650 lines
365 KiB
Plaintext
650 lines
365 KiB
Plaintext
{
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"cells": [
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{
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"cell_type": "code",
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"execution_count": 13,
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"metadata": {},
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"outputs": [],
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"source": [
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"import uproot\n",
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"import awkward as ak\n",
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"import matplotlib.pyplot as plt\n",
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"import seaborn as sns\n",
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"import numpy as np\n",
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"import mplhep\n",
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"\n",
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"from sklearn.preprocessing import PolynomialFeatures\n",
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"from sklearn.linear_model import LinearRegression, Lasso, Ridge, ElasticNet\n",
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"from sklearn.model_selection import train_test_split\n",
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"from sklearn.pipeline import Pipeline\n",
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"from sklearn.metrics import mean_squared_error\n",
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"\n",
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"mplhep.style.use([\"LHCbTex2\"])\n",
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"input_tree = uproot.open({\n",
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" \"/work/cetin/LHCb/reco_tuner/data/tracking_losses_ntuple_B_BJpsi_def_selected.root\":\n",
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" \"Selected\"\n",
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"})\n",
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"array = input_tree.arrays()\n",
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"\n",
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"array[\"yStraightOut\"] = array[\n",
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" \"ideal_state_770_y\"] + array[\"ideal_state_770_ty\"] * (\n",
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" array[\"ideal_state_10000_z\"] - array[\"ideal_state_770_z\"])\n",
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"array[\"yDiffOut\"] = array[\"ideal_state_10000_y\"] - array[\"yStraightOut\"]\n",
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"array[\"yStraightEndT\"] = array[\"ideal_state_770_y\"] + array[\n",
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" \"ideal_state_770_ty\"] * (9410.0 - array[\"ideal_state_770_z\"])\n",
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"array[\"yDiffEndT\"] = array[\"ideal_state_9410_y\"] - array[\"yStraightEndT\"]\n",
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"\n",
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"array[\"dSlope_xEndT\"] = array[\"ideal_state_9410_tx\"] - array[\n",
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" \"ideal_state_770_tx\"]\n",
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"array[\"dSlope_yEndT\"] = array[\"ideal_state_9410_ty\"] - array[\n",
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" \"ideal_state_770_ty\"]\n",
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"array[\"dSlope_xEndT_abs\"] = abs(array[\"dSlope_xEndT\"])\n",
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"array[\"dSlope_yEndT_abs\"] = abs(array[\"dSlope_yEndT\"])\n",
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"\n",
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"\n",
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"def format_array(name, coef):\n",
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" coef = [str(c) + \"f\" for c in coef if c != 0.0]\n",
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" code = f\"constexpr std::array {name}\"\n",
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" code += \"{\" + \", \".join(list(coef)) + \"};\"\n",
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" return code"
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]
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},
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {},
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"outputs": [],
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"source": []
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},
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{
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"cell_type": "code",
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"execution_count": 2,
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"metadata": {},
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"outputs": [
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{
