Suppose I have an expression involving the decimal module where I want to input multiple values and get multiple values out.
a=np.array([1,2,3])
b=np.array([4,5,6])
A=a.astype(object)
B=b.astype(object)
getcontext().prec = 100
x=Decimal(A+B)
This raises an error since Decimal is incompatible with numpy arrays.
How can I pass multiple values through a Decimal expression and get multiple values out in such a way that I could easily convert the outputs to a float and then put them in a numpy array?
The reason I would want this is that a certain calculation involves A+B being calculated incorrectly as a float but once Decimal(A+B) is calculated, the resulting output can be converted to a float and cause no further difficulties in the calculation.
EDIT: I have been developing a 'cheat' method but I don't know if it has legs:
a=np.array([1,2,3])
b=np.array([4,5,6])
A=a.astype(object)
B=b.astype(object)
getcontext().prec = 100
for i in range (0,2):
x=Decimal(A[i]+B[i])
print(x)
Key here is to indent print(x), this prints 5 7 9. Failing a true solution to the above problem, is there a way of converting 5 7 9 to np.array([5,7,9]). (Maybe by exporting as csv file and importing into Python again?)
I think you could do it manually like this:
r = np.array(tuple(Decimal(x+y) for x, y in zip(A, B)), np.float64)
print(r)
Output:
[5. 7. 9.]