https://community.wolfram.com RSS Feed for Wolfram Community showing any discussions from all groups sorted by most viewed. https://community.wolfram.com/groups/-/m/t/366628 POSTED BY: ======== **Marvin Ray Burns, and distinguished colleagues** ---------- My exciting experiences using Wolfram technologies! --------------------------------------------------- ---------- The MRB constant, a fascinating mathematical anomaly, has intrigued researchers and enthusiasts alike for decades. Defined as the limiting value of a unique alternating series, this enigmatic constant showcases the beauty of numerical exploration and convergence. Despite its relatively recent emergence, the MRB constant reveals unexpected connections to various fields within mathematics and computational analysis. In this post, we dive into its origins, properties, and the ongoing quest to uncover its more profound significance. The MRB constant is an anomaly because it emerges from an alternating series with unusual convergence behavior. Unlike many well-known mathematical constants, the MRB constant has no closed-form expression nor a known exact nature—whether it is algebraic, transcendental, or even irrational. Additionally, the sequence of partial sums that define the MRB constant oscillates between two limit points, creating a bounded yet divergent behavior. This oscillatory nature distinguishes it from more conventional mathematical constants, which typically exhibit straightforward convergence. Its mysterious properties continue to intrigue mathematicians as they explore its deeper connections to number theory and computational analysis. ---------- ---------- CMRB ![If you see this instead of an image, reload the page][1] **is the MRB constant.** Without solicitation, GPT echoed one of this discussion's contributors and gave a shoutout to Mathematica's accomplishments by saying: ------------------- > > **Why Computing Digits of the MRB Constant Is Interesting** > > At first glance, the computation of ever more digits of a numerical > constant may appear to be a sterile exercise, offering little insight > beyond the digits themselves. For the MRB constant, this > interpretation is profoundly misleading. The interest lies not in the > digits, but in the act of computing them. > > The MRB series occupies a delicate numerical regime: it is convergent, > yet only marginally so; its terms are elementary in form, yet hostile > to naive numerical evaluation; and its alternating structure conceals > severe cancellation effects. As a result, each additional digit of > accuracy is not merely an extension of a decimal expansion, but a > validation of the mathematical and algorithmic framework used to > obtain it. > > In this sense, the digits serve as a stress test for mathematics > itself. They expose the difference between formal convergence and > effective convergence, between theoretical existence and computational > feasibility. Techniques that are elegant on paper often fail > catastrophically in practice, while successful methods must balance > asymptotics, numerical stability, precision control, and computational > cost. > > Moreover, the computation of the MRB constant forces the > reconciliation of disparate mathematical ideas. Alternating series, > logarithmic asymptotics, convergence acceleration, special functions, > and analytic continuation must all agree numerically. Any hidden > inconsistency—whether conceptual or computational—reveals itself > immediately in the failure of the digits to stabilize. > > Thus, computing digits of the MRB constant transforms mathematics from > a static collection of statements into a living experiment. The > resulting digits are not trophies; they are evidence. They measure the > effectiveness of our methods, the soundness of our assumptions, and > the practical reach of our theory. > > In short, the digits themselves do not matter. What matters is that > they *can* be computed at all—and how difficult it is to do so. > That difficulty is precisely what makes the MRB constant > mathematically interesting. **In general, we will see:** ![enter image description here][7] ---------- ---------- ---------- [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Screenshot2024-11-25023042.png&userId=366611 [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Screenshot2026-01-01235656.png&userId=366611 [3]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Screenshot2026-01-01235710.png&userId=366611 [7]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Screenshot2026-02-18190718.png&userId=366611 Marvin Ray Burns A.G.S. (cum laude) 2014-10-09T18:08:49Z https://community.wolfram.com/groups/-/m/t/20688 Hello and welcome to Wolfram Community! This is the official networking portal for the users of Wolfram technologies, a virtual home to our global family. Here you can connect, interact, share ideas, and ask questions. Start from the following:  [list] [*]Read the [url=http://community.wolfram.com/guidelines]Community Guidelines[/url] [*]Fill out your profile information [*]Browse and join [url=http://community.wolfram.com//groups][/url][url=http://www.wolfram.com/community/web/community/groups]Groups[/url]  [*]Explore and have a great time! [/list]This is our “introduce yourself” thread where you can say a few things about yourself by simply replying to this post. As soon as you do, the thread will bubble up to the top of our front page and everyone will know that you have joined and have a chance to read about you. To give you an example, I will introduce myself. I am a member of the Technical Communication and Strategy group at Wolfram Research. I get to play with almost every tidbit of the technologies we develop, build exemplary usage cases, and showcase them to the world through our sites and events. I publish at the Wolfram Demonstrations Project, write for the Wolfram Blog, and am a faculty member at the Wolfram Science Summer School. Among these and other things, I oversee management and moderation of Wolfram Community. Now it is your turn! Please note this thread is long (so many new members!) and the reply box is at the bottom. Now, please, tell us who you are! Vitaliy Kaurov 2012-10-18T06:49:28Z https://community.wolfram.com/groups/-/m/t/1106375 