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"data": {
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",
|
|
"text/plain": [
|
|
"<Figure size 1200x900 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"bins = np.linspace(-200, 200, 50)\n",
|
|
"sns.regplot(\n",
|
|
" x=ak.to_numpy(array[\"ideal_state_770_y\"]),\n",
|
|
" y=ak.to_numpy(array[\"yDiffOut\"]),\n",
|
|
" x_bins=bins,\n",
|
|
" fit_reg=None,\n",
|
|
" x_estimator=np.mean,\n",
|
|
")\n",
|
|
"plt.xlabel(\"y (VELO)\")\n",
|
|
"plt.ylabel(\"$y_{corr}$ [mm]\")\n",
|
|
"mplhep.lhcb.text(\"Simulation\")\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 3,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
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"text/plain": [
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"<Figure size 1200x900 with 1 Axes>"
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]
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},
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"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"bins = np.linspace(-200, 200, 50)\n",
|
|
"sns.regplot(\n",
|
|
" x=ak.to_numpy(array[\"ideal_state_9410_y\"]),\n",
|
|
" y=ak.to_numpy(array[\"yDiffOut\"]),\n",
|
|
" x_bins=bins,\n",
|
|
" fit_reg=None,\n",
|
|
" x_estimator=np.mean,\n",
|
|
")\n",
|
|
"plt.xlabel(\"y (T)\")\n",
|
|
"plt.ylabel(\"$y_{corr}$ [mm]\")\n",
|
|
"mplhep.lhcb.text(\"Simulation\")\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 4,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1200x900 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"bins = np.linspace(-1, 1, 50)\n",
|
|
"sns.regplot(\n",
|
|
" x=ak.to_numpy(array[\"ideal_state_9410_ty\"]),\n",
|
|
" y=ak.to_numpy(array[\"yDiffOut\"]),\n",
|
|
" x_bins=bins,\n",
|
|
" fit_reg=None,\n",
|
|
" x_estimator=np.mean,\n",
|
|
")\n",
|
|
"plt.xlabel(\"ty (T)\")\n",
|
|
"plt.ylabel(\"$y_{corr}$ [mm]\")\n",
|
|
"mplhep.lhcb.text(\"Simulation\")\n",
|
|
"plt.show()"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 20,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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J0/z85z/vfZzP5xUIBIaGA/1YlqU333xTlmXpwYMHk2wRHhCLxdRsNhWNRrW3tzfrdvp60JEuvjS45ouXpQuHYun19XWVy+UTdQchj5sajYaWlpb6fm1/f39gSHaaRCLRN4gulUrKZrMj9ZZKpU7MCsxmsyqVSo7W2Nra0sbGxonPG4aher3e9zXHfx/T+D0AAAAAwKzNw3tupzx9HPKVV17RnTt3es9t2x547GkQ27bPdNwLmJXTQrD19dGPTI7KMAzF4/EToVU6nT5TACZ1++7X+ygBmGmaSqVSRz4XDof1/vvvnzjKOEg+n1c6nVYikTiy++vevXunvuas3zcAAAAAwBs8fRzy+vXrsm1bB5vVCLFwnpx2/G5ax/L6XWeca/d77SjBUq1Wm0gAdrifu3fvHumBwfcAAAAA4F+eDsEOdo0EAoFeGHbWBzBvTguIFhcXp9uIBzQaDa2urp74fKVSOVMAdiAcDk9sphoAAAAAwNs8fRzy8uXLisfjunPnjgqFguLx+JkCgEajoVdeeUUffvjh5JsEfKrfv7UrV65MdD2n/54zmcyJXVrZbNbxEP1BDMNQPp8/81FrLzq40yXD/PszTXMifzsAAAAA5ounQzBJevrpp7W0tKTvf//7Z15jeXlZTz311LncQXOetFotxWKxgTW5XE65XG5KHWESTNPsO1C/UChM7Bo3btzohWCWZXl2/letVlOpVJJpmmo0GgqHw1pcXFQ4HJZhGHr66aclSWtrayoUCgPnrZmmqUwmo8XFRZVKJV+HQo1GQ6ZpqlKpyDRNSfLUDuHz9LsAAACAtxSLRRWLxYE1rVZrSt24z/MhWDKZ1O3btyey1srKykTWgTd1Oh01m82BNe12e0rdYFL6DdMfZ0B/P+FwWNlstu+NCLzAsiytra2pWq1K6u5eO7hTbqPRUK1WU61W63394DWDHOyusyxL6+vrp94Vc541Gg1lMhk1Gg1Pz3s7D78LAAAAeFO73R76PtpPPB+CLS8vT2zHx1/+5V9OZB14UzAYVCQSGVgTCoWm1A0m4WDH03E3btyY+LUymYzK5bLu3bt3poDNNE2VSiXVarXeLq2VlRVlMpmR7oB5Wm8HO5hKpdKJ9RqNhtbX13s1koYGKYuLi54OhibBMIzezLeNjQ3PHnk9D78LAAAAeFMoFFI0Gh1Y02q11Ol0ptSRuzw9GP/A1atXJ7LO3/7t305kHXhTJBLR3t7ewAdHIedLpVLp+/lxhuGfJplMqlAojHxs2rIsJRIJpVIpVavVXmhnWZZM09T6+rqWlpb6Hul0Ymtrqxdu5fP5voGaYRja3t4+8j8Y9AsPDyuVSjIMQ4ZhnPpz9pPjdxb1kvP2uwAAAIB35HK5oe+jh202mSee3wk2STs7O7NuAcAIDu9sOuDmvKR8Pj9SfaPRUCKRGLqL56Bue3t75P43Nzd7H/c7GnpYPp/Xb3/7W21tbenevXsDa5PJ5Lk6djermZDr6+sqlUoDa87b7wIAAACYlbkMwT7++OORjo40Gg2VSiWOmwBzpNFo9N3N5MYusLOwLKs3yymdTiuVSmllZUX37t3T9vZ236N3qVRK9Xrd8V0bzzLLqlAonHqMFNNVLpdVLpeHhmAAAAAApmMuQrCPP/547Dd2tm0rEAhMuDMAbjnt3/rS0tKUO+nvYJdav91dyWRS6+vrSqVSJ76PTCbTm1M1zPEAzDRNR/PFbty4oUwm4+gacMfBnDYAAAAA3uH5mWA3btzQ0tKSyuWy6vW6bNs+0wPAfDktBJvVsbZ+Bh1vPJjTdVytVut7zPO0NQ7b2NhwtDPs4M6R7H6dDcuyPD2DDAAAADivPB2CvfXWWyoUCr0Qi51cwGxtbGwoEAic6ZFIJEa61mkBzlnu3OiGcDg8dL6XYRh9727r9I634XD4yPd7MITfyY5Y27Y987M6TyzL0urqKsdRAQAAAA/ydAh2MBA6EAjItm1dvXpV6XRa+Xxe+XxehUJh6OPgbmq8GQTmi9cHha+srDiqy+fzJ/77x+lOMOlkYNZoNHq7Y8dVq9V6d68cxLIslctlJRKJI9c9OPK3sLCgQCCgpaWlvrPQGo2GNjY2tLS01KtbX1/vG3QeXOd4iHpcKpXqrXf4Mcndb+Vy+ch1FhYWlEgk+n6PUvfnefXq1RN3Aj3c32k/a6e/iwOWZWlra0upVKr38z/ob2Njw1EI12g0tLW1deLupYd/B0tLS73ZdwAAAMDcsz0sEAjYwWDQDgaDtmmaY61Vr9ftYDA4oc7gJdFo1JZkR6PRWbdyqi8e2LZeHPz44sHJ10k68djf359Kz9ls9sS1s9msvbu7e6ZHqVQ6sZ5hGKdeP5/P9/3+K5XKVL7/Yf2k02nHr02n0ye+j93dXcevTyaTfX8W8Xh8pHVs27Z3d3ftbDZrh8Ph3jrhcPhE3f7+vl0oFOx4PH7kmqVSybbt038/B38nBwbVGYZx6t/z8b+/0xQKBUf/PnZ3dx2tZ9u2XalUej+Xw39vu7u7tmEYp/a+v79v7+7unujp+L+Fw+s5+V0cd/jfUqFQsHd3d+16vW5XKpUjv69+f6P7+/t2Pp/vfR+He9zf3z/x+z7cV71eH9obAAAA/Gce3nM75emdYAe7J/L5vFZXV8dayzAMXb16dQJdAefX0tKS4vH4mR5Od04duHLlSt/P37t3bxLfylQ9/fTTJz63s7Pj+PXb29u9OV+H1Wo1JRIJxzt1Go2Gbt265Xi3UTwePzHcfXd3V4lEQrVaTZVKRfV6Xfv7+8rn872acrmsWq2mVCol0zS1vb2t/f197e/va3t7u/ff7Y1Go7fj9zing/37/VzGYZpm79o3btw4sn48HlelUpHU7X1tbe3Ia8PhcO/v/bDj/xYOXj/K7+LAxsaG1tfXFQ6HVa/Xlc/nFY/HZRiG0um0dnd3ez1Xq1UtLS0d+du4d++eUqnUiaO8Ozs7unr1am+WXb1eV6lU6v2uLMti0D8AAADmnqdDsIOh0NeuXZvIetymHpgfpx1hnsdjWccH3Eujfx+VSuXUWWLValULCwtDj0gezCjL5/O6cePGwNqDmWfZbPZIqFMul1UoFHrBnGEYCofDKhQKR4KVRCIhwzC0u7urZDLZm2+WTCZ18+bNI+uNY9I3Shj2fycO/yyq1eqZrzPK7+JAuVzuHcUsFAp9/66k7t/KwdcajcaRQNEwDCWTyRPf58bGhiqViiqVipLJpAzDUDabPfK7Mk1zLv/9AQAAAAc8HYId7P6a1M6PcXeTAZie097ge31WWD/9Ar3f/va3I6+Tz+e1v79/6u6n9fV1pVIpR0HFaT/ffg4HTdls9tQbAhy/I+JpgdLh/i3L8mywcloQe/jzkxiA7/R3sbGx0bt+Npt1VCt1w6t+c+gOfx83b97s+3s9/rc2yg5GAAAAwGs8HYL94Ac/kG3bJ4YMn9VPfvKTiawDwH2nBS2jDJX3in4hx2nHPYcJh8OqVCra3d09cexO6v58VldXJxosOb2xyOHvc5SbkXjpToo3b95UoVBQpVIZGjRJ09uZWC6Xe9dyEpodvyGM0zuS9nP4el76XQEAAACj8nQIdvnyZf3whz/UrVu39I//+I9jr8dxSGC+9At5Go2GZ3cOjWKUnVj9xONx7e7u9v3vtVqtdmJe1TSc9S68XprzFg6Hlc/nT53BNqn/UWZU29vbvY+d/u0cDpLnMTwGAAAAJs3TIZik3tBfp0OST3P37t2ZvXkBcDb9BspL8/mG/nhANG4IdiCbzaper59Yv1qtevrndNbAbNoajYbK5bJM0+w79H6afYzq+N+YH8JjAAAAYBwXZ92AE9vb21pZWdGjjz6qjY0Nx4OQ7927J8uyVK/X9eabb7rcJTBfarWaNjc3e3e786JsNntkttGBUqk08bsCuu14ADHJMOVgAH0ikThynVKpdOqxUgxWq9W0sbGheDw+1lHCSTn8e3UaiB2/8+S9e/fmJnwEAAAA3DAXIdgHH3wgqTsQ+6y3aLdtW4FAYJJtwWNarZZisdjAmlwup1wuN6WOvG1tbW3id9abtHA4rHQ6feIufKZpqlarzWxXzqiOB2BOginTNLWxsaHd3V1H1zAMQzdv3jyya5bdr2ezvr6ucrmsbDbriQBMOtsw/uP/vie1+xAAAAD+USwWVSwWB9a0Wq0pdeM+z4dg3/nOd1QulyVJgUBAtm2PvAbh1/nQ6XTUbDYH1rTb7Sl1420HIdKgN/iTntN01vUKhcKJEEzq3v3u8JykSbAsy5WdMsfvqOckzDcMQ7VaTaZpOt7NdXx3HEPMR3cQgEnjDZOftIO/B+mf7qg57G/18L85AjAAAAD00263h76P9hNPzwS7efOmSqVSL/g6SwA2zuswX4LBoKLR6MBHKBSadZszZ1lWb7fQqEcKf/vb3060FyfBmGEYfcMI0zS1tbU1sV4ajYYSicSZd5sOcnyouZOf+0FoMU4/87JTbhyTDGtrtVovADMMw1NHB4/Pxzvoc5B6vd77eN6ODwMAAGA6QqHQ0PfRwaCno6OReHon2MFdzw52gCWTSaVSKYXD4ZHngr366qv6+OOPXewWsxaJRLS3tzfrNibGjSHWlmVpdXW1t4tk1N0hk+7J6Xr5fF7b29snBr0fzGwad+6VaZpKpVKnBm7jOryTbZS71BqGoUajoY2NDUd9Hd/5ddqNBebB8f+OP23n0yR3ux3++xq07iwGzKfTaYXD4d61S6WS8vn8wNcc/n5u3LjhZnsAAACYU05GBsViMd/sFvN0CFar1RQIBBQOh7Wzs6OrV6+eea21tTVduXJlgt0B7jrtTfhZh1ubpqn19fXeutevXx/5+uPsuhk3rNje3lYmkzlxNDKVSqlQKAwNBPqxLEsbGxsql8u94fJOf7ZOg5Byudz73rPZ7EiB3UEItrW1paWlJWWz2YH1hwM2wzDO9DPpx+n3erhu2GuGff34LrZyuXzi+zkICA+b5PD3arV6YgdVv+sddzxcbjQaRz531mO3h2e+NRqNgUdla7Va7/hkoVDw1K42AAAAYFY8vaft4P9pv3HjxlgB2MFay8vLE+gKmI7TdgwdDrIGsSyrN1x9aWlJqVTqyOtSqdSpr200Gn2Hqler1TPvgjnt+3FyrOtApVLpG+xsbGwokUic2Cl2GsuytLW1patXr6pcLiuZTI4UgEkn53z102g0escZk8nkSLvApKNhyvr6utbX10/9+ZfL5SPHQ4fNSzsc3sxiZ9Nhp13/cMCzsbGh9fV1maaparWq9fV1LS0tnQh4BoXHw655PHjLZDLa2trqHb1dWlo6EWiVSqXev7ODNY+HYAe/t4O/h+N/805/F+l0+siOwEwm07fesiytra1J6gavp4WhTn/vh3+ms/5bAQAAAMZie1gymbSDwaD91ltvTWS9Wq02kXXgLdFo1JZkR6PRWbdyqi8e2LZeHPz44kG3dnd3106n07YkVx/7+/sn+tzf37dLpZIdDodPfZ1hGHapVOr7+n52d3ftZDI5sJd8Pm/X63XHP8/t7W07Ho/3XSscDtvpdNoulUr29va2vbu7a29vb9ulUskuFApHXhcOh+1KpeLomvV6ve/PYnt7u299pVLp/RzT6bTj7+2wUqnU93tMp9N2Pp+3S6WSnc1mbcMwel9LJpOOfpbHf36n/Rz29/eP1MXj8VPXPP53WyqV+tZtb28fqctms6de+7S/xXA43PvZH66Jx+N2vV4/8ffptLdB//YKhYJt27adzWb7/k4Oy+fzfdfo9706/V0cOPy3FQ6H7VKpZNfrdbter9ulUqn393DQbz9OfwfH65LJ5MDeAAAA4D/z8J7bKU+HYJVKxQ4EAvZf//Vfz7oVeNg8/IN0EoL9+Mf9Aw83Hv2CjLOsEw6HT/2ezxrknRYq9VOpVE4NwwY9DMOwC4WC4yDvQL1e7/t9hcNhO5lM2ul02k4mk0cCilG+n+O2t7d7QV2lUrGz2aydTCbteDx+JPg5CP6GXesgYD0tWIrH473gZFCtYRh2Op3u/fyOB3HHQ5ODNbe3t08NRA3D6BvE7O/vH1k/Ho/b+Xz+SM3B546Hf/v7+0O/337XLBQKvesZhmHn8/kjfyv7+/u97+Pwz+y4fD5/pO/D4dYov4vTlEqlE39vB6877W97UCh9+HdQr9cH1g3rDQAAAP4xD++5nQrYtrdvnZhIJBQMBnX79u2x1/r5z3+uP/3TP51AV/CSgyF90WjUs4PxH3Skiy8NrvniZemCpw8oe9fB0c9bt26p0Wj0jp5J/3SXP8MwdO3aNaXT6ZFvCDDsegfXPLjOysqKMpnM2AP7AQAAAGDW5uE9t1OeD8EajYb+8A//UG+99Za++c1vjrXWtWvXJhKmwVvm4R8kIRgAAAAAYB7Nw3tupzz/ltswDL366qv69re/PdY69+/f7zvoGwAAAAAAAP53cdYNDPLzn/9ckvTP/tk/08LCgh599NETt6t3wrIsvfnmm5NuDwAAAAAAAHPC0yHYK6+8ojt37vSe27atra2tM61l27YCgcCkWgMAAAAAAMAc8fRxyOvXr8vu3sFSkgixAAAAAAAAcCaeDsHW19cldcOvgzDsrA8AAAAAAACcX54+Dnn58mXF43HduXNHhUJB8Xhci4uLI6/TaDT0yiuv6MMPP5x8kwAAAAAAAPA8T4dgkvT0009raWlJ3//+98+8xvLysp566qkzBWgAAAAAAACYf54+DilJyWRyYscZV1ZWJrIOAAAAAAAA5ovnQ7Dl5WUVCoWJrDWpdQAAAAAAADBfPH8cUpKuXr06kXWWl5cnsg68qdVqKRaLDazJ5XLK5XJT6ggAAAAAAO8qFosqFosDa1qt1pS6cd9MQ7APP/xQ//Jf/stZttDjpV5wNp1OR81mc2BNu92eUjcAAAAAAHhbu90e+j7aT2YagiUSCe3v7ysUCs2yDd2/f1+JREIPHjyYaR8YTzAYVCQSGVgz6781AAAAAAC8IhQKKRqNDqxptVrqdDpT6shdMw3BJjXwfhK81AvOJhKJaG9vb9ZtAAAAAAAwF5yMDIrFYr7ZLTbTwfiBQGCWlz/CS70AAAAAAABgsmYagrH7CgAAAAAAANMw0xBMku7evTvrFrSzszPrFgAAAAAAAOCimc4Ek6S1tTW9+OKLCofDWlxcnOq17927p0ajoXw+P9XrnlWj0dD6+rrW19eVTqencq3t7W1H9VtbW9re3tbOzo4sy5JhGIrH41pfX1cymXS1VwAAAAAAgGFmHoLt7u4qk8nMtAfbtj09E8yyLK2tralarUrSWD8vy7K0sLDgqDabzQ6tMU1TmUxGlmUpmUyqUqnIMAzVajVtbGwolUr1Ph8Oh8/cNwAAAAAAwDhmHoIdmNV8MK+HX5ubm9ra2prYmuVy2XHtxsbGwK+bpqlUKiWpG5iVSqXe1wzDUDqdViKRkGmaSiQS2t3dJQgDAAAAAAAzMfOZYLZtz3RAvleH829tbSmRSKhWq0103c3NTUd1yWRShmGc+nXLsno70gzDOBKAHVapVCR1j1fOescfAAAAAAA4v2a6E2x/f3+Wl/esWq2mZDLZm1VWLpe1vr4+9rrlclmWZSmfz/d2cJ1mZWVl4NcPjkBKg3eMHewIq1arMk1T5XLZ0TFLAAAAAACASZppCHb58uVZXt6z4vH4kefDAimnCoWCDMNQoVAYa51GoyHTNHvPr1+/PrD+6aef7s0z29jYIAQDAAAAAABTN/PjkBhuEnO0qtWqGo3G0DlfThwO0ZLJ5ND+Dt/J0rKsXiAGAAAAAAAwLYRg58Tm5qbC4fDQXVtOHB6uf3zX2mkOzxe7devW2D0AAAAAAACMghDsHKjVaqrVarIsSwsLC1paWtL6+vqZdmQdH9R/7do1R687HJaxEwwAAAAAAEwbIdg5cPwIZKPRULlcViaTUSAQUCaTcXwXysOzwCQNvIPkoLpJ3/USAAAAAABgEEIwnzs+xL6farWqRCLh6A6Ut2/fPvLc6byyK1euHHm+s7Pj6HUAAAAAAACTMNO7Q8J9hmGoVCrJsizV63WZpqlGo9G3tlwua2dnR7u7u6eud/y1Z90JVq/XHb0OAAAAAABgEgjBzoFsNnvkuWVZKpfL2tzclGVZR75Wq9WUSqW0vb3dd63TArRRHb/uJLRaLcVisbHXyeVyyuVyE+gIAAAAAIDZKBaLKhaLY6/TarUm0I03EIKdQ+FwWPl8Xvl8XtVqVWtra0dCKdM0tbW1pXw+f+K1Zw2vjh+bvHfv3pnWGaTT6ajZbI69TrvdnkA3AAAAAADMTrvdnsh7ZD8hBDvn0um0ksmkVldXjwyr39zc7BuCTYobO8GCwaAikcjY64RCoQl0AwAAAADA7IRCIUWj0bHXabVa6nQ6E+ho9gjBoHA4rN3dXSUSiV4QZlmWTNNUMpk8UTuJAMvpQP1RRCIR7e3tTXxdAAAAAADmzaRG/cRiMd/sKOPukOi5efPmkef95oItLi5O5FqTWgcAAAAAAMAJQjD0xOPxIzu/+g3BP+sOruO7x9zYCQYAAAAAAHAaQjAckUqlBn59ZWXlyHOnRyOPD8JfWloaqS8AAAAAAIBxEILhCMMweh/3O7KYSCSOPO+3W6yfer1+5PnxWWMAAAAAAABu8l0I9sEHH+jpp5/WT3/601m3MpcOh2D9jiwe3wnmNAQ7vGMsHA4fuQ4AAAAAAIDbfBeCpdNpVatVZbNZtdvtWbczd3Z2dnof9zsaGY/Hj4Rjt2/fHnnd40EaAAAAAACA23wXgl29elWStLy8rFAoNONu5s/hY4unHVm8fv167+NareZo3cN1GxsbZ+wOAAAAAADgbHwXglUqFdm2rZ/85CezbmUuVatVSVI+nz+1Zn19vfexaZpD1zxcYxgG88AAAAAAAMDU+S4EMwxDOzs7Wltb029+85tZtzMRTu/AOK5qtapGo6FwOKwbN26cWhePx48EWQfB2WkqlUrvY3aBAQAAAACAWfBdCCZ1QxrTNLW2tjYwzJkXx4fPOw3FTNPUwsKCAoGAUqnUwKOLjUZDa2trkqT333+/71D8w0qlUu/jzc3NU+ssy1K5XJbUPV6ZzWYd9Q4AAAAAADBJvgvBFhcXde3aNRUKBb3wwgsyDEPXrl3T3/zN38y6tTOxLOvE7qlbt245em2lUukFZqZpKpFIHDnKeODga4uLi6rX64rH40PXNgyjt8OrVqtpa2urb93q6qqk7h0hD+8IAwAAAAAAmKaAbdv2rJuYpK9//esyTVOBQKD3OcMwdO/ePUndeVbZbFZf+cpXZtThcJZlaW1tTZZlDZy5lUwme0cX+wVXpmn2vcNjOBxWMpnU4uKidnZ2VKvVlM/ndePGjaE7wPpdI5PJyLIspdNp3bhxo3ckdWNjQ7VaTfF43NHusrOKxWJqNpuKRqPa29tz5RrjetCRLr40uOaLl6ULvoulAQAAAADzbB7eczvluxDsxRdfVLlcVjKZVK1WO3GU8CAcMwxDL7zwgp566ilPB2LjajQaKhQKMk1T9+7dk2VZCofDWlxcVDwe19NPP90L08axtbWlW7duqdFo9K6xsrKi9fV1pdPpyXwzp5iHf5CEYAAAAACAeTQP77md8l0I9tZbbykcDveO4d2/f1+maWp7e1umaR4JxQ4CsYWFBf3DP/zDTPrF+ObhHyQhGAAAAABgHs3De26nLs66gUmLx+NHBsdfvnxZTz31lJ566ilJ0t27d4+EYpZlaX9/f0bdAgAAAAAAYBp8F4JdvXp16NfX1tZ6d0K8c+fOwLlbmB+tVkuxWGxgTS6XUy6Xm1JHAAAAAAB4V7FYVLFYHFjTarWm1I37fBeCffDBByqVSvr617+uv/iLvxhav7y8rOXl5Sl0Brd1Oh01m82BNe12e0rdAAAAAADgbe12e+j7aD/xXQiWTqd1//59VatVZTIZhUKhWbeEKQkGg4pEIgNrvPz38MYd6bnErLsAAAAAAJwXoVBI0Wh0YE2r1VKn05lSR+7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",
|
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"text/plain": [
|
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"<Figure size 1200x900 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
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|
}
|
|
],
|
|
"source": [
|
|
"bins = np.linspace(-0.5, 0.5, 50)\n",
|
|
"sns.regplot(\n",
|
|
" x=ak.to_numpy(array[\"ideal_state_770_ty\"]),\n",
|
|
" y=ak.to_numpy(array[\"yDiffOut\"]),\n",
|
|
" x_bins=bins,\n",
|
|
" fit_reg=None,\n",
|
|
" x_estimator=np.mean,\n",
|
|
")\n",
|
|
"plt.xlabel(\"$t_y$\")\n",
|
|
"plt.ylabel(\"$y_{corr}$ [mm]\")\n",
|
|
"mplhep.lhcb.text(\"Simulation\")\n",
|
|
"plt.show()\n",
|
|
"# plt.savefig(\n",
|
|
"# \"/work/cetin/LHCb/reco_tuner/parameterisations/plots/bend_y_ty_dist.pdf\",\n",
|
|
"# format=\"PDF\",\n",
|
|
"# )"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 21,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
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"image/png": 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",
|
|
"text/plain": [
|
|
"<Figure size 1200x900 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"bins = np.linspace(-0.5, 0.5, 100)\n",
|
|
"sns.regplot(\n",
|
|
" x=ak.to_numpy(array[\"dSlope_yEndT\"]),\n",
|
|
" y=ak.to_numpy(array[\"yDiffOut\"]),\n",
|
|
" x_bins=bins,\n",
|
|
" fit_reg=None,\n",
|
|
" x_estimator=np.mean,\n",
|
|
")\n",
|
|
"plt.xlabel(\"$\\Delta t_y$\")\n",
|
|
"plt.ylabel(\"$y_{corr}$ [mm]\")\n",
|
|
"mplhep.lhcb.text(\"Simulation\")\n",
|
|
"plt.show()\n",
|
|
"# plt.savefig(\n",
|
|
"# \"/work/cetin/LHCb/reco_tuner/parameterisations/plots/bend_y_deltaty_dist.pdf\",\n",
|
|
"# format=\"PDF\",\n",
|
|
"# )"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 25,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
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"image/png": 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",
|
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"text/plain": [
|
|
"<Figure size 1200x900 with 1 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
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}
|
|
],
|
|
"source": [
|
|
"bins = np.linspace(-1.0, 1.0, 50)\n",
|
|
"sns.regplot(\n",
|
|
" x=ak.to_numpy(array[\"dSlope_xEndT\"]),\n",
|
|
" y=ak.to_numpy(array[\"yDiffOut\"]),\n",
|
|
" x_bins=bins,\n",
|
|
" fit_reg=None,\n",
|
|
" x_estimator=np.mean,\n",
|
|
")\n",
|
|
"plt.xlabel(\"$\\Delta t_x$\")\n",
|
|
"plt.ylabel(\"$y_{corr}$ [mm]\")\n",
|
|
"mplhep.lhcb.text(\"Simulation\")\n",
|
|
"plt.show()\n",
|
|
"# plt.savefig(\n",
|
|
"# \"/work/cetin/LHCb/reco_tuner/parameterisations/plots/bend_y_deltatx_dist.pdf\",\n",
|
|
"# format=\"PDF\",\n",
|
|
"# )"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 55,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"name": "stdout",
|
|
"output_type": "stream",
|
|
"text": [
|
|
"intercept= 0.16257747434812642\n",
|
|
"coef= {'dSlope_yEndT': 4379.8079670973475, 'dSlope_xEndT dSlope_yEndT': 37.76975769672208, 'ideal_state_770_ty dSlope_xEndT^2': 1224.0422108322969, 'ideal_state_770_ty dSlope_yEndT^2': -18042.13200642719}\n",
|
|
"r2 score= 0.8441034202616307\n",
|
|
"RMSE = 10.185808113150346\n"
|
|
]
|
|
}
|
|
],
|
|
"source": [
|
|
"features = [\n",
|
|
