Matplotlib：轴的负侧不同比例

2 回答

• 1

  您可以定义自定义比例，其中低于零的值与高于零的值不同 .

  import numpy as np
  from matplotlib import scale as mscale
  from matplotlib import transforms as mtransforms
  from matplotlib.ticker import FuncFormatter
  
  class AsymScale(mscale.ScaleBase):
      name = 'asym'
  
      def __init__(self, axis, **kwargs):
          mscale.ScaleBase.__init__(self)
          self.a = kwargs.get("a", 1)
  
      def get_transform(self):
          return self.AsymTrans(self.a)
  
      def set_default_locators_and_formatters(self, axis):
          # possibly, set a different locator and formatter here.
          fmt = lambda x,pos: "{}".format(np.abs(x))
          axis.set_major_formatter(FuncFormatter(fmt))
  
      class AsymTrans(mtransforms.Transform):
          input_dims = 1
          output_dims = 1
          is_separable = True
  
          def __init__(self, a):
              mtransforms.Transform.__init__(self)
              self.a = a
  
          def transform_non_affine(self, x):
              return (x >= 0)*x + (x < 0)*x*self.a
  
          def inverted(self):
              return AsymScale.InvertedAsymTrans(self.a)
  
      class InvertedAsymTrans(AsymTrans):
  
          def transform_non_affine(self, x):
              return (x >= 0)*x + (x < 0)*x/self.a
          def inverted(self):
              return AsymScale.AsymTrans(self.a)
  

  使用此方法，您将提供缩放参数 a ，可以缩放轴的负部分 .

  # Now that the Scale class has been defined, it must be registered so
  # that ``matplotlib`` can find it.
  mscale.register_scale(AsymScale)
  
  import matplotlib.pyplot as plt
  fig, ax = plt.subplots()
  
  ax.plot([-2, 0, 5], [0,1,0])
  ax.set_xscale("asym", a=2)
  
  ax.annotate("negative axis", xy=(.25,0), xytext=(0,-30), 
              xycoords = "axes fraction", textcoords="offset points", ha="center")
  ax.annotate("positive axis", xy=(.75,0), xytext=(0,-30), 
              xycoords = "axes fraction", textcoords="offset points", ha="center")
  plt.show()
  

  关于需要什么xticks和标签的问题不是很清楚，所以我现在就把它留了下来 .

  回复于 2024-04-28T14:31:01+08:00
• 1

  这是如何得到你想要的 . 此解决方案使用两个twined axes 对象来获得原点左侧和右侧的不同缩放，然后隐藏所有证据：

  import matplotlib.pyplot as plt
  import matplotlib as mpl
  from numbers import Number
  
  tickkwargs = {m+k:False for k in ('bottom','top','left','right') for m in ('','label')}
  
  p = np.zeros((10, 3, 2))
  p[:,0,0] -= np.arange(10)*.1 + .5
  p[:,1,1] += np.repeat(np.arange(5), 2)*.1 + .3
  p[:,2,0] += np.arange(10)*.5 + 2
  
  fig = plt.figure(figsize=(8,6))
  host = fig.add_subplot(111)
  par = host.twiny()
  
  host.set_xlim(-6, 6)
  par.set_xlim(-1, 1)
  
  for ps in p:
      # mask the points with negative x values
      ppos = ps[ps[:,0] >= 0].T
      host.plot(*ppos)
  
      # mask the points with positive x values
      pneg = ps[ps[:,0] <= 0].T
      par.plot(*pneg)
  
  # hide all possible ticks/notation text that could be set by the second x axis
  par.tick_params(axis="both", **tickkwargs)
  par.xaxis.get_offset_text().set_visible(False)
  
  # fix the x tick labels so they're all positive
  host.set_xticklabels(np.abs(host.get_xticks()))
  
  fig.show()
  

  输出：

  这是我在上面的代码中使用的点集 p 在正常绘制时的样子：

  fig = plt.figure(figsize=(8,6))
  ax = fig.gca()
  for ps in p:
      ax.plot(*ps.T)
  fig.show()
  

  输出：

  回复于 2024-04-28T14:31:01+08:00