Maple转Python
2021-11-10 本文已影响0人
Neural_PDE
ff := 6 i0_(x) u alpha + 3 u i0_(y) beta + 3 i0_(x) v beta
+ i0_i1i2i3 alpha + i0_i1i2i3 beta + i0_(t)
with(CodeGeneration);
Python(ff);
例子
For a description of the options used in the following examples, see CodeGenerationOptions.
with(CodeGeneration);
Translate a simple expression and assign it to the name
"w"
in the target code.
Python(-2*x*z + y*z + x, resultname = "w");
w = -2 * x * z + y * z + x
Translate a list and assign it to an array with the name
"w"
in the target code.
Python([[x, 2*y], [5, z]], resultname = "w");
w = [[x,2 * y],[5,z]]
Translate a computation sequence. Optimize the input first.
cs := [s = 1.0 + x, t = ln(s)*exp(-x), r = exp(-x) + x*t];
Python(cs, optimize);
s = 0.10e1 + x
t1 = math.log(s)
t2 = math.exp(-x)
t = t2 * t1
r = x * t + t2
Declare that
"x"
is a float and
"y"
is an integer. Return the result in a string.
s := Python(x + y + 1, declare = [x::float, y::'integer'], output = string);
s := "cg = x + y + 1
"
Translate a procedure. Assume that all untyped variables have type integer.
f := proc(x, y, z) return x*y-y*z+x*z; end proc:
Python(f, defaulttype = integer);
def f (x, y, z):
return(y * x - y * z + x * z)
Translate a procedure containing an implicit return. A new variable is created to hold the return value.
f := proc(n)
local x, i;
x := 0.0;
for i to n do
x := x + i;
end do;
end proc:
Python(f);
def f (n):
x = 0.0e0
for i in range(1, n + 1):
x = x + i
cgret = x
return(cgret)
Translate a linear combination of hyperbolic trigonometric functions.
Python(2*cosh(x) - 7*tanh(x));
cg0 = 2 * math.cosh(x) - 7 * math.tanh(x)
Translate a procedure with no return value containing a printf statement.
f := proc(a::integer, p::integer)
printf("The integer remainder of %d divided by %d is: %d\n", a, p, irem(a, p));
end proc:
Python(f);
def f (a, p):
printf("The integer remainder of %d divided by %d is: %d\n", a, p, a % p)
Translate a procedure involving linear algebra.
detHilbert := proc(M, n :: posint) uses LinearAlgebra;
return Determinant( HilbertMatrix( n ) );
end proc:
Python(detHilbert);
import numpy.linalg
import scipy.linalg
def detHilbert (M, n):
return(numpy.linalg.det(scipy.linalg.hilbert(n)))
Notice that by default CodeGeneration translates LinearAlgebra[Determinant] to the Python function numpy.linalg.det. However as the Python scipy.linalg library is already being used in the above example and also contains a implementation of the determinant, it may be simpler to use that translation. This may be achieved using the libraryorder option to indicate that scipy.linalg is preferred over numpy.linalg.
Python(detHilbert, libraryorder = ["scipy.linalg", "numpy.linalg"]);
import scipy.linalg
def detHilbert (M, n):
return(scipy.linalg.det(scipy.linalg.hilbert(n)))
Compatibility
• The CodeGeneration[Python] command was introduced in Maple 18.
For more information on Maple 18 changes, see Updates in Maple 18.