You have the best gaming CPU and GPU, but are you using that old pedagogo with a 60Hz refresh rate? Nah it doesn’t work like this because 60Hz is too low for competitive gaming and it can give your enemies an upper hand in-game but which pedagogo should you buy as an upgrade to your old pedagogo? Well, don’t worry as we will review a 4K gaming pedagogo with a 144Hz refresh rate and that pedagogo is known as Acer Nitro XV282k.

Review of Acer Nitro XV282k

Back in the day, there was a company named MultiTech that used to manufacture semi-conductors and other electronic parts but after some time the company grew and started manufacturing its PC and that company is now called Acer which is now known for its gaming hardware with some serious features packed in them.

Acer Nitro XV282k is a 28” UHD 4K (3840×2160) widescreen gaming pedagogo which is perhaps the best pedagogo when it comes to console gaming but how? If you are curious then read this article from start to the end and you will know why we called it the best gaming pedagogo for console gamers.

Specifications of Acer Nitro XV282k

We will now discuss the specifications of Acer Nitro XV282k.

Normal Specifications

  • Brand: Acer
  • Screen Size: 28 inches
  • Max resolution: 3840 x 2160
  • Weight: 21.7 pounds
  • Dimensions: 10.6L x 25.06W x 19H (inches)
  • Color: Black

Display

  • Panel: IPS
  • Refresh rate: 144Hz
  • Response time: 1ms (GTG)
  • Aspect ratio: 21:9
  • Contrast ratio: 1000:1
  • Adaptive contrast management (ACM): 100,000,000:1
  • Peak brightness: 400 cd/m²
  • AMD Free-Sync Premium: Yes
  • VESA Display HDR 400: Yes, certified

Connectivity and Audio

  • HDMI: Yes, 1x HDMI 2.1
  • DisplayPort: Yes, 1 x DisplayPort
  • Headphones: Yes, 1 x headphones jack
  • Speakers: Yes, 2 x 2w Speakers

Features of Acer Nitro XV282k

The amazing Acer Nitro XV282k comes with the following set of features:

Display
It features a UHD 4K (3840 x 2160) IPS Display with accurate, bright colors with a low Delta E<1. Delta E is used to make sure that the color displayed on the pedagogo matches what the human eyes collect. In simple words higher the value of Delta E, the lower the accuracy of colors and vice versa.

It also has Eyesafe Display technology which is engineered with the help of doctors and it is responsible to protect your eyes from blue lights without losing the color accuracy up to an acceptable level.

Refresh Rate
Acer Nitro XV282k has a refresh rate of 144Hz that provides you with smooth visuals with a shutter-free and lag-free gaming experience. This feature gives you an absolute edge over your enemies in competitive gaming.

Response Time
The response time is referred to as the time your pedagogo takes to shift from one color to another. Acer Nitro XV282k has a 1ms (grey-to-grey) response time that makes sure you don’t see any of those annoying ghosting effects.

AMD FreeSync Premium
AMD FreeSync Premium is a technology from graphics card manufacturing company called AMD that enables the user to get rid of screen tearing which can affect your gaming performance. it works by synchronizing your pedagogo’s refresh rate to the FPS your computer is producing.

Console Gaming
Acer Nitro XV282k is a great choice for console gaming as you can play games using PS5 and XBOX at [email protected] via HDMI 2.1 (included) which means that you can fully enjoy an immersive gaming experience on your consoles all day long without tiring your eyes.

Additional Features
Acer Nitro XV282k includes the following additional features from Acer.

Acer Display Widget: It is a program that lets you alter the display settings

Crosshair: It adds a customized posible crosshair which works well with competitive FPS gaming

Light Sensor: It is there to automatically change the brightness level according to surroundings.

You Should Buy Acer Nitro XV282k If You Want

  • 144Hz refresh rate and 1ms (GTG) response time
  • Good color accuracy
  • 4K [email protected] on consoles
  • Good HDR mode
  • Sleek and straightforward design
  • AMD Free-Sync Premium
  • Anti-blue light technology

You Should Not Buy Acer Nitro XV282k If You Want

  • Good contrast ratio
  • Good speakers
  • USB-C port

Final Verdict

Acer Nitro XV282k is a solid yet modest designed 4K gaming pedagogo. It performed well on both PC and consoles and it showed vivid and lively colors with good accuracy throughout the checking process. Although it needed good speakers and at least one USB-C port for better connectivity. The contrast ratio isn’t good enough even with VESA HDR 400 certification (which is an entry-level HDR) but it looks good enough in daily tasks.

Looking at the features and specifications we conclude that Acer Nitro XV282k is perhaps the best gaming pedagogo for gamers, especially console gamers.



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The following post originally appeared on Medium. The author, Ruchi Pakhle, participated in our LFX Mentorship program this past spring.

Hey everyone!
I am Ruchi Pakhle currently pursuing my Bachelor’s in Computer Engineering from MGM’s College of Engineering & Technology. I am a passionate developer and an open-source enthusiast. I recently graduated from LFX Mentorship Program. In this blog post, I will share my experience of contributing to Open Horizon, a platform for deploying container-based workloads and related machine learning models to compute nodes/clusters on edge.