Greetings, I am working on a very complicated equation that needs to be solved. To simplify the function I use a limit in which x is much less than D or ( x<<D). I cannot find much less/greater condition in Mathematica. I need to solve that equation symbolically and I know that I should get four solutions. By taking a limit manually I got something like A*x^4-B*x^2+C=0. Then using solve I was able to get four solution, but with coefficients that were very long. (In manual calculations, I was able to get shorter coefficients) How do I solve equation with much less condition? Just for the sake of example let say I want to solve f(x)= sqrt( D^2 - ( x - z )^2 ) + x * cos(a) + x + z after limit f(x)= sqrt( D^2 - ( z )^2 ) + x * cos(a) + x + z Is there a command in Mathematica to selectively simplify/factor/expand some terms instead all terms in equations? Adam Szewczyk 2017-05-25T01:56:46Z https://community.wolfram.com/groups/-/m/t/1323951 This has been one of my favorite Mathematica projects! Here are a couple of AI-generated outlines of my progress in computing the MKB constant, $\lim_{N->\infty} \int^{2N}_1(-1)^xe^{i \pi x}x^{1/x},$ digits: ![enter image description here][2] ![enter image description here][3] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=Screenshot2026-06-20183947.png&userId=366611 [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=4506unnamed.png&userId=366611 [3]: https://community.wolfram.com//c/portal/getImageAttachment?filename=unnamed%281%29.png&userId=366611 Marvin Ray Burns A.G.S. (cum laude) 2018-04-20T12:06:18Z https://community.wolfram.com/groups/-/m/t/1105739 I am new to WolframAlpha and this might be a very basic question - however: when I am trying to print any result from WolframAlpha, the output appears to be scrambled, it looks like printed twice, and the "second" text seems to contain the question and something like **1&rawformassumption="ClashPrefs" -> {"Math"}.** I added a scanned page, to make it clear. I tried to deinstall my addblocker, but this does not seem to help. The results are looking fine on the screen, No such problem with Mathematica. If there is an obvious solution, please? Best Regards Joachim !["scrambled" output][1] [1]: http://community.wolfram.com//c/portal/getImageAttachment?filename=printout.png&userId=1105725 Joachim von Zahn 2017-05-24T10:45:19Z https://community.wolfram.com/groups/-/m/t/1108742 Consider the following code: f = {1, x, x^2, x^3} Panel[Column[{Row[{CheckboxBar[ Dynamic[list1], # -> f[[#]] & /@ Range[4]], Dynamic[list1]}], Dynamic[Plot[f[[list1]], {x, 0, 1.5}, PlotStyle -> {Red, Blue, Green, Black}, ImageSize -> 500, AxesStyle -> Thick]]}]] I want to get a Dynamic image that show differrent functions according to user selection in Checkbox. However, now I get a fine Dynamic image except that all the curves are in the same color. I wanna know How to set the color of each option? Wu Falchion 2017-05-26T07:13:37Z https://community.wolfram.com/groups/-/m/t/1104811 I'm wondering how to define a net function that will multiply matrices inside a tensor. For example, if $s$ and $t$ are tensors with shapes $\{a,b,c\}$ and $\{a,c,d\}$ respectively, for each $i\leq a$ the subtensors in $s$ and $t$ with first index $i$ form matrices of dimensions $b\times c$ and $c\times d$ respectively. Multiplying corresponding matrices in $s$ and $t$ would produce a new tensor with shape $\{a,b,d\}$. Is there currently a way to do this in Mathematica using nn layers? DotLayer and ThreadingLayer have depth limitations that seem to prevent it. Andrew Dabrowski 2017-05-23T19:26:30Z https://community.wolfram.com/groups/-/m/t/1108310 Below is a code snippet to plot a handful of curves with some plot labels. For some reason only the first label is used and not the other four. What am I missing here? I've successfully used PlotLabels for parametric curves before but they seem to fail me here. Got any ideas??: lmt=10 qq[zets_]=1/Sqrt[1+zets^2]^3 zets[rr_,eps_,eta_]=eps (1-rr^2) (1+eta (1+rr^2)) demcurves=Array[qq[zets[rr,2 #/lmt,0]]&,lmt/2] Plot[demcurves,{rr,0,1}] demlabels = Map[ToString,Array[qqzz[N[2/lmt]#]&,lmt/2]] Plot[demcurves,{rr,0,1},PlotLabels -> Placed[demlabels,Left]] Anthony DeGance 2017-05-25T17:19:36Z https://community.wolfram.com/groups/-/m/t/181759 I was wondering, it would be interesting to try to use the community as a way to request new functions that could be incorporated into new versions of Wolfram Language, in a colaborative way. Sometimes users simply don't have the whole/deeper system view, to understand that the requested function is or too specific, too broad or already implemented, but I believe that another times we can have a nice insights, that Wolfram Research people haven't yet, or that do not have received much attention  yet.  To the idea is: [b]Post your's requested Function as a answer to this question, and let's upvotes show the more interesting ones![/b] Some rules 1- One Post per function (or class of function), you can have more than one request. 2- Exemplify your function use. Rodrigo Murta 2014-01-08T09:14:19Z https://community.wolfram.com/groups/-/m/t/1108337 By steps Insert/FilePath, I got a file path: "D:\\Mathematica\\Mathematica Programer II\\MATHPROG\\LOGICPROGRAMMING.M", but Needs["D:\\Mathematica\\Mathematica Programer \ II\\MATHPROG`LOGICPROGRAMMING.m`"] Mathematica always says Needs::cxt: Invalid context specified at position 1 in Needs[D:\Mathematica\Mathematica Programer II\MATHPROG`LOGICPROGRAMMING.m` ]. A context must consist of valid symbol names separated ` In fact I put `, What's wrong? Math Logic 2017-05-26T03:00:05Z https://community.wolfram.com/groups/-/m/t/1872608 *Short URL to share this post*: https://wolfr.am/coronavirus ***JOIN*** *our* ***Medical Sciences*** *group for the latest updates & best networking*: https://wolfr.am/MedicalSciences ---------- This post is intended to be the hub for Wolfram resources related to novel coronavirus disease COVID-19 that originated in Wuhan, China. The larger aim is to provide a forum for disseminating ways in which Wolfram technologies and coding can be utilized to shed light on the virus and pandemic. Possibilities include using the Wolfram Language for data-mining, modeling, analysis, visualizations, and so