summaryrefslogtreecommitdiff
path: root/Water_and_Wastewater_Engineering/ch4.ipynb
diff options
context:
space:
mode:
Diffstat (limited to 'Water_and_Wastewater_Engineering/ch4.ipynb')
-rw-r--r--Water_and_Wastewater_Engineering/ch4.ipynb287
1 files changed, 287 insertions, 0 deletions
diff --git a/Water_and_Wastewater_Engineering/ch4.ipynb b/Water_and_Wastewater_Engineering/ch4.ipynb
new file mode 100644
index 00000000..c47b5c94
--- /dev/null
+++ b/Water_and_Wastewater_Engineering/ch4.ipynb
@@ -0,0 +1,287 @@
+{
+ "metadata": {
+ "name": "",
+ "signature": "sha256:69dc81267d132717cceb5ed01afab9cdbb37bfc431d05698243961d6dd4f91a3"
+ },
+ "nbformat": 3,
+ "nbformat_minor": 0,
+ "worksheets": [
+ {
+ "cells": [
+ {
+ "cell_type": "heading",
+ "level": 1,
+ "metadata": {},
+ "source": [
+ "Chapter 4 : Information Analysis"
+ ]
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 4.2 Page No : 4-22"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "from numpy import *\n",
+ "\n",
+ "#initialisation of variables\n",
+ "y_bar = 19.5\t#in\n",
+ "x = 396.8\t#in\n",
+ "n = 6\t#in\n",
+ "y1 = 2.20\t#in\n",
+ "x1 = 51.14\t#in\n",
+ "p = 5.64\t#in\n",
+ "ob_y = array([44,20,24,14,12,3])\n",
+ "ob_x = array([5.3,3.5,3.,1.2,0.48,-0.26])\n",
+ "\n",
+ "#CALCULATIONS\n",
+ "Beta = round((x-n*(y_bar)*(y1))/(x1-n*(y1)**2),2)\n",
+ "y = around(y_bar + Beta*(ob_x - 2.2),decimals=1)\n",
+ "Ri = ob_y - y\n",
+ "sumRi = sum(Ri)\n",
+ "\n",
+ "#RESULTS\n",
+ "print \"Beta B = %.2f\"%Beta\n",
+ "print \"residuals Ri are : \" ,Ri\n",
+ "print 'the method of leate squares = %.2f minimum'%(sumRi)\n",
+ "\n",
+ "# note : answer is slighty different because of rounding off error."
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Beta B = 6.31\n",
+ "residuals Ri are : [ 4.9 -7.7 -0.5 0.8 3.4 -1. ]\n",
+ "the method of leate squares = -0.10 minimum\n"
+ ]
+ }
+ ],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 4.3 Page No : 4-30"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "from numpy import *\n",
+ "\n",
+ "#initialisation of variables\n",
+ "a = 12.\t #in\n",
+ "h = 121.\t#in\n",
+ "p = 11. #in\n",
+ "s = 220.\t#in\n",
+ "observed_time = array([11,12,13,14,15,16,17,18,19,20,21])\n",
+ "i = array([1,2,3,4,5,6,7,8,9,10,11])\n",
+ "observed_magnitude = array([2,4,6,8,10,12,14,16,18,20,22])\n",
+ "y_uy = array([-10,-8,-6,-4,-2,0,2,4,6,8,10])\n",
+ "\n",
+ "#CALCULATIONS\n",
+ "B = a/p*(h-1)*s\t#per unit\n",
+ "n = len(i)\n",
+ "i_6 = i - (n+1)/2\n",
+ "i_6_y_uy = (i - (n+1)/2)*y_uy\n",
+ "\n",
+ "#RESULTS\n",
+ "print \"Observed Time \", observed_time\n",
+ "print \"Order,i \", i\n",
+ "print \"[i-(n+1)/2] \", i_6\n",
+ "print \"Observed magnitude \", observed_magnitude\n",
+ "print \"Deviation from mean \", y_uy\n",
+ "print \"[i-(n+1)/2](y-uy) \", i_6_y_uy \n",
+ "\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "Observed Time [11 12 13 14 15 16 17 18 19 20 21]\n",