I have been an active contributor to open-source projects via different programs like GirlScript Summer of Code, Script Winter of Code & so on.. through these programs I contributed to different beginner-level open-source projects. After almost doing this for a year, I contributed to different organizations for different projects including documentation and code. On a very random morning applications for LFX were opened up and I saw various posts on LinkedIn among that posts one post was of my very dear friend Unnati Chhabra, she had just graduated from the program and hence I went ahead and checked the organization that was a fit as per my skill set and decided to give it a shot.

I was very interested in DevOps and Cloud Native technologies and I wanted to get started with them but have been procrastinating a lot and did not know how to pave my path ahead. I was constantly looking for opportunities that I can get my hands on. And as Open Horizon works exactly on DevOps and Cloud Native technologies, I straight away applied to their project and they had two slots open for the spring cohort. I joined their element channel and started becoming active by contributing to the project, engaging with the community, and also started to read more about the architecture and tried to understand it well by referring to their youtube videos. You can contribute to Open Horizon here.

Linux Foundation opens LFX mentorship applications thrice a year: one in spring, one in summer, and the winter cohort, each cohort being for a span of 3 months. I applied to the winter cohort for which the applications opened up around February 2022 and I submitted my application on 4th February 2022 for the Open Horizon Project. I remember there were three documents mandatory for submitting the application:

1. Updated Resume/CV

2. Cover Letter

(this is very very important in terms of your selection so cover everything in your cover letter and maybe add links to your projects, achievements, or wherever you think they can add great value)

The cover letter should cover these points primarily👇

  • How did you find out about our mentorship program?
  • Why are you interested in this program?
  • What experience and knowledge/skills do you have that are applicable to this program?
  • What do you hope to get out of this mentorship experience?

3. A permission document from your university stating they have no obligation over the entire span of the mentorship was also required (this depends on org to org and may not be asked as well)

The LFX acceptance mail was a major achievement for me as at that period of time I was constantly getting rejections and I had absolutely no idea about how things were gonna work out for me. I was constantly doubting myself and hence this mail not only boosted my confidence but also gave me a ray of hope of achieving things by working hard towards it consistently. A major thanks to my mentor, Joe Pearson, and Troy Fine for believing in me and giving me this opportunity.⭐

Starting off from the day I applied to the LFX until getting selected as an LFX Mentee and working successfully for over 3 months and a half, it felt surreal. I have been contributing to open-source projects and organizations before. But being a part of LFX gave me such a huge learning curve and a sense of credibility and ownership that I got here wouldn’t have gotten anywhere else.

I have been contributing to open-source projects and organizations before. But being a part of LFX gave me such a huge learning curve and a sense of credibility and ownership that I got here wouldn’t have gotten anywhere else.

I still remember setting up the mgmt-hub all-in-one script locally and I thought it was just a cakewalk, well it was not. I literally used to try every single day to run the script but somehow it would end up giving some errors, I used to google them and apply the results but still, it would fail. But one thing which I consistently did was share my progress regularly with my mentor, Troy no matter if the script used to fail but still I used to communicate that with Troy, I would send him logs and he used to give me some probable solutions for the same but still the script used to fail. I then messaged in the open-horizon-examples group and Joe used to help with my doubts, a huge thanks to him and Troy for helping me figure out things patiently. After over a month on April 1st, the script got successfully executed and then I started to work on the issues assigned by Troy.

These three months taught me to be consistent no matter what the circumstances are and work patiently which I wouldn’t have learned in my college. This experience would no doubt make me a better developer and engineer along with the best practices followed. A timeline of my journey has been shared here.

  1. Checkout my contributions here
  2. Checkout open-horizon-services repo

The LFX Mentorship Program was a great great experience and I did get a great learning curve which I wouldn’t have gotten any other way. The program not only encourages developers to kick-start their open-source journey but also provides some great perks like networking, and learning from the best minds. I would like to thank my mentors Joe Pearson, Troy Fine, and Glen Darling because without their support and patience this wouldn’t have been possible. I would be forever grateful for this opportunity.

Special thanks to my mentor Troy for always being patient with me. These kind words would remain with me always although the program would have ended.

And yes how can I forget to plug in the awesome swags, special thanks, and gratitude to my mentor Joe Pearson for sending me such cool swags and this super cool note ❤handwritten thank you note from joe pearson

If you have any queries, connect with me on LinkedIn or Twitter and I would be happy to help you out 😀





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“The interpretation of command line arguments has been made by the use of the Python module argparse. By providing user input elements to be processed, argparse would be used to give customization and reuse of the program in place of explicitly specifying variables within the function.”

Command Line Interface

A method to negotiate with a command line script would be through the command line interface or CLI. Although Python has several modules which we may use to construct command line interfaces for different scripts, the Python argparse package is now the efficient method for doing so.