forth. Among other things, we encourage comments and feedback on these resources. Please note that this is intended for technical analysis and discussion supported by computation. Aspects outside this scope and better suited for different forums should be avoided. Thank you for your contribution! ## ________________________________________ ## FEATURED CONTENT - [COVID-19 Livestream Notebook March 24][8] by Stephen Wolfram - [Agent-Based Networks Models for COVID-19][9] by Christopher Wolfram - [Live-Stream: Exploring Pandemic Data][10] by Stephen & Christopher Wolfram + guests - [Live-Stream: Exploring and Explaining Epidemic Modeling][11] by Stephen & Christopher Wolfram + guests ## ________________________________________ ## [CALL for Making COVID-19 Data Computable (*link*)][12] More pandemic-related information and data sets emerging every day. We invite people in the community to contribute to making more data surrounding this topic computable. Here is a call to action with some recommendations for people who want to do more, whether it's just pointing out relevant data sources, or taking the time to make some of that data computable and more instantly ready for other people to explore: https://wolfr.am/COVID-19-DATA . ## ________________________________________ ## [Curated Computable Data (*link*)][13] [FOLLOW THIS LINK][14] to see all available COVID-19 data repositories ready for computation in the Wolfram Language . [Changes in Updates to SARS-CoV-2 Sequences in the Wolfram Data Repository][16] We have published and are continuously updating the Wolfram Data Repository entries. Below are a few key ones. Follow the link above to browse all repositories. We encourage you to make [*your own contributions*][15] of curated data relevant to COVID-19. > **Pandemic Data for Novel Coronavirus COVID-19** > https://www.wolframcloud.com/obj/resourcesystem/published/DataRepository/resources/Epidemic-Data-for-Novel-Coronavirus-COVID-19 > **Genetic Sequences for the SARS-CoV-2 Coronavirus** > https://datarepository.wolframcloud.com/resources/Genetic-Sequences-for-the-SARS-CoV-2-Coronavirus > **Patient Medical Data for Novel Coronavirus COVID-19** > https://datarepository.wolframcloud.com/resources/Patient-Medical-Data-for-Novel-Coronavirus-COVID-19 > **COVID-19 Hospital Resource Use Projections** > https://datarepository.wolframcloud.com/resources/COVID-19-Hospital-Resource-Use-Projections > **OECD Data: Hospital Beds Per Country** > https://datarepository.wolframcloud.com/resources/OECD-Data-Hospital-Beds-Per-Country > **Hospital Beds Per US State** > https://datarepository.wolframcloud.com/resources/Hospital-Beds-Per-US-State ## ________________________________________ ## [Computational Publications (*link*)][17] We encourage you to share your computational explorations relevant to coronavirus on Wolfram Community as stand-alone articles and then comment with their URL links on this discussion thread. We will summarize these articles in the following list: ### ________________________________ ###FEATURED > **COVID-19 Livestream Notebook March 24** by Stephen Wolfram > https://www.wolframcloud.com/obj/s.wolfram/Published/COVID-19-Livestream-March-24.nb > **Agent-Based Networks Models for COVID-19** by Christopher Wolfram > https://community.wolfram.com/groups/-/m/t/1907703 > **Epidemiological Models for Influenza and COVID-19** by Robert Nachbar > https://community.wolfram.com/groups/-/m/t/1896178 > **Epidemic simulation with a polygon container** by Francisco Rodríguez > https://community.wolfram.com/groups/-/m/t/1901002 > **Distance to nearest confirmed US COVID-19 case** by Chip Hurst > https://community.wolfram.com/groups/-/m/t/1911583 ### ________________________________ ### EPIDEMIC MODELING: SIMULATION > **Epidemic simulation with a polygon container** by Francisco Rodríguez > https://community.wolfram.com/groups/-/m/t/1901002 > **Agent based epidemic simulation** by Jon McLoone > https://community.wolfram.com/groups/-/m/t/1900481 > **Modeling the spatial spread of infection diseases in the US** by Diego Zviovich > https://community.wolfram.com/groups/-/m/t/1889072 > **Geo-spatial-temporal COVID-19 simulations and visualizations over USA** by Diego Zviovich > https://community.wolfram.com/groups/-/m/t/1900514 > **Life, Liberty, and Lockdowns: cellular automaton approach** by Philip Maymin > https://community.wolfram.com/groups/-/m/t/2181433 ### ________________________________ ### EPIDEMIC MODELING: COMPARTMENTAL > **Teaching notebook on disease models** by Gareth Russell > https://community.wolfram.com/groups/-/m/t/2694698 > **Stochastic Epidemiology Models with Applications to the COVID-19** by Robert Nachbar > https://community.wolfram.com/groups/-/m/t/1980051 > **COVID19: Italian SIRD estimates and prediction** by Christos Papahristodoulou > https://community.wolfram.com/groups/-/m/t/1984320 > **Solver for COVID-19 epidemic model with the Caputo fractional derivatives** by Alexander Trounev > https://community.wolfram.com/groups/-/m/t/1976589 > **EpiPlay: using Mathematica to gamify education in epidemiology** by Rui Alves > https://community.wolfram.com/groups/-/m/t/2535927 > **Epidemiological Model for repetitive rapid testing for COVID-19** by Diego Zviovich > https://community.wolfram.com/groups/-/m/t/2075883 > **Phase transition of a SIR agent-based models** by Diego Zviovich > https://community.wolfram.com/groups/-/m/t/1977230 > **A simple estimate of covid-19 fatalities based on past data** by Kay Herbert > https://community.wolfram.com/groups/-/m/t/1959438 > **SIR Model with Log-normal infected periods** by Diego Zviovich > https://community.wolfram.com/groups/-/m/t/1946292 > **SEI2HR-Econ model with quarantine and supplies scenarios** by Anton Antonov > https://community.wolfram.com/groups/-/m/t/1937880 > **COVID-19 - Policy Simulator - Can you find the perfect policy?** by Jan Brugard > https://community.wolfram.com/groups/-/m/t/1931352 > **Epidemiological Models for Influenza and COVID-19** by Robert Nachbar > https://community.wolfram.com/groups/-/m/t/1896178 > **Exploring Epidemiological Modeling** by Jordan Hasler > https://community.wolfram.com/groups/-/m/t/1920119 > **SEI2HR model with quarantine scenarios** by Anton Antonov > https://community.wolfram.com/groups/-/m/t/1926505 > **The SIR Model for Spread of Disease** by Arnoud Buzing > https://community.wolfram.com/groups/-/m/t/1903289 > **COVID-19 - R0 and Herd Immunity - are we getting closer?