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The MATLAB language uses many specialized objects. For example, Exception objects, timer objects, the serial object, and so on. MATLAB toolboxes are used to define objects to manage data and analyses performed by the toolbox. Objects provide specific functionality that is not easily available from general-purpose language components. Objects are used to inform when errors occur, to execute code at a certain time interval, to enables you to communicate with devices connected to your computer’s serial port, etc.

Syntax:

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Object_name = class_name;

How to Create Matlab Object?To create an object, first, we need to create a class, using ‘ classdef ’ we create a class, in class we take some properties and end the class and then we take methods some methods using function statements after all these lastly we end the class with an end statement. First, we save the class using the .m extension.

Now, take a new Matlab script and create an object using the same class name which we used to create a class. For creating the object we write syntax like:

Object_name = class_name;

Let’s consider a1 is an object name and BasicClass1 is a class name. In class, we create 1 property and 3 methods. After creating an object of class we can perform the several operations on a class by using that class object:-

For accessing the properties to assign the data.

To perform operations on data calling of the method.

We saw all the properties and their current values available in the class.

Examples to Implement Matlab ObjectLet see the first example, in this example first, we create one class, that class name is ‘BasicClass1 ’. In this class we take a property like value, the must be only the numbers. Then we take a method, basically, methods are nothing but operations that defined by the class. We create some operations and then we end the method also with an end statement. And then finally we end the BasicClass1 class with an end statement. In methods for operations, we use some functions. This code saves using the .m extension.

Code:

end

Example #1Let us see to create an object and how it’s used. In this example we can create an object with the respected class name in our example it’s ‘ BasicClass1 ’, we create objects namely ‘a1’. Initially the value of the property it’s empty. Then using objects we can access the properties of the class that’s nothing but the property is value. So we assign some number to the value property using a class object, and simply it can display it.

Code:

Output:

As we have seen in the command window the output was value = [ ] empty. Because the initial value of property is empty. Then we assign the number to property value and the number is pi (3.142) / 3 and displays it using the class object.

Example #2Let us see an example, for this example also we use the same class that’s ‘BasicClass1’. First, we simply create an object for the same class name that’s BasicClass1. Then we can assign the number to property value and display it. Then after we call the methods of that class by using the help of class object ‘a1’. We called the method name, the method name is ‘multiplyBy (obj1 , n1)’ multiplying operation by the given number in parenthesis we simply pass the argument and then display the result.

Code:

multiplyBy(a1,3)

Example #3Let us see an example, for this example also we use the same class that’s ‘BasicClass1’. First, we simply create an object for the same class name that’s BasicClass1. Then we can assign the number to property value and display it. Then after we call the methods of that class by using the help of class object ‘a1’. We called the method name, the method is ‘divideBy (obj1 , n1)’ divide operation by the given number in parenthesis we simply pass the argument and then display the result.

Code:

a1.divideBy( 2 )

Output:

ConclusionIn this article, we saw the concept of Matlab object. We understood the basic concept and different ways to use Matlab objects and what exactly is a Matlab object. And also we saw the syntax. Also first we saw how to declare or create a class on Matlab and then how to create a class object. And what operations we perform using that class object.

Recommended ArticlesThis is a guide to Matlab Object. Here we discuss the Introduction of Matlab Object and how to Create along with different Examples as well as its Code Implementation. You can also go through our suggested articles to learn more –

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## How To Create Pytorch Random With Examples?

Introduction to PyTorch Random

PyTorch random is the functionality available in PyTorch that enables us to get a tensor with random values that belong to the range of 0 to 1. The values are filled using a uniform distribution. In this article, we will try to dive deep into the topic of PyTorch random and understand What PyTorch random is, how to create PyTorch random, alternative PyTorch, PyTorch random examples, and finally provide our conclusion on the same.

