Friday, 6 June 2014

rCharts Parcoords x Simpsons x Blocks

Interactive Parallel Coordinates with Multiple Colours

For my research project, I need a tool to visualise results from multi-objective optimisations. Below is one of my early attempts using base R and parcoord in the MASS package, I have no problem using them for publication. However, these charts are all static. For a practical decision support tool (something I am working on), I need the charts to be interactive so that users can adjust the range/thresholds in each parameter and narrow down the things to display in real time.

Many thanks to Ken (timelyportfolio) who kindly pointed me to his code examples. Based on that, I developed a prototype version of the interactive parallel coordinates plot with multiple colours (as shown above). OK, the values in the chart are totally unrelated to my research - I just used the 'Theoph' dataset in R for testing purposes. Yet, this is a much needed exercise to see if I can use rCharts parallel coordinates for my research. The answer, of course, is YES. It also works with my customised colour palette too (using Bart Simpson this time)!

Here is the R code for the above chart:

Showing your rCharts on

In the process of making this plot, I also discovered how to display rCharts (d3, html or practically any code) on Mike Bostock's site "". If you haven't seen his site, do check this out. It is one of the coolest things on earth.

I wanted to have a gallery like that too ... but I didn't know how. I used to think that Ramnath and Ken must have bought Mike a beer so that they can have their stuff hosted on (see and I was very wrong, everyone with a GitHub account can do it. All you need are your imagination (and some gists). The site automatically pulls your gists and displays them as beautiful blocks gallery.

In order to display your cool rCharts on, you can either:
  1. publish the rCharts to gist using the '$publish' function (e.g. r1$publish('name.of.gist', host = 'gist')  where r1 is the rCharts object)
  2. save the rCharts as a stand-alone HTML (e.g. r1$save('index.html', cdn = TRUE)) and then include it in a gist.
For optimal display, I would recommend setting your rCharts size to 960 x 500 (same as the display size on You can also include a '' file and a 'thumbnail.png' to provide more information. I think the best resolution for the thumbnail is 230 x 120 (about the same aspect ratio as full display). You will need to manually push the png file (see this post for more details).

So here are the parallel coodinates plot as shown on ...

... and my gallery at

Latest on Colour Palette Generator

First, let me point you to Russell Dinnage's blog post. It is easily one of the finest R blog posts I've read so far. All these colours and graphs. Wow! It's yet another #RCanDoThat moment for me (so good it needs a hashtag).

So many thanks to his effort and cool ideas, we continue to add more functions to the rPlotter package. It is also a great opportunity for us to better understand the pull/merge GitHub mechanism.


Again, I would like to thank Ken for his help (not only this time but many times before this on visualisation stuff) as well as Ramnath, Mike and Russell.

Tuesday, 27 May 2014

Towards (Yet) Another R Colour Palette Generator. Step One: Quentin Tarantino.


I love colours, I love using colours even more. Unfortunately, I have to admit that I don't understand colours well enough to use them properly. It is the same frustration that I had about one year ago when I first realised that I couldn't plot anything better than the defaults in Excel and Matlab! It was for that very reason, I decided to find a solution and eventually learned R. Still learning it today.

What's wrong with my previous attempts to use colours? Let's look at CrimeMap. The colour choices, when I first created the heatmaps, were entirely based on personal experience. In order to represent danger, I always think of yellow (warning) and red (something just got real). This combination eventually became the default settings.

"Does it mean the same thing when others look at it?"

This question has been bugging me since then. As a temporary solution for CrimeMap, I included controls for users to define their own colour scheme. Below are some examples of crime heatmaps that you can create with CrimeMap.

Personally, I really like this feature. I even marketed this as "highly flexible and customisable - colour it the way you like it!" ... I remember saying something like that during LondonR (and I will probably repeat this during useR later).

Then again, the more colours I can use, the more doubts I have with the default Yellow-Red colour scheme. What do others see in those colours? I need to improve on this! In reality, you have one chance, maybe just a few seconds, to tell your very important key messages and to get attention. You can't ask others to tweak the colours of your data visualisation until they get what it means.