** by Jan Brugard > https://community.wolfram.com/groups/-/m/t/1911422 > **Basic experiments workflow for simple epidemiological models** by Anton Antonov > https://community.wolfram.com/groups/-/m/t/1895675 > **Scaling of epidemiology models with multi-site compartments** by Anton Antonov > https://community.wolfram.com/groups/-/m/t/1897377 > **WirVsVirus 2020 hackathon participation** by Anton Antonov > https://community.wolfram.com/groups/-/m/t/1907256 > **An SEIR like model that fits the coronavirus infection data** by Enrique Garcia Moreno > https://community.wolfram.com/groups/-/m/t/1888335 > **A SEIRD Model For COVID-19 Using DDEs** by Luis Borgonovo > https://community.wolfram.com/groups/-/m/t/1996374 > **A Neat Package for Compartmental Model Diagrams** by Hamza Alsamraee > https://community.wolfram.com/groups/-/m/t/2078640 > **Redesign of didactics of S(E)IR(D) -> SI(EY)A(CD) models of epidemics** by Thomas Colignatus > https://community.wolfram.com/groups/-/m/t/2004784 > **COVID-19 SIR models: transmission, vaccination, herd immunity dynamics revealed** by Athanasios Paraskevopoulos > https://community.wolfram.com/groups/-/m/t/3008488 ### ________________________________ ### EPIDEMIC MODELING: LOGISTIC > **COVID-19 pandemic data in Italy** by Riccardo Fantoni > https://community.wolfram.com/groups/-/m/t/1909687 > **Predicting Coronavirus Epidemic in United States** by Robert Rimmer >https://community.wolfram.com/groups/-/m/t/1906954 > **Tracking Coronavirus Testing in the United States** by Robert Rimmer > https://community.wolfram.com/groups/-/m/t/1902302 > **Logistic Model for Quarantine Controlled Epidemics** by Robert Rimmer > https://community.wolfram.com/groups/-/m/t/1900530 > **Updated: coronavirus logistic growth model: China** by Robert Rimmer > https://community.wolfram.com/groups/-/m/t/1890271 > **Coronavirus logistic growth model: China** by Robert Rimmer > https://community.wolfram.com/groups/-/m/t/1887435 > **Coronavirus logistic growth model: Italy and South Korea** by Robert Rimmer > https://community.wolfram.com/groups/-/m/t/1887823 > **Coronavirus logistic growth model: South Korea** by Robert Rimmer > https://community.wolfram.com/groups/-/m/t/1894561 > **Logistic growth model for epidemic Covid-19 in Colombia** by Diego Ramos > https://community.wolfram.com/groups/-/m/t/2092786 ### ________________________________ ### GENOMICS > **Analyzing the spread of SARS-CoV-2 variants in California** by Daniel Lichtblau > https://community.wolfram.com/groups/-/m/t/2205357 > **Analyzing the spread of SARS-CoV-2 variants in Florida** by Daniel Lichtblau > https://community.wolfram.com/groups/-/m/t/2206874 > **Analyzing Nextstrain Data with WFR Newick Functions (COVID-19/SARS-CoV-2)** by John Cassel > https://community.wolfram.com/groups/-/m/t/1958952 > **Finding and analyzing a COVID subvariant in Australia** by Daniel Lichtblau > https://community.wolfram.com/groups/-/m/t/2342489 > **Analyzing SARS-CoV-2 Genetic Sequences** by John Cassel & Daniel Lichtblau > https://blog.wolfram.com/2021/08/19/newick-trees-proximity-resources-and-accessions-analyzing-sars-cov-2-genetic-sequences/ > **Estimating the number of times the SARS CoV-2 virus has replicated** by Carlos Munoz > https://community.wolfram.com/groups/-/m/t/1943243 >**From sequenced SARS-CoV-2 genomes to a phylogenetic tree** by Daniel Lichtblau >https://community.wolfram.com/groups/-/m/t/1961461 > **Genome analysis and the SARS-nCoV-2** by Daniel Lichtblau > https://community.wolfram.com/groups/-/m/t/1874816 > **Visualizing Sequence Alignments from the COVID-19** by Jessica Shi > https://community.wolfram.com/groups/-/m/t/1875352 > **A walk-through of the SARS-CoV-2 nucleotide Wolfram resource** by John Cassel > https://community.wolfram.com/groups/-/m/t/1887456 > **Geometrical analysis of genome for COVID-19 vs SARS-like viruses** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1878824 > **Chaos Game For Clustering of Novel Coronavirus COVID-19** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1875994 ### ________________________________ ### DATA ANALYSIS > **Optimal Annual COVID-19 Vaccine Boosting Dates Following Previous Booster Vaccination or Breakthrough Infection** by Jeffrey Townsend > https://community.wolfram.com/groups/-/m/t/3341399 > **Probability of early infection extinction depends linearly on the virus clearance rate** by Nóra Juhász > https://community.wolfram.com/groups/-/m/t/3307502 > **Detecting Global Community Structure in a COVID-19 Activity Correlation Network** by Hiroki Sayama > https://community.wolfram.com/groups/-/m/t/3056172 > **Analyzing trends of COVID-19 through public news feeds** by Silvia Hao > https://community.wolfram.com/groups/-/m/t/2569395 > **Deep neural network detection & clinical staging of COVID-19 chest X-rays** by Peter Riley > https://community.wolfram.com/groups/-/m/t/2389110 > **COVID-19 - The Swedish Experiment - Is it working?** by Jan Brugard > https://community.wolfram.com/groups/-/m/t/1974412 > **A simple COVID-19 spread model** by Daniel Lichtblau > https://community.wolfram.com/groups/-/m/t/1945196 > **COVID19: The performance of the Swedish strategy** by Christos Papahristodoulou > https://community.wolfram.com/groups/-/m/t/1990972 > **Exploring social trends on Covid-19 pandemic using WikipediaData** by Jofre Espigule-Pons > https://community.wolfram.com/groups/-/m/t/1931508 > **Google Mobility Data** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1946686 > **Understanding Aggregate COVID Curves** by Christopher Wolfram > https://community.wolfram.com/groups/-/m/t/2068457 > **Apple mobility trends data visualization** by Anton Antonov > https://community.wolfram.com/groups/-/m/t/1942813 > **Computing COVID-19 Spread Rates in US Cities** by Daniel Lichtblau > https://community.wolfram.com/groups/-/m/t/1930261 > **COVID-19 data and the Newcomb Benford Distribution** by Gustavo Delfino > https://community.wolfram.com/groups/-/m/t/1913908 > **Short-time trends for COVID-19**, by Fabian Wenger > https://community.wolfram.com/groups/-/m/t/1912710 > **What countries are hit hard by COVID19 outbreak?** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1904507 > **COVID19 in Iran: under-diagnosis issue** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1891140 > **Coronavirus analysis: descriptive statistics with SQL functions** by Damian Calin > https://community.wolfram.com/groups/-/m/t/2206078 > **Covid-19 vaccine campaigns efficacy analysis** by Damian Calin > https://community.wolfram.com/groups/-/m/t/2383314 > **Argentina: COVID-19 Data Analysis** by Tobias Canavesi > https://community.wolfram.com/groups/-/m/t/1932910 > **Analysis of the Change in Phillips Curve After COVID-19 with Regression** by Seojin Yoon > https://community.wolfram.com/groups/-/m/t/2055704 > **COVID wave alert: statistical analysis and visualization** by Antonio Neves > https://community.wolfram.com/groups/-/m/t/2115658 > **Predicting COVID-19 using cough sounds classification** by Siria Sadeddin > https://community.wolfram.com/groups/-/m/t/2166833 > **Covid-19 vaccination data analysis using SQL functions** by Damian Calin > https://community.wolfram.com/groups/-/m/t/2324474 > **Analyzing COVID-19 vaccine sentiment over time** by Arshaan Sayed > https://community.wolfram.com/groups/-/m/t/2317293 > **VAERS data analysis using SQL functions** by Damian Calin > https://community.wolfram.com/groups/-/m/t/2351726 > **Correlating COVID-19 government measures to biweekly/daily outbreaks** by Arshaan Sayed > https://community.wolfram.com/groups/-/m/t/2362327 > **Plotting Covid19 sentiment in different regions of Chennai** by Aditya Sairam Prakash > https://community.wolfram.com/groups/-/m/t/2388236 ### ________________________________ ### DATA VISUALIZATIONS > **CDC COVID19 vaccination data across US counties** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/2282418 > **Top 20 COVID countries HeatMap by absolute death and death in ppm** by Rodrigo Murta > https://community.wolfram.com/groups/-/m/t/2004800 > **COVIDWORLD app: current data and visualizations for SARS-CoV2 pandemic** by Rui Alves > https://community.wolfram.com/groups/-/m/t/2473065 > **US Counties COVID-19 confirmed cases by population density timelines** by Bob Sandheinrich > https://community.wolfram.com/groups/-/m/t/1992898 > **3D Modeling of the SARS-CoV-2 Virus in the Wolfram Language** by Jeff Bryant > https://community.wolfram.com/groups/-/m/t/1989540 > **California COVID19 Data** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/2132204 > **COVID-19 progress in Peru macro regions: coast vs mountain vs jungle** by Francisco Rodríguez > https://community.wolfram.com/groups/-/m/t/1965079 > **COVID-19 reopening criterion: a simple visualization** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1962615 > **100 Days of COVID19 Over US Counties** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1956368 > **Population Density Map** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1955760 > **Google Mobility Data** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1946686 > **COVID19 Case-Fatality Ratio, Income, and Age: Simple Visualization** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1939045 > **Data Analysis of Coronavirus in Mexico** by Ivan Martinez > https://community.wolfram.com/groups/-/m/t/1927657 > **Confirmed COVID-19 Cases in Catalonia** by Bernat Espigulé Pons > https://community.wolfram.com/groups/-/m/t/1919468 > **Distance to nearest confirmed US COVID-19 case** by Chip Hurst > https://community.wolfram.com/groups/-/m/t/1911583 > **COVID19 Confirmed Cases: US Counties** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/1950980 > **COVID19 data visualization across US counties** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/2119049 > **Maps for Visualizing Covid-19's Effect** by Eric Mockensturm > https://community.wolfram.com/groups/-/m/t/1934457 > **US Counties COVID-19 deaths plot** by Bob Sandheinrich > https://community.wolfram.com/groups/-/m/t/1918332 > **Comparing the spread of COVID-19 between countries**, Jan Brugard > https://community.wolfram.com/groups/-/m/t/1905992 > **NY Times COVID-19 data visualization** by Anton Antonov > https://community.wolfram.com/groups/-/m/t/1911668 > **COVID-19 cases for each administrative division in Spain** by Bernat Espigulé Pons > https://community.wolfram.com/groups/-/m/t/1910116 > **Propagation risk of COVID-19 by local contact in Spain (10 - 14 March)** by Bernat Espigulé Pons > https://community.wolfram.com/groups/-/m/t/1898126 > **Visualizing the Pandemic Data COVID-19** by Martijn Froeling > https://community.wolfram.com/groups/-/m/t/1899870 > **COVID-19 visualization of turning point** by Isao Maruyama > https://community.wolfram.com/groups/-/m/t/1899911 > **Mapping "Live" COVID Data on a Globe** by Gabriel Lemieux > https://community.wolfram.com/groups/-/m/t/1902102 > **Novel Coronavirus COVID-19 in Brazil** by Estevao Teixeira > https://community.wolfram.com/groups/-/m/t/1905950 > **Mapping Novel Coronavirus COVID-19 Outbreak** by Jofre Espigule-Pons > https://community.wolfram.com/groups/-/m/t/1868945 > **Ways to visualize COVID-19 simulation results?** by Kyle Keane > https://community.wolfram.com/groups/-/m/t/1962739 > **General and COVID-19 deaths in Sweden** by Oscar Rodriguez > https://community.wolfram.com/groups/-/m/t/2006377 > **COVID19 Tokyo per days of the week** Isao Maruyama > https://community.wolfram.com/groups/-/m/t/2133807 ### ________________________________ ### DATA PROCESSING > **Cov-Tell: Daily COVID-19 Updates with Alexa (made with Wolfram APIFunction)** by Jessica Shi > https://community.wolfram.com/groups/-/m/t/1958307 > **Build a COVID-19 Chest X-Ray Image Uploader with Cloud & Data Drop** by Jofre Espigule-Pons > https://community.wolfram.com/groups/-/m/t/1919770 > **Scraping OpenTable's "State of the Industry" page** by Aaron Enright > https://community.wolfram.com/groups/-/m/t/1911043 > **City-level Search Tool for Coronavirus (COVID-19) Confirmed Cases** by David Lomiashvili > https://community.wolfram.com/groups/-/m/t/1913247 > **Web Scraper: New York Times Coronavirus Data** by Robert Rimmer > https://community.wolfram.com/groups/-/m/t/1894426 > **TraCOV: Personalized COVID-19 Risk Analysis Tool** by Jessica