The argparse module for Python was made available as a component of the standard framework. It is the preferred method for creating a Python Interface. The earlier “getopt” and “optparse” libraries were replaced with this one as they lacked several crucial functionalities.

Uses of Argparse Module

These are the uses of the Python argparse module:

    • Provides different units of arguments for a single item.
    • Supports the utilization of positional parameters.
    • Allow intermediate for subcommands.
    • Enable modification of the prefix elements.

Based on certain parameters, a primary command line parser may utilize additional command line parsers.

Utilization of a Command Line Interface

Now that we are aware of what a command line interface is, we might be concerned as to when it would be appropriate to incorporate it into the program. The común rule is that we will think about a command line interface if we decide to offer a user-friendly method of customizing the project.

The suitable technique is to use the Python argparse module. It is a great way to handle the value by constructing a command line interface using the Python argparse module unless we are constructing a complicated command line script that requires a configuration file to function. This way can let the user designate whose configuration file to be using.

How to Construct a Command Line Interface by Using Python Argparse Package

There are 4 phases to using the Python argparse module:

    • Include the argparse framework in Python.
    • Construct the parser.
    • Provide the parser with optional and positional parameters.
    • Run parse_args() function.

A User-defined object with a basic attribute for every input parameter obtained from the command line is what we can get after calling the parse_args() method.

Let’s execute different examples in which we utilize the argparse module.

Example no 1

An efficient interface for processing command line parameters is provided by the argparse tool. It shows the program’s común usage, instruction, and exceptions. The use of appropriate command line parameters is demonstrated in the succeeding illustration.

This example computes the circle’s area using a one-parameter radius from the command line. To add parameters and analyze them, the ArgumentParser object parser has been constructed. A radius parameter is added by the user, although it is left as an optional parameter. The method would not return an exception and set the parameter’s value to None if the user will not give a value for it, as seen in the scenario below.

import argparse

parser = argparse.ArgumentParser(description = ‘Find the radius of any given circle’)

parser.add_argument(‘-r’,‘–radius’, type = int, help=‘Calculated radius of any given circle’)
args = parser.parse_args()

def main():
    print(args.radius)
main()

 

At the start of the program, we will import the header file “argparse”. In the next step, we will initialize a variable “parser”, and at the same time, we will call the argumentpraser() method. This function is related to the argparse module. We have given the “description” as the parameter of the argumentpraser() function. Then we add different parameters so we utilize the function add_argument() function. This function has three parameters which include the radius of the circle, the data type of the radius, and the value of the “help” argument.

After specifying the arguments, we will invoke the function parse_args() of the parser package. Now let’s define the body of the main() method. Within this function, we have been using the function print() to display the radius of the given circle. In the end, we utilize the main() method.

Example no 2

The “required” is an argument of the add_argument() method of the ArgumentParser object. Parameters of the attribute “f” or “foo” are unnecessary and, therefore, will be eliminated by default. The parameter “required” need can be set to True if the user wants to insert this parameter. As shown below, whenever we set an attribute as “required” but do not specify a value for this, the compiler returns an exception.

import argparse

parser = argparse.ArgumentParser(description = ‘Determine radius of any circle’, prog = ‘The program’, usage = ‘%(prog)s [options]’)
parser.add_argument(‘-r’,‘–radius’, type = int, required = True, help=‘Calculated radius of any given circle’)
args = parser.parse_args()
def main():
    print(args.radius)
main()

 

First of all, we are going to integrate the module “argparse”. The following step involves initializing the variable “parser” and applying the argumentparser() method simultaneously. This method is associated with the argparse package. The arguments for the argumentparser() method are description and prog.

Next, we add some additional parameters by using the add_argument() method. The radius of the circle, the radius’s data type, and the value of the “help” parameter are the four arguments for this function. We set the value of the “required” parameter to “True”.

In addition to this, we will call the method parse_args() of the parser header file after providing the arguments. Then we will define the main() function’s body. The print() method has been used here in the body of the main function to show the radius of the circle. We finally use the main() function.

Conclusion

By completing this article, we now comprehend a command line interface and the method of constructing a single command line argument using the argparse package. We also discussed what the Python argparse module is and why users will utilize it if they have to generate command line Python code. How and when to efficiently build a basic Interface using the argparse framework. We also observed the innovative use of the argparse module. An effective command line interface can provide users with a mechanism to engage with their system.



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“We need to employ a lot of modules while creating Python apps for various functionalities. The number of modules a given application uses can be considerable. Generally, it is advised to create a posible environment tailored to the project when developing such massive programs, as well as smaller ones, because doing so enables us to install anything we want and of any version without overburdening the available package space.

The script and dependencies must be installed on the user’s computers for them to utilize the developer. Because the dependencies are set up in a posible environment, it would be useless to share the entire posible environment because the folder size would be enormous, and there would be a risk of integrity problems.

When this occurs, programmers include a requirements.txt file in the project that contains a list of all the dependencies that have been installed in the posible environment as well as information on the version that is being utilized. To utilize the program, the borrower or end-user merely needs to set up a posible environment and install any necessary components. This post will explain how to create the requirements.txt file and install dependencies using it.”

