I am unsure how to first of all correct this problem of missing required positional arguments, but after this I am trying to set changeable default values for n, s, x and y. I apologize if this question seems stupid, but I am new and appreciate any and all help.
import math
class RegularPolygon:
def __init__(self, n, s, x, y):
self.n = 3
self.side = 1
self.x = 0
self.y = 0
def getN(self, n):
self.n = n
return self.n
def getSide(self, s):
self.side = s
return self.side
def getX(self, x):
self.x = x
return self.x
def getY(self, y):
self.y = y
return self.y
def getPerimeter(self, n , s):
self.perimeter = n * s
return self.perimeter
def getArea(self, n, s):
self.area = (n * math.pow(s, 2)) / ( 4 * math.tan(math.pi / n))
return self.area
The error:
Traceback (most recent call last):
File "C:\Pythonstuff\Ch.7\chapter07_unittests.py", line 7, in setUp
self.poly1 = RegularPolygon()
TypeError: __init__() missing 4 required positional arguments: 'n', 's', 'x', and 'y'
You need to pass values when creating a RegularPolygon object:
c = RegularPolygon(100, 100, 100, 100)
You are now probably writing:
c = RegularPolygon()
In this class there are four positional arguments and you're not passing any now. As none of these parameters have a default value they're all required so you need to specify exactly four values in this case.
Related
'why code always print True.whenever i check for equal but not print the given string always print boolean'
class Coordinates:
def __init__(self,x,y):
self.x = x
self.y = y
def __sub__(self,other):
first = self.x-other.x
second = self.y-other.y
return (first,second)
def __mul__(self,other):
first = self.x*other.x
second = self.y*other.y
return (first,second)
def __eq__(self,other):
if self in other:
return 'The calculated coordinates are the same.'
else:
return 'The calculated coordinates are NOT the same.'
p1 = Coordinates(int(input()),int(input()))
p2 = Coordinates(int(input()),int(input()))
p4 = p1 - p2
print(p4)
p5 = p1 * p2
print(p5)
p6 = (p4 == p5)
print(p6)
'last line==>> print(p6)'
Type of p4 and p5 is tuple. They are not instances of the Coordinates class, so when you compare them you get a True or False. If your __sub__() and __mul__() methods returned an instance of Coordinates class instead of just a tuple, the equality comparison would return one of the strings you've written there.
EDIT: Replace your class with this and it will work:
class Coordinates:
def __init__(self, x, y):
self.x = x
self.y = y
def __sub__(self,other):
first = self.x - other.x
second = self.y - other.y
return Coordinates(first, second)
def __mul__(self, other):
first = self.x * other.x
second = self.y * other.y
return Coordinates(first, second)
def __repr__(self):
return f'({self.x}, {self.y})'
def __eq__(self, other):
if self.x == other.x and self.y == other.y:
return 'The calculated coordinates are the same.'
else:
return 'The calculated coordinates are NOT the same.'
please find below a piece of code from Coursera online course (lecture 2.3) on functional programming in Scala.
package week2
import math.abs
object lecture2_3_next {
def fixedPoint(f: Double => Double)(firstGuess: Double): Double = {
val tolerance = 0.0001
def isCloseEnough(x: Double, y: Double): Boolean = abs((x - y) / x) / x < tolerance
def iterate(guess: Double): Double = {
val next = f(guess)
if (isCloseEnough(guess, next)) next
else iterate(next)
}
iterate(firstGuess)
}
def averageDamp(f: Double => Double)(x: Double): Double = (x + f(x)) / 2
def sqrt(x: Double): Double = fixedPoint(averageDamp(y => x / y))(1)
sqrt(2)
}
A few points blocked me while I'm trying to understand this piece of code.
I'd like your help to understanding this code.
