I have to print this python code in a 5x5 array the array should look like this :
0 1 4 (infinity) 3
1 0 2 (infinity) 4
4 2 0 1 5
(inf)(inf) 1 0 3
3 4 5 3 0can anyone help me print this table? using indices.
for k in range(n): for i in range(n): for j in range(n): if A[i][k]+A[k][j]<A[i][j]: A[i][j]=A[i][k]+A[k][j]7 Answers
A combination of list comprehensions and str joins can do the job:
inf = float('inf')
A = [[0,1,4,inf,3], [1,0,2,inf,4], [4,2,0,1,5], [inf,inf,1,0,3], [3,4,5,3,0]]
print('\n'.join([''.join(['{:4}'.format(item) for item in row]) for row in A]))yields
0 1 4 inf 3 1 0 2 inf 4 4 2 0 1 5 inf inf 1 0 3 3 4 5 3 0Using for-loops with indices is usually avoidable in Python, and is not considered "Pythonic" because it is less readable than its Pythonic cousin (see below). However, you could do this:
for i in range(n): for j in range(n): print '{:4}'.format(A[i][j]), printThe more Pythonic cousin would be:
for row in A: for val in row: print '{:4}'.format(val), printHowever, this uses 30 print statements, whereas my original answer uses just one.
3There is always the easy way.
import numpy as np
print(np.matrix(A))for i in A: print('\t'.join(map(str, i)))I used numpy to generate the array, but list of lists array should work similarly.
import numpy as np
def printArray(args): print "\t".join(args)
n = 10
Array = np.zeros(shape=(n,n)).astype('int')
for row in Array: printArray([str(x) for x in row])If you want to only print certain indices:
import numpy as np
def printArray(args): print "\t".join(args)
n = 10
Array = np.zeros(shape=(n,n)).astype('int')
i_indices = [1,2,3]
j_indices = [2,3,4]
for i in i_indices:printArray([str(Array[i][j]) for j in j_indices])print(mat.__str__())where mat is variable refering to your matrix object
1using indices, for loops and formatting:
import numpy as np
def printMatrix(a): print "Matrix["+("%d" %a.shape[0])+"]["+("%d" %a.shape[1])+"]" rows = a.shape[0] cols = a.shape[1] for i in range(0,rows): for j in range(0,cols): print "%6.f" %a[i,j], print print
def printMatrixE(a): print "Matrix["+("%d" %a.shape[0])+"]["+("%d" %a.shape[1])+"]" rows = a.shape[0] cols = a.shape[1] for i in range(0,rows): for j in range(0,cols): print("%6.3f" %a[i,j]), print print
inf = float('inf')
A = np.array( [[0,1.,4.,inf,3], [1,0,2,inf,4], [4,2,0,1,5], [inf,inf,1,0,3], [3,4,5,3,0]])
printMatrix(A)
printMatrixE(A) which yields the output:
Matrix[5][5] 0 1 4 inf 3 1 0 2 inf 4 4 2 0 1 5 inf inf 1 0 3 3 4 5 3 0
Matrix[5][5] 0.000 1.000 4.000 inf 3.000 1.000 0.000 2.000 inf 4.000 4.000 2.000 0.000 1.000 5.000 inf inf 1.000 0.000 3.000 3.000 4.000 5.000 3.000 0.000In addition to the simple print answer, you can actually customise the print output through the use of the numpy.set_printoptions function.
Prerequisites:
>>> import numpy as np
>>> inf = np.float('inf')
>>> A = np.array([[0,1,4,inf,3],[1,0,2,inf,4],[4,2,0,1,5],[inf,inf,1,0,3],[3,4,5,3,0]])The following option:
>>> np.set_printoptions(infstr="(infinity)")Results in:
>>> print(A)
[[ 0. 1. 4. (infinity) 3.] [ 1. 0. 2. (infinity) 4.] [ 4. 2. 0. 1. 5.] [(infinity) (infinity) 1. 0. 3.] [ 3. 4. 5. 3. 0.]]The following option:
>>> np.set_printoptions(formatter={'float': "\t{: 0.0f}\t".format})Results in:
>>> print(A)
[[ 0 1 4 inf 3 ] [ 1 0 2 inf 4 ] [ 4 2 0 1 5 ] [ inf inf 1 0 3 ] [ 3 4 5 3 0 ]]If you just want to have a specific string output for a specific array, the function numpy.array2string is also available.
