Talk:Heat map

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Bioinformatics?[edit]

Heatmaps shouldn't be considered a bioinformatics topic. Rather, they are a general data visualization technique. Bioinformatics is merely one application.

Any thoughts on changing it?

I completly agree with him, as heatmaps are used for a wide variety of purposes, for example to illustrate repartition of stress (physics), heat, and so on. —Preceding unsigned comment added by 88.160.174.38 (talk) 06:33, August 30, 2007 (UTC)

I agree somewhat. There are several things to keep in mind, however. First, there are two different types of graphs commonly referenced under this term. The first is the one pictured in this article and widely used in genomics. It consists of a rectangular array of colored pixels representing a matrix. The rows and columns of this array are often permuted to show blocks of similar values. Wilkinson, The Grammar of Graphics, 2nd ed. (Springer, 2005) discusses the history of this graph. One of the earliest examples of a heatmap used for this purpose is in Sneath, P.H.A. (1957). The application of computers to taxonomy. Journal of General Microbiology, 17, 201–226. A famous reference is in Bertin, J. (1967). Sémiologie Graphique. Paris: Editions Gauthier–Villars. English translation by W.J. Berg as Semiology of Graphics, Madison, WI: University of Wisconsin Press, 1983. Adding the cluster trees to the margins of the graph was invented by Ling, R.F. (1973). A computer generated aid for cluster analysis. Communications of the ACM, 16, 355–361. The first computer program for making one (in black and white, using overstruck characters) was programmed by John Hartigan and Bob Ling for the BMDP computer program (2-way clustering). The first appearance of the graph shown in the figure of this article was in SYSTAT, Version 5 (1987). SYSTAT, because it had high-resolution color output, was able to use a heatmap color scale (the same as in this article example) and horizontal/vertical cluster trees, which were unavailable in the BMDP teletype output. SYSTAT was widely used in the 1980's and early 1990's by biological researchers, and the SYSTAT design for the graph found its way into several computer programs. The most widely used in bioinformatics was developed by Michael B. Eisen, Paul T. Spellman, Patrick O. Brown, David Botstein, Cluster analysis and display of genome-wide expression patterns Proc. Natl. Acad. Sci. USA Dec 08, 1998; 95: 14863-14868. (This is one of the most widely downloaded articles from PNAS).

The other type of graph commonly called a heatmap is actually a treemap. This display does not have rows and columns. Instead, it consists of a recursive partitioning of rectangles governed by a tree-building algorithm (cluster analysis or some other). The cells are colored similarly to the permuted heatmap display. The first published example of this graph is in Johnson, B.S. and Shneiderman, B. (1991). Treemaps: A space-filling approach to the visualization of hierarchical information structures. Proceedings of the IEEE Symposium on Information Visualization, 275–282. Its most popular incarnation is the Wall Street Smartmoney Map (http://www.smartmoney.com/marketmap/mapPage.cfm). Wikipedia already has an entry for this graph, oddly under the name Treemapping. (I don't advocate Heatmapping for this entry).

It would be unfortunate if Wikipedia confused the two types of graphs. Although they look similar, they have completely different underlying models, different motivations, and different interpretations. If the permuted-array and treemap are both called heatmaps, then a map of the US with counties colored by average temperature or the Wilkinson Anisotropy Map (http://apod.nasa.gov/apod/ap050925.html) should be called heatmaps as well. There is nothing instrinsically rectangular implied by the term Heatmap.

Therefore, I would advocate a different approach. Define a heatmap as a (usually 2D) area graphic (map) whose regions are colored using a color scale to represent the values of a variable. Mention a very old example from the early 1800's (see . Then point out the two most popular examples (cluster array and treemap) with a link to Treemapping.

Then a short History section. I would begin with a reference to the Wiki Thematic Map article, which describes the type of geographic maps that motivated the original invention of heatmaps - color used to represent a (continuous) variable. Then give credit to Bertin, Ling and the others who invented the cluster display, to Shneiderman and Johnson, who invented the treemap, and to the others who developed the software (BMDP, SYSTAT, and Eisen).

All this could be done in an article not much longer than this one. Since I am an expert in this field, I have not changed anything in the entry. Good luck! And I would be especially interested if anyone found references earlier than the ones I cited.67.173.98.211 (talk) 18:06, 24 November 2007 (UTC)[reply]

Given the above definition of a heat map as: consisting of a rectangular array of coloured pixels representing a matrix. The rows and columns of this array are often permuted to show blocks of similar values. Surely the Hovmöller diagram (1949) should be referenced.--86.12.145.251 (talk) 10:16, 27 February 2012 (UTC)[reply]

Heat map external link[edit]

Originally posted at my talk page -- John of Reading (talk) 07:54, 22 March 2011 (UTC)[reply]

Thanks for your message about the external link in heat map section. iMapbuilder is a software product which can be used to create heat maps -- as a matter of fact, many of our users including users from school and corporations, have already used iMapBuilder to create heat maps for their different projects.

