Sparse Matrix Using Linked List

This is sparse matrix program. A matrix in which number of zeros are greater than half the size of matrix is known as sparse matrix.

Source Code:

class Node:
  def __init__(self,r,c,v):
    self.r=r
    self.c=c
    self.v=v
    self.next=None
class Sparse:
  def __init__(self):
    self.start=None
  def createlist(self,newnode):
    temp=self.start
    if self.start==None:
      self.start=newnode
    else:
      while temp.next!=None:
        temp=temp.next
      temp.next=newnode
  def display(self):
    temp=self.start
    print("row\tcol\tval")
    while temp!=None:
      print("%d\t%d\t%d" %(temp.r,temp.c,temp.v))
      temp=temp.next

row=int(input("enter number of rows : "))
col=int(input("enter number of coloumns : "))

X = [[0]*col for j in range(row)]
count=0
sp=Sparse()
print ("entry elements")
for i in range (row):
  for j in range (col): 
    X[i][j] = int(input())

print("matrix is:")
for i in range(row):
    for j in range(col):
        print(X[i][j], end=' ')
    print()

for i in range(row):
    for j in range(col):
        if X[i][j]==0:
            count=count+1

print("number of zeros:",count)

if count>(row*col)//2:
    print("sparse matrix")
    for i in range(row):
      for j in range(col):
        if X[i][j]!=0:
          newnode=Node(i,j,X[i][j])
          sp.createlist(newnode)       
    sp.display()
else:

    print("not sparse matrix")

Output:

Python 3.4.0 (v3.4.0:04f714765c13, Mar 16 2014, 19:24:06) [MSC v.1600 32 bit (Intel)] on win32

Type "copyright", "credits" or "license()" for more information.

>>> ================================ RESTART ================================

>>> 

enter number of rows : 3

enter number of coloumns : 3

entry elements

1

2

3

0

0

0

4

5

6

matrix is:

1 2 3 

0 0 0 

4 5 6 

number of zeros: 3

not sparse matrix

>>> ================================ RESTART ================================

>>> 

enter number of rows : 3

enter number of coloumns : 3

entry elements

1

2

3

0

0

0

0

0

4

matrix is:

1 2 3 

0 0 0 

0 0 4 

number of zeros: 5

sparse matrix

row col val

0 0 1

0 1 2

0 2 3

2 2 4

>>>

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