Matrix in python
Question:
I am very new to Python, I need to read numbers from a file and store them in a matrix like I would do it in fortran or C;
for i
for j
data[i][j][0]=read(0)
data[i][j][1]=read(1)
data[i][j][2]=read(2)
...
...
How can I do the same in Python? I read a bit but got confused with tuples and similar things
If you could point me to a similar example it would be great
thanks
Answers:
It depends on your file format, but take a look on:
Link
and
http://docs.scipy.org/doc/scipy/reference/tutorial/io.html
Python doesn’t come with multi-dimensional arrays, though you can add them through the popular numpy third-party package. If you want to avoid third-party packages, what you would do in Python would be to use a list of lists of lists (each "list" being a 1-D "vector-like" sequence, which can hold items of any type).
For example:
data = [ [ [0 for i in range(4)] for j in range(5)] for k in range(6)]
this makes a list of 6 items which are lists of 5 items which are lists of 4 0’s — i.e., a 6 x 5 x 4 "3D matrix" which you could then address the way you want,
for i in range(6):
for j in range(5):
data[i][j][0]=read(0)
data[i][j][1]=read(1)
data[i][j][2]=read(2)
to initialize the first three of the four items on each most-nested sublist with calls to that mysterious function read which presumably you want to write yourself (I have no idea what it’s supposed to do — not "read and return the next number" since it takes a mysterious argument, but, then what?).
A simple example would be:
data = []
with open(_filename_, 'r') as f:
for line in f:
data.append([int(x) for x in line.split()])
You may want to use numpy and use the built in function for using I/O, in particular loadtxt.
http://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html
There are a lot of addictional functions to handle I/O:
Matrices are two dimensional structures. In plain Python, the most natural representation of a matrix is as a list of lists.
So, you can write a row matrix as:
[[1, 2, 3, 4]]
And write a column matrix as:
[[1],
[2],
[3],
[4]]
This extends nicely to m x n matrices as well:
[[10, 20],
[30, 40],
[50, 60]]
See matfunc.py for an example of how to develop a full matrix package in pure Python.
The documentation for it is here.
And here is a worked-out example of doing matrix multiplication in plain python using a list-of-lists representation:
>>> from pprint import pprint
>>> def mmul(A, B):
nr_a, nc_a = len(A), len(A[0])
nr_b, nc_b = len(B), len(B[0])
if nc_a != nr_b:
raise ValueError('Mismatched rows and columns')
return [[sum(A[i][k] * B[k][j] for k in range(nc_a))
for j in range(nc_b)] for i in range(nr_a)]
>>> A = [[1, 2, 3, 4]]
>>> B = [[1],
[2],
[3],
[4]]
>>> pprint(mmul(A, B))
[[30]]
>>> pprint(mmul(B, A), width=20)
[[1, 2, 3, 4],
[2, 4, 6, 8],
[3, 6, 9, 12],
[4, 8, 12, 16]]
As another respondent mentioned, if you get serious about doing matrix work, it would behoove you to install numpy which has direct support for many matrix operations:
A way to extend the list in a form to work like matrix. I have gone through other codes of matrix in python, all are using comprehensions to first initialize a list of required size and then update the values (which takes a little more time).
Let the r represents row and c for column.
r = input('Enter row size: ')
c = input('Enter column size: ')
m = []
for i in range(r):
m.append([])
for j in range(c):
m[i].append(input())
for i in m:
print i
Here, you can input the elements of matrix as it was in ‘C’ or equivalent languages. Hope this may help someone a different view of implementing matrices.
I am very new to Python, I need to read numbers from a file and store them in a matrix like I would do it in fortran or C;
for i
for j
data[i][j][0]=read(0)
data[i][j][1]=read(1)
data[i][j][2]=read(2)
...
...
How can I do the same in Python? I read a bit but got confused with tuples and similar things
If you could point me to a similar example it would be great
thanks
It depends on your file format, but take a look on:
Link
and
http://docs.scipy.org/doc/scipy/reference/tutorial/io.html
Python doesn’t come with multi-dimensional arrays, though you can add them through the popular numpy third-party package. If you want to avoid third-party packages, what you would do in Python would be to use a list of lists of lists (each "list" being a 1-D "vector-like" sequence, which can hold items of any type).
For example:
data = [ [ [0 for i in range(4)] for j in range(5)] for k in range(6)]
this makes a list of 6 items which are lists of 5 items which are lists of 4 0’s — i.e., a 6 x 5 x 4 "3D matrix" which you could then address the way you want,
for i in range(6):
for j in range(5):
data[i][j][0]=read(0)
data[i][j][1]=read(1)
data[i][j][2]=read(2)
to initialize the first three of the four items on each most-nested sublist with calls to that mysterious function read which presumably you want to write yourself (I have no idea what it’s supposed to do — not "read and return the next number" since it takes a mysterious argument, but, then what?).
A simple example would be:
data = []
with open(_filename_, 'r') as f:
for line in f:
data.append([int(x) for x in line.split()])
You may want to use numpy and use the built in function for using I/O, in particular loadtxt.
http://docs.scipy.org/doc/numpy/reference/generated/numpy.loadtxt.html
There are a lot of addictional functions to handle I/O:
Matrices are two dimensional structures. In plain Python, the most natural representation of a matrix is as a list of lists.
So, you can write a row matrix as:
[[1, 2, 3, 4]]
And write a column matrix as:
[[1],
[2],
[3],
[4]]
This extends nicely to m x n matrices as well:
[[10, 20],
[30, 40],
[50, 60]]
See matfunc.py for an example of how to develop a full matrix package in pure Python.
The documentation for it is here.
And here is a worked-out example of doing matrix multiplication in plain python using a list-of-lists representation:
>>> from pprint import pprint
>>> def mmul(A, B):
nr_a, nc_a = len(A), len(A[0])
nr_b, nc_b = len(B), len(B[0])
if nc_a != nr_b:
raise ValueError('Mismatched rows and columns')
return [[sum(A[i][k] * B[k][j] for k in range(nc_a))
for j in range(nc_b)] for i in range(nr_a)]
>>> A = [[1, 2, 3, 4]]
>>> B = [[1],
[2],
[3],
[4]]
>>> pprint(mmul(A, B))
[[30]]
>>> pprint(mmul(B, A), width=20)
[[1, 2, 3, 4],
[2, 4, 6, 8],
[3, 6, 9, 12],
[4, 8, 12, 16]]
As another respondent mentioned, if you get serious about doing matrix work, it would behoove you to install numpy which has direct support for many matrix operations:
A way to extend the list in a form to work like matrix. I have gone through other codes of matrix in python, all are using comprehensions to first initialize a list of required size and then update the values (which takes a little more time).
Let the r represents row and c for column.
r = input('Enter row size: ')
c = input('Enter column size: ')
m = []
for i in range(r):
m.append([])
for j in range(c):
m[i].append(input())
for i in m:
print i
Here, you can input the elements of matrix as it was in ‘C’ or equivalent languages. Hope this may help someone a different view of implementing matrices.