diff --git "a/notebook.ipynb" "b/notebook.ipynb"
--- "a/notebook.ipynb"
+++ "b/notebook.ipynb"
@@ -21,8 +21,15 @@
},
{
"cell_type": "code",
- "execution_count": 11,
- "metadata": {},
+ "execution_count": 1,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2025-02-28T13:48:41.076303Z",
+ "iopub.status.busy": "2025-02-28T13:48:41.075959Z",
+ "iopub.status.idle": "2025-02-28T13:48:43.022704Z",
+ "shell.execute_reply": "2025-02-28T13:48:43.022206Z"
+ }
+ },
"outputs": [
{
"name": "stdout",
@@ -34,7 +41,7 @@
],
"source": [
"# Installing the dependencies within the notebook to make it easier to run on colab\n",
- "%pip install -Uqq fastai ipywidgets"
+ "%pip install -Uqq fastai ipywidgets plotly"
]
},
{
@@ -53,8 +60,15 @@
},
{
"cell_type": "code",
- "execution_count": 12,
- "metadata": {},
+ "execution_count": 2,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2025-02-28T13:48:43.046898Z",
+ "iopub.status.busy": "2025-02-28T13:48:43.046687Z",
+ "iopub.status.idle": "2025-02-28T13:48:44.806003Z",
+ "shell.execute_reply": "2025-02-28T13:48:44.805644Z"
+ }
+ },
"outputs": [],
"source": [
"from fastai.basics import torch, plt\n",
@@ -76,8 +90,15 @@
},
{
"cell_type": "code",
- "execution_count": 13,
- "metadata": {},
+ "execution_count": 3,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2025-02-28T13:48:44.807734Z",
+ "iopub.status.busy": "2025-02-28T13:48:44.807583Z",
+ "iopub.status.idle": "2025-02-28T13:48:44.932485Z",
+ "shell.execute_reply": "2025-02-28T13:48:44.932167Z"
+ }
+ },
"outputs": [
{
"data": {
@@ -118,8 +139,15 @@
},
{
"cell_type": "code",
- "execution_count": 14,
- "metadata": {},
+ "execution_count": 4,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2025-02-28T13:48:44.934018Z",
+ "iopub.status.busy": "2025-02-28T13:48:44.933889Z",
+ "iopub.status.idle": "2025-02-28T13:48:44.986980Z",
+ "shell.execute_reply": "2025-02-28T13:48:44.986688Z"
+ }
+ },
"outputs": [
{
"data": {
@@ -166,13 +194,20 @@
},
{
"cell_type": "code",
- "execution_count": 15,
- "metadata": {},
+ "execution_count": 5,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2025-02-28T13:48:44.988436Z",
+ "iopub.status.busy": "2025-02-28T13:48:44.988340Z",
+ "iopub.status.idle": "2025-02-28T13:48:45.066937Z",
+ "shell.execute_reply": "2025-02-28T13:48:45.066688Z"
+ }
+ },
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "374ca6dc04ab43db861a6b3e932e4884",
+ "model_id": "9c4f8110066643b9bdb127196d03378f",
"version_major": 2,
"version_minor": 0
},
@@ -211,8 +246,15 @@
},
{
"cell_type": "code",
- "execution_count": 16,
- "metadata": {},
+ "execution_count": 6,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2025-02-28T13:48:45.069264Z",
+ "iopub.status.busy": "2025-02-28T13:48:45.069168Z",
+ "iopub.status.idle": "2025-02-28T13:48:45.072524Z",
+ "shell.execute_reply": "2025-02-28T13:48:45.072248Z"
+ }
+ },
"outputs": [
{
"name": "stdout",
@@ -251,13 +293,20 @@
},
{
"cell_type": "code",
- "execution_count": 17,
- "metadata": {},
+ "execution_count": 7,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2025-02-28T13:48:45.073811Z",
+ "iopub.status.busy": "2025-02-28T13:48:45.073716Z",
+ "iopub.status.idle": "2025-02-28T13:48:45.124196Z",
+ "shell.execute_reply": "2025-02-28T13:48:45.123944Z"
+ }
+ },
"outputs": [
{
"data": {
"application/vnd.jupyter.widget-view+json": {
- "model_id": "6690b52c9e1b4a5dafaaf59f76340d16",
+ "model_id": "bd6de8572bc548d6a46ea06d97d37530",
"version_major": 2,
"version_minor": 0
},
@@ -300,13 +349,9046 @@
"\n",
"---\n",
"\n",
- "With PyTorch we can use the `require_grad=True` on tensors and it automatically handles the differentiation and the calculation of the *gradients* for us. Which tbh looks a bit like dark magic. Let's use AI to understand how it works by doing two Example on a function like $f(x) = m*x + b$ , and two different inputs (`x1` and `x2`)🕵️♂️"
+ "Using AI, we can plot this hill. The following plot shows the \"error surface\" (MAE) for the function $f(x) = m*x + b$. By fixing one variable (e.g., `b=2`), we can visualize the differentiated function in terms of `m` and determine whether to increase or decrease `m` to move \"downhill.\""
]
},
{
"cell_type": "code",
- "execution_count": 18,
+ "execution_count": 8,
+ "metadata": {
+ "execution": {
+ "iopub.execute_input": "2025-02-28T13:48:45.126122Z",
+ "iopub.status.busy": "2025-02-28T13:48:45.126032Z",
