Mathias Brandewinder on .NET, F#, VSTO and Excel development, and quantitative analysis / machine learning.
by Mathias 24. July 2010 17:35

When I moved to California a few years back, I soon realized that to get anything done in the Silicon Valley, you pretty much have to have a car. So, I purchased my first car. Fast forward today: I live in San Francisco now, and noticed that I am driving less and less. Bicycle is very convenient in my neighborhood, and I don’t have to commute to work on a daily basis. Which got me thinking – do I really need a car? Public transportation only is not an option, because coverage is too spotty, but what about using a car sharing service?

The 2 major services available in my area are ZipCar and CityCarShare; their pricing system is largely similar: they both:

  • charge by the hour of usage,
  • charge a higher cost over the week-end,
  • offer a discount for full-day rental,
  • have a pay-as-you-go option, and better rates with minimum commitment plans.

Both include gas, with one difference: ZipCar charges by the hour, whereas CityCarShare has a hybrid pricing, with a lower per-hour cost, and a per-mile cost.

By contrast, when you own a car, you

  • pay a large upfront investment (buying the car),
  • recoup some of the upfront cost if you resell eventually.
  • pay regular fixed costs (insurance, registration taxes, garage),
  • pay by the mile (gas),
  • pay some additional costs, like maintenance, which are somewhat linked to mileage.

In addition to that, you bear the risk that your car gets damaged or totaled in an accident.

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by Mathias 15. July 2010 12:14

Time to wrap this series on VSTO add-ins for Excel 2007. Now that we have a working application-level add-in, we want to deploy it on the user machine. There are two ways to do that: ClickOnce and Windows Installer. In this post, I will go over creating a basic installer using Windows installer with Visual Studio 2008. Very soon, we’ll have a VIP guest blogger who will tell you all you need to know about ClickOnce deployment and VSTO.

This post borrows heavily from the Microsoft white paper linked below, which is absolutely excellent. I mostly paraphrased it, focusing on the how and not the why. I strongly encourage you to go to the source and read it for more details:

Deploying a VSTO 3.0 Solution for Office 2007 System Using Windows Installer

The white paper comes with sample code, covering a few scenarios:

VSTO installer sample code 

Note: the following applies to Office 2007 projects. If your add-in needs to run on Excel 2003, you should follow this guidance instead: Deploying VSTO Solutions Using Windows Installer (Part 2 of 2)

Surgeon General Warning: prolonged reading of material pertaining to msi deployment can cause drowsiness or confusion; absolutely no risk whatsoever of euphoria is to be expected.

This post is not going to be sexy. My goal is to have a check-list of what to do to get your add-in to install correctly. The steps require no thinking, and are frankly rather boring. I find some steps pretty obscure, and recommend patience and soothing music; you may consider also having  some sacrificial offering ready to appease the Great Installer Voodoo deity (a nice chicken will usually do). 

Prepare the add-in

We will start from where we left off, with a working add-in (download the add-in here). Let’s first fill in the fields describing our assembly, by right-clicking on the project:

ClearLines.Anakin > Properties > Application > Assembly information:

AssemblyInfo

Next, let’s set the configuration to Release, so that we feed the optimized release version to the installer. Right-click on the Solution (not the add-in project), select Configuration Manager, and set ClearLines.Anakin to Release instead of Debug.

ReleaseMode

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by Mathias 13. July 2010 14:45

Found on Epic Win FTW – The Sparklines of Excel 2010 are cool, but this is an Epic Win indeed. Pretty amazing, and another shining example of how Excel is used for lots of purposes, some of them probably never considered by Microsoft :)

MarioExcel

by Mathias 8. July 2010 11:03

A new method of forecasting has been brought to my attention: Paul. Paul is an English-born octopus, currently living in Germany, and has been predicting with high accuracy the results of the German soccer team, by picking between two boxes marked with the flag of the two competing teams:

How unlikely is it that Paul would have such a string of correct forecasts? Pretty unlikely. If you assume that Paul’s picks were completely random, with a 50% chance of correctly calling the winner, the probability of making 11 good calls out of 12 comes down to 0.29%. Does this mean Paul is the next big thing in forecasting? It’s possible, but I don’t think so (this said with all due respect to Paul and his skills). Leonard Mlodinow, in his excellent book, The Drunkard's Walk, makes the following comment:

This example illustrates an important point: even with data significant at, say, the 3 percent level, if you test 100 nonpsychic people for psychic abilities […], you ought to expect a few people to show up as psychic.

Mallarme In other words, if a phenomenon is random, you should typically see the “average” case regularly, but you should also see highly unlikely cases happen from time to time – observing such a rare occurrence doesn’t contradict the randomness of the phenomenon. Or, in the words of the French poet Mallarmé, Un Coup de Dés Jamais N'Abolira Le Hasard (A throw of the Dice will Never Abolish Chance).

by Mathias 5. July 2010 16:16

In our last post, we saw how to use F# to read historical stock quotes from Yahoo. Today we’ll take the raw response, which is a big block of text, and break it up into a list of individual quotes.

Breaking up the response into lines

The function we wrote last time, GetResponse, receives one chunk of text from the web service, formatted like this:


Date,Open,High,Low,Close,Volume,Adj Close
2010-03-08,28.52,28.93,28.50,28.63,39414500,28.50
2010-03-05,28.66,28.68,28.42,28.59,56001800,28.46
2010-03-04,28.46,28.65,28.27,28.63,42890600,28.50

What we need to do now is break up this into individual lines of text, and parse them to read individual quotes. The first part is straightforward: the function BreakIntoLines calls String.Split(), using char(10), the code for line break, as a delimiter, and returns an Array of strings.

let BreakIntoLines (response:string) =
  response.Split((char)10)

Note the type annotation on the function argument: without context, F# cannot infer the type of “response”, and we need to specify that this function expects a string argument.

Parsing valid lines into Quote records

The second part is a bit more complex. We need to break each line into 7 components (date, open, etc…), deal with lines that are not valid, like the header, and store the result in an appropriate structure.

We will store individual quotes into records. A Record is a data type somewhat similar to the C# struct. It has named fields, which makes it more expressive than Tuples, and is less involved than a class. Here is the declaration for our Quote record – concise, and pretty self-explanatory:

type Quote={
  Symbol:string;
  Date:DateTime;
  Open:double;
  Close:double;
  Low:double;
  High:double;
  Volume:int64}

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