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simulate the spiral shape pattern in the matrix

We have a matrix with dimensions n and n (n is an odd number and the user enters it) Write a program to simulate the spiral shape pattern in the matrix.
The pattern is such that starting from the central part of the matrix, whose value is equal to zero, 1 unit to the right and up (odd number) and then 2 We move the unit left and down (even number) and repeat this pattern n-1 times according to whether the number is even or odd. 0 to n-1 to be replaced according to the pattern)
6 6 6 6 6 6 5
6 4 4 4 4 3 5
6 4 2 2 1 3 5
6 4 2 0 1 3 5
6 4 2 3 3 3 5
6 4 5 5 5 5 5
6 7 7 7 7 7 7

First of all we get a number from user then assuming you have to draw the spiral out. Start by generating a list of the sequence (from the center to the end) , then write a function to put that list into the spiral
bellow link can explain it in more detail.
I change the directions of it's solution.
newbedev.com/creating-a-spiral-array-in-python
NORTH, S, W, E = (0, 1), (0, -1), (-1, 0), (1, 0) # directions
turn_left = {NORTH: E, E: S, S: W, W: NORTH} # old -> new direction
def spiral(width, height, matrixList):
if width < 1 or height < 1:
raise ValueError
x, y = width // 2, height // 2 # start near the center
dx, dy = NORTH # initial direction
matrix = [[None] * width for _ in range(height)]
count = 0
while True:
matrix[y][x] = matrixList[count] # visit
count += 1
# try to turn left
new_dx, new_dy = turn_left[dx, dy]
new_x, new_y = x + new_dx, y + new_dy
if (0 <= new_x < width and 0 <= new_y < height and
matrix[new_y][new_x] is None): # can turn left
x, y = new_x, new_y
dx, dy = new_dx, new_dy
else: # try to move straight
x, y = x + dx, y + dy
if not (0 <= x < width and 0 <= y < height):
return matrix # nowhere to go
def print_matrix(matrix):
width = len(str(max(el for row in matrix for el in row if el is not None)))
fmt = "{:0%dd}" % width
for row in matrix:
print(" ".join("_"*width if el is None else fmt.format(el)
for el in row))
n = int(input())
totalRecord = n*n
numberOfOccurance = 2
numberOfOccuranceIndex = 1
number = 1
index = 1
row = [0]
while index < totalRecord:
while numberOfOccuranceIndex <= numberOfOccurance:
row.append(number)
index += 1
numberOfOccuranceIndex += 1
if index >= totalRecord:
break
numberOfOccurance += 2
numberOfOccuranceIndex = 1
number += 1
print_matrix(spiral(n, n,row))

How to find figures with even areas

We have shape with n angles and its coordinates. I need to divide that figure into 2 figures with the same area. Division is performed in parallel to the axis y. The task is to find such x-coordinate, which would comply with the terms.
Test,E.g
4 (n angles)
0 0
0 2
2 2
2 0
The output must be 1
I wrote
n = int(input())
coordinates = []
for i in range(n):
x,y = map(int,input().split())
coordinates.append([x,y])
s = 0
for i in range(len(coordinates)-1):
s += coordinates[i][0]*coordinates[i+1][1]
s -= coordinates[i][1]*coordinates[i+1][0]
s = s/2
x = 0
print(s)
And after that I don't have any ideas what to do next..

How can I recursively divide the grid in my maze?

I am trying to create a maze generator using recursive division. I use this link:
Maze generation - recursive division (how it works?) as my guide as to how to approach the problem.
Here is my code so far:
import random
# Maze: 0 - N : 4 x 4 Grid
# Grid: 0 - (2n + 1) : 9 x 9 Array
# TODO: Now, Find a way to save the previous walls and not just only one at a time
rows = 9
cols = 9
start = 2
end = 7
# -------------------------------------------------------------------------------------
# Lists for all even / odd numbers in given range
evens = [n for n in range(start, end+1) if n % 2 == 0]
odds = [m for m in range(start, end+1) if m % 2 != 0]
# Generate random even/odd integer value for walls/ passages respectively
# Walls: Not sure if 2 variables are necessary-----------------------------------------
wallX = random.choice(evens)
wallY = random.choice(evens)
# Passages
passageX = random.choice(odds)
passageY = random.choice(odds)
#--------------------------------------------------------------------------------------
# Random direction: True = Horizontal Slice, False = Vertical Slice
randomDirection = random.choice([True, False])
arr = [['0' for i in range(cols)] for j in range(rows)]
def displayBoard(arr):
print()
for i in range(len(arr)):
for j in range(len(arr[i])):
# Print just the edges
if i == 0 or i == 8 or j == 0 or j == 8:
print('*', end = ' ')
# Print wall
elif arr[i][j] == 1:
print('.', end = ' ')
else:
print (' ', end = ' ')
print()
# Function choose direction to slice
def chooseDir(arr):
for i in range(len(arr)):
for j in range(len(arr[i])):
# Horizontal Direction Slice
if randomDirection:
arr[wallX][j] = 1
arr[wallX][passageY] = 2
print(arr[i][j], end = ' ')
# Vertical Slice
else:
arr[i][wallY] = 1
arr[passageX][wallY] = 2
print(arr[i][j], end = ' ')
print()
displayBoard(arr)
print()
mazeX = 0
mazeY = 0
# Write the recursive division function:
def divide():
chooseDir(arr)
print()
divide()
What this produces is a grid that is randomly sliced at an even index (creating walls) and creates passages at odd indices.
Output: 1 = wall, 2 = passage made
0 0 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0
0 0 0 0 2 0 0 0 0
0 0 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0
0 0 0 0 1 0 0 0 0
* * * * * * * * *
* . *
* . *
* *
* . *
* . *
* . *
* . *
* * * * * * * * *
My issue is that I don't know how to write my recursive function. Do I call division on the two new cells created when a wall is made and continuously divide the "sub cells".
Or I know that a 4 x 4 cell grid will provide an array of 9 x 9 and I will have 16 cells total.
Then I can call division until a certain condition is met, increment to the next cell until all 16 were visited.
In both cases, I am not sure how to represent the new walls/cells created so that I can write the division function. Up until now, I've been using the grid coordinates.

