Python/C2/Plotting-the-data/English
Visual Cue | Narration |
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Containing title, name of the production team along with the logo of MHRD |
Hello Friends and Welcome to this tutorial on "Plotting Experimental data". |
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Learning objectives |
At the end of this tutorial, you will be able to,
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Simple Pendulum data |
One needs to be familiar with the concepts of plotting mathematical functions in Python.
We will use data from a Simple Pendulum Experiment to illustrate. |
L = [0.1, 0.2, 0.3, 0.4, 0.5,0.6, 0.7, 0.8, 0.9]
T= [0.69, 0.90, 1.19,1.30, 1.47, 1.58, 1.77, 1.83, 1.94] |
As we know for a simple pendulum, length L is directly proportional to the square of time T. We shall be plotting L and T^2 values.
First we will have to initiate L and T values. We initiate them as sequence of values. We define a sequence by comma separated values inside two square brackets. This is also called a List. Let's create two sequences L and t. |
Tsquare=square(T)
Tsqaure array([ 0.4761, 0.81 , 1.4161, 1.69 , 2.1609, 2.4964, 3.1329, 3.3489, 3.7636]) |
To obtain the square of sequence T we will use the function square with argument T.This is saved into the variable Tsquare. |
plot(L,Tsquare,'.') | Now to plot L vs T^2, we will simply type |
clf()
plot(L,Tsquare,'o') clf() |
'.' here displays the plot in a dot pattern. You can also specify 'o' for big dots. For this let us clear the plot first. |
Let us move further. For any experimental there is always an error in measurements due to instrumental and human constraints. Now we shall try and take these errors into account in our plots . | |
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Assignment 1 |
Pause the video here, try out the following exercise and resume the video.
Plot the given experimental data with large dots. The data is on your screen. |
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Assessment 1 data |
The error data we will use is on your screen. |
delta_L= [0.08,0.09,0.07,0.05,0.06,0.00,0.06,0.06,0.01]
delta_T= [0.04,0.08,0.03,0.05,0.03,0.03,0.04,0.07,0.08] |
We shall again initialize the sequence values in the same manner as we did for L and T. |
errorbar(L,Tsquare,xerr=delta_L, yerr=delta_T, fmt='bo') | Now to plot L vs T^2 with an error bar we use the function errorbar(). |
clf()
errorbar(L,Tsquare,xerr=delta_L, yerr=delta_T, fmt='r.') |
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.
similarly we can draw the same error bar with small red dots just change the parameters of fmt to 'r.'. |
errorbar? | you can explore other options to errorbar using the documentation of errorbar. |
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Assignment 2 |
Pause the video here, try out the following exercise and resume the video.
Plot the given experimental data with small dots. Also include the error in your plot. |
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Assignment 2 data' |
The data is on your screen |
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Summary Slide |
This brings us to the end of the end of this tutorial. In this tutorial, we have learnt to,
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Self assessment questions slide |
Here are some self assessment questions for you to solve
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Solution of self assessment questions on slide |
And the answers,
1. To square a sequence of values, we use the function square square(distance_values) 2. We pass an additional argument stating the desired parameter plot(L,T,'r+') |
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Acknowledgment slide |
Hope you have enjoyed this tutorial and found it useful. Thank You! |