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What is PyTorch random? Torch.rand (* size, *, out = None, stype = None, layout = torch. strided, device = None, requires_grad = FalseOutput -The return value of the above function is a tensor object containing random values. Here, the argument named size helps specify the tensor size we want as an output.

Let’s understand various arguments or parameters that we need to pass to the rand function to get a tensor of random values –

Size – This is the integer value that helps specify the shape of the tensor that we get as a resultant and is a sequence of integers. It can be a tuple, list, or any variable number of parameters.

Out – We get the optional parameter and a tensor value as the output.

Device – It is an optional argument and is of the type torch. device. It helps in the specification of the required devices of the output tensor. When not specified, the default value of this argument corresponds to None, which means that the same current device is used for that type of tensor. For example, in the case of CUDA tensor types, the device of CUDA that is currently used is the preferred device, while in the case of CPU tensor types, its corresponding CPU device is referred to by the device.

Generator – It is an optional argument of type torch. Generator and us a pseudo-random number created or generated just for the sampling.

Dtype – It is also an optional argument of type torch. dtype is used to specify the data type we want for the return output tensor. The default value corresponds to None and is a global value when not specified. For more information about this, you can read about the torch. set_default_tensor_type().

Requires_grad – It is an optional argument of Boolean type and has its default value set to false. It specifies whether the auto grad should record all the operations carried on returned tensor.

Layout – It is an optional argument of the torch. Layout type that has its default value set to torch. strode. It helps get the choice of device we want for the output tensor.

How to Create PyTorch random?We can create the PyTorch random tensor containing random values in the range of 0 to 1 simply by importing the torch library in your program and then use the rand function to create your tensor by passing the required size of the output tensor in the parameter. Other optional arguments can also be passed as per your requirement and convenience.

Suppose you want to create a tensor containing random values of size 4, then you can write the statement in your program as a torch.rand(4) after you import the torch at the top. This will create a tensor object having uniformly distributed random values between the range of 0 to 1 of size 4, which means four columns in 1 row.

Alternative PyTorch randomNone of the equivalent alternatives are present for implementing np.random.choice(). You can use the indexing with random integer values or shuffled indexing.

When you want to carry out this without doing any replacement, then you can follow the below steps –

You can go for the generation of n indices that are created randomly.

Further, you can use these indices to index the source tensor object, which is your original tensor.

For example, when you have a tensor named images, you can use the following statement – images [torch.randint(len(images))]

When you want to perform the same task without the involvement of any replacement, then you can follow the below steps –

The index should be shuffled.

Retrieve the first n elements from the tensor.

For example, we will refer to the same scenario above and use the following code.

sampleIndexes = torch.randperm(len(images))[:10] images[smapleIndexes]Suppose you want more information about the torch.randint and torch.randperm, refer to this article.

PyTorch random examplesLet us now consider some examples that will help us understand the implementation of PyTorch random, the rand function.

Example #1We are creating one tensor containing random values and having the shape (2,3)

sampleEducbaTensor1 = torch.rand(2, 3) print(sampleEducbaTensor1)Output:

Example #2We will take one example where we are passing the tuple to define the shape

Code:

sampleEducbaTensor2 = torch.rand((2, 3)) print(sampleEducbaTensor2)Output:

Example #3Let’s create a tensor having four size

sampleEducbaTensor3 = torch.rand(4) print(sampleEducbaTensor3)Output:

Example #4Creating a tensor with the shape of (2,3)

Code:

sampleEducbaTensor4 = torch.rand(2, 3) print(sampleEducbaTensor4)Output:

ConclusionPyTorch random functionality generates a tensor with a random value in nature and between intervals of [0,1]. For this, we will have to use the torch.rand() function and we can specify the desired size and shape of the output tensor we want as a resultant.

Recommended ArticlesWe hope that this EDUCBA information on “PyTorch Random” was beneficial to you. You can view EDUCBA’s recommended articles for more information.

