Python reads the file and converts it to a matrix __python

Code Flow:

1. read the data from the file .
2. Convert the data into a matrix form.
3. For the matrix processing .

The specific Python code is as follows :
-The file path needs to be set correctly.
-String processing.
-The conversion of a string array to an integer array. ( nums = [Int (x) for x in Nums])
-The construction of matrices. (matrix = Np.array (nums))
-The NumPy module has a great advantage in matrix processing.

List Contents

#-*-Coding:utf-8-*-
import NumPy as NP
def readFile (path):
    # Open File (note path)
    f = open (path)
    # to process row by line 
  first_ele = True for
    the data in F.readlines ():
        # # Remove line breaks for each line, ' \ n '
        data = Data.strip (' \ n ')
        # # to split by space.
        nums = Data.split ("")
        # # is added to the matrix.
        if First_ele:
            ### Converts a string to integer data
            nums = [Int (x) for x in Nums]
            ### joins the matrix.
            matrix = Np.array (nums)
            First_ele = False
        else:
            nums = [Int (x) for x in nums]
            matrix = Np.c_[mat Rix,nums]
    Dealmatrix (matrix)
    F.close ()

def dealmatrix (Matrix):
    # # some basic processing.
    print "Transpose The matrix"
    matrix = matrix.transpose ()
    print matrix

    print "Matrix Trace"
    Print Np.trace (matrix)

# test.
if __name__ = = ' __main__ ':
    readFile ("Matrix")

The contents of the matrix file are as follows:

0 0 0 1 1 0 1 0 1 0 1 1 1 1-1 1

python constructs a matrix of m* n

-Generate matrices by way of a list (array).
-The matrix does not apply to sparse matrices. (sparse matrices are not constructed like this)
-Note: If the volume of data is particularly large, this method is equivalent to loading all the things in the matrix into memory, and if the row reaches 10000 +, it is best to consider using sparse matrices. (easy to appear Memoryerror)
-The operation of sparse matrices should also be considered.

Related code:

def fixed_matrix (Row,col): return
    [[0 to I in range (COL)] for J in range (row)]