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calib_scripts/calib_cernox_2024-12-09.ipynb
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initial commit
2026-02-13 14:40:58 +01:00
{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Scripts for Calibration of Cernox Sensors\n",
"---------------------------------------\n",
"\n",
"Make a copy of this notebook for an other run."
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import numpy as np\n",
"import matplotlib.pyplot as plt\n",
"import math\n",
"from scipy.interpolate import splrep, splev\n",
"from zcalib import read_curve, convert_res, compare_calib, make_calib, logrange, Sensor, CalibRun, nplog, npexp"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('lsdat', 'READ /afs/psi.ch/project/SampleEnvironment/SE_internal/Thermometer_calibs/2012/73027 Cernox 5/X75610.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c1.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c1.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c1.dat')\n",
"{'selected': 0, 'averaged': 59}\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c2.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c2.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c2.dat')\n",
"{'selected': 0, 'averaged': 59}\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c4.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c4.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c4.dat')\n",
"{'selected': 0, 'averaged': 59}\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c5.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c5.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c5.dat')\n",
"(65.544, 81.2136, 42.325388448806535, -0.47883866188906127)\n",
"(62.4943, 77.5486, 40.60352175244162, -0.47641193068035237)\n",
"(60.8736, 75.6053, 39.68410649020259, -0.47511475398943476)\n",
"{'selected': 1, 'averaged': 47}\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c6.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c6.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c6.dat')\n",
"{'selected': 0, 'averaged': 59}\n"
]
}
],
"source": [
"run = CalibRun([\n",
" Sensor(3, 'X75610'), # the reference sensor must be the first\n",
" Sensor(1, 'X142475', 'CX-1050-CU-HT'),\n",
" Sensor(2, 'X221296', 'CX-1050-CU-HT'),\n",
" Sensor(4, 'X149797', 'CX-1050-SD-HT'),\n",
" Sensor(5, 'X221297', 'CX-1050-CU-HT'),\n",
" Sensor(6, 'X221298', 'CX-1050-CU-HT'),\n",
" ],\n",
" t_points = (1.58,1.59) + logrange(1.6, 310, n=195) + (330,), # the points to be used in the cal file\n",
" caldate = '2024-12-09', # the first measuring day!\n",
" logT = False,\n",
" logR = True,\n",
" calib_data_file = '/home/l_samenv/sea/calib_scripts/calib_data/calib%s_p%d_c%d.dat',\n",
" outputpath='%s/%s.340')\n",
"# smooth depends on number of measured points (1e-7 for 60, 0.8e-7 for 48 and 0.4e-7 for 24 points)\n",
"run.make(diflim=0.001, smoothref=1e-7, smoothtst=0.4e-7)"
]
},
{
"cell_type": "code",
"execution_count": 26,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('z340', 'READ 2023-11-05/X133982.340')\n"
]
},
{
"ename": "IOError",
"evalue": "[Errno 2] No such file or directory: '2023-11-05/X133982.340'",
"output_type": "error",
"traceback": [
"\u001b[0;31m\u001b[0m",
"\u001b[0;31mIOError\u001b[0mTraceback (most recent call last)",
"\u001b[0;32m<ipython-input-26-fb75a641ebf6>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m 4\u001b[0m \u001b[0mtestlist\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X133982'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X133928'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X131824'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X132254'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'X137461'\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 5\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0msensno\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mtestlist\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 6\u001b[0;31m \u001b[0mr0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt0\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mread_curve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'2023-11-05/%s.340'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0msensno\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m'z340'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 7\u001b[0m \u001b[0mr1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt1\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mread_curve\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'2023-11-05/%s.340'\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0msensno\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkind\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 8\u001b[0m \u001b[0mdiff\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mcompare_calib\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mr1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mr0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mt0\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;32m/home/l_samenv/sea/calib_scripts/zcalib.pyc\u001b[0m in \u001b[0;36mread_curve\u001b[0;34m(filename, kind, instance, **filterargs)\u001b[0m\n\u001b[1;32m 118\u001b[0m \u001b[0;32mprint\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mkind\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m\"READ %s\"\u001b[0m \u001b[0;34m%\u001b[0m \u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 119\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 120\u001b[0;31m \u001b[0;32mwith\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m 121\u001b[0m \u001b[0mcurves\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mc\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfilter\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moutput\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m 122\u001b[0m \u001b[0;32mfor\u001b[0m \u001b[0mline\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
"\u001b[0;31mIOError\u001b[0m: [Errno 2] No such file or directory: '2023-11-05/X133982.340'"
]
},
{
"data": {
"text/plain": [
"<Figure size 720x432 with 0 Axes>"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"# compare known sensors (skip if not applicable)\n",
"plt.figure(figsize=(10, 6))\n",
"tmin,tmax,dmax=1.4,310,0.001\n",
"testlist = (('X133982', 'z340'),('X133928', 'z340'),('X131824', 'z340'),('X132254', 'z340'),('X137461', 'z340'))\n",
"for sensno, kind in testlist:\n",
" r0, t0 = read_curve('2023-11-05/%s.340' % sensno, 'z340')\n",
" r1, t1 = read_curve('2023-11-05/%s.340' % sensno, kind)\n",
