TypeError: unsupported operand type(s) for -: 'list' and 'list'

Question

I am trying to implement the Naive Gauss and getting the unsupported operand type error on execution. Output:

  execfile(filename, namespace)   File "/media/zax/MYLINUXLIVE/A0N-.py", line 26, in <module>     print Naive_Gauss([[2,3],[4,5]],[[6],[7]])   File "/media/zax/MYLINUXLIVE/A0N-.py", line 20, in Naive_Gauss     b[row] = b[row]-xmult*b[column] TypeError: unsupported operand type(s) for -: 'list' and 'list' >>>    

This is the code

def Naive_Gauss(Array,b):     n = len(Array)      for column in xrange(n-1):         for row in xrange(column+1, n):             xmult = Array[row][column] / Array[column][column]             Array[row][column] = xmult             #print Array[row][col]             for col in xrange(0, n):                 Array[row][col] = Array[row][col] - xmult*Array[column][col]             b[row] = b[row]-xmult*b[column]       print Array     print b  print Naive_Gauss([[2,3],[4,5]],[[6],[7]]) 

Answer 1

You can't subtract a list from a list.

>>> [3, 7] - [1, 2] Traceback (most recent call last):   File "<stdin>", line 1, in <module> TypeError: unsupported operand type(s) for -: 'list' and 'list' 

Simple way to do it is using numpy:

>>> import numpy as np >>> np.array([3, 7]) - np.array([1, 2]) array([2, 5]) 

You can also use list comprehension, but it will require changing code in the function:

>>> [a - b for a, b in zip([3, 7], [1, 2])] [2, 5] 

---

>>> import numpy as np >>> >>> def Naive_Gauss(Array,b): ...     n = len(Array) ...     for column in xrange(n-1): ...         for row in xrange(column+1, n): ...             xmult = Array[row][column] / Array[column][column] ...             Array[row][column] = xmult ...             #print Array[row][col] ...             for col in xrange(0, n): ...                 Array[row][col] = Array[row][col] - xmult*Array[column][col] ...             b[row] = b[row]-xmult*b[column] ...     print Array ...     print b ...     return Array, b  # <--- Without this, the function will return `None`. ... >>> print Naive_Gauss(np.array([[2,3],[4,5]]), ...                   np.array([[6],[7]])) [[ 2  3]  [-2 -1]] [[ 6]  [-5]] (array([[ 2,  3],        [-2, -1]]), array([[ 6],        [-5]]))