Atom C++ Mac
Dec 15, 2012 I am learning C for a class at my university and wish to write the program using the TextWrangler text editor on my Mac (running OSX Lion 10.7). Once I write the.c file, I compile it using gcc. Atom is for people who want to learn c or c and want to quickly compile.Note: You should have gcc compiler in path of your.
Clustering is an invaluable cheminformatics technique for subdividing a typically large compound collection into small groups of similar compounds. One of the advantages is that once clustered you can store the cluster identifiers and then refer to them later this is particularly valuable when dealing with very large datasets. This often used in the analysis of high-throughput screening results, or the analysis of virtual screening or docking studies.
In theory any molecular descriptor can be used in clustering, in practice the use of a large number of descriptors, in particular some of the more esoteric ones, can make it difficult for a medicinal chemist to understand why compounds might be in the same cluster. It is perhaps better to stick to molecular fingerprints based on structural fragments, this usually results in clusters that chemists can see are similar. For this work I've tried to stick with Morgan/Circular type descriptors, however since all the packages will have their own implementation they are probably not exactly the same. A number of clustering techniques are available but the most common are nearest neighbours, this method assigns a single compound to each of the desired number of clusters, ideally the most diverse selection. Next each compound remaining is assigned to the nearest cluster, the centroid of each cluster is recalculated as each new compound is assigned to the cluster.
I've looked at a number of options for clustering molecules from toolkits like RDKit to commercial applications such as Vortex and I've tried them with a variety of different sized data sets, one containing 789 molecules, one 150,000 molecules and a large set containing 4,400,000 molecules. The clustering tools often have many different options but I've tried to stick to the default values. All work was run on a 12-core MacPro desktop with 64GB of RAM with 1TB of internal SSCD storage. I'm sure there are other options but I've limited the work to those that have in built support for chemistry. I've also limited the investigation to applications that are run locally since I suspect most chemists won't want to run calculations on an external server.
RDKit
RDKit is an open source toolkit for cheminformatics, it has Core data structures and algorithms in C++ with a user friendly Python wrapper. It also integrates nicely with Jupyter Notebooks. The RDKit Cookbook contains tips for using the the Butina clustering algorithm D Butina, 'Unsupervised Database Clustering Based on Daylight's Fingerprint and Tanimoto Similarity: A Fast and Automated Way to Cluster Small and Large Data Sets', JCICS, 39, 747-750 (1999) and I've implemented it in a Jupyter Notebook.
Now read in the molecules
This dataset contains < 1000 molecules, now generate fingerprints
Then cluster
For a modest dataset of <1000 molecules the clustering is almost instantaneous , we can then look at a specific cluster
Using the larger dataset of 150,000 molecules, reading in the structures took 90 seconds and 3.8 GB RAM, adding the fingerprints took another 20 secs and took RAM usage up to 3.83GB. Clustering used only one core, and after 23 mins and consuming 80GB RAM the kernel died.
After chatting to Greg Landrum, he suggested if using a large set of molecules you wouldn't want to ever have all the molecules in memory, so it might be better to read the molecules and generate the fingerprints in a single step like this
Also for the clustering use
The reordering flag is documented as follows 'if this toggle is set, the number of neighbors is updated for the unassigned molecules after a new cluster is created such that always the molecule with the largest number of unassigned neighbors is selected as the next cluster center'.
Whilst this lowered the initial memory requirements, unfortunately once the clustering started the memory usage steadily increased and the kernel died.
Chemfp
Chemfp is a set of command-line tools and a Python library for fingerprint generation and high-performance similarity searches. Whilst the current version is commercial older versions are available for free and can be installed using PIP. However it seems you have to explicitly define the version to install
This installs a variety of command line tools.
The command-line tools are written in Python, with a C extension for better performance. The Python library has a large and well-documented public API which you can use from your own programs. The core functionality works with fingerprints as byte or hex strings, reads and writes fingerprint files, and performs similarity searches. Chemfp does not understand chemistry. Instead, it knows how to use RDKit, OEChem/OEGraphSim, and Open Babel to handle molecule I/O and to compute fingerprints for a molecule, and makes all of that work through a portable cross-toolkit API.