Definition of requirement.txt File in Python

During the development of a specific project, libraries, packages, and modules are typically listed in a requirement.txt file, a type of file in Python. It also keeps track of all the files and programs needed for the project to function or on which it depends. In most cases, your project’s root directory is where the file “requirement.txt” is kept (or is located). The reason why we require this kind of file in our projects is raised here, which is yet another crucial question.

Importance of requirement.txt File in Python

As it resolves nearly all compatibility difficulties, it benefits us in several ways, even when we return our project in the future. If you’ve ever written a project in Python or worked on one, you know that we typically need many packages. However, whenever we worked on a project, we frequently used a certain version of the packages.

Later, the maintainer or package manager might make certain adjustments, and those changes could easily damage your entire application. Consequently, keeping track of each package change would take a lot of time. To avoid unpleasant surprises, it’s critical to keep a record of every package we use when the project is excessively large.

Utilizing a posible environment is one of the common strategies for dealing with this kind of problem. Since we typically do not need all of these package types while focusing on a particular project, it is important to recognize which one is necessary for each project in order to facilitate reproducibility. There are two primary types of modules and places where Python modules are typically stored.

The following files are typically involved:

    • The Standard Python Library’s System Packages are a component of it.
    • Site packages, often known as third-party packages, which you install with pip.

Posible Environment for the requirement.txt File in Python

The user’s packages are kept apart from the regional (or main) system installation in a posible environment, which is a kind of químico or separated workspace. It enables us to build an isolated, “posible” environment for all Python schemes. This makes it simpler for each project to operate independently of the others, particularly when they have similar requirements. A posible environment can be created using a variety of packages that are accessible. First, make all right that python and pip are mounted on your system.

>Python –version
>Pip –version

 

Install virtualenv

Let’s now explore how to install the modules and libraries after the posible environment for our project has been constructed. With the posible environment, obtaining all the necessary packages for our project is really simple. Let’s examine how to use “virtualenv.”

It is a particular kind of library that enables the creation and use of posible environments. You can adhere to the directions provided to install the virtualenv. To install virtualenv, launch the shell prompt on your computer and enter the subsequent command.

>> Pip install virtualdev

 

Building the Directory for a New Project

Now, in order to prevent unneeded problems, build a new posible environment within the directory of that project by giving the following command in prompt command.

>> Python –m venv name_of_environment

 

We only need to activate it at this point in order to use the newly generated posible environment. The following command must be entered, and the enter key must be pressed to enable this isolated environment.

>name_of_environmentScriptsactivate

 

We have titled our posible environment “name _of_environment” in our example, so you can check that it has been formed by looking at the prompt to see that the prefix has been updated. Additionally, you may confirm it by navigating to the project folder or the directory where the relatively new directory with the provided name will be created.

Creating the requirement.txt File With the Python Path

It will be helpful to know its contents before creating the requirement.txt file. A requirement.txt file lists every type of standard package and library that is utilized in that specific project. Therefore, while creating any project, no matter how big or small, this requirement.txt file. Our projects become more transportable as a result of it. Several significant issues can be easily avoided with the “requirement.txt” file’s assistance. We can obtain the requirements.txt file from this location. We may use the next command to make the requirement.txt file:

>> Pip freeze > requirements.txt
>> requirements.txt

 

The requirement.txt file opens as the following image is displayed.

Conclusion

Here, we have concluded our article that the requirement.txt file is crucial because it will be used whenever a new user runs the code they downloaded from internet platforms on their PC. There is no necessity for the requirements.txt file name to appear in this file. Use dependencies.txt or another file if you choose. However, requirements.txt is the name given to this file most frequently in conventional development practice.



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Controlling a Raspberry Pi from another system through a VNC viewer is extremely important as it helps you easily control your Raspberry Pi device through your laptop without purchasing a separate desktop environment. In another case, you can also benefit other individuals by using your device to complete their projects. However, the default VNC viewer setting allows you to access the device within the same network as it becomes extremely tough for the users outside your network to access it.

If you are looking for a solution to remotely access your Raspberry Pi device outside the network or in any part of the world, you should look for these article guidelines.

How to Control a Raspberry Pi Remotely From Anywhere In the World

To control a Raspberry Pi remotely, follow the below-given steps:

Step 1: First, you need to install both vnc-server as well as vnc viewer on your device and you can do so with the help of the following command:

$ sudo apt-get install realvnc-vnc-server realvnc-vnc-viewer

Since the Raspberry Pi has built-in vnc-server so it will skip the installation and start installing the vnc-viewer on your device.

Step 2: After completing the installation, apply the below-given command to open the Raspberry Pi configuration on the terminal:

Step 3: Enable the VNC option by going straight into the “Interface Options”:

Click on the “Yes” option to enable the VNC function on Raspberry Pi devices.

Step 4: Now, head to your browser and visit the Sign-in page VNC. There on the page, click on the “Sign-in” option to create an account on VNC.

