There are different kinds of heatmaps:
https://gis.stackexchange.com/questions/256/how-to-build-effective-heat-maps
Just a quick question, is the Google Maps's implementation of heat maps based on Concentration of points (e.g., kernel density) or Distributions of attribute values?
Or is this true?
Heatmap Tools For Web Apps
"Heat maps are often used in place of a more conventional term: kernel density estimators..."
Sorry I am quite new in this and thanks in advance!
You should take a look here: https://developers.google.com/maps/documentation/javascript/heatmaplayer
Let me know if after that you still have questions.
Related
I am starting a new project in python (to be used through jupyter-notebooks), where I'll need to visualise some hierarchically clustered graphs.
I have looked for existing packages, but so far I am not convinced by what I have seen.
I am not interested in the clustering process in itself, because this will be another part of the project and I know (roughly) how the graphs will be built up progressivelly.
What I am looking for are:
an appropriate data structure for storing hierarchically clustered graphs,
visualisation tools that would allow to represent the graph on a map (based on X and Y coordinates of the nodes) and either represent the subparts of the clusters, or simplify the clusters depending on their type or depth in the graph structure,
ideally, bring some interactivity, for example the ability to zoom-in or-out, or click on some clustered nodes to expand the nodes that were hidden in the cluster.
It looks pretty specific and despite some cool packages I have seen I am not sure which one would help without having too much to reimplement. So far, NetworkX looks like a cool starting point, especially with some D3.js (as shown here), but it is still far from what I have in mind.
Any advice about where to start digging?
Thanks a lot.
Gautier
For Python, Seaborn's clustermaps are nice. Seaborn is mainly meant to be used with Pandas dataframes; however, the documentation for clustermap says it can be rectangular data, and so I think it means other arrays will wor.
See also:
Dendrogram with heat map
SciPy Hierarchical Clustering and Dendrogram Tutorial
Hierarchical Clustering in Python
Sorry for the question, but I have a variable that I would like to plot like this:
I am a newby on R, so I am having some difficulties. I appreciate any kind of help.
Thanks!
Since you're looking to plot what appears to be a 3d surface, I'd suggest starting with the persp function, from the graphics package. This blog post (http://www.r-bloggers.com/3d-plots-in-r/) gives a good treatment of several options for 3D plotting:
the generic function persp() in the base graphics package draws perspective plots of a surface over the x–y plane. Typing demo(persp) at the console will give you an idea of what this function can do.
And running demo(persp) gives you a number of examples, including this one:
There are also some more suggestions for going further:
The plot3D package from Karline Soetaert builds on on persp()to provide functions for both 2D and 3D plotting. [...] Load the package and type the following commands at the console: example(persp3D), example(surf3D) and example(scatter3D) to see examples of 3D surface and scatter plots.
As a side note, #rawr's comment is spot on - I found all this in less than a minute, using two google searches - one of which was the title of your post. I'm putting this answer up anyway, since StackOverflow posts frequently become the top google result for many topics. But the best advice I can give you going forward is that R is one of the most aggressively well-documented languages out there, both in terms of formal and informal documentation, and you can find a lot just by googling what you want to do.
Source of image : https://math.stackexchange.com/questions/144268/is-there-a-name-for-this-type-of-plot-function-on-complex-plane-vs-time-shown
I had in one of my lectures a graph of how sin, cos and exp are related in complex domain with a figure that close to that one. I searched on-line a lot until I found that picture on Math.SE.
As per my search I found that it is only PTC mathcad that is stating it is possible to draw complex domain graphs but couldn't find any information related in mathcad manual or even in books including such graphs. Did any one managed to have such graphs drawn before. I would appreciate it as it will help me imagine graphically the circulation of complex numbers and the changes in formulas.
Can any one help?
In Mathcad, use CreateSpace with the appropriate functions of time. You'll have to open the plot dialog box to set the various axis and backplane options. You'll also need to ensure that each of the 3 plot elements is set to Data Points rather than Surface (the default display for the 3D plot component).
I typed the plot's expressions for exp, sin and cos elsewhere in the worksheet and then dragged them onto the plot.
The R function ellipse() (package: ellipse) allows to generate the coordinates of confidence regions for two parameters. Does anyone know how to generate the coordinates of hyperellipsoid confidence regions for D>2 parameters?
If I understand your question, I think what you want is described in the "Introduction to rggobi" document which you can find with a search. They call it a graphical manova. I implemented it in 3D in the function makeEllipsein the package ChemoSpec. If you study that and related functions, I think you can extend it to more dimensions. You can see it in action by running the examples in plotScores3D or plotScoresRGL. Good luck.
I recently found this web page Crime in Downtown Houston that I'm interested in reproducing. This is my first learning experience with mapping in R and thus lack the vocabulary and understanding necessary to make appropriate decisions.
At the end of the page David Kahle states:
One last point might be helpful. In making these kinds of plots, one
might tempted to use the map raster file itself as a background. This
method can be used to make map plots much more quickly than the
methods described above. However, the method has one very significant
disadvantage which, if not handled properly, can destroy the entire
purpose of using the map.
In very plain English what is the difference between the raster file
approach and his approach?
Does the RgoogleMaps package have the ability to produce these types
of high quality maps as seen on the page I referenced above that
calls a google map into R?
I ask not because I lack information but the opposite. There's too much and I want to make a good decision(s) about the approach to pursue so I'm not wasting my time on outdated or inefficient techniques.
Feel free to pass along any readings you think would benefit me.
Thank you in advance for your direction.
Basically, you had two options at the time this plot was made:
draw the map as a layer using geom_tile, where each pixel of the image is mapped onto the x,y axes (slow but accurate)
add a background image to the plot, as a purely "cosmetic" annotation. This method is faster, because you can use grid.raster which draws images more efficiently, but the image is not constrained by the axes of the plotting region. In other words, you have to manually adjust the x and y axes limits to make sure that the image corresponds to the actual positions on the plot.
Now, I would suggest you look at the new annotation_raster in ggplot2 v. 0.9.0. It should have the advantage of speed and leaner output files, and still conform to the data space of the plot. I believe that this function, as well as geom_raster and annotation_map did not exist when David made those plots.