How can I translate this SageMath code to run in Python?

问题

What do I have to do to make this code run in Python? I got the code from here. If I run it in a SageMath workbook on CoCalc, it works with no adjustment needed. When I run it in Python after importing sage and numpy, I get various name and attribute errors.

def mean_x(factor, values):
    return sum([cos(2*pi*v/factor) for v in values])/len(values)

def mean_y(factor, values):
    return sum([sin(2*pi*v/factor) for v in values])/len(values)

def calculatePeriodAppeal(factor, values):
    mx = mean_x(factor, values)
    my = mean_y(factor, values)
    appeal = sqrt(mx^2+my^2)
    return appeal

def calculateBestLinear(factor, values):
    mx = mean_x(factor, values).n()
    my = mean_y(factor, values).n()
    y0 = factor*atan2(my,mx)/(2*pi).n()
    err = 1-sqrt(mx^2+my^2).n()
    return [factor*x + y0, err]

def calculateGCDAppeal(factor, values):
    mx = mean_x(factor, values)
    my = mean_y(factor, values)
    appeal = 1 - sqrt((mx-1)^2+my^2)/2
    return appeal

testSeq = [0,125,211,287,408,520,650,735,816,942,1060] 
gcd = calculateGCDAppeal(x,testSeq)
agcd = find_local_maximum(gcd,2,100)
print(agcd)
plot(gcd,(x,2,100))

回答1:

The first error is

RuntimeError: Use ** for exponentiation, not '^', which means xor
in Python, and has the wrong precedence.

Once that is fixed, there are various missing imports.

Find each of them with Sage's import_statements function.

sage: import_statements(x)
from sage.calculus.predefined import x

sage: import_statements(sum)
from sage.misc.functional import symbolic_sum

sage: import_statements(cos)
from sage.functions.trig import cos

sage: import_statements(sin)
from sage.functions.trig import sin

In the end the code might look like:

from sage.calculus.predefined import x
from sage.misc.functional import symbolic_sum as sum
from sage.functions.trig import cos, sin

def mean_x(factor, values):
    return sum(cos(2*pi*v/factor) for v in values) / len(values)

def mean_y(factor, values):
    return sum(sin(2*pi*v/factor) for v in values) / len(values)

def calculatePeriodAppeal(factor, values):
    mx = mean_x(factor, values)
    my = mean_y(factor, values)
    appeal = sqrt(mx**2 + my**2)
    return appeal

def calculateBestLinear(factor, values):
    mx = mean_x(factor, values).n()
    my = mean_y(factor, values).n()
    y0 = factor*atan2(my, mx)/(2*pi).n()
    err = 1-sqrt(mx**2 + my**2).n()
    return [factor*x + y0, err]

def calculateGCDAppeal(factor, values):
    mx = mean_x(factor, values)
    my = mean_y(factor, values)
    appeal = 1 - sqrt((mx - 1)**2 + my**2)/2
    return appeal

testSeq = [0, 125, 211, 287, 408, 520, 650, 735, 816, 942, 1060]
gcd = calculateGCDAppeal(x, testSeq)
agcd = find_local_maximum(gcd, 2, 100)
print(agcd)
plot(gcd, (x, 2, 100))

Search Ask Sage for "import_statements", some answers there go into more detail on this topic.

Search import_statements on Ask Sage

来源：https://stackoverflow.com/questions/63820416/how-can-i-translate-this-sagemath-code-to-run-in-python

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