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valgur/VLP-16_vertical_offset.ipynb

Created June 5, 2023 20:07
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VLP-16_vertical_offset.ipynb
{
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"id": "bc79bd07-3014-4eb0-b1b4-4ee4840353c9",
"metadata": {
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},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import pandas as pd\n",
"np.set_printoptions(suppress=True)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "88889d09-5cea-4c88-8faa-dcdeac6548bf",
"metadata": {
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"source": [
"meas = np.array([\n",
" [ 14.71, 14.35, 14.70],\n",
" [ 12.30, 12.45, 12.75],\n",
" [ 10.40, 10.55, 10.80],\n",
" [ 8.50, 8.65, 8.85],\n",
" [ 6.40, 6.55, 6.75],\n",
" [ 4.50, 4.65, 4.85],\n",
" [ 2.80, 2.85, 2.95],\n",
" [ 0.80, 0.85, 0.95],\n",
" [ -1.00, -1.05, -1.00],\n",
" [ -2.90, -2.95, -2.95],\n",
" [ -4.90, -4.95, -4.95],\n",
" [ -6.70, -6.80, -6.90],\n",
" [ -8.55, -8.75, -8.85],\n",
" [-10.45, -10.65, -10.80],\n",
" [-12.45, -12.65, -12.80],\n",
" [-14.25, -14.45, -14.70]\n",
"])\n",
"d = np.array([0.75, 1, 2])\n",
"angles = np.array([15, 13, 11, 9, 7, 5, 3, 1, -1, -3, -5, -7, -9, -11, -13, -15])"
]
},
{
"cell_type": "code",
"execution_count": 3,
"id": "e20aff64-955e-44dc-8127-1521bb7b02c9",
"metadata": {
"tags": []
},
"outputs": [
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"source": [
"err_no_offset = meas - angles[:, None]\n",
"pd.DataFrame(np.abs(err_no_offset), columns=d).style.background_gradient(cmap='GnBu', vmin=0, vmax=0.8).format('{:.2f}')"
]
},
{
"cell_type": "code",
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"id": "6846c8f4-02a7-40a9-88f5-149893d6ad5b",
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"array([[ 14.2 , 14.4 , 14.7 ],\n",
" [ 12.3 , 12.47, 12.74],\n",
" [ 10.4 , 10.55, 10.77],\n",
" [ 8.5 , 8.63, 8.81],\n",
" [ 6.61, 6.71, 6.85],\n",
" [ 4.72, 4.79, 4.9 ],\n",
" [ 2.83, 2.87, 2.94],\n",
" [ 0.94, 0.96, 0.98],\n",
" [ -0.94, -0.96, -0.98],\n",
" [ -2.83, -2.87, -2.94],\n",
" [ -4.72, -4.79, -4.9 ],\n",
" [ -6.61, -6.71, -6.85],\n",
" [ -8.5 , -8.63, -8.81],\n",
" [-10.4 , -10.55, -10.77],\n",
" [-12.3 , -12.47, -12.74],\n",
" [-14.2 , -14.4 , -14.7 ]])"
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"f = 41.910e-3\n",
"expected_with_offset = np.rad2deg(np.arctan(((d - f) / d * np.tan(np.deg2rad(angles[None].T)))))\n",
"np.round(expected_with_offset, 2)"
]
},
{
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"id": "f11cea34-09d6-45b0-b326-219668a1f7f0",
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" <td id=\"T_334c0_row0_col0\" class=\"data row0 col0\" >0.51</td>\n",
" <td id=\"T_334c0_row0_col1\" class=\"data row0 col1\" >0.05</td>\n",
" <td id=\"T_334c0_row0_col2\" class=\"data row0 col2\" >0.00</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row1\" class=\"row_heading level0 row1\" >1</th>\n",
" <td id=\"T_334c0_row1_col0\" class=\"data row1 col0\" >0.00</td>\n",
" <td id=\"T_334c0_row1_col1\" class=\"data row1 col1\" >0.02</td>\n",
" <td id=\"T_334c0_row1_col2\" class=\"data row1 col2\" >0.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row2\" class=\"row_heading level0 row2\" >2</th>\n",
" <td id=\"T_334c0_row2_col0\" class=\"data row2 col0\" >0.00</td>\n",
" <td id=\"T_334c0_row2_col1\" class=\"data row2 col1\" >0.00</td>\n",
" <td id=\"T_334c0_row2_col2\" class=\"data row2 col2\" >0.03</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row3\" class=\"row_heading level0 row3\" >3</th>\n",
" <td id=\"T_334c0_row3_col0\" class=\"data row3 col0\" >0.00</td>\n",
" <td id=\"T_334c0_row3_col1\" class=\"data row3 col1\" >0.02</td>\n",
" <td id=\"T_334c0_row3_col2\" class=\"data row3 col2\" >0.04</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row4\" class=\"row_heading level0 row4\" >4</th>\n",
" <td id=\"T_334c0_row4_col0\" class=\"data row4 col0\" >0.21</td>\n",
" <td id=\"T_334c0_row4_col1\" class=\"data row4 col1\" >0.16</td>\n",
" <td id=\"T_334c0_row4_col2\" class=\"data row4 col2\" >0.10</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row5\" class=\"row_heading level0 row5\" >5</th>\n",
