axes

I have a custom figure class and would like to ensure that all of the axes associated with it, whether created with subplots() or twinx() , etc. have custom behaviors. Right now I accomplish this by binding new methods to each axis after it has been created, e.g. by using import types def my_ax_method(ax, test): print('{0} is doing something new as a {1}.'.format(ax, test)) class MyFigure(matplotlib.figure.Figure): def __init__(self, **kwargs): super(MyFigure, self).__init__(**kwargs) axes_a = None axes_b = None axes_c = None def setup_axes(self, ax): self.axes_a = ax self.axes_b = self.axes_a

I am drawing a graph using the plot() function, but by default it doesn't show the axes. How do we enable showing the axes at x=0 and y=0 on the graph? Actually my graph is something like: And I want a horizontal line corresponding to y=0 . How do I get that? By default, plot does show axes, unless you've modified some settings. Try the following hold on; % make sure no new plot window is created on every plot command axes(); % produce plot window with axes plot(% whatever your plot command is); plot([0 10], [0 0], 'k-'); % plot the horizontal line dysan This should work in Matlab: set(gca,

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: So far I have the following code: colors = ('k','r','b') ax = [] for i in range(3): ax.append(plt.axes()) plt.plot(datamatrix[:,0],datamatrix[:,i],colors[i]+'o') ax[i].set(autoscale_on=True) With the autoscale_on=True option for each axis, I thought each plot should have its own y-axis limits, but it appears they all share the same value (even if they share different axes). How do I set them to scale to show the range of each datamatrix[:,i] (just an explicit call to .set_ylim() ?) And also, how can I create an offset y-axis for the third

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I have the following plot: import matplotlib.pyplot as plt fig2 = plt.figure() ax3 = fig2.add_subplot(2,1,1) ax4 = fig2.add_subplot(2,1,2) ax4.loglog(x1, y1) ax3.loglog(x2, y2) ax3.set_ylabel('hello') I want to be able to create axes labels and titles not just for each of the two subplots, but also common labels that span both subplots. For example, since both plots have identical axes, I only need one set of x and y- axes labels. I do want different titles for each subplot though. I tried a few things but none of them worked right 回答1: You

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: What is the difference between the Axes.plot() and pyplot.plot() methods? Does one use another as a subroutine? It seems that my options for plotting are line = plt.plot(data) or ax = plt.axes() line = ax.plot(data) or even fig = plt.figure() ax = fig.add_axes([0,0,1,1]) line = ax.plot(data) Are there situations where it is preferable to use one over the other? 回答1: For drawing a single plot, the best practice is probably fig = plt.figure() plt.plot(data) fig.show() Now, lets take a look in to 3 examples from the queston and explain what

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 由 翻译 强力驱动 问题: I'm trying to animate two subplots, each with multiple lines. I am using Matplotlib , and I am using the FuncAnimation , which is used by many of the animation examples . Using animation: If I try to animate it, I only get the result of the first frame: Without using animation: If I manually call my update_lines function, it works fine. Code: Below is the full code (uncommenting the 3 indicated lines in main() works, but I would like to see it update in real-time, hence trying to use the animation). import matplotlib . pyplot as

可以将文章内容翻译成中文,广告屏蔽插件可能会导致该功能失效(如失效，请关闭广告屏蔽插件后再试): 问题: I want to plot data, in two different subplots. After plotting, I want to go back to the first subplot and plot an additional dataset in it. However, when I do so I get this warning: MatplotlibDeprecationWarning: Adding an axes using the same arguments as a previous axes currently reuses the earlier instance. In a future version, a new instance will always be created and returned. Meanwhile, this warning can be suppressed, and the future behavior ensured, by passing a unique label to each axes instance. warnings.warn(message, mplDeprecation,