" diff = compare_calib(r1, t1, r0, t0)\n",
" plt.plot(t0, diff, '-')\n",
"plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
"plt.legend([sensno + \".\" + kind[-3:] for sensno, kind in testlist] + [\"window\"])\n",
"plt.xscale('log')\n",
"plt.yscale('symlog',linthreshy=dmax)\n",
"plt.grid(True, axis='y')\n",
"plt.axis([1.0,350,-1,1])\n",
"plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('z340', 'READ 2024-12-09/X142475.340')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c1.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c1.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c1.dat')\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"('z340', 'READ 2024-12-09/X221296.340')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c2.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c2.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c2.dat')\n"
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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
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"('z340', 'READ 2024-12-09/X149797.340')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c4.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c4.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c4.dat')\n"
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"data": {
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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
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"('z340', 'READ 2024-12-09/X221297.340')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c5.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c5.dat')\n"
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{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"('z340', 'READ 2024-12-09/X221298.340')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c6.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c6.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c6.dat')\n"
]
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"# compare calibration files from points 0,1,2\n",
"# with the optimized (average or selection of best)\n",
"\n",
"for sensor in run.sensors:\n",
" r0, t0 = read_curve(sensor.outputpath, sensor.outputkind)\n",
" plt.figure()\n",
" dif = [0,0,0]\n",
" for j in range(3):\n",
" rr, rt = read_curve(sensor.caldat_file[j], 'zdat')\n",
" rc, tc = make_calib(run.rref, run.tref, rr, rt, run.t_points)\n",
" dif[j] = compare_calib(r0, t0, rc, tc)\n",
" plt.plot(t0, dif[j], '-')\n",
" plt.xscale('log')\n",
" plt.yscale('symlog', linthreshy=0.001)\n",
" plt.grid(True, axis='y')\n",
" plt.axis([min(t0),max(t0),-1,1])\n",
" tmin,tmax,dmax=1.4,310,0.001\n",
" plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
" plt.legend(['dif1','dif2','dif3','est'])\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('z340', 'READ 2024-12-09/X142475.340')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c1.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c1.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c1.dat')\n"
]
},
{
"data": {
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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"('z340', 'READ 2024-12-09/X221296.340')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c2.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c2.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c2.dat')\n"
]
},
{
"data": {
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"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
},
{
"name": "stdout",
"output_type": "stream",
"text": [
"('z340', 'READ 2024-12-09/X149797.340')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c4.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c4.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c4.dat')\n"
]
},
{
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p2_c5.dat')\n"
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"text/plain": [
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]
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"('z340', 'READ 2024-12-09/X221298.340')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p0_c6.dat')\n",
"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2024-12-09_p1_c6.dat')\n",
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{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 432x288 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"for sensor in run.sensors:\n",
" r0, t0 = read_curve(sensor.outputpath, sensor.outputkind)\n",
" plt.figure()\n",
" dif = [0,0,0]\n",
" for j in range(3):\n",
" rr, rt = read_curve(sensor.caldat_file[j], 'zdat')\n",
" rc, tc = make_calib(run.rref, run.tref, rr, rt, run.t_points)\n",
" dif[j] = compare_calib(r0, t0, rc, tc)\n",
" plt.plot(t0, dif[j], '-')\n",
" plt.xscale('log')\n",
" plt.yscale('symlog', linthreshy=0.001)\n",
" plt.grid(True, axis='y')\n",
" plt.axis([min(t0),max(t0),-1,1])\n",
" tmin,tmax,dmax=1.4,310,0.001\n",
" plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
" plt.legend(['dif1','dif2','dif3','est'])\n",
" plt.show()"
]
},
{
"cell_type": "code",
"execution_count": 74,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"('z340', 'READ 2024-12-09/X142475.340')\n",
"('z340', 'READ 2024-12-09/X221296.340')\n",
"('z340', 'READ 2024-12-09/X149797.340')\n",
"('z340', 'READ 2024-12-09/X221297.340')\n",
"('z340', 'READ 2024-12-09/X221298.340')\n"
]
},
{
"data": {
"text/plain": [
"<matplotlib.legend.Legend at 0xc954590>"
]
},
"execution_count": 74,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": "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
"text/plain": [
"<Figure size 1500x900 with 1 Axes>"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"plt.figure(figsize=(10,6),dpi=150)\n",
"for sensor in run.sensors:\n",
" r0, t0 = read_curve(sensor.outputpath, sensor.outputkind)\n",
" plt.loglog(t0,r0,'o',alpha=0.5, label=\"CH{}:{} {}\".format(sensor.channel, sensor.serialno, sensor.model))\n",
"\n",
"plt.title(sensor.outputpath.split('/')[0])\n",
"plt.grid(which='both',alpha=0.2)\n",
"plt.xlabel('T (K)')\n",
"plt.ylabel('R (Ohm)')\n",
"plt.legend()"
]
},
{
"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": []
},
{
"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": []
}
],
"metadata": {
"kernelspec": {
"display_name": "Python 2.7",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
"version": 2
},
"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython2",
"version": "2.7.5"
},
"widgets": {
"application/vnd.jupyter.widget-state+json": {
"state": {},
"version_major": 2,
"version_minor": 0
}
}
},
"nbformat": 4,
"nbformat_minor": 4
}
Reference in New Issue Copy Permalink