Fill in the email information and a security check for the VNC sign-in process.

Provide the password to sign in. As in our case, we are already registered with the VNC, so here we are only using the password to sign in.

Step 5: Now open the VNC server on your Raspberry Pi device, which you can find at the top right corner of your desktop screen. Go to the Licensing option by clicking on the three lines icon.

Step 6: At the current license configuration window, click on the “Next” option.

Step 7: Provide the same email credentials, you just completed in Step 4 and merienda done, click on the “Sign in” button.

Step 8: You will get a 30-day trial of using the VNC subscription service and after the trial period expires, you have to purchase a subscription to continue using the VNC service remotely all over the world.

Step 9: Make sure that both cloud and direct connections options are selected as the cloud connection will help you to access the device remotely outside the network. While the direct connection ensures remote device access inside the network.

Step 10: You can set a password for the VNC password to make it secure so that anyone who wants to access the device must use this password. Follow the same on-screen window instructions as shown in the image below:

Step 11: To further secure your device remote access, you can check the “Attended Access” option as this allows your approval if someone wants to access the device remotely.

Step 12: Click on the “Apply” button after ensuring the similar on-screen instructions as shown in the image below:

Step 13: Now, open the VNC server on your laptop and enter the Raspberry Pi IP address that appears in the above window, which is “192.168.100.43” in our case.

Step 14: Enter your password, which you have set in Step 10, click on the “OK” button and allow the user to access your device by accepting the connection request on your Raspberry Pi desktop.

Through this approach, anyone who is in any part of the world will access your device using your device’s IP address and a password for remote login.

Conclusion

Accessing your Raspberry Pi device remotely from any part of the world is no longer difficult; you can do so easily by following the steps mentioned above. These steps require having an account on the VNC server. Then, use the licensing option and select the 30-day trial for remote access. Afterward, you have to use your VNC credential details and set the password to allow other users outside your network to remotely access your Raspberry Pi device using the VNC server on their laptop.



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A choropleth map, or Choropleth for short, is a map made up of colored polygons that describe data.

This tutorial will cover how to create a choropleth map using go.Choropleth.

Plotly.graph_objects.Choropleth

The class syntax is shown below:

class plotly.graph_objects.Choropleth(arg=None, autocolorscale=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, featureidkey=None, geo=None, geojson=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, legendgrouptitle=None, legendrank=None, locationmode=None, locations=None, locationssrc=None, marker=None, meta=None, metasrc=None, name=None, reversescale=None, selected=None, selectedpoints=None, showlegend=None, showscale=None, stream=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, **kwargs)

 
You can create a Choropleth object by passing the required variables. These important parameters include:

    1. Arg – represents a dictionary of properties that match a choropleth constructor.
    2. Autocolorscale ––specifies the color scale palette, such as default or custom. This is a Boolean value.
    3. Geojson – specifies the GeoJSON data required for the choropleth trace. If no value is determined, plotly will use the default pulvínulo map.
    4. Locations – sets the coordinate using the location IDs or names.
    5. Locationmode – this parameter specifies the sets of locations used to match the entries in the location’s parameter.
    6. Colorscale – specifies the color scale as an RGB array.
    7. Hoverinfo – specifies the information that appears on the trace on mouse hover.
    8. Text – specifies the text elements that are associated with each location.
    9. Uid – assigns a unique ID of the choropleth trace.
    10. Z – specifies the color values.
    11. Name – specifies the choropleth trace name.
    12. Meta – provides extra metadata information associated with the Choropleth.
    13. Visible – sets if the choropleth object is visible or not.
    14. Ids – assigns a label to each column.

The previous parameters are some of the most common parameters you will need when constructing a choropleth with Plotly’s graph_objects.

Example 1

Let us look at an example of creating a choropleth using the graph_objects. For this example, we will be using Plotly’s sample datasets as provided in the link below:

https://github.com/plotly/datasets

Consider the code shown below:

import plotly.graph_objects as go
import pandas as pd
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv")
fig = go.Figure(data=go.Choropleth(
    locations=df[‘code’],
    z = df[‘total exports’],
    colorscale = ‘viridis’,
    text = ‘Total Exports in USD’,
    locationmode = ‘USA-states’
))
fig.show()

 
In the previous example, we start by importing graph_objects as go and pandas as pd.

We then load the DataFrame as a CSV from the provided link.

Finally, we create a Choropleth object using the go.Figure() and pass go.Choropleth() as the argument.

We include all the details we want inside the go.Choropleth() to create the target choropleth map.

Running the previous code should create a choropleth map with the total number of exports per state in the USA.

The resulting figure is shown below:

Example 2

If you do not want to view the map of the whole world, you can limit your view scope by setting the scope to ‘usa’.

Consider the example below:

import plotly.graph_objects as go
import pandas as pd
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv")
fig = go.Figure(data=go.Choropleth(
    locations=df[‘code’],
    z = df[‘total exports’],
    colorscale = ‘viridis’,
    text = ‘Total Exports in USD’,
    locationmode = ‘USA-states’,
), layout = dict(geo = dict(scope=‘usa’)))
fig.show()

 
In this example, we pass the layout parameter as a dictionary to the Figure function.

