398 lines
148 KiB
Plaintext
398 lines
148 KiB
Plaintext
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{
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"cells": [
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{
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Scripts for Calibration of Cernox Sensors\n",
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"---------------------------------------\n",
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"\n",
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"Make a copy of this notebook for an other run."
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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": 5,
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"metadata": {},
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"outputs": [],
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"source": [
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"import numpy as np\n",
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"import matplotlib.pyplot as plt\n",
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"import math\n",
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"from scipy.interpolate import splrep, splev\n",
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"from zcalib import read_curve, convert_res, compare_calib, make_calib, logrange, Sensor, CalibRun, nplog, npexp"
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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": 6,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"('lsdat', 'READ /afs/psi.ch/project/SampleEnvironment/SE_internal/Thermometer_calibs/2012/73027 Cernox 5/X75610.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p0_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p1_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p2_c1.dat')\n",
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"{'selected': 0, 'averaged': 62}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p0_c2.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p1_c2.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p2_c2.dat')\n",
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"{'selected': 1, 'averaged': 61}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p0_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p1_c4.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p2_c4.dat')\n",
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"{'selected': 1, 'averaged': 61}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p0_c5.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p1_c5.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p2_c5.dat')\n",
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"{'selected': 1, 'averaged': 61}\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p0_c6.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p1_c6.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p2_c6.dat')\n",
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"{'selected': 0, 'averaged': 62}\n"
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]
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}
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],
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"source": [
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"run = CalibRun([\n",
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" Sensor(3, 'X75610'), # the reference sensor must be the first\n",
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" Sensor(1, 'X174787', 'CX-1050-CU'),\n",
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" Sensor(2, 'X174783', 'CX-1050-CU'),\n",
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" Sensor(4, 'X174786', 'CX-1050-CU'),\n",
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" Sensor(5, 'X174782', 'CX-1050-CU'),\n",
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" Sensor(6, 'X174785', 'CX-1050-CU'),\n",
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" ],\n",
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" t_points = (1.0, 1.2) + logrange(1.4, 310, n=195) + (330,), # the points to be used in the cal file\n",
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" caldate = '2022-02-21', # the first measuring day!\n",
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" logT = False,\n",
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" logR = True,\n",
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" calib_data_file = '/home/l_samenv/sea/calib_scripts/calib_data/calib%s_p%d_c%d.dat',\n",
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" outputpath='%s/%s.340')\n",
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"# smooth depends on number of measured points (1e-7 for 60, 0.8e-7 for 48 and 0.4e-7 for 24 points)\n",
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"run.make(diflim=0.001, smoothref=1e-7, smoothtst=0.4e-7)"
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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": 7,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"('z340', 'READ 2018-11-22/X133982.340')\n",
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"('z340', 'READ 2018-11-20/X133982.340')\n",
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"('z340', 'READ 2018-11-22/X133928.340')\n",
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"('z340', 'READ 2018-11-20/X133928.340')\n",
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"('z340', 'READ 2018-11-22/X131824.340')\n",
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"('z340', 'READ 2018-11-20/X131824.340')\n",
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"('z340', 'READ 2018-11-22/X132254.340')\n",
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"('z340', 'READ 2018-11-20/X132254.340')\n",
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"('z340', 'READ 2018-11-22/X137461.340')\n",
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"('z340', 'READ 2018-11-20/X137461.340')\n"
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]
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},
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{
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"data": {
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"image/png": "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"text/plain": [
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"<Figure size 720x432 with 1 Axes>"
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]
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},
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"metadata": {
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"needs_background": "light"
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},
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"output_type": "display_data"
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}
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],
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"source": [
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"# compare known sensors (skip if not applicable)\n",
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"plt.figure(figsize=(10, 6))\n",
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"tmin,tmax,dmax=1.4,310,0.001\n",
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"testlist = (('X133982', 'z340'),('X133928', 'z340'),('X131824', 'z340'),('X132254', 'z340'),('X137461', 'z340'))\n",
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"for sensno, kind in testlist:\n",
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" r0, t0 = read_curve('2018-11-22/%s.340' % sensno, 'z340')\n",
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" r1, t1 = read_curve('2018-11-20/%s.340' % sensno, kind)\n",
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" diff = compare_calib(r1, t1, r0, t0)\n",
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" plt.plot(t0, diff, '-')\n",
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"plt.plot([tmin,tmax,tmax,tmin,tmin], [-dmax,-dmax,dmax,dmax,-dmax], '-')\n",
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"plt.legend([sensno + \".\" + kind[-3:] for sensno, kind in testlist] + [\"window\"])\n",
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"plt.xscale('log')\n",
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"plt.yscale('symlog',linthreshy=dmax)\n",
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"plt.grid(True, axis='y')\n",
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"plt.axis([1.0,350,-1,1])\n",
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"plt.show()"
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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": 4,
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"metadata": {},
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"outputs": [
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{
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"name": "stdout",
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"output_type": "stream",
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"text": [
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"('z340', 'READ 2022-02-21/X174787.340')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p0_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p1_c1.dat')\n",
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"('zdat', 'READ /home/l_samenv/sea/calib_scripts/calib_data/calib2022-02-21_p2_c1.dat')\n"
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]
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},
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{
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"data": {
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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": 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": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"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": []
|
||
|
|
},
|
||
|
|
{
|
||
|
|
"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"
|
||
|
|
}
|
||
|
|
},
|
||
|
|
"nbformat": 4,
|
||
|
|
"nbformat_minor": 2
|
||
|
|
}
|