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).
Related
I would like to create some number of for-loops equal to the length of a list, and iterate through the values in that list. For example, if I had the list:
[1,2,3,4]
I would like the code to function like:
for i in range(1):
for j in range(2):
for k in range(3):
for l in range(4):
myfunc(inputs)
I understand I would need to do this recursively, but I'm not quite sure how. Ideally, I would even be able to iterate through these list values by a variable step; perhaps I want to count by two's for one loop, by .8's for another, etc. In that case, I would probably deliver the information in a format like this:
[[value,step],[value,step] ... [value,step],[value,step]]
So, how could I do this?
Not quite sure what you want at the very end, but here's a way to recursively set-up your loops:
test = [1,2,3,4]
def recursive_loop(test):
if len(test) == 1:
for i in range(test[0]):
print('hi') # Do whatever you want here
elif len(test) > 1:
for i in range(test[0]):
recursive_loop(test[1:])
recursive_loop(test)
You can certainly do it with recursion, but there's already a library function for that:
itertools.product
from itertools import product
def nested_loops(myfunc, l):
for t in product(*(range(n) for n in l)):
myfunc(*t)
## OR EQUIVALENTLY
# def nested_loops(myfunc, l):
# for t in product(*map(range, l)):
# myfunc(l)
nested_loops(print, [1, 2, 3, 4])
# 0 0 0 0
# 0 0 0 1
# 0 0 0 2
# 0 0 0 3
# 0 0 1 0
# 0 0 1 1
# ...
# 0 1 2 1
# 0 1 2 2
# 0 1 2 3
You can of course include steps too. Library function zip can be useful.
def nested_loops_with_steps_v1(myfunc, upperbounds, steps):
for t in product(*(range(0, n, s) for n,s in zip(upperbounds, steps))):
myfunc(*t)
nested_loops_with_steps_v1(print, [1,2,8,10], [1,1,4,5])
# 0 0 0 0
# 0 0 0 5
# 0 0 4 0
# 0 0 4 5
# 0 1 0 0
# 0 1 0 5
# 0 1 4 0
# 0 1 4 5
Or if your steps and upperbounds are already zipped together:
def nested_loops_with_steps_v2(myfunc, l):
for t in product(*(range(0, n, s) for n,s in l)):
myfunc(*t)
nested_loops_with_steps_v2(print, [(1,1),(2,1),(8,4),(10,5)])
# 0 0 0 0
# 0 0 0 5
# 0 0 4 0
# 0 0 4 5
# 0 1 0 0
# 0 1 0 5
# 0 1 4 0
# 0 1 4 5
I have a list with 4 elements. Each element is a correct score that I am pulling from a form. For example:
scoreFixed_1 = 1
scoreFixed_2 = 2
scoreFixed_3 = 3
scoreFixed_4 = 4
scoreFixed = [scoreFixed_1, scoreFixed_2, scoreFixed_3, scoreFixed_4]
Then, I need to add:
scoreFixed_1 to fixture[0][0]
scoreFixed_2 to fixture[0][1]
scoreFixed_3 to fixture[1][0]
scoreFixed_4 to fixture[1][1]
Hence, I need to create a triple for loop that outputs the following sequence so I can index to achieve the result above:
0 0 0
1 0 1
2 1 0
3 1 1
I have tried to use this to create this matrix, however I am only able to get the first column correct. Can anyone help?
