The add and mul definitions here are nonsensical because of their dependence on returning self, causing infinite loops. If they create a new distribution using the lambdas then it works fine, as in my own answer below.
I'm just playing around with classes and overriding trying to build a small statistics tool. However, when I run this code I get stuck in a recursion loop inside the __mul__
call which is being run in the n1.pdf
call and I cannot figure out why. I think it has something to do with Python lazily executing the __mul__
instead of doing what I kind of 'wanted' (let's say in the language of CS) which was to create a new pointer to the old function call for pdf that is owned by the new pointer to pdf, and then to set the old pointer (the main .pdf pointer) to the new function.
I think this is quite poorly worded so edits extremely welcome if you understand what I'm asking.
import math
import random
class Distribution:
def __init__(self, pdf, cdf):
self.pdf = pdf
self.cdf = cdf
def pdf(self, x):
return self.pdf(x)
def cdf(self, x):
return self.cdf(x)
def __mul__(self, other):
if isinstance(other, float) or isinstance(other, int):
newpdf = lambda x : self.pdf(x) * other
self.pdf = newpdf
newcdf = lambda x : self.cdf(x) * other
self.cdf = newcdf
return self
else:
return NotImplemented
def __add__(self, other):
self.pdf = lambda x : self.pdf(x) other.pdf(x)
self.cdf = lambda x : self.cdf(x) other.cdf(x)
return Distribution(self.pdf, self.cdf)
class Normal(Distribution):
def __init__(self, mean, stdev):
self.mean = mean
self.stdev = stdev
def pdf(self, x):
return (1.0 / math.sqrt(2 * math.pi * self.stdev ** 2)) * math.exp(-0.5 * (x - self.mean) ** 2 / self.stdev ** 2)
def cdf(self, x):
return (1 math.erf((x - self.mean) / math.sqrt(2) / self.stdev)) / 2
def sample(self):
return self.mean self.stdev * math.sqrt(2) * math.cos(2 * math.pi * random.random())
if __name__ == "__main__":
n1 = Normal(1,2)
n1half = n1 * 0.5
x = n1.pdf(1)
print(x)
p.s. I know that it is no longer a pdf after being multiplied by 0.5, this is not an issue.
CodePudding user response:
class Distribution:
...
def pdf(self, x):
return self.pdf(x)
pdf()
calls itself, which calls itself, which calls itself... infinitely.
Same with cdf()
.
CodePudding user response:
Thanks for the help @John and @Tom and @bbbbbb... The problem was trying to return self instead of creating a new distribution. If I change the def'n of mul to
def __mul__(self, other):
if isinstance(other, float) or isinstance(other, int):
def newpdf(x):
return self.pdf(x) * other
def newcdf(x):
return self.cdf(x) * other
return Distribution(newpdf, newcdf)
else:
return NotImplemented
Then this solves this problem
CodePudding user response:
def pdf(self, x):
return self.pdf(x)
def cdf(self, x):
return self.cdf(x)
I assume your intent is to delegate to the attributes. Since they are always assigned, they will be found (assuming you do the lookup on an instance) instead of the class methods (which would straightforwardly be infinite recursion without those attributes); but this in turn means that these class methods are just useless. x.cdf(y)
, where cdf
is a callable instance attribute, just works; there is no need to provide a method as well.
newpdf = lambda x : self.pdf(x) * other
self.pdf = newpdf
I assume your intent is to create a new function that relies upon the existing value of self.pdf
. Unfortunately, it doesn't work that way. The problem is that the lambda is late binding. When it executes, that is the time at which it will look up self.pdf
... and find itself.
There is a separate problem here, in that you are writing __mul__
and __add__
implementations - that is, the *
and
operators, which are supposed to return a new value, and not mutate either operand. (If you wrote a = 3
and b = 4
and then c = a * b
, you would be extremely surprised if the values of a
or b
changed, yes?)
We can solve both problems at once, by simply using the computed pdf
and cdf
to create a new instance (which we need anyway):
def __mul__(self, other):
if isinstance(other, float) or isinstance(other, int):
newpdf = lambda x : self.pdf(x) * other
newcdf = lambda x : self.cdf(x) * other
return Distribution(newpdf, newcdf)
else:
return NotImplemented
Similarly, __add__
should use local variables, rather than modifying self
:
def __add__(self, other):
newpdf = lambda x : self.pdf(x) other.pdf(x)
newcdf = lambda x : self.cdf(x) other.cdf(x)
return Distribution(newpdf, newcdf)
Note that implementing these methods also gives you the augmented assignment operators *=
and =
(albeit by creating a new object and rebinding the name).
Let's test it:
if __name__ == "__main__":
n1 = Normal(1,2)
n1half = n1 * 0.5
print(n1.pdf(1))
print(n1half.pdf(1))
n1 = n1
print(n1.pdf(1))
I get:
>py test.py
0.19947114020071635
0.09973557010035818
0.3989422804014327