I was wondering what the use of the comma was when slicing Python arrays - I have an example that appears to work, but the line that looks weird to me is
p = 20*numpy.log10(numpy.abs(numpy.fft.rfft(data[:2048, 0])))
Now, I know that when slicing an array, the first number is start, the next is end, and the last is step, but what does the comma after the end number designate? Thanks.
It is being used to extract a specific column from a 2D array.
So your example would extract column 0 (the first column) from the first 2048 rows (0 to 2047). Note however that this syntax will only work for numpy arrays and not general python lists.
__getitem__ function. Python simply passes in the relevant arguments, but regular 2D lists won't know what to do with it. See more here stackoverflow.com/questions/21165751/…
Empirically - create an array using numpy
m = np.fromfunction(lambda i, j: (i +1)* 10 + j + 1, (9, 4), dtype=int)
which assigns an array like below to m
array(
[[11, 12, 13, 14],
[21, 22, 23, 24],
[31, 32, 33, 34],
[41, 42, 43, 44],
[51, 52, 53, 54],
[61, 62, 63, 64],
[71, 72, 73, 74],
[81, 82, 83, 84],
[91, 92, 93, 94]])
Now for the slice
m[:,0]
giving us
array([11, 21, 31, 41, 51, 61, 71, 81, 91])
I may have misinterpreted Khan Academy (so take with grain of salt):
In linear algebra terms,
m[:,n]is taking thenthcolumn vector of the matrixm
See Abhranil's note how this specific interpretation only applies to numpy
It slices with a tuple. What exactly the tuple means depends on the object being sliced. In NumPy arrays, it performs a m-dimensional slice on a n-dimensional array.
>>> class C(object):
... def __getitem__(self, val):
... print val
...
>>> c = C()
>>> c[1:2,3:4]
(slice(1, 2, None), slice(3, 4, None))
>>> c[5:6,7]
(slice(5, 6, None), 7)
__getitem__, and that, together with either of the other answers, explains the use of the comma in the array index.