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Diffstat (limited to 'Thermodynamics_by_J._P._Holman/ch5_1.ipynb')
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diff --git a/Thermodynamics_by_J._P._Holman/ch5_1.ipynb b/Thermodynamics_by_J._P._Holman/ch5_1.ipynb new file mode 100755 index 00000000..eac11d77 --- /dev/null +++ b/Thermodynamics_by_J._P._Holman/ch5_1.ipynb @@ -0,0 +1,209 @@ +{ + "metadata": { + "name": "", + "signature": "sha256:7515996c0789938329f86975cb5205356a100488f9513af4795fb2fe55a812d5" + }, + "nbformat": 3, + "nbformat_minor": 0, + "worksheets": [ + { + "cells": [ + { + "cell_type": "heading", + "level": 1, + "metadata": {}, + "source": [ + "Chapter 5 : principles of statistical\n", + "thermodynamics" + ] + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example 5.1 pg : 104" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from math import factorial\n", + "\t\t\t\n", + "# Variables\n", + "N1 = 1.\n", + "N2 = 1.\n", + "N3 = 3.\n", + "N4 = 1.\n", + "\t\t\t\n", + "# Calculations\n", + "N = N1+N2+N3+N4\n", + "sig = factorial(N) /(factorial(N1) *factorial(N2)*factorial(N3)*factorial(N4))\n", + "\t\t\t\n", + "# Results\n", + "print \"No. of ways of arranging = %d \"%(sig)\n" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "No. of ways of arranging = 120 \n" + ] + } + ], + "prompt_number": 1 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example 5.2 pg : 104" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "\t\t\t\n", + "# Variables\n", + "N = 6.\n", + "g = 4.\n", + "\t\t\t\n", + "# Calculations\n", + "sig = factorial(g+N-1) /(factorial(g-1) *factorial(N))\n", + "\t\t\t\n", + "# Results\n", + "print \"No. of ways of arranging = %d \"%(sig)\n" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "No. of ways of arranging = 84 \n" + ] + } + ], + "prompt_number": 2 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example 5.3 pg : 104" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "from math import factorial\t\t\t\n", + "# Variables\n", + "N = 6.\n", + "g = 8.\n", + "\t\t\t\n", + "# Calculations\n", + "sig = factorial(g) /(factorial(N) *factorial(g-N))\n", + "\t\t\t\n", + "# Results\n", + "print \"No. of ways = %d \"%(sig)\n" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "No. of ways = 28 \n" + ] + } + ], + "prompt_number": 3 + }, + { + "cell_type": "heading", + "level": 2, + "metadata": {}, + "source": [ + "Example 5.4 pg : 121" + ] + }, + { + "cell_type": "code", + "collapsed": false, + "input": [ + "%matplotlib inline\n", + "\n", + "\n", + "import math \n", + "from matplotlib.pyplot import bar\n", + "\n", + "# Variables\n", + "N0 = 1.\n", + "\t\t\t\n", + "# Calculations\n", + "N1 = 3/math.e\n", + "N2 = 6/math.e**2\n", + "N3 = 10/math.e**3\n", + "N = N0+N1+N2+N3\n", + "ei = [0, 1, 2, 3]\n", + "\n", + "f0 = N0/N\n", + "f1 = N1/N\n", + "f2 = N2/N\n", + "f3 = N3/N\n", + "fi = [f0, f1, f2, f3]\n", + "\t\t\t\n", + "# Results\n", + "print \"fractional population of level 0 = %.3f\"%(f0)\n", + "print \" fractional population of level 1 = %.3f\"%(f1)\n", + "print \" fractional population of level 2 = %.3f\"%(f2)\n", + "print \" fractional population of level 3 = %.3f\"%(f3)\n", + "bar(ei,fi,0.1)\n" + ], + "language": "python", + "metadata": {}, + "outputs": [ + { + "output_type": "stream", + "stream": "stdout", + "text": [ + "fractional population of level 0 = 0.293\n", + " fractional population of level 1 = 0.323\n", + " fractional population of level 2 = 0.238\n", + " fractional population of level 3 = 0.146\n" + ] + }, + { + "metadata": {}, + "output_type": "pyout", + "prompt_number": 1, + "text": [ + "<Container object of 4 artists>" + ] + }, + { + "metadata": {}, + "output_type": "display_data", + "png": 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+ "text": [ + "<matplotlib.figure.Figure at 0x103672c90>" + ] + } + ], + "prompt_number": 1 + } + ], + "metadata": {} + } + ] +}
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