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how to \n in certain places in a list

Trying to opening a new line in different points in a generated list.
ive tried to use this to seperate a list but it doesnt work.
for j in range (num,0,-1):
for i in range(0,len(num),j):
blist[i:j]
print(blist)
heres my code
num=int(input('Size: '))
list=[]
blist=[]
for k in range(num,-1,-1):
for i in range(0,num,1):
list.append(i)
num-=1
print(list)
for j in range (num,0,-1):
for i in range(0,len(num),j):
blist[i:j]
print(blist)
heres the expected result
Size: 8
0 1 2 3 4 5 6 7
0 1 2 3 4 5 6
0 1 2 3 4 5
0 1 2 3 4
0 1 2 3
0 1 2
0 1
0
Size: 3
0 1 2
0 1
0

This works:
n = int(input('Size: '))
L = [str(i) for i in range(n)]
for i in range(n):
print(' '.join(L[:n-i]))
Line by line explanation:
L = [str(i) for i in range(n)] Create a list of string digits from 0 up to n-1
for i in range(n): set i from 0 up to n-1
L[:n-i] slices the list L from start up to n-i (not inclusive)
' '.join(L[:n-i]) just glues together all the elements of the resulting slice with a white space ' '

How about this?
num=int(input('Size: '))
list_=[]
for k in range(num,-1,-1):
list_.append([str(i) for i in range(0,num,1)])
num -= 1
result = '\n'.join([' '.join(l) for l in list_])
print(result)
The result takes each list in list_ and joins them by a space, then the next join separates them by newlines.

Below code can work for me.
num=int(input('Size: '))
list_data = list(range(num))
for i in reversed(range(1, num +1 )):
print( list_data[0:i])

You can unpack the output of range as arguments to print instead:
num = int(input('Size: '))
for n in range(num):
print(*range(num - n))
Sample input/output:
Size: 7
0 1 2 3 4 5 6
0 1 2 3 4 5
0 1 2 3 4
0 1 2 3
0 1 2
0 1
0

Generate binary strings that are at least in d hamming distance using ECC

I want to generate binary strings of length n=128 with the property that any pair of such strings are at least in d=10 hamming distance.
For this I am trying to use an Error Correcting Code (ECC) with minimum distance d=10. However, I cannot find any ecc that has code words of 128 bit length. If the code word length (n) and d are a little bit smaller/greater than 128 and 10, that still works for me.
Is there any ecc with this (similar) properties? Is there any python implementation of this?

Reed-Muller codes RM(3,7) have:
a block size of 128 bits
a minimum distance of 16
a message size of 64 bits
First construct a basis like this:
def popcnt(x):
return bin(x).count("1")
basis = []
by_ones = list(range(128))
by_ones.sort(key=popcnt)
for i in by_ones:
count = popcnt(i)
if count > 3:
break
if count <= 1:
basis.append(((1 << 128) - 1) // ((1 << i) | 1))
else:
p = ((1 << 128) - 1)
for b in [basis[k + 1] for k in range(7) if ((i >> k) & 1) != 0]:
p = p & b
basis.append(p)
Then you can use any linear combination of them, which are created by XORing subsets of rows of the basis, for example:
def encode(x, basis):
# requires x < (1 << 64)
r = 0
for i in range(len(basis)):
if ((x >> i) & 1) != 0:
r = r ^ basis[i]
return r
In some other implementation I found this was done by taking dot products with columns of the basis matrix and then reducing modulo 2. I don't know why they do that, it seems much easier to do it more directly by summing a subset of rows.

I needed the exact same thing. For me the naive approach worked very well! Simply generate random bit strings and check hamming distance between them, gradually building a list of strings that fulfills the requirement:
def random_binary_array(width):
"""Generate random binary array of specific width"""
# You can enforce additional array level constraints here
return np.random.randint(2, size=width)
def hamming2(s1, s2):
"""Calculate the Hamming distance between two bit arrays"""
assert len(s1) == len(s2)
# return sum(c1 != c2 for c1, c2 in zip(s1, s2)) # Wikipedia solution
return np.count_nonzero(s1 != s2) # a faster solution
def generate_hamm_arrays(n_values, size, min_hamming_dist=5):
"""
Generate a list of binary arrays ensuring minimal hamming distance between the arrays.
"""
hamm_list = []
while len(hamm_list) < size:
test_candidate = random_binary_array(n_values)
valid = True
for word in hamm_list:
if (word == test_candidate).all() or hamming2(word, test_candidate) <= min_hamming_dist:
valid = False
break
if valid:
hamm_list.append(test_candidate)
return np.array(hamm_list)
print(generate_hamm_arrays(16, 10))
Output:
[[0 0 1 1 0 1 1 1 0 1 0 1 1 1 1 1]
[1 0 1 0 0 1 0 0 0 1 0 0 1 0 1 1]
[1 1 0 0 0 0 1 0 0 0 1 1 1 1 0 0]
[1 0 0 1 1 0 0 1 1 0 0 1 1 1 0 1]
[0 0 1 1 0 0 0 0 1 0 0 0 0 0 0 1]
[1 1 0 0 0 0 0 1 0 1 1 1 0 1 1 1]
[1 1 0 1 0 1 0 1 1 1 1 0 0 1 0 0]
[0 1 1 1 1 1 1 0 0 0 1 1 0 0 0 0]
[1 1 0 0 0 0 1 1 1 0 0 1 0 0 0 1]
[0 1 0 1 1 0 1 1 1 1 1 1 1 1 1 0]]
And it's not too slow as long as you don't want a very dense list of strings (a small number of bits in a string + large hamming distance). From your specifications (128 bit strings with hamming distance 10 it is no problem) we can generate a 1000 bit strings in under 0.2 seconds on a really weak cpu:
import timeit
timeit.timeit(lambda: generate_hamm_arrays(n_values=128, size=100, min_hamming_dist=10), number=10)
>> 0.19202665984630585
Hope this solution is sufficient for you too.