There are different types of heat maps, the particular type of heat map iMapBuilder creates is very useful for data visualization purpose. It provides an useful tool for users who need to create this type of heat map. Therefore it is not off topic for the related link to be posted on this page.

If required, we can provide samples of heat maps created for your reference. We believe including this link can help many users to find a tool which are suitable for their usage. It is definitely not a spam.

Maybe it would be more appropriate to modify the link to point directly to a heat map sample on the website? —Preceding unsigned comment added by 203.198.150.93 (talk) 05:03, 22 March 2011 (UTC)[reply]

The guidelines for the "External links" section are stricter than any readers and editors realise. In particular, links to commercial sites are not encouraged - see point 5 at WP:LINKSTOAVOID. However, I've copied your post here so that interested editors can consider it. -- John of Reading (talk) 07:54, 22 March 2011 (UTC)[reply]

Are choropleths heat maps?[edit]

There are a few references to choropleths being a subspecies of heatmap, and there's a link to a choropleth under 'examples'. But I don't think this is correct, and a few sources to back me up: http://cartonerd.blogspot.com/2012/08/getting-steamed-up-over-heat-maps.html, http://indiemaps.com/blog/2008/06/this-is-not-a-heat-map/.

My understanding is that choropleths and heatmaps are overlapping sets. A heatmap is a choropleth when the dimensions of a regular 2d heatmap have been broken down into squares/rectangles of latitude and longitude and colored accordingly (as in this example). But when states or counties or voting districts are drawn on the map and then these shapes are colored according to a variable (as in this example, this is merely a choropleth -- not a heatmap. Heat maps are used in stock market applications

I propose removing references to choropleths from this article, or, better, including a 'Heat Maps vs. Choropleths' section illuminating the differences. Unfortunately I had trouble finding more scholarly articles on the issue than the two blogposts above. Anybody else have more expertise than me here, or can help? — Preceding unsigned comment added by Rfcima (talkcontribs) 17:52, 14 May 2014 (UTC)[reply]

A better question might be "are isopleths heat maps". or maybe better yet, "are heat maps isopleth maps". My answer would be a qualified yes, and they are most certainly at least the great, great grandchild of isopleth maps (A. Humboldt, 1817). It's interesting that one of the first illustrations used in this article is not a map of air temperatures, which have largely defied remote sensing efforts to be detected on a global scale. It is described as a map of temperatures when in fact it is a frame grab from an animated map of carbon dioxide concentrations. as we know this has a relationship to temperature, but it is not.. actually.. temperature. We can sometimes sense temperatures of land surfaces on a global scale and this has been a very useful tool for detecting and displaying land and ocean temperatures and visualizing the dynamic nature of these. air temps not so much. gridded raster images of interpolated temps measured at points are useful and can be animated to some degree (npi). Remote sensing of various land surface and atmospheric phenomena has been an important part of the science focused on climate change and its global effects. IMHO the term "heat map" should be reserved for maps of air temperature. Pmchaffie (talk) 01:33, 13 October 2022 (UTC)[reply]

Replace examples using "jet" colormap[edit]

Jet is an awful colormap, which is explained on this page for those that aren't aware. The examples on this page should be replaced with examples that use modern, luminance-corrected colormaps. Richard☺Decal (talk) 22:47, 24 September 2015 (UTC)[reply]

Yes, the jet colormap is awful. There are much better maps available, as described here: Smit, Noeska (23 February 2016). "Better than the rainbow: The Matplotlib alternative colormaps". medvis.org.. --Pakaraki (talk) 20:47, 19 June 2016 (UTC)[reply]

Link to surface plot[edit]

In the exemples, there is a link to surface plot. Which I guess may be really usefull. Except that this link discuss radar, and navigation. Is there a correct link ? Or should we create a page for this subject ? — Preceding unsigned comment added by Arthur MILCHIOR (talkcontribs) 12:53, 18 May 2018 (UTC)[reply]

@Arthur MILCHIOR: I've converted surface plot to a disambiguation page, and changed the link here to surface plot (mathematics), which redirects to Graph of a function#Functions of two variables. --Pokechu22 (talk) 19:11, 16 August 2020 (UTC)[reply]

Code examples[edit]

@Schakel2: I don’t think these edits are encyclopaedic. The many statement of belief like “One of the most popular heat map software implementations is Python” or

One advantage of Plotly over Seaborn or matplotlib is it’s natural ability to display interactive data on the web. It also works well with other languages other than Python, leading itself to be the natural choice for a multi-language framework.

are not appropriate, and the section in general is very promotional toward Python, violating neutrality. There are also sentence fragments and broken text. Worst of all, code samples are plagiarized. Strebe (talk) 04:26, 19 April 2022 (UTC)[reply]

