PCAM Authors Speaking About Their Work at SAMSI

The Statistical and Applied Mathematical Sciences Institute (SAMSI) has just run a Workshop on the Interface of Statistics and Optimization. Among the speakers were four authors of articles in The Princeton Companion to Applied Mathematics (PCAM).

In an earlier post I provided links to videos of PCAM authors giving talks related to the topics of their PCAM articles. To add to those, here are the four PCAM author talks from the SAMSI workshop.

I have also included the talk by Margaret Wright, because it provides insight into a number of important topics covered in PCAM in a very lucid way.

  • John Burns, Parameter Identification for Dynamical Systems with Structured Uncertainty (author of PCAM article Optimal Sensor Location in the Control of Energy-Efficient Buildings)

  • Jack Dongarra, The Road to Exascale and Legacy Software for Dense Linear Algebra (author of PCAM article High-Performance Computing)

  • Yonina Eldar, Phase Retrieval and Analog to Digital Compression (author of PCAM article Compressed Sensing)

  • Stephen Wright, Randomness in Coordinate Descent (author of PCAM article Continuous Optimization (Nonlinear and Linear Programming)

  • Margaret Wright, Old, New, Borrowed, and Blue in the Marriage of Statistics and Optimization

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Preparing CMYK Figures for Book Printing

All printing is done in CMYK, the color space based on the four colors cyan, magenta, yellow, and black. Figures that we generate in MATLAB and other systems are invariably saved in RGB format (red, green, blue). When we send a paper for publication we submit RGB figures and they are transformed to CMYK somewhere in the production process, usually without us realizing that it has been done.

If you are one of those people who writes books and prefers to generate the final PDF yourself then you will need to convert any color figures to CMYK. The generation and use of CMYK files is something of a dark art. Here I report what I found out about it when producing the third edition (2017) of MATLAB Guide, co-authored with Des Higham. This is the first edition of the book to use color.

CMYK produces a different range of colors than RGB. Since it is a subtractive color space, designed for inks, it cannot produce some of the brilliant colors that RGB can, especially in the blues. In other words, some RGB colors are out of gamut in CMYK. (Less importantly, the converse is true: some CMYK colors cannot be produced in RGB.) This is something we are used to, but usually do not notice. Whenever we print a document on a laser printer we view a CMYK representation of the colors. In many cases, a figure will look very similar in print and on screen, but there are plenty of exceptions.

The following image shows an RGB image on the left, the result of converting that image to CMYK and then back to RGB in the middle, and a scan of a laser printer’s reproduction of the RGB image on the right. circle-rgb-cmyk-scan.jpg The differences between the RGB version and the other two versions may be shocking! Fortunately, when the CMYK version is viewed on a printed page in isolation from the RGB version (necessarily displayed on a monitor) it does not look so bad. [Of course, if you are reading a printed version of this post then the first two images will look essentially the same.]

After some experimentation, I settled on the following procedure, which I describe for a PDF workflow. For a PostScript workflow, PDF files need to be replaced by EPS files.

  • Print the whole document from an RGB file.
  • Find figures that look very different in print than on screen and select from those any where the difference is not acceptable. In most cases an unacceptable difference will be one where contrast between colors, or saturation of colors, has been reduced.
  • Edit the selected figures in Photoshop, or some other image manipulation package that can save in CMYK form, in order to produce a better looking CMYK file. In Photoshop, Image-Mode-CMYK Color converts an image to CMYK form, but before using this command you should set the correct CMYK working space under Edit-Color Settings (see the Color Space section below). You can edit the RGB image (making use of View-Proof Color to see how the image will look in CMYK, and View-Gamut Warning to see colors that will be out of gamut in CMYK) and then convert to CMYK, or you can convert to CMYK and then edit the file. Save the CMYK image as a PDF file.
  • Generate the PDF file of the book using the edited CMYK figures and the RGB forms of all the other figures, that is, those that did not need special treatment.
  • Load the PDF file into Adobe Acrobat Pro and issue the command
    Tools - Print Production - Convert Colors
    

    This converts all objects in the file to CMYK.

Of the well over 100 figures in MATLAB Guide, only two needed special treatment.

