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routine
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dpeana committed Jun 28, 2022
1 parent 35fcbd0 commit ca2077d
Showing 7 changed files with 1,276 additions and 55 deletions.
4 changes: 2 additions & 2 deletions .ipynb_checkpoints/AtomNumberEq-checkpoint.ipynb
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@@ -388,7 +388,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -402,7 +402,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"version": "3.9.7"
}
},
"nbformat": 4,
552 changes: 552 additions & 0 deletions .ipynb_checkpoints/Jon_analysis-checkpoint.ipynb

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6 changes: 6 additions & 0 deletions .ipynb_checkpoints/Untitled-checkpoint.ipynb
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{
"cells": [],
"metadata": {},
"nbformat": 4,
"nbformat_minor": 5
}
4 changes: 2 additions & 2 deletions AtomNumberEq.ipynb
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@@ -388,7 +388,7 @@
],
"metadata": {
"kernelspec": {
"display_name": "Python 3",
"display_name": "Python 3 (ipykernel)",
"language": "python",
"name": "python3"
},
@@ -402,7 +402,7 @@
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.7.4"
"version": "3.9.7"
}
},
"nbformat": 4,
64 changes: 13 additions & 51 deletions CSV_read_and_fit.ipynb

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536 changes: 536 additions & 0 deletions Jon_analysis.ipynb

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165 changes: 165 additions & 0 deletions Untitled.ipynb
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{
"cells": [
{
"cell_type": "code",
"execution_count": 3,
"id": "483c4293",
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd"
]
},
{
"cell_type": "code",
"execution_count": 12,
"id": "3c2cd2ad",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"[0 1 2 3 4 5 6 7 8 9]\n"
]
}
],
"source": [
"import numpy as np\n",
"x= np.arange(10)\n",
"print(x)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"id": "7cb5505a",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"-0.5\n",
"-0.6111111111111112\n",
"-0.7222222222222222\n",
"-0.8333333333333333\n",
"-0.9444444444444444\n",
"-1.0555555555555556\n",
"-1.1666666666666665\n",
"-1.2777777777777777\n",
"-1.3888888888888888\n",
"-1.5\n"
]
}
],
"source": [
"ms = 1e-3\n",
"sweep_time = 2 * ms \n",
"npts = 10\n",
"vMOT_lower = 0.5\n",
"igbt_voltage = 1.5\n",
"\n",
"scan = np.linspace(vMOT_lower, igbt_voltage, npts)\n",
"for m in range(npts):\n",
" print(-scan[m])\n",
" "
]
},
{
"cell_type": "code",
"execution_count": 45,
"id": "f119a424",
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"10\n",
"[0.3, 0.4333, 0.5666, 0.6999, 0.8332, 0.9665, 1.0998, 1.2331, 1.3664, 1.4997]\n",
"0.3\n",
"0.4333\n",
"0.5666\n",
"0.6999\n",
"0.8332\n",
"0.9665\n",
"1.0998\n",
"1.2331\n",
"1.3664\n",
"1.4997\n"
]
}
],
"source": [
"sweep_time = 2 * ms \n",
"npts = 10\n",
"\n",
"\n",
"igbt_voltage= 1.5\n",
"vMOT_lower= 0.3\n",
"step =(igbt_voltage -vMOT_lower)/(npts-1)\n",
"\n",
"mult = 10000\n",
"scan = [x/mult for x in range(int(mult*vMOT_lower), int(mult*igbt_voltage), int(mult*step ) ) ]\n",
"\n",
"print(len(scan))\n",
"print(scan)\n",
"\n",
"for m in range(npts):\n",
" print(scan[m])"
]
},
{
"cell_type": "code",
"execution_count": 52,
"id": "dae7e9e5",
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"array([0.3 , 0.4333, 0.5666, 0.6999, 0.8332, 0.9665, 1.0998, 1.2331,\n",
" 1.3664, 1.4997], dtype=float32)"
]
},
"execution_count": 52,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"np.float32(scan)"
]
},
{
"cell_type": "code",
"execution_count": null,
"id": "b3484f8a",
"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": "3.9.7"
}
},
"nbformat": 4,
"nbformat_minor": 5
}

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