Plt Axes Limits

Plt Axes Limits The plt plot or ax plot function will automatically set default x and y limits If you wish to keep those limits and just change the stepsize of the tick marks then you could use ax get xlim to

I d like to create a colorbar legend for a heatmap such that the labels are in the center of each discrete color Example borrowed from here import matplotlib pyplot as plt import numpy as See the documentation on plt axis This plt axis equal doesn t work because it changes the limits of the axis to make circles appear circular What you want is plt axis square This

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As others have said plt savefig or fig1 savefig is indeed the way to save an image However I ve found that in certain cases the figure is always shown You are creating a new figure and a new axes in every iteration of your loop put fig plt figure and ax fig add subplot 1 1 1 outside of the loop Don t use the Locators Call the functions

Python 3 4 1 winXP 32bit plt show ba Fig plt figure create the canvas for plotting ax1 plt subplot 2 1 1 2 1 1 indicates total number of rows columns and figure number respectively ax2 plt subplot 2 1 2 However

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Using plt rcParams There is also this workaround in case you want to change the size without using the figure environment So in case you are using plt plot for example you If the directory you wish to save to is a sub directory of your working directory simply specify the relative path before your file name

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Changing The Tick Frequency On The X Or Y Axis Stack Overflow

https://stackoverflow.com › questions
The plt plot or ax plot function will automatically set default x and y limits If you wish to keep those limits and just change the stepsize of the tick marks then you could use ax get xlim to

Get More Here!!

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Python Matplotlib Colorbars And Its Text Labels Stack Overflow

https://stackoverflow.com › questions
I d like to create a colorbar legend for a heatmap such that the labels are in the center of each discrete color Example borrowed from here import matplotlib pyplot as plt import numpy as

Get More Here!!