However, there was one problem with this procedure. A handful of images are screen dumps that show a MATLAB window, and these are necessarily low resolution, at 72dpi. When converted to CMYK in Adobe Acrobat these images degraded badly. The solution was to resample the images to 150dpi in Photoshop via Image-Image Size and save to PDF; conversion in Acrobat then worked fine. (Such resampling is probably good practice anyway.)

This is not quite the full story. Here are some more gory details, which are worth reading if you are actually producing a book.

Color Spaces

There is no unique CMYK or RGB color space: these spaces are device dependent. RGB spaces can have different white points and CMYK spaces are designed for particular combinations of paper and ink. Adobe Acrobat Pro offers “U.S. Web Coated (SWOP) v2”, “Uncoated FOGRA29 (ISO 12647-2:2004)” and many other inscrutably named CMYK profiles. So “convert to CMYK” is an ill-defined instruction unless the precise profile is specified. The conversion settings I used are shown in this screen dump of the dialog box, and were provided by the company who printed the book. Your settings might need to be different. acrobat-cymk-conversion.jpg There are a couple of things to note. First, Adobe Acrobat does not remember the settings in the dialog box, so they need to be re-entered every time. Second, since “Embed profile” is not selected with the settings shown, there is no way to tell which profile has been used once the conversion has been done.

Does it really matter what CMYK profile you use? Yes, if you want the best possible results. Consider the following figure. circle-rgb_cmtk-2convs.jpg On the left is the result of converting the original RGB image to “U.S. Web Coated (SWOP) v2” and on the right is the result of converting to “Photoshop 5 default CMYK” (and converting back to RGB in both cases, the latter conversion producing no visual difference in Photoshop). There is a significant difference between the two conversions in every color except white! In principle, both conversions will produce the same result when printed with the target ink and paper, but if you choose the profile without knowing the target you have little idea what the printed result will be.

Photography Books

An important assumption in the process described above is that the accuracy of the color reproduction is not vital. For photography books this assumption clearly does not hold and conversion to CMYK enters a new and frightening realm where images might need to be individually fine-tuned. Indeed high quality photography books typically undergo one or more proof stages using actual galley proofs from the ultimate printing device, sometimes with the author present at the printing press.

Generating CMYK Files in MATLAB

Most of the figures in MATLAB Guide are (naturally) produced in MATLAB. Figures saved with the print function are by default in RGB mode. CMYK is supported for EPS and PS files only, using the ‘-cmyk’ option. This is not very useful if you are using a PDF workflow, as I do.

Instead of using the print function I experimented with export_fig, which is available on MathWorks File Exchange and can save in CMYK format to PDF, EPS, or TIFF files. export_fig creates a PDF file via an EPS file using Ghostscript.

This sounds straightforward, but I found that many of the PDF files generated by export_fig were not fully in CMYK Mode. A PDF file can contain objects in different color spaces and I had files where a color plot was in CMYK but the colorbar was in RGB! The question arises of how one can check whether a given PDF file has any RGB objects. Unfortunately, there seems to be no simple way to do so in Adobe Acrobat Pro. What one can do is invoke

Tools - Print Production - Preflight - PDF analysis - 
List objects using ICCbased CMYK - Analyze

then open up

Overview - color spaces

(I am using Adobe Acrobat Pro XI, 11.0.18; usage could differ in other versions). This should contain “DeviceCMYK color space”, but if it contains “DeviceRGB color space” or “DeviceGray color space” then RGB or Grayscale objects are present. If the latter terms appear in a multi-page PDF file, double clicking on the corresponding icon should take you to the last such object.

You can also open up

Overview - Images

to get a list of pages and object types on those pages. Double clicking on a page icon takes you to that page.

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Good Times in MATLAB: How to Typeset the Multiplication Symbol

The MATLAB output

>> A = rand(2); whos
  Name      Size            Bytes  Class     Attributes

  A         2x2                32  double

will be familiar to seasoned users. Consider this, however, from MATLAB R2016b:

>> s = string({'One','Two'})

s = 
  1×2 string array
    "One"    "Two"

At first sight, you might not spot anything unusual, other than the new string datatype. But there are two differences. First, MATLAB prints a header giving the type and size of the array. It does so for arrays of type other than double precision and char. Second, the times symbol is no longer an “x” but is now a multiplication symbol: “×”.

