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