for x in range(1):
for y in range(1):
for z in range(4):
print(z, x, y)
which outputs:
0 0 0
1 0 0
2 0 0
3 0 0
Your logic does not generate the table, you want something like:
rownum = 0
for x in range(2):
for y in range(2):
print (rownum, x, y)
rownum += 1
(Edit: The question has been changed, to accomplish the new desire, you want something like this:)
scoreIndex = 0
for x in range(2):
for y in range(2):
fixture[x][y] += scoreFixed[scoreIndex]
scoreIndex += 1
After your edit, it seems like we can split the 'sequence' into:
First column, regular ascending variable ( n += 1)
Second and third column, binary counter (00, 01, 10, 11)
0 0 0
1 0 1
2 1 0
3 1 1
^ ^------- These seem like a binary counter
(00, 01, 10, 11)
^------ A regular ascending variable
( n += 1 )
Using that 'logic' we can create a code that looks like
import itertools
scoreFixed = 0
for i in itertools.product([0,1],repeat=2):
print(scoreFixed, ' '.join(map(str,i)))
scoreFixed += 1
And wil output:
0 0 0
1 0 1
2 1 0
3 1 1
As you can test in this online demo
for x in range(4):
z = int(bin(x)[-1])
y = bin(x)[-2]
y = int(y) if y.isdigit() else 0
print(x, y, z)
I have the following:
df['PositionLong'] = 0
df['PositionLong'] = np.where(df['Alpha'] == 1, 1, (np.where(np.logical_and(df['PositionLong'].shift(1) == 1, df['Bravo'] == 1), 1, 0)))
This lines basically only take in df['Alpha'] but not the df['PositionLong'].shift(1).. It cannot recognize it but I dont understand why?
It produces this:
df['Alpha'] df['Bravo'] df['PositionLong']
0 0 0
1 1 1
0 1 0
1 1 1
1 1 1
However what I wanted the code to do is this:
df['Alpha'] df['Bravo'] df['PositionLong']
0 0 0
1 1 1
0 1 1
1 1 1
1 1 1
I believe the solution is to loop each row, but this will take very long.
Can you help me please?
You are looking for a recursive function, since a previous PositionLong value depends on Alpha, which itself is used to determine PositionLong.
But numpy.where is a regular function, so df['PositionLong'].shift(1) is evaluated as a series of 0 values, since you initialise the series with 0.
A manual loop need not be expensive. You can use numba to efficiently implement your recursive algorithm:
from numba import njit
#njit
def rec_algo(alpha, bravo):
res = np.empty(alpha.shape)
res[0] = 1 if alpha[0] == 1 else 0
for i in range(1, len(res)):
if (alpha[i] == 1) or ((res[i-1] == 1) and bravo[i] == 1):
res[i] = 1
else:
res[i] = 0
return res
df['PositionLong'] = rec_algo(df['Alpha'].values, df['Bravo'].values).astype(int)
Result:
print(df)
Alpha Bravo PositionLong
0 0 0 0
1 1 1 1
2 0 1 1
3 1 1 1
4 1 1 1
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']
I am interested in generating all binary combination of N variables without having to implement a manual loop of iterating N times over N and each time looping over N/2 and so on.
Do we have such functionality in python?
E.g:
I have N binary variables:
pool=['A','B','C',...,'I','J']
len(pool)=10
I would like to generate 2^10=1024 space out of these such as:
[A B C ... I J]
iter0 = 0 0 0 ... 0 0
iter1 = 0 0 0 ... 0 1
iter2 = 0 0 0 ... 1 1
...
iter1022 = 1 1 1 ... 1 0
iter1023 = 1 1 1 ... 1 1
You see that I don't have repetitions here, each variable is enabled once per each of these iter's sequences. How can I do that using Python's itertools?
itertools.product with the repeat parameter is the simplest answer:
for A, B, C, D, E, F, G, H, I, J in itertools.product((0, 1), repeat=10):
The values of each variable will cycle fastest on the right, and slowest on the left, so you'll get:
0 0 0 0 0 0 0 0 0 0
0 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 0 1 1
0 0 0 0 0 0 0 1 0 0
etc. This may be recognizable to you: It's just the binary representation of an incrementing 10 bit number. Depending on your needs, you may actually want to just do:
for i in range(1 << 10):
then mask i with 1 << 9 to get the value of A, 1 << 8 for B, and so on down to 1 << 0 (that is, 1) for J. If the goal is just to print them, you can even get more clever, by binary stringifying and then using join to insert the separator:
for i in range(1 << 10):
print(' '.join('{:010b}'.format(i)))
# Or letting print insert the separator:
print(*'{:010b}'.format(i)) # If separator isn't space, pass sep='sepstring'