SymPy dsolve with a parameter gives a wrong answer when the parameter is zero



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1















My Code



I have a program that calculates the solutions to a 2nd-order differential equation, like in the code snippet below:



import sympy as sp
print('sympy version:', sp.__version__)

t = sp.symbols('t', real=True, nonnegative=True)
n = sp.symbols('n', integer=True, nonnegative=True)
f = sp.symbols('f', cls=sp.Function)

diff_eq = sp.Eq(f(t).diff(t, 2) + n**2*f(t), 0)

print('general solution:', sp.dsolve(diff_eq, f(t)))
print('solution at n=0 (pre-subs):', sp.dsolve(diff_eq.subs(n, 0), f(t)))
print('solution at n=0 (post-subs):', sp.dsolve(diff_eq, f(t)).subs(n, 0))


Results:




sympy version: 1.3



general solution: Eq(f(t), C1*sin(n*t) + C2*cos(n*t))



solution at n=0 (pre-subs): Eq(f(t), C1 + C2*t)



solution at n=0 (post-subs): Eq(f(t), C2)




My Problem



The solution form for a general n does not seem to accurately describe the specific solution form for n=0. Specifically, using dsolve first and subs(n, 0) second produces different results than using subs(n, 0) first and dsolve second, even though the two should be logically equivalent.



Can somebody explain the reason for the discrepancy in my results? Am I doing something wrong, or is this a bug?










share|improve this question






























    1















    My Code



    I have a program that calculates the solutions to a 2nd-order differential equation, like in the code snippet below:



    import sympy as sp
    print('sympy version:', sp.__version__)

    t = sp.symbols('t', real=True, nonnegative=True)
    n = sp.symbols('n', integer=True, nonnegative=True)
    f = sp.symbols('f', cls=sp.Function)

    diff_eq = sp.Eq(f(t).diff(t, 2) + n**2*f(t), 0)

    print('general solution:', sp.dsolve(diff_eq, f(t)))
    print('solution at n=0 (pre-subs):', sp.dsolve(diff_eq.subs(n, 0), f(t)))
    print('solution at n=0 (post-subs):', sp.dsolve(diff_eq, f(t)).subs(n, 0))


    Results:




    sympy version: 1.3



    general solution: Eq(f(t), C1*sin(n*t) + C2*cos(n*t))



    solution at n=0 (pre-subs): Eq(f(t), C1 + C2*t)



    solution at n=0 (post-subs): Eq(f(t), C2)




    My Problem



    The solution form for a general n does not seem to accurately describe the specific solution form for n=0. Specifically, using dsolve first and subs(n, 0) second produces different results than using subs(n, 0) first and dsolve second, even though the two should be logically equivalent.



    Can somebody explain the reason for the discrepancy in my results? Am I doing something wrong, or is this a bug?










    share|improve this question


























      1












      1








      1








      My Code



      I have a program that calculates the solutions to a 2nd-order differential equation, like in the code snippet below:



      import sympy as sp
      print('sympy version:', sp.__version__)

      t = sp.symbols('t', real=True, nonnegative=True)
      n = sp.symbols('n', integer=True, nonnegative=True)
      f = sp.symbols('f', cls=sp.Function)

      diff_eq = sp.Eq(f(t).diff(t, 2) + n**2*f(t), 0)

      print('general solution:', sp.dsolve(diff_eq, f(t)))
      print('solution at n=0 (pre-subs):', sp.dsolve(diff_eq.subs(n, 0), f(t)))
      print('solution at n=0 (post-subs):', sp.dsolve(diff_eq, f(t)).subs(n, 0))


      Results:




      sympy version: 1.3



      general solution: Eq(f(t), C1*sin(n*t) + C2*cos(n*t))



      solution at n=0 (pre-subs): Eq(f(t), C1 + C2*t)



      solution at n=0 (post-subs): Eq(f(t), C2)




      My Problem



      The solution form for a general n does not seem to accurately describe the specific solution form for n=0. Specifically, using dsolve first and subs(n, 0) second produces different results than using subs(n, 0) first and dsolve second, even though the two should be logically equivalent.



      Can somebody explain the reason for the discrepancy in my results? Am I doing something wrong, or is this a bug?










      share|improve this question
















      My Code



      I have a program that calculates the solutions to a 2nd-order differential equation, like in the code snippet below:



      import sympy as sp
      print('sympy version:', sp.__version__)

      t = sp.symbols('t', real=True, nonnegative=True)
      n = sp.symbols('n', integer=True, nonnegative=True)
      f = sp.symbols('f', cls=sp.Function)

      diff_eq = sp.Eq(f(t).diff(t, 2) + n**2*f(t), 0)

      print('general solution:', sp.dsolve(diff_eq, f(t)))
      print('solution at n=0 (pre-subs):', sp.dsolve(diff_eq.subs(n, 0), f(t)))
      print('solution at n=0 (post-subs):', sp.dsolve(diff_eq, f(t)).subs(n, 0))


      Results:




      sympy version: 1.3



      general solution: Eq(f(t), C1*sin(n*t) + C2*cos(n*t))



      solution at n=0 (pre-subs): Eq(f(t), C1 + C2*t)



      solution at n=0 (post-subs): Eq(f(t), C2)




      My Problem



      The solution form for a general n does not seem to accurately describe the specific solution form for n=0. Specifically, using dsolve first and subs(n, 0) second produces different results than using subs(n, 0) first and dsolve second, even though the two should be logically equivalent.