+ "iopub.status.idle": "2025-02-28T13:48:45.481311Z",
+ "shell.execute_reply": "2025-02-28T13:48:45.480927Z"
+ }
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ " \n",
+ " \n",
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+ },
+ "metadata": {},
+ "output_type": "display_data"
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+ {
+ "data": {
+ "application/vnd.plotly.v1+json": {
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+ "plotlyServerURL": "https://plot.ly"
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with line showing gradient of m at fixed b=2"
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+ "import plotly.graph_objects as go\n",
+ "\n",
+ "def demo_mae_surface():\n",
+ " # Actual data points\n",
+ " x_actual = torch.tensor([1.0, 2.0])\n",
+ " y_actual = torch.tensor([2.0, 4.0])\n",
+ "\n",
+ " # Range of m and b values to explore\n",
+ " m_vals = torch.linspace(-1, 5, 100) # Explore m from -1 to 5\n",
+ " b_vals = torch.linspace(-1, 5, 100) # Explore b from -1 to 5\n",
+ "\n",
+ " # Create a meshgrid of m and b values\n",
+ " M, B = torch.meshgrid(m_vals, b_vals, indexing='ij')\n",
+ "\n",
+ " # Initialize an array to store MAE values for the surface plot\n",
+ " mae_values_surface = torch.zeros_like(M)\n",
+ "\n",
+ " # Calculate MAE for each combination of m and b for the surface plot\n",
+ " for i in range(M.shape[0]):\n",
+ " for j in range(M.shape[1]):\n",
+ " m = M[i, j]\n",
+ " b = B[i, j]\n",
+ " preds = m * x_actual + b\n",
+ " mae = mean_absolute_error(preds, y_actual)\n",
+ " mae_values_surface[i, j] = mae.item() # Store the scalar value\n",
+ "\n",
+ " # --- Calculate MAE for fixed b to show gradient of m ---\n",
+ " fixed_b = 2.0 # Fixed b value\n",
+ " mae_values_fixed_b = []\n",
+ " for m in m_vals:\n",
+ " preds = m * x_actual + fixed_b\n",
+ " mae = mean_absolute_error(preds, y_actual)\n",
+ " mae_values_fixed_b.append(mae.item())\n",
+ "\n",
+ "\n",
+ " # Create the surface plot using Plotly\n",
+ " fig = go.Figure(data=[go.Surface(z=mae_values_surface.numpy(), x=b_vals.numpy(), y=m_vals.numpy(), colorscale='RdBu', name='MAE Surface')])\n",
+ "\n",
+ " # Add the line plot for fixed b, offsetting z values slightly\n",
+ " z_offset_line = 0.1 # Offset to lift the line above the surface\n",
+ " fig.add_trace(go.Scatter3d(\n",
+ " x=[fixed_b] * len(m_vals), # Fixed b value for all m values\n",
+ " y=m_vals.numpy(),\n",
+ " z=[z + z_offset_line for z in mae_values_fixed_b], # Add offset to z values\n",
+ " mode='lines',\n",
+ " line=dict(color='green', width=4),\n",
+ " name=f'MAE with fixed b={fixed_b}'\n",
+ " ))\n",
+ "\n",
+ " # Add annotation - Adjusted for better readability, offsetting z value slightly\n",
+ " annotation_m = 2.0\n",
+ " annotation_mae = mean_absolute_error(annotation_m * x_actual + fixed_b, y_actual).item()\n",
+ " z_offset_point = 0.1 # Offset to lift the point above the surface\n",
+ " fig.add_trace(go.Scatter3d(\n",
+ " x=[fixed_b],\n",
+ " y=[annotation_m],\n",
+ " z=[annotation_mae + z_offset_point], # Add offset to z value\n",
+ " mode='markers+text',\n",
+ " marker=dict(size=8, color='red'),\n",
+ " text=[\"At m=2, decrease m to go dowhill\"], # Shortened text\n",
+ " textposition=\"top center\", # Changed text position to top center\n",
+ " textfont=dict(size=10) # Reduced text size\n",
+ " ))\n",
+ "\n",
+ "\n",
+ " fig.update_layout(\n",
+ " title='3D Error Surface: Mean Absolute Error (MAE) for f(x) = mx + b
with line showing gradient of m at fixed b=2', # Added
for title wrapping\n",
+ " scene=dict(\n",
+ " xaxis_title='b (y-intercept)',\n",
+ " yaxis_title='m (slope)',\n",
+ " zaxis_title='MAE',\n",
+ " camera=dict(eye=dict(x=1.5, y=-1.5, z=0.8)) # Rotate perspective\n",
+ " ),\n",
+ " width=700,\n",
+ " height=700\n",
+ " )\n",
+ "\n",
+ "\n",
+ " fig.show()\n",
+ "\n",
+ "demo_mae_surface()\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
"metadata": {},
+ "source": [
+ "With PyTorch, we can use `require_grad=True` on tensors, which automatically handles differentiation and the calculation of the gradients for us. To be honest, it looks a bit like dark magic. Let's look at some examples where we can see this functionality from PyTorch being applied to our function $f(x) = m*x + b$, along with two different inputs (`x1` and `x2`)🕵️♂️."
