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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.
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
Median The median is defined only for a data set which has been sorted first, that means that the values are in order. The median of a sorted set of data values (n) is defined
Operation on file: We concentrate first on the fgetl function that reads strings from the file one line at a time. The fgetl functions afford more control over how the data is
Mode The mode of a data set is the value which appears most often. The built-in function in a MATLAB for this is known as the mode. >> x = [9 10 10 9 8 7 3 10 9 8 5 10];
Nested Functions: We have seen that the loops can be nested, that means that one inside of the other, functions can be nested. The terminology for nested functions is that an
Example of Vectorizing: Likewise, for an operation on a matrix, a nested loop would be needed; for illustration, supposing a matrix variable mat: [r c] = size(mat); for
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
Illustration of Binary search: An illustration to search for the key of 91 in the vector is as shown below: The table below shows what will happen in each iteration of
Example of Median For the vector [1 4 5 9 12 33], the median is the average of the 5 & 9 in the middle: >> median([1 4 5 9 12 33]) ans = 7
Example of Mode When no value appears more often than any other, the smallest value in the vector will be the mode of the vector. >> shortx = [2 5 1 4]; >> mode(shortx
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