You asked "Do I call division on the two new cells created when a wall is made and continuously divide the "sub cells"". Yes, that is the essence of recursion. Take a big problem and make smaller problem(s). Repeat with the smaller problems. Eventually, the problems are small enough to easily solve. Then put all the small problems back together to solve the original problem.
For the maze, the first wall split the maze into two smaller mazes. Use the same algorithm to split each of them and there are not 4 smaller mazes. Repeat until the sub-mazes are too small to split any more.
Your code that splits the maze should go in a function. If the sub-maze is big enough to split, the function splits the sub-maze and then calls itself on the two smaller sub-mazes.

Find all paths of length 2 in a graph

I've tried to create an algorithm for finding all paths of length 2, but it doesn't seem to work properly:
input_split = input().split(' ')
node_count = int(input_split[0])
input_count = int(input_split[1])
items = np.zeros((node_count, node_count), dtype=np.int32) # matrix of adjacency
for j in range(input_count):
split = input().split(' ')
x = int(split[0]) - 1 # convert 1 based coordinates to 0 based
y = int(split[1]) - 1
items[x][y] = 1
items[y][x] = 1
result = np.linalg.matrix_power(items, 2)
result_sum = int(np.sum(result) / 2) # reverse paths are counted only once
print(result_sum)
Sample input:
6 7
1 2
2 3
3 1
2 4
4 5
5 6
6 2
The result should be 11, but it prints 18.

You're on the right track when calculating the square of the adjacency matrix. After the exponentiation you would get result matrix that looks like this:
[[2 1 1 1 0 1]
[1 4 1 0 2 0]
[1 1 2 1 0 1]
[1 0 1 2 0 2]
[0 2 0 0 2 0]
[1 0 1 2 0 2]]
First you need to exclude all diagonal entries from this matrix, because those denote walks that are not paths, as their starting and ending node is the same. Note that for length 2 that is the only way how nodes can be repeating.
The other entries need to be counted only once, because of symmetry. So only look at the upper right triangle of the matrix.
One way to do it is:
result_sum = 0
for i in range(input_count - 1):
for j in range(i + 1, input_count - 1):
result_sum += result[i][j]
print(result_sum) # prints 11
More Pythonic way, one-liner using numpy.trace():
result_sum = (np.sum(result) - np.trace(result)) // 2

You are calculating walks, which would include walks 6-7-6 (which is not a P2)
this discussion might help:
https://math.stackexchange.com/questions/1890620/finding-path-lengths-by-the-power-of-adjacency-matrix-of-an-undirected-graph

Kadane's Algorithm for 2D array with known boundaries

I have implemented the Kadane's algorithm for a 2D array in Python 2 with known boundaries, but I'm using the implementation for an online contest and the time it takes is more than the time given.
So that made me think if there is maybe another algorithm similar to Kadane's that has a smaller complexity, or if my code can be optimized in a way. My implementation works for any array with dimensions N x M and a subarray with dimensions maxRows x maxCols.
maxSumSubarray.py
import numpy as np
# returns the maximum sum for the given vector using kadane's algorithm, with
# maxRows maximum members in the sum
def kadane1DwithBounds(maxRows):
global temp
m = s = sum(temp[i] for i in xrange(maxRows))
k = 0
for i in xrange(1, N - maxRows + 1):
s -= temp[k]
s += temp[maxRows + i - 1]
k += 1
m = max(m, s)
return m
# prints the maximum "area" given by the values of an NxM array inside a
# subarray with dimensions maxRows x maxCols. temp holds the latest vector to be
# given to kadane1DwithBounds()
def kadane2DwithBounds(maxRows, maxCols):
global temp
for i in xrange(N):
temp[i] = sum(table[i][j] for j in xrange(maxCols))
m = kadane1DwithBounds(maxRows)
k = 0
for j in xrange(1, M - maxCols + 1):
for i in xrange(N):
temp[i] -= table[i][k]
temp[i] += table[i][maxCols + j - 1]
k += 1
m = max(m, kadane1DwithBounds(maxRows))
print m
line = map(int, raw_input().split())
N = line[0]
M = line[1]
maxRows = line[2]
maxCols = line[3]
table = []
temp = np.empty(N, dtype = int)
for _ in xrange(N):
table.append(map(int, raw_input().split()))
kadane2DwithBounds(maxRows, maxCols)
test.txt
4 8 2 3
1 1 2 3 3 1 1 1
2 2 2 2 2 2 2 2
3 3 3 1 1 3 3 4
0 0 1 1 3 2 2 1
Run with
python maxSumSubarray.py < test.txt
it gives
16
which is correct and is the following rectangle:
2 2 2
3 3 4
I've tried with other dimensions too and I'm pretty sure it works fine. Only problem is time/complexity. Any help would be appreciated! Thanks for your time.