lambdify should not be needed to work with or create SymPy
expressions. Its purpose is to make a SymPy expression usable by other
libraries.
As I wrote, "dict shenanigans" were not needed. A MatrixSymbol is an
iterable. `zip(MatrixSymbol, array_of_values)` creates an iterator of
tuples, indicating what element is substituted by what value. A
natural thing to do in Python, I wouldn't look to replace it with
lambdify and DeferredVector (which apparently isn't removed because
everyone forgot about it).
On Mon, Mar 19, 2018 at 6:29 PM, Nico Schlömer <nico.schloe...@gmail.com> wrote:
> I see!
> I also noticed that I can use `DeferredVector`s instead of `MatrixSymbol`s
> to get avoid those dict shenanigans. This
> ```
> import numpy
> import sympy
>
> a = sympy.DeferredVector('a')
> b = sympy.DeferredVector('b')
>
> x = sympy.Symbol('x')
>
> P = (a[0] + a[1]*x) / (1 + b[0]*x + b[1]*x**2 + b[2]*x**3)
>
> val_a = numpy.random.rand(2)
> val_b = numpy.random.rand(3)
>
> Pa = sympy.lambdify((a, b), P)(val_a, val_b)
>
>
> print(P)
> print(Pa)
> ```
> works. It's a bit weird to create a lambdify only to call it straight away
> though. Also, I'm reading [1] that `DeferredVector` were once scheduled for
> removal? Probably outdated.
>
> [1] https://github.com/sympy/sympy/issues/6788
>
>
>
> On Monday, March 19, 2018 at 11:24:59 PM UTC+1, Leonid Kovalev wrote:
>>
>> P_a = P.subs(dict(zip(a, val_a)))
>>
>> returns
>>
>> (0.450033195586719*x + 0.829322314411828)/(x**3*b[2, 0] + x**2*b[1, 0] +
>> x*b[0, 0] + 1)
>>
>> You need to substitute individual MatrixElement objects like a[0], not the
>> MatrixSymbol itself (which isn't even present in the expression P).
>>
>>
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