Hello Michael,
We investigated using ExprTk to parse analytical formulas instead of
muParser, it is known to be faster.
Almost all muParser formulas can be parsed by ExprTk without changes,
but it also provides many more features. And multiple outputs are
trivial with this backend.
This has been implemented on current master, your example can be written:
inputs = ['Q', 'Ks', 'Zv', 'Zm', 'Hd', 'Zb', 'L', 'B']
outputs = ['H', 'S']
formula = """var alpha := (Zm - Zv)/L;
H := (Q/(Ks*B*sqrt(alpha)))^(3.0/5.0);
var Zc := H + Zv;
var Zd := Zb + Hd;
S := Zc - Zd;"""
myFunction = SymbolicFunction(inputs, outputs, formula)
This is almost straightforward; input and output variables are
declared, all other variables must be prefixed by the keyword 'var',
assignment is ':=', and statements must be separated by semicolons.
But Python can be as fast as SymbolicFunction; pull request #699
avoids copies between OT and Python, your code could be rewritten as
import numpy as np
def functionCrueSample(X) :
Q, Ks, Zv, Zm, Hd, Zb, L, B = np.array(X, copy=False).T
alpha = (Zm - Zv)/L
H = (Q/(Ks*B*np.sqrt(alpha)))**(3.0/5.0)
Zc = H + Zv
Zd = Zb + Hd
S = Zc - Zd;
Y = np.zeros((len(H), 2))
Y[:,0] = H
Y[:,1] = S
return Y
myFunction = PythonFunction(8, 2, func_sample=functionCrueSample)
Denis
2018-02-14 12:30 GMT+01:00 BAUDIN Michael <[email protected]>:
> Hi,
>
>
>
> I have a symbolic function that I would like to simplify and I do not see
> how.
>
>
>
> Here is the test case. The function has 8 inputs and 2 outputs. In Python it
> is simple to define :
>
>
>
> def functionCrue(X) :
>
> Q, Ks, Zv, Zm, Hd, Zb, L, B = X
>
> alpha = (Zm - Zv)/L
>
> H = (Q/(Ks*B*sqrt(alpha)))**(3.0/5.0)
>
> Zc = H + Zv
>
> Zd = Zb + Hd
>
> S = Zc - Zd
>
> return [H,S]
>
> myFunction = PythonFunction(8, 2, functionCrue)
>
>
>
> As you can see, the code is simplified by intermediate variables which are
> used by subsequent Python statements. For exemple, the slope of the river
> alpha is first computed, then the height H is computed depending on the
> slope. Then the variable S is computed based on Zc and Zd, where Zc is
> computed depending on the height H.
>
>
>
> When I define the function as a symbolic function, the current definition is
> more involved.
>
>
>
> inputs = ['Q', 'Ks', 'Zv', 'Zm', 'Hd', 'Zb', 'L', 'B']
>
> formulas = ['(Q/(Ks*B*sqrt((Zm - Zv)/L)))^(3.0/5.0)','(Q/(Ks*B*sqrt((Zm -
> Zv)/L)))^(3.0/5.0)+Zv-(Zb + Hd)']
>
> myFunction = SymbolicFunction(inputs, formulas)
>
>
>
> As you can see, I cannot reuse the value of the first output into the second
> output.
>
>
>
> The following interface would be much easier to use. The formulas variable
> is a list of couples, where the first item is the name of the output
> variable and the second item is the string to evaluate it.
>
>
>
> inputs = ['Q', 'Ks', 'Zv', 'Zm', 'Hd', 'Zb', 'L', 'B']
>
> output1 = [‘alpha’, '(Zm - Zv)/L']
>
> output2 = [‘H’, '(Q/(Ks*B*sqrt(alpha)))^(3.0/5.0)']
>
> output3 = [‘Zc’, 'H + Zv']
>
> output4 = [‘Zd’, 'Zb + Hd']
>
> output5 = [‘S’, 'Zc - Zd']
>
> formulas = [output1,output2,output3,output4,output5]
>
> myFunction = SymbolicFunction(inputs, formulas)
>
>
>
> Is there another way of doing this ? Do you agree that the suggestion is
> worth being developed ?
>
>
>
> Best regards,
>
>
>
> Michaël
>
>
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