The new “times” certainly looks better. There are still remnants of “x”, for example in whos s for the example above, but I presume that all occurrences of “x” will be changed to the new symbol in the next release

However, there is a catch: the “×” symbol is a Unicode character, so it will not print correctly when you include the output in LaTeX (at least with the version provided in TeX Live 2016). Moreover, it may not even save correctly if your editor is not set up for Unicode characters.

Here is how we dealt with the problem in the third edition (published in January 2017) of MATLAB Guide. We put the code

\usepackage[utf8x]{inputenc}
\DeclareUnicodeCharacter{0215}{\ensuremath{\times}}

in the preamble of the master TeX file, do.tex. We also told our editor, Emacs, to use a UTF-8 coding, by putting the following code at the end of each included .tex file (we have one file per chapter):

%%% Local Variables:
%%% coding: utf-8
%%% mode: latex
%%% TeX-master: "do"
%%% End:

With this setup we can cut and paste output including “×” into our .tex files and it appears as expected in the LaTeX output.

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Hyphenation of Compound Words

Compound words are common in mathematical writing and it can be hard to remember how to hyphenate them. Unfortunately, there are no hard and fast rules. In this article I give some guidance and illustrative examples. The principle to keep in mind is that hyphenation should help to avoid ambiguity.

In phrases of the form “adjective noun noun” or “noun adjective/participle noun” a hyphen is usually used: closed-form solution, nineteenth-century mathematics, error-correcting code. But if the adjective follows the noun then no hyphen is needed: solution in closed form, mathematics of the nineteenth century, code that is error correcting. Here are some other examples:

  • nearest-neighbor interpolation,
  • higher-dimensional discrete Fourier transforms,
  • large-scale optimization problem,
  • minimum-norm solution but solution of minimum norm,
  • first-order differential equation but differential equation of first order,
  • the parameter-dependent ODE but the ODE is parameter dependent,
  • rank-1 matrix but the matrix has rank 1.

In examples such as finite-difference method and finite-element method it is a matter of convention and taste whether to hyphenate. Some authors do and some don’t. Most authors do not hyphenate singular value decomposition.

Compounds beginning with adverbs ending in ly are not hyphenated, since they are usually unambiguous. Examples: slowly converging sequence, highly oscillatory integrand, continuously differentiable function, numerically oriented examples.

An important special case is compounds beginning with ill, well, little, much, and best, the first two of which are particularly common in mathematical writing. Here, a hyphen is used for a compound of two words used adjectivally, but if the compound itself is modified then no hyphen is used. Examples (these also apply with ill replaced by well):

  • This is an ill-conditioned problem.
  • This is a very ill conditioned problem.
  • The problem is ill conditioned.
  • This problem is very ill conditioned.

If the first example were to be written as This is an ill conditioned problem then it could be read as if ill were an adjective modifying the compound conditioned problem. Confusion is unlikely in this instance, but in ill-prepared contestant the hyphen is needed unless we are talking about a contestant who is prepared but not well.

Here are two further examples that are complete sentences.

  • MATLAB allows a two-dimensional array to be subscripted as though it were one dimensional.
  • This approach is particularly well-suited to high-precision computation.

The hyphen in well-suited in the last example is not essential, but is rather a matter of taste.

I know from personal experience that it is hard to achieve good, consistent hyphenation when you are concentrating on all the other aspects of writing. This is where having the services of a copy editor is extremely valuable. To benefit, you need to publish with a journal or book publisher that takes copy editing seriously (SIAM, PUP, CUP, OUP, …).

I give the final word to an Oxford University Press style manual, as quoted in the Economist Style Guide:

If you take hyphens seriously, you will surely go mad.

I am indebted to Sam Clark of T&T Productions for checking this post (and for saving me from many hyphenation blunders in my last two books).

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MATLAB Guide, Third Edition (2017)

The third edition of MATLAB Guide, which I co-wrote with Des Higham, has just been published by SIAM. It is a major update of the second edition (2005) to reflect the many changes in MATLAB over the last twelve years, and is 25 percent longer. There are new sections and chapters, and almost every page has changed.