The help is incredibly well documented, for example to generate the fingerprint file we need to use rdkit2fps, typing
Generating the fingerprint file
Andrew Dalke has provided a python script to help with the clustering and give some information on timings etc. it is available from here https://www.macinchem.org/reviews/clustering/clusteringfiles/taylorbutina.zip
Running on the ApprovedDrugs 789 dataset with a similarity threshold of 0.6 was effectively instantaneous
The resulting cluster file can be opened in a text editor and has this format
With some Python scripting it should be straight-forward to edit the script to output to cluster numbers and combine them with the original sdf file that was used to generate the fingerprint file.
Running the same process with a larger dataset took an unexpectedly long time and I noticed that it was only using one core. Chatting with Andrew Dalke it was apparent that Clang, the 'LLVM native' C/C++/Objective-C compiler, under MacOSX, doesn't include OpenMP support. Chemfp uses OpenMP for parallelism.
Compiling Chemfp for OpenMP
To compile Chemfp for OpenMP you'll need to install gcc then use the CC environment variable to configure the build step to use that compiler. I've written up instructions for installing gcc (plus other things) here using Homebrew.
I had to first remove Chemfp
However, you'll have to remove your local pip wheel file. A 'wheel' file is the new(ish) Python distribution format. It can include pre-compiled code, including byte code. 'pip install' internally makes a wheel file, stores it in a cache, then installs from the wheel file. The 'pip uninstall' will remove the installation butnot the wheel file.
Then reinstall Chemfp
I then ran the same exercise with the 150,000 structure file, this time running at similarities of 0.8 and 0.6 to see how it might effect performance, generating the fingerprint file took very little time and the timings for the clustering are shown below.
took just under a minute for 0.8 threshold and made use of all available cores.
took just over a minute at 0.6, so a little slower. As before the cluster output was a text file with the same format.
I had some problems generating the fingerprint file for the 4.4 million structures, it is often a problem when a file is derived from mulitiple sources and quality control is not consistent.
I ended up tidying up the file using this script.
This gave me a data set in SMILES format of just over 4.3 million structures. I then regenerated the sdf file and used that to generate the fingerprints without incident. (Apparently you can add '--errors ignore' to the rdkit2fps command, I've not tested it).
Generating the fingerprint file for the 4.3 million structures took 35 mins, generating the clusters using a 0.8 similarity took 10 hours. The python script also outputs a useful summary.
DataWarrior
DataWarrior is an open-source data analysis package I've reviewed previously. The cluster algorithm implemented in DataWarrior is simple, reproducible, but computationally demanding. By default Datawarrior uses Fragfp fingerprints
FragFp is a substructure fragment dictionary based binary fingerprint similar to the MDL keys. It relies on a dictionary of 512 predefined structure fragments.
To get a better comparison with the other clustering algorithms I generated the SphereFp fingerprint.
SphereFp descriptor encodes circular spheres of atoms and bonds into a hashed binary fingerprint of 512 bits. From every atom in the molecule, DataWarrior constructs fragments of increasing size by including n layers of atom neighbours (n=1 to 5). These circular fragments are canonicalized considering aromaticity, but neglecting stereo configurations. From the canonical representation a hash code is generated, which is used to set the respective bit of the fingerprint.
One the dataset of 789 molecules the clustering was instantaneous, and it was very easy to browse through the results.
Reading in the 150,000 structure file took 20 seconds and consumed 550 MB of RAM, adding the descriptors took the RAM usage up to 1.14GB. Unfortunately when I tried to do the clustering I got this message.
MOE
MOE is a molecular modelling package from Chemical Computing Group. Whilst MOE does not include Morgan/circular type fingerprints there is a SVL script based on the work by Rogers et al DOI that can be used to generate them. One the small dataset of 789 structures the clustering was complete within 15 seconds. One the larger set of 150,000 molecules generation of the fingerprints took 2 mins and the subsequent clustering took (>40 hours and counting)
I did not attempt to cluster the 4.4 million structure file using MOE.
