Is there a way to enlarge the axis-scale label in matplotlib (circled in red in the enlarged plot below)?
I've used ax.tick_params() to successfully edit the tick labels, but I haven't been able to find anything about this specific piece of the plot.
Worse comes to worst, I could go with a manual text() insertion, but I'd like something more direct if possible.
Add a line like this
ax.xaxis.get_children()[1].set_size(15)
To change your major tick scale label (I guess we can call it so) to 15 points, if you plot the plot on ax.
If you plot using the pyplot API, add a line of ax=plt.gca() as well.
Related
When plotting multiple plots using plt.subplots, most of the time the spacing between subplots is not ideal so the the xtick labels of the top plot would overlap with the title of the bottom plots. There is a way to fix this manually by calling say plt.subplots_adjust(hspace=0.5) and changing the parameters interactively to obtain a decent looking plot. Is there a way to calculate the subplot_adjust parameter automatically? Meaning finding the minimum hspace and wspace so that there is not overlap between texts of the plots.
You can use tight_layout https://matplotlib.org/stable/tutorials/intermediate/tight_layout_guide.html or constrained_layout https://matplotlib.org/stable/tutorials/intermediate/constrainedlayout_guide.html
I'm pretty certain that the closest your going to find to an inbuilt calculation method is:
plt.tight_layout()
or
figure.Figure.tight_layout() #if you are using the object version of the code
I am plotting a distribution of variables that are outputs from two different versions of a program. They look very similar (this is great because they should!) and I am showing their ratio in the same figure but on a different axis. My goal is to show the ratio as a scatter plot but with a horizontal line at y=1.0 to show 100% agreement. The issue I am having is even if I plot the line first and then the scatter, my scatter points still show underneath the line plot. (Please see the image linked below.) You can see the scatter in black underneath the line plot in red, even though I call the plot function first. Any recommendations? Thank you!
Distribution of two variables with ratio plot underneath
I want to plot boxplots on top of the scattered points like this.
I know I have to bin the data into intervals first but I couldn't find the function that does all of this. Sample x and y data are saved here as .npy.
I would look into using matplotlib. Boxes can be drawn as such:
https://matplotlib.org/gallery/pyplots/boxplot_demo_pyplot.html?highlight=boxplot
and scatter plots can also be drawn as such: https://matplotlib.org/gallery/lines_bars_and_markers/scatter_demo2.html?highlight=scatter
There is a search functionality on their site, along with plenty of documentation on how to utilize their library.
As for your specific question, you can specify zorder when drawing many of the things in matplotlib, and you could use that to define your boxplots to be on top. I believe if no zorder is defined that it draws items in the order they are encountered in your program (so you could draw scatter plots and then box plots and they should appear correctly as in your diagram above!
Some code gives me the following matplotlib figure:
Unfortunately, the figure size is fixed and hence on the top right, the legend and the lines overlap. Is there any way to have the legend not stack on top of the lines?
I am aware that legend allows ax2.legend(loc=0), where 0 will put it into the "best" location. However, with two y axis as here, this will stack both legends on top of each other - not really the best allocation.
My next best try would be to "scale up" the figure, as manually done with an interactive graph, where I have only scaled up both axis:
Doing this with the "real" figure scale requires iterated "trying numbers and checking how far it goes" procedure - which may need to be redone if the graph changes. Is there any way of having matplotlib compute the scale "intelligently"?
If the best location plt.legend(loc='best') fails, try putting the legend outside of the plot:
plt.legend(loc='upper left', bbox_to_anchor=(1.02, 1), borderaxespad=0)
You can scale only legend, not the whole plot. Link here
More on legends here and also here.
I want to create a big figure using matplotlib, and then save a few parts of it at different specific coordinates (so manual zooming after plt.show() is not an option - there is no guarantee I can zoom to some precise coordinates - or is there?). The picture is fairly large, so I don't want to generate it all over again and again, specifying xlim and ylim every time before plotting. Is there any way to change axes limits after the figure is created? And I am not using an ipython console, but I need to use it in a script.
There is no problem with using xlim and ylim here. Take the following example:
import matplotlib.pyplot as plt
plt.plot(range(20))
plt.savefig("1.png")
plt.xlim(0,10)
plt.savefig("2.png")
plt.xlim(0,30)
plt.savefig("3.png")
Here a diagonal line is plotted, then we zoom into the first half of the line, then we zoom back out. At each stage a new png file is created. There is no need for redrawing here.