## Different Function Of Linspace In Matlab With Examples

Introduction to Linspace MATLAB

MATLAB is a technical computing language. MATLAB gets its popularity from providing an easy environment for performing and integrating computing tasks, visualizing & programming.

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Uses of MATLAB include (but not limited to)

Computation

Simulation

Modeling

Data analytics (Analysing and Visualizing data)

Prototyping

Application development

Engineering & Scientific graphics

Linspace Function in MATLABIn this article, we will understand a very useful function of MATLAB called ‘linspace’. This function will generate a vector of values linearly spaced between two endpoints. It will need two inputs for the endpoints and an optional input to specify the number of points to include in the two endpoints.

X = linspace(a1, a2)

Now let us understand this one by one

1. X=linspace(a1,a2)This function will return a row of a vector of 100(default) linearly spaced points between a1 and a2

a1 and a2 can be real or complex

a2 can be either larger or smaller than a1

If a2 is smaller than a1 then the vector contains descending values

Here is an example to understand this:

Example #1X = linspace(-1, 1)

It will generate a vector of 100 evenly spaced vectors for the interval [-1, 1]

Output:

Example #2X = linspace(2, 3)

It will generate a vector of 100 evenly spaced vectors for the interval [2,3]

Output:

Example #3X = linspace(2, 1)

Here a2 is smaller than a1, it will generate a vector of 100 evenly spaced vectors for the interval [2,1] in descending order

Output:

2. X=linspace(a1,a2,n)This function will return a row of a vector of “n” points as specified in input for linearly spaced points between a1 and a2. This function gives control of the number of points and will always include the endpoints specified in the input as well.

If n is 1, the function will return a2 as output

If n is zero or negative, the function will return 1by0 empty matrix

Here is an example to understand this:

Example #1X = linspace(-1, 1, 7 )

It will generate a vector of 7 evenly spaced vectors for the interval [-1, 1]

Output:

Example #2X = linspace(2,3,5)

It will generate a vector of 5 evenly spaced vectors for the interval [2,3]

Output:

Example #3X = linspace(2, 3, 1)

Here n = 1, so the function will return a2 input parameter

Output:

Example #4Here n = 0, so function will return 1X0 empty double row vector

Output:

Vector of evenly spaced Complex numbersX = linspace(2+2i, 3+3i)

Here a1 and a2 are complex numbers, it will generate a vector of complex numbers for 100 evenly spaced points for the interval [2+21, 3+3i]

Output:

X= linspace(1+1i, 5+5i, 4)

It will generate a vector of complex numbers with 4 evenly spaced point for the interval [1+1i, 5+5i]

Output:

The linspace function in MATLAB provides us with an array/matrix comprising the desired number of values starting from and ending at a declared value. The produced array will have exactly the desired number of terms which will be evenly spaced. The values will be in the range of start and end values passed. So, the linspace function will help us in creating an instantiated matrix or array.

Recommended ArticlesThis is a guide to Linspace MATLAB. Here we discuss the introduction, Linspace Function in MATLAB and Vector of evenly spaced Complex numbers with examples and outputs. You can also go through our other suggested articles to learn more–

## How To Print Object Array In Javascript?

In this tutorial, we will learn how to print object arrays in JavaScript.

What is an object array or an array of objects? An array of objects is used to store a fixed-size sequential collection of identical elements and store many values in one variable.

Next, we will see the options to print an array of objects in JavaScript.

Using the stringify() Method of the JSON ObjectUsers can follow the syntax below to use this.

Syntax JSON.stringify(v,r,s)In the syntax above, the last two parameters are optional.

Parameters

v − This is the array of objects.

r − This is the replacer. It can change the output by altering or eliminating values. The method will print all values if the r value is null or unspecified. Either a function or an array is used as a replacer.

s − This is the spacing value for the output display. It is for readability purposes. Nothing, null, string, or 1-10 are the possible values of this parameter. If the value is less than 1, JSON print will not have space. If the value is greater than 10, 10 only is taken for indentation. If the value is a string, either the string or the first ten characters of the string are considered for spacing.