" <td id=\"T_334c0_row5_col0\" class=\"data row5 col0\" >0.22</td>\n",
" <td id=\"T_334c0_row5_col1\" class=\"data row5 col1\" >0.14</td>\n",
" <td id=\"T_334c0_row5_col2\" class=\"data row5 col2\" >0.05</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row6\" class=\"row_heading level0 row6\" >6</th>\n",
" <td id=\"T_334c0_row6_col0\" class=\"data row6 col0\" >0.03</td>\n",
" <td id=\"T_334c0_row6_col1\" class=\"data row6 col1\" >0.02</td>\n",
" <td id=\"T_334c0_row6_col2\" class=\"data row6 col2\" >0.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row7\" class=\"row_heading level0 row7\" >7</th>\n",
" <td id=\"T_334c0_row7_col0\" class=\"data row7 col0\" >0.14</td>\n",
" <td id=\"T_334c0_row7_col1\" class=\"data row7 col1\" >0.11</td>\n",
" <td id=\"T_334c0_row7_col2\" class=\"data row7 col2\" >0.03</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row8\" class=\"row_heading level0 row8\" >8</th>\n",
" <td id=\"T_334c0_row8_col0\" class=\"data row8 col0\" >0.06</td>\n",
" <td id=\"T_334c0_row8_col1\" class=\"data row8 col1\" >0.09</td>\n",
" <td id=\"T_334c0_row8_col2\" class=\"data row8 col2\" >0.02</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row9\" class=\"row_heading level0 row9\" >9</th>\n",
" <td id=\"T_334c0_row9_col0\" class=\"data row9 col0\" >0.07</td>\n",
" <td id=\"T_334c0_row9_col1\" class=\"data row9 col1\" >0.08</td>\n",
" <td id=\"T_334c0_row9_col2\" class=\"data row9 col2\" >0.01</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row10\" class=\"row_heading level0 row10\" >10</th>\n",
" <td id=\"T_334c0_row10_col0\" class=\"data row10 col0\" >0.18</td>\n",
" <td id=\"T_334c0_row10_col1\" class=\"data row10 col1\" >0.16</td>\n",
" <td id=\"T_334c0_row10_col2\" class=\"data row10 col2\" >0.05</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row11\" class=\"row_heading level0 row11\" >11</th>\n",
" <td id=\"T_334c0_row11_col0\" class=\"data row11 col0\" >0.09</td>\n",
" <td id=\"T_334c0_row11_col1\" class=\"data row11 col1\" >0.09</td>\n",
" <td id=\"T_334c0_row11_col2\" class=\"data row11 col2\" >0.05</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row12\" class=\"row_heading level0 row12\" >12</th>\n",
" <td id=\"T_334c0_row12_col0\" class=\"data row12 col0\" >0.05</td>\n",
" <td id=\"T_334c0_row12_col1\" class=\"data row12 col1\" >0.12</td>\n",
" <td id=\"T_334c0_row12_col2\" class=\"data row12 col2\" >0.04</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row13\" class=\"row_heading level0 row13\" >13</th>\n",
" <td id=\"T_334c0_row13_col0\" class=\"data row13 col0\" >0.05</td>\n",
" <td id=\"T_334c0_row13_col1\" class=\"data row13 col1\" >0.10</td>\n",
" <td id=\"T_334c0_row13_col2\" class=\"data row13 col2\" >0.03</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row14\" class=\"row_heading level0 row14\" >14</th>\n",
" <td id=\"T_334c0_row14_col0\" class=\"data row14 col0\" >0.15</td>\n",
" <td id=\"T_334c0_row14_col1\" class=\"data row14 col1\" >0.18</td>\n",
" <td id=\"T_334c0_row14_col2\" class=\"data row14 col2\" >0.06</td>\n",
" </tr>\n",
" <tr>\n",
" <th id=\"T_334c0_level0_row15\" class=\"row_heading level0 row15\" >15</th>\n",
" <td id=\"T_334c0_row15_col0\" class=\"data row15 col0\" >0.05</td>\n",
" <td id=\"T_334c0_row15_col1\" class=\"data row15 col1\" >0.05</td>\n",
" <td id=\"T_334c0_row15_col2\" class=\"data row15 col2\" >0.00</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n"
],
"text/plain": [
"<pandas.io.formats.style.Styler at 0x7f2fc0e51550>"
]
},
"execution_count": 5,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"err_with_offset = meas - expected_with_offset\n",
"pd.DataFrame(np.abs(err_with_offset), columns=d).style.background_gradient(cmap='GnBu', vmin=0, vmax=0.8).format('{:.2f}')"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "2a60a802-7c3f-4697-86ee-4bcf60c75754",
"metadata": {},
"outputs": [],
"source": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 3
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.8.10"
}
},
"nbformat": 4,
"nbformat_minor": 5
}
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