I came across some code with a line similar to
x[x<2]=0
Playing around with variations, I am still stuck on what this syntax does.
In general it could mean anything. It was already explained what it means if x is a list or numpy.ndarray but in general it only depends on how the comparison operators (<, >, ...) and also how the get/set-item ([...]-syntax) are implemented.
x.__getitem__(x.__lt__(2)) # this is what x[x < 2] means!
x.__setitem__(x.__lt__(2), 0) # this is what x[x < 2] = 0 means!
Because:
x < value is equivalent to x.__lt__(value)x[value] is (roughly) equivalent to x.__getitem__(value) x[value] = othervalue is (also roughly) equivalent to x.__setitem__(value, othervalue).This can be customized to do anything you want. Just as an example (mimics a bit numpys-boolean indexing):
class Test:
def __init__(self, value):
self.value = value
def __lt__(self, other):
# You could do anything in here. For example create a new list indicating if that
# element is less than the other value
res = [item < other for item in self.value]
return self.__class__(res)
def __repr__(self):
return '{0} ({1})'.format(self.__class__.__name__, self.value)
def __getitem__(self, item):
# If you index with an instance of this class use "boolean-indexing"
if isinstance(item, Test):
res = self.__class__([i for i, index in zip(self.value, item) if index])
return res
# Something else was given just try to use it on the value
return self.value[item]
def __setitem__(self, item, value):
if isinstance(item, Test):
self.value = [i if not index else value for i, index in zip(self.value, item)]
else:
self.value[item] = value
So now let's see what happens if you use it:
>>> a = Test([1,2,3])
>>> a
Test ([1, 2, 3])
>>> a < 2 # calls __lt__
Test ([True, False, False])
>>> a[Test([True, False, False])] # calls __getitem__
Test ([1])
>>> a[a < 2] # or short form
Test ([1])
>>> a[a < 2] = 0 # calls __setitem__
>>> a
Test ([0, 2, 3])
Notice this is just one possibility. You are free to implement almost everything you want.