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The new chapters are

  • Object-Oriented Programming: presents an introduction to object-oriented programming in MATLAB through two examples of classes.
  • Graphs: describes the new MATLAB classes graph and digraph for representing and manipulating undirected graphs and directed graphs.
  • Large Data Sets: describes MATLAB features for handling data sets so large that they do not fit into the memory of the computer.
  • The Parallel Computing Toolbox: describes this widely used and increasingly important toolbox.

The chapter The Symbolic Math Toolbox has been revised to reflect the change of the underlying symbolic engine from Maple (at the time of the second edition) to MuPAD.

New sections include Empty Matrices, Matrix Properties, Argument Checking and Parsing, Fine Tuning the Display of Arrays, Live Editor, Unit Tests, String Arrays, Categorical Arrays, Tables and Timetables, and Timing Code.

Two other big changes are that figures are now printed in color and there are thirteen “Asides”, highlighted in gray boxes, which contain discussions of MATLAB-related topics, such as anonymous functions, reproducibility, and color maps.

The book was launched with a reception hosted by The Mathworks and SIAM at the SIAM booth at the Joint Mathematics Meetings in Atlanta on January 6, 2017. Jim Rundquist (Senior Education Technical Evangelist) represented MathWorks, and several SIAM staff, including SIAM Publisher David Marshall, were present.

Two delicious cakes, one containing a representation of the cover of the book, were enjoyed by reception attendees. Inspired by MATLAB, the cakes were served using slice, deal, and input, and an occasional reshape or rotate, with a pool of workers consuming them asynchronously.

170106-1547-18-5574-Edit.jpg

Elizabeth Greenspan (Executive Editor, SIAM), Jim Rundquist (Senior Education Technical Evangelist, The MathWorks), Nick Higham (University of Manchester), Bruce Bailey (Book Marketing Associate, SIAM), and David Marshall (SIAM Publisher).

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Taking Up the SIAM Presidency

I am honored to be taking over the reins from Pam Cook as president of the Society for Industrial and Applied Mathematics (SIAM) for the next two years, starting January 1, 2017. Pam remains as past-president during 2017. I look forward to helping to address the challenges facing SIAM and to working with the excellent SIAM officers and staff.

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SIAM headquarters, Philadelphia.

Eighteen months ago I wrote a “candidate statement” for the fall 2015 SIAM elections. The comments I made then remain valid and so I thought it would be worth reproducing the statement here.

The January/February 2017 issue of SIAM News will contain my first From the SIAM President column, in which I give further thoughts on SIAM’s future.

I am happy to receive comments from SIAM members or potential members, either in the box below or by email.

Candidate Statement: SIAM is the leading international organization for applied mathematics and has been an important part of my professional life since I joined as a PhD student, 31 years ago. SIAM is the first place that many people turn to for publications, conferences, and news about applied mathematics and it represents the profession nationally and internationally.

I have been fortunate to be involved in the leadership for many years, having spent six years on the Council, eight years on the Board, and having recently served two terms as Vice President At Large (2010-2013).

SIAM faces a number of challenges that, if elected as President, I relish helping to address, working with SIAM members, SIAM officers, and the excellent SIAM staff.

SIAM’s publications remain strong, but are vulnerable to changes in the way scholarly journals operate (open access, article processing charges, etc.). SIAM needs to monitor the situation and respond appropriately, while striving to provide an even greater service to authors, referees and editors, for example by better use of web tools.

SIAM’s membership is also healthy, but SIAM must continue to enhance membership benefits and work hard to attract and retain student members, who are the future of the society, and to provide value for its members in industry.

Book sales are declining globally and in academic publishing it is becoming harder to find authors with the time to write a book. Nevertheless, the SIAM book program is in a strong position and the 2015 review of the program that I chaired has produced a list of recommendations that should help it to thrive.