The 2 points that annoying me are :
- when you call averageDamp, there are 2 parameters 'x' and 'y' in the function passed (eg. averageDamp(y => x / y)) but you never specify the 'y' parameter in the definition of the averageDamp function (eg. def averageDamp(f: Double => Double)(x: Double): Double = (x + f(x)) / 2). Where and how do the scala compiler evaluate the 'y' parameter.
- second point may be related to the first, I don't know in fact. When I call the averageDamp function, I pass only the function 'f' parameter (eg. y => x / y) but I don't pass the second parameter of the function which is 'x' (eg. (x: Double) second parameter). How the scala compiler is evaluating the 'x' parameter in this case to render the result of the averageDamp call.
I think I missed something about the evaluation or substitution model of scala and functional programming.
Thank's for your help and happy new year !
Hervé
1) You don't pass an x and an y parameter as f, you pass a function. The function is defined as y => x / y, where y is just a placeholder for the argument of this function, while x is a fixed value in this context, as it is given as argument for the sqrt method (in the example x is 2). Instead of the fancy lambda-syntax, you could write as well
def sqrt(x: Double): Double = fixedPoint(averageDamp(
new Function1[Double,Double] {
def apply(y:Double):Double = x / y
}
))(1)
Nothing magic about this, just an abbreviation.
2) When you have a second parameter list, and don't use it when calling the method, you do something called "currying", and you get back a partial function. Consider
def add(x:Int)(y:Int) = x + y
If you call it as add(2)(3), everything is "normal", and you get back 5. But if you call add(2), the second argument is still "missing", and you get back a function expecting this missing second argument, so you have something like y => 2 + y
The x is not a parameter of the (anonymous) function, it is a parameter of the function sqrt. For the anonymous function it is a bound closure.
To make it more obvious, let's rewrite it and use a named instead of an anonymous function:
def sqrt(x: Double): Double = fixedPoint(averageDamp(y => x / y))(1)
will can be rewritten as this:
def sqrt(x: Double): Double = {
def funcForSqrt(y: Double) : Double = x / y // Note that x is not a parameter of funcForSqrt
// Use the function fundForSqrt as a parameter of averageDamp
fixedPoint(averageDamp(funcForSqrt))(1)
}
In this function "f" :
def f(x: => Int) : Int = x * x * x //> f: (x: => Int)Int
var y = 0 //> y : Int = 0
f {
y += 1
println("invoked")
y
} //> invoked
//| invoked
//| invoked
//| res0: Int = 6
"f" is invoked same amount of times as "x" parameter is multiplied.
But why is function invoked multiple times ?
Should "f" not expand to 1 * 1 * 1 not 1 * 2 * 3 ?
Your x is not a function, it is a by-name parameter, and its type is a parameterless method type.
Parameterless method type means the same as def x, something that is evaluated every time you reference it. By reference, we mean x and not x.apply() or x().
The expression you're passing to your function f is evaluated every time x is referenced in f. That expression is the whole thing in braces, a block expression. A block is a sequence of statements followed by the result expression at the end.
Here's another explanation: https://stackoverflow.com/a/13337382/1296806
But let's not call it a function, even if it behaves like one under the covers.
Here is the language used in the spec:
http://www.scala-lang.org/files/archive/spec/2.11/04-basic-declarations-and-definitions.html#by-name-parameters
It's not a value type because you can't write val i: => Int.
It was a big deal when they changed the implementation so you could pass a by-name arg to another method without evaluating it first. There was never a question that you can pass function values around like that. For example:
scala> def k(y: => Int) = 8
k: (y: => Int)Int
scala> def f(x: => Int) = k(x) // this used to evaluate x
f: (x: => Int)Int
scala> f { println("hi") ; 42 }
res8: Int = 8
An exception was made to "preserve the by-name behavior" of the incoming x.
This mattered to people because of eta expansion:
scala> def k(y: => Int)(z: Int) = y + y + z
k: (y: => Int)(z: Int)Int
scala> def f(x: => Int) = k(x)(_) // normally, evaluate what you can now
f: (x: => Int)Int => Int
scala> val g = f { println("hi") ; 42 }
g: Int => Int = <function1>
scala> g(6)
hi
hi
res11: Int = 90
The question is how many greetings do you expect?