+ "Order,i [ 1 2 3 4 5 6 7 8 9 10 11]\n",
+ "[i-(n+1)/2] [-5 -4 -3 -2 -1 0 1 2 3 4 5]\n",
+ "Observed magnitude [ 2 4 6 8 10 12 14 16 18 20 22]\n",
+ "Deviation from mean [-10 -8 -6 -4 -2 0 2 4 6 8 10]\n",
+ "[i-(n+1)/2](y-uy) [50 32 18 8 2 0 2 8 18 32 50]\n"
+ ]
+ }
+ ],
+ "prompt_number": 18
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 4.5 Page No : 4-31"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math \n",
+ "\t\n",
+ "#initialisation of variables\n",
+ "a = 4404.\t#ft\n",
+ "q = 9.\t#ft\n",
+ "mu = 12.\t#ft\n",
+ "\t\n",
+ "#CALCULATIONS\n",
+ "F = math.sqrt(a/q)\t#ft\n",
+ "CF = F/mu*100\t#percent\n",
+ "\t\n",
+ "#RESULTS\n",
+ "print 'the coefficient of fluctuation is = %.0f percent'%(CF)\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "the coefficient of fluctuation is = 184 percent\n"
+ ]
+ }
+ ],
+ "prompt_number": 1
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 4.7 Page No : 4-35"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math \n",
+ "\t\n",
+ "#initialisation of variables\n",
+ "h2 = 5\t#in\n",
+ "x = 3.72\t#in\n",
+ "x1 = 1.28\t#in\n",
+ "\t\n",
+ "#CALCULATIONS\n",
+ "H = h2*x1/x\t#in\n",
+ "\t\n",
+ "#RESULTS\n",
+ "print 'the either side of the center of the scale = %.2f in'%(H)\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "the either side of the center of the scale = 1.72 in\n"
+ ]
+ }
+ ],
+ "prompt_number": 2
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 4.8 Page No : 4-35"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "\t\n",
+ "#initialisation of variables\n",
+ "p = 80\t#in\n",
+ "q = 20\t#in\n",
+ "\t\n",
+ "#CALCULATIONS\n",
+ "K = p+q\t#ft\n",
+ "\t\n",
+ "#RESULTS\n",
+ "print 'the moments of the arithmetically normal frequency curve = %.0f ft'%(K)\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "the moments of the arithmetically normal frequency curve = 100 ft\n"
+ ]
+ }
+ ],
+ "prompt_number": 3
+ },
+ {
+ "cell_type": "heading",
+ "level": 2,
+ "metadata": {},
+ "source": [
+ "Example 4.9 Page No : 4-38"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "collapsed": false,
+ "input": [
+ "import math \n",
+ "\t\n",
+ "#initialisation of variables\n",
+ "g = 3.2541\t#in\n",
+ "g1 = 3.46\t#in\n",
+ "m = 0.5390\t#ft\n",
+ "h = 2./99\t#ft\n",
+ "p = 1.52\t#ft\n",
+ "\t\n",
+ "#CALCULATIONS\n",
+ "L = math.sqrt(g*h)\t#in\n",
+ "mu = g1*p\t#in\n",
+ "M = g1/p\t#percent\n",
+ "\t\n",
+ "#RESULTS\n",
+ "print 'the points necessary to plot the straigt line of fit on math.log probability = %.2f percent'%(M)\n"
+ ],
+ "language": "python",
+ "metadata": {},
+ "outputs": [
+ {
+ "output_type": "stream",
+ "stream": "stdout",
+ "text": [
+ "the points necessary to plot the straigt line of fit on math.log probability = 2.28 percent\n"
+ ]
+ }
+ ],
+ "prompt_number": 4
+ }
+ ],
+ "metadata": {}
+ }
+ ]
+} \ No newline at end of file
generated by cgit (git 2.34.1) at 2025-04-03 08:55:53 +0000