问题描述
我想用SymPy对包含erf函数的符号表达式进行lambd化.可以对标量参数执行以下操作:
I would like to lambdify a symbolic expression containing the erf function with SymPy. This can be done for scalar arguments as follows:
log_normal = 0.5 + 0.5 * sym.erf((sym.log(x) - mu) / sym.sqrt(2 * sigma**2))
F = sym.lambdify([x, mu, sigma], log_normal)
F(1.0, 0.0, 1.0)
我想对以上内容进行矢量化处理.通常我会按照以下步骤做...
I would like to vectorize the above. Normally I would do as follows...
log_normal = 0.5 + 0.5 * sym.erf((sym.log(x) - mu) / sym.sqrt(2 * sigma**2))
vector_F = sym.lambdify([x, mu, sigma], log_normal, modules='numpy')
vector_F(1.0, 0.0, 1.0)
但是上面提到了NameError ...
However the above raises a NameError...
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
<ipython-input-29-14adde48d4a1> in <module>()
----> 1 vector_F(1.0, 0.0, 1.0)
/Users/drpugh/anaconda/lib/python2.7/site-packages/numpy/__init__.pyc in <lambda>(x, mu, sigma)
NameError: global name 'erf' is not defined
这是一个错误，还是我缺少一些琐碎的东西?
Is this a bug, or am I missing something trivial?
推荐答案
您告诉lambdify它只有numpy作为模块可以使用；为它提供erf的来源. IOW，你有
You told lambdify it only had numpy as a module to play with; give it a source for erf. IOW, you have
>>> vector_F = sym.lambdify([x, mu, sigma], log_normal, modules=['numpy'])
>>> vector_F(1.0, 0.0, 1.0)
Traceback (most recent call last):
File "<ipython-input-10-14adde48d4a1>", line 1, in <module>
vector_F(1.0, 0.0, 1.0)
File "<string>", line 1, in <lambda>
NameError: global name 'erf' is not defined
但是
>>> vector_F = sym.lambdify([x, mu, sigma], log_normal, modules=['numpy', 'sympy'])
>>> vector_F(1.0, 0.0, 1.0)
0.500000000000000
或
>>> vector_F = sym.lambdify([x, mu, sigma], log_normal, modules=['numpy', 'math'])
>>> vector_F(1.0, 0.0, 1.0)
0.5
或您喜欢的任何erf，具体取决于您要的是sympy.core.numbers.Float还是float.
or whichever erf you prefer, depending on whether you want a sympy.core.numbers.Float or a float.
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