SIAM conferences are a terrific place to learn about the latest developments in the subject, meet SIAM staff, browse SIAM books, and attend a business meeting. Attendances continue to grow (the SIAM CSE meeting in Salt Lake City last March was the largest ever SIAM meeting, with over 1700 attendees), but in any given year, the majority of SIAM’s 14,000 members do not attend a SIAM conference. Audio and slide captures of selected lectures are made available on SIAM Presents, but we need to do more to help members engage in virtual participation.

The SIAM web site has provided sterling service for a number of years, but is in need of a major redesign, which is underway. This is an excellent opportunity to integrate better the many services (conferences, journals, books, membership, activity groups, chapters, sections, etc.) in a responsive design. Beyond the core website, SIAM has a strong social media presence, posts a wide variety of videos on its YouTube channel, hosts SIAM Blogs (which I was involved in setting up in 2013), has recently made SIAM News available online, and has SIAM Connect and SIAM Unwrapped as further outlets. Optimizing the use of all these communication tools will be an ongoing effort.

These are just some of the challenges facing SIAM in the future as it continues to play a global leadership role for applied mathematics.

July 2015

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Numerical Linear Algebra Group 2016

The Manchester Numerical Linear Algebra group (some of whom are in the photo below) was very active in 2016. This post summarizes what we got up to. Publications are not included here, but many of them can be found on MIMS EPrints under the category Numerical Analysis.

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Software

The group has joined Jack Dongarra’s team at the University of Tennessee to become one of the two partners involved in the development of PLASMA: Parallel Linear Algebra Software for Multicore Architectures.

We continue to make our research codes available, which is increasingly done on GitHub; see the repositories of Higham, Relton, Sego, Tisseur, Zhang. We also put MATLAB software on MATLAB Central File Exchange and on our own web sites, e.g., the Rational Krylov Toolbox (RKToolbox).

Several algorithms have been incorporated in other software packages, such as, from Stefan Guettel, the NLEIGS solver which is now part of SLEPc, the Zolotarev quadrature approach which is now part of the FEAST eigenvalue solver package, and rational deferred correction which is now part of pySDC.

PhD Students

After defending her thesis in March 2016, Nataša Strabić (2012-2016) left in May to take up a position as Teacher of Mathematics at Sevenoaks School, Kent.

Bahar Arslan defended her PhD thesis in December 2016.

Mario Berljafa defended his PhD thesis in November 2016. In September he took up a postdoctoral position in the Department of Computer Science at KU Leuven.

Weijian Zhang spent January-February visiting the MIT Computer Science and Artificial Intelligence Laboratory (CSAIL) Lab.

New PhD students Jennifer Lau and Steven Elsworth joined the group in September 2016.

Postdoctoral Research Associates (PDRAs)

Pedro Valero Lara and Mawussi Zounon joined us in January 2016 to work on the Parallel Numerical Linear Algebra for Extreme Scale Systems (NLAFET) project. Sam Relton, who had previously been working on the Functions of Matrices: Theory and Computation project, moved onto this project in March.

Jakub Sistek joined us in March 2016 to work on the Programming Model INTERoperability ToWards Exascale (INTERTWinE) project.

Mary Aprahamian (2011-2016) left in May to take up a position as Data Scientist at Bloom Agency in Leeds.

After several years as PhD student and then PDRA, James Hook left in April to take up a fellowship in the Institute for Mathematical Innovation at the University of Bath.

Prashanth Nadukandi joined the group in September 2016, supported by a Marie Skłodowska-Curie Individual Fellowship.

Timothy Butters (2013-2016), KTP Associate with Sabisu, has taken up a permanent position as Head of Research & Development with the company following the completion of the KTP in December 2016.

Pedro Valero Lara left in October to take up a position as Senior Researcher on the Human Brain project at Barcelona Supercomputer Centre.

David Stevens joined us in December 2016 to work on the Programming Model INTERoperability ToWards Exascale (INTERTWinE) project.

Presentations

Members of the group gave presentations (talks or posters) at the following conferences and workshops.

SIAM UKIE Meeting 2016, January 7, 2016, University of Cambridge, UK: Strabic.

Bath–RAL Numerical Analysis Day, January 11, 2016, Didcot, UK: Guettel.

