GMapsFX 2.12.0 Released – Mac OSX Garbled Text Fixed!

The latest version of GMapsFX has been released and includes a major bug fix and a few enhancements.

Bug Fix

Last month I reported a bug that has been affecting users of GMapsFX on Mac OSX where the text appeared ‘garbled’.  An example image is below.
Screen Shot 2017-03-29 at 2.15.45 PM

The underlying issue is that the JavaFx WebView component on Mac OSX is rendering icons rather than letters for some websites, including Google Maps.

I receive a tweet from @ggeorgopoulos1 with a proposed work around that involves injecting CSS programatically into the page with the correct font.  I’ve incorporated the code into the latest GMapsFX library and I am happy to say that it is working once again on Mac OSX!

 

Screen Shot 2016-03-18 at 3.40.46 PM


Enhancements

Added a setKey() method to the GoogleMap compoment

This will allow a key to be set in the FXML and will eliminate the need to programatically set a key on the map object at runtime.

 

Support for Clustered Markers

Added ability to cluster markers by utilizing the Google Maps Marker Clustering API.  https://developers.google.com/maps/documentation/javascript/marker-clustering

clusteredMarkers

Ability to Set Route Colors

Route colors can now be specified rather than having to rely on the default blue that Google Maps uses.

ColorRoute

 

 

Garbled Text in GMapsFX on Mac OSX

 

I have been receiving a lot of messages the last couple of months regarding the text in GMapsFX applications looking “garbled”, as illustrated in the screenshot below.

 

Screen Shot 2017-03-29 at 2.15.45 PM

 

This is appears to only affect applications running on Mac OSX.  GMapsFX makes use of the JavaFX WebView component under the hood, so I created a simple test app that loads Google Maps into a WebView to confirm the issue was the WebView component.

Screen Shot 2017-03-01 at 5.09.09 PM.png

I filed a bug report with Oracle, but apparently this is a known issue that affects only some websites in WebView on Mac. Linux and Windows applications using the WebView component are unaffected.

http://bugs.java.com/bugdatabase/view_bug.do?bug_id=JDK-8088205

The issue has been open for a couple of years now which leads me to think that a recent Mac update may be contributing to the problem becoming more widespread.

Unfortunately a fix for this won’t be available until Java 9, and there is no work around that I know of.

 

 

Get the Lat/Long of a Mouse Click in a GMapsFX Map

A new API has been created for mouse events in the GMapsFX API which will begin to make it easier to obtain information about mouse events occurring within the Google Map without having to interact with the underlying Javascript API.

So now getting the Lat/Long of a mouse click is a relatively straightforward process.

We tell the map we want to add a click UI event listener and pass in an event handler which handles a GMapMouseEvent event object.  From that object the latitude and longitude of the event can be determined.

Currently the Lat/Long are the only properties available on the GMapMouseEvent object, but additional properties will be added as demand warrants.

Below is a screenshot of one of the example applications included with the GMapsFX project that illustrates how to capture the lat/long of a mouse click.

 

latlongscreenshot.png

 

Help! How do I Ship my Freight? Ask the Machine.

Problem: Lynden, Inc. a freight and logistics company owns a number of operating companies that ship via different modes of transport (air, truck, sea), and also specialize in shipping different types of commodities.  How do I, as a customer know which Lynden company to call if I want to have something shipped? Below is a table of a few of our operating companies, with the company abbreviation (referenced later in this post), and how each company moves their freight.

 

Company Abbreviation Mode of Transport
Alaska Marine Lines AML Sea
Lynden International LINT Air
Lynden Air Cargo LAC Air
Alaska West Express AWE Truck
Lynden Transport LTIA Truck
LTI, Inc. LTII Truck

Currently there is a single number that a customer can call to get directed to the appropriate company that can move the freight.  However this has proved to be a somewhat error prone process as there are a number of exception cases that can dictate which company can move the freight, such as is it oversized, or hazmat.

I wanted to see if we could gain any insight to this problem by looking at our historical shipments and possibly use various attributes about a shipment itselfto make an accurate recommendation as to which company to call.  This boils down to a classification problem, ie how do we classify the company that ships the freight based on attributes that the customer tells us about their freight?  Classification problems are one of the areas where machine learning has been applied extensively over the last few years.

There are dozens and dozens of attributes related to our shipments which could be used to feed into a machine learning model, but to keep things simple for this experiment I chose to use the freight description field. If the customer could give a description of their freight to a predictive model, could it properly suggest which company should ship it?  The exercise would be to see if there was any predictive power at all with the description field, and if so, additional fields could potentially be added to refine the model further.

I obtained data from 50,000 historical shipments which included a short description of the goods being shipped and the abbreviation of the company that shipped the goods.  I imported this data into R Studio for analysis.

data

 

There are a number of different machine learning models to choose from for classification problems.  I selected the Naive Bayes model which is the same model that most spam filters use to classify email  as spam based on the words within the email.

Out of curiosity I decided to use R to create a word cloud of common terms for a few of the companies just to see what pops out.   The first cloud below is common words found in the descriptions of freight shipped with Alaska Marine Lines (AML).

amlplot

 

The word cloud below was generated for freight shipped with Lynden International (LINT).
lintplot

Finally, the last cloud is for freight that was shipped with LTI, Inc. (LTII), with an interesting combination of commodities which were returned.  Hopefully the same tankers that are being used to ship sulfur are also not being used to ship wine!
ltiiplot

Next it was time to train the model.  I took 40,000 of the records and submitted it to a Naive Bayes model that I had configured in R.  This would give the model a chance to look at the terms in each shipment, and associate it with the company that shipped the freight, hopefully finding commonalities that it could use when it needed to predict the company based on the description.

