Adding zero to my complex number class - python

I'm creating my own complex number class (not using Python's built in one) and I'm running into a problem when I try to add zero to my complex number. For reference this is the error:
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
File "display.py", line 25, in __init__
t.color(mandelbrot(c).getColor())
File "C:\Users\Joe\Desktop\Python\mandelbrot.py", line 10, in __init__
z = z*z + self.__starting_value
TypeError: unsupported operand type(s) for +: 'int' and 'complex'
Where self.__starting_value is the complex number.
The addition definition goes as follows:
class complex:
def __init__(self, a = 0, b = 0):
self.__real = float(a)
self.__imag = float(b)
def __add__(self, other):
return complex(self.__real + other.__real, self.__imag + other.__imag)
The solution should be simple enough but I am still learning Python and could use the help.

Two problems:
You are only handling addition of a complex object to a complex object, when you want to also be able to handle complex object + int.
When adding in this order (int + custom type), you need to add a reflected addition method (__radd__)
class complex:
def __init__(self, a = 0, b = 0):
self.__real = float(a)
self.__imag = float(b)
def __add__(self, other):
if isinstance(other, complex):
return complex(self.__real + other.__real, self.__imag + other.__imag)
else:
return complex(self.__real + other, self.__imag)
def __radd__(self, other):
return self + other
N.B.: It is considered bad style to shadow built-in names (like complex).

int + complex will first try to useint.__add__. complex + int will first try to use complex.__add__.
You need to implement complex.__radd__. See the related note in Emulating numeric types:
These functions are only called if the left operand does not support the corresponding operation and the operands are of different types.
You will need to handle the case where other is int in both complex.__add__ and complex.__radd__.

__add__ is for addition when the left-hand-side operand is of the type you're writing. When Python fails to call the int __add__ method, it tries __radd__. If you define __radd__ (with the same behavior), you'll get the result you want.

Related

How the python deal with add,sub,mul,div? [duplicate]

I have a vector class:
class Vector:
def __init__(self, x, y):
self.x, self.y = x, y
def __str__(self):
return '(%s,%s)' % (self.x, self.y)
def __add__(self, n):
if isinstance(n, (int, long, float)):
return Vector(self.x+n, self.y+n)
elif isinstance(n, Vector):
return Vector(self.x+n.x, self.y+n.y)
which works fine, i.e. I can write:
a = Vector(1,2)
print(a + 1) # prints (2,3)
However if the order of operation is reversed, then it fails:
a = Vector(1,2)
print(1 + a) # raises TypeError: unsupported operand type(s)
# for +: 'int' and 'instance'
I understand the error: the addition of an int object to an Vector object is undefined because I haven't defined it in the int class. Is there a way to work around this without defining it in the int (or parent of int) class?
You need to also define __radd__
Some operations do not necessarily evaluate like this a + b == b + a and that's why Python defines the add and radd methods.
Explaining myself better: it supports the fact that "int" does not define a + operation with class Vector instances as part of the operation. Therefore vector + 1 is not the same as 1 + vector.
When Python tries to see what the 1.__add__ method can do, an exception is raised. And Python goes and looks for Vector.__radd__ operation to try to complete it.
In the OP's case the evaluation is true and suffices with __radd__ = __add__
class Vector(object):
def __init__(self, x, y):
self.x, self.y = x, y
def __str__(self):
return '(%s,%s)' % (self.x, self.y)
def __add__(self, n):
if isinstance(n, (int, long, float)):
return Vector(self.x+n, self.y+n)
elif isinstance(n, Vector):
return Vector(self.x+n.x, self.y+n.y)
__radd__ = __add__
a = Vector(1, 2)
print(1 + a)
Which outputs:
(2,3)
The same applies to all number-like operations.
When you say x + y, Python calls x.__add__(y). If x does not implement __add__ (or that method returns NotImplemented), Python tries to call y.__radd__(x) as a fallback.
Thus all you have to do is to define the __radd__() method in your Vector class and 1 + y will work as you would expect.
Note: you would have to do similar for other operations too, e.g. implement __mul__() and __rmul__() pair, etc.
You might also want to look at this question, it explains the same principle in more details.
Update:
Depending on your use case, you might also want to implement the __iadd__() method (and its cousins) to override the += operator.
For example, if you say y += 1 (y being an instance of Vector here), you might want to modify the y instance itself, and not return a new Vector instance as a result, which what your __add__() method currently does.

