I would like to use pyplot.contour feature in bokeh. Is there any way I can use it?? I know pyplot.pcolormesh and bokeh.plotting.image. Can I use conotur plot with it?
pyplot.contour is part of Matplotlib, not Bokeh. As of Bokeh 2.3.0 there is no built-in contouring function or capability. Recently a MultiPolygons glyph that can support "polygons with holes" was added. This is a first necessary step to being able to have real contour plots in Bokeh. A next step would be for someone to write a set of functions that can accept array inputs and generate the multi-polygon data necessary to drive Bokeh graphics, but this has not been done by anyone yet.
If image contour plots (similar to pcolormesh) or line (unfilled) contours suit your needs, that you can consider using Holoviews, which can generate Bokeh contour plots for those kinds of cases:
http://holoviews.org/reference/elements/bokeh/Contours.html
I am having a hard time using Matplotlib to visualize reprojection results of my data in 3 dimensions after applying Principle components analysis or Linear discriminant analysis. After doing a scatter plot, I cannot rotate the data or change the point of view while zooming easily (Rotation axis stays the same even after you zoom, and if you zoom too much points just disappear) and every change takes one second to occur. Matplotlib is very useful but for this specific use case it starts to get very frustrating as it probably wasn't designed for such tasks. Is there an alternative to Matplotlib in Python that can handle 3d scatter plots better and where one could fluidly navigate through the cloud?
An example is shown in the next figure. I have drawn spheres around each data cluster corresponding to a specific class and colored overlapping spheres with red. Now I want to see how these sphere intersect. I think the biggest problem with Matplotlib is that it doesn't allow shifting of the whole graph with the mouse, it only allows rotation around a fixed point, which makes things very messy once you zoom a bit.
matplotlib is not quite mature for 3d graphics :
http://matplotlib.org/mpl_toolkits/mplot3d/faq.html
mplot3d was intended to allow users to create simple 3D graphs with the same “look-and-feel” as matplotlib’s 2D plots. Furthermore, users can use the same toolkit that they are already familiar with to generate both their 2D and 3D plots.
I don't think easy navigation in a 3d plot is easily doable (even 3d scaling is not possible without tweaking the lib). mplot3d was not really intended to be a full-fledged 3D graphics library in the beginning, but more a nice addition for people who needed basic 3D and who were acquainted with matplotlib 2D plot structure.
You might want to take a look at MayaVI (which is pretty good) :
MayaVi2 is a very powerful and featureful 3D graphing library. For advanced 3D scenes and excellent rendering capabilities, it is highly recomended to use MayaVi2.
Note that unlike matplotlib, MayaVI is not yet compatible with Python3 (and might not be in the foreseeable future), so you'll need a Python2 installation.
A very good alternative, but not in Python, is the 3D plot from ILNumerics (http://ilnumerics.net/). It is in .NET
Matplotlib works alright for 3D however, not too fast when interactivity is needed:
https://matplotlib.org/mpl_toolkits/mplot3d/tutorial.html
Mayavi is really fast and compatible with Python 3:
https://docs.enthought.com/mayavi/mayavi/mlab.html#id1
I'm writing a web interface for a database of genes values of some experiments with CGI in Python and I want to draw a graph for the data queried. I'm using matplotlib.pyplot, draw a graph, save it, and perform it on the web page. But usually there are many experiments queried hence there are a lot of values. Sometimes I want to know which experiment does one value belong to because it's a big value, whereas it's hard to identify because the picture is small in size. The names of the experiments are long strings so that it will mess the x axis if I put all the experiment names on the x axis.
So I wonder if there is a way to draw a graph that can interact with users, i.e. if I point my mouse to some part on the graph, there would be one small window appears and tells me the exact value and what is the experiment name here. And the most important is, I can use this function when I put the graph on the web page.
Thank you.
What you want is basically D3.js rendering of your plots. As far as I know, there are currently three great ways of achieving this, all under rapid development:
MPLD3 for creating graphs with Matplotlib and serving them as interactive web graphics (see examples in Jake's blog post).
Plotly where you can either generate the plots directly via Plotly or from Matplotlib figures (e.g. using matplotlylib) and have them served by Plotly.