Therefore, I know another learning-by-doing journey is required to better understand the use of colours. Only this time, I already have about a year of experience with R under my belt, I decided to capture all the references, thinking and code in one R package.

Existing Tools

Given my poor background in colours, a bit of research on what's available is needed. So far I have found the following. Please suggest other options if you think I should be made aware of (thanks!). I am sure this list will grow as I continue to explore more options.

Online Palette Generator with API

Key R Packages

  • RColorBrewer by Erich Neuwirth - been using this since very first days
  • colorRamps by Tim Keitt - another package that I have been using for a long time
  • colorspace by Ross Ihaka et al. - important package for HCL colours
  • colortools by Gaston Sanchez - for HSV colours
  • munsell by Charlotte Wickham - very useful for exploring and using Munsell colour systems

Funky R Packages and Posts:

Other Languages:

The Plan

"In order to learning something new, find an interesting problem and dive into it!" - This is roughly what Sebastian Thrun said during "Introduction to A.I.", the very first MOOC I participated. It has a really deep impact on me and it has been my motto since then. Fun is key. This project is no exception but I do intend to achieve a bit more this time. Algorithmically, the goal of this mini project can be represented as code below:

>"my.colours") & is.informative("my.colours")

Seriously speaking, based on the tools and packages mentioned above, I would like to develop a new R package that does the following five tasks. Effectively, these should translate into five key functions (plus a sixth one as a wrapper that goes through all steps in one go).
  1. Extracting colours from images (local or online).
  2. Selecting and (adjusting if needed) colours with web design and colour blindness in mind.
  3. Arranging colours based on colour theory.
  4. Evaluating the aesthetic of a palette systematically (quantifying beauty).
  5. Sharing the palette with friends easily (think the publish( ) and load_gist( ) functions in Shiny, rCharts etc).
I decided to start experimenting with colourful movie posters, especially those from Quentin Tarantino. I love his movies but I also understand that those movies might be offensive to some. That is not my intention here as I just want to bring out the colours. If these examples somehow offend you, please accept my apologies in advance.

First function - rPlotter :: extract_colours( )

The first step is to extract colours from an image. This function is based on dsparks' k-means palettle gist. I modified it slightly to include the excellent EBImage package for easy image processing. For now, I am including this function with my rPlotter package (a package with functions that make plotting in R easier - still in early development).

Note that this is the very first step of the whole process. This function ONLY extracts colours and then returns the colours in simple alphabetical order (of the hex code). The following examples further illustrate why a simple extraction alone is not good enough.

Example One - R Logo

Let's start with the classic R logo.

So three-colour palette looks OK. The colours are less distinctive when we have five colours. For the seven-colour palette, I cannot tell the difference between colours (3) and (5). This example shows that additional processing is needed to rearrange and adjust the colours, especially when you're trying to create a many-colour palette for proper web design and publication.

Example Two - Kill Bill

What does Quentin_Tarantino see in Yellow and Red?

Actually the results are not too bad (at least I can tell the differences).

Example Three - Palette Tarantino

OK, how about a palette set based on some of his movies?

I know more work is needed but for now I am quite happy playing with this.

Example Four - Palette Simpsons

Don't ask why, ask why not ...

I am loving it!

Going Forward

So the above examples show my initial experiments with colours. It will be, to me, a very interesting and useful project in long-term. I look forward to making some sports related data viz when the package reaches a stable version.

The next function in development will be "select_colours()". This will be based on further study on colour theory and other factors like colour blindness. I hope to develop a function that automatically picks the best possible combination of original colours (or adjusts them slightly only if necessary). Once developed, a blog post will follow. Please feel free to fork rPlotter and suggest new functions.

useR! 2014

If you're going to useR! this year, please do come and say hi during the poster session. I will be presenting a poster on the crime maps projects. We can have a chat on CrimeMap, rCrimemap, this colour palette project or any interesting open-source projects.