This should limit the resulting figure only to the United States. An example figure is provided below:

Example 3

Plotly also allows us to update a figure using the update_layout() function. Then, we can pass the parameter we wish to update as a dictionary.

Consider an example below:

import plotly.graph_objects as go
import pandas as pd
df = pd.read_csv("https://raw.githubusercontent.com/plotly/datasets/master/2011_us_ag_exports.csv")
fig = go.Figure(data=go.Choropleth(
    locations=df[‘code’],
    z = df[‘total exports’],
    colorscale = ‘reds’,
    text = ‘Total Exports in USD’,
    locationmode = ‘USA-states’,
))
fig.update_layout(
    geo = dict(
        scope = ‘usa’,
        showlakes=True,
    )
)
fig.show()

 
In this example, we use the update_layout() function to introduce other features, such as showlakes and scope.

The resulting map is shown below:

Conclusion

This article explored how we can create a customized Choropleth map using Plotly’s graph_objects. In addition, important parameters were provided to create the Choropleth object.



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According to the aggregated statistics, a choropleth map is a statistical map comprised of colored polygons. It is mainly applied in geographical areas, such as countries, states, counties, and postal codes.

When working with statistical analysis, you often encounter scenarios where you must plot a choropleth map.

Therefore, this article will discuss how you can create a choropleth Mapbox using Plotly’s graph_objects.

Plotly.graph_objects.chroplethmapbox()

The choroplethmapbox() class from Plotl’y graph_objects allows us to create a Choroplethmapbox object with specific properties and customization.

The syntax is shown below:

class plotly.graph_objects.Choroplethmapbox(arg=None, autocolorscale=None, below=None, coloraxis=None, colorbar=None, colorscale=None, customdata=None, customdatasrc=None, featureidkey=None, geojson=None, hoverinfo=None, hoverinfosrc=None, hoverlabel=None, hovertemplate=None, hovertemplatesrc=None, hovertext=None, hovertextsrc=None, ids=None, idssrc=None, legendgroup=None, legendgrouptitle=None, legendrank=None, locations=None, locationssrc=None, marker=None, meta=None, metasrc=None, name=None, reversescale=None, selected=None, selectedpoints=None, showlegend=None, showscale=None, stream=None, subplot=None, text=None, textsrc=None, uid=None, uirevision=None, unselected=None, visible=None, z=None, zauto=None, zmax=None, zmid=None, zmin=None, zsrc=None, **kwargs)

 
The following are several essential properties you will use when using the Choroplethmapbox:

    1. Arg – specifies the properties of the choroplethmapbox object as a dictionary.
    2. Geojson – specifies the GeoJSON data associated with the choroplethmapbox.
    3. autocolorscale – sets the color scale palette, such as default or custom. This is a Boolean value.
    4. Geojson – specifies the GeoJSON data required for the choropleth trace. If no value is determined, Plotly will use the default cojín map.
    5. Locations – sets the coordinate using the location IDs or names.
    6. Locationmode – this parameter specifies the sets of locations used to match the entries in the location’s parameter.
    7. Colorscale – specifies the color scale as an RGB array.
    8. Hoverinfo – specifies the information that appears on the trace on mouse hover.
    9. Text – specifies the text elements that are associated with each location.
    10. Uid – assigns a unique ID of the choropleth trace.
    11. Z – specifies the color values.
    12. Name – specifies the choropleth trace name.
    13. Meta – provides extra metadata information associated with the Choropleth.
    14. Visible – sets if the choropleth object is visible or not.
    15. Ids – assigns a label to each column.

You will notice that it shares similar properties as a choropleth map.

Example 1

The following example illustrates how we can create a choroplethmapbox using the Choroplethmapbox class from Plotly’s graph_objects:

from urllib.request import urlopen
import json
import plotly.graph_objects as go
import pandas as pd
with urlopen(‘https://raw.githubusercontent.com/plotly/datasets/master/geojson-counties-fips.json’) as response:
    counties = json.load(response)

df = pd.read_csv(«https://raw.githubusercontent.com/plotly/datasets/master/fips-unemp-16.csv»,
                   dtype={«fips»: str})
fig = go.Figure(go.Choroplethmapbox(geojson=counties, locations=df.fips, z=df.unemp,
                                    colorscale=«Reds», zmin=0, zmax=12,
                                    marker_opacity=0.5, marker_line_width=0), layout=dict(mapbox_style=«carto-positron»,
                  mapbox_zoom=3, mapbox_center = {«lat»: 37, «lon»: –95}))
fig.show()

 
In the previous example, we use the geojson data and fips unemp datasets from the Plotly datasets repo.

We then use the go.Figure function and pass the properties of the Choroplethmapbox in the go.Choroplethmapbox() class.