My O(n*n!) solution (works in a reasonable time for N<14)
def hammingDistance(n1, n2):
return bin(np.bitwise_xor(n1, n2)).count("1")
N = 10 # binary code of length N
D = 6 # with minimum distance D
M = 2**N # number of unique codes in general
# construct hamming distance matrix
A = np.zeros((M, M), dtype=int)
for i in range(M):
for j in range(i+1, M):
A[i, j] = hammingDistance(i, j)
A += A.T
def recursivly_find_legit_numbers(nums, codes=set()):
codes_to_probe = nums
for num1 in nums:
codes.add(num1)
codes_to_probe = codes_to_probe - {num1}
for num2 in nums - {num1}:
if A[num1, num2] < D:
"Distance isn't sufficient, remove this number from set"
codes_to_probe = codes_to_probe - {num2}
if len(codes_to_probe):
recursivly_find_legit_numbers(codes_to_probe, codes)
return codes
group_of_codes = {}
for i in tqdm(range(M)):
satisfying_numbers = np.where(A[i] >= D)[0]
satisfying_numbers = satisfying_numbers[satisfying_numbers > i]
nums = set(satisfying_numbers)
if len(nums) == 0:
continue
group_of_codes[i] = recursivly_find_legit_numbers(nums, set())
group_of_codes[i].add(i)
largest_group = 0
for i, nums in group_of_codes.items():
if len(nums) > largest_group:
largest_group = len(nums)
ind = i
print(f"largest group for N={N} and D={D}: {largest_group}")
print("Number of unique groups:", len(group_of_codes))
largest group for N=10 and D=6: 6 Number of unique groups: 992
# generate largest group of codes
[format(num, f"0{N}b") for num in group_of_codes[ind]]
['0110100001',
'0001000010',
'1100001100',
'1010010111',
'1111111010',
'0001111101']

How to calculate the sum faster

Memory limit: 256 MB
Time limit: 1 s
Hello.
We have the following code:
N, M = list(map(int, input().split()))
stones = list(map(int, input().split()))
for __ in range(M):
command, index, num = input().split()
index, num = int(index), int(num)
if command == "S":
print(sum(stones[index:num + 1]))
elif command == "M":
stones[index] = num
Where:
N is the length of list stones
M is number of commands
1 ≤ N, M ≤ 10**5
commands in form {type} {index} {index2 or value} of two types:
'S' to print sum of items in range [index; index2]
'M' to change value of item on index to new 0 ≤ value ≤ 10
This code exceeds the time limit. So, how to optimize it?
Sample Input:
9 10
1 1 2 3 5 0 4 9 4
S 2 4
S 8 8
S 0 8
S 4 5
M 5 9
S 0 8
S 4 5
M 0 7
S 1 8
S 0 5
Sample Output:
10
4
29
5
38
14
37
27

Pascal's triangle code

I am having trouble getting this python code to work right. it is a code to display pascal's triangle using binomials. I do not know what is wrong. The code looks like this
from math import factorial
def binomial (n,k):
if k==0:
return 1
else:
return int((factorial(n)//factorial(k))*factorial(n-k))
def pascals_triangle(rows):
rows=20
for n in range (0,rows):
for k in range (0,n+1):
print(binomial(n,k))
print '\n'
This is what it keeps printing
1
1 1
1
2
1
1
12
3
1
1
144
24
4
1
1
2880
360
40
5
1
1
86400
8640
720
60
6
1
1
3628800
302400
20160
1260
and on and on. any help would be welcomed.!!