+ ]
+ },
+ {
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- "model_module_version": "2.0.0",
- "model_name": "LayoutModel",
- "state": {}
- },
- "15bcdbc851ed4bf29e29859357fbae52": {
- "model_module": "@jupyter-widgets/base",
- "model_module_version": "2.0.0",
- "model_name": "LayoutModel",
- "state": {}
- },
- "185a9bd78ffc46609d01ca7c0e6c398d": {
+ "0455666d943a462894e585af892675c3": {
"model_module": "@jupyter-widgets/base",
"model_module_version": "2.0.0",
"model_name": "LayoutModel",
- "state": {}
- },
- "2406bb8acaf24c31b23c88432252cc1c": {
- "model_module": "@jupyter-widgets/output",
- "model_module_version": "1.0.0",
- "model_name": "OutputModel",
"state": {
- "layout": "IPY_MODEL_0696762f8b6d40a4a9f83ccc89e6ad73",
- "outputs": [
- {
- "data": {
- "image/png": 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"outputs": [
{
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",
+ "image/png": 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XViKJJO7lj1trAACBlJm5TyNn/6whk5dqRcZ2VShRWO3Pr6wWdcopNTVFgfXww9Lu3W5LygQL0JGiJw0AIQ/QPYfN0Oh5q73r9ilsYdmCc9Oap2hgu/rBDNTTp0sNGkhly7qtKIsWVaJhThoAcFTWg7YAvXd/gDZ2abftvN0fOPv2SQ884K6npydkgI4UQRoAQsyGuK0HnR07P2TKMgXOF19IY8e6CmMdOyqZEaQBIMRsDjqnAVc7v3LDNgVKZubBXrRtopE/uVOrCNIAEGKWJJbTjLOdL59WRIEydKirKnb++VLLlkp2BGkACDHL4s4pMczOtz+vkgJj+3aX0W2efdYyr5TsCNIAEGK2zMqyuPOlphzoUdul3bbzdn+gyn+uWCFdf710wQUKA5ZgAUDIHVgnPWWZNwdtQ9zWgw7UOum1+8t/Wm96/nypWjUlukjiHkEaABB8PXpIL78s9ewpvfSSkgFBGgCQ+L7/XqpZUypSxJX/LFVKyYBiJgCAxPeXv0h79kgPPZQ0ATpS9KQBAMH11VdSo0bSaadJCxdKhQsrWdCTBgAkrsxM6e673fUnn0yqAB0pgjQAIJjeecdtpHHOOVLbtgojhrvDvM0bAATVtm2uNreti54wQWrYUMmG/aR92uZtzaadmrVitr6Y/0twt3kDgCB7/nkXoFu1SsoAHSl60nk0YuZK3TN8tret25GsYs9zreuoZb3yvrQNABLSqlWuWMnu3a5wiRUxSUIkjsVBQm7zBgBB1qePtHWr9Oc/J22AjhTD3WHb5g1AwkvqPBjb4eqNN6STTz64mUaIEaTzyP44bA56X6Js8wYgoSV1HowN/fbq5S779ZNKlFDYMdwdpm3eACQ860FbgLY8mKzOgV3abTtv9yes//xHGj/elQC94w6/WxMIBOkwbfMGIOElbR7Mjh3Svfe66wMGSPkZ6DX8FvLIess2vBT4bd4AJIWkzYOxvaKXLJGaN5eaNPG7NYFBkI4CC8S2zIqlVgBiLSnzYGzJVf/+UoEC0nPP+d2aQGG4GwASSFLmwfTuLW3Z4vaKtvXROIBiJgCQ4NndKfsDtOXBJFx2d1Ztblty9cMPocroTokg7hGkASBR10kneh6MfeZfeKE0ebI0eLDUpYvCJIUgDQAIrKFDpfbtpbp1pW++kfLlU5ikxLss6MqVK9WyZUudfPLJKlWqlNq0aaO1a9dG8yUAAMlg82bp/vvd9YEDQxegIxXVIN29e3fvctmyZVqyZIl27NihP1vtVQAADvX44y6ru127UO9yFdcgvXjxYq/3XKxYMZ144om64YYbNHfu3Gi+BAAg0S1a5LaiLFJEevppv1sTniB99913a/jw4dq4caMyMjI0bNgwNbeF6QAAZLn7bmnXLreBRoUKfrcmPEH6wgsv1Jo1a5SWlqaSJUtqw4YNevDBB7N9bHp6ujdpnnUAAEJg9Gjp44+lKlVcsEZ8gnRmZqaaNGniBeotW7Z4h12/4oorcgzSltWWdQAAktzOnW6PaGPD3YUK+d2iwIvaEqx169apdOnSWr58uSrsH76w6xUrVvQyvC3b+6gNYQkWACS3J56QHnpIuuoq6ZNP7INfYZYSzyVYFoTPOOMMvfzyy15Wtx123QL2sQI0ACDJ/fST9Nhj0gknSC++GPoA7cuc9EcffaQZM2aofPnyKlu2rKZNm6aRI0dG8yUAAInItqHcts1dUp87YlQcAwDE1pgxbvvJ006TFiyQihb1u0XhrDgGAMBhbKmV7W6VlSxGgM4VgjQAIHZs/vm776TLLpOuv97v1iQchrsBALGxfLl01lmuNz17truOAxjuBgD45667pK1bXbIYAfq40JMGAETfp59KV18tVaokzZ/v6nTjMPSkAQDxt2PHwWSxl14iQOcBQRoAEF1PPSX9+KPUrJnUooXfrUloDHcDAKK7DWWtWq6imA1zn3663y0KLIa7AQDxYwGne3e3kYZtQ0mAzjN60gCA6PjXv6R27aQzz3RLrgoW9LtFgRZJ3CNIAwDyLiNDqlFDWr1a+vJLqXFjv1sUeAx3AwDiw7agtADdoQMBOoroSQMA8mbqVOn886W0NGnhQtu72O8WJQR60gCA2NqzR+rSxSWNPfMMATrKCNIAgLxtoGFJYhddJN16q9+tSToMdwMAjs+SJW5N9O7d0syZUs2afrcooTDcDQCIDQsu3bpJ27ZJf/kLATpG6EkDAHJv2DDpxhvdmuhZs6RChfxuUcJhnTQAIPp+/dVtPbl2rTRunNSokd8tSkgMdwMAou+++1yA7tSJAB1j9KQBAJGzamKXXiqdcoq0YIFbG43jQk8aABA9liR2xx0Hl14RoGOOIA0AiEx6utuKsnlzqU0bv1sTCgx3AwCO7ZtvpHPPlYoVk+bNkypU8LtFCY/hbgBA3u3aJXXsKGVmutKfBOi4IUgDAI7u6aeluXPd7laW0Y24YbgbAJCz+fOlevWk1FQXqM84w+8WJY1I4l7+uLUGAJBY9u51PWcb7rZhbgJ03DHcDQDIni2zmjxZOuccqVcvv1sTSgx3AwB+6/vvpTp1XLLYjBlsoBEDDHcDAI5vmNuyuXfskPr3J0D7iOFuAMDhBg2SJk2S6td3dbrhG4a7AQAHWUWx2rWlPXtcARO7jpigmAkAIHI2/3z77dL27VLv3gToAKAnDQBwXnhBuusuqW5dado0qUABv1uU1CKJewRpAIC0cKELzpY0Nn26dPbZfrco6ZHdDQA4Npt/7tDBZXM//jgBOkCYkwaAsHv2WWnqVOkPfyCbO2AY7gaAMLN63L//vZQvnzRzplSjht8tCo0UhrsTU2bmPo2c/bOGTF6qFRnbVaFEYbU/v7Ja1Cmn1NQUv5sHIFlYTW4b5t69W3rqKQJ0ANGTDmCA7jlshkbPW+1dt9+IhWULzk1rnqKB7eoTqAFEx8MPuznoiy6Sxo1zO10hblgnnYCsB20Beu/+AG3s0m7bebsfAPLs66+lJ5+UTjxRevttAnRARf1/ZeTIkapbt66KFi2qcuXKafDgwdF+iaRmQ9zWg86OnR8yZVnc2wQgyWzZIrVv74qX2E5XlSv73SLEY0569OjR6tatm4YOHaqLLrpImzZt0urVq6P5EknP5qBzGvyw8ys3bItziwAknXvukRYvllq2lG691e/WIF5Buk+fPnrkkUfUuHFj73ZaWpp3IHKWJLZm085sA7XNRJdPK+JDqwAkjVGjpNdfl8qUcZcp5LiEYrh769atmj59ulauXKnq1avr1FNPVevWrbVq1apsH5+enu5NmmcdcCyLO6fEMDvf/rxKcW8TgCSxdq3UqZO7/o9/SKVL+90ixCtIb9iwwctSGzFihL744gstWrRIBQsW1M0335xjkLbHZx1wbJmVZXHnS03xes7GLu22nbf7ASDX7HPWNs+wKcjOnaVmzfxuEeK5BCsjI8Mb2v773/+u2+2NIOnHH39UtWrVtHnzZi+R7KgNYQnWb9dJT1nmzUHbELf1oFknDeC4WRJv165S9erSjBnSMT6TkWTFTEqUKKGKFStmex/BN3csELesV947ACDPFiyQ7r5byp9feucdAnRYl2DdcccdGjhwoDcvvX37dvXr10+XXXaZihUrFs2XAQBEaudO6cYb3R7R/fpJDRr43SL4ld39l7/8RevXr1edOnW825dccomGDBkSzZcAAORGnz7SrFnSxRdL99/vd2uQS5QFBYBkNWaMdMUVUvHi0pw5Ug5TkvAHZUEBIMzLrayqmAWB114jQCcogjQAJBsLzFZJ7JdfpI4dpRtu8LtFOE4MdwNAsrF63L16SWeeKU2fTjZ3QEUS9wjSAJBMZs6UzjvPXZ86Vapb1+8WIQjrpAEAAdjdql07adcu15smQCc85qQBIFl07y4tXOhKfvbs6XdrEAUMdwNAMnjzTem226Ty5d266FKl/G4RjoE5aQAIg/nzpXPOcdXFxo2TGjb0u0WIAHPSAJDstm2T2rRxl48/ToBOMgRpAIjHrnaTl2pFxnZVKFHY2zc+arva2dzzvHnSlVdKDzwQjSYjQBjuBoAYBuiew2Zo9LzV3nX7hLOwnLp/f/iB7ernLVDb3gi33CKVLevmocuUiWbzEWOUBQUAH1kP2gL03v0B2til3bbzdv9xmztX6tLFIr707rsE6CRFkAaAGLEhbutBZ8fOD5my7PieePNmqVUrt/1k//5S48Z5aygCiyANADFic9A5DWba+ZUbtuX+SW14tFMn6fvv3Xpotp9MagRpAIgRSxLLacbZzpdPK5L7Jx00SPr3v6XKlaW33nLD3Uha/O8CQIxYFndOiWF2vv15lXL3hFaL+557pBNOkIYPl0qWjE5DEVgEaQCIEVtmZVnc+VJTDvSo7dJu23m7P2Jr1kjXXy/t3i298ILUoEGsmo0ASc4lWPY8mZlSvnzReT4AyOs66SnLvDloG+K2HnSu1knv2SM1aeKqidmSKysBmhKFNdbwVTjLgtouMLffLlWoID33XDSaBgD+uu8+6dln3a5WX38tFS7sd4sQBeEsC7punTRmjLR+vfT730s33uh3iwDg+NncswXotDTpww8J0CGTfD1p88UXUtOmUsGC7lsne6oCSNSNM/7wB1eX+//+z32uIWmEt+KYzd08+aRb6H/ttdKvv/rdIgDInYwMqWVLaetWqW9fAnRIJWdP2thztW3r1hNedpk0erSUP/lG9wEkob17pebNpU8/la65xg1zsx466YS3J20s8/GNN6Szz5bGjpUefNDvFgFAZPr0cQH6d79zm2gQoEMreXvSWX780W2GvmGDNHSodNNN0X8NAIgWG/274QapRAlp2jSpWjW/W4QYCecSrKMlkhUoIE2Y4II2AATN7NnSBRe4fBoSxZJeuIe7j0wkszXTO3e6RIxVq/xuEQD8tqKYzT9bJvcTTxCgEaKetLHntiIn//yndO65rnJPoUKxez0AiJR1IC6/XJo4UWrXTnrnHSqKhUAKPelD2Bv+1Vel8893Repts/RgfD8BEGb2OdS1qwvQNhX3j38QoBHCIG2suIktZbCSoW+/LT39tN8tAhB2Awa4Eb5y5aQRI6gohpAOdx9q5kypYUOXnPHBB67gCQDEmyWH2Xpo23rSklrZ2SpUUhjuzkG9em7Ox9x8swvaABBPc+e6gku2Y5/takWARjbCGaSNZXlb6VDLpLRvsj//7HeLAITFL79IzZpJmzdLjz7q1kUD2QjncHd2Gd+2Y9b48VLRovFtA4BwsY5B48bS//7niitZRTESxUIphWImEdi1y62j/uort0bR5qjz5Yt/OwAEQmbmPo2c/bOGTF6qFRnbVaFEYbU/v7Ja1Cmn1NQ8BlMb2m7Txn3OWF6MbatrCa0IpRSCdIRslyyr8vP999Kdd0ovvOBPOwD4HqB7Dpuh0fNWe9ftE8nCsgXnpjVP0cB29fMWqB94wK0qqVLFLQUtVSqazUeCIXEsUief7LIs7Q/mxRfdASB0rAdtAXrv/gBt7NJu23m7/7gNHuwCtNXk/uQTAjQiQpDOUrWqNHKkq0J2111uvSKAULEhbutBZ8fOD5my7Pie+OOPpe7d3VKrjz6SatTIW0MRGgTpQ1k1Mtspy9x4oxuOAhAaNged0+CjnV+5YVvun9QSxLKWWr31lnTxxXltJkKEIH2k66+Xnn3WFTr54x/dPDWAULAksZxmnO18+bQiuXvCxYvdUivL6LahbgvWQC4QpLNz991uyNsSymwnGlvTCCDpWRZ3Tolhdr79eZUif7J166SrrnK7W9lQ9733Rq+hCI2YBOnt27frjDPOUAlLkEhU1pu2AgNLlrgetRUdAJDUbJmVZXHnS0050KO2S7tt5+3+iGzdenAkzpZ2WjIqa6FxHGKyBOu+++7TjBkzNH36dGVkZAR/CdbRto+znrRta2lrqUeNcokfAJJ/nfSUZd4ctA1xWw864nXSu3dLLVpIo0e7tdCff86mGQjOOmkLzLfeequee+45tWnTJrGDtNm4UbroIldn1/Z5tcSyVGYJAGTDksM6dHCfEzVruk0z0tL8bhUCKu7rpPfs2aPOnTvr5Zdf1gnH6HGmp6d7Dcw6Auukk9w34sqVpWHDXLGTIH6ZAOA/K1ZiAfq009znBgEaeRTVIP3MM8+oXr16ujiCJQYWpO0bRNYRaLbPqw1ZlSkjDRok9evnd4sABI1t2GO5LCVLSp995vatB/Iov6Jk0aJFGjx4sGYm67aP1aq5b8ZWGD893VUp69HD71YBCAKrJvbgg26DHqteeNZZfrcISSJqPemJEydq9erVql69ukqVKqVrrrlGmzZt8q5PTZaiILYPtVUls4L4f/7zwT2pAYSXTYN163awmti55/rdIiSRqCWObdu2TevXrz9we/LkyerUqZPmzZunMmXKHHOOOrCJY9mxQH3dde76+++7vakBhI/V4La/f/vsGj5cuvZav1uEBBLXxLEiRYqoQoUKB47SpUt7DbDrxwrQCceWV7z9tsvktLXUNl8NIFxsaWarVpYxK73xBgEaMcFWlXnx+utSly5uDaQlithSLQDJ7+uvpSuucEVLrFCJTX8BucRWlbF2xx3S888frPNthfQBJLdvvnHlPi1AW0Y3ARoxRJDOK6vx3bevKxtq36xnzPC7RQBiZc4c93e+aZP0yCNuXTQQQwx3R4O1++GHpSeecGsk//tfqU4dv1sFIJrmz3dLMNeutdrH0lNPUY8biVcWNJRB2ljb77/fFTMoVUr68kupVi2/WwUgGhYskC65RFq92tVHeOklAjTyjCAdb9Z+2+byhRdcdTLL/qSoAZDYvvvO9aAtQHftKr38MgEaUUHiWLzZH64lktk3bdtD1v6w583zu1UA8hKgs3rQf/qTKwtMgEYcEaSjzf6AbSjMNnnPCtSWbAIgMQP0L7+4pZbWg2YHPMQZ77hYBeqBA92OWevWSZdeKs2a5XerAETq22+lRo1cgLallq+8QoCGL3jXxTJQDxjg5qh//dUF6unT/W4VgGOxTYJsBMxGwmxE7NVXCdDwDe+8WAdqy/a2rO8NG1ygtkpFAIJp2jT3d2pfrO0Lto2IEaDhI9598QjUVpWoTx9XAKFJE2nsWL9bBeBIEydKl18uZWS4bSftCzZJYvAZQToe7A+9Xz9X/GDbNldC9OOP/W4VgCy2V7xVErPKgbZffP/+BGgEAuuk480SUGyeK39+aehQt4sWAP/YFpM33STt3i0995wb5gbigHXSQWSbw7/5ptvmsl07l5QCwB//+IfUtq20d6+7ToBGwBCk/dChg/T++1KBAi5o21B4GEYRgKCwv7dnnpE6dZLy5ZPee0/q2NHvVgG/wXC3n6y+9zXXuHkwq1Jm+9KSSQrElo1i3XuvWyJZpIj04YfSlVf63SqEUAq1uxOAbW3ZtKnbWceGv//5T6lgQb9bBSSnXbuk226T3n1XOvlk6ZNPpHPP9btVCKkUgnSC+P57l1m6bJkrQ2jf7EuU8LtVQHKxEavrr5e++EKqVEn67DPpzDP9bhVCLIUgnUBWrXJLs6zakW1x+X//J512mt+tApLDzz9LzZq5v6+zz3ZLrsqV87tVCLkUsrsTSNmy0vjxbm7M6gaff740d67frQISn/09nXfewXKfX31FgEbCIEgHyYknuiInNme2cqXUsKEbkgNwfMaMkS68UFq+XLr5ZteDZioJCYQgHTS2LMvWaz76qCsjakPgrKUGcs+SMK+6yv0dWVnet98mKRMJhznpILOKZLff7jJSe/VytYRtTSeAnFlhEqu9beugrbLfa6+xBhqBROJYshT9b9nS7cpjiS/vvCMVL+53q4DgZnBbiU+bNkpLc0WDbFcrIIAI0snixx9dgP7uO+l3v5M++kg64wy/WwUEiy1hbN7cJVxWry6NGiVVq+Z3q4Ackd2dLKpWlSZPdkVP5s+X/vAHlxADQJmZ+zTh7+9rY626XoCeXaOBPnn9Q2VW5YssEh896USda7PyobZjz513RrSlnn2QjZz9s4ZMXqoVGdtVoURhtT+/slrUKafUVLbkQ2LK3JupD257QNcOfV7592Xqn79vrv6XdtK+/PnVtOYpGtiuPu9vBBbD3cmcUGYbA+zc6ebfLDGmaNGjBuiew2Zo9LzV3nX7LdvHln148UGGhLVjh35qc4sqfjxcO/MV0MNXdtf7Z19+4O58qSl6rnUdtaxX3tdmAjlhuDtZ2XrPCRNcRTJLJLPCJ4sW5fhw60FbgN67P0Abu7Tbdt7uBxLK0qVeHQEL0KuKnazWNz11WIA29oV0yJRlvjURiAaCdKI65xxp+nTpsstcokyDBi6jNRs2xG0fWNnhgwwJxzbFqF/fe//PqlRLzW99QXPKVv/Nw+wdv3LDNl+aCEQLQTqRlS7tKpLZPPXGjVKLFu76nj2HPczmoHMaUOGDDAmVk9G7t1vpsGGDdM89evyeQfq1aFq2D7cJnPJpReLeTCCaCNKJzoqbPP649J//SCedJD35pNtJa8WKAw+xJLGcZpz5IEPCbEBjO8X17+/qBHzwgVfc58aGZ+SYT2Hn259XKe5NBaKJIJ0srOCJ7U1tw95WAKVuXenTT727LIubDzIkLKu3XaeO9N//SrVrS998I113nXeXrU6w5EdLEst6h9ul3bbzdj+QyMjuTjaW8f3AA9KLL7rb99yjzL8+pp4fzotqdjdLuhBzVg734YddOVzTtatbdli4cPbvxSnLvKkbGxmyL568FxF0LMEKMxv+tnrFGRlerzrznXc1cmfxqHyQsaQLMffDD2554f/+53at+vvfpeuv97tVQFQRpMPOtudr397tU229jwEDpDvuiKj4ydGMmLlS9wyf7S3hOhJrU5En9hnwt79Jd90lbdvmlhcOGyZVYkoGyYd10mFn66jHjnXJNrt3S3/6k8sAtyScPGBJF2JizRrpmmukLl3ctE3fvtJXXxGgEWoE6TBkfz/0kDRpkttswDYdqFVL+ve/j/spWdKFmEzPnH22W+tvm8fY+/WRR9xWk0CIEaTDwjblmDlT6tlTWr9euuEGqW1btwVmLrGkC1Fj778bb3TZ2taTtukYe5+ee67fLQMCgSAdJlbf+6WX3BB4xYrSe++5rS+tV52LfACWdCFqvWd7/9mcc4UKbqmV1aEvVszvlgGBQZAOo0svlebMcZt0WO/FetW2znrlyoj+OWtTkSeWE9G69cHes70Pv/1WuvJKv1sGBE7Usrt37typHj16aMyYMVq3bp3Kly+v+++/Xx1tGVAkDSG72x9WIKJzZ2nxYlfJ6amn3JCjbYV5FNFem8q66xDIzHSZ27aO38rY2mjO668TnBFaKfFcgrV161Y99dRT6tChg6pUqaKpU6fqqquu0nvvvacrrJxfFBqLGLGlLo8+Kj3/vPsgtfnAV1+V6tWLy8uz7joE5s1zqwsmTtS+1FSNatxazzW8SSefUpIvYwitFL/XSV933XWqVauW+vXrd8zHEqQDwHbVsg9SK7toPWlLMrP/O+thxxDrrpPYpk1SerrLhdi7V8srVVfPS7pp9iln8GUMoZfi5zrpHTt2aNq0aapttXazkZ6e7jUw60AA/P730pQp0ssvu+QdKy165pnSW2+5HnaMsO46CdkHz7vvuvePFdEpUkRz735Ul7V9VrP2B2jvYexrDsQ/SNs3g06dOqlatWpebzqnIG2PyzoQoHXV3bpJCxe6soy//CLdequr/DR1akxeknXXScZKeV588cH3z803e++n9KpNtDuHjxy+jAFxCtIWcLt166aFCxdqxIgRSj1GAhIC6tRTpaFDXVEJ21lr2jTpvPOkW26Rfvopqi/FuuskYduj2vvD1uTbTmw2imYlaYcMkcqW5csYcBxSox2gu3fv7iWNff755zrJ9jdGYrvgAteDfuMN6ZRT3Adu9eouQ9c274gC1l0nOMvU7tPHvS/s/WHvE8vitq1TrUe9H1/GAJ+DtC3BmjRpkr744gulpaVF86nhJxsNue02tzORlWq0IfGnn5aqVnUZ4du35+npWXedoHbscFtHVqkiPfaYy1t48EH3PrG1z/Y+OQRfxoDci1p297Jly1S5cmUVLFhQ+Q+pt3vzzTdr8ODBx24I2d2JVYzCMnZt+0D7YC5XztUHtw/mggWP6ynZEzjB9nm2ZELL/LchbvsSZ3kLtozP1j7ngKV2QMCWYOUGQToBLVjgPpiHD3e37QO6d2+pQwfphBP8bh1iEZzffFN6/HH7Vu7OWWKo9aLPOiuip+DLGHAQQRrxMWuWC9YjR7rbVof5vvtcz7qIf/OMVDGLEpvOsJ7zE08cTBr84x/d//k55/jdOiBhEaQR/6U31qvKCtalS0t33eUKpMQ5R4Gh1SjYsMFVnrP18lZj2zRr5vISCM5AnhGk4Q/bvMN6Xba7ls1ZW2/aarjfeafbKzgOqGKWB0uWSIMGubraW7a4Oefrr3cZ/VbwBkDiVxxDiNn6WNt+8LvvXC/a3oT2oW9LdGy3rTFjYlrBzFDFLJfs/8g2W7H/n6ys/d27pS5dXGEb+8JFgAbijp40Ym/dOrdPsAVqq0BlLGBbALes4BgMhZ/7+Bit3rQzx/tPLV5QUx66POqvm5BD2ra22XrNtglGViGbrl1dgLY1zwBiguFuBMvOndL777t5TqtkZgoVckOptg77kkuOuUVmpK5/ZZJm/JSRbYUrm4muXylNH3S9QKFkf2cTJrgldJaZb+udjc0z25SE7fW8Pzuf5DsgdgjSCPa8tQVrKz1q855ZS7hs+ZbVeraedh4wJ50NKzJivWb7ndu8sznxRFdj2/YUr1//sIeTfAfEFkEawbd1q/TBB9I//ymNG3fwvAWMtm2lNm2kSrmvREWA2c/WM9vv1+aUD90g5cIL3VSD/Y5tx7Ns8EUHiC2CNBKL9e6sp5eVdJbFhmEtockOK5oR4damoSycYX9D33/vlsHZ1IJtjJLFMuvbt3cjFVbK8xiYMgBiiyCNxGTvg7lzpX/9S3rvPWnx4sMDja3VveIKqVEjX4ulBIbNKdsc8yefSKNGST/+ePA+y9Ru1codlp2di73bSb4DYosgjcRn74lvv5VGjJA++kiaPv3gfVYn/KKLpMsucwHbglAYypHu2SPNnCmNHeuWs1kSXlbyV9ZUgVUEs5KdderkKjAfip40EFsEaSQf29Dhs8/cYQHKlhBlKVxYOv98qWFDt6exDZOXKaOE9+uvrprb11+7gGxzyzaXn8W2hLXM+Kuvdkf56MwTMycNxBZBGslt714XvMaPl776Spo4Udq06fDHWNJZgwbS2We7o1YtNwR8xDaKgekh29D+/PluuN/2Y7Yjq152Fkv0Ou886dJLpcsvdz3nGPw8JN8BsUWQRviC9uzZ0pQpLmHKArjt1HXk+8qGyS1Q2/y2HXbdNgXJOkqVitp67d+0z3rFttXn8uUuUc6OpUtdspctkbKdpg5lQ9VnnukC8QUXuKxs+7IRpy8ZoUy+A+KEIA1Yz9p6pVmHrc+2wG3BMie2H/rJJx88SpZ0vdeiRV2imh32GAvkFkTtsF6wFWvJOmztd0aGtHGju1y71m1SYYE6J7YhiWWv21GzpgvMNqecwxIpAImNIA3kxOayLQt60SI3xLxypZvvtuPnn10Qt9rV0WJB3UpsWslNO2ze+PTTDx62JMp68ABCI4UgDRwney9ab9iC9fr1yty8Ra9+MlvzFv2iQrt22B+OUvdlKl/KPp1dtrjaXVhVqYUKuqF0O6z3W6KES+rKOmIxhA4gYUUS9/LHrTVAIrEhbCuZaUflyho5c6Wez79Fe6v/tgjI8NQUFa1LpjOA6OOrPRABtr4E4AeCNBAB2wEqp0EpO2+ZzwAQbQRpIAK2RWNOC47svC1NAoBoY04aiIDtoTxrRfbVt2y9sK0dzq1Y7NXM/s9AciG7G/Ch+lYsqnlRIQxILJHEPYa7gQhYcLMgZ/WqbWMJ2wHKLu328QQ/6+1aMLWeedafqF3abTtv9+dWLJ4TgL8Y7gYiZIHYlllFY6lVJNniuX2dWDwnAH/RkwaSJFucDHQg+RCkgSTJFicDHUg+BGnAB5ZxndM89vFmi8fiOQH4iyAN+MCWRFnGdb7UlAO9X7u023be7g/CcwLwF0uwAJ/EYq9m9n8GEge7YAEAEFCskwYAIIERpAEACCiCNAAAAUWQBgAgoAjSAAAEFEEaAICAIkgDABBQBGkAAAKKIA0AQEARpAEACEOQ3r17t3r06KG0tDSVLFlSPXv21J49e6L5EgAAhEZUg/Rjjz2miRMnav78+Zo3b54mTJigxx9/PJovAQBAaER1g43TTjtNAwYMUKtWrbzbw4cP17333qtly5YduyFssAEACJGUSOLevihZv369vdK+H3744cC577//3juXkZHxm8c/+uij3n0cHBwcHBxhPY4laj3p5cuXq2LFilq7dq1KlSrlnbPrZcqU8e6rUKGCgogevL/4/fuP/wN/8fv3X0qA/w+iNiddrFgx73Ljxo0HzmVdP/HEE6P1MgAAhEbUgrRldFtvedasWQfO2XWbpz7ppJOi9TIAAIRGVLO7b7vtNvXv31+//PKLd1hmd6dOnRRkjz76qN9NCDV+//7j/8Bf/P7992iA/w+imt1t66R79eqld99917t98803e9ne+fPnj9ZLAAAQGlEN0gAAIHooCwoAQEARpAEACCiCNAAAAUWQBgAgoAjSkj755BNdfPHF3lpvq5BmtcdXrFjhd7NCY9WqVWrRooXKlSvnVf45dK09Yodd6/w1aNAgNWjQQAULFlTLli39bk7o7Ny5U507d9bpp5/uFdyqUaOG3njjDQUNQXp/ZbQHHnjAK1+6ZMkSFS9eXG3atPG7WaGRmpqqpk2basSIEX43JVTYtc5f9qW0d+/eXqBA/O3Zs0dly5bVmDFjtGnTJr355pu655579PnnnytIWIKVjTlz5qhevXreNy3WeMeX9aRnzpypunXr+t2UpJeXXesQPenp6d7oEV9S/XfdddepVq1a6tevn4KCnnQ2xo8fr7POOosAjaS1YcMGb0rn0C9Ddv2nn346rP4+EBY7duzQtGnTVLt2bQVJ0gfpZs2aeb2znI6lS5ce9njrxfXp08frYSD+v3/Ex5YtW7zLEiVKHDiXdX3z5s2+tQvww759+7wS1tWqVfN600GS9F1FK1G6a9euHO+3hJksc+fO1VVXXeUldDRp0iROLUxuufn9I34O3bUua2tZdq1DWAN0t27dtHDhQm9+2nJkgiTpg7QlgUXCAvTll1+uJ5980qs5jvj+/hFfh+5aV7VqVe8cu9YhjAG6e/fumjp1qsaOHRvI936wvjL4xDJbLUBbtqvt5AV/5oPsMNbztuuZmZl+NyupJeKudcmWXWzvc7u097pdP9qoE6LPliBOmjRJX3zxhffFNYjI7t7/YfXWW2+pSJEih523pSkVK1b0rV1hYvPTR/ryyy/VuHFjX9oTBuxa539Wd9++fQ8716hRI40bN863NoXJsmXLVLlyZW+d+qHvefs7GDx4sIKCIA0AQEAx3A0AQEARpAEACCiCNAAAAUWQBgAgoAjSAAAEFEEaAICAIkgDABBQBGkAAAKKIA0AQEARpAEAUDD9P9WffEKI06CHAAAAAElFTkSuQmCC",
- "text/plain": ""
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ]
- }
- },
- "36a6488e798e4e4ca9581731dd81ec3a": {
- "model_module": "@jupyter-widgets/output",
- "model_module_version": "1.0.0",
- "model_name": "OutputModel",
- "state": {
- "layout": "IPY_MODEL_e0b9eb9700674070b3e74d5640b90f20",
- "outputs": [
- {
- "data": {
- "image/png": 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",
- "text/plain": ""
- },
- "metadata": {},
- "output_type": "display_data"
- }
- ]
+ "_model_module": "@jupyter-widgets/controls",
+ "_model_module_version": "2.0.0",
+ "_model_name": "SliderStyleModel",
+ "_view_count": null,
+ "_view_module": "@jupyter-widgets/base",
+ "_view_module_version": "2.0.0",
+ "_view_name": "StyleView",
+ "description_width": "",
+ "handle_color": null
}
},
- "36bd0c4eeaec4568bd8c9436a320316e": {
+ "221ff784a1f44aa7b6f88199239a1988": {
