numpy.piecewise中的多个部分


问题内容

我正在上模糊系统课程,并在计算机上记笔记。这意味着我不得不不时在计算机上绘制图形。由于这些图的定义非常明确,因此我认为将其绘制numpy为一个好主意(我使用LaTeX做笔记,并且在python
shell上相当快,因此我认为可以摆脱这种情况)。

模糊隶属函数的图形是高度分段的,例如:

模糊隶属度函数

为了对此进行绘图,我尝试使用以下代码进行编码numpy.piecewise(这给了我一个神秘的错误):

In [295]: a = np.arange(0,5,1)

In [296]: condlist = [[b<=a<b+0.25, b+0.25<=a<b+0.75, b+0.75<=a<b+1] for b in range(3)]
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-296-a951e2682357> in <module>()
----> 1 condlist = [[b<=a<b+0.25, b+0.25<=a<b+0.75, b+0.75<=a<b+1] for b in range(3)]

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()

In [297]: funclist = list(itertools.chain([lambda x:-4*x+1, lambda x: 0, lambda x:4*x+1]*3))

In [298]: np.piecewise(a, condlist, funclist)
---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
<ipython-input-298-41168765ae55> in <module>()
----> 1 np.piecewise(a, condlist, funclist)

/Library/Frameworks/Python.framework/Versions/2.7/lib/python2.7/site-packages/numpy/lib/function_base.pyc in piecewise(x, condlist, funclist, *args, **kw)
    688     if (n != n2):
    689         raise ValueError(
--> 690                 "function list and condition list must be the same")
    691     zerod = False
    692     # This is a hack to work around problems with NumPy's

ValueError: function list and condition list must be the same

在这一点上,我对如何绘制此函数感到很困惑。我不太了解错误消息,这进一步阻碍了我调试该错误的努力。

最终,我希望将这个函数绘制并导出到EPS文件中,因此,我也很感谢这些帮助。


问题答案:

通常,当您仅将代码编写为数字时,numpy数组非常擅长做明智的事情。链接比较是罕见的例外之一。您看到的错误本质上是这样的(piecewise内部和ipython错误格式对此进行了混淆):

>>> a = np.array([1, 2, 3])
>>> 1.5 < a
array([False,  True,  True], dtype=bool)
>>> 
>>> 1.5 < a < 2.5
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all()
>>> 
>>> (1.5 < a) & (a < 2.5)
array([False,  True, False], dtype=bool)
>>>

您也可以使用np.logical_and,但是按位and工作就可以了。

就绘图而言,numpy本身不执行任何操作。这是matplotlib的示例:

>>> import numpy as np
>>> def piecew(x):
...   conds = [x < 0, (x > 0) & (x < 1), (x > 1) & (x < 2), x > 2]
...   funcs = [lambda x: x+1, lambda x: 1, 
...            lambda x: -x + 2., lambda x: (x-2)**2]
...   return np.piecewise(x, conds, funcs)
>>>
>>> import matplotlib.pyplot as plt
>>> xx = np.linspace(-0.5, 3.1, 100)
>>> plt.plot(xx, piecew(xx))
>>> plt.show() # or plt.savefig('foo.eps')

注意这piecewise是一个反复无常的野兽。特别是,它需要将其x参数设置为数组,如果不是,则甚至不会尝试对其进行转换(numpy用语:x需要为ndarray,而不是array_like):

>>> piecew(2.1)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 4, in piecew
  File "/home/br/.local/lib/python2.7/site-packages/numpy/lib/function_base.py", line 690, in piecewise
    "function list and condition list must be the same")
ValueError: function list and condition list must be the same
>>> 
>>> piecew(np.asarray([2.1]))
array([ 0.01])