Division in fraction calculator in python [duplicate]

I have a class called Time, and I need to implement a Frequency class. How can I implement dividing ints or floats by an instance of Time to get an instance of Frequency ?
I already know about __div__, __truediv__, __floordiv__ and other Python special methods, and I already use them in my code to divide instances of classes by numbers or instances of other classes, but I cannot find a way to divide a number by an instance of my class.
Is it possible to implement dividing a number by an instance of a class in Python ?
The __rtruediv__ method is what you're looking for.
When x / y is executed, if type(x) does not implement a __div__(self, other) method where other can be of class type(y), then type(y).__rtruediv__(y, x) is executed, and its result is returned.
Usage:
class Foo:
def __init__(self, x):
self.x = x
def __truediv__(self, other):
return self.x / other
def __rtruediv__(self, other):
return other / self.x
>>> f = Foo(10)
>>> f / 10
1.0
>>> 10 / f
1.0
Yes. You just have to make sure that Time.__rtruediv__() returns a Frequency instance when it receives a float or integer.
Usage:
>>> 100 / Time(2)
Frequency(50.0)
>>> 2.5 / Time(5)
Frequency(0.5)
Implementation:
class Time:
def __init__(self, value):
self.value = value
def __rtruediv__(self, other):
if not isinstance(other, (int, float)):
return NotImplemented
return Frequency(other / self.value)
class Frequency:
def __init__(self, value):
self.value = value
def __repr__(self):
return '{}({})'.format(self.__class__.__name__, self.value)
The python docs contains a full example on implementing the arithmetic operations for your custom classes.
The proper way to handle incompatible types is to return the special value NotImplemented.
NotImplemented
Special value which should be returned by the binary
special methods (e.g. __eq__(), __lt__(), __add__(), __rsub__(), etc.)
to indicate that the operation is not implemented with respect to the
other type
Suppose you try to use a unsupported complex number, returning NotImplemented will eventually cause a TypeError with a correct error message. (at least in python 3)
>>> 100j / Time(2)
Traceback (most recent call last):
File "python", line 1, in <module>
TypeError: unsupported operand type(s) for /: 'complex' and 'Time'
you need to implement __rtruediv__ and__rfloordiv__.
from the documentation
object.__radd__(self, other)
object.__rsub__(self, other)
object.__rmul__(self, other)
object.__rmatmul__(self, other)
object.__rtruediv__(self, other)
object.__rfloordiv__(self, other)
object.__rmod__(self, other)
object.__rdivmod__(self, other)
object.__rpow__(self, other)
object.__rlshift__(self, other)
object.__rrshift__(self, other)
object.__rand__(self, other)
object.__rxor__(self, other)
object.__ror__(self, other)
These methods are called to implement the binary arithmetic operations
(+, -, *, #, /, //, %, divmod(), pow(), **, <<, >>, &, ^, |) with
reflected (swapped) operands. These functions are only called if the
left operand does not support the corresponding operation [3] and the
operands are of different types. [4] For instance, to evaluate the
expression x - y, where y is an instance of a class that has an
__rsub__() method, y.__rsub__(x) is called if x.__sub__(y) returns NotImplemented.

Overloading operators for operands of different types in Python

Consider the following example of a 'wrapper' class to represent vectors:
class Vector:
def __init__(self, value):
self._vals = value.copy()
def __add__(self, other):
if isinstance(other, list):
result = [x+y for (x, y) in zip(self._vals, other)]
elif isinstance(other, Vector):
result = [x+y for (x, y) in zip(self._vals, other._vals)]
else:
# assume other is scalar
result = [x+other for x in self._vals]
return Vector(result)
def __str__(self):
return str(self._vals)
The __add__ method takes care of adding two vectors as well as adding a vector with a scalar. However, the second case is not complete as the following examples show:
>>> a = Vector([1.2, 3, 4])
>>> print(a)
[1.2, 3, 4]
>>> print(a+a)
[2.4, 6, 8]
>>> print(a+5)
[6.2, 8, 9]
>>> print(5+a)
Traceback (most recent call last):
File "<stdin>", line 1, in <module>
TypeError: unsupported operand type(s) for +: 'int' and 'Vector'
To my understanding the reason is that the overloaded operator only tells Python what to do when it sees a + x where a is an instance of Vector, but there is no indication of what to do for x + a (with a an instance of Vector and x a scalar).
How one should overload the operators in such circumstances to cover all cases (i.e., to support the case that self is not an instance of Vector but other is)?
Ok. I guess I found the answer: one has to overload __radd__ operator as well:
class Vector:
def __init__(self, value):
self._vals = value.copy()
def __add__(self, other):
if isinstance(other, list):
result = [x+y for (x, y) in zip(self._vals, other)]
elif isinstance(other, Vector):
result = [x+y for (x, y) in zip(self._vals, other._vals)]
else:
# assume other is scalar
result = [x+other for x in self._vals]
return Vector(result)
def __radd__(self, other):
return self + other
def __str__(self):
return str(self._vals)
Although to me this looks a bit redundant. (Why Python does not use the commutativity of addition by default, assuming __radd__(self, other) always returns self + other? Of course for special cases the user can override __radd__.)
You could define a Scalar class that has int as its base class.
Then override __add__ to do what you want.
class Scalar(int):
def __add__(self):
# do stuff
You already figured out you need to implement __radd__. This is an answer as to why this is so, and why you need to do this in addition to implementing __add__, as a Both quotes are taken from Python Docs (Data Model - 3.3.8 Emulating numeric types), starting with the obvious:
These methods are called to implement the binary arithmetic operations (+, -, *, #, /, //, %, divmod(), pow(), **, <<, >>, &, ^, |). For instance, to evaluate the expression x + y, where x is an instance of a class that has an __add__() method, x.__add__(y) is called.
So order determines which object's implementation of __add__ is called. When the method doesn't support the operation with the passed argument NotImplemented should be returned. That's where the so-called "reflected methods" come into play:
These functions are only called if the left operand does not support the corresponding operation and the operands are of different types. For instance, to evaluate the expression x - y, where y is an instance of a class that has an __rsub__() method, y.__rsub__(x) is called if x.__sub__(y) returns NotImplemented [sic].
Now, why wouldn't __radd__(self, other) just fall back to __add__(self, other)? While ring addition is always commutative (see this and this math.stackexchange answers), you could have algebraic structures that are do not satisfy this assumption (e.g., near-rings). But my guess as a non-mathematician would be that it's just desirable to have a consistent data model across different numerical methods. While addition might be commonly commutative, multiplication is less so. (Think matrices and vectors! Although, admittedly this is not the best example, given __matmul__). I also prefer to see there being no exceptions, especially if I had to read about rings, etc. in a language documentation.

