{
"metadata": {
"name": ""
},
"nbformat": 3,
"nbformat_minor": 0,
"worksheets": [
{
"cells": [
{
"cell_type": "heading",
"level": 1,
"metadata": {},
"source": [
"Kako nari\u0161emo graf meritve"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Zakaj rezultate meritev prika\u017eemo na grafu?\n",
"\n",
"- \u010clove\u0161ki mo\u017egani tako la\u017eje procesirajo kompleksne ideje in povezave.\n",
"
- Graf meritve pogosto razkrije zna\u010dilnosti, ki jih, \u010de podatke predstavimo v tabeli, ne opazimo. \n",
"
- Ve\u010dina bralcev znanstvenih \u010dlankov najprej pogleda slike in se na osnovi njih odlo\u010di, ali bodo \u010dlanek prebrali. \n",
"
"
]
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Orodja za risanje grafov"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Obstaja vrsta programov, namenjenih risanju grafov:\n",
"\n",
"- matploatlib\n",
"
- gnuplot \n",
"
- Asymptote\n",
"
- Grace\n",
"
- Wolfram Mathematica (pla\u010dljiv, instaliran na ra\u010dunalnik FMF) \n",
"
- MATLAB (pla\u010dljiv, instaliran na ra\u010dunalnik FMF)\n",
"
- Origin (pla\u010dljiv)\n",
"
- IGOR Pro (pla\u010dljiv)\n",
"
- ...\n",
"
- Excel (ni priporo\u010dljiv)\n",
"
\n",
"Zgledi na predavanjih bodo prikazani v programu matplotlib."
]
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Napotki"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"Znanstvene revije obi\u010dajno podajo napotke, kako naj grafi v objavljenih \u010dlankih izgledajo. Nekaj primerov iz pomembnej\u0161ih fizikalnih revij:\n",
"\n",
"Pomembno je, da so grafi konsistentni (imajo vsi osi enake debeline, enako velikost pisave -- le ta naj bo enako velika kot v tekstu, ...) To najla\u017eje dose\u017eemo tako, da si pripravimo standarden nabor nastavitev, ki jih potem uporabimo pri vseh grafih. Primer:"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"from pylab import *\n",
"%matplotlib inline\n",
"\n",
"# nastavitve za izris grafov (http://matplotlib.org/1.3.1/users/customizing.html)\n",
"rc('text', usetex=True)\n",
"rc('font', size=12, family='serif', serif=['Computer Modern'])\n",
"rc('xtick', labelsize='small')\n",
"rc('ytick', labelsize='small')\n",
"rc('legend', frameon=False, fontsize='medium')\n",
"rc('figure', figsize=(5, 3))"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 1
},
{
"cell_type": "heading",
"level": 4,
"metadata": {},
"source": [
"Primer enostavnega grafa"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Pri nekem poskusu so merili odgovor mi\u0161i\u010dnega vlakna na adrenalin. Mi\u0161i\u010dno vlakno iz \u017eabjega srca so napeli na mikrosilomer. Vlakno so oblivali z raztopino adrenalina razli\u010dnih koncentracij in merili silo skr\u010denja. Rezultati teh meritev so shranjeni v datoteki adrenalin.dat. V prvem stolpcu datoteke je koncentracija adrenalina v $\\mu$g/l, v drugem pa sila skr\u010denja, ki so jo normirali na 100% pri najve\u010dji koncentraciji.\n",
"\n",
"Podatke najprej preberemo iz datoteke v dvodimenzionalno polje. "
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"podatki=loadtxt('adrenalin.dat')\n",
"podatki"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 2,
"text": [
"array([[ 1. , 0. ],\n",
" [ 2. , 0. ],\n",
" [ 7. , 15.3],\n",
" [ 10. , 34.6],\n",
" [ 20. , 49.3],\n",
" [ 70. , 82.6],\n",
" [ 200. , 96. ],\n",
" [ 1000. , 100. ]])"
]
}
],
"prompt_number": 2
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Prebrane podatke prika\u017eemo na grafu, da dobimo ob\u010dutek o obna\u0161anju izmerjene koli\u010dine. Pri poskusih obi\u010dajno kontroliramo eno koli\u010dino in opazujemo, kako le-ta vpliva na neko drugo koli\u010dino. Prvo (v na\u0161em primeru koncentracijo adrenalina) prika\u017eemo na vodoravni osi grafa, drugo (normirano silo skr\u010denja) pa na navpi\u010dni osi."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"plot(podatki[:, 0], podatki[:, 1])"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "pyout",