Vortex
Vortex is a high performance, interactive data visualization and analysis application, with native cheminformatics and bioinformatics intelligence built in. Reading in the 789 structure file and then clustering was instantaneous. Vortex provides k-means clustering as standard, and uses either atom-based similarity (called DotFPCA) hex-packed to 1024 bits. This is the Dotmatics implementation of Morgan/circular type fingerprints.
Working with the 150,000 structure file, again using the default options, took less than a minute to generate the fingerprints and complete the clustering.
Using the 4.4M structure file took a little longer, reading in the file took less than 3 mins and consumed 13GB of RAM. Generating the fingerprints took 18 mins. used 4 cores and took the RAM usage up to 16GB, the clustering then took a further 40 mins using available cores with the RAM usage rising to 17.5 GB. Two columns are added: a CLUSTER number, and a DISTANCE; the centroid has a distance of 0 and all other compounds vary in distance up to 1.
With over 4 million structures it is not really practical to simply scroll through the table, but here are a couple of tools that might help with further analysis. A question that might then arise is “How many molecules belong to each cluster?”, the GenericClusterAnalysis script creates a new workspace containing two columns. The first containing the cluster number the second the count of occurrences for each cluster, for this 4.4 million structures it took a couple of seconds to run.
Alternatively you can use a variation on the duplicate check script to select the first example from each cluster, you can download it here http://macinchem.org/reviews/vortexscripts/ChoseOneFromClusters.vpy.zip. An alternative is to select the centroid of each cluster by modifying the script to perform an additional selection based on the DISTANCE value, the script can be downloaded here http://macinchem.org/reviews/vortexscripts/ChoseCentreFromClusters.vpy.zip.
Dan Ormsby at Dotmatics provided me with a couple of script snippets that expose the fingerprint generation code, it turns out that under the hood there are a wide variety of fingerprint options the default options are all pre-set for the typical medicinal chemist user. I used the 150,000 molecule set to explore the impact of varying a couple of the options. Changing the atom path length in the fingerprint from 2 to 10 had minimal impact on the time taken, all less than 1 minute. To improve efficiency when working with these fingerprints they are usually delivered into Vortex in a hex packed format, the default is 1024 bits. I also did the clustering using the unpacked fingerprints since this would represent the slowest method. Using the unpacked fingerprints the run took two minutes to complete.
Summary
For small data sets of a few thousand structures there are multiple options for clustering, from Open Source toolkits to sophisticated desktop applications. However as the dataset increases the computational demands increase, and support for the use of all available cores becomes essential. For very large datasets I've only found two options Chemfp and Vortex. I've only used the free version of Chemfp (the commercial version may have better performance) and whilst it copes with several million structures it is very considerably slower than Vortex. Vortex also has the advantage of having the nice graphical user interface and scripting tools to allow further exploration of the dataset.
Last Updated 22 July 2017
You just need to go to advanced system settings and then environment variables and then just choose the path environment variable in system variables. And then either double click on it or just click add it and then we are going to add a new variable and then just paste this path. Which is c colon backslash mingw.
Download the file, which is likely called AtomSetup-x64.exe, and run it. There are no options; the installer simply installs Atom for the current user, closes, and launches Atom. The first time Atom runs, it adds itself to the system path for the current user. That way you can launch Atom from the command prompt.
How to setup atom to compile C + +?
Atom is not an IDE. It's a text editor. That means that you will have to download other tools to compile C++. If you are on Ubuntu or Debian you can install G++ which is the GNU project C and C++ compiler. You can install it by typing into the console: sudo apt-get install g++.
Is it possible to run a C program in Atom editor?
Now, it's possible to run and compile (also debug) C and C++ program from within atom editor. Install gpp compiler package in atom editor. You'll need to install MinGW and add it to your system PATH. You'll need to install XCode. The GNU Compiler Collection may come with your distribution.
How to create an atom in Windows 10?
Open up Control Panel, select System and Security, and then System. On the left, the last item on the list is Advanced System Settings. Click it. Then find Environment Variables near the bottom. Open it. Under System Variables, double click the Path variable and select New. Now add the path to Atom.
