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Example of Core objects:
The one core graphics object is a line that is also what the plot function produces. Here is an illustration of generating a line object, altering some properties, and saving the handle in a variable hl:
>> x = -2*pi: 1/5 : 2*pi;
>> y = sin(x);
>> hl = line(x,y,'LineWidth', 3, 'Color', [0.5 0.5 0.5])
hl =
159.0405
As shown in figure below, this draws a reasonably thick grey line for the sin function. As the handle will be valid as long as the Figure Window is not closed. A few of the properties of this object are as shown below:
>> get(hl)
Color = [0.5 0.5 0.5]
EraseMode = normal
LineStyle = -
LineWidth = [3]
Marker = none
MarkerSize = [6]
t = auto
MarkerFaceColor = none
XData = [ (1 by 63) double array]
YData = [ (1 by 63) double array]
ZData = []
etc.
Logical Built-In Functions: There are built-in functions in the MATLAB which are useful in conjunction with vectors or matrices of all logical true or false values; two of the
Properties of the text box - graphics objects: By using get will show properties of the text box, the illustration is as shown below: >> get(thand) BackgroundColor
Combining Nested FOR Loops and the IF Statements: The statements inside a nested loop can be any of the valid statement, involving any selection statement. For e.g., there can
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Statistics There are numerous statistical analyses which can be executed on data sets. In MATLAB software, the statistical functions are in the data analysis help topic known a
Illustration of Nested loops: Running the script shows the output: >> printstars ***** ***** ***** The variable rows identifies the number of rows to print, and
Program of Persistent variables: The program below elaborates this. The script calls a function func1 that initializes a variable count to 0, then increment it, and print the
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#qYou will need to examine two of the nine sections of data: one section of qualitative data (choose either Gender or Position) one section of quantitative data (choose either Intr
Introduction and Purpose In the lectures and tutorials you have been introduced to a number of probability distributions. You have also learned that modelling any system (such
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