I then took the remaining 10,000 records and had the model guess which company shipped the goods based solely on the freight description.  I then tabulated the accuracy of the model’s 10,000 predictions.

The table below illustrates what percent of the time the model selected the correct company given the description of the freight.

  • AML:  95%
  • AWE:  94%
  • LTII:   94%
  • LTIA:  83%
  • LAC:   52%

I was quite surprised by the accuracy of the results given that just one attribute of the shipment data was being used by the model.  LAC is the big outlier, and freight that should have been classified as LAC was most commonly misclassified as LINT.  Likewise freight that should have been classified as LTIA was most commonly misclassified as AML.

The next step would be to take a look at some of the other attributes of the freight and see if we can further refine the model, by possibly using fields such as origin, destination, weight, etc.

If you are curious about the R code that I wrote to perform this experiment I have included it below.

 

Why You Shouldn’t Use Complex Objects as HashMap Keys

I’m a big believer in learning from my mistakes, but I’m an even bigger believer in learning from other people’s mistakes.  Hopefully someone else will be able to learn from my mistakes.

mistakes

 

This post is inspired by an issue that took me a number of days to track down and pin point the root cause.  It started with NullPointerExceptions randomly be thrown in one of my applications.  I wasn’t able to consistently replicate the issue, so I added an indiscriminate amount of logging to the code to see if I could track down what was going on.

What I found was that when I was attempting to pull a value out of a particular hashmap, the value would sometimes be Null, which was a bit puzzling because after initializing the map with the keys/values, there were no more calls to put(), only calls to get(), so there should have been no opportunity to put a null value in the map.

Below is a code snippet similar (but far more concise) to the one I had been working on.

There is a ProductSummaryBean with a short summary of the product, and a ProductDetailBean with further product details.  The summary bean is below and contains four properties.

 

Any guesses what happens when the code above is run?

Exception in thread "main" java.lang.NullPointerException
 at com.lynden.mapdemo.TestClass.runTest(TestClass.java:34)
 at com.lynden.mapdemo.TestClass.main(TestClass.java:50)

 

So what happened?  The HashMap stores its keys by using the hashcode of the key objects.  If we print out the hashcode when the ProductSummaryBean is first created and also after its read out of the DB we get the following.

SummaryBean hashcode before: -298224643
SummaryBean hashcode after: -298224679

 

We  can see that the hashcode before and after are different, so there must be something different about the two objects.

SummaryBean before: ProductBean{priceFormatter=java.text.DecimalFormat@67500, price=19.95, name=MyWidget, upcCode=Z332332}
SummaryBean after: ProductBean{priceFormatter=java.text.DecimalFormat@674dc, price=19.95, name=MyWidget, upcCode=Z332332}

 

Printing out the entire objects shows that while name, upc code, and price are all the same, the DecimalFormatter used for the price is different.  Since the DecimalFormatter is part of the hashcode() calculation for the ProductSummaryBean, the hashcodes between the before and after versions of the bean turned out different.  Since the hashcode was modified, the map was not able to find the corresponding ProductDetailBean which in turned caused the NullPointerException.

Now one may ask, should the DecimalFormat object in the bean been used as part of the equals() and hashcode() calculations?  In this case, probably not, but this may not be true in your case.  The safer way to go for the hashmap key would be to have used the product’s upc code as the HashMap key to avoid the danger of the keys changing unexpectedly.

 

 

 

 

 

How to Import the GMapsFX Component into SceneBuilder

I recently received a question regarding how to add the GMapsFX component to SceneBuilder, so it could be dragged and dropped onto the UI as its being constructed.

I thought I would address the question here since the good folks at Gluon have made it extremely easy to import custom components to SceneBuilder.

The first step is to click the small ‘gear’ icon just to the right of the Library search box and select the “JAR/FXML Manager” menu item from the popup menu.

screen-shot-2016-09-30-at-2-49-38-pm

 

 

Since the GMapsFX binaries are in the Maven Central repository SceneBuilder can directly download and install the component from there.  Click the “Search repository” link in the Library Manager dialog box.

screen-shot-2016-09-30-at-2-52-03-pm

 

Next, enter “GMapsFX” into the Group or artifact ID text box, and click the “Search” button.  You should get a search result with the com.lynden:GMapsFX artifact. Select the result and click “Add JAR”.

screen-shot-2016-09-30-at-2-52-24-pm

 

The GoogleMapView should be the only component available in the Jar file, select it and click the “Import Component” button.

screen-shot-2016-09-30-at-2-52-33-pm

 

Finally, you should get a confirmation that the library was imported into SceneBuilder.

screen-shot-2016-09-30-at-2-52-41-pm

 

At this point the GoogleMapView component should be visible in the “Custom” component section of the pallette, and ready to be dragged and dropped onto your UI.  Due to the way the component is constructed, a map will not display in SceneBuilder or the SceneBuilder preview tool, but the proper FXML will be generated and the map will display when the program is run.

screen-shot-2016-09-30-at-2-52-50-pm

 

Feel free to tweet me at:  @RobTerpilowski with any questions.

 

GMapsFX 2.0.5 Released

GMapsFX 2.0.5 has been released and is now available via bintray and maven central.

This version contains a major bugfix where the directions pane was always enabled.  The framework has been updated to make the direction pane an option that can be toggled on or off at runtime as it is needed.

GMapsFX is a Java library that makes it extremely easy to add a Google Map to a JavaFX application.

 

<dependency> 
  <groupId>com.lynden</groupId> 
  <artifactId>GMapsFX</artifactId> 
  <version>2.0.5</version> 
  <type>pom</type> 
</dependency>

 

GMaps Home: http://rterp.github.io/GMapsFX/
twitter: @RobTerpilowski