How to install and configure Atom to run C++ code
You’ll need “gpp-compiler” package to install in Atom. gpp-compiler. This Atom package allows you to compile and run C++ and C code within the editor. To compile C++, press F5 or right click the file in tree view and click Compile and Run C++. To compile C, press F6 or right click the file in tree view and click Compile and Run C.
Answer (1 of 2): Yeah why not. I myself use atom for c++ programming even though i have dev c++ as well as codeblocks installed i prefer Atom. Just install gcc or similar package for atom
Atom is 'simply' a Text editor that is not able to compile anything. If you use a Makefile, then there are a few add-ons for building targets via key bindings. If not, open a terminal and use the C compiler on your system. On Linux/Unix machines you probably want to use gcc: gcc <your_source>.c -o <output_name> EDIT. Or take a look at This Package
Open Atom and go to edit > preferences > install and then search for the package you want to install. Click on the Install button and the package gets installed. Note: For some packages some additional settings are required which will be covered depending on the case. List of Community Packages is given as following: atom-beautify; atom-ternjs; autoclose-html; emmet; csslint; linter
Run the downloaded setup program and choose Custom installation and then choose the C++ component. To add C and C++ support to an existing Visual Studio 2015 installation, click on the Windows Start button and type Add Remove Programs. Open the program from the results list and then find your Visual Studio 2015 installation in the list of installed programs.
How to Install Atom on Windows
Git is an example of a distributed version control system (DVCS) commonly used for open source and commercial software development. DVCSs allow full access to every file, branch, and iteration of a project, and allows every user access to a full and self-contained history of all changes. #git #github
This Atom package allows you to compile and run C++ and C within the editor. To compile C or C++, press F5 or right click the file in tree view and click Compile and Run. To compile C or C++ and attach the GNU Debugger, press F6 or right click the file in tree view and click Compile and Debug. Dependencies. This package relies on a C / C++ compiler (gcc). Linux. The GNU Compiler Collection may come with your distribution.
Step 3: Set up your editor. It is fairly easy to configure Sublime Text and Notepad++ to use the MinGW-w64 compiler for your C++ files: Sublime Text. Sublime Text has a build system already built-in, but the C/C++ builder doesn't work properly with MinGW out of the box.
The following post will help you set up Sublime Text in a way that leads to a good workflow - from reading the problem statement to submitting the solution. Setting up the Environment 1. Install MinGW Compiler. MinGW is a native Windows port of the GNU Compiler Collection (GCC). Install the latest MinGW compiler, after downloading from here.
A text editor is at the core of a developer’s toolbox, but it doesn't usually work alone. Work with Git and GitHub directly from Atom with the GitHub package. Create new branches, stage and commit, push and pull, resolve merge conflicts, view pull requests and more—all from within your editor.
How to setup Atom to compile c++
If not, click on Basic Setup. Out of the numerous check boxes presented to you on the right side, tick ' mingw32-gcc-g++-bin '. If you are prompted with a menu, click on Mark for Install. Then on the top left corner click on Installation > Apply Changes. And wait while it downloads a billion files and installs them.
A Beginner’s Guide to Install gcc and g++ Compiler on Windows 10. Programming / By Dinesh S. If you are a developer and trying to compile your C/C++ program in command prompt, then this article will help you to install gcc compiler and g++ compiler on your Windows 10 computer in order to compile your code.
We need a C/C++ compiler, either GCC (GNU Compiler Collection) from MinGW or Cygwin (for Windows), or Visual C/C++ Compiler, or others. We need the following sets of libraries in programming OpenGL: Core OpenGL (GL) : consists of hundreds of functions, which begin with a prefix ' gl ' (e.g., glColor , glVertex , glTranslate , glRotate ).
Smart editor withfull language support. Our IDEs natively support C and C++, including modern C++ standards, Boost and libc++ libraries. C++ templates and macros are resolved correctly and supported for all IDE features. Besides, they seamlessly integrate with unit testing frameworks and support Doxygen.
I am sorry, Community is just a consumer forum, due to the scope of your question (Windows Application Development and Visual Studio) can you please post this question to our sister forum on MSDN (The Developer Network) in the Visual Studio 2019 section (linked below)
Can I use Atom for C/C++?
