Grace/C3/Data-Fitting/English-timed
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Revision as of 13:07, 30 August 2022 by PoojaMoolya (Talk | contribs)
Time | Narration |
00:01 | Welcome to the tutorial on Data fitting in Grace. |
00:06 | In this tutorial, we will
Fit a given set of data points to a linear equation |
00:14 | Add two datasets to a graph panel |
00:18 | Add legends and format the legend properties |
00:24 | To record this tutorial, I am using
Ubuntu Linux 16.04 OS |
00:33 | Grace 5.1.25 and Gedit 3.18.3 |
00:42 | To follow this tutorial,
Learner must be familiar with the Grace interface. |
00:48 | For pre-requisite tutorials, please visit this website. |
00:54 | Data fitting is a process to find a mathematical relation between two variables. |
01:01 | An equation is used to describe the XY dataset pair. |
01:06 | Using an iterative process, the coefficients are optimized. |
01:11 | The process returns the best possible coefficients for the equation. |
01:17 | Go to Desktop. Notice the file, line-fit.txt. |
01:24 | This file is provided to you in the Code Files link. |
01:29 | I have downloaded, extracted and saved the file to the Desktop directory. |
01:36 | Next, open the Grace program and load this file to plot an XY graph. |
01:43 | Choose XY data set, and autoscale data. |
01:48 | Next I will format the plot. |
01:52 | I have changed the symbols, line style, tick marks and axis labels. |
01:59 | The data points do not lie on a straight line. |
02:04 | The data points look scattered around a straight line. |
02:08 | We will fit this data to a straight line. |
02:12 | For a straight line, this is process is called linear regression. |
02:18 | A straight line is described by an equation in two variables, |
02:24 | The equation has the form, y equals mx+c. |
02:29 | Here, m is the slope of the line and c is the intercept. |
02:36 | Go to Data and select Transformations. |
02:42 | Notice the available options. |
02:46 | Choose Regression from the list. |
02:48 | A Regression dialog box opens. |
02:52 | Choose the data set of interest from Apply to set. |
02:58 | Currently only a single set is loaded and it is shown as S0. |
03:05 | The next number is the number of points that are present in the dataset. |
03:12 | If many datasets are loaded more sets will be seen, in the Apply to set box. |
03:19 | Choose linear for Type of fit. |
03:23 | In the Load drop-down, choose Fitted values. |
03:29 | For restrictions choose None. |
03:33 | If only part of the data set needs to be fitted, enter the required range. |
03:39 | We can also specify the start load at and stop load at values in the form. |
03:47 | I will leave it as is and will not make changes here. |
03:52 | Click on Accept to run the data fitting. |
03:56 | The data fitting algorithm runs. |
03:59 | A Grace console window appears with mathematical details. |
04:04 | We can see the equation used for the fitting. |
04:08 | The output values of residual, slope, intercept and other parameters are seen. |
04:17 | The fitted line appears on the screen. |
04:21 | The fitted values are loaded in a different set, S1. |
04:26 | Click on File, Save to save the parameters. |
04:31 | The Grace: Save logs window opens. |
04:35 | In Save to file text box, type the filename as line-regression.txt. |
04:43 | Click on Apply and then click on Close to close the dialog box. |
04:49 | Close the Grace Console by File, Close or press theEsc key. |
04:56 | Click on Close in the Regression window. |
05:00 | Double click on the line in the graph. |
05:03 | Grace Set appearance window opens. |
05:07 | In the select set form, select S1 data set.
This is the fitted data. |
05:15 | Right click to open the context menu. |
05:19 | Select Edit, and in In spreadsheet option. |
05:24 | The Grace: Spreadsheet dataset editor appears. |
05:29 | Notice the x and corresponding fitted y values of the fitted data. |
05:36 | These values are different from the input data. |
05:40 | This line fits the input data best, with a linear equation. |
05:46 | Close the Spreadsheet dataset Editor. |
05:50 | The original data set and the fitted values are the 2 datasets in the graph. |
05:58 | Datasets are labeled as [S0] for first set and [S1] for the second set. |
06:05 | We can add more datasets to this graph panel. |
06:10 | For this load the data using the Data, import, ASCII option from the menu. |
06:18 | Next, we will add legends to the plot. |
06:22 | Open the Set Appearance window and choose the dataset S0. |
06:29 | Under Legend, in the String field, type Data as the legend label.
Click on Apply. |
06:38 | Next choose S1 dataset from the Select set data form. |
06:45 | Here, I will type Fitted data for the legend and click on Apply. |
06:53 | Close the Set Appearance window. |
06:57 | For some users, the legend position may be outside the graph border. |
07:03 | To reposition the legends, place the cursor in the legend box. |
07:09 | Then press Control and L keys together. |
07:13 | The cursor changes to a pointer. |
07:17 | Left click and drag the legend box to the desired position. |
07:24 | Then, press Enter. |
07:27 | Press the Escape key to exit the movement mode. |
07:32 | Next, open the Graph appearance window. |
07:36 | In the window, click on the Legends tab, to format the legend fonts. |
07:43 | Under the text properties, move the character size slider to 70. |
07:49 | The legends look very large compared to the graph. |
07:53 | I will retain the font type as Times-Roman. |
07:58 | Click on Apply to apply the changes. |
08:02 | Click on the legend box tab. |
08:06 | We can also specify the position of the legend in the location section.
I will leave it as is. |
08:10 | In the Frame line section, for Pattern, I will choose None. |
08:22 | Click on Apply.
This will remove the legend frame box. |
08:28 | Then Close the dialog box. |
08:31 | Now save the project in the Desktop directory. |
08:36 | I will use the file name regression dot agr. |
08:41 | Press Control Q or Click on File, Exit to exit Grace. |
08:49 | Let’s summarize. |
08:51 | In this tutorial we,
Performed data fitting for a straight line. |
08:57 | Added two datasets in the graph panel. |
09:01 | Added legends to the plot and Formatted the legend properties. |
09:08 | For assignment activity, please do the following. |
09:13 | Two assignment files are provided in the Code files link. |
09:18 | Plot them in the same graph panel. |
09:22 | Perform quadratic regression on the parabola1.txt file. |
09:28 | Load the fitted data in the graph. |
09:32 | Add legend strings and reposition them inside the graph panel. |
09:38 | Format the appearance of the three datasets to distinguish them. |
09:43 | Your completed assignment may look similar to this. |
09:48 | This video summarizes the Spoken Tutorial Project.
Please download and watch it. |
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10:24 | This is Rani from IIT Bombay. Thank you for joining. |