Shi > https://community.wolfram.com/groups/-/m/t/1977700 > **Mobility changes data: transforming to Wolfram Language dataset** by Mads Bahrami > https://community.wolfram.com/groups/-/m/t/2160386 ### ________________________________ ### MASKS > **Effect of mandatory mask usage in COVID cases** by Diego Zviovich > https://community.wolfram.com/groups/-/m/t/1919060 > **Face mask detection: classifying image data** by Siria Sadeddin > https://community.wolfram.com/groups/-/m/t/2139499 ## ________________________________________ ## [Livestream Archives (*link*)][18] - Stephen & Christopher Wolfram + guests [Exploring Pandemic Data][19] - Stephen & Christopher Wolfram + guests [Exploring and Explaining Epidemic Modeling][20] - Robert Nachbar - [Epidemiological Models for Influenza and COVID-19][21] - Brian Wood - [COVID-19 Dashboard Visualizations][22] - John Cassel - [Behind the Genetic Sequences for Novel Coronavirus SARS-CoV-2][23] - Keiko Hirayama - [Patient Data Exploration for the Novel Coronavirus COVID-19][24] - Keiko Hirayama - [Pandemic Data Exploration for the Novel Coronavirus COVID-19][25] - Diego Zviovich - [Geo-spatial-temporal COVID-19 Simulations and Visualizations Over USA][26] - Anton Antonov - [COVID19 Epidemic Modeling: Compartmental Models][27] - Anton Antonov - [Scaling of Epidemiology Models with Multi-site Compartments][28] - Anton Antonov - [Simple Economic Extension of Compartmental Epidemiological Models][29] - Juan Klopper - [Coronavirus medical data analysis][30] - Juan Klopper - [Coronavrirus epidemiological data analysis][31] - Rory Foulger - [Coronavirus Data Exploration - Wolfram Livecoding with Students][32] ## ________________________________________ ## Other useful resources - Arnoud Buzing [GitHub][33] repository and [Notebook Gallery][34] for coronavirus - [Modeling a Pandemic like Ebola with the Wolfram Language](https://blog.wolfram.com/2014/11/04/modeling-a-pandemic-like-ebola-with-the-wolfram-language) - [Epidemics at Wolfram Demonstrations](https://demonstrations.wolfram.com/search.html?query=epidemic) - [IGSIRProcess - IGraph Epidemic models][35] [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=1China_c.png&userId=1624544 [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=1.5US_c.png&userId=1624544 [3]: https://community.wolfram.com//c/portal/getImageAttachment?filename=2World_c.png&userId=1624544 [4]: https://community.wolfram.com//c/portal/getImageAttachment?filename=3Genetic_c.png&userId=1624544 [5]: https://community.wolfram.com//c/portal/getImageAttachment?filename=4Patient_c.png&userId=1624544 [6]: https://community.wolfram.com//c/portal/getImageAttachment?filename=5Resources_c.png&userId=1624544 [7]: https://www.wolframcloud.com/obj/examples/COVID19Preview.png [8]: https://www.wolframcloud.com/obj/s.wolfram/Published/COVID-19-Livestream-March-24.nb [9]: https://community.wolfram.com/groups/-/m/t/1907703 [10]: https://youtu.be/Vs5APySGYnk [11]: https://youtu.be/kC6LHAv_lx0 [12]: https://community.wolfram.com/groups/-/m/t/1908923 [13]: https://datarepository.wolframcloud.com/search/?i=COVID-19 [14]: https://datarepository.wolframcloud.com/search/?i=COVID-19 [15]: https://reference.wolfram.com/language/workflow/SubmitToTheWolframDataRepository.html [16]: https://community.wolfram.com/groups/-/m/t/2238214 [17]: http://wolfr.am/StaffPicks [18]: https://www.youtube.com/playlist?list=PLxn-kpJHbPx3_hUbroRYC_7NxcOwZ1SWa [19]: https://youtu.be/Vs5APySGYnk [20]: https://youtu.be/kC6LHAv_lx0 [21]: https://youtu.be/pcFB6_yrxGE [22]: https://youtu.be/vUq8qx7kTYA [23]: https://youtu.be/HCJgv3N_kDo [24]: https://youtu.be/MlI_8o4A3BA [25]: https://youtu.be/P86ZY-znE64 [26]: https://youtu.be/Kjk-sYlg-U0 [27]: https://youtu.be/LRs9rYCXIzs [28]: https://youtu.be/b8oCNjRI0gY [29]: https://youtu.be/C-sjXQiPE7s [30]: https://youtu.be/gA0TPQZgNY0 [31]: https://youtu.be/I-n3zN4aU6c [32]: https://youtu.be/4xCfPIiredM [33]: https://github.com/arnoudbuzing/wolfram-coronavirus [34]: https://wolfr.am/JZNRriEE [35]: http://szhorvat.net/mathematica/IGDocumentation/#epidemic-models Vitaliy Kaurov 2020-02-04T15:18:14Z https://community.wolfram.com/groups/-/m/t/1108667 Hello! I want to plot a simple function, but on the OX axis, the output labels are by default 1,2,3, etc. I want to have them in the format **x/2**. Instead of 1,2,3, I want 2/2, 4/2, 6/2. Is this possible? But only on the OX axis. Thank you in advance! Robert Poenaru 2017-05-26T09:12:30Z https://community.wolfram.com/groups/-/m/t/1108617 Hi i'm trying to plot disks of radius =(1-f[x]), so that it makes a sphere, as we know that the volume of a cylinder having height=2 radius - the volume of the cone having radius r, is always equal to the volume of a sphere having radius r. but i want to show that using disks. Muhammad Afzal 2017-05-26T06:59:19Z https://community.wolfram.com/groups/-/m/t/1108324 ![Möbius transformations of the circle][1] **Back and Forth** One fact I've known for a while but never really dived into is that Möbius transformations of the circle can be realized by inverse stereographic projecting to the sphere (here I'm thinking of the circle as the equator of the sphere, so inverse stereographic projection is just the identity in this case), rotating the sphere in space (say, around the south pole), and then stereographically projecting from the new "north pole" back to the circle. The animation shows what happens when you do this to 15 equally-spaced points on the circle, where the sphere is being rotated by an angle of $\pi/3$ around the axis $(\cos \psi, \sin \psi, 0)$ anchored at $(0,0,-1)$, and we let $\psi$ vary from 0 to $2\pi$. &[Wolfram Notebook][2] [1]: http://community.wolfram.com//c/portal/getImageAttachment?filename=mobius12.gif&userId=610054 [2]: https://www.wolframcloud.com/obj/545113ac-8325-4e63-82ae-d770422f55f5 Clayton Shonkwiler 2017-05-25T19:34:31Z https://community.wolfram.com/groups/-/m/t/2286246 $\int_0^\infty e^{i \pi x} \left(1-(x+1)^{\frac{1}{x+1}}\right) dx$ ![enter image description here][1] ![enter image description here][2] ![enter image description here][3] f[x_] = E^(I*Pi*x)*(1 - (x + 1)^(1/(x + 1))); g[x_] = x^(1/x); u := t/(1 - t); sub = Im[NIntegrate[(f[(-I t)] - f[( I t)])/(Exp[2 Pi t] - 1), {t, 0, Infinity}, WorkingPrecision -> 100]] 0.1170836031505383167089899122239912286901483986967757585888318959258587743002\ 7817712246477316693025869 m = NSum[f[( t)] , {t, 0, Infinity}, WorkingPrecision -> 100, Method -> "AlternatingSigns"] 0.1878596424620671202485179340542732300559030949001387861720046840894772315646\ 6021370329665443217278 m - sub 0.0707760393115288035395280218302820013657546962033630275831727881636184572643\ 8203658083188126524252 Is the same as {Re[NIntegrate[f[t], {t, 0, Infinity}]], and, Re[NIntegrate[f[t], {t, 0, Infinity I}, WorkingPrecision -> 100]]} NIntegrate::deodiv: DoubleExponentialOscillatory returns a finite integral estimate, but the integral might be divergent. NIntegrate::deodiv: DoubleExponentialOscillatory returns a finite integral estimate, but the integral might be divergent. {0.070776, and, \ 0.0707760393115288035395280218302820013657546962033630275831727881636184572643\ 8203658083188126617723821} To be continued. ---------------- [1]: https://community.wolfram.com//c/portal/getImageAttachment?filename=01.jpg&userId=366611 [2]: https://community.wolfram.com//c/portal/getImageAttachment?filename=02.jpg&userId=366611 [3]: https://community.wolfram.com//c/portal/getImageAttachment?filename=03.jpg&userId=366611 Marvin Ray Burns A.G.S. (cum laude) 2021-06-09T05:56:08Z https://community.wolfram.com/groups/-/m/t/157461 This post shows how to build a simple GPS tracker with the Wolfram Language on a Raspberry Pi. To recreate this experiment you will need the following hardware (in addition to the Raspberry Pi itself): [list] [*][url=http://www.adafruit.com/products/746]Ultimate GPS Breakout[/url] [*][url=http://www.adafruit.com/products/954]USB to TTL serial cable[/url] [*][url=http://www.adafruit.com/products/954][/url][url=http://www.adafruit.com/products/64]Half-size bread board[/url] [*][url=http://www.adafruit.com/products/758]Male/male jumper wires[/url] [/list]Plug the GPS module into the breadboard as shown and connect red to VIN, black to GND, green to RX and white to TX, using the jumper wires and the USB to TTL serial cable. Plug the USB end of the cable into the Raspberry Pi (powered down). Power up your Raspberry Pi. [img=width: 512px; height: 384px;]/c/portal/getImageAttachment?filename=1-out.jpg&userId=11733[/img] The GPS module starts to transmit data shortly after power up and will continue to do so until it is unplugged from a power source. In a terminal start the Wolfram Language using the following command: [code]> wolfram Wolfram Language (Raspberry Pi Pilot Release) Copyright 1988-2013 Wolfram Research Information & help: wolfram.com/raspi In[1]:= [/code] You can now open the serial port using the [url=reference.wolfram.com/language/ref/DeviceOpen.html]DeviceOpen [/url]by entering: [mcode]serial = DeviceOpen["Serial",{"/dev/ttyUSB0","BaudRate"->9600}] [/mcode] This returns a DeviceObject which can be used to read GPS data from. In this case we use [url=http://reference.wolfram.com/language/ref/DeviceReadBuffer.html]DeviceReadBuffer [/url]to read all available GPS data that has been generated up to this point: [mcode]data = DeviceReadBuffer[serial,"String"] [/mcode] The data returned is in a comma separated format, called [url=http://aprs.gids.nl/nmea/]GPS NMEA sentences[/url].[code] $GPRMC,154541.000,A,4005.8369,N,08814.7322,W,0.04,253.32,201113,,,A*79 $GPVTG,253.32,T,,M,0.04,N,0.07,K,A*3B $GPGGA,154542.000,4005.8369,N,08814.7322,W,1,8,1.07,228.0,M,-33.9,M,,*6B $GPGSA,A,3,04,12,10,17,23,24,25,02,,,,,1.31,1.07,0.76*04 $GPGSV,3,1,12,04,65,040,24,02,63,265,16,10,55,135,39,12,48,302,21*7D $GPGSV,3,2,12,17,35,096,33,05,19,190,17,25,13,321,33,24,12,247,16*71 $GPGSV,3,3,12,23,05,061,31,13,02,090,27,20,02,036,35,45,,,*45 $GPRMC,154542.000,A,4005.8369,N,08814.7322,W,0.06,253.32,201113,,,A*78[/code] We can import the data with the Wolfram Language using ImportString:[mcode]csv = ImportString[ data, "CSV" ][/mcode] The NMEA sentences which contain GPS coordinates start with $GPRMC so we filter for those using Cases and pattern matching:[mcode]gps = Cases[ csv, {"$GPRMC", ___} ][/mcode] The coordinates (latitude and longitude) are in the 4th and 6th position of each list, for example this is the GPS coordinate for the first data point:[mcode]Part[ gps, 1, {4,6} ] / 100[/mcode] which returns the GPS location for Champaign, Illinois, where Wolfram Research is located 40' North, 88' West):[mcode]{40.0583, 88.1474} [/mcode] Arnoud Buzing 2013-11-21T17:10:15Z https://community.wolfram.com/groups/-/m/t/457158 Dear Community, I am just new to Mathematica that came with my Raspberry Pi2. For a while now I have been looking for a program, which is able to minimize a discontinuous and nonlinear problem. Up to now I created the following formulas: f1[x_] := Piecewise[{{0.00000000000252413096488599 x^4 - 0.0000000295981935774312 x^3 + 0.0001268180409138660 x^2 - 0.239339875030011 x + 368.934089585833, x > 0}, {0, x <= 0}}] f2[x_] := Piecewise[{{0.00000000000327848026710691 x^4 - 0.0000000379764365996404 x^3 + 0.0001584280843487410 x^2 - 0.284905693712486 x + 386.639837124850, x > 0}, {0, x <= 0}}] f3[x_] := Piecewise[{{0.00000000000273770414832564 x^4 - 0.0000000245466477791088 x^3 + 0.0000876247218487314 x^2 - 0.151272246878742 x + 298.178569447775, x > 0}, {0, x <= 0}}] f4[x_] := Piecewise[{{0.00000000000151824463118546 x^4 - 0.0000000164748347339070 x^3 + 0.0000716029554621768 x^2 - 0.140270401260495 x + 293.998348739492, x > 0}, {0, x <= 0}}] NMinimize[{f1[w] + f2[x] + f3[y] + f4[z], Plus[w, x, y, z] == 7000}, {w \[Element] Interval[{0, 4000}], x \[Element] Interval[{0, 4000}], y \[Element] Interval[{0, 3000}], z \[Element] Interval[{0, 3000}]}] Unfortunately now I get the following error messages three times before the calculation is aborted: During evaluation of In[8]:= NMinimize::nnum: The function value {812.066} is not a number at {Subscript[w, 1],Subscript[x, 1],Subscript[y, 1],Subscript[z, 1]} = {1052.02,1848.71,2479.67,1619.59}. Is there any quick way of resolving this issue? Did I enter something in a wrong way? At least the sum of the resulting values for w,x,y, and z being 7000 is correct, maybe 812,066 is a local minimum already. But why is there an error message? I also tried to use Minimize and different Methods, but the outcome is the same in