" \"ideal_state_770_ty\",\n",
|
|
" # \"ideal_state_9410_ty\",\n",
|
|
" # \"ideal_state_770_y\",\n",
|
|
" # \"ideal_state_9410_y\",\n",
|
|
" \"dSlope_xEndT\",\n",
|
|
" \"dSlope_yEndT\",\n",
|
|
"]\n",
|
|
"target_feat = \"yDiffOut\"\n",
|
|
"order = 3\n",
|
|
"\n",
|
|
"data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
|
|
"target = ak.to_numpy(array[target_feat])\n",
|
|
"X_train, X_test, y_train, y_test = train_test_split(data,\n",
|
|
" target,\n",
|
|
" test_size=0.2,\n",
|
|
" random_state=42)\n",
|
|
"\n",
|
|
"poly = PolynomialFeatures(degree=order, include_bias=False)\n",
|
|
"X_train_model = poly.fit_transform(X_train)\n",
|
|
"X_test_model = poly.fit_transform(X_test)\n",
|
|
"\n",
|
|
"poly_features = poly.get_feature_names_out(input_features=features)\n",
|
|
"\n",
|
|
"# keep = [\n",
|
|
"# # \"ideal_state_770_ty\", #\n",
|
|
"# # \"dSlope_xEndT\", #\n",
|
|
"# \"dSlope_yEndT\", # keep\n",
|
|
"# # \"ideal_state_770_ty^2\", #\n",
|
|
"# # \"ideal_state_770_ty dSlope_xEndT\", #\n",
|
|
"# # \"ideal_state_770_ty dSlope_yEndT\", #\n",
|
|
"# # \"dSlope_xEndT^2\", # do not keep\n",
|
|
"# \"dSlope_xEndT dSlope_yEndT\", # keep\n",
|
|
"# # \"dSlope_yEndT^2\", #\n",
|
|
"# # \"ideal_state_770_ty^3\",\n",
|
|
"# # \"ideal_state_770_ty^2 dSlope_xEndT\", #\n",
|
|
"# # \"ideal_state_770_ty^2 dSlope_yEndT\",\n",
|
|
"# \"ideal_state_770_ty dSlope_xEndT^2\", # keep\n",
|
|
"# # \"ideal_state_770_ty dSlope_xEndT dSlope_yEndT\", #\n",
|
|
"# \"ideal_state_770_ty dSlope_yEndT^2\", # keep\n",
|
|
"# # \"dSlope_xEndT^3\", # do not keep\n",
|
|
"# # \"dSlope_xEndT^2 dSlope_yEndT\", #\n",
|
|
"# # \"dSlope_xEndT dSlope_yEndT^2\", #\n",
|
|
"# # \"dSlope_yEndT^3\",\n",
|
|
"# # \"ideal_state_770_ty^4\",\n",
|
|
"# # \"ideal_state_770_ty^3 dSlope_xEndT\",\n",
|
|
"# # \"ideal_state_770_ty^3 dSlope_yEndT\",\n",
|
|
"# # \"ideal_state_770_ty^2 dSlope_xEndT^2\", #\n",
|
|
"# # \"ideal_state_770_ty^2 dSlope_xEndT dSlope_yEndT\",\n",
|
|
"# # \"ideal_state_770_ty^2 dSlope_yEndT^2\",\n",
|
|
"# # \"ideal_state_770_ty dSlope_xEndT^3\", # do not keep\n",
|
|
"# # \"ideal_state_770_ty dSlope_xEndT^2 dSlope_yEndT\", #\n",
|
|
"# # \"ideal_state_770_ty dSlope_xEndT dSlope_yEndT^2\",\n",
|
|
"# # \"ideal_state_770_ty dSlope_yEndT^3\",\n",
|
|
"# # \"dSlope_xEndT^4\", #\n",
|
|
"# \"dSlope_xEndT^3 dSlope_yEndT\", # keep\n",
|
|
"# # \"dSlope_xEndT^2 dSlope_yEndT^2\", #\n",
|
|
"# # \"dSlope_xEndT dSlope_yEndT^3\",\n",
|
|
"# # \"dSlope_yEndT^4\",\n",
|
|
"# # \"ideal_state_770_ty^5\",\n",
|
|
"# # \"ideal_state_770_ty^4 dSlope_xEndT\",\n",
|
|
"# # \"ideal_state_770_ty^4 dSlope_yEndT\",\n",
|
|
"# # \"ideal_state_770_ty^3 dSlope_xEndT^2\",\n",
|
|
"# # \"ideal_state_770_ty^3 dSlope_xEndT dSlope_yEndT\",\n",
|
|
"# # \"ideal_state_770_ty^3 dSlope_yEndT^2\",\n",
|
|
"# # \"ideal_state_770_ty^2 dSlope_xEndT^3\", #\n",
|
|
"# # \"ideal_state_770_ty^2 dSlope_xEndT^2 dSlope_yEndT\",\n",
|
|
"# # \"ideal_state_770_ty^2 dSlope_xEndT dSlope_yEndT^2\",\n",
|
|
"# # \"ideal_state_770_ty^2 dSlope_yEndT^3\",\n",
|
|
"# \"ideal_state_770_ty dSlope_xEndT^4\", # keep\n",
|
|
"# # \"ideal_state_770_ty dSlope_xEndT^3 dSlope_yEndT\", #\n",
|
|
"# # \"ideal_state_770_ty dSlope_xEndT^2 dSlope_yEndT^2\",\n",
|
|
"# # \"ideal_state_770_ty dSlope_xEndT dSlope_yEndT^3\",\n",
|
|
"# # \"ideal_state_770_ty dSlope_yEndT^4\",\n",
|
|
"# # \"dSlope_xEndT^5\", #\n",
|
|
"# \"dSlope_xEndT^4 dSlope_yEndT\", # keep\n",
|
|
"# # \"dSlope_xEndT^3 dSlope_yEndT^2\", #\n",
|
|
"# # \"dSlope_xEndT^2 dSlope_yEndT^3\",\n",
|
|
"# # \"dSlope_xEndT dSlope_yEndT^4\",\n",
|
|
"# # \"dSlope_yEndT^5\",\n",
|
|
"# ]\n",
|
|
"\n",
|
|
"keep = [\n",
|
|
" \"dSlope_yEndT\", # keep\n",
|
|
" \"dSlope_xEndT dSlope_yEndT\", # keep\n",
|
|
" \"ideal_state_770_ty dSlope_xEndT^2\", # keep\n",
|
|
" \"ideal_state_770_ty dSlope_yEndT^2\", # keep\n",
|
|
" # \"dSlope_xEndT^3 dSlope_yEndT\", # do not keep\n",
|
|
" # \"ideal_state_770_ty dSlope_xEndT^4\", # keep\n",
|
|
" # \"dSlope_xEndT^4 dSlope_yEndT\", # keep\n",
|
|
"]\n",
|
|
"\n",
|
|
"# keep = [\n",
|
|
"# \"ideal_state_770_ty dSlope_yEndT^2\",\n",
|
|
"# \"ideal_state_770_ty dSlope_xEndT^2\",\n",
|
|
"# ]\n",
|
|
"remove = [i for i, f in enumerate(poly_features) if f not in keep]\n",
|
|
"\n",
|
|
"X_train_model = np.delete(X_train_model, remove, axis=1)\n",
|
|
"X_test_model = np.delete(X_test_model, remove, axis=1)\n",
|
|
"poly_features = np.delete(poly_features, remove)\n",
|
|
"# print(poly_features)\n",
|
|
"lin_reg = LinearRegression()\n",
|
|
"# lin_reg = Lasso(fit_intercept=False, alpha=0.000001)\n",
|
|
"# lin_reg = Lasso(alpha=0.1)\n",
|
|
"# lin_reg = LassoCV(max_iter=2000)\n",
|
|
"# lin_reg = ElasticNet(alpha=0.1)\n",
|
|
"# lin_reg = Ridge(alpha=0)\n",
|
|
"lin_reg.fit(X_train_model, y_train)\n",
|
|
"y_pred_test = lin_reg.predict(X_test_model)\n",
|
|
"print(\"intercept=\", lin_reg.intercept_)\n",
|
|
"print(\"coef=\", dict(zip(poly_features, lin_reg.coef_)))\n",
|
|
"print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
|
|
"print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 45,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"['dSlope_xEndT^2', 'dSlope_xEndT^3']"
