How to take element-wise logarithm of a matrix in sympy?

Question

Working with a sympy Matrix or numpy array of sympy symbols, how does one take the element-wise logarithm?

For example, if I have:

m=sympy.Matrix(sympy.symbols('a b c d'))

Then np.abs(m) works fine, but np.log(m) does not work ("AttributeError: log").

Any solutions?

Answer 1

Use Matrix.applyfunc:

In [6]: M = sympy.Matrix(sympy.symbols('a b c d'))

In [7]: M.applyfunc(sympy.log)
Out[7]:
⎡log(a)⎤
⎢      ⎥
⎢log(b)⎥
⎢      ⎥
⎢log(c)⎥
⎢      ⎥
⎣log(d)⎦

You can't use np.log because that does a numeric log, but you want the symbolic version, i.e., sympy.log.

Answer 2

If you want an elementwise logarithm, and your matrices are all going to be single-column, you should just be able to use a list comprehension:

>>> m = sympy.Matrix(sympy.symbols('a b c d'))
>>> logm = sympy.Matrix([sympy.log(x) for x in m])
>>> logm
Matrix([
[log(a)],
[log(b)],
[log(c)],
[log(d)]])

This is kind of ugly, but you could wrap it in a function for ease, e.g.:

>>> def sp_log(m):
    return sympy.Matrix([sympy.log(x) for x in m])

>>> sp_log(m)
Matrix([
[log(a)],
[log(b)],
[log(c)],
[log(d)]])