You're technically trying to index an uninitialized array. You have to first initialize the outer list with lists before adding items; Python calls this "list comprehension".
# Creates a list containing 5 lists, each of 8 items, all set to 0
w, h = 8, 5
Matrix = [[0 for x in range(w)] for y in range(h)]
#You can now add items to the list:
Matrix[0][0] = 1
Matrix[6][0] = 3 # error! range...
Matrix[0][6] = 3 # valid
Note that the matrix is "y" address major, in other words, the "y index" comes before the "x index".
print Matrix[0][0] # prints 1
x, y = 0, 6
print Matrix[x][y] # prints 3; be careful with indexing!
Although you can name them as you wish, I look at it this way to avoid some confusion that could arise with the indexing, if you use "x" for both the inner and outer lists, and want a non-square Matrix.
Answer from Manny D on Stack OverflowNon-shitty languages:
int[] myArray = new int[5][5]
Python:
myArray = [[0]*5]*5
Next:
myArray[1][0] = 1
print(myArray[0][0])
Non-shitty languages:
0
Python:
1
python - How to define a two-dimensional array? - Stack Overflow
Need help with a two-dimensional array
Two dimensional array
Is a 2d array better than two parallel arrays in python?
Your data structure is more important than performance. and parallel arrays are a terrible idea.
[a, g, t, a, g, t] [t, c, g, a, t, c]
Consider what happens if you insert/remove an item from one array and they fall out of sync.
I'd argue the 2D array is a better data structure for what you need. I'd also argue that having each pair as it's own type is even better. Then each base pair is a single item in an array
DNA = [BasePair(a, t), BasePair(g, c), etc]More on reddit.com
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You're technically trying to index an uninitialized array. You have to first initialize the outer list with lists before adding items; Python calls this "list comprehension".
# Creates a list containing 5 lists, each of 8 items, all set to 0
w, h = 8, 5
Matrix = [[0 for x in range(w)] for y in range(h)]
#You can now add items to the list:
Matrix[0][0] = 1
Matrix[6][0] = 3 # error! range...
Matrix[0][6] = 3 # valid
Note that the matrix is "y" address major, in other words, the "y index" comes before the "x index".
print Matrix[0][0] # prints 1
x, y = 0, 6
print Matrix[x][y] # prints 3; be careful with indexing!
Although you can name them as you wish, I look at it this way to avoid some confusion that could arise with the indexing, if you use "x" for both the inner and outer lists, and want a non-square Matrix.
If you really want a matrix, you might be better off using numpy. Matrix operations in numpy most often use an array type with two dimensions. There are many ways to create a new array; one of the most useful is the zeros function, which takes a shape parameter and returns an array of the given shape, with the values initialized to zero:
>>> import numpy
>>> numpy.zeros((5, 5))
array([[ 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0.],
[ 0., 0., 0., 0., 0.]])
Here are some other ways to create 2-d arrays and matrices (with output removed for compactness):
numpy.arange(25).reshape((5, 5)) # create a 1-d range and reshape
numpy.array(range(25)).reshape((5, 5)) # pass a Python range and reshape
numpy.array([5] * 25).reshape((5, 5)) # pass a Python list and reshape
numpy.empty((5, 5)) # allocate, but don't initialize
numpy.ones((5, 5)) # initialize with ones
numpy provides a matrix type as well, but it is no longer recommended for any use, and may be removed from numpy in the future.