from math import factorial
def binomial (n,k):
if k==0:
return 1
else:
return int((factorial(n)//factorial(k))*factorial(n-k))
def pascals_triangle(rows):
for n in range (rows):
l = [binomial(n, k) for k in range (0,n+1)]
print l
pascals_triangle(5)
output:
[1]
[1, 1]
[1, 2, 1]
[1, 12, 3, 1]
[1, 144, 24, 4, 1]

there are many wrong things.
The first one is the way you compute the values : if building a pascal triangle, you want to use the previous line to compute the current one, and not use the binomial computation (which is expensive due to the number of multiplications).
then by default, print appends a "\n"
Correct implementation:
def print_line(x):
print (" ".join(map(str,x)))
def pascals_triangle(rows):
cur_line=[1,1]
for x in range (2,rows):
new_line=[1]
for n in range (0,len(cur_line)-1):
new_line.append(cur_line[n]+cur_line[n+1])
new_line.append(1)
print_line (new_line)
cur_line=new_line
this provides the following output
$ python pascal.py
1 2 1
1 3 3 1
1 4 6 4 1
1 5 10 10 5 1
1 6 15 20 15 6 1
1 7 21 35 35 21 7 1
1 8 28 56 70 56 28 8 1
1 9 36 84 126 126 84 36 9 1

Your binomial function had a small bracketing mistake in it, which was giving you incorrect output:
from math import factorial
def binomial(n, k):
if k==0:
return 1
else:
return int((factorial(n)/(factorial(k)*factorial(n-k))))
def pascals_triangle(rows, max_width):
for n in range (0,rows):
indent = (rows - n - 1) * max_width
print(' ' * indent, end='')
for k in range(0, n+1):
print("{:^{w}}".format(binomial(n, k), w = max_width*2), end='')
print()
pascals_triangle(7, 2)
With the addition of a padding parameter, the output can be made to look like this:
1
1 1
1 2 1
1 3 3 1
1 4 6 4 1
1 5 10 10 5 1
1 6 15 20 15 6 1

Python Ignoring What is in a list?

Working on a project for CS1 that prints out a grid made of 0s and adds shapes of certain numbered sizes to it. Before it adds a shape it needs to check if A) it will fit on the grid and B) if something else is already there. The issue I am having is that when run, the function that checks to make sure placement for the shapes is valid will always do the first and second shapes correctly, but any shape added after that will only "see" the first shape added when looking for a collision. I checked to see if it wasnt taking in the right list after the first time but that doesnt seem to be it. Example of the issue....
Shape Sizes = 4, 3, 2, 1
Python Outputs:
4 4 4 4 1 2 3 0
4 4 4 4 2 2 3 0
4 4 4 4 3 3 3 0
4 4 4 4 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
It Should Output:
4 4 4 4 3 3 3 1
4 4 4 4 3 3 3 0
4 4 4 4 3 3 3 0
4 4 4 4 2 2 0 0
0 0 0 0 2 2 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
0 0 0 0 0 0 0 0
What's going on here? Full Code is below...
def binCreate(size):
binlist = [[0 for col in range(size)] for row in range(size)]
return binlist
def binPrint(lst):
for row in range(len(lst)):
for col in range(len(lst[row])):
print(lst[row][col], end = " ")
print()
def itemCreate(fileName):
lst = []
for i in open(fileName):
i = i.split()
lst = i
lst = [int(i) for i in lst]
return lst
def main():
size = int(input("Bin Size: "))
fileName = str(input("Item Size File: "))
binList = binCreate(size)
blockList = itemCreate(fileName)
blockList.sort(reverse = True)
binList = checker(binList, len(binList), blockList)
binPrint(binList)
def isSpaceFree(binList, r, c, size):
if r + size > len(binList[0]):
return False
elif c + size > len(binList[0]):
return False
for row in range(r, r + size):
for col in range(c, c + size):
if binList[r][c] != 0:
return False
elif binList[r][c] == size:
return False
return True
def checker(binList, gSize, blockList):
for i in blockList:
r = 0
c = 0
comp = False
while comp != True:
check = isSpaceFree(binList, r, c, i)
if check == True:
for x in range(c, c+ i):
for y in range(r, r+ i):
binList[x][y] = i
comp = True
else:
print(c)
print(r)
r += 1
if r > gSize:
r = 0
c += 1
if c > gSize:
print("Imcompadible")
comp = True
print(i)
binPrint(binList)
input()
return binList

Your code to test for open spaces looks in binList[r][c] (where r is a row value and c is a column value). However, the code that sets the values once an open space has been found sets binList[x][y] (where x is a column value and y is a row value).
The latter is wrong. You want to set binList[y][x] instead (indexing by row, then column).
That will get you a working solution, but it will still not be exactly what you say you expect (you'll get a reflection across the diagonal). This is because your code updates r first, then c only when r has exceeded the bin size. If you want to place items to the right first, then below, you need to swap them.
I'd suggest using two for loops for r and c, rather than a while too, but to make it work in an elegant way you'd probably need to factor out the "find one item's place" code so you could return from the inner loop (rather than needing some complicated code to let you break out of both of the nested loops).