Here we explain the new features in the code nr2.py.
The code starts with the definition of functions. These definitions
are stored by Python and not executed until they are needed.
The first executable statement is at the very end of the code, namely
main()in the code above. When the main program needs to evaluate the functions
dfdx(x)control passes to them. Control passes back to the calling program when a function is finished.
We have used a full line of comment hashes
###### to mark
off the function definitions that start with the key word
def. This is not required, but it helps to find the
components of the code.
We have defined ``functions'' for evaluating the function and its
derivative, and we turned the ``main'' program into a function, as
well. This last step is not required. It is a matter of style. You
can also omit the
def main():, if you like, and the last
main() and undo the indentation of the main code.
The subprogram for evaluating the function takes only three lines:
The general pattern for the definition is
The comment explaining the purpose of the function is actually
optional, but I recommend you include it. Standard Python style puts
the comment line immediately after the
def line. (With
three quotes you may break a long string into multiple lines.)
The result of the subprogram
f is called its ``return
return statement in a function definition
has the general form
It causes the expression to be evaluated and the result handed back as
the return value of the function. You could also do it in two steps
with an intermediate variable:
pnewthe Python interpreter realizes that to evaluate the expression
f(p)/dfdx(p)in the main program, it has to hand over the current value of
pto the subprogram
f, which determines the value of the function for that value of
xand hands the result back to the main program. The compiler does the same for the derivative. Finally, it divides and subtracts the result from
p. We say that the main program ``calls'' the function subprograms. Each subprogram does its work and and then returns control to the calling program.
The function argument list (sometimes called the ``parameter list'')
specifies input and/or additional output values for the function. In
this case we have only one input value, which must be of numerical
type, and the output value is returned as the value of the function.
With more parameters, they are separated by commas. Here is what it
looks like with two:
def f(x, c):
"""Evaluate the function"""
return c*x - math.cos(x)
Of course, in that case we would have to call the function with
to get the same result as before.
We say that when the function is called, the input parameters are
``passed'' to the function. For the input parameters we can think of
this operation as an implied assignment. In this example we have,
x = p
c = 4
In the next lesson we make more precise sense of such implied
assignments when we discuss the concept of the ``scope'' of a
variable's definition. Note that in these implied assignments above,
that the names on the left-hand side (lhs) belong to the subprogram
and the names on the right-hand side (rhs) belong to the calling
The names of the subprogram arguments may differ from the names in the
calling program, but the purpose and data type must match in the
order given.convert among the base numeric types
The implied assignment can involve expressions. In the
quadratic.py example we could have written
math.sqrt(b*b - 4*a*c). The compiler evaluates the expression and
passes the result to
We will discuss function subprograms in greater depth in the next lesson.