The semester is already ending, so Danil made an effort and decided to visit a lesson on harmony analysis to know how does the professor look like, at least. Danil was very bored on this lesson until the teacher gave the group a simple task: find 4 vectors in 4-dimensional space, such that every coordinate of every vector is 1 or  - 1 and any two vectors are orthogonal. Just as a reminder, two vectors in *n*-dimensional space are considered to be orthogonal if and only if their scalar product is equal to zero, that is: 

Danil quickly managed to come up with the solution for this problem and the teacher noticed that the problem can be solved in a more general case for 2<sup class="upper-index">*k*</sup> vectors in 2<sup class="upper-index">*k*</sup>-dimensinoal space. When Danil came home, he quickly came up with the solution for this problem. Can you cope with it?
The only line of the input contains a single integer *k* (0 ≤ *k* ≤ 9).
Consider all scalar products in example:
 -  Vectors 1 and 2: ( + 1)·( + 1) + ( + 1)·( - 1) + ( - 1)·( + 1) + ( - 1)·( - 1) = 0 -  Vectors 1 and 3: ( + 1)·( + 1) + ( + 1)·( + 1) + ( - 1)·( + 1) + ( - 1)·( + 1) = 0 -  Vectors 1 and 4: ( + 1)·( + 1) + ( + 1)·( - 1) + ( - 1)·( - 1) + ( - 1)·( + 1) = 0 -  Vectors 2 and 3: ( + 1)·( + 1) + ( - 1)·( + 1) + ( + 1)·( + 1) + ( - 1)·( + 1) = 0 -  Vectors 2 and 4: ( + 1)·( + 1) + ( - 1)·( - 1) + ( + 1)·( - 1) + ( - 1)·( + 1) = 0 -  Vectors 3 and 4: ( + 1)·( + 1) + ( + 1)·( - 1) + ( + 1)·( - 1) + ( + 1)·( + 1) = 0
2
++++
+*+*
++**
+**+
1
++
+*
3
++++++++
+*+*+*+*
++**++**
+**++**+
++++****
+*+**+*+
++****++
+**+*++*
0
+
4
++++++++++++++++
+*+*+*+*+*+*+*+*
++**++**++**++**
+**++**++**++**+
++++****++++****
+*+**+*++*+**+*+
++****++++****++
+**+*++*+**+*++*
++++++++********
+*+*+*+**+*+*+*+
++**++****++**++
+**++**+*++**++*
++++********++++
+*+**+*+*+*++*+*
++****++**++++**
+**+*++**++*+**+
5
++++++++++++++++++++++++++++++++
+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*
++**++**++**++**++**++**++**++**
+**++**++**++**++**++**++**++**+
++++****++++****++++****++++****
+*+**+*++*+**+*++*+**+*++*+**+*+
++****++++****++++****++++****++
+**+*++*+**+*++*+**+*++*+**+*++*
++++++++********++++++++********
+*+*+*+**+*+*+*++*+*+*+**+*+*+*+
++**++****++**++++**++****++**++
+**++**+*++**++*+**++**+*++**++*
++++********++++++++********++++
+*+**+*+*+*++*+*+*+**+*+*+*++*+*
++****++**++++**++****++**++++**
+...
6
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*
++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**
+**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**+
++++****++++****++++****++++****++++****++++****++++****++++****
+*+**+*++*+**+*++*+**+*++*+**+*++*+**+*++*+**+*++*+**+*++*+**+*+
++****++++****++++****++++****++++****++++****++++****++++****++
+**+*++*+**+*++*+**+*++*+**+*++*+**+*++*+**+*++*+...
7
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*
++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**
+**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++**++...
8
++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+*+...
9
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++...
"""
The semester is already ending, so Danil made an effort and decided to visit a lesson on harmony analysis to know how does the professor look like, at least. 
Danil was very bored on this lesson until the teacher gave the group a simple task: find 4 vectors in 4-dimensional space, such that every coordinate of every 
vector is 1 or -1 and any two vectors are orthogonal. Just as a reminder, two vectors in n-dimensional space are considered to be orthogonal if and only if 
their scalar product is equal to zero.

Danil quickly managed to come up with the solution for this problem and the teacher noticed that the problem can be solved in a more general case for 2k vectors 
in 2k-dimensinoal space. When Danil came home, he quickly came up with the solution for this problem. Can you cope with it?

Input
The only line of the input contains a single integer k (0≤k≤9).

Output
Print 2k lines consisting of 2k characters each. The j-th character of the i-th line must be equal to '*' if the j-th coordinate of the i-th vector is equal to -1, and must be equal to '+' if it's equal to +1. It's guaranteed that the answer always exists.

If there are many correct answers, print any.

Exapmles

input:
2

output:
++**
+*+*
++++
+**+

Tutorial Solution:

    Recrusive definition/Recurrence relation of the Hadamard Matrix:

                   H(1<<(k-1))  H(1<<(k-1))  
        H(1<<k) = 
                   H(1<<(k-1)) -H(1<<(k-1))

        H(1<<0) = 1

How and why does this translate to a solution to the problem?
"""
import numpy as np

k = int(input())
dim = 1<<k

# 'False' = '+' = 1 ; 'True' = '*' = -1 ;
key = ['+','*']

# res = [[False for j in range(dim)] for i in range(dim)]
# for s in range(k):
#     d = 1<<s
#     for i in range(d<<1):
#         for j in range(d<<1):
#             flag = (i>>s) & (j>>s)
#             res[i][j] = flag ^ res[i%d][j%d]

res = np.array([[False]])
for s in range(k):
    res = np.concatenate((np.concatenate((res,res),axis=1),np.concatenate((res,~res),axis=1)),axis=0)

for i in range(dim):
    for j in range(dim):
        print(key[int(res[i][j])],end='')
    print()


