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Here is what I am currently doing, it works but it's a little cumbersome:
x = np.matrix([[1, 1], [2, -3]]) xmax = x.flat[abs(x).argmax()] 
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To calculate the absolute value, we can use two methods, fabs() and absolute(). To return the absolute value element-wise, use the numpy. fabs() method in Python Numpy.
Python has two ways to get the absolute value of a number: The built-in abs() function returns the absolute value. The math. fabs() function also returns the absolute value, but as a floating-point value.
The value you're looking for has to be either x.max() or x.min() so you could do
max(x.min(), x.max(), key=abs) which is similar to aestrivex's solution but perhaps more readable? Note this will return the minimum in the case where x.min() and x.max() have the same absolute value e.g. -5 and 5. If you have a preference just order the inputs to max accordingly.
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