I would like to thank Karthik Ram for developing and sharing the wesanderson package in the first place. I asked him if I could add some more colours to it and he came back with some suggestions. The conversation was followed by some more interesting tweets from Russell Dinnage and Noam Ross. Thank you all!

I would also like to thank Roland Kuhn for showing how to embed individual files of a gist. This is the first time I embed code here properly.

Tweets are the easiest way for me to discuss R these days. Any feedback or suggestion,

Friday, 21 March 2014

Updates on Interactive rCrimemap, rBlocks ... and the Packt offer!

Testing rCrimemap as a Self-Contained Web Page

I've been learning more about rMaps and rCharts since the LondonR meeting. There are many amazing things you can do with rCharts but it does take time to learn all the tweaks. For example, I just discovered that the rMaps objects (like other rCharts ojects) can be saved as a self-contained webpage.

So here are the links to one of the maps I rendered with rCrimemap - visualising all the England, Wales and N. Ireland crimes in Jan 2014 (not sure why some of the crimes were recorded in Scotland - I'll need to further investigate this later). Eventually, I hope to build a new Shiny web app for rCrimemap that allows users to change the settings like the original CrimeMap.

Note: I would recommend NOT to try this on smartphones. I will need to figure out how the map can be trimmed and optimised for smartphones later.

Yet Another rBlocks Experiment

Playing with the EBImage package this time, I wrote this script to pixelate a picture and re-colour it with rBlocks (just for fun - not practical at all ...) (Gist - rBlocks_test_04_pixelation.R)

Celebrating Packt's 2000th Book

Finally, Packt is offering "Buy One Get One Free" on all ebooks to celebrate the 2000th title!!!

Wednesday, 19 March 2014

The #rBlocks Experiments

What's this ?

Conway's Game of Life Animated using #rstats #rBlocks #a... on Twitpic

Where should I start? OK, the story goes like this ...

What's next? Let's go crazy with colours ... (to be continued)

Wednesday, 12 March 2014

Slidify my R journey from @matlabulous to rCrimemap

My LondonR Talk

Thanks to Mango Solutions (LondonR organiser), I was given the opportunity last night to talk about my mini project ‘CrimeMap’Instead of going through all the technical details behind the scenes, I chose to talk the audience through my R journey from a noob to a heavy user. CrimeMap was used as a case study to show how ones can benefit from learning R (or, in some ways, trying to justify the time I spent staring at RStudio IDE last year). The feedback was really great and the talk effectively expanded my network in the data science community so I am really grateful for that! You can find my presentation here.

Before the main event, there was an excellent R-Python workshop by Chris Musselle. The other two interesting presentations were "Dynamic Report Generation" by Kate Hanley and "Customer Clustering for Retail Marketing" by Jon Sedar. Their presentations will soon be made available here.

CrimeMap - A Wonderful Learning Experience

When I first started learning R for real, the goal was very simple - "let's plot something pretty with ggplot2". Well, a lot has changed since then. The more I learned, the more I discovered. It is really hard to summarise the 'R' awesomeness in a few slides due to its diversity. One thing I am absolutely certain is that I made the right move about a year ago to shift from MATLAB to R. Yet, I am keeping my twitter account name @matlabulous just to remind myself that ones should always keep an open mind for new and evolving technology (... and should avoid getting a tattoo of your potential ex-gf/bf's name. On that note, no, I don't have a tattoo.For more information about the CrimeMap, please see my previous posts here, here and here.