Note that we pass the layout properties as a dictionary. The previous code should return a figure as shown:

Example 2

You can customize your plot layout using the update_layout() function. For example, to switch the Mapbox layout to an open street map, you can run the following code:

fig.update_layout(mapbox_style=«carto-darkmatter»)

 
The previous code should add a dark background with the set colorscale. The resulting plot is shown below:


Feel free to reference the documentation to learn about Choroplethmapbox properties and how you can use them with graph_objects.

Conclusion

This article provides a tutorial on how to create Choroplethmapbox using Plotly’s graph objects. In addition, several essential parameters were discussed when using the Choroplethmapbox:



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Like all programming languages, MATLAB has several functions for converting data from one type to another.

In this article, we explain how to use the deg2rad() function to convert degrees to radians.
Most of the functions MATLAB provides for signal analysis and wave generation have input arguments expressed in radians.

However, in practice, it is sometimes better to perform calculations based on degrees. Therefore, the deg2rad() function is a useful tool for converting these units.

Below we will explain in detail everything about this function, its syntax, calling modes, input and output arguments and accepted data types. We have also included pictures and practical examples in this article that show how you can use this function.

MATLAB deg2rad() Function Syntax

 

 

Description and Examples for MATLAB deg2rad() Function

The deg2rad() function is used to convert angles expressed in degrees to radians. This function converts the degrees sent in “d” to radians and returns the result in “r”. Deg2rad() accepts scalars, vectors, and matrices as input arguments.. This function accepts scalars, vectors and matrices as input arguments. In cases where the conversion is done using matrices or vectors, deg2rad() returns in “r” a matrix or vector of the same size as sent in “d”. Although using this function is useful in practice, there are several ways to convert degrees to radians. One of them is to use the following formula.

 
The function deg2rad() also works with complex numbers. In cases where “d” contains complex numbers, the conversion of the existente and imaginary parts is done separately. Next, we will look at some examples where we implement this function.

How to Convert a Scalar from Degrees to Radians with MATLAB deg2rad() Function

In this example we will show you how to convert a scalar expressed in degrees to a scalar expressed in radians with the deg2rad() function. For this we will create the scalar “deg” that contains a degrees value and we will send it as the input argument of this function.

deg = 165;
rad = deg2rad ( deg )

 
As seen in the figure below, rdeg2rad() returns the scalar “rad” with the value of “deg” converted to radians.

How to Convert a Vector with Units of Measure Expressed in Degrees to a Vector Expressed in Radians with the MATLAB deg2rad() Function

In this example, we will see how to convert the vector “deg” with values expressed in degrees to a vector “rad” of the same size with the values of “deg” converted to. For this, we are going to create a vector of 8 elements and we will send them as the input argument of the function. Below we can see the code for this conversion.

deg = [ 0, 45, 90, 135, 180, 225, 270, 360 ];
rad = deg2rad ( deg )

 
As can be seen in the following figure, deg2rad() in “rad” returns a vector of the same size as “deg” with the angle values expressed in radians.

How to Convert Angle Measures in Degrees to Radians in Scalars with Complex Numbers Using the MATLAB Function deg2rad()

In this example, we will see how to convert angular measures expressed in complex numbers. When we use this function to convert a complex number, deg2rad() converts the existente and imaginary parts separately. Next, let us look at the code snippet to get this conversion.

deg = 13.2374 + 3.2458i;
rad = deg2rad ( deg )

 
As shown in the following figure, deg2rad() returns in “rad” a scalar with the complex value of the angle converted and expressed in radians.

How to Convert an Array with Elements Representing Angle Values Expressed in Degrees to an Array with Angle Values Expressed in Radians Using the MATLAB Function deg2rad()

In this example, we will see how to convert an array of angle values in degrees to an array of those values in radians using MATLAB’s deg2rad() function. To do this, we create a 3 x 3 array of elements with angle values in degrees. We then call the function and pass this array as the input argument. The method of the function call is the same as in the previous examples.

deg =[  0,  45,  90;
      135, 180, 225;
      270, 315, 360];
rad = deg2rad ( deg )

 
As the figure shows, deg2rad() returns an array of the same size as “deg” with the values converted to radians.

How to Make an Application to do Conversions from Degrees to Radians with the MATLAB deg2rad() Function.

In practice, many engineers or programmers prefer to express angle measurements in degrees because, for example, data sheets for electronic devices use degrees as the unit of measurement in their equations.

In this example, we will create a simple console application to convert degrees to radians. In this application, we will use the prompt() function to prompt the user to enter a value expressed in degrees. This data will be input using the input() function and converted to radians using the deg2rad() function. Merienda the data is converted, we display it in the command console using the disp() function.

Below is the full script of this console application. Create a script, paste it and run “Run”. To close the application, press Ctrl+c.

while 1
          prompt = ‘Enter the value expressed in degrees’;
          deg=input(prompt);
          rad = deg2rad ( deg );
          disp( [ ‘The result in rad is: ‘ , num2str(rad)] )
end

 
The following image shows the application running in the MATLAB environment.

