Please review matplotlib: Tight Layout guide and try using matplotlib.pyplot.tight_layout, or matplotlib.figure.Figure.tight_layout As a quick example: import matplotlib.pyplot as plt fig, axes = plt.subplots(nrows=4, ncols=4, figsize=(8, 8)) fig.tight_layout() # Or equivalently, “plt.tight_layout()” plt.show() Without Tight Layout With Tight Layout
Instead of hiding each element, you can hide the whole axis: frame1.axes.get_xaxis().set_visible(False) frame1.axes.get_yaxis().set_visible(False) Or, you can set the ticks to an empty list: frame1.axes.get_xaxis().set_ticks([]) frame1.axes.get_yaxis().set_ticks([]) In this second option, you can still use plt.xlabel() and plt.ylabel() to add labels to the axes.
Problem Cause In mac os image rendering back end of matplotlib (what-is-a-backend to render using the API of Cocoa by default). There are Qt4Agg and GTKAgg and as a back-end is not the default. Set the back end of macosx that is differ compare with other windows or linux os. Solution I assume you have … Read more
You can use the Axes.set_yscale method. That allows you to change the scale after the Axes object is created. That would also allow you to build a control to let the user pick the scale if you needed to. The relevant line to add is: ax.set_yscale(‘log’) You can use ‘linear’ to switch back to a … Read more
Use this on a figure object: fig.set_figheight(15) fig.set_figwidth(15) Alternatively, when using .subplots() to create a new figure, specify figsize=: fig, axs = plt.subplots(2, 2, figsize=(15, 15))
I think this would be best explained by the following picture: To initialize the above, one would type: import matplotlib.pyplot as plt fig = plt.figure() fig.add_subplot(221) #top left fig.add_subplot(222) #top right fig.add_subplot(223) #bottom left fig.add_subplot(224) #bottom right plt.show()
This can be a somewhat confusing way of defining the size but you are basically specifying the area of the marker. This means, to double the width (or height) of the marker you need to increase s by a factor of 4. [because A = WH => (2W)(2H)=4A] There is a reason, however, that the … Read more
Get current axis via plt.gca(), and then set its limits: ax = plt.gca() ax.set_xlim([xmin, xmax]) ax.set_ylim([ymin, ymax])
They all do different things, since matplotlib uses a hierarchical order in which a figure window contains a figure which may consist of many axes. Additionally, there are functions from the pyplot interface and there are methods on the Figure class. I will discuss both cases below. pyplot interface pyplot is a module that collects … Read more
You could explicitly set where you want to tick marks with plt.xticks: plt.xticks(np.arange(min(x), max(x)+1, 1.0)) For example, import numpy as np import matplotlib.pyplot as plt x = [0,5,9,10,15] y = [0,1,2,3,4] plt.plot(x,y) plt.xticks(np.arange(min(x), max(x)+1, 1.0)) plt.show() (np.arange was used rather than Python’s range function just in case min(x) and max(x) are floats instead of ints.) … Read more