GAMM Annual Meeting, March 7-11, 2016, Braunschweig, Germany: Guettel

SIAM Conference on Parallel Processing for Scientific Computing, April 12-15, 2016, Paris: Valero Lara, Zhang.

University of Strathclyde SIAM Student Chapter Meeting, Glasgow, May 3, 2016: Higham.

Workshop on Batched, Reproducible, and Reduced Precision BLAS, Innovative Computing Laboratory, University of Tennessee, May 18–19, 2016: Zounon. See the report on the workshop by Sven Hammarling.

ESSAM School on Mathematical Modelling, Numerical Analysis and Scientific Computing, Czech Republic, May 29-June 3, 2016: Sistek.

ECCOMAS Congress 2016, Crete, Greece, June 5-10, 2016: Sistek.

Programs and Algorithms of Numerical Mathematics, Czech Republic June 19-24, 2-16: Sistek.

SIAM Annual Meeting, Boston, USA, July 11-15, 2016: Fasi, Higham, Tisseur, Zemaityte, Zhang.

Fifth IMA Conference on Numerical Linear Algebra and Optimization, University of Birmingham, UK, September 7-9, 2016: Gwynne, Relton, Tisseur, Zounon.

GAMM Workshop on Applied and Numerical Linear Algebra, TU Hamburg–Harburg, Germany. September 15-16, 2016: Guettel

4th Workshop on Sustainable Software for Science: Practice and Experiences (WSSSPE4), University of Manchester, September 12-14, 2016: Relton.

Chebyshev Day, University of Oxford, UK, November 14, 2016: Guettel.

SIAM Annual Student Chapter Conference, University of Warwick, November 23, 2016: Zhang.

Conference and Workshop Organization

The Manchester SIAM Student Chapter organized their 6th Manchester SIAM Student Chapter Conference on May 4, 2016.

Jakub Sistek was one of the organizers of

Françoise Tisseur was on the organizing/scientific committees of

Mario Berljafa, Jonathan Deakin, Nick Higham, Matthew Gwynne, Mante Zemaityte, and Weijian Zhang organized the Manchester Julia Workshop, September 19-20, 2016 at the University of Manchester. Videos of the talks are available on YouTube.

Jakub Sistek and Maksims Abalenkovs were on the organizing committee of the European Exascale Applications Workshop held here in the School of Mathematics, October 11-12, 2016.

Visitors

Vedran Sego visited the group until May 2016.

Peter Kandolf visited the group from September 2015 to March 2016.

Tomáš Gergelits visited the group from October 2015 to March 2016.

Meisam Sharify visited the group in September 2016.

Knowledge Transfer

The three-year Knowledge Transfer Partnership with Sabisu (a data analytics platform for the oil and gas industries), involving KTP Associate Tim Butters, Stefan Guettel, Nick Higham, and Jon Shapiro (School of Computer Science) was completed in December 2016. Among other achievements, an alarm management system has been developed and launched as a product.

Recognition and Service

Françoise Tisseur was elected SIAM Fellow.

Stefan Guettel was elected Secretary/Treasurer of the SIAM UKIE section, 2016–2018, and has also taken on the role of vice-chair of the GAMM Activity Group on Applied and Numerical Linear Algebra. He joined the editorial board of the SIAM Journal on Scientific Computing in January 2016.

Weijian Zhang won a bronze medal in the SET for Britain 2016 competition, which took place at the House of Commons, London, for his poster “Time-Dependent Network Modelling for Mining Scientific Literature”.

SET2016_maths_winners.jpg

Photo from LMS Newsletter. April 2016. (l to r) Dr Stephen Benn (Royal Society of Biology), Sylaja Srinivasan (Bank of England), Professor Nick Woodhouse (Clay Mathematics Institute), Weijian Zhang (Bronze Award Winner), Dr Philip Pearce (Gold Award Winner), Dr Tom Montenegro-Johnson (Silver Award Winner), Professor Sir Adrian Smith (CMS), Stephen Metcalfe MP

Mario Berljafa won a SIAM Student Paper Prize for his work with Stefan Guettel entitled “Generalized Rational Krylov Decompositions with an Application to Rational Approximation”.

