I"m trying to plot a figure without tickmarks or numbers on either of the axes (I use axes in the traditional sense, not the matplotlib nomenclature!). An issue I have come across is where matplotlib adjusts the x(y)ticklabels by subtracting a value N, then adds N at the end of the axis.
This may be vague, but the following simplified example highlights the issue, with "6.18" being the offending value of N:
import matplotlib.pyplot as plt import random prefix = 6.18 rx = [prefix+(0.001*random.random()) for i in arange(100)] ry = [prefix+(0.001*random.random()) for i in arange(100)] plt.plot(rx,ry,"ko") frame1 = plt.gca() for xlabel_i in frame1.axes.get_xticklabels(): xlabel_i.set_visible(False) xlabel_i.set_fontsize(0.0) for xlabel_i in frame1.axes.get_yticklabels(): xlabel_i.set_fontsize(0.0) xlabel_i.set_visible(False) for tick in frame1.axes.get_xticklines(): tick.set_visible(False) for tick in frame1.axes.get_yticklines(): tick.set_visible(False) plt.show()
The three things I would like to know are:
How to turn off this behaviour in the first place (although in most cases it is useful, it is not always!) I have looked through
matplotlib.axis.XAxis and cannot find anything appropriate
How can I make N disappear (i.e.
Is there a better way to do the above anyway? My final plot would be 4x4 subplots in a figure, if that is relevant.
Instead of hiding each element, you can hide the whole axis:
Or, you can set the ticks to an empty list:
In this second option, you can still use
plt.ylabel() to add labels to the axes.
If you want to hide just the axis text keeping the grid lines:
frame1 = plt.gca() frame1.axes.xaxis.set_ticklabels() frame1.axes.yaxis.set_ticklabels()
set_ticks() will also hide the grid lines.
If you are like me and don"t always retrieve the axes,
ax, when plotting the figure, then a simple solution would be to do
I"ve colour coded this figure to ease the process.
import matplotlib.pyplot as plt fig = plt.figure() ax = fig.add_subplot(111)
You can have full control over the figure using these commands, to complete the answer I"ve add also the control over the splines:
ax.spines["top"].set_visible(False) ax.spines["right"].set_visible(False) # X AXIS -BORDER ax.spines["bottom"].set_visible(False) # BLUE ax.set_xticklabels() # RED ax.set_xticks() # RED AND BLUE TOGETHER ax.axes.get_xaxis().set_visible(False) # Y AXIS -BORDER ax.spines["left"].set_visible(False) # YELLOW ax.set_yticklabels() # GREEN ax.set_yticks() # YELLOW AND GREEN TOGHETHER ax.axes.get_yaxis().set_visible(False)
I was not actually able to render an image without borders or axis data based on any of the code snippets here (even the one accepted at the answer). After digging through some API documentation, I landed on this code to render my image
plt.axis("off") plt.tick_params(axis="both", left="off", top="off", right="off", bottom="off", labelleft="off", labeltop="off", labelright="off", labelbottom="off") plt.savefig("foo.png", dpi=100, bbox_inches="tight", pad_inches=0.0)
I used the
tick_params call to basically shut down any extra information that might be rendered and I have a perfect graph in my output file.
Somewhat of an old thread but, this seems to be a faster method using the latest version of matplotlib:
set the major formatter for the x-axis
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