|
|
]
|
|
},
|
|
"execution_count": 45,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": [
|
|
"koeffs = dict(zip(poly_features, lin_reg.coef_))\n",
|
|
"\n",
|
|
"remove = []\n",
|
|
"for itr in koeffs.items():\n",
|
|
" if abs(itr[1]) < 1.0:\n",
|
|
" remove.append(itr[0])\n",
|
|
"remove"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 50,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"ls_koeffs = []\n",
|
|
"for itr in koeffs.items():\n",
|
|
" ls_koeffs.append(itr[0])\n",
|
|
"# ls_koeffs"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 65,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"text/plain": [
|
|
"['1', 'dSlope_xEndT^2', 'dSlope_xEndT^3', 'dSlope_xEndT^6']"
|
|
]
|
|
},
|
|
"execution_count": 65,
|
|
"metadata": {},
|
|
"output_type": "execute_result"
|
|
}
|
|
],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": 59,
|
|
"metadata": {},
|
|
"outputs": [
|
|
{
|
|
"data": {
|
|
"image/png": 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6DcATgjAAAAAAwNgY5d6zbMzvj4WFBZ06dapjDUEZxkXIdV036CYAP83Pz6vRaGhubk53794Nup2ZwWb5AAAAmDQEYaPD5zSMC2aEAQAAAABm0qi+zCVwA8YHQRgwQuvr69rb29PCwoLW1taGPh6ztDAp3vjbv9WvfvUrffCDH9Rn/uiPgm4HGBu8NoCj8doAjjbqzxvAJCIIA0ZofX1dt2/f1qlTp3hjAlq88cYb+te9Pf32wgIfaIAWvDaAo/HaAI7G5w2gO4IwTK1Go6HTp093rFlbW+MNAgAAAACAGUEQhqnW7cwke3t7I+oEAAAAwKwa1ZYlH/zjz0r/T2kkYwGTiiAMU63bKXwXFhZG1Mlv/Ic/+xN9cGGB/bsAAAAAABixuaAbAIZlbm5Ot27d6nhhWSQAAAAATK58Pq94PK7FxUWFQiFFIhElk0lVq9WJHDvIxzMrCMIAAAAAAMBEqVarWlxcVDablSSVSiXV63XlcjlZlqV4PK54PC7HcSZi7CAfz6xhaSQAAAAAAJgY1WpV8XhckpRKpVQoFJq/MwxDiURC0WhU1WpV0WhUtVpN4XB4bMcO8vHMImaEAQAAAACAieA4jpLJpKT9kKg1NGpVKu2fNMC27Wb9OI4d5OOZVcwIA9CzN/72b/WrX/1KH/zgB/WZP/qjoNvpG48DfpuWf4tpeBzT8BimyTT8e0zDY5Cm53FMi2n495iGxyBNz+OYBclksrk88GAZ4VEOZlKVy2VVq1UVi0WlUqmxGzvIxzOrmBEGoGdvvPGG/t///b/1xhuTfeZLHgf8Ni3/FtPwOKbhMUyTafj3mIbHIE3P45gW0/DvMQ2PQZqexzHtbNtu2zR+dXW1Y/2FCxea1zuFTEGNHeTjmWUEYQAAAAAAYOzlcrnm9Vgs1nWfrEQi0bzuOI7K5fJYjR3k45llBGEAAAAAAGDsFYvF5nXTND3dxzCM5vWNjY2xGjvIxzPLCMIAAAAAAMBYsyyr7fb58+c93a81YOp3BtUwxg7y8cw6gjAAAAAAADDWWvfSktpnRnVyuO5wABXU2EE+nllHEAYAAAAAAMba1tZW2+1u+2kdeOCBB9pub29vj8XYQT6eWUcQBgAAAAAAxppt2223+51BVa/Xx2LsIB/PrCMIAwAAAAAAY+1wcNQvx3HGYuwgH8+sC7mu6wbdBOCnUCjUvD43N15Zb6PR0NyJD0qSQmPWWy/cRqN5nccRvGl4HNPwGCQexziZhscg8TjGyTQ8BonHMW6m4XFMw2OQputxNN79lST/Pgu5riu/Y4N+jtf6Oa+XY1SrVcXj8ebtRCKhUqkU+NhBPp5Zd1/QDQDD1Gh5QxsXB29MAAAAADAs4/hZaBwEOYNqGGMzI6x3BGGYauM2IwwAAAAAJskwZoT1IxwO+xL6eN2UfthjB/l4Zh1BGKbOOPxHGgAAAADgn6WlJV+Co6WlpbEYO8jHM+uYLgMAAAAAAMZavzOfDodN/c4I83vsIB/PrCMIAwAAAAAAY215ebntttfZVDs7O223I5HIWIwd5OOZdQRhAAAAAABgrEWj0bbbtm17ul+9Xm+7HYvFxmLsIB/PrCMIAwAAAAAAY+3wDCqvwVHrTKtwOCzDMMZi7CAfz6wjCAMAAAAAAGPNNM22/bC2trY83W97e7t5/XD4FOTYQT6eWUcQBgAAAAAAxt7q6mrzumVZnu7TWpfNZsdq7CAfzywLua7rBt0EAAAAAABAJ5Zlte2t1S3OqFarisfjkiTDMO7ZXyvosYN8PLOMGWEAAAAAAGDsmabZtjl8uVzuWF8qlZrXu82eKhaLymazx+7VNYyxh/l4cDxmhAEAAAAAgIlg27YikYik/SCpVqsdWec4jhYXFyXtn1mxUqkce8x4PK5qtdq8vbu727Z/1zDHHsYx0RkzwgAAAAAAwEQwDKM5M8qyLOXz+SPrVlZWJO2fWbF1JtVRWkMwSdrc3BzZ2MM4JjojCAMAAAAAABMjkUioUqkoHA4rm80qmUzKsiw5jqNqtapoNCrLsmSapm7cuHHk7K5Wh39vGMbIxh7WMXE8gjAgYJFIRKFQqOt68KPk83nF43EtLi4qFAopEokomUze840GMI4sy1I6nW6+Bg6ew9lsVo7j9H1cXheYBjyPMQt4HwD6w+eHfbFYTLu7u8rlcrJtWysrK1pcXFQymdTS0pJKpZJqtZqn0KhUKskwDIXDYWUymbZ9u4Y99jCPiWO4AAKTyWRcSa4kt1Qqeb5fpVJxw+GwK8mNxWJupVJx6/W6WyqVXMMwmj/f3d0dXvNAn3Z3d91EItF87h93KRQKPR2X1wWmAc9jzALeB4D+8fkBGBxBGBCQSqXS9see1zey1vulUqkja0zTdCW5hmHwZoaxsru72/xjy8vluOf4YbwuMA14HmMW8D4A9I/PD4A/OGskEADHcXTmzJm2af+lUkmJRMLz/QzDUL1eP7Ku9cwjnFEE4+TgjDymaerSpUsyTVPS/vKYra2tIzcH7fba4HWBacDzGLOC9wGgP3x+AHwUdBIHzKJEIuEahtGcniyP3+jEYjHPywValxz0urQAGIZCoeBKcjOZzLE19Xq9+Y3kwSUcDnc8Lq8LTAOex5gFvA8A/ePzA+AfZoQBI1YsFpVOp1Wr1bSystL8VqfbNzqt39JI0u7ubseNEsvlspLJpKT9s6Ds7u760j/Qr0gkIsMwun7DePi5LkmVSuXITUt5XWAa8DzGrOB9AOgPnx8Af3HWSGCEbNtWOp1WJpNpLgXwKpfLNa/HYrGuZwtpfVN0HKevs8oAfrEsS7Ztq1Qqda01DKPt+X5w/6PwusA04HmMWcD7ANAfPj8A/iMIA0YomUzKNM17/rjzolgsNq97fRM0DKN5fWNjo+cxAb9sbGwolUp5Pt3z4W/933777SPreF1gGvA8xizgfQDoD58fAP/dF3QDwKzIZrOyLOvYDSo7Ofwt6Pnz5z3dzzRN2bYtSXyjg0BduHCh7Q+rbg7/sXZ4iYzE6wLTgecxZgXvA0Dv+PwADAczwoARsCxL+XxehUKhpz8CD1Sr1bbbXo9xuO64ZQXAsJmm6XkWgKS2MyJJRz/neV1gGvA8xqzgfQDoDZ8fgOEhCANGYGVlRYlEQqlUqq/7b21ttd32+ofkAw880HZ7e3u7r/GBUTv4JvLAURsk87rANOB5DByN9wHMOj4/AMNDEAYM2cGZV65evdr3MQ7/MdjvNzr9TKsGgtD6R9dxfwDyusA04HkMHI33AcwyPj8Aw8UeYcAQlctllctlVSqVnpYDHHb4jaxfh5cZAOOqUCg0r2ez2SNreF1gGvA8Bo7G+wBmFZ8fgOFjRhgwJI7jKJlMKpVKHTmdv9dj9ePwm+fOzs5AfQCjYNt2cz+KXC537DeYvC4wDXgeA/fifQCzis8PwGgQhAFDsrKyIsMw2r7RDBrf6GASHJwe3DAMZTKZoY/H6wLTgOcxpgnvA5hVfH4ARoMgDBiCfD4vy7JUKpV8Od4g06KHcRxgWCzLUrFYVDgcVqVS6VjL6wLTgOcx0I73AcwqPj8Ao0MQhplSLBYVCoV8vUSj0bYxLMtSNptVLpeTaZq+9L20tDRWx8F0GcXrwquLFy9Kkq5du9Z1U1deF5gGPI+BdrwPYBbx+QEYLYIwwGfJZFKmafo6lb/fb2IOT2XmGx2Ms3Q63fwm1MsfgbwuMA14HgO/wfsAZhWfH4DR4qyRmCmxWMy36cYHWt8c8vm8bNtWLBZrnva4k9Y3msuXL2tjY6N5+8KFC0okEpKk5eXl5qaxB/fz8qZ0eHPLSCTS9T6YPcN+XXhRLBZVLBZVKBSaz/tueF1gGvA8BvbxPoBZxecHYPQIwjBTDMPoOs1+EG+//bYkqVqt9nxfy7La3qwMw2i+kR1eZmbbtqdvSuv1etvtQc8+g+k07NdFN9VqVel0WoVCQalUyvP9eF1gGvA8BngfwGzj8wMweiyNBCbA8vJy223btj3dr/Ubo3A4HGjYARzFsizF43HlcrmePvxIvC4wHXgeY9bxPgAMB68P4HgEYYCPcrmcXNf1fGl9YymVSm2/Ozh1uCSZptk2lXlra8tTP9vb283rh98MgaDZtq2VlRVlMpm+9sTgdYFpwPMYs4z3AYDPD0