2020-05-18 03:38:17 +00:00
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{
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"cells": [
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2020-05-22 16:18:56 +00:00
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{
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"cell_type": "code",
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"execution_count": 1,
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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": [
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"\"Oct 11 2016\""
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]
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},
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"execution_count": 1,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"my_date = \"Oct 11 2016\" # needs updating"
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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": 2,
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"metadata": {},
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"outputs": [],
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"source": [
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"using Dates"
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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": 3,
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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": [
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"2016-10-11T00:00:00"
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]
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},
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"execution_count": 3,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"Dates.DateTime(my_date,\"u d y\")"
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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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{
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"data": {
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"text/plain": [
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"54×9 Array{Any,2}:\n",
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" 613 28637 11314 3804 2536 10675 4808 14122 3955 \n",
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" 606 28634 11314 3804 2536 10672 4808 14122 3955 \n",
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" 599 28635 11314 3805 2536 10672 4808 14122 3955 \n",
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" 592 28607 11314 3810 2536 10672 4808 14089 3955 \n",
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" 582 28539 11298 3806 2535 10672 4808 14061 3955 \n",
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" 575 28476 11298 3803 2535 10672 4808 14001 3955 \n",
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" 568 28454 11297 3800 2534 10672 4808 13982 3955 \n",
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" 554 28388 11296 3805 2533 10672 4808 13911 3955 \n",
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" 547 28295 11295 3800 2532 10672 4808 13823 3955 \n",
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" 540 28220 11291 3792 2530 10672 4808 13756 3953 \n",
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" 533 28147 11291 3792 2530 10672 4808 13683 3953 \n",
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" 526 28073 11290 3792 2529 10672 4808 13609 3953 \n",
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" 512 27952 11284 3786 2524 10672 4808 13494 3952 \n",
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" ⋮ ⋮ \n",
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" 140 1835 1011 506 373 599 323 730 315 \n",
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" 130 1437 825 472 346 391 227 574 252 \n",
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" 123 1201 672 427 319 249 129 525 224 \n",
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" 114 982 613 411 310 174 106 397 197 \n",
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" 102 779 481 412 305 115 75 252 101 \n",
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" 87 528 337 398 264 33 24 97 49 \n",
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" 66 309 202 281 186 12 11 16 5 \n",
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" 51 260 182 248 171 12 11 \"–\" \"–\"\n",
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" 40 239 160 226 149 13 11 \"-\" \"-\"\n",
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" 23 176 110 168 108 8 2 \"–\" \"–\"\n",
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" 9 130 82 122 80 8 2 \"–\" \"–\"\n",
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" 0 49 29 49 29 \"–\" \"–\" \"–\" \"–\""
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"using DelimitedFiles\n",
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"\n",
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"indata = DelimitedFiles.readdlm(\"wikipediaEVDdatesconverted.csv\", ',')"
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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": 26,
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"metadata": {},
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"outputs": [],
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"source": [
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"test = ones(4,5)\n",
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"\n",
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"row,col = size(test)\n",
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"\n",
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"val = 0\n",
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"for j = 1:col\n",
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" for i = 1:row\n",
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" test[i,j] = test[i,j] + val\n",
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" val = val + 1\n",
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" end\n",
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"end"
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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": 27,
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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": [
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"4×5 Array{Float64,2}:\n",
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" 1.0 5.0 9.0 13.0 17.0\n",
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" 2.0 6.0 10.0 14.0 18.0\n",
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" 3.0 7.0 11.0 15.0 19.0\n",
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" 4.0 8.0 12.0 16.0 20.0"
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]
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},
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"execution_count": 27,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"test"
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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": 28,
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"metadata": {},
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"outputs": [],
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"source": [
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"diagsum = 0\n",
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"for k = 1:2\n",
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" diagsum = diagsum + test[k,k]\n",
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"end"
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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": 32,