More quirks:
scala> def f(x: => Int) = (1 to 5) foreach (_ => x)
f: (x: => Int)Unit
scala> def g(x: () => Int) = (1 to 5) foreach (_ => x())
g: (x: () => Int)Unit
scala> var y = 0
y: Int = 0
scala> y = 0 ; f { y += 1 ; println("hi") ; y }
hi
hi
hi
hi
hi
y: Int = 5
scala> y = 0 ; g { y += 1 ; println("hi") ; () => y }
hi
y: Int = 1
scala> y = 0 ; g { () => y += 1 ; println("hi") ; y }
hi
hi
hi
hi
hi
y: Int = 5
Functions don't cause this problem:
scala> object X { def f(i: Int) = i ; def f(i: => Int) = i+1 }
defined object X
scala> X.f(0)
res12: Int = 0
scala> trait Y { def f(i: Int) = i }
defined trait Y
scala> object X extends Y { def f(i: => Int) = i+1 }
defined object X
scala> X.f(0)
<console>:11: error: ambiguous reference to overloaded definition,
both method f in object X of type (i: => Int)Int
and method f in trait Y of type (i: Int)Int
match argument types (Int)
X.f(0)
^
Compare method types:
http://www.scala-lang.org/files/archive/spec/2.11/03-types.html#method-types
This is not a pedantic distinction; irrespective of the current implementation, it can be confusing to think of a by-name parameter as "really" a function.
Another way of saying what has already been said is that inside f you invoke the function x three times. The first time it increments the y var and returns 1. The second time it again increments y returning 2 and the third time it again increments y and returns 3.
If you want it invoked only once then you may want to do something like this:
def f(x: => Int) : Int = x * x * x
var y = 0
lazy val xx = {
y += 1
println("invoked")
y
}
f {xx}
This will print 'invoked' only once and result in a returned value of 1.
x: T means need a T value.
x: => T means need a T value, but it is call by name.
x: () => T This means need a function given nothing to T
However, this question is not related to the difference between function and method.
The reason is call by name is invoked every time you try to use it.
change to call by value def f(x: Int) : Int, it will only invoke once.
Because you increment y by 1 every time the argument is used inside f
The result which your function f() returns is changing, because there is a global variable that is incremented with every subsequent call to that function.
the x in f(x: => Int) is interpreted as "some function that returns Int". So it has to be called 3 times to evaluate the x*x*x expression. With every call, you increment the global variable and return the result, which is how you arrive at three subsequent natural numbers (because the global variable is initialized to 0). Hence 1*2*3.
I have my own class
class Point():
def __init__(self, x, y):
self.x = x
self.y = y
I need to make working in, for example this should return true:
s = set()
s.add(Point(5,5))
b = Point(5,5)
print(b in s)
You don't override in specifically, you make your type hashable in the right way and many capabilities (including but not limited to set.__contains__) start to work. When you just want to consider equality over a set of attributes, the easiest way is to delegate to tuples:
class Point:
def __init__(self, x, y):
self.x = x
self.y = y
def __eq__(self, other):
return self.x == other.x and self.y == other.y
def __hash__(self):
return hash((self.x, self.y))
Note however that you can't sensibly mutate a Point once it's been inserted. Because mutation changes the hash value (according to this new definition of __hash__), you "lose access" to prior values, and basically leak them:
p = Point(1, 2)
s = {p}
p.x = 3
assert p not in s
# ... even though ...
assert list(s)[0] == p
Even more insidious: Sometimes it might work by chance, due to hash collisions.