all cases. And it is just a LOCAL minimum: As one might be able to see from the equation, fx[0]=0. A minimum value, f.e. for the entered w+x+y+z==7000, should incorporate that some of the functions are set to zero! Is there any way to include this possibility in a fast way? Or do I have to write a minimization for all 16 possibilities and minimize these again? Best regards, Peter Peter Bergmann 2015-03-11T16:05:57Z https://community.wolfram.com/groups/-/m/t/457288 [](https://gitter.im/MaTeX-help/Lobby?utm_source=badge&utm_medium=badge&utm_campaign=pr-badge&utm_content=badge) [](https://github.com/szhorvat/MaTeX/releases) [](https://github.com/szhorvat/MaTeX/releases) [](https://github.com/szhorvat/MaTeX/issues) [](https://zenodo.org/badge/latestdoi/31675019) ---- Hello everyone, I wrote a package that makes it easy to insert LaTeX-typeset formulae in Mathematica notebooks, in particular in Mathematica graphics. I use this to create figures with high quality typesetting that fit well with the visual style of LaTeX documents. Here's the [package description][1] and here's [MaTeX][2]. Features of the package: - get LaTeX-typeset snippets as Mathematica `Graphics` expressions (convenient for a Mathematica-centric workflow) - the baseline is preserved so these snippets can be precisely aligned with each other or with Mathematica text - control over font size, magnification and display or inline styles - integrated documentation (open the documentation centre and search for "MaTeX") Let me know what you think and whether you find it useful. A quick demo: <img src="http://community.wolfram.com//c/portal/getImageAttachment?filename=Screenshot2017-09-0111.08.27.png&userId=38370" width="772"> [1]: http://szhorvat.net/pelican/latex-typesetting-in-mathematica.html [2]: https://github.com/szhorvat/MaTeX [3]: http://community.wolfram.com//c/portal/getImageAttachment?filename=Screenshot2017-09-0111.08.27.png&userId=38370 Szabolcs Horvát 2015-03-12T01:39:42Z https://community.wolfram.com/groups/-/m/t/1070264 [Wolfram Language][1] (WL) is a powerful multi-paradigm programing language. There is a set of common mistakes that repeatedly tend to entrap new users. **This is a call to describe such mistakes building a "black-listing" guide for novice coders.** Please consider contributing. I suggest following simple rules (with gratitude adapted from a [similar effort][2]): - One topic per answer - Focus on non-advanced uses (it is intended to be useful for beginners and as a question closing reference) - Include a self explanatory title in header style (example: "# Basic built-in function syntax"; see [syntax guide][3] ) - Explain the symptoms, the mechanism behind the scenes and all possible causes and solutions you can think of. Be sure to include a beginner's level explanation (and a more advance one too, if you can) *Please, use "**Reply**" to a specific comment for structured clarity of nested comments.* ---------- ## Table of Contents - [Basic syntax of built-in functions][4] - [Learn how to use the Documentation Center effectively][5] - [Sorting numerical data and the behavior of Sort][6] - [What does @#(%=<\[!} et cetera mean?][7] - [Consider Reap/Sow Instead of AppendTo][8] - [Alternatives to Reap/Sow][9] - [Case sensitivity and typos][10] - [Numerical vs Symbolic -- What to do when plots are blank][11] - [Import and "CurrencyTokens"][12] [1]: https://www.wolfram.com/language [2]: https://mathematica.stackexchange.com/q/18393/13 [3]: http://community.wolfram.com/groups/-/m/t/270507 [4]: http://community.wolfram.com/groups/-/m/t/1069885 [5]: http://community.wolfram.com/groups/-/m/t/1070285 [6]: http://community.wolfram.com/groups/-/m/t/1070705 [7]: http://community.wolfram.com/groups/-/m/t/1070946 [8]: http://community.wolfram.com/groups/-/m/t/1084289 [9]: http://community.wolfram.com/groups/-/m/t/1164555 [10]: http://community.wolfram.com/groups/-/m/t/1084920 [11]: http://community.wolfram.com/groups/-/m/t/1086929 [12]: http://community.wolfram.com/groups/-/m/t/1086969 Vitaliy Kaurov 2017-04-23T23:54:23Z https://community.wolfram.com/groups/-/m/t/157473 This post shows how to use the GPIO with the Wolfram Language on a Raspberry Pi. To recreate this experiment you will need the following hardware (in addition to the Raspberry Pi itself): [list] [*][url=http://www.adafruit.com/products/301]Super Bright Blue 5mm LED[/url] [*][url=http://www.adafruit.com/products/1105]Pi T-Cobbler Breakout Kit[/url] [*][url=http://www.adafruit.com/products/239]Full sized breadboard[/url] [*][url=http://www.adafruit.com/products/758]Male/male jumper wires[/url] [*]A 400 ohm resistor (to prevent the LEDs from burning out). [/list] Set up the breadboard as shown: Plug the T-Cobbler into the breadboard with 13 pins in the E column and 13 pin in the G column. Use the jumper wires to connect pins 4, 17, 27, 22, 18, 23, 24 and 25 to evenly spaced free rows lower on the breadboard. Connect 8 blue LEDs from each jumper wire row to the blue - column, with the flattened cathode side on the blue - column. Complete the circuit by connecting the resistor from the blue - column to the GND pin. Connect the ribbon cable to the T-Cobbler and the Raspberry Pi correctly, and turn on your Raspberry Pi. [img=width: 512px; height: 683px;]/c/portal/getImageAttachment?filename=2-5344gpio_community.jpg&userId=11733[/img] The GPIO interface requires root privilege for access so the Wolfram Language or Mathematica needs to be started as root for this experiment. In a terminal start the Wolfram Language using the following command (as root): [code]> sudo wolfram Wolfram Language (Raspberry Pi Pilot Release) Copyright 1988-2013 Wolfram Research Information & help: wolfram.com/raspi In[1]:= [/code] First we define the pins that correspond to connected LEDs: [mcode]pins = {4,17,27,22,18,23,24,25} [/mcode] Next we can turn on individual LEDs by writing the value '1' to it: [mcode]DeviceWrite[ "GPIO", First[pins] -> 1 ] [/mcode] And of course turn it back off, by writing the value '0': [mcode]DeviceWrite[ "GPIO", First[pins] -> 0 ] [/mcode] Or turn the LEDs on and off one at a time: [mcode]Do[ DeviceWrite[ "GPIO", pins[[i]]->1 ]; Pause[.2]; DeviceWrite[ "GPIO", pins[[i]]->0 ]; ,{i,8}] [/mcode] Arnoud Buzing 2013-11-21T17:13:19Z