Bokeh if you do not mind moving away from Matplotlib.
I want to draw 3D primitives like spheres, cylinders and planes (patches) in a 3D plot and I would like to be able to interactively rotate, translate and zoom the scene. I want to do that in Python. I'm use to use Matplotlib for 2d graphs but I never worked with 3D graphics with Python.
Any suggestions?
Any link to tutorials?
Any ideas?
If you're used to matplotlib, then mplot3d is probably a good option if it meets your requirements.
Alternatively there is VPython. This allows you greater freedom to create arbitrary objects and manipulate them, but, of course, more to learn.
I need to plot some data in various forms. Currently I'm using Matplotlib and I'm fairly happy with the plots I'm able to produce.
This question is on how to plot the last one. The data is similar to the "distance table", like this (just bigger, my table is 128x128 and still have 3 or more number per element).
Now, my data is much better "structured" than a distance table (my data doesn't varies "randomly" like in a alphabetically sorted distance table), thus a 3D barchart, or maybe 3 of them, would be perfect. My understanding is that such a chart is missing in Matplotlib.
I could use a (colored) Countor3d like these or something in 2D like imshow, but it isn't really well representative of what the data is (the data has meaning just in my 128 points, there isn't anything between two points). And the height of bars is more readable than color, IMO.
Thus the questions:
is it possible to create 3D barchart in Matplotlib? It should be clear that I mean with a 2D domain, not just a 2D barchart with a "fake" 3D rendering for aesthetics purposes
if the answer to the previous question is no, then is there some other library able to do that? I strongly prefer something Python-based, but I'm OK with other Linux-friendly possibilities
if the answer to the previous question is no, then do you have any suggestions on how to show that data? E.g. create a table with the values, superimposed to the imshow or other colored way?
For some time now, matplotlib had no 3D support, but it has been added back recently. You will need to use the svn version, since no release has been made since, and the documentation is a little sparse (see examples/mplot3d/demo.py). I don't know if mplot3d supports real 3D bar charts, but one of the demos looks a little like it could be extended to something like that.
Edit: The source code for the demo is in the examples but for some reason the result is not. I mean the test_polys function, and here's how it looks like:
example figure http://www.iki.fi/jks/tmp/poly3d.png
The test_bar2D function would be even better, but it's commented out in the demo as it causes an error with the current svn version. Might be some trivial problem, or something that's harder to fix.
MyavaVi2 can make 3D barcharts (scroll down a bit). Once you have MayaVi/VTK/ETS/etc. installed it all works beautifully, but it can be some work getting it all installed. Ubuntu has all of it packaged, but they're the only Linux distribution I know that does.
One more possibility is Gnuplot, which can draw some kind of pseudo 3D bar charts, and gnuplot.py allows interfacing to Gnuplot from Python. I have not tried it myself, though.
This is my code for a simple Bar-3d using matplotlib.
import mpl_toolkits
from mpl_toolkits.mplot3d import Axes3D
import matplotlib.pyplot as plt
%matplotlib inline
## The value you want to plot
zval=[0.020752244,0.078514652,0.170302899,0.29543857,0.45358061,0.021255922,0.079022499,\
0.171294169,0.29749654,0.457114286,0.020009631,0.073154019,0.158043498,0.273889264,0.419618287]
fig = plt.figure(figsize=(12,9))
ax = fig.add_subplot(111,projection='3d')
col=["#ccebc5","#b3cde3","#fbb4ae"]*5
xpos=[1,2,3]*5
ypos=range(1,6,1)*5
zpos=[0]*15
dx=[0.4]*15
dy=[0.5]*15
dz=zval
for i in range(0,15,1):
ax.bar3d(ypos[i], xpos[i], zpos[i], dx[i], dy[i], dz[i],
color=col[i],alpha=0.75)
ax.view_init(azim=120)
plt.show()
http://i8.tietuku.com/ea79b55837914ab2.png
You might check out Chart Director:
http://www.advsofteng.com
It has a pretty wide variety of charts and graphs and has a nice Python (and several other languages) API.
There are two editions: The free version puts a blurb on the generated image, and the
pay version is pretty reasonably priced.
Here's one of the more interesting looking 3d stacked bar charts:
(source: advsofteng.com)