def wronskian(functions, var, method='bareis'):
 from .dense import Matrix
 for index in range(0, len(functions)):
  functions[index] = sympify(functions[index])
 n = len(functions)
 if (n == 0):
  return 1
 W = Matrix(n, n, (lambda i, j: functions[i].diff(var, j)))
 return W.det(method)

def wronskian ( functions , var , method = 'bareis' ) : from . dense import Matrix for index in range ( 0 , len ( functions ) ) : functions [ index ] = sympify ( functions [ index ] ) n = len ( functions ) if ( n == 0 ) : return 1 W = Matrix ( n , n , ( lambda i , j : functions [ i ] . diff ( var , j ) ) ) return W . det ( method )
compute wronskian for [] of functions | f1 f2 .