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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": [
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"7.0"
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]
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},
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"execution_count": 32,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"diagsum = test[1,1] + test[2,2]"
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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": 33,
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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": [
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"7.0"
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]
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},
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"execution_count": 33,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"diagsum"
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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": 30,
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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": [
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"14.0"
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]
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},
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"execution_count": 30,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"diagsum = sum(test[1:2,1:2])"
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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": 8,
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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": [
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"2×6 Array{Any,2}:\n",
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" \"The name of the rose\" \"3.2,\" \"7,\" 8 9 100\n",
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" \"Under Milk Wood\" \"5.7,\" \"11,\" 3 6 42"
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]
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},
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"execution_count": 8,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"litsamp = readdlm(\"litsampling.dat\", ' ')"
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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": 10,
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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": [
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"\"3.2,\""
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]
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},
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"execution_count": 10,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"litsamp[1,2]"
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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": 11,
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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": [
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"3-element Array{Int64,1}:\n",
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" 7\n",
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" 8\n",
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" 9"
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]
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},
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"execution_count": 11,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"a = [1,2,3]; b = [4,5,6]; c = [7,8,9]"
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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": 12,
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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": [
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"3-element Array{Array{Int64,1},1}:\n",
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" [1, 2, 3]\n",
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" [4, 5, 6]\n",
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" [7, 8, 9]"
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]
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},
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"execution_count": 12,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"[a,b,c]"
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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": 13,
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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": [
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"Plots.GRBackend()"
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]
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},
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"execution_count": 13,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"using Plots\n",
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"gr()"
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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": 38,
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"metadata": {},
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"outputs": [
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{
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"data": {
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"image/svg+xml": [
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"<?xml version=\"1.0\" encoding=\"utf-8\"?>\n",
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"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"600\" height=\"400\" viewBox=\"0 0 2400 1600\">\n",
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"<defs>\n",
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" <clipPath id=\"clip700\">\n",
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" <rect x=\"0\" y=\"0\" width=\"2400\" height=\"1600\"/>\n",
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" </clipPath>\n",
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"</defs>\n",
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"<path clip-path=\"url(#clip700)\" d=\"\n",
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"M0 1600 L2400 1600 L2400 0 L0 0 Z\n",
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" \" fill=\"#ffffff\" fill-rule=\"evenodd\" fill-opacity=\"1\"/>\n",
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"<defs>\n",
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" <clipPath id=\"clip701\">\n",
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" <rect x=\"480\" y=\"0\" width=\"1681\" height=\"1600\"/>\n",
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" </clipPath>\n",
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"</defs>\n",
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"<path clip-path=\"url(#clip700)\" d=\"\n",
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"image/png": "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
|
|
|
|
|
},
|
|
|
|
|
"execution_count": 39,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"#using Plots\n",
|
|
|
|
|
"pyplot() # Use PyPlot as a GUI (may already be the default)\n",
|
|
|
|
|
"\n",
|
|
|
|
|
"x = collect(1:7)\n",
|
|
|
|
|
"y(x) = 2 - 2x + x^2/4\n",
|
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|
|
"\n",
|
|
|
|
|
"plot(x,y.(x))\n",
|
|
|
|
|
"plot!(x, y.(x), marker = :diamond, linewidth=2)\n",
|
|
|
|
|
"plot!(title = \"Sample plot\", leg=false)"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 40,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"image/png": "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
|
|
|
|
|
},
|
|
|
|
|