Magic methods with > 1 operands between MyClass and standard Class

Imagine I want to define a new number class. Say, RationalFractions or GaussIntegers, whatever. Of course, I can easily define a + b for two objects of MyClass. But i would like to be able to add an object of MyClass with some existing, like "integer" or "float". With the result having a relevant type (from my point of view). E.g. the result of GaussInteger + float = GaussInteger, RationalFraction + integer = RationalFraction, etc.
I guess I should somehow alter add for Object class, or "integer", "float"? Or there is a way to do it without meddling with the existing classes?
Edit. So, an example:
class RatFr:
def __init__(self, m, n=1):
self.m = m
self.n = n
def __add__(self, other):
temp = (RatFr(other) if type(other) == int else other)
return RatFr(self.m * temp.n + self.n * temp.m, self.n * temp.n)
def __str__(self):
return f'{self.m}/{self.n}'
a = RatFr(5,3)
b = 1
print(a)
print(a + b)
print(b + a)
I get as a result:
5/3
8/3
Traceback (most recent call last):
File "/Users/aleksej/PycharmProjects/Alex2/playaround.py", line 19, in <module>
print(b + a)
TypeError: unsupported operand type(s) for +: 'int' and 'RatFr'
Trying to convert self does nothing good. As soon as the first operand is int, python obviously looks for integer add method.
Yes. You will want to override __add__ from object, taking self and say x as parameters. You can then deal with x according to its type. Here you have a few options. You can do explicit type checking, but this is not very Pythonic. I would probably make a conversion function to convert from int, float, etc to your type and call it on x. Then you can do whatever addition would do between two objects of your type. This sort of call to a conversion function before doing an operation is done in the mpmath library, in the backend. Remember that you will need to check if the thing you are converting is already the right type.

Overriding Commutative Operations For Same Class Operands in Python

I am trying to understand how operator overriding works for two operands of a custom class.
For instance, suppose I have the following:
class Adder:
def __init__(self, value=1):
self.data = value
def __add__(self,other):
print('using __add__()')
return self.data + other
def __radd__(self,other):
print('using __radd__()')
return other + self.data
I initialize the following variables:
x = Adder(5)
y = Adder(4)
And then proceed to do the following operations:
1 + x
using __radd__()
Out[108]: 6
x + 2
using __add__()
Out[109]: 7
The two operations above seem straigtforward. If a member of my custom class is to the right of the "+" in the addition expression, then __radd__ is used. If it is on the left, then __add__ is used. This works for expressions when one operand is of the Adder type and another one is something else.
When I do this, however, I get the following result:
x + y
using __add__()
using __radd__()
Out[110]: 9
As you can see, if both operands are of the custom class, then both __add__ and __radd__ are called.
My question is how does Python unravel this situation and how is it able to call both the right-hand-addition function, as well as the left-hand-addition function.
It's because inside your methods you add the data to other. This is itself an instance of Adder. So the logic goes:
call __add__ on x;
add x.data (an int) to y (an Adder instance)
ah, right-hand operand is an instance with a __radd__ method, so
call __radd__ on y;
add int to y.data (another int).
Usually you would check to see if other was an instance of your class, and if so add other.data rather than just other.
That's the because the implementation of your __add__ and __radd__ method do not give any special treatment to the instances of the Adder class. Therefore, each __add__ call leads to an integer plus Adder instance operation which further requires __radd__ due to the Adder instance on the right side.
You can resolve this by doing:
def __add__(self, other):
print('using __add__()')
if isinstance(other, Adder):
other = other.data
return self.data + other
def __radd__(self, other):
print('using __radd__()')
return self.__add__(other)

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