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.
Examples:
>>> x = [1,2,3,4,5] >>> x[x<2] 1 >>> x[x<3] 1 >>> x[x>2] 2 >>> x[x<2]=0 >>> x [0, 2, 3, 4, 5]
0. if not i%2==0 can also be written as, if (i%2!=0) . i%2 gives the remainder obtained when i is divided by 2. So the expression stands true if the remainder of i when divided by 2 is not 0. Therefore, the expression stands true for all odd numbers because any odd number when divides with 2, leaves a remainder of 1.
== 0 means "equal to 0 (zero)". So if foo == 0: means "do the following if foo is equal to 0", thus if x % 2 == 0: means "do the following if x % 2 is equal to 0". Follow this answer to receive notifications.
Answer 54d752ae86f5529472005430 It means that the remainder must be equal to zero when that number is divided by 3. == means “equal to”.
x^2 means "x to the power of 2", i.e. "x squared".
This only makes sense with NumPy arrays. The behavior with lists is useless, and specific to Python 2 (not Python 3). You may want to double-check if the original object was indeed a NumPy array (see further below) and not a list.
But in your code here, x is a simple list.
Since
x < 2
is False i.e 0, therefore
x[x<2]
is x[0]
x[0]
gets changed.
Conversely, x[x>2]
is x[True]
or x[1]
So, x[1]
gets changed.
Why does this happen?
The rules for comparison are:
When you order two strings or two numeric types the ordering is done in the expected way (lexicographic ordering for string, numeric ordering for integers).
When you order a numeric and a non-numeric type, the numeric type comes first.
When you order two incompatible types where neither is numeric, they are ordered by the alphabetical order of their typenames:
So, we have the following order
numeric < list < string < tuple
See the accepted answer for How does Python compare string and int?.
If x is a NumPy array, then the syntax makes more sense because of boolean array indexing. In that case, x < 2
isn't a boolean at all; it's an array of booleans representing whether each element of x
was less than 2. x[x < 2] = 0
then selects the elements of x
that were less than 2 and sets those cells to 0. See Indexing.
>>> x = np.array([1., -1., -2., 3]) >>> x < 0 array([False, True, True, False], dtype=bool) >>> x[x < 0] += 20 # All elements < 0 get increased by 20 >>> x array([ 1., 19., 18., 3.]) # Only elements < 0 are affected
>>> x = [1,2,3,4,5] >>> x<2 False >>> x[False] 1 >>> x[True] 2
The bool is simply converted to an integer. The index is either 0 or 1.
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