At GitHub, we’re building the text editor we’ve always wanted: hackable to the core, but approachable on the first day without ever touching a config file. We can’t wait to see what you build with it.
For more details about installing MSYS2 check out Install gcc compiler on Windows with MSYS2 for C/C++. Trying to get an open source toolchain configured in Windows for C++ can sometimes be a headache. In Windows, you can simply install Visual Studio and use the Microsoft C++ compiler, but you may want to use the free GNU compiler (g++) instead.
I am trying to setup visual studio code for opengl development. I already have it working for plain c/c++ development I am now trying to add in opengl development to the mix. I know how to setup opengl on other platforms (i.e. Eclipse, Xcode, Visual Studio, CodeBlocks). The root of my problem is more how to setup dependencies in visual studio code.
The Win32 API (also called the Windows API) is the original platform for native C/C++ Windows applications that require direct access to Windows and hardware. It provides a first-class development experience without depending on a managed runtime environment like .NET and WinRT (for UWP apps for Windows 10).
NetBeans is an integrated development environment for writing C++ programs. It is one of the best c++ ide for windows that has a project window that shows a list of projects currently exists. Features: You can set exception, variable, function breakpoints, etc. and view them in the Breakpoints window.
How to Install C++ Compiler on Windows?
Install C/C++ Compiler. C/C++ extension does not include a C++ compiler. So, you will need to install one or use which is already installed on your computer. Windows: Download MinGW64.zip (latest release) and extract it to the C Drive. Mac: XCode. Linux: GCC. Also, Make sure to add C++ compiler PATH to environment variable of your platform.
Notepad++ (Only for Windows); Microsoft Visual Studio Code (For Windows and Linux); ATOM (For Windows and Linux); IDEs (Integrated Development Environment) such as Eclipse or Netbeans may be used but if you are a beginner in C programming, prefer using text editors mentioned above.; Install C/GCC Compiler for Windows. One of the preferred way to install C/GCC compiler is to use CodeBlocks.
C/C++ for Visual Studio Code. C/C++ support for Visual Studio Code is provided by a Microsoft C/C++ extension to enable cross-platform C and C++ development on Windows, Linux, and macOS.. Install the extension. Open VS Code. Select the Extensions view icon on the Activity bar or use the keyboard shortcut (⇧⌘X (Windows, Linux Ctrl+Shift+X)).Search for 'C++'.
3. CLion. Clion is a modern IDE by JetBrains which is designed to run C and C++ on various platforms like windows, Linux, and MacOS. It provides intelligent code assistance support so that the main focus must be on important things. 4. Eclipse. Eclipse is one of the most popular and powerful IDE for C++ developers.
Installing Cython¶. Many scientific Python distributions, such as Anaconda [Anaconda], Enthought Canopy [Canopy], and Sage [Sage], bundle Cython and no setup is needed.Note however that if your distribution ships a version of Cython which is too old you can still use the instructions below to update Cython.
Getting Started with Visual Studio for C and C++ Development
When targeting Windows 10, this can provide advantages including streamlined deployment, greater reach, simpler monetization, simplified setup authoring, and differential updates. Try out Visual Studio 2017 for desktop development with C++! Download Visual Studio 2017, try it out and share your feedback.
Atom is one of the most popular code editors on the market, developed and maintained by GitHub. It comes with multiple awesome features such as a built-in package manager, smart autocompletion, and cross-platform editing. As Atom is completely customizable, you can also change the look and feel of the editor with the help of pre-designed Atom themes.
Atom C++ Ide
Eclipse – Well known opensource IDE for Java, C/C++ and PHP that has support for many programming language. Visual Studio Code – It is an editor and has great feature like IntelliSense and one of the best free editor for front-end developers. Sublime Text – A paid text editor with many quality features. Tags: codeblocks, IDE, windows.
Setting up the Environment. After completing the above steps, GCC is up and running. Now, the Environment Variable’s Path is to be updated. Follow the below steps for the same: Go to My Computer, then Right Click to get Properties > Advanced System Settings > Environment Variables.. Now under the System Variables Tab, look for Path > Click on Path > Click on Edit > Click on New.
