9H7vvvvtO3333nY4fP66MjAxt375dc+fOlSTNnDnTaQEBAACQNzdV7IYPH64RI0aoVq1aKlWqlGw2m7NzAQAA4AbdVLGbNm2aZs+erW7dujk7DwAAAG7STV08kZqaqvr16zs7CwAAAG7BTRW7p556yn4+HQAAAAqHPB+KHTx4sP3/MzIyNH36dH377beqWrVqlpsVjxs3znkJAQAAkCd5Lnbbt293eFy9enVJ0p49exzGuZACAADANfJc7FatWpWfOQAAAHCLbuocOwAAABQ+FDsAAACLoNgBAABYBMUOAADAIih2AAAAFkGxAwAAsAiKHQAAgEVQ7AAAACyCYgcAAGARFDsAAACLoNgBAABYRKEpdqNHj5bNZtPAgQPtY5cuXVJ8fLzCwsJUpEgRdezYUYmJia4LCQAAUIgVimK3efNmvffee6patarD+KBBg/Tll1/q008/1Zo1a3T06FF16NDBRSkBAAAKN5cXuwsXLuixxx7TjBkzFBoaah8/d+6c3n//fY0bN0733XefatasqVmzZmn9+vX68ccfXZgYAACgcHJ5sYuPj1fbtm0VFxfnML5161alpaU5jFeqVElRUVHasGFDQccEAAAo9Lxc+ebz58/Xtm3btHnz5izPHTt2TD4+PipatKjDeMmSJXXs2LEc55mSkqKUlBT746SkJElSWlqa0tLSnBO8gGTmLey53SWnRNb84C45JbJKks3Dub/2M+fn7PlKzl92tr/zuUtOyb2yXutGMtuMMSYfs+ToyJEjqlWrllasWGE/t65JkyaqXr26JkyYoLlz56pnz54OJU2S6tSpo6ZNm2rMmDHZznfYsGEaPnx4lvG5c+cqICDA+QsCAACQj5KTk9W1a1edO3dOwcHBuU7rsmK3aNEiPfTQQ/L09LSPpaeny2azycPDQ8uWLVNcXJzOnDnjsNcuOjpaAwcO1KBBg7Kdb3Z77CIjI3Xy5MnrrozCJi0tTStWrFDz5s3l7e3t6jg5cpecElnzg7vklMgqSVNGPuu0eUlX9tRF391Kv29fKpNx2anzfnbIFKfOj+3vfO6SU3KvrNdKSkpS8eLF81TsXHYotlmzZtq9e7fDWM+ePVWpUiW9+OKLioyMlLe3t1auXKmOHTtKkvbt26fDhw+rXr16Oc7X19dXvr6+Wca9vb3dbkNmcpfs7pJTImt+cJec0t87q7PL19Xzdfa882sb/Z23f35xl5ySe2XNdCN5XVbsgoKCdOeddzqMBQYGKiwszD7+5JNPavDgwSpWrJiCg4PVr18/1atXT/fcc48rIgMAABRqLr144nrGjx8vDw8PdezYUSkpKWrZsqWmTHHurnkAAACrKFTFbvXq1Q6P/fz8NHnyZE2ePNk1gQAAANyIy+9jBwAAAOeg2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAW4eXqAAAAZCfmpa+dOj9fT6OxdaQ7hy1TSrrNafM9NLqt0+YF3Cr22AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARVDsAAAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCC9XBwAAt7dqlPPnaTwkVZJ+GCfZMpw/fzcw0Ou/Tp2fzcNLUjs967lYxnbZiXNu68R5AbeGPXYAAAAW4dJiN2rUKNWuXVtBQUEqUaKE2rdvr3379jlMc+nSJcXHxyssLExFihRRx44dlZiY6KLEAAAAhZdLi92aNWsUHx+vH3/8UStWrFBaWppatGihixcv2qcZNGiQvvzyS3366adas2aNjh49qg4dOrgwNQAAQOHk0nPsli5d6vB49uzZKlGihLZu3apGjRrp3Llzev/99zV37lzdd999kqRZs2apcuXK+vHHH3XPPfe4IjYAOJiw8lenz9Pm4aWYmpU0ZfUBmQxnng8GwMoK1cUT586dkyQVK1ZMkrR161alpaUpLi7OPk2lSpUUFRWlDRs2ZFvsUlJSlJKSYn+clJQkSUpLS1NaWlp+xne6zLyFPbe75JTImh/cJaeUf1mvnJTvXJnzzI95O5O75JTyL2t+fPbd5efKXXJK7pX1WjeS2WaMMfmYJc8yMjL0wAMP6OzZs1q7dq0kae7cuerZs6dDUZOkOnXqqGnTphozZkyW+QwbNkzDhw/PMj537lwFBATkT3gAAIB8kpycrK5du+rcuXMKDg7OddpC80+s+Ph47dmzx17qbtbLL7+swYMH2x8nJSUpMjJSLVq0uO7KKGzS0tK0YsUKNW/eXN7e3q6OkyN3ySmRNT+4S04p/7JOGfms0+aVyebhpei7W+n37UsL9aFYd8kp5V/WZ4dMcdq8MrnLz5W75JTcK+u1Mo8+5kWhKHZ9+/bVV199pe+//15ly5a1j0dERCg1NVVnz55V0aJF7eOJiYmKiIjIdl6+vr7y9fXNMu7t7e12GzKTu2R3l5wSWfODu+SUnJ81PwuNybhc6AuT5D45Jednzc/Pvbv8XLlLTsm9sma6kbwuvSrWGKO+fftq4cKF+u6771SuXDmH52vWrClvb2+tXLnSPrZv3z4dPnxY9erVK+i4AAAAhZpL99jFx8dr7ty5Wrx4sYKCgnTs2DFJUkhIiPz9/RUSEqInn3xSgwcPVrFixRQcHKx+/fqpXr16XBELAABwDZcWu6lTp0qSmjRp4jA+a9Ys9ejRQ5I0fvx4eXh4qGPHjkpJSVHLli01ZYrzz2cAAABwdy4tdnm5INfPz0+TJ0/W5MmTCyARAACA++K7YgEAACyCYgcAAGARFDsAAACLoNgBAABYBMUOAADAIih2AAAAFkGxAwAAsAiKHQAAgEVQ7AAAACyCYgcAAGARFDsAAACLoNgBAABYBMUOAADAIih2AAAAFkGxAwAAsAiKHQAAgEVQ7AAAACyCYgcAAGARFDsAAACLoNgBAABYBMUOAADAIih2AAAAFkGxAwAAsAiKHQAAgEVQ7AAAACyCYgcAAGARFDsAAACLoNgBAABYBMUOAADAIih2AAAAFkGxAwAAsAiKHQAAgEVQ7AAAACyCYgcAAGARFDsAAACLoNgBAABYBMUOAADAIih2AAAAFkGxAwAAsAiKHQAAgEVQ7AAAACyCYgcAAGARFDsAAACLoNgBAABYBMUOAADAIih2AAAAFkGxAwAAsAiKHQAAgEVQ7AAAACyCYgcAAGARFDsAAACLoNgBAABYBMUOAADAIih2AAAAFkGxAwAAsAiKHQAAgEVQ7AAAACyCYgcAAGARFDsAAACLoNgBAABYBMUOAADAIih2AAAAFkGxAwAAsAiKHQAAgEVQ7AAAACyCYgcAAGARblHsJk+erJiYGPn5+alu3bratGmTqyMBAAAUOoW+2C1YsECDBw/Wq6++qm3btqlatWpq2bKljh8/7upoAAAAhUqhL3bjxo3T008/rZ49e6pKlSqaNm2aAgICNHPmTFdHAwAAKFQKdbFLTU3V1q1bFRcXZx/z8PBQXFycNmzY4MJkAAAAhY+XqwPk5uTJk0pPT1fJkiUdxkuWLKlffvkl29ekpKQoJSXF/vjcuXOSpNOnTystLS3/wuaDtLQ0JScn69SpU/L29nZ1nBy5S06JrPnBXXJK+Zc1JS3DafPKZPPIUHJyslLSMmQynD9/Z3GXnFL+ZT116pTT5pXJXX6u3CWn5F5Zr3X+/HlJkjHmutMW6mJ3M0aNGqXhw4dnGS9XrpwL0gDArXCXU07cJaeUH1lfGvuh0+cJZOf8+fMKCQnJdZpCXeyKFy8uT09PJSYmOownJiYqIiIi29e8/PLLGjx4sP1xRkaGTp8+rbCwMNlstnzN62xJSUmKjIzUkSNHFBwc7Oo4OXKXnBJZ84O75JTImh/cJadE1vzgLjkl98p6LWOMzp8/r9KlS1932kJd7Hx8fFSzZk2tXLlS7du3l3SlqK1cuVJ9+/bN9jW+vr7y9fV1GCtatGg+J81fwcHBbvEhdJecElnzg7vklMiaH9wlp0TW/OAuOSX3ynq16+2py1Soi50kDR48WN27d1etWrVUp04dTZgwQRcvXlTPnj1dHQ0AAKBQKfTFrkuXLjpx4oSGDh2qY8eOqXr16lq6dGmWCyoAAAD+7gp9sZOkvn375njo1cp8fX316quvZjm0XNi4S06JrPnBXXJKZM0P7pJTImt+cJeckntlvRU2k5drZwEAAFDoFeobFAMAACDvKHYAAAAWQbEDAACwCIpdIfD999/r/vvvV+nSpWWz2bRo0SKH53v06CGbzebwp1WrVq4J+39Gjx4tm82mgQMH2seaNGmSJeczzzzjknwxMTFZsthsNsXHx7s06/W2tTFGQ4cOValSpeTv76+4uDjt37//uss2evToAs86bNgwVapUSYGBgQoNDVVcXJw2btxY4Fmvl1OSfv75Zz3wwAMKCQlRYGCgateurcOHD9ufL6jPw/WyJiYmqkePHipdurQCAgLUqlWrLNu/ILKOGjVKtWvXVlBQkEqUKKH27dtr37599udPnz6tfv36qWLFivL391dUVJT69+9v/wrHTNn9DM6fP79As0p5W2eFJeuxY8fUrVs3RUREKDAwUDVq1NBnn33mME1+/1xNnTpVVatWtd/vrV69elqyZIn9+enTp6tJkyYKDg6WzWbT2bNns8yjoH5PXS9rJmOMWrdune3PXUFs+4JEsSsELl68qGrVqmny5Mk5TtOqVSv9+eef9j/z5s0rwISONm/erPfee09Vq1bN8tzTTz/tkHPs2LEuSHgl49U5VqxYIUnq1KmTS7Neb1uPHTtW77zzjqZNm6aNGzcqMDBQLVu21KVLlxymGzFihEP2fv36FXjW22+/Xe+++652796ttWvXKiYmRi1atNCJEycKNOv1ch48eFANGjRQpUqVtHr1au3atUtDhgyRn5+fw3QF8XnILasxRu3bt9dvv/2mxYsXa/v27YqOjlZcXJwuXrxYoFnXrFmj+Ph4/fjjj1qxYoXS0tLUokULe46jR4/q6NGjeuutt7Rnzx7Nnj1bS5cu1ZNPPpllXrNmzXLImnmz+YLKmikv66wwZH3iiSe0b98+ffHFF9q9e7c6dOigzp07a/v27Q7zys+fq7Jly2r06NHaunWrtmzZovvuu08PPvigfvrpJ0lScnKyWrVqpVdeeSXX+RTE76nrZc00YcKEXL99Kr+3fYEyKFQkmYULFzqMde/e3Tz44IMuyXOt8+fPmwoVKpgVK1aYxo0bmwEDBtifu/ZxYTJgwAATGxtrMjIyjDGFI+u12zojI8NERESYN9980z529uxZ4+vra+bNm2cfi46ONuPHjy/ApNl/Lq917tw5I8l8++239rGCzppdzi5dupjHH38819e54vNwbdZ9+/YZSWbPnj32sfT0dBMeHm5mzJhhH3NF1uPHjxtJZs2aNTlO88knnxgfHx+TlpZmH8vL58bZssual3VWWLIGBgaaDz/80GG6YsWKOXwGXPE7IDQ01PznP/9xGFu1apWRZM6cOZNleldkzHRt1u3bt5syZcqYP//8M9vt7Iptn5/YY+cmVq9erRIlSqhixYr6xz/+oVOnTrkkR3x8vNq2bau4uLhsn58zZ46KFy+uO++8Uy+//LKSk5MLOGFWqamp+vjjj9WrVy+Hf7EVtqwJCQk6duyYw7oNCQlR3bp1tWHDBodpR48erbCwMN1999168803dfny5YKO6yA1NVXTp09XSEiIqlWr5vCcK7NmZGTo66+/1u23366WLVuqRIkSqlu3braHa139eUhJSZEkhz2JHh4e8vX11dq1a12aNfMQa7FixXKdJjg4WF5ejrdHjY+PV/HixVWnTh3NnDlTJp/vsJVT1ryss8KQtX79+lqwYIFOnz6tjIwMzZ8/X5cuXVKTJk0cXltQP1fp6emaP3++Ll68qHr16t3Qawv6Zz+7rMnJyeratasmT56c43fMSwW/7fOVi4slrqFs/uUwb948s3jxYrNr1y6zcOFCU7lyZVO7dm1z+fLlAs02b948c+edd5q//vrLGJP1X8HvvfeeWbp0qdm1a5f5+OOPTZkyZcxDDz1UoBmzs2DBAuPp6Wn++OMP+1hhyHrttl63bp2RZI4ePeowXadOnUznzp3tj99++22zatUqs3PnTjN16lRTtGhRM2jQoALNmunLL780gYGBxmazmdKlS5tNmzY5PF/QWa/Nmfkv9ICAADNu3Dizfft2M2rUKGOz2czq1avt07ni83Bt1tTUVBMVFWU6depkTp8+bVJSUszo0aONJNOiRQuXZU1PTzdt27Y19957b47TnDhxwkRFRZlXXnnFYXzEiBFm7dq1Ztu2bWb06NHG19fXTJw4scCz5mWdFZasZ86cMS1atDCSjJeXlwkODjbLli1zmKYgfq527dplAgMDjaenpwkJCTFff/11lmly22NXkD/7uWXt3bu3efLJJ+2Ps/tdVtDbPr9R7AqZnP4CvdrBgwezHPLKb4cPHzYlSpQwO3futI9d7/DGypUrjSRz4MCBAkiYsxYtWph27drlOo0rst5ssbvW+++/b7y8vMylS5fyK2qOn8sLFy6Y/fv3mw0bNphevXqZmJgYk5iY6LKs1+b8448/jCTz6KOPOkx3//33m0ceeSTH+RTE5yG7dbplyxZTrVo1I8l4enqali1bmtatW5tWrVq5LOszzzxjoqOjzZEjR7J9/ty5c6ZOnTqmVatWJjU1Ndd5DRkyxJQtWzY/Yhpjrp81U17Wmauy9u3b19SpU8d8++23ZseOHWbYsGEmJCTE7Nq1K8d55cfPVUpKitm/f7/ZsmWLeemll0zx4sXNTz/95DBNbsWuIDJeL+vixYtN+fLlzfnz5+3T5uXv2Pze9vmNYlfI5OVDZ4wxxYsXN9OmTcv/QP9n4cKF9r9sMv9IMjabzXh6ema79/DChQtGklm6dGmB5bzWoUOHjIeHh1m0aFGu07ki67XbOrOwb9++3WG6Ro0amf79++c4nz179hhJ5pdffsmnpHn/XJYvX9688cYbOT6f31mvzZmSkmK8vLzMyJEjHaZ74YUXTP369XOcT0F8HnJbp2fPnjXHjx83xhhTp04d8+yzz+Y4n/zMGh8fb8qWLWt+++23bJ9PSkoy9erVM82aNbPvyc/NV199ZSTly1/u18t6tbysM1dkPXDgQJbzLI0xplmzZqZPnz45zq8gfgc0a9bM9O7d22HsRopdQWTMlJl1wIAB9r+jrv57y8PDwzRu3DjH1+fnti8IbvFdsXD0v//9T6dOnVKpUqUK7D2bNWum3bt3O4z17NlTlSpV0osvvihPT88sr9mxY4ckFWjOa82aNUslSpRQ27Ztc52uMGQtV66cIiIitHLlSlWvXl2SlJSUpI0bN+of//hHjq/bsWOHPDw8VKJEiQJKmrOMjAz7uWLZKeisPj4+ql27dpZbSvz666+Kjo7O8XWu/jyEhIRIkvbv368tW7Zo5MiROU6bH1mNMerXr58WLlyo1atXq1y5clmmSUpKUsuWLeXr66svvvgiy1XGOWUNDQ116nd15iVrdjmk3NeZK7Jmnvfn4eF4+runp6cyMjJyzZrfP1fX+9m+noL82c/MOnz4cD311FMOz911110aP3687r///hxfnx/bviBR7AqBCxcu6MCBA/bHCQkJ2rFjh4oVK6ZixYpp+PDh6tixoyIiInTw4EG98MILKl++vFq2bFlgGYOCgnTnnXc6jAUGBiosLEx33nmnDh48qLlz56pNmzYKCwvTrl27NGjQIDVq1Cjb26IUhIyMDM2aNUvdu3d3OKHblVlz29ZRUVEaOHCgXnvtNVWoUEHlypXTkCFDVLp0aful9xs2bNDGjRvVtGlTBQUFacOGDRo0aJAef/xxhYaGFljWsLAwvf7663rggQdUqlQpnTx5UpMnT9Yff/xhv6VMQWW93jp9/vnn1aVLFzVq1EhNmzbV0qVL9eWXX2r16tWSCvbzcL2sn376qcLDwxUVFaXdu3drwIABat++vVq0aFGgWePj4zV37lwtXrxYQUFBOnbsmKQrhdPf319JSUlq0aKFkpOT9fHHHyspKUlJSUmSpPDwcHl6eurLL79UYmKi7rnnHvn5+WnFihV644039NxzzzktZ16y5mWdFZaslSpVUvny5dWnTx+99dZbCgsL06JFi7RixQp99dVXkgrm5+rll19W69atFRUVpfPnz2vu3LlavXq1li1bJunKvfaOHTtm/yzv3r1bQUFBioqKUrFixQr091RuWSMiIrK9YCIqKspeqgtq2xcoF+8xhPn/u7Ov/dO9e3eTnJxsWrRoYcLDw423t7eJjo42Tz/9tDl27JirYzucY3f48GHTqFEjU6xYMePr62vKly9vnn/+eXPu3DmX5Vu2bJmRZPbt2+cw7sqsuW1rY67c8mTIkCGmZMmSxtfX1zRr1swh/9atW03dunVNSEiI8fPzM5UrVzZvvPFGvhwyyC3rX3/9ZR566CFTunRp4+PjY0qVKmUeeOABh4snCirr9dapMVfO7ylfvrzx8/Mz1apVczg0X5Cfh+tlnThxoilbtqzx9vY2UVFR5t///rdJSUkp8KzZZZRkZs2aletySDIJCQnGGGOWLFliqlevbooUKWICAwNNtWrVzLRp00x6enqBZs3LOissWY0x5tdffzUdOnQwJUqUMAEBAaZq1aoOtz8piJ+rXr16mejoaOPj42PCw8NNs2bNzPLly+3Pv/rqq7kuR0H+nrpe1mvpmlMgCmrbFySbMe58TS8AAAAycR87AAAAi6DYAQAAWATFDgAAwCIodgAAABZBsQMAALAIih0AAIBFUOwAAAAsgmIHAABgERQ7AC5jjFHv3r1VrFgx2Ww2+3d4/p0cOnTob7vsAJyPYgfAZZYuXarZs2frq6++0p9//pnl+4gzGWMUFxeX7fcjT5kyRUWLFtX//ve/fMnYsmVLeXp6avPmzfky/5vRo0cP2Ww2PfPMM1mei4+Pl81mU48ePQo+GACXo9gByBepqanXnebgwYMqVaqU6tevr4iICHl5eWU7nc1m06xZs7Rx40a999579vGEhAS98MILmjRpksqWLeu07JkOHz6s9evXq2/fvpo5c6bT538rIiMjNX/+fP3111/2sUuXLmnu3LmKiopyYTIArkSxA+AUTZo0Ud++fTVw4EAVL15cLVu21J49e9S6dWsVKVJEJUuWVLdu3XTy5ElJV/Y69evXT4cPH5bNZlNMTEyu84+MjNTEiRP13HPPKSEhQcYYPfnkk2rRooW6du2qJ598UuXKlZO/v78qVqyoiRMn2l+7Z88eeXh46MSJE5Kk06dPy8PDQ4888oh9mtdee00NGjRweM9Zs2apXbt2+sc//qF58+Y5lKjMZe7fv79eeOEFFStWTBERERo2bJjDNL/88osaNGggPz8/ValSRd9++61sNpsWLVqU47Lmtt4y1ahRQ5GRkfr888/tY59//rmioqJ09913O0ybkZGhUaNG2ddPtWrV9N///tf+fHp6eq7rT7qyvdq3b6+33npLpUqVUlhYmOLj45WWlpbjcgAoeBQ7AE7zwQcfyMfHR+vWrdPo0aN133336e6779aWLVu0dOlSJSYmqnPnzpKkiRMnasSIESpbtqz+/PPPPB3q7N69u5o1a6ZevXrp3Xff1Z49e/Tee+8pIyNDZcuW1aeffqq9e/dq6NCheuWVV/TJJ59Iku644w6FhYVpzZo1kqQffvjB4bEkrVmzRk2aNLE/NsZo1qxZevzxx1WpUiWVL1/eoQxdvcyBgYHauHGjxo4dqxEjRmjFihWSrhSm9u3bKyAgQBs3btT06dP1r3/9K9dlPHv2bK7r7Wq9evXSrFmz7I9nzpypnj17Zplu1KhR+vDDDzVt2jT99NNPGjRokB5//HH78l9v/WVatWqVDh48qFWrVumDDz7Q7NmzNXv27FyXB0ABMwDgBI0bNzZ33323/fHIkSNNixYtHKY5cuSIkWT27dtnjDFm/PjxJjo6+obeJzEx0RQvXtx4eHiYhQsX5jhdfHy86dixo/1xhw4dTHx8vDHGmIEDB5rnn3/ehIaGmp9//tmkpqaagIAAs3z5cvv0y5cvN+Hh4SYtLc2etXHjxlmWuUGDBg5jtWvXNi+++KIxxpglS5YYLy8v8+eff9qfX7FihZFkz56QkGAkme3btxtj8rbeunfvbh588EFz/Phx4+vraw4dOmQOHTpk/Pz8zIkTJ8yDDz5ounfvbowx5tKlSyYgIMCsX7/eYZ5PPvmkefTRR/O8/rp3726io6PN5cuX7WOdOnUyXbp0yXEeAApe9ie0AMBNqFmzpv3/d+7cqVWrVqlIkSJZpjt48KBuv/32m3qPEiVKqE+fPlq0aJHat29vH588ebJmzpypw4cP66+//lJqaqqqV69uf75x48aaPn26pCt759544w39+uuvWr16tU6fPq20tDTde++99ulnzpypLl262M/7e/TRR/X888/r4MGDio2NtU9XtWpVh3ylSpXS8ePHJUn79u1TZGSkIiIi7M/XqVMn1+W7kfUWHh6utm3bavbs2TLGqG3btipevLjDaw4cOKDk5GQ1b97cYTw1NdXhkO311p90Zc+np6enw7Lu3r071+UBULAodgCcJjAw0P7/Fy5c0P33368xY8Zkma5UqVK39D5eXl4OF1rMnz9fzz33nN5++23Vq1dPQUFBevPNN7Vx40b7NE2aNNHAgQO1f/9+7d27Vw0aNNAvv/yi1atX68yZM6pVq5YCAgIkXTkHb+HChUpLS9PUqVPt80hPT9fMmTP1+uuv28e8vb0dstlsNmVkZNz0st3oeuvVq5f69u0r6Uo5y25+kvT111+rTJkyDs/5+vpKytv6k5y/rACcj2IHIF/UqFFDn332mWJiYnK82tVZ1q1bp/r16+vZZ5+1jx08eNBhmrvuukuhoaF67bXXVL16dRUpUkRNmjTRmDFjdObMGYfz6+bMmaOyZctmucBh+fLlevvttzVixAiHPVc5qVixoo4cOaLExESVLFlSkq57LuGNrrdWrVopNTVVNpst29vBVKlSRb6+vjp8+LAaN26c7Tzysv4AuAcungCQL+Lj43X69Gk9+uij2rx5sw4ePKhly5apZ8+eSk9Pd+p7VahQQVu2bNGyZcv066+/asiQIVkKlM1mU6NGjTRnzhx7iatatapSUlK0cuVKh9Lz/vvv6+GHH9add97p8OfJJ5/UyZMntXTp0jzlat68uWJjY9W9e3ft2rVL69at07///W97nuzc6Hrz9PTUzz//rL1792ZbNoOCgvTcc89p0KBB+uCDD3Tw4EFt27ZNkyZN0gcffJDn9QfAPVDsAOSL0qVLa926dUpPT1eLFi101113aeDAgSpatKg8PJz7q6dPnz7q0KGDunTporp16+rUqVMOe58yNW7cWOnp6fZi5+HhoUaNGslms9nPr9u6dat27typjh07Znl9SEiImjVrpvfffz9PuTw9PbVo0SJduHBBtWvX1lNPPWW/KtbPzy/b19zMegsODlZwcHCOOUaOHKkhQ4Zo1KhRqly5slq1aqWvv/5a5cqVk5T39Qeg8LMZY4yrQwDA38W6devUoEEDHThwwOEiDABwBoodAOSjhQsXqkiRIqpQoYIOHDigAQMGKDQ0VGvXrnV1NAAWxMUTAAqFw4cPq0qVKjk+v3fvXrf8qqzz58/rxRdf1OHDh1W8eHHFxcXp7bffdnUsABbFHjsAhcLly5d16NChHJ8viKtrAcDdUewAAAAsgqtiAQAALIJiBwAAYBEUOwAAAIug2AEAAFgExQ4AAMAiKHYAAAAWQbEDAACwCIodAACARfw/NCy9hHPqoTMAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -2593,7 +3114,7 @@
     },
     {
      "data": {
-      "image/png": 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Wrdsl13377bcrJCREKSkp6tatm1JSUuTt7a377rvPbVxkZKQkqVy5cm7Lvb29Vbp0abc/ktdCP+fbu3evli1bpkcffVS+vr557kNy3zohSU6nUw6HQ99++22OLRnSua1HV6t+/foKCAjQ0qVLFR0drbCwMFWuXFnNmzfXpEmTlJGR4TpzOJvD4dCsWbO0atUqffXVV5o/f74efPBBvfbaa1q1alWB1HU+p9OpGjVqaOzYsbk+HxUVled1Xe17nNsYSZe85uHFOJ1OSdIrr7zitqXpwvmvJDAXBX9/f3Xs2FGzZ8/WpEmTdPDgQf3444968cUXXWOye3vqqacuulXxwtB14fdGkvr3769p06YpOTlZjRs3VkhIiBwOh+677z7XHFci+zUzZszI9Wz17Msx4frCdx22Ub9+fUnndsNcTNeuXTVq1CglJCRc9I9PNn9/f91zzz364IMPdPDgQX366ae5Xu6jXr16kpRjV8yZM2f0999/q2zZsvnoxrp+zpfbpV3yKz4+XsYYxcXFXXLX79XI3pW4bNkyRUdHu3ZNN2/eXBkZGfrwww918ODBXC/7ctNNN+mmm27SCy+8oJSUFN1///36+OOP9fDDD1923piYGEnntqBk71KVzu1uS01NVa1atVzL4uPjXdcDvNxdFq70LgyF8R7HxMRo8+bNMsa41bN9+/Ycc0tScHDwRS+gLZ070zkwMNC1tel8F64zN9nzbN68+aLzZH8/clvftm3bVKZMGbfLj3Tp0kXTp0/XwoULtXXrVhljXLthJbm2uvr6+l6yt8uZNWuWevbsqddee8217PTp0zp27FiO+nfu3Jnj9Rcuy34vwsLCrqou2Au7YnHNWbRoUa5bFLKPm7nU7pyHH35Yw4cPd/tgvZT7779fmZmZeuyxx/TXX3/lGnBatmypsLAwffjhh24XBn7//feVlZWlNm3aXFP9nC8lJUXR0dFul9LIr06dOsnb21sjR47M0a8xRocPH77qOaRzIW716tVatGiRK9iVKVNGCQkJGjNmjGtMtqNHj+aoJzsk53XrUv369VW2bFlNmTJFZ86ccS1///33c/zR7ty5s/744w9NnTo1x3r++ecf1y5CSQoKCsrx+kspjPf41ltv1f79+zVr1izXslOnTuW4G0i9evUUHx+vV1991XXc6fn++usvSee2EiYlJWnOnDnau3ev6/mtW7dq/vz5l62nbt26iouL0/jx43O8N9k9R0REqHbt2po+fbrbmM2bN+u7777Trbfe6va61q1bKzQ0VDNnztTMmTPVsGFDt12pYWFhatmypd56661c/6GV3dvleHt75/i+TJgwQVlZWW7LkpKStHLlSq1fv9617MiRIznu+pKUlKTg4GC9+OKLuR4fmte6YC9sscM1p3///jp16pTuuusuVa1aVWfOnNGKFSs0c+ZMxcbGqnfv3hd9bUxMTJ6uiZYtMTFRFSpU0BdffKHAwEB16tQpxxh/f3+98sor6tmzp1q0aKHu3btr7969ev3119W8efNcX+PJ/WTbvHmzNm7cqCFDhhTI/Tvj4+M1atQoDR06VLt371bHjh1VokQJpaamavbs2Xr00Uf11FNPXfU8zZs31wsvvKB9+/a5BbgWLVrorbfeUmxsrOu6YpI0ffp0TZo0SXfddZfi4+N14sQJTZ06VcHBwTkCwMX4+vpq1KhReuyxx3TzzTerS5cuSk1N1bRp03IcY9e9e3d98skn6tOnjxYtWqSmTZsqKytL27Zt0yeffKL58+e7ttbWq1dP33//vcaOHavIyEjFxcVd8nqDhfEeP/LII3rzzTfVo0cPrVmzRhEREZoxY4aKFSvmNs7Ly0vvvPOO2rdvr+rVq6t3794qX768/vjjDy1atEjBwcH66quvJEkjR47UvHnz1Lx5cz3++OM6e/asJkyYoOrVq2vjxo2XrMfLy0uTJ0/WHXfcodq1a6t3796KiIjQtm3b9L///c8VDl955RW1b99ejRs31kMPPaR//vlHEyZMUEhISI7fGV9fX3Xq1Ekff/yx0tPT9eqrr+aYd+LEiWrWrJlq1KihRx55RDfccIMOHjyolStX6vfff9eGDRsu+17efvvtmjFjhkJCQlStWjWtXLlS33//fY6Lmj/99NP673//qzZt2qh///4KCgrSO++8o+joaB05csT1+xgcHKzJkyere/fuqlu3ru677z6VLVtWe/fu1dy5c9W0aVO9+eabl60LNlO0J+ECV+/bb781Dz74oKlataopXry48fPzMxUrVjT9+/c3Bw8edBubfXmQS8nt8iDnGzx4sJF02ct9fPTRR6ZWrVrG39/flCtXzvTr1y9P133z1H6yL4WycePGy/ZwvstdquSzzz4zzZo1M0FBQSYoKMhUrVrV9O3b1+2SK/m93IkxxqSlpRlvb29TokQJt8tN/Pe//zWSTPfu3d3Gr1271nTt2tVER0cbf39/ExYWZm6//Xbzyy+/XPHckyZNMnFxccbf39/Ur1/fLF261CQmJrpd7sSYc5dHGTNmjKlevbrx9/c3pUqVMvXq1TMjR450XW/PGGO2bdtmWrRoYQIDA40k16VPCuI9TkxMdLtOW7aePXuamJgYt2V79uwxd955pylWrJgpU6aMGTBggJk3b16O69gZY8y6detMp06dTOnSpY2/v7+JiYkxnTt3NgsXLnQbt2TJElOvXj3j5+dnbrjhBjNlyhRXX3mxfPly06ZNG1OiRAkTFBRkatasaSZMmOA25vvvvzdNmzY1gYGBJjg42Nxxxx1my5Ytua5vwYIFRpJxOBxm3759uY7ZtWuX6dGjhwkPDze+vr6mfPny5vbbbzezZs1yjbnU79/Ro0dN7969TZkyZUzx4sVNUlKS2bZtm4mJiclxWZt169aZ5s2bG39/f1OhQgUzevRo88YbbxhJ5s8//3Qbu2jRIpOUlGRCQkJMQECAiY+PN7169crXzzCufQ5j8nGULAAAKFLJycl66623dPLkyYue+AJwjB0AAB7mn3/+cXt8+PBhzZgxQ82aNSPU4ZI4xg6Axzt58mSuB+Sfr2zZsoXyB+/IkSNuJ0RcyNvbO99nPgMX07hxY7Vs2VIJCQk6ePCg3n33XaWlpWnYsGFWlwYPR7AD4PFeffVVjRw58pJjUlNTFRsbW+Bzd+rUKdebxGeLiYnJ9SbuwNW49dZbNWvWLL399ttyOByqW7eu3n333Vwv1QOcj2PsAHi83377ze02V7lp1qyZAgICCnzuNWvWXPIi04GBgWratGmBzwsA+UGwAwAAsAlOngAAALAJ2x9j53Q6tX//fpUoUaJALrIKAABQlIwxOnHihCIjI+XldeltcrYPdvv377+im2oDAAB4on379rndOSc3tg92JUqUkHTuzQgODi6UOTIzM/Xdd9+pbdu28vX1LZQ5PBn90z/90z/90z/9F17/aWlpioqKcmWaS7F9sDv/nnqFGeyKFSum4ODg6/YHm/7pn/7pn/7p/3pT1P3n5ZAyTp4AAACwCYIdAACATRDsAAAAbML2x9gBAICilZWVpczMTKvLKHSZmZny8fHR6dOnlZWVle/1+Pr6Fti9rgl2AACgQBhj9Oeff+rYsWNWl1IkjDEKDw/Xvn37rvpauSVLllR4ePhVr4dgBwAACkR2qAsLC1OxYsVsf2MAp9OpkydPqnjx4pe9cPDFGGN06tQpHTp0SJIUERFxVTUR7AAAwFXLyspyhbrSpUtbXU6RcDqdOnPmjAICAvId7CQpMDBQknTo0CGFhYVd1W5ZTp4AAABXLfuYumLFillcybUp+3272mMTCXYAAKDA2H33a2EpqPeNYAcAAGATBDsAAACb4OQJAABQqGKHzC2yuXa/dFuRzeWJ2GIHAABwBc6cOWN1CRdFsAMAANe1li1bql+/furXr59CQkJUpkwZDRs2TMYYSVJsbKyef/559ejRQ8HBwXr00UclScuXL1f79u0VFBSkqKgoPfHEE0pPT7eyFYIdAADA9OnT5ePjo59++kmvv/66xo4dq3feecf1/KuvvqpatWpp3bp1GjZsmHbt2qVbb71Vd955p9avX6+ZM2dq+fLl6tevn4VdcIwdAACAoqKiNG7cODkcDlWpUkWbNm3SuHHj9Mgjj0iSbr75Zj355JOu8Q8//LC6deumf/3rXwoODlaVKlX0xhtvKDExUZMnT1ZAQIAlfRDsAKAgLBsrOZzWzN1qqDXzAjZy0003uV1LrnHjxnrttdeUlZUlSapfv77b+A0bNmjjxo1KSUlxLTPGyOl0KjU1VQkJCUVT+AUIdgAAAJcRFBTk9vjkyZN69NFH1bt37xz3io2Oji7q8lwIdgAA4Lq3evVqt8erVq1SpUqVLnrf1rp162rr1q264YYbFBwcfFX3ii1InlEFAACAhfbu3atBgwZp+/bt+uijjzRhwgQNGDDgouOfeeYZrVixQoMHD9b69eu1Y8cOffHFF5w8AQAAYLUePXron3/+UcOGDeXt7a0BAwa4LmuSm5o1a2rRokUaOnSoEhMTZYxRfHy8unTpUoRV50SwAwAAhepauBuEr6+vxo8fr8mTJ+d4bvfu3bm+pkGDBvr888/ZFQsAAICCR7ADAACwCXbFAgCA69rixYutLqHAsMUOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACb4Dp2AACgcC0aXXRztRpadHPlweLFi9WqVSsdPXpUJUuWLPT52GIHAABgEwQ7AABwXWvZsqX69eunfv36KSQkRGXKlNGwYcNkjJEkHT16VD169FCpUqVUrFgxtW/fXjt27HC9fs+ePbrjjjtUqlQpBQUFqXr16vrmm2+0e/dutWrVSpJUqlQpORwO9erVq1B7IdgBAIDr3vTp0+Xj46OffvpJr7/+usaOHat33nlHktSrVy/98ssv+vLLL7Vy5UoZY3TrrbcqMzNTktSvXz9lZGRo6dKl2rRpk8aMGaPixYsrKipKn332mSRp+/btOnDggF5//fVC7YNj7AAAwHUvKipK48aNk8PhUJUqVbRp0yaNGzdOLVu21Jdffqkff/xRTZo0kSR9+OGHioqK0pw5c5SUlKR9+/bp7rvvVo0aNSRJN9xwg2u9oaGhkqSwsDCOsQMAACgKN910kxwOh+tx48aNtWPHDm3ZskU+Pj5q1KiR67nSpUurSpUq2rZtm6RzW+xGjRqlpk2bavjw4dq4cWOR15+NYAcAAHAVHn74Yf3222/q3r27Nm3apPr162vChAmW1EKwAwAA173Vq1e7PV61apUqVaqkatWq6ezZs27PHz58WNu3b1dCQoJrWVRUlPr06aPPP/9cTz75pKZOnSpJ8vPzkyRlZWUVQRcEOwAAAO3du1eDBg3S9u3b9dFHH2nChAkaMGCAKlWqpA4dOuiRRx7R8uXLtWHDBj3wwAMqX768OnToIEkaOHCg5s+fr9TUVK1du1aLFi1yhb6YmBg5HA59/fXX+uuvv3Ty5MlC7YNgBwAArns9evTQP//8o4YNG6pv374aMGCAHn30UUnStGnTVK9ePd1+++1q3LixjDH65ptv5OvrK+nc1ri+ffsqISFB7dq1U+XKlTVp0iRJUvny5TVy5EgNGTJE5cqVU79+/Qq1D86KBQAAhcvD7gaRG19fX40fP16TJ0/O8VypUqX0wQcf5FjudDolSW+88Ya8vC6+rWzYsGEaNmxYwRV7CWyxAwAAsAmCHQAAgE2wKxYAAFzXFi9ebHUJBYYtdgAAADZBsAMAALAJgh0AACgw2WeK4soU1PvGMXYAAOCq+fn5ycvLS/v371fZsmXl5+fndu9VO3I6nTpz5oxOnz59ycudXIoxRmfOnNFff/0lLy8v150q8otgBwAArpqXl5fi4uJ04MAB7d+/3+pyioQxRv/8848CAwOvOsQWK1ZM0dHR+Q6I2Qh2AACgQPj5+Sk6Olpnz54tsnujWikzM1NLly5VixYtXHehyA9vb2/5+PgUyBZOgh0AACgwDodDvr6+VxV0rhXe3t46e/asAgICPKZfgh2AgrFsrOSw6KDpa+B2RQBQFDgrFgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABswtJgN3r0aDVo0EAlSpRQWFiYOnbsqO3bt7uNOX36tPr27avSpUurePHiuvvuu3Xw4EGLKgYAAPBclga7JUuWqG/fvlq1apUWLFigzMxMtW3bVunp6a4xAwcO1FdffaVPP/1US5Ys0f79+9WpUycLqwYAAPBMll7Hbt68eW6P33//fYWFhWnNmjVq0aKFjh8/rnfffVcpKSm6+eabJUnTpk1TQkKCVq1apZtuusmKsgEAADySR12g+Pjx45Kk0NBQSdKaNWuUmZmp1q1bu8ZUrVpV0dHRWrlyZa7BLiMjQxkZGa7HaWlpks7d9iMzM7NQ6s5eb2Gt39PRP/1LUqaxcAeAhe89/fPzf/5/rzf0XzT9X8n6HcYYU4i15JnT6dSdd96pY8eOafny5ZKklJQU9e7d2y2oSVLDhg3VqlUrjRkzJsd6RowYoZEjR+ZYnpKSomLFihVO8QAAAIXk1KlT6tatm44fP67g4OBLjvWYLXZ9+/bV5s2bXaEuv4YOHapBgwa5HqelpSkqKkpt27a97JuRX5mZmVqwYIHatGnjMfeKK0r0T/8LFixQm+K/yteqW4o1H3T5MYWE/vn5p3/6L+z+s/c+5oVHBLt+/frp66+/1tKlS1WhQgXX8vDwcJ05c0bHjh1TyZIlXcsPHjyo8PDwXNfl7+8vf3//HMuL4obE18tNjy+G/q/z/h1O64KNB7zv133/1/vPP/3TfyH2fyXrtjTYGWPUv39/zZ49W4sXL1ZcXJzb8/Xq1ZOvr68WLlyou+++W5K0fft27d27V40bN7aiZADI1aTFO2WcZy2ZO7mVJdMC8ECWBru+ffsqJSVFX3zxhUqUKKE///xTkhQSEqLAwECFhITooYce0qBBgxQaGqrg4GD1799fjRs35oxYAACAC1ga7CZPnixJatmypdvyadOmqVevXpKkcePGycvLS3fffbcyMjKUlJSkSZMmFXGlAAAAns/yXbGXExAQoIkTJ2rixIlFUBEAAMC1i3vFAgAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEz5WFwAAwNWIHTLXsrn9vY1ebmjZ9EAObLEDAACwCbbYAbjmscUGAM5hix0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ARnxQIArtqNI+YrI8thdRnAdY8tdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgpMnABSISYt3yjjPWjR7TYvmBQDPwhY7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAm+DOEwCAq/a49xcyDmvuPDL+7D2WzAt4IrbYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgE1zHDsA1L9lnlmVzO7x8JN1u2fwAcD622AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATXBWLABc6xaNtm5u4yWpqnXzA3DDFjsAAACbINgBAADYBMEOAADAJgh2AAAANsHJEwBwjRu/8FfL5nZ4+Si2HidPAJ6CLXYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCUuD3dKlS3XHHXcoMjJSDodDc+bMcXu+V69ecjgcbl/t2rWzplgAAAAPZ2mwS09PV61atTRx4sSLjmnXrp0OHDjg+vroo4+KsEIAAIBrh4+Vk7dv317t27e/5Bh/f3+Fh4cXUUUAAADXLo8/xm7x4sUKCwtTlSpV9K9//UuHDx+2uiQAAACPZOkWu8tp166dOnXqpLi4OO3atUv//ve/1b59e61cuVLe3t65viYjI0MZGRmux2lpaZKkzMxMZWZmFkqd2estrPV7Ovqnf0lyeHn0x0mhye6b/q3r39/bWDe317m5r/fff/ov3P6vZP0OY4x1vxHncTgcmj17tjp27HjRMb/99pvi4+P1/fff65Zbbsl1zIgRIzRy5Mgcy1NSUlSsWLGCKhcAAKBInDp1St26ddPx48cVHBx8ybHX1D8xb7jhBpUpU0Y7d+68aLAbOnSoBg0a5HqclpamqKgotW3b9rJvRn5lZmZqwYIFatOmjXx9fQtlDk9G//S/YMEC7Vk3T8Z51upyipzDy0cxddrRv4X9T8rqYMm80rktds/Xd173v//0X7j9Z+99zItrKtj9/vvvOnz4sCIiIi46xt/fX/7+/jmW+/r6FvoPXVHM4cno//ru3zjPXpfBJhv9W9d/RpbDknnPd73//tN/4fZ/Jeu2NNidPHlSO3fudD1OTU3V+vXrFRoaqtDQUI0cOVJ33323wsPDtWvXLj399NOqWLGikpKSLKwaAADAM1ka7H755Re1atXK9Th7F2rPnj01efJkbdy4UdOnT9exY8cUGRmptm3b6vnnn891ixwAAMD1ztJg17JlS13q3I358+cXYTUAAADXNo+/jh0AAADyhmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCauqQsUAwBwoWSfWZbNfe4eubdbNj9wIbbYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYKJNhlZWVp/fr1Onr0aEGsDgAAAPmQr2CXnJysd999V9K5UJeYmKi6desqKipKixcvLsj6AAAAkEf5CnazZs1SrVq1JElfffWVUlNTtW3bNg0cOFD/+c9/CrRAAAAA5E2+gt3ff/+t8PBwSdI333yje++9V5UrV9aDDz6oTZs2FWiBAAAAyJt8Bbty5cppy5YtysrK0rx589SmTRtJ0qlTp+Tt7V2gBQIAACBvfPLzot69e6tz586KiIiQw+FQ69atJUmrV69W1apVC7RAAAAA5E2+gt2IESNUo0YN7d27V/fee6/8/f0lSd7e3hoyZEiBFggAAIC8ueJgl5mZqXbt2mnKlCm6++673Z7r2bNngRUGAMA1Y9lYyeG0Zu5WQ62ZFx7pio+x8/X11caNGwujFgAAAFyFfJ088cADD7iuYwcAAADPkK9j7M6ePav33ntP33//verVq6egoCC358eOHVsgxQEAACDv8hXsNm/erLp160qSfv31V7fnHA7H1VcFAACAK5avYLdo0aKCrgMAAABXKV/H2AEAAMDz5GuLXatWrS65y/WHH37Id0EAAADIn3wFu9q1a7s9zszM1Pr167V582auZQcAAGCRfAW7cePG5bp8xIgROnny5FUVBAAAgPwp0GPsHnjgAb333nsFuUoAAADkUYEGu5UrVyogIKAgVwkAAIA8yteu2E6dOrk9NsbowIED+uWXXzRs2LACKQwAAABXJl/BLiQkxO2xl5eXqlSpoueee05t27YtkMIAAABwZfIV7KZNm1bQdQAAAOAq5SvYZVuzZo22bt0qSapevbrq1KlTIEUBAADgyuUr2B06dEj33XefFi9erJIlS0qSjh07platWunjjz9W2bJlC7JGAAAA5EG+zort37+/Tpw4of/97386cuSIjhw5os2bNystLU1PPPFEQdcIAACAPMjXFrt58+bp+++/V0JCgmtZtWrVNHHiRE6eAAAAsEi+ttg5nU75+vrmWO7r6yun03nVRQEAAODK5SvY3XzzzRowYID279/vWvbHH39o4MCBuuWWWwqsOAAAAORdvoLdm2++qbS0NMXGxio+Pl7x8fGKjY1VWlqaJkyYUNA1AgAAIA/ydYxdVFSU1q5dq4ULF7oud5KQkKDWrVsXaHEAAADIu3xfx+6HH37QDz/8oEOHDsnpdGrdunVKSUmRJL333nsFViAAAADyJl/BbuTIkXruuedUv359