      Can somebody explain the reason for the discrepancy in my results? Am I doing something wrong, or is this a bug?







      python sympy






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      edited Nov 15 '18 at 1:18







      user6655984

















      asked Nov 14 '18 at 7:28









      CrepeGoatCrepeGoat

      958915




      958915






















          1 Answer
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          It can be considered a bug in dsolve logic: it finds two eigenvalues n and -n and treats them as different without considering the special case n=0 when they are equal. Ideally it would output a Piecewise like the following code does.



          sol_nonzero = sp.dsolve(diff_eq, f(t)).rhs
          sol_zero = sp.dsolve(diff_eq.subs(n, 0), f(t)).rhs
          sol_complete = sp.Piecewise((sol_nonzero, sp.Ne(n, 0)), (sol_zero, True))
          print('general solution:', sol_complete)
          print('solution at n=0:', sol_complete.subs(n, 0))


          This prints



          general solution: Piecewise((C1*sin(n*t) + C2*cos(n*t), Ne(n, 0)), (C1 + C2*t, True))
          solution at n=0: C1 + C2*t


          A more familiar mathematical form is provided by sp.pprint(sol_complete).



          ⎧C₁⋅sin(n⋅t) + C₂⋅cos(n⋅t) for n ≠ 0

          ⎩ C₁ + C₂⋅t otherwise





          share|improve this answer























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            It can be considered a bug in dsolve logic: it finds two eigenvalues n and -n and treats them as different without considering the special case n=0 when they are equal. Ideally it would output a Piecewise like the following code does.



            sol_nonzero = sp.dsolve(diff_eq, f(t)).rhs
            sol_zero = sp.dsolve(diff_eq.subs(n, 0), f(t)).rhs
            sol_complete = sp.Piecewise((sol_nonzero, sp.Ne(n, 0)), (sol_zero, True))
            print('general solution:', sol_complete)
            print('solution at n=0:', sol_complete.subs(n, 0))


            This prints



            general solution: Piecewise((C1*sin(n*t) + C2*cos(n*t), Ne(n, 0)), (C1 + C2*t, True))
            solution at n=0: C1 + C2*t


            A more familiar mathematical form is provided by sp.pprint(sol_complete).



            ⎧C₁⋅sin(n⋅t) + C₂⋅cos(n⋅t) for n ≠ 0

            ⎩ C₁ + C₂⋅t otherwise





            share|improve this answer



























              1














              It can be considered a bug in dsolve logic: it finds two eigenvalues n and -n and treats them as different without considering the special case n=0 when they are equal. Ideally it would output a Piecewise like the following code does.



              sol_nonzero = sp.dsolve(diff_eq, f(t)).rhs
              sol_zero = sp.dsolve(diff_eq.subs(n, 0), f(t)).rhs
              sol_complete = sp.Piecewise((sol_nonzero, sp.Ne(n, 0)), (sol_zero, True))
              print('general solution:', sol_complete)
              print('solution at n=0:', sol_complete.subs(n, 0))


              This prints



              general solution: Piecewise((C1*sin(n*t) + C2*cos(n*t), Ne(n, 0)), (C1 + C2*t, True))
              solution at n=0: C1 + C2*t


              A more familiar mathematical form is provided by sp.pprint(sol_complete).



              ⎧C₁⋅sin(n⋅t) + C₂⋅cos(n⋅t) for n ≠ 0

              ⎩ C₁ + C₂⋅t otherwise





              share|improve this answer

























                1












                1








                1







                It can be considered a bug in dsolve logic: it finds two eigenvalues n and -n and treats them as different without considering the special case n=0 when they are equal. Ideally it would output a Piecewise like the following code does.



                sol_nonzero = sp.dsolve(diff_eq, f(t)).rhs
                sol_zero = sp.dsolve(diff_eq.subs(n, 0), f(t)).rhs
                sol_complete = sp.Piecewise((sol_nonzero, sp.Ne(n, 0)), (sol_zero, True))
                print('general solution:', sol_complete)
                print('solution at n=0:', sol_complete.subs(n, 0))


                This prints



                general solution: Piecewise((C1*sin(n*t) + C2*cos(n*t), Ne(n, 0)), (C1 + C2*t, True))
                solution at n=0: C1 + C2*t


                A more familiar mathematical form is provided by sp.pprint(sol_complete).



                ⎧C₁⋅sin(n⋅t) + C₂⋅cos(n⋅t) for n ≠ 0

                ⎩ C₁ + C₂⋅t otherwise





                share|improve this answer













                It can be considered a bug in dsolve logic: it finds two eigenvalues n and -n and treats them as different without considering the special case n=0 when they are equal. Ideally it would output a Piecewise like the following code does.



                sol_nonzero = sp.dsolve(diff_eq, f(t)).rhs
                sol_zero = sp.dsolve(diff_eq.subs(n, 0), f(t)).rhs
                sol_complete = sp.Piecewise((sol_nonzero, sp.Ne(n, 0)), (sol_zero, True))
                print('general solution:', sol_complete)
                print('solution at n=0:', sol_complete.subs(n, 0))


                This prints



                general solution: Piecewise((C1*sin(n*t) + C2*cos(n*t), Ne(n, 0)), (C1 + C2*t, True))
                solution at n=0: C1 + C2*t


                A more familiar mathematical form is provided by sp.pprint(sol_complete).



                ⎧C₁⋅sin(n⋅t) + C₂⋅cos(n⋅t) for n ≠ 0

                ⎩ C₁ + C₂⋅t otherwise






                share|improve this answer












                share|improve this answer



                share|improve this answer










                answered Nov 15 '18 at 1:26







                user6655984




































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