A special thanks goes to Facebook's Nuclide team for providing the Atom IDE user interface package. Both Nuclide and Atom IDE are developed by Facebook and supported by an open source community. At this time, Facebook has decided to retire their open source efforts on Nuclide, the Atom IDE, and other associated repos.
Install C and C++ support in Visual Studio
Download Turbo C++ for windows 11 or 10 in just 7 Mb and run your first C++ program . C++ programming is one of the earliest and evergreen programming languages.It is still the choice of many experienced programmers and novice programmers alike who enter into the world of programming.
8) Atom. Atom is a simple editor for a writing C program. It can be customized to do anything without modifying a config file. This C Programming IDE enables you to search, preview and replace any text as you type in your program. Features: It has an integrated package manager.
Created by Github with love, Atom is a modular, advanced, hackable editor for programmers. We all know Editor play’s very important to keep developers like you productive. To install atom editor in your Ubuntu system, you can visit the official web-site here to download the Atom editor for Mac, Windows and Linux.
You can view the C/C++ configuration UI by running the command C/C++: Edit Configurations (UI) from the Command Palette (⇧⌘P (Windows, Linux Ctrl+Shift+P)). This opens the C/C++ Configurations page. When you make changes here, VS Code writes them to a file called c_cpp_properties.json in the .vscode folder.
Its development was started by Bjarne Stroustrup at Bells Lab in 1979. It is an extension of one of the popular language C. So, it is also possible for programmers to code C++ in a C style or object-oriented style. It is a middle-level programming language as it encapsulates both high-level and low-level language features.
Top 16 IDEs for C or C++ Developers in 2021 & Beyond!
Install Windows ADB and start the ADB server in Windows. Note: Windows’ and WSL’s adb versions must be the same version, e.g., if WSL has ADB 1.0.39, you need to download the corresponding Windows ADB from here .
Here, I’ll look at how you can set up a “python friendly” development environment with Atom, some of the packages that are useful to coding in python, and then take a look at writing some basic code. 1) Downloading Atom. First thing’s first, if we’re going to use Atom as our text editor, we better download it.
C/C++ language servers. The below was written for clangd, but much applies to cquery and ccls as well. CCLS. A newer project emerged from cquery. Build and install from source, see ccls wiki. Cquery. Build and install from source, see cquery wiki Note that work on cquery has stopped. Prefer using ccls or clangd. Clangd
Everything you need in one place. CLion includes all the essentials of everyday development: VCS (SVN, Git, GitHub, Mercurial, Perforce), Google Test, Catch and Boost.Test frameworks for unit testing, Doxygen, Database tools, and Markdown support. Discover all features.
.NET Core has specific Windows prerequisites for Windows 8.1 and earlier. Windows 10 Enterprise LTSC edition, Windows 10 S and Windows 10 Team Edition are not supported for development. You may use Visual Studio 2019 to build apps that run on Windows 10 LTSC, Windows 10 S and Windows 10 Team Edition.
PlatformIO IDE for Atom
Follow these steps to install g++ (the GNU C++ compiler) for Windows. There is no room for creativity here; you must follow the directions exactly. Pick the drive and a folder in which you want to install g++. I’ll assume that it is C:, but you can choose a different one.
Install Go Programming Language (Golang) on Windows 10. Go, also known as Golang is a statically typed programming language developed at Google. To start programming with Go on your Windows 10 machine you will need to install Golang on your computer.
Install MinGW. MinGW means Minimalist GNU for Windows: GNU is a source of open source programming tools (GNU stands for GNU is Not Unix).. In this handout you will download the files needed by GNU C++; in the next you will download a version of Eclipse that is already set up to use MinGW.
Gpp Compiler
Code::Blocks is a free C, C++ IDE created to meet the most demanding needs of the developers of C and C++. This is an IDE with all the features you need for C and C++ development. Features: Works on Windows, Linux, and Mac OS X as well. It is designed to be fully configurable and extensible with its plugins.
C-mac Laryngoscope
Step 2: Install the Atom Editor. As mentioned above, installing Atom Editor is the easiest thing one can ever do. Simply locate the setup file which you just download and then double click and run the installer. That’s all you have to do. The installer will launch the Atom editor once it’s done installing it.