Reputation: 504
I've written a function to replace scipy.interp1d by approximating the relationship between two variables (elev and MaxQ) in order to speed up my code. The equation is a fourth order polynomial. I would like the function to be able to compute Q values for single inputs and for 1D array inputs. The function is shown below.
def CalculateMaxFlow(elev):
size=np.shape(elev)
if size==():
if (elev>367.8): #minimum elev for flow
return -0.00028194553726719*elev**4+0.284027992763652*elev**3-80.3765236558431*elev**2+1900880.72298153
else: return 0
else:
MaxQ=np.zeros(np.shape(elev)[0])
for i in range(np.shape(elev)[0]):
if (elev[i]>367.8): #4th order polynomial. Not exact but okay for speeding up code
MaxQ[i]= -0.00028194553726719*((elev[i])**4)+0.284027992763652*((elev[i])**3)-80.3765236558431*((elev[i])**2)+1900880.72298153
else: MaxQ[i]= 0
return MaxQ
elev1=380
elev5a=380+np.zeros(5)
elev5b=np.asarray([380,380,380,380,380])
Q1=CalculateMaxFlow(elev1)
print("Q1:"+ str(Q1))
Q2=CalculateMaxFlow(elev5a)
print("Q2:"+str(Q2))
Q3=CalculateMaxFlow(elev5b)
print("Q3:"+str(Q3))
The answers are as follows:
Q1:746.828053304
Q2:[ 746.8280533 746.8280533 746.8280533 746.8280533 746.8280533]
Q3:[ 6055481.13713196 6055481.13713196 6055481.13713196 6055481.13713196 6055481.13713196]
Q1 and Q2 give me the answer I expect. For some reason, Q3 does not. I'm wondering why this is. The only difference I can see in my console between eleva and elevb is that a is a float64 and b is an int32. Why would this change the result of the equation? Why then, does the result for Q1 (which is an int) also work as expected?
Upvotes: 3
Views: 554
Reputation: 281056
With Q3, elev[i]
is a numpy.int32
instance, and elev[i]**4
overflows. With Q1, elev
is a Python int, and elev**4
uses arbitrary-precision arithmetic.
Upvotes: 4