"model_module": "@jupyter-widgets/output",
"model_module_version": "1.0.0",
"model_name": "OutputModel",
"state": {
- "layout": "IPY_MODEL_f8640cee3fb641738efbd6e09e1b54c6",
+ "_dom_classes": [],
+ "_model_module": "@jupyter-widgets/output",
+ "_model_module_version": "1.0.0",
+ "_model_name": "OutputModel",
+ "_view_count": null,
+ "_view_module": "@jupyter-widgets/output",
+ "_view_module_version": "1.0.0",
+ "_view_name": "OutputView",
+ "layout": "IPY_MODEL_761f10915fcd4b24875ace55621e70a4",
+ "msg_id": "",
"outputs": [
{
"data": {
- "image/png": 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",
+ "image/png": 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+ "_model_module": "@jupyter-widgets/controls",
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+ "_model_name": "FloatSliderModel",
+ "_view_count": null,
+ "_view_module": "@jupyter-widgets/controls",
+ "_view_module_version": "2.0.0",
+ "_view_name": "FloatSliderView",
"behavior": "drag-tap",
- "description": "a",
- "layout": "IPY_MODEL_76928ef54d994d60af1240ed80f7a039",
+ "continuous_update": true,
+ "description": "b",
+ "description_allow_html": false,
+ "disabled": false,
+ "layout": "IPY_MODEL_0d3a1efaaefd430f8993ae6e16cf1bb8",
"max": 4.5,
"min": -1.5,
+ "orientation": "horizontal",
+ "readout": true,
+ "readout_format": ".2f",
"step": 0.1,
- "style": "IPY_MODEL_8716fb0022064cb481faecc7254c9aa3",
+ "style": "IPY_MODEL_04ac22c57d4d413ea95ec833e2a60995",
+ "tabbable": null,
+ "tooltip": null,
"value": 1.5
}
},
- "eba36e6595f74306b538c1309ba45c0a": {
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"model_module": "@jupyter-widgets/controls",
"model_module_version": "2.0.0",
"model_name": "FloatSliderModel",
"state": {
+ "_dom_classes": [],
+ "_model_module": "@jupyter-widgets/controls",
+ "_model_module_version": "2.0.0",
+ "_model_name": "FloatSliderModel",
+ "_view_count": null,
+ "_view_module": "@jupyter-widgets/controls",
+ "_view_module_version": "2.0.0",
+ "_view_name": "FloatSliderView",
"behavior": "drag-tap",
- "description": "b",
- "layout": "IPY_MODEL_7c6dc3e3fa5546559c61785be2e0482c",
+ "continuous_update": true,
+ "description": "a",
+ "description_allow_html": false,
+ "disabled": false,
+ "layout": "IPY_MODEL_9dc894b703d04c5d93c52ac438e707c1",
"max": 4.5,
"min": -1.5,
+ "orientation": "horizontal",
+ "readout": true,
+ "readout_format": ".2f",
"step": 0.1,
- "style": "IPY_MODEL_890b1a7bbca84bb5abff84c42eeacf06",
+ "style": "IPY_MODEL_049bc8edddc64daa869a0f747e7deb94",
+ "tabbable": null,
+ "tooltip": null,
"value": 1.5
}
},
- "f362a9df407c4e33b2774107e5e816bf": {
- "model_module": "@jupyter-widgets/controls",
- "model_module_version": "2.0.0",
- "model_name": "SliderStyleModel",
- "state": {
- "description_width": ""
- }
- },
- "f376bb226310468a8de1a66fb0e94538": {
- "model_module": "@jupyter-widgets/output",
- "model_module_version": "1.0.0",
- "model_name": "OutputModel",
- "state": {
- "layout": "IPY_MODEL_72e9ca110b3b40f9843ce5b67e008445",
- "outputs": [
- {
- "data": {
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