RUREyOFwFHRdAAAAuEL5CnZTpkzR+++/r+7duxd0PQAAAMinfJ08cebMGTVp0qSgawEAAMBVyFewe/jhh13H0wEAAMAz5HlX7KBBg1z/73Q69fbbb+v7779XzZo1c1yseOzYsQVXIQAAAPIkz8Fu3bp1bo9r164tSdq8ebPbck6kAAAAsEaeg92iRYsKsw4AAABcpXwdYwcAAADPQ7ADAACwCYIdAACATRDsAAAAbCLf94oF4Dlih8y1bG5/b6OXG1o2PQDgPGyxAwAAsAmCHQAAgE1YGuyWLl2qO+64Q5GRkXI4HJozZ47b88YYPfvss4qIiFBgYKBat26tHTt2WFMsAACAh7M02KWnp6tWrVqaOHFirs+//PLLeuONNzRlyhStXr1aQUFBSkpK0unTp4u4UgAAAM9n6ckT7du3V/v27XN9zhij8ePH6//9v/+nDh06SJI++OADlStXTnPmzNF9991XlKUCAAB4PI89KzY1NVV//vmnWrdu7VoWEhKiRo0aaeXKlRcNdhkZGcrIyHA9TktLkyRlZmYqMzOzUGrNXm9hrd/T0b/1/ft7G+vm9jo3t8PLYz9OClV23/R/ffefaSzcAWbhZ48nfP5Zqaj6v5L1O4wx1v1FOI/D4dDs2bPVsWNHSdKKFSvUtGlT7d+/XxEREa5xnTt3lsPh0MyZM3Ndz4gRIzRy5Mgcy1NSUlSsWLFCqR0AAKCwnDp1St26ddPx48cVHBx8ybG2+yfW0KFDNWjQINfjtLQ0RUVFqW3btpd9M/IrMzNTCxYsUJs2beTr61soc3gy+re+/xtHzLdkXuncFrvn6zu1Z908GedZy+qwisPLRzF12tH/dd5/m+K/ytfhtKaI5oMuP6aQeMLnn5WKqv/svY954bHBLjw8XJJ08OBBty12Bw8eVO3atS/6On9/f/n7++dY7uvrW+g/dEUxhyejf+v6z8hyWDLv+Yzz7HX5hz0b/V/f/fs6nNYFOw/43OXzv3D7v5J1e+x17OLi4hQeHq6FCxe6lqWlpWn16tVq3LixhZUBAAB4Jku32J08eVI7d+50PU5NTdX69esVGhqq6OhoJScna9SoUapUqZLi4uI0bNgwRUZGuo7DAwAAwP+xNNj98ssvatWqletx9rFxPXv21Pvvv6+nn35a6enpevTRR3Xs2DE1a9ZM8+bNU0BAgFUlAwAAeCxLg13Lli11qZNyHQ6HnnvuOT333HNFWBUAAMC1yWOPsQMAAMCVIdgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACb8LG6AAAArnWTFu+UcZ61ZO7kVpZMCw/FFjsAAACbINgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyC69gBNpDsM8uyuR1ePpJut2x+AMD/YYsdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANiEj9UFAACAq7BotHVzGy9JVa2bHzmwxQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbMKjg92IESPkcDjcvqpWrWp1WQAAAB7Jx+oCLqd69er6/vvvXY99fDy+ZAAAAEt4fEry8fFReHi41WUAAAB4PI8Pdjt27FBkZKQCAgLUuHFjjR49WtHR0Rcdn5GRoYyMDNfjtLQ0SVJmZqYyMzMLpcbs9RbW+j0d/Vvfv8PLul/l7LmtrMFK9E//5//XCpnGuqOqsufm879w+7+S9TuMMaYQa7kq3377rU6ePKkqVarowIEDGjlypP744w9t3rxZJUqUyPU1I0aM0MiRI3MsT0lJUbFixQq7ZAAAgAJ16tQpdevWTcePH1dwcPAlx3p0sLvQsWPHFBMTo7Fjx+qhhx7KdUxuW+yioqL0999/X/bNyK/MzEwtWLBAbdq0ka+vb6HM4cno3/r+Jz3/uCXzSue2VMTUaac96+bJOM9aVodV6J/+re7/8ZYVLZlXOrfFbsHJynz+F3L/aWlpKlOmTJ6C3TW17bxkyZKqXLmydu7cedEx/v7+8vf3z7Hc19e30H/oimIOT0b/1vXvCX9QjfOsR9RhFfqnf6v693U4LZnXrQY+/wu1/ytZt0df7uRCJ0+e1K5duxQREWF1KQAAAB7Ho4PdU089pSVLlmj37t1asWKF7rrrLnl7e6tr165WlwYAAOBxPHpX7O+//66uXbvq8OHDKlu2rJo1a6ZVq1apbNmyVpcGAADgcTw62H388cdWlwAAAHDN8OhdsQAAAMg7j95iBwAALm38wl8tm9vh5aPYetzD3ZOwxQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJvwsboAAABwbbtxxHxlZDksmXv3S7dZMq+nYosdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATXDnCaCAWHnl9WR+kwEAYosdAACAbRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANiEj9UFAHbxuPcXMo6zVpcBALiOscUOAADAJgh2AAAANkGwAwAAsAmCHQAAgE1w8gQAALhmxQ6Za9nc/t5GLze0bPpcscUOAADAJgh2AAAANsGuWAAAcFWsvI7n+LP3WDKvp2KLHQAAgE2wxQ62wMGzAABcI1vsJk6cqNjYWAUEBKhRo0b66aefrC4JAADA43h8sJs5c6YGDRqk4cOHa+3atapVq5aSkpJ06NAhq0sDAADwKB6/K3bs2LF65JFH1Lt3b0nSlClTNHfuXL333nsaMmSIxdUBAAArJfvMsmxuh5ePpNstmz83Hr3F7syZM1qzZo1at27tWubl5aXWrVtr5cqVFlYGAADgeTx6i93ff/+trKwslStXzm15uXLltG3btlxfk5GRoYyMDNfj48ePS5KOHDmizMzMQqkzMzNTp06d0uHDh+Xr61soc3gyT+jf52y6JfNKko/T6NQppzIynTJOp2V1WMXh5dSpU6fon/7pn/6tLqfIZfdf2H//Tpw4IUkyxlx2rEcHu/wYPXq0Ro4cmWN5XFycBdXgetHN6gIs957VBViM/q9v9H99K7r+T5w4oZCQkEuO8ehgV6ZMGXl7e+vgwYNuyw8ePKjw8PBcXzN06FANGjTI9djpdOrIkSMqXbq0HA5HodSZlpamqKgo7du3T8HBwYUyhyejf/qnf/qnf/qn/8Lr3xijEydOKDIy8rJjPTrY+fn5qV69elq4cKE6duwo6VxQW7hwofr165fra/z9/eXv7++2rGTJkoVc6TnBwcHX5Q92Nvqnf/qn/+sV/dN/Yfd/uS112Tw62EnSoEGD1LNnT9WvX18NGzbU+PHjlZ6e7jpLFgAAAOd4fLDr0qWL/vrrLz377LP6888/Vbt2bc2bNy/HCRUAAADXO48PdpLUr1+/i+569QT+/v4aPnx4jl3A1wv6p3/6p3/6p//rkSf27zB5OXcWAAAAHs+jL1AMAACAvCPYAQAA2ATBDgAAwCYIdgVg4sSJio2NVUBAgBo1aqSffvrJ6pKKxOjRo9WgQQOVKFFCYWFh6tixo7Zv3251WZZ56aWX5HA4lJycbHUpReaPP/7QAw88oNKlSyswMFA1atTQL7/8YnVZRSIrK0vDhg1TXFycAgMDFR8fr+effz5Pt/y5Fi1dulR33HGHIiMj5XA4NGfOHLfnjTF69tlnFRERocDAQLVu3Vo7duywpthCcKn+MzMz9cwzz6hGjRoKCgpSZGSkevToof3791tXcAG73Pf/fH369JHD4dD48eOLrL7Clpf+t27dqjvvvFMhISEKCgpSgwYNtHfv3iKvlWB3lWbOnKlBgwZp+PDhWrt2rWrVqqWkpCQdOnTI6tIK3ZIlS9S3b1+tWrVKCxYsUGZmptq2bav0dOvu22qVn3/+WW+99ZZq1qxpdSlF5ujRo2ratKl8fX317bffasuWLXrttddUqlQpq0srEmPGjNHkyZP15ptvauvWrRozZoxefvllTZgwwerSCkV6erpq1aqliRMn5vr8yy+/rDfeeENTpkzR6tWrFRQUpKSkJJ0+fbqIKy0cl+r/1KlTWrt2rYYNG6a1a9fq888/1/bt23XnnXdaUGnhuNz3P9vs2bO1atWqPN0h4Vpyuf537dqlZs2aqWrVqlq8eLE2btyoYcOGKSAgoIgrlWRwVRo2bGj69u3repyVlWUiIyPN6NGjLazKGocOHTKSzJIlS6wupUidOHHCVKpUySxYsMAkJiaaAQMGWF1SkXjmmWdMs2bNrC7DMrfddpt58MEH3ZZ16tTJ3H///RZVVHQkmdmzZ7seO51OEx4ebl555RXXsmPHjhl/f3/z0UcfWVBh4bqw/9z89NNPRpLZs2dP0RRVhC7W/++//27Kly9vNm/ebGJiYsy4ceOKvLaikFv/Xbp0MQ888IA1BV2ALXZX4cyZM1qzZo1at27tWubl5aXWrVtr5cqVFlZmjePHj0uSQkNDLa6kaPXt21e33Xab28/B9eDLL79U/fr1de+99yosLEx16tTR1KlTrS6ryDRp0kQLFy7Ur7/+KknasGGDli9frvbt21tcWdFLTU3Vn3/+6fY7EBISokaNGl2Xn4XSuc9Dh8NRZLe0tJrT6VT37t01ePBgVa9e3epyipTT6dTcuXNVuXJlJSUlKSwsTI0aNbrk7urCRLC7Cn///beysrJy3AWjXLly+vPPPy2qyhpOp1PJyclq2rSpbrzxRqvLKTIff/yx1q5dq9GjR1tdSpH77bffNHnyZFWqVEnz58/Xv/71Lz3xxBOaPn261aUViSFDhui+++5T1apV5evrqzp16ig5OVn333+/1aUVuezPOz4Lzzl9+rSeeeYZde3a9bq5f+qYMWPk4+OjJ554wupSityhQ4d08uRJvfTSS2rXrp2+++473XXXXerUqZOWLFlS5PVcE3eegOfr27evNm/erOXLl1tdSpHZt2+fBgwYoAULFlhzHIXFnE6n6tevrxdffFGSVKdOHW3evFlTpkxRz549La6u8H3yySf68MMPlZKSourVq2v9+vVKTk5WZGTkddE/cpeZmanOnTvLGKPJkydbXU6RWLNmjV5//XWtXbtWDofD6nKKnNPplCR16NBBAwcOlCTVrl1bK1as0JQpU5SYmFik9bDF7iqUKVNG3t7eOnjwoNvygwcPKjw83KKqil6/fv309ddfa9GiRapQoYLV5RSZNWvW6NChQ6pbt658fHzk4+OjJUuW6I033pCPj4+ysrKsLrFQRUREqFq1am7LEhISLDkLzAqDBw92bbWrUaOGunfvroEDB16XW2+zP++u98/C7FC3Z88eLViw4LrZWrds2TIdOnRI0dHRrs/CPXv26Mknn1RsbKzV5RW6MmXKyMfHx2M+Dwl2V8HPz0/16tXTwoULXcucTqcWLlyoxo0bW1hZ0TDGqF+/fpo9e7Z++OEHxcXFWV1Skbrlllu0adMmrV+/3vVVv3593X///Vq/fr28vb2tLrFQNW3aNMflbX799VfFxMRYVFHROnXqlLy83D9Cvb29Xf96v57ExcUpPDzc7bMwLS1Nq1evvi4+C6X/C3U7duzQ999/r9KlS1tdUpHp3r27Nm7c6PZZGBkZqcGDB2v+/PlWl1fo/Pz81KBBA4/5PGRX7FUaNGiQevbsqfr166thw4YaP3680tPT1bt3b6tLK3R9+/ZVSkqKvvjiC5UoUcJ1LE1ISIgCAwMtrq7wlShRIsfxhEFBQSpduvR1cZzhwIED1aRJE7344ovq3LmzfvrpJ7399tt6++23rS6tSNxxxx164YUXFB0drerVq2vdunUaO3asHnzwQatLKxQnT57Uzp07XY9TU1O1fv16hYaGKjo6WsnJyRo1apQqVaqkuLg4DRs2TJGRkerYsaN1RRegS/UfERGhe+65R2vXrtXXX3+trKws1+dhaGio/Pz8rCq7wFzu+39hkPX19VV4eLiqVKlS1KUWisv1P3jwYHXp0kUtWrRQq1atNG/ePH311VdavHhx0Rdr9Wm5djBhwgQTHR1t/Pz8TMOGDc2qVausLqlISMr1a9q0aVaXZpnr6XInxhjz1VdfmRtvvNH4+/ubqlWrmrffftvqkopMWlqaGTBggImOjjYBAQHmhhtuMP/5z39MRkaG1aUVikWLFuX6+96zZ09jzLlLngwbNsyUK1fO+Pv7m1tuucVs377d2qIL0KX6T01Nvejn4aJFi6wuvUBc7vt/Ibtd7iQv/b/77rumYsWKJiAgwNSqVcvMmTPHklodxtj0MukAAADXGY6xAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJgh2AAAANkGwA+ARjDF69NFHFRoaKofDofXr11tdUq4WL14sh8OhY8eOWV3KFenVq9dV397rWu0duJ4Q7AB4hHnz5un999/X119/rQMHDtjqfruxsbEaP3681WUAuA74WF0AAPs7c+bMZW+EvmvXLkVERKhJkyZFVJVnycrKksPhkJcX/94GkH98ggAocC1btlS/fv2UnJysMmXKKCkpSZs3b1b79u1VvHhxlStXTt27d9fff/8t6dxuwv79+2vv3r1yOByKjY295Pq//vprlSxZUllZWZKk9evXy+FwaMiQIa4xDz/8sB544AFJ0p49e3THHXeoVKlSCgoKUvXq1fXNN9/kqZdvvvlGlStXVmBgoFq1aqXdu3fnGLN8+XI1b95cgYGBioqK0hNPPKH09HTXe7Fnzx4NHDhQDodDDodDkvT++++rZMmS+vLLL1WtWjX5+/tr7969ysjI0FNPPaXy5csrKChIjRo10uLFi11zZb9u/vz5SkhIUPHixdWuXTsdOHDANSYrK0uDBg1SyZIlVbp0aT399NO68LbgTqdTo0ePVlxcnAIDA1WrVi3NmjXrinsH4GEMABSwxMREU7x4cTN48GCzbds2s2rVKlO2bFkzdOhQs3XrVrN27VrTpk0b06pVK2OMMceOHTPPPfecqVChgjlw4IA5dOjQJdd/7Ngx4+XlZX7++WdjjDHjx483ZcqUMY0aNXKNqVixopk6daoxxpjbbrvNtGnTxmzcuNHs2rXLfPXVV2bJkiWX7WPv3r3G39/fDBo0yGzbts3897//NeXKlTOSzNGjR40xxuzcudMEBQWZcePGmV9//dX8+OOPpk6dOqZXr17GGGMOHz5sKlSoYJ577jlz4MABc+DAAWOMMdOmTTO+vr6mSZMm5scffzTbtm0z6enp5uGHHzZNmjQxS5cuNTt37jSvvPKK8ff3N7/++