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1 .. Objectives |
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2 .. ---------- |
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3 |
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4 .. By the end of this tutorial, you will be able to |
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5 |
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6 .. 1. Defining a list of numbers |
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7 .. 2. Squaring a list of numbers |
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8 .. 3. Plotting data points. |
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9 .. 4. Plotting errorbars. |
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10 |
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11 |
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12 .. Prerequisites |
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13 .. ------------- |
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14 |
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15 .. 1. getting started with plotting |
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16 |
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17 |
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18 .. Author : Amit |
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19 Internal Reviewer : |
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20 External Reviewer : |
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21 Checklist OK? : <put date stamp here, if OK> [2010-10-05] |
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22 |
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23 Plotting Experimental Data |
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24 ============================= |
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25 Hello and welcome , this tutorial on Plotting Experimental data is |
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26 presented by the fossee team. |
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27 |
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28 {{{ Show the slide containing title }}} |
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29 |
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30 |
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31 {{{ Show the Outline Slide }}} |
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32 |
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33 Here we will discuss plotting Experimental data. |
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34 |
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35 1. We will see how we can represent a sequence of numbers in Python. |
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36 |
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37 2. We will also become fimiliar with elementwise squaring of such a |
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38 sequence. |
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39 |
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40 3. We will also see how we can use our graph to indicate Error. |
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41 |
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42 One needs to be fimiliar with the concepts of plotting |
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43 mathematical functions in Python. |
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44 |
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45 We will use data from a Simple Pendulum Experiment to illustrate our |
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46 points. |
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47 |
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48 {{{ Simple Pendulum data Slide }}} |
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49 |
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50 |
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51 |
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52 |
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53 As we know for a simple pendulum length,L is directly proportional to |
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54 the square of time,T. We shall be plotting L and T^2 values. |
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55 |
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56 |
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57 First we will have to initiate L and T values. We initiate them as sequence |
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58 of values. To tell ipython a sequence of values we write the sequence in |
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59 comma seperated values inside two square brackets. This is also called List |
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60 so to create two sequences |
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61 |
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62 L,t type in ipython shell. :: |
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63 |
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64 In []: L = [0.1, 0.2, 0.3, 0.4, 0.5,0.6, 0.7, 0.8, 0.9] |
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65 |
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66 In []: t= [0.69, 0.90, 1.19,1.30, 1.47, 1.58, 1.77, 1.83, 1.94] |
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67 |
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68 |
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69 |
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70 To obtain the square of sequence t we will use the function square |
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71 with argument t.This is saved into the variable tsquare.:: |
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72 |
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73 In []: tsquare=square(t) |
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74 |
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75 array([ 0.4761, 0.81 , 1.4161, 1.69 , 2.1609, 2.4964, 3.1329, |
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76 3.3489, 3.7636]) |
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77 |
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78 |
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79 Now to plot L vs T^2 we will simply type :: |
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80 |
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81 In []: plot(L,t,.) |
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82 |
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83 '.' here represents to plot use small dots for the point. :: |
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84 |
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85 In []: clf() |
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86 |
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87 You can also specify 'o' for big dots.:: |
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88 |
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89 In []: plot(L,t,o) |
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90 |
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91 In []: clf() |
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92 |
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93 |
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94 {{{ Slide with Error data included }}} |
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95 |
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96 |
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97 Now we shall try and take into account error into our plots . The |
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98 Error values for L and T are on your screen.We shall again intialize |
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99 the sequence values in the same manner as we did for L and t :: |
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100 |
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101 In []: delta_L= [0.08,0.09,0.07,0.05,0.06,0.00,0.06,0.06,0.01] |
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102 |
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103 In []: delta_T= [0.04,0.08,0.11,0.05,0.03,0.03,0.01,0.07,0.01] |
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104 |
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105 |
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106 |
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107 Now to plot L vs T^2 with an error bar we use the function errorbar() |
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108 |
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109 The syntax of the command is as given on the screen. :: |
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110 |
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111 |
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112 In []: errorbar(L,tsquare,xerr=delta_L, yerr=delta_T, fmt='b.') |
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113 |
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114 This gives a plot with error bar for x and y axis. The dots are of blue color. The parameters xerr and yerr are error on x and y axis and fmt is the format of the plot. |
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115 |
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116 |
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117 similarly we can draw the same error bar with big red dots just change |
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118 the parameters to fmt to 'ro'. :: |
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119 |
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120 In []: clf() |
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121 In []: errorbar(L,tsquare,xerr=delta_L, yerr=delta_T, fmt='ro') |
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122 |
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123 |
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124 |
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125 thats it. you can explore other options to errorbar using the documentation |
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126 of errorbar.:: |
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127 |
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128 In []: errorbar? |
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129 |
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130 |
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131 {{{ Summary Slides }}} |
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132 |
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133 In this tutorial we have learnt : |
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134 |
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135 1. How to declare a sequence of number , specifically the kind of sequence we learned was a list. |
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136 |
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137 2. Plotting experimental data extending our knowledge from mathematical functions. |
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138 |
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139 3. The various options available for plotting dots instead of lines. |
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140 |
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141 4. Plotting experimental data such that we can also represent error. We did this using the errorbar() function. |
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142 |
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143 |
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144 {{{ Show the "sponsored by FOSSEE" slide }}} |
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145 |
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146 |
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147 |
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148 This tutorial was created as a part of FOSSEE project. |
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149 |
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150 Hope you have enjoyed and found it useful. |
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151 |
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152 Thankyou |
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153 |
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154 |
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155 |
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156 Author : Amit Sethi |
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157 Internal Reviewer : |
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158 Internal Reviewer 2 : |