python_sparse

import random
# Deepcopy is imported in order not to change the matrix a itself
from copy import deepcopy
def sparse_gen(num_row, num_col, spar):
    # Total number of elements
    nelem = num_row * num_col
    # Number of nonzero elements
    n_nonzero = int(nelem * spar)
    # Position of nonzero elements
    poselem = random.sample(range(nelem), n_nonzero)
    # Create an empty dictionary here
    spardict = {};
    # Add entries into the dictionary here  in a for loop
    for i in range(len(poselem)):
        # Create a string from the number in poselem and use it as a key
        key = str(poselem[i])
        # Select -1 or 1  randomly
        spardict[key]  = random.choice([-1,1])
    # Add the size of the matrix with the key value -1
    spardict['-1'] = [num_row, num_col]
    # Return the sparse matrix for reference later on
    return spardict
# Here is the function for addition of two matrices
def sparse_add(a, b):
    # First lets check if the matrix sizes are equal or not
    if a['-1'] != b['-1'] :
        print('Matrix sizes should be equal. Exiting!')
        return
    # Copy matrix a into matrix c the sum a + b = c
    c = deepcopy(a)
    # Delete the size info from  b and retrieve the keys
    del b['-1']
    bkeys = b.keys()
    # Write the for loop for summation iterating over keys of b
    for bkey in iter(bkeys):
        if (bkey in a):
            if ((c[bkey] + b[bkey]) == 0):
                del c[bkey]
                continue
            else:
                c[bkey] += b[bkey]
        else:
                c[bkey] = b[bkey]
    # Since it gives rise to problems later readd b['-1']
    b['-1'] = a['-1']
    return c
# The function for printing sparse matrices is defined here
def sparse_print(a):
    # Lets retrieve the size information first (rows, columns)
    # Remember the size information is a list
    nrow = a['-1'][0]
    ncol = a['-1'][1]
    # Lets write a for loop to print out the relevant info
    for i in range(nrow * ncol):
        # if the i is in a print that value otherwise print 0
        return_str = ""
        if str(i) in a:
            return_str += "%3d " %  a[str(i)]
        else:
            return_str += "%3d " % 0
        # Print new line if we hit the end of the row
        if ((i + 1) % nrow) == 0:
            return_str += "\n"
    return_str += "\n\n"# Two new line characters to avoid confusion
    return return_str
# The function for converting sparse matrices to full is defined here
def mat2sparse(a):
    spardict = {}
    num_row = len(a)
    num_col = len(a[0])
    nelem = num_row * num_col
    # Input the size information
    spardict['-1'] = [num_row, num_col]
    for i in range(num_row):
        for j in range(num_col):
            if a[i][j] != 0:
                # Calculate the position of the key
                key = str(i*num_col + j)
                spardict[key] = a[i][j]
    return spardict