Using Slidify for Professional Presentation

The talk was also the first time I presented something totally unrelated to water engineering. I thought, for a change, let’s try something different. Then I remembered looking at the Slidify slides from Jeff Leek’s Data Analysis course back in Jan-March last year. I thought that would fit perfectly for LondonR because the whole presentation would be coded completely in R. It would be a good reason to learn Slidify too. So I went through the Slidify examples, put some slides together, tweaked the CSS a little bit and then published it to GitHub – a streamline Slidify workflow well thought and designed by Ramnath Vaidyanathan. To me, the results are amazing! So amazing that I am confident to leave PowerPoint and use Slidify for professional presentations in the future.

rMaps + CrimeMap = rCrimemap

Two weeks before the presentation, I wrote an email to Ramnath as I wanted to thank him for Slidify. I told him how I enjoyed using Slidify for the LondonR slides. Out of the blue, Ramnath told me that he had seen my CrimeMap already and he kindly pointed me to this blog post about using Leaflet heat map in rMaps. I thought, OMG, why now? Then I thought, yeah, why not? So I created a new package called ‘rCrimemap’ based on Ramnath’s example and the codes from the CrimeMap project – just in time for the LondonR meeting. At first, I wanted to called the package something different but eventually I chose rCrimemap so it aligns well with Ramnath’s rCharts and rMaps.

Using ‘rCrimemap’

rCrimemap is still raw and experimental. It depends on some new packages such as dplyr, dev version of rCharts and rMaps etc. I have only developed and tested it recently on Linux. Please give it a try if you have a chance. All feedback and suggestions are welcome. Codes are here.

To install it, you will need the RStudio IDE version 0.98.501 or newer and the following packages ...

install.packages(c("base64enc", "ggmap", "rjson", "dplyr"))

After that, install rCrimemap package via ... 


rCrimemap is basically a big wrapper function. In fact, there is only one function 'rcmap( )' in the package at the moment. (OK, it is obviously an overkill ... but I really wanted to try developing a package.) The function is very similar to the first one I did for CrimeMap prior to the Shiny development. In terms of graphical functionality, it is not as flexible as the CrimeMap yet (for example, CrimeMap can do all these colours and facet). However, it is much more powerful than CrimeMap in the sense that users can move around, zoom in and out like using a real digital map. The colour of the heat map also changes when you zoom in/out. This gives users a much better visibility of where the local crime hot spots are when they zoom in. OK, enough said, let’s go through some example usage …

The arguments of the function 'rcmap( )' are:
  1. location: point of interest within England, Wales and Northern Ireland
  2. period: a month between Dec 2010 and Jan 2014 (in the format of yyyy-mm)
  3. type: category of crime (e.g. "All", "Anti-social behaviour")
  4. map_size: the resolution of the map in pixel (e.g. Full HD = c(1920, 1080))
  5. provider: the base map provider (e.g. "Nokia.normalDay", "MapQuestOpen.OSM")
  6. zoom: zoom level of the map (e.g. I recommend starting with 10 to show all the crimes)

Example 1: “Ball Brothers EC3R 7PP” (LondonR venue since March 2013) during the London riot (Aug 2011). The map can be viewed within RStudio IDE or be exported to a browser. The animation was created outside R (Oh ... what if rCrimemap + animation package? ... I will leave that for later.)

rcmap("Ball Brothers EC3R 7PP", "2011-08", "All", c(1000,1000),"Nokia.normalDay")

Example 2: Manchester in Jan 2014 - using "MapQuestOpen.OSM" as base map instead.

rcmap("Manchester", "2014-01", "All", c(1000,1000), "MapQuestOpen.OSM")


There you go, enjoy :)

Wednesday, 22 January 2014

CrimeMap, LondonR and a Book Review

In preparation for my LondonR talk in March, I am polishing up my CrimeMap (see previous blog post here and here) in my spare time.

Thanks to Chris Beeley and Packt, I won a free e-copy of Chris Beeley’s book following his great talk about Shiny web app during the last LondonR meeting. I find this book really useful as I am trying to implement new functionality and ideas into my CrimeMap. It illustrates very well what you can do with Shiny using lots of practical examples. So here is a quick book review for those who are also interested in developing Shiny web apps.