AQCMKACbG6utq83joFupPWumw263tPQL9s21Y0GlUqlWr7o63bffL5fNvPeF1gGvA8xizifQAYPl4fwNEIwoAJkU6nm9e97CHQWmMYBuv7MTYcx1E8Htfq6qrnDz/S/hmVDj+PeV1gGvA8xqzhfQAYDV4fwNEIwoAJYZpm25tRuVzuWN96FkC+zcG4cBxH0WhUhmEom83Ktu2ul2q12tzw9fAmr7wuMA14HmOW8D4AjA6vD+BoIdd13aCbAGZVJBJpblxZKpW6ni7ctu3mKYxN01StVjuyznEcLS4uSto/00ulUvGxa6B/0WjU89T8w447mxivC0wDnseYFbwPAIPh8wMwOGaEARPEMIzmNzWWZd2zT8aBlZUVSftnemn9ZgcI0iAffiQdezYxXheYBjyPMQt4HwBGj9cHcC+CMGDCJBIJVSoVhcNhZbNZJZNJWZYlx3GaSwcsy5Jpmrpx40bb2WKAoBw8T/t13IefA7wuMA14HmOa8T4ABIfXB9COpZHABMvn89rY2JBt23IcR+FwWMvLy0qn012nSQPTitcFpgHPY6B/vH6A4/H6AAjCAAAAAAAAMCNYGgkAAAAAAICZQBAGAAAAAACAmUAQBgAAAAAAgJlAEAYAAAAAAICZQBAGAAAAAACAmUAQBgAAAAAAgJlAEAYAAAAAAICZQBAGAAAAAACAmUAQBgAAAAAAgJlAEAYAAAAAAICZQBAGAAAAAACAmUAQBgAAAAAAgJlAEAYAAAAAAICZQBAGAAAAAACAmUAQBgAAAACYOY7jKBQKdb1YlhV0q2Mrn893/f8vEokE3SbQJuS6rht0EwAAAAAAjJLjOFpcXGzeNk1TV69elWEYbXXhcHjEnU0Wx3Ga13d2dlStVpVOp5s/MwxD9Xo9gM6AoxGEAQAAAABmzuEgrFQqKZFIBNjR9EgmkyqXy5IIwjB+WBoJAAAAAJh5zPzyz+FZdcA4IQgDAAAAAMy8paWloFsAMAIEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAA9MhxHOXzeUWj0eYZEg+Uy2XF43EtLi4qFAopGo2qWCwee5xsNqtoNNpWf/iY494HMCnuC7oBAAAAAIA3juNoe3tblmVpa2tLtm3LsiyVSiUlEolj75dMJlWtVhWLxXT16lXOkNgny7JUrVa1sbEhy7Lu+b1t20omk/f8zrIspdNp1Wo1FQqF5s/z+byy2eyR4ySTSWUyGeVyubHtA5hEIdd13aCbAAAAAAB0Vq1Wm2HE9va2HMdp/s4wDNXr9SPvZ1mWotFo83YqlWoLQWaV4zhaXFxs3q7VajJN89h627abYdHhWVKlUkk7OztKp9MyTVMXLlyQYRiybVuXL19u+7eqVCqKxWKKx+Pa3t7W6uqqotGolpaWtLW1pXw+33bser0uwzDGro9Ostls8/6dnptAEAjCAAAAAGACxeNxVavV5u2DYOMwx3F05syZZghimqZqtdqo2hxbvQZhrQ7PoDIMQzs7O7p69eo9M/Ns21YkEmnePhhjaWlJpVLpntl51WpV8Xi8ebtTcDkufRxGEIZxxh5hAAAAADCBSqVS2+3jQopwOKwbN260BR8YzFGB2e7u7pHLUw3DaAsoLcuS4ziqVCpHLlGNxWJtM69aw85x7QOYJARhAAAAADCBwuGwMplM83anTc3D4bCuXbsm6ejwBL05HCZ22p9NUtvMKklH7sfVqvXfyLbtse8DmCQEYQAAAAAwodLpdNvtTrN2Dmb9XLhwYZgt4QiHZ1x1m5V3eC8uv0KocekDCBJBGAAAAABMKMMw2sKKw8slW1WrVRmGwYywAAy6HLV1k/tp6AMIEkEYAAAAAEyw1uVwm5ubx9YVCoV7ZpBhPD3wwANBtyBpfPoA/EQQBgAAAAATrHXfJ8dxjly+5jiOqtVq255iADCLCMIAAAAAYIK1nglQOnqfsMuXLyuVSo2qJQAYW/cF3QAAAAAAYDCxWKwZgNVqtbbfOY6jYrGoGzduBNEaAIwVZoQBAAAAwIRrXR55eEbYwWyww2cMBIBZRBAGAAAAABOudXlk6x5htm2rWCwql8t1PYbjOEqn04pGo1pcXFQkElEymTxyqWUry7KUTCYViUS0uLioxcVFRaNRFYvFjmPl83lFIpHm7Xg8rlAodM+eZ17qAMArgjAAAAAAmHCmabbdPgjDstmspxAsn8/rzJkzikajunbtmnZ3d1UoFFQulxWPx5XNZo+8XzabVTQa1fnz51Wr1bS7u6taraalpaVmqNYazBWLxWbQls1mZdu2HMdRNBptBm7ValX/9b/+V0913UI6ADiMIAwAAAAApkBrGGZZVvPSbZP8bDarbDarUqnUtoQyFos1j5nP5+85G2U2m1U+n1cmk1Emk2nezzAMVSoVmaYpy7IUjUblOI4kaXV1VaVSqW2Z5sWLF1UqlVSv12WapgzD0H/7b//NU93y8nJ//2cBmFkEYQAAAAAwBVpDoa2tLSWTSRUKhY73sSxL+XxesVjsnrNPStKlS5c63k/SsTPOrl69Kml/OePFixclSeFwWIZhtI2VTqebwVatVlO9XtfHPvYxT3WTuu/Zzs5O0C1IGp8+gFEiCAMAAACAKRCNRpvX8/n8PUHSUQ6WPCaTySN/n0gkVK/Xtbu7K8Mwmj+/fPmypHuXZLYyTbP5+3K5fM+MsgPdeuy1bhwdDpwOZsgd5+23357qPoAgEYQBAAAAwBQ4vEywVCp1vc/BHludlhgahnHPzCvLsiRJS0tLHY/fGl5N035eh0O9boHS4d/X6/We6o8LEcelD2CSEIQBAAAAwBRonZ1VKBS6LhscJNQ4uG+3pXUHZ3uUuocuk+RgRtyBzc3NY0Mox3HuWaK6ubnZMdza3Nxs+9lxS1zHpQ9gkhCEAQAAAMAUMU2z6wb5Uvtsn15CsV7u17qc8oEHHvA8xjiyLEvxeFyLi4vNGXEHHMfR4uKiotGoyuVys/7gzJdHzdyKRCKKRqMqFouS9mfMRSIRRSKRe8KsarWqxcVFxeNx/a//9b/Gog9mh2FS3Rd0AwAAAACAwZXLZYXDYV27ds1TfesMskqlokQi4el+rTPNelmK1xqKTSLTNFWpVHqqr9VqnutjsZjnWXN/9md/NhZ9AJOIGWEAAAAAMOEOzsx49erVns6keFBbLBY7zvCxbbt5lkhJbaHZwcyjo7QunfQatAHAMBGEAQAAAMCESyaTSqVSPYdNrUsok8nkkTO8bNtuHv9ALpdrXj+8T1Wrgw37W+sBIEgEYQAAAAAwwQ5mavUTNuVyueasMMuydObMGWWzWZXLZVWrVWWzWUWjUV26dKltpplhGM3xLMs68oyQtm2rWq3KNE1lMpneH9iIddv4H8B0IAgDAAAAgAlVrVZVKBSaM6/6UavVmvt3OY6jfD6vZDKpeDyufD6vXC535EyzTCbTDMPi8XjbEslqtapoNKpEInHknmWtm7wf3vC9nzo/sPm7f7rtHQcEiSAMAAAAAMZcsVhsng3wILApl8tKp9Oq1Wo97Qt2mGEYqtfrymQyzUDMMAwlEgnV6/WOZ6DMZDKq1+tKJBK6ePGiFhcXFYlElMvldPXqVZVKpbbe8vm8IpFIW+i0srKidDrdNqvMa52fstmsqtWqHMdpu6Czw/9/VavV5hkogXEUcl3XDboJAAAAAMDxQqFQ2+1wOCzDMHTt2rWBQrBZ5jiOFhcXu9bVarW2M2ziN/L5vLLZbMeag6AVGBcEYQAAAAAw5qLRaNvSwEQiMdBySACYVQRhAAAAADDmHMdRsVjU22+/rQsXLjBDCQD6RBAGAAAAAACAmcBm+QAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCQRhAAAAAAAAmAkEYQAAAAAAAJgJBGEAAAAAAACYCf8/docA6/SiH4AAAAAASUVORK5CYII=",
|
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"text/plain": [
|
|
"<Figure size 1200x900 with 2 Axes>"
|
|
]
|
|
},
|
|
"metadata": {},
|
|
"output_type": "display_data"
|
|
}
|
|
],
|
|
"source": [
|
|
"bins = np.linspace(-40, 40, 41)\n",
|
|
"ax = sns.regplot(\n",
|
|
" x=y_test,\n",
|
|
" y=y_test - y_pred_test,\n",
|
|
" x_bins=bins,\n",
|
|
" fit_reg=None,\n",
|
|
" x_estimator=np.mean,\n",
|
|
" label=\"bla\",\n",
|
|
")\n",
|
|
"ax2 = ax.twinx()\n",
|
|
"ax2.hist(\n",
|
|
" y_test,\n",
|
|
" bins=30,\n",
|
|
" range=[-40, 40],\n",
|
|
" color=\"#2A9D8F\",\n",
|
|
" alpha=0.5,\n",
|
|
" align=\"mid\",\n",
|
|
" density=True,\n",
|
|
")\n",
|
|
"ax.set_xlabel(r\"$y_{\\mathrm{corr}}$ [mm]\")\n",
|
|
"ax.set_ylabel(\n",
|
|
" r\"$\\left\\langle y_{\\mathrm{corr}}-y_{\\mathrm{corr}}^{\\mathrm{pred}}\\right\\rangle$ [mm]\"\n",
|
|
")\n",
|
|
"ax2.set_ylabel(\"Number of Tracks (normalised)\")\n",
|
|
"mplhep.lhcb.text(\"Simulation\", loc=0)\n",
|
|
"# plt.show()\n",
|
|
"plt.savefig(\n",
|
|
" \"/work/cetin/LHCb/reco_tuner/parameterisations/plots/bend_y_regression_plot.pdf\",\n",
|
|
" format=\"PDF\",\n",
|
|
")"
|
|
]
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": []