ExampleHere in this code, we are taking an array of objects. JSON.stringify() is called directly with this value. Here, the indentation is 1. A condition is given to display the name key alone from the JSON object. This is the second parameter.

let

arr

=

[

{

name

:

“Orange”

,

value

:

1

}

,

{

name

:

“Grapes”

,

value

:

2

}

,

{

name

:

“Apple”

,

value

:

3

}

]

;

document

.

getElementById

(

“idPrint”

)

.

innerHTML

=

JSON

.

stringify

(

arr

,

null

,

4

)

;

Using console.table() MethodHere we will learn how the console.table() method works. This method strictly needs one input. The input is either an array or an object. The method also processes nested cases of both the array and the objects. The second parameter is the column, which is optional.

All browsers that use standard consoles support this method, and Internet Explorer does not support it.

Users can follow the syntax below to use this.

Syntax console.table(d, c)In the syntax above, we need to give the array of objects as the first input.

Parameters

d − An array of objects.

c − Here, we need to specify the key names of the object. The specified key’s keyvalue pairs only will is displayed in the output.

ExampleWe are creating an array of objects in this example program using the new method. This data is given as the first parameter to the console.table() method.

Here, three objects are there in the input. But we have restricted to display of only two in the table format. The key names of the required objects are given as the second parameter. The console.log() method with the program title in the first parameter and the CSS values as the next parameters display the styled title in the following output.

Users need to open the console to see the output for the below example.

function

infoDisp

(

id

,

name

,

job

)

{

this

.

Id

=

id

;

this

.

Name

=

name

;

this

.

Work

=

job

;

}

const

a

=

new

infoDisp

(

1

,

“John”

,

“Doctor”

)

;

const

b

=

new

infoDisp

(

2

,

“Grace”

,

“Homemaker”

)

;

const

c

=

new

infoDisp

(

3

,

“Eagan”

,

“Not working”

)

;

console

.

log

(

‘

%

cThe JavaScript program prints an array

of

objects using

%

cconsole

.

table

(

)

method

‘, ‘

font

–

weight

:

bold

;

font

–

size

:

16

px

;

color

:

#

000000

;

‘, ‘

font

–

weight

:

bold

;

font

–

style

:

italic

;

font

–

size

:

16

px

;

color

:

#

000000

;

‘

)

;

console

.

table

(

[

a

,

b

,

c

]

,

[

“Name”

,

“Work”

]

)

;

This tutorial helped us to learn about the two ways to print an object array. We use the console.dir() generally to verify the object array. To display the object array on the page, JSON.stringify() is used.

We can use the console if we need the table format of the object array.table() method. The only drawback is that some consoles do not support this method. Some console displays the column names in ascending order. That is, the actual object key order is lost.

In short, both methods are simple. Users have choice to choose any method according to their print requirements.

## How Autocorrelation Function Works In Matlab?

Definition of Matlab Autocorrelation

In Matlab, Autocorrelation function means a correlation between numbers in a set or series with other numbers in the same set or series separated by provided time interval. Autocorrelation is also called a serial correlation because it correlates numbers with a delayed copy of itself set or series. Autocorrelation is used in signal processing for analyzing a series of values like time-domain signals. Autocorrelation means the correlation between the observation at the current time spot and the observation at previous time spots. Autocorrelation is used to determine the terms used in the MA model. Autocorrelation is used to measure the relation between the elements’ current value and past values of the same element.

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How does Autocorrelation Function work in Matlab?Autocorrelation measures the relation between elements’ current value and past values of the same element. There are the following steps of autocorrelation function to work in Matlab: –

Step 1: Load and read all the data from the file.

Step 2: Assign all data to a variable.

Step 3: Then, use the appropriate syntax of the ‘Matlab Autocorrelation’ function.