The book begins with a short but essential introduction to some key R functions for handling data and graphics. Chapter 2 is a walk-through of key Shiny components nicely demonstrated by an example of Google Analytics API integration. It then discusses how Shiny can be further extended with the use of HTML, CSS, JavaScript and jQuery. I find chapter 4 most useful as it goes deep into the practical aspects of handling reactivity and taking full control of inputs and outputs. The book ends with some tips on code sharing and browser compatibility.

I hope you will find this short review useful. Reviews from others can be found here, here and here

BTW, LondonR is great (thank you very much Mango Solutions for sponsoring it since 2009)!!! You can find the presentations from previous meetings here.

Wednesday, 4 December 2013

A Recap of the Last Couple Months (Part 1)

It's been a while. I know. I had hoped to finish this a lot earlier and to make my regular contributions to the Stream's Stream. Oh well ... better late than never :)

STREAM Challenge Week (Morpeth, 7-12 July)

Back in July, (nearly) all research engineers from STREAM spent a couple days in Morpeth together. I am only going to show you some photos here. You can find out more about the event from my fellow STREAM-ers Jack Bloodworth and Sarah Cotterill.

Kielder Water and Forest Park
Walking around Morpeth
Carlisle Park - It's Picnic Time!
The Beautiful Morpeth Stepping Stones
STREAM Conference at Newcastle University
Inter-Cohort Rounders' Championship Tournament
Group Presentations for the Morpeth Flooding Challenge 
Dinner and Awards Presentation
STREAM Group Photo at Longhirst Hall

35th IAHR World Congress (Chengdu, 8-13 September)

For the very first time, I travelled back to my home country for work. After a rather busy 2012, I cut down significantly on travel and conferences this year. This conference was my only international duty (well, excluding the Institute of Water Annual Conference in Edinburgh which I travelled from England to Scotland) this year. The IAHR conference was definitely one of the biggest conferences I had ever been to with over 1400 attendances gathering in the Chengdu Century City International Convention Center.

On the first day of conference, I met with XP Solutions' distributor in China - Ewaters. We discussed some potential case studies based on projects in China and agreed on the dates for the post-conference software workshops in Shanghai.

Opening Ceremony. Looking at the back of Professors Dawei Han and Dragan Savic (my past and current supervisor) - what are the chances?

After the technical sessions in the afternoon, we were all invited to join Prof. Roger Falconer (IAHR President) for the president's reception where he welcomed everyone to the congress. It was a very interesting and entertaining evening with stunning face-changing performance by the local Sichuanese opera.

IAHR President's Reception at Shunxing Teahouse

On the third day, I had chosen to visit the Dujiangyan Irrigation Project for the in-congress technical tour. It is one of the oldest irrigation systems in the world and an excellent example of ancient Chinese science and engineering. The project has successfully prevented flooding in Chengdu ever since its completion about 2200 years ago. Simply astonishing!

In-Congress Technical Tour - Dujianyan Irrigation Project
Congress Dinner

On a more serious note, I suited up and delivered a presentation on the last day of the conference. The presentation was a summary of my progress so far and a prologue to the post-conference software workshops. It generated some interests from the Hong Kong Drainage Services Department's representatives. Afterwards, we discussed the possibilities of applying my work in Hong Kong and they had kindly invited me to attend their conference in Hong Kong next year.

As usual, flooding the crowd with colourful visuals.

After the conference, I had a short window to explore the city. (Making the most of it - right, Sarah?)

Wu Hou Shrine Museum
Jin Li, The Ancient Chinese Machine Gun and the Inevitable Invasion of Starbucks
Chengdu at night - Tianfu Square (a Yin Yang from above!)

Overall, I think the IAHR conference was an invaluable experience for me. It allowed me to connect with the people there and to gain a much better understanding of the situation, challenges and needs in China - which means a lot to me as it is my home country. I would also like to thank STREAM and my supervisor Dragan for giving me the opportunities to attend different conferences in last couple years.

Next Stop: Shanghai

XPDRAINAGE workshops in Shanghai and life after the China trip. Watch this space!