A poster “The Math behind Alarm Redundancy Detection” by Mario Berljafa, Massimiliano Fasi, Matthew Gwynne, Goran Malic, Mante Zemaityte, and Weijian Zhang won a prize in SIAM’s “Math Matters” contest and is featured on the Math Matters, Apply It! website.

Nick Higham served as president-elect of SIAM. He was also elected to Academia Europaea.

Weijian Zhang won a SIAM Travel Award to attend the SIAM Conference on Parallel Processing for Scientific Computing in Paris in April 2016.

Mario Berljafa, Massimiliano Fasi and Mante Zemaityte were awarded SIAM Student Travel Awards to attend the SIAM Annual Meeting 2016 in Boston. Weijian Zhang represented the Manchester Student Chapter at the meeting.

Jakub Sistek was re-elected in Februrary as treasurer of the Czech Network for Mathematics in Industry EU-MATHS-IN.CZ.

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New Guidelines for DOI Linking and Display

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For sometime I have been collecting digital object identifiers (DOIs) in my BibTeX entries, as described in this blog post. When I use my own BST file to format the references BibTeX creates hyperlinks to the published source via the DOI. If I use the the SIAM BST file the DOI is instead displayed as part of the reference.

The Crossref organization (which provides DOIs) has recently issued revised guidelines on the display of DOIs. Up until now, DOIs have typically been displayed as, for example, 10.1137/130920137, and linked to as http://dx.doi.org/10.1137/16M1057577. The new guidelines say that the link should be https://doi.org/10.1137/16M1057577 and that it should always be displayed in this form, as a full URL. Note that the “dx” part of the URL has gone, and “https” has replaced “http”.

The main reason for the change is that the pure DOI on its own is not much use, as it can’t be clicked on or pasted into a browser address bar without first adding the https://doi.org/ prefix. Additionally, https provides more secure browsing than http, and Google gives a small ranking boost to sites that use https.

Crossmark states that the old http://dx.doi.org/10.1137/16M1057577 form of URL will continue to work forever.

I have updated my BST file myplain2-doi.bst in this GitHub repository, which contains a BibTeX bibliography for all my outputs, so that it produces links in the required form.

SIAM has updated the BST file in its macro packages to implement the new guidelines.

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Hyphenation Question: Row-wise or Rowwise?

Sam Clark of T&T Productions, the copy editor for the third edition of MATLAB Guide (co-authored with Des Higham and to be published by SIAM in December 2016), recently asked whether we would like to change “row-wise” to “rowwise”.

A search of my hard disk reveals that I have always used the hyphen, probably because I don’t like consecutive w’s. Indeed, in 1999 I published a paper Row-Wise Backward Stable Elimination Methods for the Equality Constrained Least Squares Problem .

A bit more searching found recent SIAM papers containing “rowwise”, so it is clearly acceptable usage to omit the hyphen..

My dictionaries and usage guides don’t provide any guidance as far as I can tell. Here is what some more online searching revealed.

  • The Oxford English Dictionary does not contain either form (in the entry for “row” or elsewhere), but the entry for “column” contains “column-wise” but not “columnwise”.
  • The Google Ngram Viewer shows a great prevalence of the hyphenated form, which was about three time as common as the unhyphenated form in the year 2000.
  • A search for “row-wise” and “rowwise” at google.co.uk finds about 724,000 and 248,00 hits, respectively.
  • A Google Scholar search for “row-wise” and “rowwise” finds 31,600 and 18,900 results, respectively. For each spelling, there are plenty of papers with that form in the title. The top hit for “rowwise” is a 1993 paper The rowwise correlation between two proximity matrices and the partial rowwise correlation, which manages to include the word twice for good measure!

Since the book is about MATLAB, it also seemed appropriate to check how the MATLAB documentation hyphenates the term. I could only find the hyphenated form:

doc flipdim:
When the value of dim is 1, the array is flipped row-wise down

But for columnwise I found that MATLAB R2016b is inconsistent, as the following extracts illustrate, the first being from the documentation for the Symbolic Math Toolbox version of the function.

doc reshape:
The elements are taken column-wise from A ...
Reshape a matrix row-wise by transposing the result.

doc rmmissing:
1 for row-wise (default) | 2 for column-wise

doc flipdim:
When dim is 2, the array is flipped columnwise left to right.

doc unwrap:
If P is a matrix, unwrap operates columnwise.

