I got a super graph that I would like to export as an html file to be showed on an website but I don't know how to figure that. Have you got an idea ?
You can use mpld3. This is a great tutorial. The mpld3 library's main functionality is to take an existing matplotlib visualization and transform it into some HTML code that you can embed on your website.
Use fig_to_html file, which accepts a matplotlib figure object as its sole argument and returns HTML.
To use the fig_to_html method , simply add the following code to the end of our Python script:
html_str = mpld3.fig_to_html(fig)
Html_file= open("index.html","w")
Html_file.write(html_str)
Html_file.close()
Related
basically the title is the question:
I would like to use lualatex for all the text handling in a matplotlib plot without using the pgf backend.
I need fontenc package and customized fonts to have identical fonts in plots and in my latex documents but do not want to use the pgf backend.
Is there a hidden option somewhere?
The context is the following: I have a mycommands.sty file where all my defind \newcommand for math are stored. I use some specific fonts for, e. g., \mathscr{p}, which is not possible (small letter) without the fontenc package.
Now I want to use these custom commands in different places (legend, labels, title, ...) in the plot and have them work and look exactly the same as in the document I write and compile with lualatex.
The only point why it is not possible is that matplotlib internally uses pdflatex for the compilation which gives me errors when using fontenc and therefore some of my commands do not work.
Thanks.
Context
I'm looking for a simple way to import properly typeset mathematics (with LaTeX) into blender. A solution for this has already been given. But that means getting out of blender, using multiple tools and then going back to blender and importing the whole thing.
Blender comes with Python and can import svg
I'd like to find an other way and blender has a set of powerful tools based on Python. I was thinking: can I make Python parse some TeX input and then generate a svg (virtual) file inside blender. That would solve the problem.
matplotlib "emulates" TeX
It is possible to install any Python library and use it inside blender. So this made me think of a possible "hack" of matplotlib.
mathtext is a module that provides a parser for strings with TeX-like syntax for mathematical expressions. svg is one of the available "backends".
Consider the following snippet.
import matplotlib.mathtext as mathtext
parser = mathtext.MathTextParser('svg')
t = parser.parse(r'$\int_{0}^{t} x^2 dx = \frac{t^3}{3}$')
t is a tuple that has all the information needed. But I can't find a way (in the backend api) to convert it to a (virtual) svg file.
Any ideas?
Thanks
Matplotlib needs a figure (and currently also a canvas) to actually be able to render anything. So in order to produce an svg file whose only content is a text (a mathtext formula) you still need a figure and a canvas and the text needs to actually reside inside the figure, which can be achieved by fig.text(..).
Then you can save the figure to svg via fig.savefig(..). Using the bbox_inches="tight" option ensures the figure to be clipped to the extent of the text. And setting the facecolor to a transparent color removes the figure's background patch.
from matplotlib.backends.backend_agg import FigureCanvasAgg
from matplotlib.figure import Figure
fig = Figure(figsize=(5, 4), dpi=100)
canvas = FigureCanvasAgg(fig)
fig.text(.5, .5, r'$\int_{0}^{t} x^2 dx = \frac{t^3}{3}$', fontsize=40)
fig.savefig("output.svg", bbox_inches="tight", facecolor=(1,1,1,0))
I am trying to scale my decision tree to fit notebook but it appears not to scale properly. I have to keep scrolling for a better view. Can I please have some help on how to fix this. Attach is a pic of how it looks like.
from graphviz import Source
from sklearn import tree
from IPython.display import SVG
graph = Source( tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
SVG(graph.pipe(format='svg'))
Perhaps it's not relevant any more, since this question has been open for about six months now. However, I just stumbled into it, as apparently 83 other readers, and I just crafted my way around this. The easy way is to use the pydot package (pip install pydot), and then add the default size. I have also been using %matplotlib inline so that it displays nicely within the notebook but without using the svg module. With your example:
%matplotlib inline
from graphviz import Source
from sklearn import tree
import pydot
dot_data = tree.export_graphviz(dt_classifier, out_file=None, feature_names=X.columns))
pdot = pydot.graph_from_dot_data(dot_data)
# Access element [0] because graph_from_dot_data actually returns a list of DOT elements.
pdot[0].set_graph_defaults(size = "\"15,15\"")
graph = Source(pdot[0].to_string())
graph
I also added rotate=True to export_graphviz so that it displays in horizontal style, the root of the tree is directly visible, and is easier to follow. Of course, you can play around with size so as to reach something that is acceptable for you.
I want to do something like the following using a loop and PyPlot to plot in figure windows. My question is how to save the figure windows to a movie file within the loop?
using PyPlot
for k=1:5
pcolormesh(rand(10,10))
if k==1; colorbar(); end
# save figure window to movie file here??
sleep(.5)
end
This is possible by directly using the animation submodule of matplotlib (the underlying Python library that PyPlot.jl wraps). However, it is painful; see e.g. the following notebook (in Spanish):
https://github.com/dpsanders/fisica_computacional/blob/master/como_animar.ipynb
The simplest way, however, seems to be using Plots.jl:
https://github.com/tbreloff/ExamplePlots.jl/blob/master/docs/pyplot_examples.md#functions-adding-data-and-animations.
I'd like the background of my matplotlib plots to be transparent in my IPython notebook. This may sound silly because the notebook itself defaults to a white background but:
1) I use a solarized background and
2) more importantly, I want them to be transparent for when I embed the notebook directly into my blog via nbconvert.
It's easy enough to use something like savefig('file', transparent=True) , but I'm not saving the figures, I am displaying them inline (by calling IPython with ipython notebook --matplotlib inline.
I've been playing around with the IPython notebook configuration file, especially with c.InlineBackend.rc. For example, I upgraded to the dev version of matplotlib to get access to its new savefig.transparent rcParam, and tried configuring that with c.InlineBackend.rc = {'savefig.transparent': True}, but as expected it only affects plots saved with savefig.
Note that I am using the recent IPython 2.0 release. This must be possible somehow, right? Any light that you can shed would be appreciated.
Just to follow up, the issue opened on Github by tillsten has been patched so something like this:
rcParams['figure.facecolor'] = (0,0,0,0)
should work now after you update IPython. Three cheers for open source.
The inline plots are html objects (<img>) with class ui-resizable. So you can change their default behavior by customizing the CSS for your notebooks:
locate your settings for notebooks: in a terminal, type
ipython locate
in the indicated directory, go to subdir profile_default\static\custom (or any profile you want to use instead)
edit or create a CSS file named custom.css
put this in it:
img.ui-resizable
{
opacity:0.4;
}
Close your notebooks, kill IPython and restart it (so that it recreates the served files).
It should work with exported notebooks, as long as you export them as html and you change the css there too.
It's not exactly what you want, but it does the job.