Let me clarify my question by example. This is a standard exponentiation algorithm written with tail recursion in Scala:
def power(x: Double, y: Int): Double = {
def sqr(z: Double): Double = z * z
def loop(xx: Double, yy: Int): Double =
if (yy == 0) xx
else if (yy % 2 == 0) sqr(loop(xx, yy / 2))
else loop(xx * x, yy - 1)
loop(1.0, y)
}
Here sqr method is used to produce the square of loop's result. It doesn't look like a good idea - to define a special function for such a simple operation. But, we can't write just loop(..) * loop(..) instead, since it doubles the calculations.
We also can write it with val and without sqr function:
def power(x: Double, y: Int): Double = {
def loop(xx: Double, yy: Int): Double =
if (yy == 0) xx
else if (yy % 2 == 0) { val s = loop(xx, yy / 2); s * s }
else loop(xx * x, yy - 1)
loop(1.0, y)
}
I can't say that it looks better then variant with sqr, since it uses state variable. The first case is more functional the second way is more Scala-friendly.
Anyway, my question is how to deal with cases when you need to postprocess function's result? Maybe Scala has some other ways to achieve that?
You are using the law that
x^(2n) = x^n * x^n
But this is the same as
x^n * x^n = (x*x)^n
Hence, to avoid squaring after recursion, the value in the case where y is even should be like displayed below in the code listing.
This way, tail-calling will be possible. Here is the full code (not knowing Scala, I hope I get the syntax right by analogy):
def power(x: Double, y: Int): Double = {
def loop(xx: Double, acc: Double, yy: Int): Double =
if (yy == 0) acc
else if (yy % 2 == 0) loop(xx*xx, acc, yy / 2)
else loop(xx, acc * xx, yy - 1)
loop(x, 1.0, y)
}
Here it is in a Haskell like language:
power2 x n = loop x 1 n
where
loop x a 0 = a
loop x a n = if odd n then loop x (a*x) (n-1)
else loop (x*x) a (n `quot` 2)
You could use a "forward pipe". I've got this idea from here: Cache an intermediate variable in an one-liner.
So
val s = loop(xx, yy / 2); s * s
could be rewritten to
loop(xx, yy / 2) |> (s => s * s)
using an implicit conversion like this
implicit class PipedObject[A](value: A) {
def |>[B](f: A => B): B = f(value)
}
As Petr has pointed out: Using an implicit value class
object PipedObjectContainer {
implicit class PipedObject[A](val value: A) extends AnyVal {
def |>[B](f: A => B): B = f(value)
}
}
to be used like this
import PipedObjectContainer._
loop(xx, yy / 2) |> (s => s * s)
is better, since it does not need a temporary instance (requires Scala >= 2.10).
In my comment I pointed out that your implementations can't be tail call optimised, because in the case where yy % 2 == 0, there is a recursive call that is not in tail position. So, for a large input, this can overflow the stack.
A general solution to this is to trampoline your function, replacing recursive calls with data which can be mapped over with "post-processing" such as sqr. The result is then computed by an interpreter, which steps through the return values, storing them on the heap rather than the stack.
The Scalaz library provides an implementation of the data types and interpreter.
import scalaz.Free.Trampoline, scalaz.Trampoline._
def sqr(z: Double): Double = z * z
def power(x: Double, y: Int): Double = {
def loop(xx: Double, yy: Int): Trampoline[Double] =
if (yy == 0)
done(xx)
else if (yy % 2 == 0)
suspend(loop(xx, yy / 2)) map sqr
else
suspend(loop(xx * x, yy - 1))
loop(1.0, y).run
}
There is a considerable performance hit for doing this, though. In this particular case, I would use Igno's solution to avoid the need to call sqr at all. But, the technique described above can be useful when you can't make such optimisations to your algorithm.
In this particular case
No need for utility functions
No need for obtuse piping / implicits
Only need a single standalone recursive call at end - to always give tail recursion
def power(x: Double, y: Int): Double =
if (y == 0) x
else {
val evenPower = y % 2 == 0
power(if (evenPower) x * x else x, if (evenPower) y / 2 else y - 1)
}