qvb61q3bm1+/vlns2bNGpOQkGC6devmqnvMmDGmVKlS5rPPPjNbtmwxDz30kClRooTp0KGDa8yoUaNM1apVzbx588yuXbvMtGnTjL+/v1m8eHGeewfgeQh2AApcYmKiqVOnjuvx888/b9q2bes2Zt++fUaS2b59uzHGmHHjxpmYmJg8z1G3bl3zyiuvGGOM6dixo3nhhReMn5+fOXHihPn999+NJFcYqlGjhhkxYsQV9zF06FBTrVo1t2XPPPOMW7h56KGHzKOPPuo2ZtmyZcbLy8v8888/xhhjYmJizLhx49zGTJs2zUgy69evdy3bs2eP8fb2Nn/88Yfb2FtuucUMHTrU7XU7d+50PT9x4kRTrlw51+OIiAjz8ssvux5nZmaaChUquILd6dOnTbFixcyKFSvc5nnooYdM165d89w7AM/DMXYACkW9evVc/79hwwYtWrRIxYsXzzFu165dqly58hWvPzExUYsXL9aTTz6pZcuWafTo0frkk0+0fPlyHTlyRJGRkapUqZIk6YknntC//vUvfffdd2rdurXuvvtu1axZ87JzbN26VY0aNXJb1rhxY7fHGzZs0MaNG/Xhhx+6lhlj5HQ6lZqaqoSEhIuu38/Pz62OTZs2KSsrK8f7kZGRodKlS7seFytWTPHx8a7HEREROnTokCTp+PHjOnDggFvdPj4+ql+/vmt37M6dO3Xq1Cm1adPGbZ4zZ86oTp06ee4dgOch2AEoFEFBQa7/P3nypO644w6NGTMmx7iIiIh8rb9ly5Z67733tGHDBvn6+qpq1apq2bKlFi9erKNHjyoxMdE19uGHH1ZSUpLmzp2r7777TqNHj9Zrr72m/v3752vu8508eVKPPfaYnnjiiRzPRUdHX/K1gYGBrmPustfl7e2tNWvWyNvb223s+aHY19fX7TmHw5HjGLrL1SxJc+fOVfny5d2e8/f3z/N6AHgegh2AQle3bl199tlnio2NlY9PwXzsNG/eXCdOnNC4ceNcIa5ly5Z66aWXdPToUT355JNu46OiotSnTx/16dNHQ4cO1dSpUy8b7BISEvTll1+6LVu1apXb47p162rLli2qWLHiRdfj5+fnOtHjUurUqaOsrCwdOnRIzZs3v+z43ISEhCgiIkKrV69WixYtJElnz57VmjVrVLduXUlyO1nj/AB8vrz0DsDzcFYsgELXt29fHTlyRF27dtXPP/+sXbt2af78+erdu3eeAk9uSpUqpZo1a+rDDz9Uy5YtJUktWrTQ2rVr9euvv7oFluTkZM2fP1+pqalau3atFi1adMldpNn69OmjHTt2aPDgwdq+fbtSUlL0/vvvu4155plntGLFCvXr10/r16/Xjh079MUXX6hfv36uMbGxsVq6dKn++OMP15nAualcubLuv/9+9ejRQ59//rlSU1P1008/afTo0Zo7d26e35sBAwbopZde0pw5c7Rt2zY9/vjjbhcVLlGihJ566ikNHDhQ06dP165du7R27VpNmDBB06dPz3PvADwPwQ5AoYuMjNSPP/6orKwstW3bVjVq1FBycrJKlix5VddtS0xMVFZWlivYhYaGqlq1agoPD1eVKlVc47KystS3b18lJCSoXbt2qly5siZNmnTZ9UdHR+uzzz7TnDlzVKtWLU2ZMkUvvvii25iaNWtqyZIl+vXXX9W8eXPVqVNHzz77rCIjI11jnnvuOe3evVvx8fEqW7bsJeecNm2aevTooSeffFJVqlRRx44d9fPPP192t+75nnzySXXv3l09e/ZU48aNVaJECd11111uY55//nkNGzZMo0ePdr0vc+fOVVxcXJ57B+B5HOZKDswAAACAx2KLHQAAgE0Q7AB4nL1796p48eIX/dq7d2+BzNOnT5+LztGnT58CmQMAihK7YgF4nLNnz17y9lUFdXbtoUOHlJaWlutzwcHBCgsLu+o5AKAoEewAAABsgl2xAAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJv4/9crpp1GaMnQAAAAASUVORK5CYII=",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -2798,7 +3319,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "91a8eaef818d425a9f54f99efc05ce25",
+       "model_id": "01e19c50184b4789a71e2d2545e4b542",
        "version_major": 2,
        "version_minor": 0
       },
@@ -2920,7 +3441,7 @@
     {
      "data": {
       "text/markdown": [
-       "{'ref': 'SMV7', 'ref_ws_col': 'ref_ws_est_blend', 'distance_m': 314.4465998943834, 'bearing_deg': 173.69483366777283, 'ref_max_northing_error_v_reanalysis': np.float64(2.6590754551807976), 'ref_max_northing_error_v_wf': np.float64(2.842170943040401e-14), 'ref_max_ws_drift': np.float64(0.08697706942338845), 'ref_max_ws_drift_pp_period': np.float64(0.08697706942338845), 'ref_powercurve_shift': np.float64(0.003117456887993697), 'ref_rpm_shift': np.float64(0.0015313319638985412), 'ref_pitch_shift': np.float64(0.22323442242659364), 'ref_wind_speed_shift': np.float64(-0.0009576682888782218), 'detrend_pre_r2_improvement': np.float64(0.004942384513915488), 'detrend_post_r2_improvement': np.float64(0.0011487228730558963), 'mean_power_pre': np.float64(1149.2323289820358), 'mean_power_post': np.float64(1148.4157066585956), 'mean_test_yaw_offset_pre': np.float64(-0.022511156888877885), 'mean_test_yaw_offset_post': np.float64(3.8213264238880478), 'mean_test_yaw_offset_command_pre': np.float64(0.0002638323353293413), 'mean_test_yaw_offset_command_post': np.float64(6.636967675544794), 'mean_ref_yaw_offset_command_pre': np.float64(0.0), 'test_ref_warning_counts': 1, 'time_calculated': Timestamp('2024-10-09 11:22:51.699109+0000', tz='UTC'), 'uplift_frc': np.float64(-0.010361770845398625), 'unc_one_sigma_frc': np.float64(0.0057851151530948705), 't_value_one_sigma': np.float64(1.000630119597717), 'missing_bins_unc_scale_factor': 1, 'pp_valid_hours_pre': np.float64(132.5), 'pp_valid_hours_post': np.float64(136.0), 'pp_valid_hours': np.float64(268.5), 'pp_data_coverage': np.float64(0.11496467565831728), 'pp_invalid_bin_count': np.int64(16), 'uplift_noadj_frc': np.float64(-0.011505660672016103), 'unc_one_sigma_noadj_frc': np.float64(0.0057851151530948705), 'poweronly_uplift_frc': np.float64(-0.012003308408347353), 'reversed_uplift_frc': np.float64(-0.009715528755112396), 'reversal_error': np.float64(0.0022877796532349576), 'unc_one_sigma_lowerbound_frc': np.float64(0.0011438898266174788), 'unc_one_sigma_bootstrap_frc': np.float64(0.0049406532714673), 'uplift_p5_frc': np.float64(-0.000846103203498606), 'uplift_p95_frc': np.float64(-0.019877438487298643), 'wind_up_version': '0.1.9', 'test_wtg': 'SMV6', 'test_pw_col': 'test_pw_clipped', 'lt_wtg_hours_raw': 0, 'lt_wtg_hours_filt': 0, 'test_max_ws_drift': np.float64(0.03653354205095605), 'test_max_ws_drift_pp_period': np.float64(0.03653354205095605), 'test_powercurve_shift': np.float64(0.0010615707256107498), 'test_rpm_shift': np.float64(0.0011316163321652972), 'test_pitch_shift': np.float64(0.07625563544756919), 'test_wind_speed_shift': np.float64(-0.00621481122601375), 'preprocess_warning_counts': 0, 'test_warning_counts': 0}"
+       "{'ref': 'SMV7', 'ref_ws_col': 'ref_ws_est_blend', 'distance_m': 314.4465998943834, 'bearing_deg': 173.69483366777283, 'ref_max_northing_error_v_reanalysis': np.float64(2.6590754551807976), 'ref_max_northing_error_v_wf': np.float64(2.842170943040401e-14), 'ref_max_ws_drift': np.float64(0.08697706942338845), 'ref_max_ws_drift_pp_period': np.float64(0.08697706942338845), 'ref_powercurve_shift': np.float64(0.003117456887993697), 'ref_rpm_shift': np.float64(0.0015313319638985412), 'ref_pitch_shift': np.float64(0.22323442242659364), 'ref_wind_speed_shift': np.float64(-0.0009576682888782218), 'detrend_pre_r2_improvement': np.float64(0.004942384513915488), 'detrend_post_r2_improvement': np.float64(0.0011487228730558963), 'mean_power_pre': np.float64(1149.2323289820358), 'mean_power_post': np.float64(1148.4157066585956), 'mean_test_yaw_offset_pre': np.float64(-0.022511156888877885), 'mean_test_yaw_offset_post': np.float64(3.8213264238880478), 'mean_test_yaw_offset_command_pre': np.float64(0.0002638323353293413), 'mean_test_yaw_offset_command_post': np.float64(6.636967675544794), 'mean_ref_yaw_offset_command_pre': np.float64(0.0), 'test_ref_warning_counts': 1, 'time_calculated': Timestamp('2024-11-18 11:36:39.481470+0000', tz='UTC'), 'uplift_frc': np.float64(-0.010361770845398625), 'unc_one_sigma_frc': np.float64(0.0057851151530948705), 't_value_one_sigma': np.float64(1.000630119597717), 'missing_bins_unc_scale_factor': 1, 'pp_valid_hours_pre': np.float64(132.5), 'pp_valid_hours_post': np.float64(136.0), 'pp_valid_hours': np.float64(268.5), 'pp_data_coverage': np.float64(0.11496467565831728), 'pp_invalid_bin_count': np.int64(16), 'uplift_noadj_frc': np.float64(-0.011505660672016103), 'unc_one_sigma_noadj_frc': np.float64(0.0057851151530948705), 'poweronly_uplift_frc': np.float64(-0.012003308408347353), 'reversed_uplift_frc': np.float64(-0.009715528755112396), 'reversal_error': np.float64(0.0022877796532349576), 'unc_one_sigma_lowerbound_frc': np.float64(0.0011438898266174788), 'unc_one_sigma_bootstrap_frc': np.float64(0.0049406532714673), 'uplift_p5_frc': np.float64(-0.000846103203498606), 'uplift_p95_frc': np.float64(-0.019877438487298643), 'wind_up_version': '0.1.10', 'test_wtg': 'SMV6', 'test_pw_col': 'test_pw_clipped', 'lt_wtg_hours_raw': 0, 'lt_wtg_hours_filt': 0, 'test_max_ws_drift': np.float64(0.03653354205095605), 'test_max_ws_drift_pp_period': np.float64(0.03653354205095605), 'test_powercurve_shift': np.float64(0.0010615707256107498), 'test_rpm_shift': np.float64(0.0011316163321652972), 'test_pitch_shift': np.float64(0.07625563544756919), 'test_wind_speed_shift': np.float64(-0.00621481122601375), 'preprocess_warning_counts': 0, 'test_warning_counts': 0}"