Step 4: then execute the code.

Examples of Matlab AutocorrelationLets us discuss the examples of Matlab Autocorrelation.

Example #1In this example, we calculate the autocorrelation of random Gaussian noise in Matlab. We know that autocorrelation means matching signals with the delayed version itself. Now for random Gaussian noise, only when shift= 0 is there some autocorrelation value, and for all other cases, the autocorrelation result will be zero. Now first, we will generate random Gaussian noise in Matlab. For generating random Gaussian noise, we will use randn function in Matlab. “x= randn(1, length(t))” generates length t Gaussian sequence with mean 0 and variance 1. After that, we use the subplot and plot function to plot the random Gaussian noise signal. Here we will use the Matlab autocorrelation function to calculate the autocorrelation of random Gaussian noise in Matlab.“autocorr(x)” this syntax is used for calculating the autocorrelation of random Gaussian noise. Then subplot and plot function is used for plotting the autocorrelation of random Gaussian noise. To calculate the autocorrelation of a random Gaussian signal, execute the Matlab code.

Code :

Output:

Example #2In this example, we can see how we can find the periodicity of the signal using the function. So let’s first load the data. Here we use office temperature for data. This is, by default, available in Matlab. Once we load the data, we plot the data. We use a plot function to plot the data. After the plotting data, we will find the temperature oscillates. So we take the normal temperature by using mean temperature. “normal_temp= temp -mean(temp)” ones we subtract mean temperature from temperature, we get the normal temperature. After that, we will plot the normal temperature using the plot function. so we get normal temperatures varying around zero. Now we will set sampling ‘fs’ as 24. Then we are going to create a time vector t. The t will start from 0 and go up to the length of the normal temperature. Then we use Matlab autocorrelation to find the periodicity of the signal. Then we use above syntax “[autocor, lags]= xcorr (normal_temp,3*7*fs,’coeff’)”. Here ‘autocor’ variable stores the autocorrelation matrix, and ‘lags’ this variable stores the lags between the data. ‘xcorr’ correlates between normal temperature and sampling frequency. Then we plot the data that lag/fs, and autocor plot the autocorrelation of the signal.

Code:

plot(lags/fs,autocor);

Output:

Example #3In this example, we calculate the autocorrelation of the input sine signal. Now we load the signal in variable ‘x.’ “x= sin(2*t)” is used to get the sine signal in Matlab. After that, we use the subplot and plot function to plot the sine signal. Here we will use the function to calculate the autocorrelation of random Gaussian noise in Matlab.“autocorr(x)” this syntax is used for calculating the autocorrelation of sine signal. Then subplot and plot function is used for plotting the autocorrelation of the sine signal.

Code:

autocorr(x)

Output:

ConclusionIn this article, we saw the concept of Matlab autocorrelation. Basically, this function is used to measure the relation between elements’ current values and past values of the same element. Then we saw how we could find the periodicity of the signal using this function and the efficient work of the Matlab autocorrelation function.

Recommended ArticlesThis is a guide to Matlab Autocorrelation. Here we discuss the definition, How Autocorrelation Function works in Matlab, along with code implementation. You may also have a look at the following articles to learn more –

## How To Remove An Object From A List In Python?

To remove items (elements) from a list in Python, use the list functions clear(), pop(), and remove(). You can also delete items with the del statement by specifying a position or range with an index or slice.

In this article, we will show you how to remove an object/element from a list using python. The following are the 4 different methods to accomplish this task −

Using remove() method

Using del keyword

Using pop() method

Using clear() method

Assume we have taken a list containing some elements. We will return a resultant list after removing the given item from an input list using different methods as specified above.

Method 1: Using remove() methodThe remove() function deletes the given item passed as an argument to it. −

Syntax list.remove(element) Return Value:The remove() function will not return any value(returns None) Algorithm (Steps)Following are the Algorithm/steps to be followed to perform the desired task

Create a variable to store the input list.