"prompt_number": 3,
"text": [
"[]"
]
},
{
"metadata": {},
"output_type": "display_data",
"png": 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1ZrO5Y19GqX+lUgnHcTqvb12q53kelUoFy7L2tK9QKGx7nYHfLBmnNYaO45DP5ykWixiG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\nPQWhiMSeglBEYu//lT9tCYZqkH4AAAAASUVORK5CYII=\n",
"text": [
""
]
}
],
"prompt_number": 3
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Graf priredimo:\n",
"\n",
"- Rezultate poskusa prika\u017eemo s to\u010dkami, saj so daljice, ki povezujejo izmerjene vrednosti na zgornjem grafu, zavajajo\u010de.\n",
"
- Odstranimo barve, \u010de le-te niso nujno potrebne.\n",
"
- Ob oseh zapi\u0161emo fizikalne koli\u010dine. \u010ce je prostora dovolj, jih opi\u0161emo z besedami, sicer uporabimo ustrezno oznako (oznaka naj bo v le\u017ee\u010di pisavi). \n",
"
- Ob vseh fizikalnih koli\u010dinah zapi\u0161emo, v katerih enotah so prikazane (enota naj bo v pokon\u010dni pisavi).\n",
"
- Nekoliko skr\u010dimo obmo\u010dje koncentracij adrenalina na vodoravni osi, da se lep\u0161e vidi obna\u0161anje pri majhnih koncentracijah.\n",
"
- Dodamo mre\u017eo, da la\u017eje od\u010ditavamo vrednosti. \n",
"
"
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"graf=figure()\n",
"plot(podatki[0:7, 0], podatki[0:7, 1], 'ko', clip_on=False)\n",
"xlabel(r'Koncentracija adrenalina ($\\mu$g/l)')\n",
"ylabel(r'$F/F_\\textrm{max}$ (\\%)')\n",
"yticks(linspace(0, 100, 5))\n",
"grid(True)"
],
"language": "python",
"metadata": {},
"outputs": [
{
"metadata": {},
"output_type": "display_data",
"png": 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"text": [
""
]
}
],
"prompt_number": 4
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Graf shranimo v datoteko adrenalin.pdf. \u010ce je le mogo\u010de, uporabimo vektorski format, ki omogo\u010da poljubno pove\u010davo brez izgube kvalitete slike."
]
},
{
"cell_type": "code",
"collapsed": false,
"input": [
"graf.tight_layout(pad=0.3)\n",
"graf.savefig('adrenalin.pdf')"
],
"language": "python",
"metadata": {},
"outputs": [],
"prompt_number": 5
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"Datoteko z grafom vklju\u010dimo v \u010dlanek (vektorski format, bitni format). Nad ali pod grafom dodamo opisno vrstico, ki naj vsebuje \u0161tevilko grafa in opis na grafu prikazanih koli\u010din. Graf, skupaj z opisno vrstico, naj bo bralcu razumljiv sam po sebi, brez branja \u010dlanka!\n",
"\n"
]
},
{
"cell_type": "heading",
"level": 2,
"metadata": {},
"source": [
"Naloge"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"\n",
"- Nari\u0161i graf s podatki iz datoteke mtt1.dat. To je meritev diferencialnega sipalnega\n",
"preseka (drugi stolpec, v enotah fb $c^2$/GeV) za tvorbo para kvarkov top in anti-top v odvisnosti od invariantne mase tak\u0161nega para (prvi stolpec v enotah GeV/$c^2$) na trkalniku protonov in antiprotonov Tevatron v Fermilabu, ZDA.\n",
"\n",
"
- V datoteki Kredarica.zip so zbrani vremenski podatki z merilne postaje Kredarica za obdobje od 1. 1. 1955 do 31. 1. 2014. Datoteka TG_STAID001752.txt vsebuje podatke o povpre\u010dni dnevni temperaturi (zapis podatkov je razlo\u017een v glavi datoteke). Na grafu prika\u017ei, kako se je povpre\u010dna dnevna temperatura spreminjala v letu 2010.\n",
"\n",
"
- Nari\u0161i graf s podatki iz datoteke CSL123.MuD. To je meritev absorpcije rentgenskih \u017earkov (logaritem razmerja vpadnega in prepu\u0161\u010denega toka, drugi stolpec), z energijo fotonov (prvi stolpec) v podro\u010dju robov L (L3 = 5017.8 eV, L2 = 5365.6 eV, L1 = 5720.4 eV), v cezijevi pari, izvedena na sinhrotronu v Hamburgu. Nari\u0161i posebej \u0161e o\u017eje obmo\u010dje robu L3 (-50 eV, 150 eV), da bo profil robu razlo\u010dnej\u0161i. Ali meni\u0161, da je ostri vrh pri\u0161krnjen zaradi pregrobega koraka v energiji?\n",
"
"
]
}
],
"metadata": {}
}
]
}