a = 0.5
b = 1
l = Symbol('l')
l = solve(a*b/2+b/l-1, l)[0]
num = 1-l/b*(r-a*b/2)
-1/l*np.log(num)
gives error TypeError: loop of ufunc does not support argument 0 of type Float which has no callable log method
How should I fix this?
As noted, r is undefined.
In [83]: a = 0.5
...: b = 1
...: l = sp.Symbol('l')
...: l = sp.solve(a*b/2+b/l-1, l)[0]
...: num = 1-l/b*(r-a*b/2)
---------------------------------------------------------------------------
NameError Traceback (most recent call last)
Cell In[83], line 5
3 l = sp.Symbol('l')
4 l = sp.solve(a*b/2+b/l-1, l)[0]
----> 5 num = 1-l/b*(r-a*b/2)
NameError: name 'r' is not defined
But checking l:
In [84]: l
Out[84]:
1.33333333333333
In [85]: type(l)
Out[85]: sympy.core.numbers.Float
Trying to take log of that produces your error:
In [86]: np.log(l)
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
AttributeError: 'Float' object has no attribute 'log'
The above exception was the direct cause of the following exception:
TypeError Traceback (most recent call last)
Cell In[86], line 1
----> 1 np.log(l)
TypeError: loop of ufunc does not support argument 0 of type Float which has no callable log method
sympy has a log that does work:
In [88]: sp.log(l)
Out[88]:
0.287682072451781
Your l looks like a regular float, but is actually a sympy version. np.log if given a non-numeric array, first makes an array:
In [89]: np.array(l)
Out[89]: array(1.33333333333333, dtype=object)
If object dtype it then tries to apply a log METHOD to each element of the array. Almost no one implements a x.log() method.
In general using numpy with sympy does not work well. Bits and pieces work, but they aren't designed to work together. Use sympy functions when available. sp.lambdify can, in some cases convert an expression to a python function that will work.
In [92]: import math
In [93]: math.log(l)
Out[93]: 0.28768207245178085