Use the remove() method to remove the particular item from the input list by passing the list item to be deleted as an argument to it and applying it to the input list.

Print the result list after removing the specified item from the input list

ExampleThe following program removes the specified item from an input list using the remove() method and prints the resultant list −

inputList

=

[

‘TutorialsPoint’

,

‘Python’

,

‘Codes’

,

‘hello’

,

‘everyone’

]

inputList

.

remove

(

“TutorialsPoint”

)

(

“Input List after removing {TutorialsPoint}:n”

,

inputList

)

OutputOn executing, the above program will generate the following output −

Input List after removing {TutorialsPoint}: ['Python', 'Codes', 'hello', 'everyone']As an input to the code, we were given a sample list with some random values, as well as an object/element to remove from the list. The element was then passed to the remove() method, where it was deleted/removed from the list. If the object/element is not found in the list, a value error will be returned.

Method 2: Using del KeywordThe del statement is not a List function. The del statement can be used to delete items from the list by passing the index of the item (element) to be deleted

Algorithm (Steps)Following are the Algorithm/steps to be followed to perform the desired task −

Create a variable to store the input list.

Use the del keyword, to remove the item present at the specified index (here 2nd index(Codes)) from the list.

Print the resultant list i,e after removing the specified item from the list.

ExampleThe following program removes the specified item from an input list using the del keyword and prints the resultant list −

inputList

=

[

‘TutorialsPoint’

,

‘Python’

,

‘Codes’

,

‘hello’

,

‘everyone’

]

del

inputList

[

2

]

(

“Input List after removing the item present at the 2nd index{Codes}:n”

,

inputList

)

OutputOn executing, the above program will generate the following output −

Input List after removing the item present at the 2nd index{Codes}: ['TutorialsPoint', 'Python', 'hello', 'everyone'] Method 3: Using pop() methodWith pop() method, you can delete the element at the specified position and retrieve its value.

The starting value of the index is 0 (zero-based indexing).

If no index is specified, the pop() method removes the last element from the list.

Negative values can be used to represent the position from the end. The last index is -1.

Algorithm (Steps)Following are the Algorithm/steps to be followed to perform the desired task −

Create a variable to store the input list.

Use the pop() method, bypassing the index of a list item as an argument the to it to remove the item at the given index

Pass the negative index values as an argument to the pop() method, to remove the list items from the last. Here for removing the last item from the list we passed the -1 index as an argument to the pop() method.

Print the resultant list i,e after removing the specified item from the list.

ExampleThe following program removes the specified item from an input list using the pop() method and prints the resultant list −

inputList

=

[

‘TutorialsPoint’

,

‘Python’

,

‘Codes’

,

‘hello’

,

‘everyone’

]

del_item

=

inputList

.

pop

(

0

)

last_del_item

=

inputList

.

pop

(

–

1

)

(

“Input List after removing {TutorialsPoint}, {everyone}:n”

,

inputList

)

Output Input List after removing {TutorialsPoint}, {everyone}: ['Python', 'Codes', 'hello'] Method 4: Using clear() methodThe clear() method removes all items from the list. The list is still there, but it is empty.

Algorithm (Steps)Following are the Algorithm/steps to be followed to perform the desired task −

Create a variable to store the input list.

Use the clear() method, to remove all the items from the list.

Print the resultant list i,e after removing all the from the list.

ExampleThe following program clears or empties the complete list using the clear() function −

inputList

=

[

‘TutorialsPoint’

,

‘Python’

,

‘Codes’

,

‘hello’

,

‘everyone’

]

inputList

.

clear

(

)

(

“Input List after removing all the items:”

,

inputList

)

Output Input List after removing all the items: [] ConclusionWe learned how to remove an object/element from a list using four different methods in this article: remove(), pop(), clear(), and the del keyword. We also learned about the errors that those methods generate if the element is not in the list.

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