I reluctantly agree with your statement that “One of the most popular heat map software implementations is Python” is not encyclopedic. With that being said, I'm sure we can find a source that shows downloads/language and Python would be toward the top, it's literally been around since 1991.
I re-worked the section to not have such a heavy emphasis on Python libraries; however, I elaborated on matplotlib since it's the library that I have the most experience in. Maybe we could get some other experts in languages like R to expand on those sections.
Also, is using open-source code considered plagiarizing if you cite it? Schakel2 (talk) 13:53, 20 April 2022 (UTC)[reply]
We're not a software directory or a howto site. This sort of content does not belong on Wikipedia. MrOllie (talk) 13:57, 20 April 2022 (UTC)[reply]

Python Specific Additions to Software Implementations Sections[edit]

I wanted to elaborate on the software implementations section with a Python addition. I understand now that I shouldn't be adding source code as articles shouldn't be a code repository. I also understand that I shouldn't be making blanketed claims like "Python is one of the most used languages".

Can anyone provide insight as to how I could contribute to a Python section while maintaining neutrality? Is there anything more I can do other than providing an additional bullet point and showing a Python-created heat map? — Preceding unsigned comment added by Schakel2 (talkcontribs) 14:39, 20 April 2022 (UTC)[reply]

You also should not be listing nonnotable libraries, especially not adding external links to nonnotable libraries. I also do not believe that a general purpose programming language should be listed alongside focused solutions. MrOllie (talk) 21:58, 20 April 2022 (UTC)[reply]
IMO Python is worth mentioning (it would be very silly not to include it in the section), especially since we already have an article on Matplotlib. I found an article[1] that specifically mentions Matplotlib (and Seaborn), though since data science is not my field of study, I can't really say how good it is (it doesn't seem any worse than the existing references in that section, though). --Pokechu22 (talk) 22:07, 20 April 2022 (UTC)[reply]
The R section lists an external link to a library, too. The fact of whether or not it's notable is an opinion. This entire article lists non-notable external links as well. Python is worth mentioning and while it is definitely a general-purpose language, it's only general purpose for someone who has exposure to programming - which this article does not cater to. You should re-instate the edit. Schakel2 (talk) 01:20, 21 April 2022 (UTC)[reply]
Notable has a specific definition on Wikipedia. MrOllie (talk) 02:06, 21 April 2022 (UTC)[reply]
Indeed it does. From that page, notability is a test used by editors to decide whether a given topic warrants its own article and [t]hese guidelines only outline how suitable a topic is for its own article or list. They do not limit the content of an article or list[...]. So you could argue that the article Matplotlib could be deleted under notability at WP:AFD, but it doesn't make sense to do so for the inclusion in the list here. --Pokechu22 (talk) 03:00, 21 April 2022 (UTC)[reply]

Surely there is no serious objection to listing Python as being frequently used for constructing heat maps, along with mention of the prominent packages. This just needs to be done properly cited and with balance. My objection was about the imbalance and the tutorial. I encourage Schakel2 to track down and add suitable references along with balanced text.

The mention of R is also wrong; R does not have heat map functionality as part of the language. It the stats package includes a heatmap function, but this is not, in any technical sense, “part of the language”. The citations given do not support the claim in the text. Strebe (talk) 22:56, 21 April 2022 (UTC)[reply]

We could perhaps list matplotlib specifically, but listing 'Python' makes no more sense than listing C++ or any other general purpose language in which someone happens to have written a heatmap library. MrOllie (talk) 22:57, 21 April 2022 (UTC)[reply]
listing 'Python' makes no more sense than listing C++…. Python and R are far and away the most common languages used to construct heat map visualizations. Matlab is also common among data visualization producers, but, being a proprietary language, doesn’t accrue as many users. Using the same language to construct a heat map as used in the analysis of the data permits rapid iteration. C++ and other languages are not commonly used for statistical and data analysis because using a compiled, strongly typed language for such purposes has obvious productivity and verstility disadvantages that are overcome only if the processing efficiencies of the language can be exploited in massively repeated calculations. Meanwhile data visualization and statistical libraries available for R and Python are considerable and top-notch. This is well known anecdotally among researchers who deal with data visualization, but nobody seems to have done a study, so… Strebe (talk) 02:33, 22 April 2022 (UTC)[reply]

References

  1. ^ Brittain, Jim; Cendon, Mariana; Nizzi, Jennifer; Pleis, John (20 July 2018). "Data Scientist's Analysis Toolbox: Comparison of Python, R, and SAS Performance". SMU Data Science Review. 1 (2). Southern Methodist University: 13. Archived from the original on April 20, 2022.

Edit problems[edit]

@Leonardo Guagenti: What does this sentence even mean? Choropleth maps and heat maps are often used in place of one another incorrectly when referring to data visualized geographically. What was there before your edit was clear. Are you restating what was there, or are you stating something else? And where does this something else come from? What was there previously was cited.