{"id":8505,"date":"2017-04-07T09:00:50","date_gmt":"2017-04-07T13:00:50","guid":{"rendered":"https:\/\/blogs.mathworks.com\/pick\/?p=8505"},"modified":"2017-08-27T20:06:15","modified_gmt":"2017-08-28T00:06:15","slug":"r2017a-heatmap","status":"publish","type":"post","link":"https:\/\/blogs.mathworks.com\/pick\/2017\/04\/07\/r2017a-heatmap\/","title":{"rendered":"R2017a: heatmap"},"content":{"rendered":"\r\n

Jiro<\/a>‘s pick this week is the new heatmap<\/tt><\/a> function introduced in R2017a.<\/p>

Last month, a new release of MATLAB (R2017a) came out with many new features<\/a>. Of those, I’d like to highlight heatmap<\/tt><\/a>, which over the years had predecessors<\/a> created by the user community.<\/p>

Meet heatmap<\/tt><\/b><\/p>

Heatmap charts display data as an image where each element is represented by a color. The value of the element is also displayed on the image. As a simple example, let’s visualize a magic square<\/a>.<\/p>

m = magic(15);\r\nheatmap(m);\r\n<\/pre>\"\" 
You can imagine that if the size of the matrix is large, or if the figure is resized to a small window, the image can quickly become crowded with a lot of text. No need to worry. The heatmap intelligently turns off the text display when it makes sense to do so.<\/p>
set(gcf,'Position'<\/span>,[100 100 400 350])\r\n<\/pre>\"\" 
heatmap<\/tt> returns a HeatmapChart<\/tt> object, which you can use to customize.<\/p>
figure\r\nhMap = heatmap(m);\r\nhMap.ColorbarVisible = 'off'<\/span>;\r\nhMap.CellLabelColor = 'red'<\/span>;\r\nhMap.GridVisible = 'off'<\/span>;\r\n<\/pre>\"\" 
For example, if we have a table of data for 100 people with information about whether they smoke and their self-assessed health status, we can group them into the various categories and visualize as a heatmap.<\/p>
load patients<\/span>\r\ntbl = table(Age,Gender,SelfAssessedHealthStatus,Smoker,Weight,Location);\r\nheatmap(tbl,'Smoker'<\/span>,'SelfAssessedHealthStatus'<\/span>);\r\n<\/pre>\"\" 
Instead of showing the aggregated count, we can choose to display the average age for each category.<\/p>
heatmap(tbl,'Smoker'<\/span>,'SelfAssessedHealthStatus'<\/span>, ...<\/span>\r\n    'ColorVariable'<\/span>,'Age'<\/span>);\r\n<\/pre>\"\" 
Or the median weight.<\/p>
heatmap(tbl,'Smoker'<\/span>,'SelfAssessedHealthStatus'<\/span>, ...<\/span>\r\n    'ColorVariable'<\/span>,'Weight'<\/span>,'ColorMethod'<\/span>,'median'<\/span>);\r\n<\/pre>\"\" 
For Previous Releases<\/b><\/p>
If you haven’t upgraded or cannot upgrade to R2017a, you can check out some of the user-submitted entries<\/a>. One of my favorites is Customizable Heat Maps<\/a> by Ameya<\/a>, a former collegue of mine.<\/p>
Comments<\/b><\/p>
If you have R2017a, give it a try and let us know what you think here<\/a>!<\/p>
Another feature of heatmap<\/tt> that I like is the ability to pass a table<\/a> data. For tables, you specify the x and the y variables, and the function will calculate and display the aggregated result, such as the count, of the various x-y combinations.<\/p>