"execution_count": 40,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"plot(x,y.(x))"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 41,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"image/png": "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
|
|
|
|
|
},
|
|
|
|
|
"execution_count": 41,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"plot!(x, y.(x), marker = :diamond, linewidth=2)"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 42,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"image/png": "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
|
|
|
|
|
},
|
|
|
|
|
"execution_count": 42,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"plot!(title = \"Sample plot\", leg=false)"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 1,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"text/plain": [
|
|
|
|
|
"Plots.GRBackend()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
"execution_count": 1,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"output_type": "execute_result"
|
|
|
|
|
}
|
|
|
|
|
],
|
|
|
|
|
"source": [
|
|
|
|
|
"using Plots\n",
|
|
|
|
|
"gr()"
|
|
|
|
|
]
|
|
|
|
|
},
|
|
|
|
|
{
|
|
|
|
|
"cell_type": "code",
|
|
|
|
|
"execution_count": 2,
|
|
|
|
|
"metadata": {},
|
|
|
|
|
"outputs": [
|
|
|
|
|
{
|
|
|
|
|
"data": {
|
|
|
|
|
"image/svg+xml": [
|
|
|
|
|
"<?xml version=\"1.0\" encoding=\"utf-8\"?>\n",
|
|
|
|
|
"<svg xmlns=\"http://www.w3.org/2000/svg\" xmlns:xlink=\"http://www.w3.org/1999/xlink\" width=\"600\" height=\"400\" viewBox=\"0 0 2400 1600\">\n",
|
|
|
|
|
"<defs>\n",
|
|
|
|
|
" <clipPath id=\"clip100\">\n",
|
|
|
|
|
" <rect x=\"0\" y=\"0\" width=\"2400\" height=\"1600\"/>\n",
|
|
|
|
|
" </clipPath>\n",
|
|
|
|
|
"</defs>\n",
|
|
|
|
|
"<path clip-path=\"url(#clip100)\" d=\"\n",
|
|
|
|
|
"M0 1600 L2400 1600 L2400 0 L0 0 Z\n",
|
|
|
|
|
" \" fill=\"#ffffff\" fill-rule=\"evenodd\" fill-opacity=\"1\"/>\n",
|
|
|
|
|
"<defs>\n",
|
|
|
|
|
" <clipPath id=\"clip101\">\n",
|
|
|
|
|
" <rect x=\"480\" y=\"0\" width=\"1681\" height=\"1600\"/>\n",
|
|
|
|
|
" </clipPath>\n",
|
|
|
|
|
"</defs>\n",
|
|
|
|
|
"<path clip-path=\"url(#clip100)\" d=\"\n",
|
|
|
|
|
"M147.848 1486.45 L2352.76 1486.45 L2352.76 123.472 L147.848 123.472 Z\n",
|
|
|
|
|
" \" fill=\"#ffffff\" fill-rule=\"evenodd\" fill-opacity=\"1\"/>\n",
|
|
|
|
|
"<defs>\n",
|
|
|
|
|
" <clipPath id=\"clip102\">\n",
|
|
|
|
|
" <rect x=\"147\" y=\"123\" width=\"2206\" height=\"1364\"/>\n",
|
|
|
|
|
" </clipPath>\n",
|
|
|
|
|
"</defs>\n",
|
|
|
|
|
"<polyline clip-path=\"url(#clip102)\" style=\"stroke:#000000; stroke-width:2; stroke-opacity:0.1; fill:none\" points=\"\n",
|
|
|
|
|
" 210.251,1486.45 210.251,123.472 \n",
|
|
|
|
|
" \"/>\n",
|
|
|
|
|
"<polyline clip-path=\"url(#clip102)\" style=\"stroke:#000000; stroke-width:2; stroke-opacity:0.1; fill:none\" points=\"\n",
|
|
|
|
|
" 626.272,1486.45 626.272,123.472 \n",
|
|
|
|
|
" \"/>\n",
|
|
|
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},
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}
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],
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"source": [
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"x = [1, 2, 3, 4, 5, 6]\n",
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"y = (x.-3).^2/4\n",
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]
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},
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},
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}
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],
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"source": [
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"x = [1 2 3 4 5 6]'\n",
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"y = (x.-3).^2/4\n",
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]
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},
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" 210.251,876.395 626.272,1305 1042.29,1447.87 1458.31,1305 1874.33,876.395 2290.35,162.047 \n",
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" \"/>\n",
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"<path clip-path=\"url(#clip222)\" d=\"M210.251 892.395 L196.395 884.395 L196.395 868.395 L210.251 860.395 L224.107 868.395 L224.107 884.395 Z\" fill=\"#009af9\" fill-rule=\"evenodd\" fill-opacity=\"1\" stroke=\"#000000\" stroke-opacity=\"1\" stroke-width=\"3.2\"/>\n",
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"<path clip-path=\"url(#clip222)\" d=\"M1458.31 1321 L1444.46 1313 L1444.46 1297 L1458.31 1289 L1472.17 1297 L1472.17 1313 Z\" fill=\"#009af9\" fill-rule=\"evenodd\" fill-opacity=\"1\" stroke=\"#000000\" stroke-opacity=\"1\" stroke-width=\"3.2\"/>\n",
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"<path clip-path=\"url(#clip222)\" d=\"M1874.33 892.395 L1860.48 884.395 L1860.48 868.395 L1874.33 860.395 L1888.19 868.395 L1888.19 884.395 Z\" fill=\"#009af9\" fill-rule=\"evenodd\" fill-opacity=\"1\" stroke=\"#000000\" stroke-opacity=\"1\" stroke-width=\"3.2\"/>\n",
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"<path clip-path=\"url(#clip222)\" d=\"M2290.35 178.047 L2276.5 170.047 L2276.5 154.047 L2290.35 146.047 L2304.21 154.047 L2304.21 170.047 Z\" fill=\"#009af9\" fill-rule=\"evenodd\" fill-opacity=\"1\" stroke=\"#000000\" stroke-opacity=\"1\" stroke-width=\"3.2\"/>\n",
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"</svg>\n"
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]
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},
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"execution_count": 5,
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"metadata": {},
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"output_type": "execute_result"
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}
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],
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"source": [
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"x = [1 2 3 4 5 6]'\n",
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"y = (x.-3).^2/4\n",
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"plot(x,y, marker = :hex, leg=false)\n",
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"plot!(title=\"Plot for graded quiz\", linewidth = 2, linecolor=:black)"
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]
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},
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2020-05-18 03:38:17 +00:00
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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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"metadata": {
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"kernelspec": {
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"display_name": "Julia 1.2.0",
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"language": "julia",
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"name": "julia-1.2"
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},
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"language_info": {
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"file_extension": ".jl",
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"mimetype": "application/julia",
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"name": "julia",
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"version": "1.2.0"
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}
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},
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"nbformat": 4,
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"nbformat_minor": 4
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}
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