|
|
},
|
|
{
|
|
"cell_type": "code",
|
|
"execution_count": null,
|
|
"metadata": {},
|
|
"outputs": [],
|
|
"source": [
|
|
"features = [\n",
|
|
" \"ideal_state_770_ty\",\n",
|
|
" \"ideal_state_770_tx\",\n",
|
|
" \"dSlope_xEndT\",\n",
|
|
" \"dSlope_yEndT\",\n",
|
|
" \"dSlope_xEndT_abs\",\n",
|
|
" \"dSlope_yEndT_abs\",\n",
|
|
"]\n",
|
|
"target_feat = \"yDiffEndT\"\n",
|
|
"\n",
|
|
"data = np.column_stack([ak.to_numpy(array[feat]) for feat in features])\n",
|
|
"target = ak.to_numpy(array[target_feat])\n",
|
|
"X_train, X_test, y_train, y_test = train_test_split(data,\n",
|
|
" target,\n",
|
|
" test_size=0.2,\n",
|
|
" random_state=42)\n",
|
|
"\n",
|
|
"poly = PolynomialFeatures(degree=6, include_bias=False)\n",
|
|
"X_train_model = poly.fit_transform(X_train)\n",
|
|
"X_test_model = poly.fit_transform(X_test)\n",
|
|
"poly_features = poly.get_feature_names_out(input_features=features)\n",
|
|
"keep = [\n",
|
|
" #'dSlope_xEndT',\n",
|
|
" \"dSlope_yEndT\", # keep\n",
|
|
" #'dSlope_yEndT_abs',\n",
|
|
" #'ty dSlope_xEndT',\n",
|
|
" #'ty dSlope_yEndT',\n",
|
|
" \"ideal_state_770_ty dSlope_xEndT_abs\", # keep\n",
|
|
" \"ideal_state_770_ty dSlope_yEndT_abs\", # keep\n",
|
|
" \"ideal_state_770_ty dSlope_yEndT^2\", # keep\n",
|
|
" \"ideal_state_770_ty dSlope_xEndT^2\", # keep\n",
|
|
" #'tx dSlope_xEndT',\n",
|
|
" #'tx dSlope_xEndT_abs',\n",
|
|
" #'tx dSlope_yEndT',\n",
|
|
" \"ideal_state_770_ty ideal_state_770_tx dSlope_xEndT\", # keep\n",
|
|
" \"ideal_state_770_tx^2 dSlope_yEndT\", # keep\n",
|
|
" #'ty^2 dSlope_xEndT',\n",
|
|
" #'ty^2 dSlope_yEndT',\n",
|
|
" #'ty^2 dSlope_xEndT_abs',\n",
|
|
" #'ty^2 tx dSlope_xEndT',\n",
|
|
" #'ty tx^2 dSlope_yEndT',\n",
|
|
" \"ideal_state_770_ty ideal_state_770_tx^2 dSlope_xEndT_abs\", # keep\n",
|
|
" \"ideal_state_770_ty^3 ideal_state_770_tx dSlope_xEndT\", # keep\n",
|
|
" #'ty tx^3 dSlope_xEndT',\n",
|
|
" #'ty^3 dSlope_yEndT_abs',\n",
|
|
"]\n",
|
|
"do_not_keep = [\n",
|
|
" \"dSlope_xEndT\",\n",
|
|
" \"dSlope_yEndT_abs\",\n",
|
|
" \"ideal_state_770_ty dSlope_xEndT\",\n",
|
|
" \"ideal_state_770_tx dSlope_xEndT\",\n",
|
|
" \"ideal_state_770_tx dSlope_xEndT_abs\",\n",
|
|
" \"ideal_state_770_tx dSlope_yEndT\",\n",
|
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" \"ideal_state_770_ty^2 dSlope_xEndT\",\n",
|
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" \"ideal_state_770_ty^3 dSlope_yEndT_abs\",\n",
|
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" \"ideal_state_770_ty ideal_state_770_tx dSlope_yEndT\",\n",
|
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" \"ideal_state_770_ty ideal_state_770_tx^3 dSlope_xEndT\",\n",
|
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" \"ideal_state_770_ty ideal_state_770_tx^2 dSlope_yEndT\",\n",
|
|
"]\n",
|
|
"reduce = True\n",
|
|
"if reduce:\n",
|
|
" remove = [\n",
|
|
" i for i, f in enumerate(poly_features) if (keep and f not in keep)\n",
|
|
" ]\n",
|
|
" X_train_model = np.delete(X_train_model, remove, axis=1)\n",
|
|
" X_test_model = np.delete(X_test_model, remove, axis=1)\n",
|
|
" poly_features = np.delete(poly_features, remove)\n",
|
|
" print(poly_features)\n",
|
|
"if not reduce:\n",
|
|
" remove = [\n",
|
|
" i for i, f in enumerate(poly_features)\n",
|
|
" if (\"dSlope_\" not in f) or (\"EndT^\" in f) or (\"abs^\" in f) or (\n",
|
|
" \"EndT dSlope\" in f) or (\"abs dSlope\" in f)\n",
|
|
" ]\n",
|
|
" X_train_model = np.delete(X_train_model, remove, axis=1)\n",
|
|
" X_test_model = np.delete(X_test_model, remove, axis=1)\n",
|
|
" poly_features = np.delete(poly_features, remove)\n",
|
|
" # print(poly_features)\n",
|
|
" lin_reg = Lasso(fit_intercept=False, alpha=0.000001)\n",
|
|
"else:\n",
|
|
" lin_reg = LinearRegression(fit_intercept=False)\n",
|
|
"lin_reg.fit(X_train_model, y_train)\n",
|
|
"y_pred_test = lin_reg.predict(X_test_model)\n",
|
|
"print(\"intercept=\", lin_reg.intercept_)\n",
|
|
"print(\n",
|
|
" \"coef=\",\n",
|
|
" {\n",
|
|
" k: v\n",
|
|
" for k, v in zip(poly_features, lin_reg.coef_)\n",
|
|
" if abs(v) > 1.0 and k not in keep and k not in do_not_keep\n",
|
|
" },\n",
|
|
")\n",
|
|
"print(\"r2 score=\", lin_reg.score(X_test_model, y_test))\n",
|
|
"print(\"RMSE =\", mean_squared_error(y_test, y_pred_test, squared=False))\n",
|
|
"print(\n",
|
|
" \"straight RMSE =\",\n",
|
|
" mean_squared_error(\n",
|
|
" array[\"ideal_state_9410_y\"],\n",
|
|
" array[\"ideal_state_770_y\"] + array[\"ideal_state_770_ty\"] *\n",
|
|
" (array[\"ideal_state_9410_z\"] - array[\"ideal_state_770_z\"]),\n",
|
|
" squared=False,\n",
|
|
" ),\n",
|
|
")\n",
|
|
"print(format_array(\"y_xEndT_diff\", lin_reg.coef_))"
|
|
]
|
|
}
|
|
],
|
|
"metadata": {
|
|
"kernelspec": {
|
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"display_name": "Python 3.10.6 (conda)",
|
|
"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": "3.10.12"
|
|
},
|
|
"orig_nbformat": 4,
|
|
"vscode": {
|
|
"interpreter": {
|
|
"hash": "a2eff8b4da8b8eebf5ee2e5f811f31a557e0a202b4d2f04f849b065340a6eda6"
|
|
}
|
|
}
|
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},
|
|
"nbformat": 4,
|
|
"nbformat_minor": 2
|
|
}
|