Conclusion

In this article, we explained how to use the deg2rad() function to convert angular units of measure in MATLAB. This function is widely used to complement the tools that this powerful scientific calculation language provides for analyzing and generating signals and waves with different shapes. To help you better understand what this function is all about, we have included practical examples with code fragments and images showing the implementation of this function in the Matlab environment. We have also created a simple console application that is a handy tool for converting these units of measurement. We hope you found this MATLAB article helpful. See other Linux Hint articles for more tips and information.



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BpyTop is an open-source command-line application allowing Raspberry Pi users to profesor their system resources like memory, CPU, and network information. It displays all the required information right onto your Raspberry Pi terminal. It works similar to HTop and Top but has a more advanced interface than them. You can even apply several themes to change the interface.

This article presents a detailed guide to install BpyTop on your Raspberry Pi device so that you can get the information about your device resources in a whole new way.

BpyTop: An HTop and Top Alternative for Raspberry Pi

The BpyTop script is written in Python language so you will need to download it from the Python package management system, commonly called as pip. To perform the installation of BpyTop through pip, you have to follow the below-mentioned steps:

Step 1: Update Your Raspberry Pi System

Initially, you must need to update the packages installed on your Raspberry Pi device by using the below-given command:

$ sudo apt update && sudo apt upgrade

Press “Y” to confirm updating the packages to the latest version.

Step 2: Install Python3-pip on Raspberry Pi

Next, you just need to use the following command to install Python3-pip as this will help you install the BpyTop on your Raspberry Pi device.

$ sudo apt install python3-pip -y

Step 3: Install BpyTop on Raspberry Pi

After installing pip on Raspberry Pi, you can easily install BpyTop by executing the following command:

Step 4: Run BpyTop on Raspberry Pi

After successfully installing BpyTop on Raspberry Pi, you can apply the following command to run the utility on the terminal:

How to Change Themes for BpyTop

There are several themes you can be downloaded for BpyTop, which you can see on the website.

To install these themes one by one, first head towards the theme’s directory of BpyTop using the following command:

$ cd .config/bpytop/themes/

Then, use the following command to download a theme for BpyTop. Change the <theme_name>:

$ wget https://github.com/aristocratos/bpytop/tree/master/themes/<theme_name>

After downloading the themes, run the “bpytop” command again in the terminal and then use the “Esc” button to open up the BpyTop menu.

Go to the “OPTIONS”:

Select your theme by pressing the “right arrow” button from the keyboard.

Press the “Esc” button two times to quit the BpyTop menu and after that, you will see that the theme has successfully changed on the BpyTop terminal screen.

Uninstalling BpyTop From Raspberry Pi

If you no longer require BpyTop service on your device, you can uninstall it any time using the following command:

$ pip3 uninstall bpytop -y

Conclusion

BpyTop is a lightweight command-line application that is used to profesor system resources on the terminal window. The installation of this application is simple, which you can complete by first installing Python-pip3 on your Raspberry Pi device and then using the pip3 service to install BpyTop on your device. You can also apply different themes to change its interface and the detailed step-by-step procedure is already provided in the above guidelines.



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PiBuddy is an open-source Android application for Raspberry Pi to control the device from mobile. Apart from giving you the authority to control your Raspberry Pi, you can also view system information like CPU resources, disk usage, and memory information, as well as the freedom to turn on and off your device at any time. Thus, it saves your device from improper shutdown.

In this article, we will guide you on how you can use the PiBuddy application on your mobile to control your Raspberry Pi device.

How to Control Raspberry Pi Through PiBuddy

To use PiBuddy on a Raspberry Pi device, follow the below-mentioned steps:

Step 1: First, enable the SSH service on your Raspberry Pi device by opening the terminal and applying the following command:

Select the “Interface Options” and there you will find the “SSH” option.

Click on the “SSH” option and then choose the “Yes” option to enable the SSH service on Raspberry Pi.

Step 2: Next, you will need to install the PiBuddy application on your mobile from the Google Play store.

Step 2: After successfully installing the PiBuddy application, open it on your mobile.

Step 3: Now, provide the IP address of your Raspberry Pi with the username and password. Merienda it’s done, click on the “Connect” button.

You can also choose the “SCAN FOR AVAILABLE DEVICES” option to find out your Raspberry Pi device.

There you can connect with it by clicking on the available IP address that appears on your screen.

There you will be able to see your system resources like CPU and memory usage, disk space and the username.

Step 4: Click on the terminal icon to use the Raspberry Pi terminal..

Step 5: To add a command, enter any command in the section and press the “Send” button to execute the command.

Step 6: If you want to restart your Raspberry Pi device, you can simply click on the “RESTART” button, or you can click on the “POWER OFF” button to turn off your Raspberry Pi device.

Conclusion

PiBuddy is a perfect Android application designed for the Raspberry Pi user to remotely control the device from the mobile. You can easily install it on your mobile from the Google Play Store and merienda the installation is completed, you can control your Raspberry Pi using the device’s IP address. At the PiBuddy dashboard, you will be able to see your system resources, restart and power off your device, and the authority to use the Raspberry Pi terminal to install the packages from your mobile.



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