本质上,您需要将以下转换应用于您的Y
值:-log10(1-y)
. 这施加了唯一的限制y < 1
,因此您应该能够在转换后的图上具有负值。
这是文档中的一个修改示例matplotlib
,显示了如何将自定义转换合并到“比例”中:
import numpy as np
from numpy import ma
from matplotlib import scale as mscale
from matplotlib import transforms as mtransforms
from matplotlib.ticker import FixedFormatter, FixedLocator
class CloseToOne(mscale.ScaleBase):
name = 'close_to_one'
def __init__(self, axis, **kwargs):
mscale.ScaleBase.__init__(self)
self.nines = kwargs.get('nines', 5)
def get_transform(self):
return self.Transform(self.nines)
def set_default_locators_and_formatters(self, axis):
axis.set_major_locator(FixedLocator(
np.array([1-10**(-k) for k in range(1+self.nines)])))
axis.set_major_formatter(FixedFormatter(
[str(1-10**(-k)) for k in range(1+self.nines)]))
def limit_range_for_scale(self, vmin, vmax, minpos):
return vmin, min(1 - 10**(-self.nines), vmax)
class Transform(mtransforms.Transform):
input_dims = 1
output_dims = 1
is_separable = True
def __init__(self, nines):
mtransforms.Transform.__init__(self)
self.nines = nines
def transform_non_affine(self, a):
masked = ma.masked_where(a > 1-10**(-1-self.nines), a)
if masked.mask.any():
return -ma.log10(1-a)
else:
return -np.log10(1-a)
def inverted(self):
return CloseToOne.InvertedTransform(self.nines)
class InvertedTransform(mtransforms.Transform):
input_dims = 1
output_dims = 1
is_separable = True
def __init__(self, nines):
mtransforms.Transform.__init__(self)
self.nines = nines
def transform_non_affine(self, a):
return 1. - 10**(-a)
def inverted(self):
return CloseToOne.Transform(self.nines)
mscale.register_scale(CloseToOne)
if __name__ == '__main__':
import pylab
pylab.figure(figsize=(20, 9))
t = np.arange(-0.5, 1, 0.00001)
pylab.subplot(121)
pylab.plot(t)
pylab.subplot(122)
pylab.plot(t)
pylab.yscale('close_to_one')
pylab.grid(True)
pylab.show()

请注意,您可以通过关键字参数控制 9 的数量:
pylab.figure()
pylab.plot(t)
pylab.yscale('close_to_one', nines=3)
pylab.grid(True)