       ],
       "text/plain": [
        "<IPython.core.display.Markdown object>"
@@ -3547,7 +4068,7 @@
     },
     {
      "data": {
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",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -3567,7 +4088,7 @@
     },
     {
      "data": {
-      "image/png": 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oo4/qjTfe0KpVq/Klrr/KzMxUzZo1NW7cuByfz/q9yY0bfY1zGiPpqtc8vJLMzExJ0muvvaY6derkOKZo0aLXFZgLg6+vrzp37qwvv/xSkydP1tGjR/Xjjz/q5Zdfdo7J6u2ZZ57JdnJSlstD1+U/G0nq37+/pk+froSEBDVp0kRBQUFyOBx66KGHnHNcj6zvmTlzZo5nq//1cky4dfBTh200aNBAknT48OErjnn44Yc1evRoxcTEXPGPTxZfX1/df//9+uijj3T06FH95z//ua7Lffzyyy+SLp3ZmRfu0M+VLu2SFxUrVpQxRtHR0c4tIfnNx8fHeTZqRESEWrRoIenSlrzU1FR9/PHHOnr0aI6Xfbn99tt1++2366WXXlJiYqK6d++uTz/9VH379r3mvJGRkZIubUG54447nMvT0tK0d+9e1a5d27msYsWKzusBXusuC9d7F4aCeI0jIyO1ZcsWGWNc6tmxY0e2uSUpMDDwihfQli69H/z9/Z1bm/7q8nXmJGueLVu2XHGerJ9HTuvbvn27goODXS4/8uCDD2rGjBlavHixtm3bJmOMHnzwQefzWVtdvb29r9rbtcyePVu9evXSG2+84Vx24cIFnTp1Klv9u3fvzvb9ly/Lei1CQkJuqC7YC7ticdNJSkrKcYvCd999J+nqu3P69u2r4cOHu3ywXk337t2Vlpamv//97/r9999zDDi///57tmVnzpzRhAkTFBwcrPr16191Dnfr568SExMVERHhcimNvOratas8PT01cuTIbP0aY3T8+PEbnkO6FOJWr16tpKQkZ7ALDg5WTEyMxo4d6xyT5eTJk9nqyQrJud261KBBA5UuXVpTp07VxYsXncs//PDDbH+0H3jgAf3666+aNm1atvX8+eefzl2EkhQQEJDt+6+mIF7ju+66S7/99ptmz57tXHb+/PlsdwOpX7++KlasqNdff11nz57Ntp6s94mnp6fi4uI0Z84cHThwwPn8tm3bNH/+/GvWU69ePUVHR2vChAnZXpusnsPCwlSnTh3NmDHDZcyWLVu0YMEC3XXXXS7f16ZNG5UsWVKzZs3SrFmz1KhRI5ddqSEhIWrVqpXeeeedHP+hldNnQE48PT2z/VwmTpyojIwMl2VxcXFauXKlNmzY4Fx24sSJbHd9iYuLU2BgoF5++eUcL2WU27pgL2yxw02nf//+On/+vLp06aJq1arp4sWLWrFihWbNmqWoqCj16dPnit8bGRmZq2uiZYmNjVX58uU1d+5c+fv7q2vXrtnGTJo0SXPmzFHHjh0VERGhw4cP64MPPtCBAwc0c+ZM+fj43FT9ZNmyZYs2bdqkIUOG5Mv9OytWrKjRo0dr6NCh2rdvnzp37qxixYpp7969+vLLL/XEE0/omWeeueF5WrRooZdeekkHDx50CXAtW7bUO++8o6ioKOd1xSRpxowZmjx5srp06aKKFSvqzJkzmjZtmgIDA7MFgCvx9vbW6NGj9fe//1133HGHHnzwQe3du1fTp0/Pdoxdjx499Nlnn+nJJ59UUlKSmjVrpoyMDG3fvl2fffaZ5s+f79xaW79+fS1atEjjxo1T2bJlFR0dfdXrDRbEa/z444/r7bffVs+ePbVu3TqFhYVp5syZKlKkiMs4Dw8Pvffee+rQoYNq1KihPn36qFy5cvr111+VlJSkwMBAff3115KkkSNHat68eWrRooWeeuoppaena+LEiapRo4Y2bdp01Xo8PDw0ZcoUdezYUXXq1FGfPn0UFham7du367///a8zHL722mvq0KGDmjRposcee0x//vmnJk6cqKCgoGzvGW9vb3Xt2lWffvqpzp07p9dffz3bvJMmTVLz5s1Vs2ZNPf7446pQoYKOHj2qlStX6tChQ9q4ceM1X8t77rlHM2fOVFBQkKpXr66VK1dq0aJFKlWqlMu45557Tv/+97/Vtm1b9e/fXwEBAXrvvfcUERGhEydOON+PgYGBmjJlinr06KF69erpoYceUunSpXXgwAF9++23atasmd5+++1r1gWbKeyzNYAb9f3335tHH33UVKtWzRQtWtT4+PiYSpUqmf79+5ujR4+6jP3rWaRXcqWzSLM8++yzRtIVL/exYMEC07ZtWxMaGmq8vb1N8eLFTbt27czixYtvyn6yZF0KZdOmTbnqI8u1zmj9/PPPTfPmzU1AQIAJCAgw1apVM/369XO55Epez4o1xpiUlBTj6elpihUr5nK5iX//+99GkunRo4fL+PXr15uHH37YREREGF9fXxMSEmLuuece89NPP1333JMnTzbR0dHG19fXNGjQwCxdutTExsa6nBVrzKUzIseOHWtq1KhhfH19TYkSJUz9+vXNyJEjndfbM8aY7du3m5YtWxp/f38jyXmGbH68xrGxsS7XacvSq1cvExkZ6bJs//795t577zVFihQxwcHBZuDAgWbevHnZrmNnjDE///yz6dq1qylVqpTx9fU1kZGR5oEHHsj2fliyZImpX7++8fHxMRUqVDBTp0519pUby5cvN23btjXFihUzAQEBplatWmbixIkuYxYtWmSaNWtm/P39TWBgoOnYsaPZunVrjutbuHChkWQcDoc5ePBgjmP27Nljevbs6XyvlytXztxzzz1m9uzZzjFXe/+dPHnS9OnTxwQHB5uiRYuauLg4s337dhMZGZnt7Oeff/7ZtGjRwvj6+pry5cubMWPGmLfeestIMkeOHHEZm5SUZOLi4kxQUJDx8/MzFStWNL17987T7zBufg5j8nCULAAAKFQJCQl65513dPbs2Sue+AJwjB0AAG7mzz//dHl8/PhxzZw5U82bNyfU4ao4xg6A2zt79myOB+T/VenSpQvkD96JEydcToi4nKenZ57PfAaupEmTJmrVqpViYmJ09OhRvf/++0pJSdGwYcOsLg1ujmAHwO29/vrrGjly5FXH7N27V1FRUfk+d9euXXO8SXyWyMjIHG/iDtyIu+66S7Nnz9a7774rh8OhevXq6f3338/xUj3AX3GMHQC398svvzivC3glzZs3l5+fX77PvW7dOpc7MVzO399fzZo1y/d5ASAvCHYAAAA2wckTAAAANmH7Y+wyMzP122+/qVixYvlykVUAAIDCZIzRmTNnVLZsWXl4XH2bnO2D3W+//XZdN9UGAABwRwcPHnS5c05ObB/sihUrJunSixEYGFggc6SlpWnBggVq166dvL29C2QOd0b/9E//9E//9E//Bdd/SkqKwsPDnZnmamwf7P56T72CDHZFihRRYGDgLfuLTf/0T//0T//0f6sp7P5zc0gZJ08AAADYBMEOAADAJgh2AAAANmH7Y+wAAEDhysjIUFpamtVlFLi0tDR5eXnpwoULysjIyPN6vL298+1e1wQ7AACQL4wxOnLkiE6dOmV1KYXCGKPQ0FAdPHjwhq+VW7x4cYWGht7wegh2AAAgX2SFupCQEBUpUsT2NwbIzMzU2bNnVbRo0WteOPhKjDE6f/68jh07JkkKCwu7oZoIdgAA4IZlZGQ4Q12pUqWsLqdQZGZm6uLFi/Lz88tzsJMkf39/SdKxY8cUEhJyQ7tlOXkCAADcsKxj6ooUKWJxJTenrNftRo9NJNgBAIB8Y/fdrwUlv143gh0AAIBNEOwAAABsgpMnAABAgYoa8m2hzbXvlbsLbS53xBY7AACA63Dx4kWrS7gigh0AALiltWrVSvHx8YqPj1dQUJCCg4M1bNgwGWMkSVFRURo1apR69uypwMBAPfHEE5Kk5cuXq0OHDgoICFB4eLgGDBigc+fOWdkKwQ4AAGDGjBny8vLSmjVr9Oabb2rcuHF67733nM+//vrrql27tn7++WcNGzZMe/bs0V133aV7771XGzZs0KxZs7R8+XLFx8db2AXH2AEAACg8PFzjx4+Xw+FQ1apVtXnzZo0fP16PP/64JOmOO+7Q008/7Rzft29fdevWTf/4xz8UGBioqlWr6q233lJsbKymTJkiPz8/S/og2AG46RXmgdmX8/U0erWRZdMDyCe33367y7XkmjRpojfeeEMZGRmSpAYNGriM37hxozZt2qTExETnMmOMMjMztXfvXsXExBRO4Zch2AEAAFxDQECAy+OzZ8/qiSeeUJ8+fbLdKzYiIqKwy3Mi2AEAgFve6tWrXR6vWrVKlStXvuJ9W+vVq6dt27apQoUKCgwMvKF7xeYn96gCAADAQgcOHNDgwYO1Y8cOffLJJ5o4caIGDhx4xfHPP/+8VqxYoWeffVYbNmzQrl27NHfuXE6eAAAAsFrPnj31559/qlGjRvL09NTAgQOdlzXJSa1atZSUlKShQ4cqNjZWxhhVrFhRDz74YCFWnR3BDgAAFKib4W4Q3t7emjBhgqZMmZLtuX379uX4PQ0bNtQXX3zBrlgAAADkP4IdAACATbArFsBNL8FrtmVzOzy8JN1j2fwAblxycrLVJeQbttgBAADYBMEOAADAJgh2AAAANkGwAwAAsAlOngCQP5aNkxyZVlcBALc0ttgBAADYBMEOAADAJtgVCwAAClbSmMKbq/XQwpsrF5KTk9W6dWudPHlSxYsXL/D52GIHAABgEwQ7AABwS2vVqpXi4+MVHx+voKAgBQcHa9iwYTLGSJJOnjypnj17qkSJEipSpIg6dOigXbt2Ob9///796tixo0qUKKGAgADVqFFD3333nfbt26fWrVtLkkqUKCGHw6HevXsXaC8EOwAAcMubMWOGvLy8tGbNGr355psaN26c3nvvPUlS79699dNPP+mrr77SypUrZYzRXXfdpbS0NElSfHy8UlNTtXTpUm3evFljx45V0aJFFR4ers8//1yStGPHDh0+fFhvvvlmgfbBMXYAAOCWFx4ervHjx8vhcKhq1aravHmzxo8fr1atWumrr77Sjz/+qKZNm0qSPv74Y4WHh2vOnDmKi4vTwYMHdd9996lmzZqSpAoVKjjXW7JkSUlSSEgIx9gBAAAUhttvv10Oh8P5uEmTJtq1a5e2bt0qLy8vNW7c2PlcqVKlVLVqVW3fvl3SpS12o0ePVrNmzTR8+HBt2rSp0OvPQrADAAC4AX379tUvv/yiHj16aPPmzWrQoIEmTpxoSS0EOwAAcMtbvXq1y+NVq1apcuXKql69utLT012eP378uHbs2KGYmBjnsvDwcD355JP64osv9PTTT2vatGmSJB8fH0lSRkZGIXRBsAMAANCBAwc0ePBg7dixQ5988okmTpyogQMHqnLlyurUqZMef/xxLV++XBs3btQjjzyicuXKqVOnTpKkQYMGaf78+dq7d6/Wr1+vpKQkZ+iLjIyUw+HQN998o99//11nz54t0D4IdgAA4JbXs2dP/fnnn2rUqJH69eungQMH6oknnpAkTZ8+XfXr19c999yjJk2ayBij7777Tt7e3pIubY3r16+fYmJi1L59e1WpUkWTJ0+WJJUrV04jR47UkCFDVKZMGcXHxxdoH5wVCwAACpab3Q0iJ97e3powYYKmTJmS7bkSJUroo48+yrY8MzNTkvTWW2/Jw+PK28qGDRumYcOG5V+xV8EWOwAAAJuwNNiNGTNGDRs2VLFixRQSEqLOnTtrx44dLmMuXLigfv36qVSpUipatKjuu+8+HT161KKKAQAA3JelwW7JkiXq16+fVq1apYULFyotLU3t2rXTuXPnnGMGDRqkr7/+Wv/5z3+0ZMkS/fbbb+ratauFVQMAADtJTk7WhAkTrC4jX1h6jN28efNcHn/44YcKCQnRunXr1LJlS50+fVrvv/++EhMTdccdd0i6dABjTEyMVq1apdtvv92KsgEAANySWx1jd/r0aUn/u/3GunXrlJaWpjZt2jjHVKtWTREREVq5cqUlNQIAALgrtzkrNjMzUwkJCWrWrJluu+02SdKRI0fk4+OT7d5qZcqU0ZEjR3JcT2pqqlJTU52PU1JSJElpaWnOm/Xmt6z1FtT63R39078kpRnr/p3o8LDuoyxr7lv+50//Fldijb/2n5mZKWOM0tPTnWeL2p0xxvnfG+05PT3d+fpd/vt0Pb9fDpNVlcX+8Y9/6Pvvv9fy5ctVvnx5SVJiYqL69OnjEtQkqVGjRmrdurXGjh2bbT0jRozQyJEjsy1PTExUkSJFCqZ4AACgMmXKqGjRoipZsqS8vNxm25HbS09P14kTJ3T27NkcTxA9f/68unXrptOnTyswMPCq63KLVz0+Pl7ffPONli5d6gx1khQaGqqLFy/q1KlTLlvtjh49qtDQ0BzXNXToUA0ePNj5OCUlReHh4WrXrt01X4y8SktL08KFC9W2bVvnxQpvJfRP/wsXLlTbojvl7bDmX+mTk3dbMq90aYtdZN32/Pzpn/69vZWWlqajR4/q1KlTVpdWKIwxunDhgvz8/ORwOG5oXQEBAapQoUKOv0dZex9zw9JgZ4xR//799eWXXyo5OVnR0dEuz9evX1/e3t5avHix7rvvPknSjh07dODAATVp0iTHdfr6+srX1zfbcm9v7wJ/0xXGHO6M/m/x/h2ZlgU7k5luybx/dcv//Omf/v//V1RUlNLT0wvt3qhWSktL09KlS9WyZcsb+vl7enrKy8vriuHwetZtabDr16+fEhMTNXfuXBUrVsx53FxQUJD8/f0VFBSkxx57TIMHD1bJkiUVGBio/v37q0mTJpwRCwCAG3I4HLdM0PX09FR6err8/Pzcpl9Lg13WbTtatWrlsnz69Onq3bu3JGn8+PHy8PDQfffdp9TUVMXFxTnvvwYAAID/sXxX7LX4+flp0qRJmjRpUiFUBAAAcPNyq+vYAQAAIO8IdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ISlFygGkE+Sxlg3t/GQVE2Tk3e7xT1bAeBWxhY7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADbByRMAkA9uGzFfqRkOS+be98rdlswLwP2wxQ4AAMAmCHYAAAA2wa5YwAYmLN5p2dwODy9F1a9m2fwAgP9hix0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ISX1QUAgB085TlXxpFu0ex3WzQvAHfDFjsAAACbINgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJrysLgAAcIOSxlg3t/GQVM26+QG4YIsdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmLA12S5cuVceOHVW2bFk5HA7NmTPH5fnevXvL4XC4fLVv396aYgEAANycpcHu3Llzql27tiZNmnTFMe3bt9fhw4edX5988kkhVggAAHDz8LJy8g4dOqhDhw5XHePr66vQ0NBCqggAAODmZWmwy43k5GSFhISoRIkSuuOOOzR69GiVKlXqiuNTU1OVmprqfJySkiJJSktLU1paWoHUmLXeglq/u6N/6/t3eFj3Vs6a28oarOQO/acZ63a+ZM3N+5/+b0WF1f/1rN9hjDEFWEuuORwOffnll+rcubNz2aeffqoiRYooOjpae/bs0T//+U8VLVpUK1eulKenZ47rGTFihEaOHJlteWJioooUKVJQ5QMAABSI8+fPq1u3bjp9+rQCAwOvOtatg93lfvnlF1WsWFGLFi3SnXfemeOYnLbYhYeH648//rjmi5FXaWlpWrhwodq2bStvb+8CmcOd0b/1/U8e9ZQl80qXtlRF1m2v/T/Pk8lMt6wOq7hD/0+1qmTJvNKlLXYLz1bh/U//9F+A/aekpCg4ODhXwe6m2ndSoUIFBQcHa/fu3VcMdr6+vvL19c223Nvbu8B/6QpjDndG/9b17w6BymSmu0UdVrGyf29HpiXzutTA+5/+6b9A159bN9V17A4dOqTjx48rLCzM6lIAAADcjqVb7M6ePavdu3c7H+/du1cbNmxQyZIlVbJkSY0cOVL33XefQkNDtWfPHj333HOqVKmS4uLiLKwaAADAPVka7H766Se1bt3a+Xjw4MGSpF69emnKlCnatGmTZsyYoVOnTqls2bJq166dRo0aleOuVgAAgFudpcGuVatWutq5G/Pnzy/EagAAAG5uN9UxdgAAALgygh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCZuqnvFAgCym7B4p2VzOzy8FFW/mmXzA3DFFjsAAACbINgBAADYBMEOAADAJgh2AAAANsHJEwCAG7dsnOTItGbu1kOtmRdwQ2yxAwAAsAmCHQAAgE2wKxYAcMMmJ++WyUy3ZO6E1pZMC7glttgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJrilGADgphY15FvL5vb1NHq1kWXTA9mwxQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJvIl2CXkZGhDRs26OTJk/mxOgAAAORBnoJdQkKC3n//fUmXQl1sbKzq1aun8PBwJScn52d9AAAAyKU8BbvZs2erdu3akqSvv/5ae/fu1fbt2zVo0CD961//ytcCAQAAkDt5CnZ//PGHQkNDJUnfffed/va3v6lKlSp69NFHtXnz5nwtEAAAALmTp2BXpkwZbd26VRkZGZo3b57atm0rSTp//rw8PT3ztUAAAADkjldevqlPnz564IEHFBYWJofDoTZt2kiSVq9erWrVquVrgQAAAMidPAW7ESNGqGbNmjpw4ID+9re/ydfXV5Lk6empIUOG5GuBAAAAyJ3rDnZpaWlq3769pk6dqvvuu8/luV69euVbYQAAALg+132Mnbe3tzZt2lQQtQAAAOAG5OnkiUceecR5HTsAAAC4hzwdY5eenq4PPvhAixYtUv369RUQEODy/Lhx4/KlOAAAAORenoLdli1bVK9ePUnSzp07XZ5zOBw3XhUAAACuW56CXVJSUn7XAQAAgBuUp2PsAAAA4H7ytMWudevWV93l+sMPP+S5IAAAAORNnoJdnTp1XB6npaVpw4YN2rJlC9eyAwAAsEiegt348eNzXD5ixAidPXv2hgoCAABA3uTrMXaPPPKIPvjgg/xcJQAAAHIpX4PdypUr5efnl5+rBAAAQC7laVds165dXR4bY3T48GH99NNPGjZsWL4UBgAAgOuTp2AXFBTk8tjDw0NVq1bViy++qHbt2uVLYQAAALg+eQp206dPz+86AAAAcIPyFOyyrFu3Ttu2bZMk1ahRQ3Xr1s2XogAAAHD98hTsjh07poceekjJyckqXry4JOnUqVNq3bq1Pv30U5UuXTo/awQAAEAu5Oms2P79++vMmTP673//qxMnTujEiRPasmWLUlJSNGDAgPyuEQAAALmQpy128+bN06JFixQTE+NcVr16dU2aNImTJwAAACySpy12mZmZ8vb2zrbc29tbmZmZN1wUAAAArl+egt0dd9yhgQMH6rfffnMu+/XXXzVo0CDdeeed+VYcAAAAci9Pwe7tt99WSkqKoqKiVLFiRVWsWFFRUVFKSUnRxIkT87tGAAAA5EKejrELDw/X+vXrtXjxYuflTmJiYtSmTZt8LQ4AAAC5l+fr2P3www/64YcfdOzYMWVmZurnn39WYmKiJOmDDz7ItwIBAACQO3kKdiNHjtSLL76oBg0aKCwsTA6HI7/rAgAAwHXKU7CbOnWqPvzwQ/Xo0SO/6wEAAEAe5enkiYsXL6pp06b5XQsAAABuQJ6CXd++fZ3H0wEAAMA95HpX7ODBg53/n5mZqXfffVeLFi1SrVq1sl2seNy4cflXIQAAAHIl18Hu559/dnlcp04dSdKWLVtclnMiBQAAgDVyHeySkpIKsg4AAADcoDwdY5dfli5dqo4dO6ps2bJyOByaM2eOy/PGGL3wwgsKCwuTv7+/2rRpo127dllTLAAAgJuzNNidO3dOtWvX1qRJk3J8/tVXX9Vbb72lqVOnavXq1QoICFBcXJwuXLhQyJUCAAC4vzzfeSI/dOjQQR06dMjxOWOMJkyYoP/7v/9Tp06dJEkfffSRypQpozlz5uihhx4qzFIBAADcnqXB7mr27t2rI0eOuNx/NigoSI0bN9bKlSuvGOxSU1OVmprqfJySkiJJSktLU1paWoHUmrXeglq/u6N/6/t3eFj3Vs6a28oarET/1vfv62msm9vj0tx8/tF/YcyTGw5jjHXviL9wOBz68ssv1blzZ0nSihUr1KxZM/32228KCwtzjnvggQfkcDg0a9asHNczYsQIjRw5MtvyxMREFSlSpEBqBwAAKCjnz59Xt27ddPr0aQUGBl51rO3+iTl06FCXa+6lpKQoPDxc7dq1u+aLkVdpaWlauHCh2rZtm+2afrcC+re+/8mjnrJkXunSlprIuu21/+d5MpnpltVhFfq3vv/JGZ0smVe6tMVuVINMPv/ov0D7z9r7mBtuG+xCQ0MlSUePHnXZYnf06FHnNfRy4uvrK19f32zLvb29C/yXrjDmcGf0b13/7hAoTGa6W9RhFfq3rv/UDOuvn8rnH/0XZP/Xs25Lz4q9mujoaIWGhmrx4sXOZSkpKVq9erWaNGliYWUAAADuydItdmfPntXu3budj/fu3asNGzaoZMmSioiIUEJCgkaPHq3KlSsrOjpaw4YNU9myZZ3H4QEAAOB/LA12P/30k1q3bu18nHVsXK9evfThhx/queee07lz5/TEE0/o1KlTat68uebNmyc/Pz+rSgYAAHBblga7Vq1a6Won5TocDr344ot68cUXC7EqAACAm5PbHmMHAACA60OwAwAAsAmCHQAAgE0Q7AAAAGzCbS9QDABAbiR4zbZs7kv3yL3HsvmBy7HFDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgrNiAQC4UcvGSY5Ma+ZuPdSaeeGW2GIHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ISX1QUAAHCzm5y8WyYz3ZK5E1pbMi3cFFvsAAAAbIJgBwAAYBPsigXyyW0j5is1w2HJ3Am8kwEAYosdAACAbRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAmCHYAAAA2QbADAACwCYIdAACATRDsAAAAbIJgBwAAYBMEOwAAAJsg2AEAANgEwQ4AAMAm3DrYjRgxQg6Hw+WrWrVqVpcFAADglrysLuBaatSooUWLFjkfe3m5fckAAACWcPuU5OXlpdDQUKvLAADAPSWNsW5u4yGJPWnuxO2D3a5du1S2bFn5+fmpSZMmGjNmjCIiIq44PjU1Vampqc7HKSkpkqS0tDSlpaUVSI1Z6y2o9bs7+r/Ut6+HsawGh4d1b+Wsua2swUr0T/9//a8V0ox1R1VlzX2rf/4XdP/Xs36HMca6v0bX8P333+vs2bOqWrWqDh8+rJEjR+rXX3/Vli1bVKxYsRy/Z8SIERo5cmS25YmJiSpSpEhBlwwAAJCvzp8/r27duun06dMKDAy86li3DnaXO3XqlCIjIzVu3Dg99thjOY7JaYtdeHi4/vjjj2u+GHmVlpamhQsXqm3btvL29i6QOdwZ/V/qf9hPHkrNdFhSw1Oecy2ZV7q0pSKybnvt/3meTGa6ZXVYhf7p3+r+n2pVyZJ5pUtb7BaerXLLf/4XdP8pKSkKDg7OVbC7qbadFy9eXFWqVNHu3buvOMbX11e+vr7Zlnt7exf4L11hzOHObvX+UzMdSs2wJtgZh/V/UE1m+i35hz0L/dO/Vf17OzItmdelhlv887+g+7+edbv15U4ud/bsWe3Zs0dhYWFWlwIAAOB23DrYPfPMM1qyZIn27dunFStWqEuXLvL09NTDDz9sdWkAAABux613xR46dEgPP/ywjh8/rtKlS6t58+ZatWqVSpcubXVpAAAAbsetg92nn35qdQkAAAA3DbfeFQsAAIDcI9gBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYhFvfUgy4mTzlOVfGkW51GQCAWxhb7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATXlYXAAAA8m7C4p2Wze3w8FJU/WqWzY/s2GIHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABswsvqAgAAwM3tthHzlZrhsGTufa/cbcm87ootdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgEwQ7AAAAmyDYAQAA2ATBDgAAwCYIdgAAADZBsAMAALAJgh0AAIBNEOwAAABsgmAHAABgE15WFwDkh6gh31o2t6+n0auNLJseAAAnttgBAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOAADAJrilGGwhwWu2ZXM7PLwk3WPZ/ABwK+OWkq5uii12kyZNUlRUlPz8/NS4cWOtWbPG6pIAAADcjtsHu1mzZmnw4MEaPny41q9fr9q1aysuLk7Hjh2zujQAAAC34va7YseNG6fHH39cffr0kSRNnTpV3377rT744AMNGTLE4uoAAMBTnnNlHOmWzD0h/X5L5nVXbr3F7uLFi1q3bp3atGnjXObh4aE2bdpo5cqVFlYGAADgftx6i90ff/yhjIwMlSlTxmV5mTJltH379hy/JzU1Vampqc7Hp0+fliSdOHFCaWlpBVJnWlqazp8/r+PHj8vb27tA5nBn7tB/alqmJfNKksMjU+fPn1dqWqZMpnV1WIX+6Z/+6d/K/r0yzlkyryR5ZRqdP59Z4H//zpw5I0kyxly7pgKrwiJjxozRyJEjsy2Pjo62oBrcOj6wugCL0f+tjf5vbVb3/5Gls3crxLnOnDmjoKCgq45x62AXHBwsT09PHT161GX50aNHFRoamuP3DB06VIMHD3Y+zszM1IkTJ1SqVCk5HI4CqTMlJUXh4eE6ePCgAgMDC2QOd0b/9E//9E//9E//Bde/MUZnzpxR2bJlrznWrYOdj4+P6tevr8WLF6tz586SLgW1xYsXKz4+Psfv8fX1la+vr8uy4sWLF3CllwQGBt6Sv9hZ6J/+6Z/+b1X0T/8F3f+1ttRlcetgJ0mDBw9Wr1691KBBAzVq1EgTJkzQuXPnnGfJAgAA4BK3D3YPPvigfv/9d73wwgs6cuSI6tSpo3nz5mU7oQIAAOBW5/bBTpLi4+OvuOvVHfj6+mr48OHZdgHfKuif/umf/umf/m9F7ti/w+Tm3FkAAAC4Pbe+QDEAAAByj2AHAABgEwQ7AAAAmyDY5YNJkyYpKipKfn5+aty4sdasWWN1SYVizJgxatiwoYoVK6aQkBB17txZO3bssLosy7zyyityOBxKSEiwupRC8+uvv+qRRx5RqVKl5O/vr5o1a+qnn36yuqxCkZGRoWHDhik6Olr+/v6qWLGiRo0alatb/tyMli5dqo4dO6ps2bJyOByaM2eOy/PGGL3wwgsKCwuTv7+/2rRpo127dllTbAG4Wv9paWl6/vnnVbNmTQUEBKhs2bLq2bOnfvvtN+sKzmfX+vn/1ZNPPimHw6EJEyYUWn0FLTf9b9u2Tffee6+CgoIUEBCghg0b6sCBA4VeK8HuBs2aNUuDBw/W8OHDtX79etWuXVtxcXE6duyY1aUVuCVLlqhfv35atWqVFi5cqLS0NLVr107nzll33z6rrF27Vu+8845q1apldSmF5uTJk2rWrJm8vb31/fffa+vWrXrjjTdUokQJq0srFGPHjtWUKVP09ttva9u2bRo7dqxeffVVTZw40erSCsS5c+dUu3ZtTZo0KcfnX331Vb311luaOnWqVq9erYCAAMXFxenChQuFXGnBuFr/58+f1/r16zVs2DCtX79eX3zxhXbs2KF7773XgkoLxrV+/lm+/PJLrVq1Kld3SLiZXKv/PXv2qHnz5qpWrZqSk5O1adMmDRs2TH5+foVcqSSDG9KoUSPTr18/5+OMjAxTtmxZM2bMGAurssaxY8eMJLNkyRKrSylUZ86cMZUrVzYLFy40sbGxZuDAgVaXVCief/5507x5c6vLsMzdd99tHn30UZdlXbt2Nd27d7eoosIjyXz55ZfOx5mZmSY0NNS89tprzmWnTp0yvr6+5pNPPrGgwoJ1ef85WbNmjZFk9u/fXzhFFaIr9X/o0CFTrlw5s2XLFhMZGWnGjx9f6LUVhpz6f/DBB80jjzxiTUGXYYvdDbh48aLWrVunNm3aOJd5eHioTZs2WrlypYWVWeP06dOSpJIlS1pcSeHq16+f7r77bpffg1vBV199pQYNGuhvf/ubQkJCVLduXU2bNs3qsgpN06ZNtXjxYu3cuVOStHHjRi1fvlwdOnSwuLLCt3fvXh05csTlPRAUFKTGjRvfkp+F0qXPQ4fDUWi3tLRaZmamevTooWeffVY1atSwupxClZmZqW+//VZVqlRRXFycQkJC1Lhx46vuri5IBLsb8McffygjIyPbXTDKlCmjI0eOWFSVNTIzM5WQkKBmzZrptttus7qcQvPpp59q/fr1GjNmjNWlFLpffvlFU6ZMUeXKlTV//nz94x//0IABAzRjxgyrSysUQ4YM0UMPPaRq1arJ29tbdevWVUJCgrp37251aYUu6/OOz8JLLly4oOeff14PP/zwLXP/1LFjx8rLy0sDBgywupRCd+zYMZ09e1avvPKK2rdvrwULFqhLly7q2rWrlixZUuj13BR3noD769evn7Zs2aLly5dbXUqhOXjwoAYOHKiFCxdacxyFxTIzM9WgQQO9/PLLkqS6detqy5Ytmjp1qnr16mVxdQXvs88+08cff6zExETVqFFDGzZsUEJCgsqWLXtL9I+cpaWl6YEHHpAxRlOmTLG6nEKxbt06vfnmm1q/fr0cDofV5RS6zMxMSVKnTp00aNAgSVKdOnW0YsUKTZ06VbGxsYVaD1vsbkBwcLA8PT119OhRl+VHjx5VaGioRVUVvvj4eH3zzTdKSkpS+fLlrS6n0Kxbt07Hjh1TvXr15OXlJS8vLy1ZskRvvfWWvLy8lJGRYXWJBSosLEzVq1d3WRYTE2PJWWBWePbZZ51b7WrWrKkePXpo0KBBt+TW26zPu1v9szAr1O3fv18LFy68ZbbWLVu2TMeOHVNERITzs3D//v16+umnFRUVZXV5BS44OFheXl5u83lIsLsBPj4+ql+/vhYvXuxclpmZqcWLF6tJkyYWVlY4jDGKj4/Xl19+qR9++EHR0dFWl1So7rzzTm3evFkbNmxwfjVo0EDdu3fXhg0b5OnpaXWJBapZs2bZLm+zc+dORUZGWlRR4Tp//rw8PFw/Qj09PZ3/er+VREdHKzQ01OWzMCUlRatXr74lPgul/4W6Xbt2adGiRSpVqpTVJRWaHj16aNOmTS6fhWXLltWzzz6r+fPnW11egfPx8VHDhg3d5vOQXbE3aPDgwerVq5caNGigRo0aacKECTp37pz69OljdWkFrl+/fkpMTNTcuXNVrFgx57E0QUFB8vf3t7i6glesWLFsxxMGBASoVKlSt8RxhoMGDVLTpk318ssv64EHHtCaNWv07rvv6t1337W6tELRsWNHvfTSS4qIiFCNGjX0888/a9y4cXr00UetLq1AnD17Vrt373Y+3rt3rzZs2KCSJUsqIiJCCQkJGj16tCpXrqzo6GgNGzZMZcuWVefOna0rOh9drf+wsDDdf//9Wr9+vb755htlZGQ4Pw9LliwpHx8fq8rON9f6+V8eZL29vRUaGqqqVasWdqkF4lr9P/vss3rwwQfVsmVLtW7dWvPmzdPXX3+t5OTkwi/W6tNy7WDixIkmIiLC+Pj4mEaNGplVq1ZZXVKhkJTj1/Tp060uzTK30uVOjDHm66+/Nrfddpvx9fU11apVM++++67VJRWalJQUM3DgQBMREWH8/PxMhQoVzL/+9S+TmppqdWkFIikpKcf3e69evYwxly55MmzYMFOmTBnj6+tr7rzzTrNjxw5ri85HV+t/7969V/w8TEpKsrr0fHGtn//l7Ha5k9z0//7775tKlSoZPz8/U7t2bTNnzhxLanUYY9PLpAMAANxiOMYOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACbINgBAADYBMEOgFswxuiJJ55QyZIl5XA4tGHDBqtLylFycrIcDodOnTpldSnXpXfv3jd8e6+btXfgVkKwA+AW5s2bpw8//FDffPONDh8+bKv77UZFRWnChAlWlwHgFuBldQEA7O/ixYvXvBH6nj17FBYWpqZNmxZSVe4lIyNDDodDHh78extA3vEJAiDftWrVSvHx8UpISFBwcLDi4uK0ZcsWdejQQUWLFlWZMmXUo0cP/fHHH5Iu7Sbs37+/Dhw4IIfDoaioqKuu/5tvvlHx4sWVkZEhSdqwYYMcDoeGDBniHNO3b1898sgjkqT9+/erY8eOKlGihAICAlSjRg199913uerlu+++U5UqVeTv76/WrVtr37592cYsX75cLVq0kL+/v8LDwzVgwACdO3fO+Vrs379fgwYNksPhkMPhkCR9+OGHKl68uL766itVr15dvr6+OnDggFJTU/XMM8+oXLlyCggIUOPGjZWcnOycK+v75s+fr5iYGBUtWlTt27fX4cOHnWMyMjI0ePBgFS9eXKVKldJzzz2ny28LnpmZqTFjxig6Olr+/v6qXbu2Zs+efd29A3AzBgDyWWxsrClatKh59tlnzfbt282qVatM6dKlzdChQ822bdvM+vXrTdu2bU3r1q2NMcacOnXKvPjii6Z8+fLm8OHD5tixY1dd/6lTp4yHh4dZu3atMcaYCRMmmODgYNO4cWPnmEqVKplp06YZY4y5++67Tdu2bc2mTZvMnj17zNdff22WLFlyzT4OHDhgfH19zeDBg8327dvNv//9b1OmTBkjyZw8edIYY8zu3btNQECAGT9+vNm5c6f58ccfTd26dU3v3r2NMcYcP37clC9f3rz44ovm8OHD5vDhw8YYY6ZPn268vb1N06ZNzY8//mi2b99uzp07Z/r27WuaNm1qli5danbv3m1ee+014+vra3bu3OnyfW3atDFr164169atMzExMaZbt27OuseOHWtKlChhPv/8c7N161bz2GOPmWLFiplOnTo5x4wePdpUq1bNzJs3z+zZs8dMnz7d+Pr6muTk5Fz3DsD9EOwA5LvY2FhTt25d5+NRo0aZdu3auYw5ePCgkWR27NhhjDFm/PjxJjIyMtdz1KtXz7z22mvGGGM6d+5sXnrpJePj42POnDljDh06ZCQ5w1DNmjXNiBEjrruPoUOHmurVq7sse/75513CzWOPPWaeeOIJlzHLli0zHh4e5s8//zTGGBMZGWnGjx/vMmb69OlGktmwYYNz2f79+42np6f59ddfXcbeeeedZujQoS7ft3v3bufzkyZNMmXKlHE+DgsLM6+++qrzcVpamilfvrwz2F24cMEUKVLErFixwmWexx57zDz88MO57h2A++EYOwAFon79+s7/37hxo5KSklS0aNFs4/bs2aMqVapc9/pjY2OVnJysp59+WsuWLdOYMWP02Wefafny5Tpx4oTKli2rypUrS5IGDBigf/zjH1qwYIHatGmj++67T7Vq1brmHNu2bVPjxo1dljVp0sTl8caNG7Vp0yZ9/PHHzmXGGGVmZmrv3r2KiYm54vp9fHxc6ti8ebMyMjKyvR6pqakqVaqU83GRIkVUsWJF5+OwsDAdO3ZMknT69GkdPnzYpW4vLy81aNDAuTt29+7dOn/+vNq2besyz8WLF1W3bt1c9w7A/RDsABSIgIAA5/+fPXtWHTt21NixY7ONCwsLy9P6W7VqpQ8++EAbN26Ut7e3qlWrplatWik5OVknT55UbGysc2zfvn0VFxenb7/9VgsWLNCYMWP0xhtvqH///nma+6/Onj2rv//97xowYEC25yIiIq76vf7+/s5j7rLW5enpqXXr1snT09Nl7F9Dsbe3t8tzDocj2zF016pZkr799luVK1fO5TlfX99crweA+yHYAShw9erV0+eff66oqCh5eeXPx06LFi105swZjR8/3hniWrVqpVdeeUUnT57U008/7TI+PDxcTz75pJ588kkNHTpU06ZNu2awi4mJ0VdffeWybNWqVS6P69Wrp61bt6pSpUpXXI+Pj4/zRI+rqVu3rjIyMnTs2DG1aNHimuNzEhQUpLCwMK1evVotW7aUJKWnp2vdunWqV6+eJLmcrPHXAPxXuekdgPvhrFgABa5fv346ceKEHn74Ya1du1Z79uzR/Pnz1adPn1wFnpyUKFFCtWrV0scff6xWrVpJklq2bKn169dr586dLoElISFB8+fP1969e7V+/XolJSVddRdplieffFK7du3Ss88+qx07digxMVEffvihy5jnn39eK1asUHx8vDZs2KBdu3Zp7ty5io+Pd46JiorS0qVL9euvvzrPBM5JlSpV1L17d/Xs2VNffPGF9u7dqzVr1mjMmDH69ttvc/3aDBw4UK+88ormzJmj7du366mnnnK5qHCxYsX0zDPPaNCgQZoxY4b27Nmj9evXa+LEiZoxY0auewfgfgh2AApc2bJl9eOPPyojI0Pt2rVTzZo1lZCQoOLFi9/QddtiY2OVkZHhDHYlS5ZU9erVFRoaqqpVqzrHZWRkqF+/foqJiVH79u1VpUoVTZ48+Zrrj4iI0Oeff645c+aodu3amjp1ql5++WWXMbVq1dKSJUu0c+dOtWjRQnXr1tULL7ygsmXLOse8+OKL2rdvnypWrKjSpUtfdc7p06erZ8+eevrpp1W1alV17txZa9euveZu3b96+umn1aNHD/Xq1UtNmjRRsWLF1KVLF5cxo0aN0rBhwzRmzBjn6/Ltt98qOjo6170DcD8Ocz0HZgAAAMBtscUOAADAJgh2ANzOgQMHVLRo0St+HThwIF/mefLJJ684x5NPPpkvcwBAYWJXLAC3k56eftXbV+XX2bXHjh1TSkpKjs8FBgYqJCTkhucAgMJEsAMAALAJdsUCAADYBMEOAADAJgh2AAAANkGwAwAAsAmCHQAAgE0Q7AAAAGyCYAcAAGATBDsAAACb+H+ajH6nc455LwAAAABJRU5ErkJggg==",
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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -3772,7 +4293,7 @@
     {
      "data": {
       "application/vnd.jupyter.widget-view+json": {
-       "model_id": "7bab1e694a3046049de16c0e9ce51eda",
+       "model_id": "13d6607e187641129ccaeb32f035d25c",
        "version_major": 2,
        "version_minor": 0
       },
@@ -3894,7 +4415,7 @@
     {
      "data": {
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diff --git a/pyproject.toml b/pyproject.toml
index 513e721..7fdd6cc 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -68,7 +68,7 @@ all = ["res-wind-up[dev,examples]"]
 
 [tool.setuptools.packages.find]
 where = ["."]
-include = ["wind_up*"]
+include = ["wind_up*", "examples"]
 
 [tool.ruff]
 line-length = 120
@@ -161,6 +161,10 @@ sequence = [
     { cmd = "coverage report -m" },
 ]
 
+[tool.poe.tasks.smarteole-nb]
+help = "Runs Smarteole notebook"
+shell = "jupyter nbconvert --execute --to notebook --inplace examples/smarteole_example.ipynb"
+
 [tool.poe.tasks.all]
 help = "Run all required pre-push commands"
-sequence = [{ ref = "lint" }, { ref = "test" }]
+sequence = [{ ref = "lint" }, { ref = "test" }, { ref = "smarteole-nb" }]
diff --git a/wind_up/ops_curve_shift.py b/wind_up/ops_curve_shift.py
index d04b3e0..5c7dd32 100644
--- a/wind_up/ops_curve_shift.py
+++ b/wind_up/ops_curve_shift.py
@@ -208,7 +208,7 @@ def _calculate_curve_shift(curve_shift_input: CurveShiftInput) -> float:
     post_df = curve_shift_input.post_df
     wtg_name = curve_shift_input.turbine_name
 
-    bins = np.arange(0, pre_df[conf.x_col].max() + conf.x_bin_width, conf.x_bin_width) if conf.x_bin_width > 0 else 10  # type: ignore[operator]
+    bins = np.arange(0, pre_df[conf.x_col].max() + conf.x_bin_width, conf.x_bin_width) if conf.x_bin_width > 0 else 10  # type: ignore[operator,var-annotated]
 
     mean_curve = pre_df.groupby(pd.cut(pre_df[conf.x_col], bins=bins, retbins=False), observed=True).agg(
         x_mean=pd.NamedAgg(column=conf.x_col, aggfunc="mean"),