So what is our conclusion? We’re sticking to “row-wise” because we think it is easier to parse, especially for those whose first language is not English.

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What’s New in MATLAB R2016b

MATLAB R2016b was released in the middle of September 2016. In this post I discuss some of its new features (I will not consider the toolboxes). This is personal selection of highlights; for a complete overview see the Release Notes.

The features below are discussed in greater detail in the third edition of MATLAB Guide, to be published by SIAM in December 2016.

Live Editor

The Live Editor, introduced in R2016a, provides an interactive environment for editing and running MATLAB code. When the code that you enter is executed the results (numerical or graphical) are displayed in the editor. The code is divided into sections that can be evaluated, and subsequently edited and re-evaluated, individually. The Live Editor works with live scripts, which have a .mlx extension. Live scripts can be published (exported) to HTML or PDF. R2016b adds more functionality to the Live Editor, including an improved equation editor and the ability to pan, zoom, and rotate axes in output figures​.

The Live Editor is particularly effective with the Symbolic Math Toolbox, thanks to the rendering of equations in typeset form, as the following image shows.

live-editor1.jpg

The Live Editor is a major development, with significant benefits for teaching and for script-based workflows. No doubt we will see it developed further in future releases.

Implicit Expansion

I have already written about this powerful generalization of the long-standing MATLAB feature of scalar expansion. See this blog post.

Local Functions

Local functions are what used to be called subfunctions: they are functions within functions or, to be more precise, functions that appear after the main function in a function file. What’s new in R2016b is that a script can have local functions. This is a capability I have long wanted. When writing a script I often find that a particular computation or task, such as printing certain statistics, needs to be repeated at several places in the script. Now I can put that code in a local function instead of repeating the code or having to create an external function for it.

String Arrays

MATLAB has always had strings, created with a single quote, as in

s = 'a string'

which sets up a 1-by-8 character vector. A new datatype string has been introduced. A string is an array for which each entry contains a character vector. The syntax

str = string('a string')

sets up a 1-by-1 string array, whereas

str = string({'Boston','Manchester'})

sets up a 1-by-2 string array via a cell array. String arrays are more memory efficient than cell arrays and allow for more flexible handling of strings. They are particularly useful in conjunction with tables. According to this MathWorks video, string arrays “have a multitude of new methods that have been optimized for performance”. At the moment, support for strings across MATLAB is limited and it is inconvenient to have to set up a string array by passing a cell array to the string function. No doubt string arrays will be integrated more seamlessly in future releases.

Tall Arrays

Tall arrays provide a way to work with data that does not fit into memory. Calculations on tall arrays are delayed until a result is explicitly requested with the gather function. MATLAB optimizes the calculations to try to minimize the number of passes through the data. Tall arrays are created with the tall function, which take as argument an array (numeric, string, datetime, or one of several other data types) or a datastore. Many MATLAB functions (but not the linear algebra functions, for example) work the same way with tall arrays as they do with in-memory arrays.

Timetables

Tables were introduced in R2013b. They store tabular data, with columns representing variables of possibly different types. The newly introduced timetable is a table for which each row has an associated date and time, stored in the first column. The timerange function produces a subscript that can be used to select rows corresponding to a particular time interval. These new features make MATLAB an even more powerful tool for data analysis.

Missing Values

MATLAB has new capabilities for dealing with missing values, which are defined according to the data type: NaNs (Not-a-Number) for double and single data, NaTs (Not-a-Time) for datetime data, <undefined> for categorical data, and so on. For example, the function ismissing detects missing data and fillmissing fills in missing data according to one of several rules.

Mac OS Version

I have Mac OS X Version 10.9.5 (Mavericks) on my Mac. Although this OS is not officially supported, R2016b installed without any problem and runs fine. The pre-release versions of R2016a and R2016b would not install on Mavericks, so it seems that compatibility with older operating systems is ensured only for the actual release.

At the time of writing, there are some compatibility problems with Mac OS Version 10.12 (Sierra) for certain settings of Language & Region.

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