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//Similar to this Java :)
List sum = new ArrayList();
for(int i=0; i<4; i++){
for(int j=0; j<4; j++){
sum.add(arr[i][j]+arr[i][j+1]+arr[i][j+2]+arr[i+1][j+1]+arr[i+2][j]+arr[i+2][j+1]+arr[i+2][j+2]);
}
}
System.out.println(Collections.max(sum));
}
Just check the constraints in the problem statement. The algorithm is meant to solve it for a 2D array of size 4x4. Easy to generalize, just get the array dimensions and use it for iteration thresholds.
They are storing all the sums for every hourglass in the array/list. What I don't like about this solution is that you need more memory (allocate another array/list) and finally you need the max function, which may add extra complexity depending on the implementation. I prefer the max variable + if solution better.
To save space, you can check for max sum with every calculation of the hourglass sum. So instead of having an array with all values and then comparing the max, we can get the result as we traverse :)
my approch has -1 calculation on each glass and no additional array sum. Look on it.
.
'''
def hourglassSum(arr):
len_arr = len(arr)
n=(len_arr-2)**2
s_max = None
for k in range(n):
i = k//(len_arr-2)
j = k%(len_arr-2)
if j==0: # new row glass sum
_ = sum((arr[i][0],arr[i][1],arr[i][2],
arr[i+1][1],
arr[i+2][0],arr[i+2][1],arr[i+2][2])
if(s_max is None):
s_max = _
else: # next glass in the same row sum calc
_ += (-arr[i][j-1]-arr[i+1][j]-arr[i+2][j-1] + \
arr[i][j+2]+arr[i+1][j+1]+arr[i+2][j+2])
s_max = max(s_max,_)
return s_max
'''
2D Array - DS
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Python3 answer
Brilliant!
//Similar to this Java :) List sum = new ArrayList(); for(int i=0; i<4; i++){ for(int j=0; j<4; j++){ sum.add(arr[i][j]+arr[i][j+1]+arr[i][j+2]+arr[i+1][j+1]+arr[i+2][j]+arr[i+2][j+1]+arr[i+2][j+2]); } } System.out.println(Collections.max(sum)); }
why we are iterating upto 4 ??
coz after 4 iteration will ends the matrix .if you count 6*6 matrix and if you need only 3*3 than it will be possible only uptu 4 iterartion
9 -9 -9 1 1 1 0 -9 0 4 3 2 -9 -9 -9 1 2 3 0 0 8 6 6 0 -->>4th line 0 0 0 -2 0 0 0 0 1 2 4 0
you can iterate til 4th line because next iteration give 2 lines only
Just check the constraints in the problem statement. The algorithm is meant to solve it for a 2D array of size 4x4. Easy to generalize, just get the array dimensions and use it for iteration thresholds.
Could you please explain!
They are storing all the sums for every hourglass in the array/list. What I don't like about this solution is that you need more memory (allocate another array/list) and finally you need the max function, which may add extra complexity depending on the implementation. I prefer the max variable + if solution better.
One liner in Python 3:
As array indices also start from zero, it would be convenient to let range function start from 0 (which it does by default):
print(max([sum(arr[i][j:j+3] + [arr[i+1][j+1]] + arr[i+2][j:j+3]) for i in range(4) for j in range(4)]))
Why does the max function contain brackets that also wrap around everything inside?
it's a list comprehension https://python-course.eu/list_comprehension.php
Excellent Well done
print(max(sum(arr[i-1][j-1:j+2] + [arr[i][j]] + arr[i+1][j-1:j+2]) for j in range(1, 5) for i in range(1, 5))) no '[]' list generator,more faster!
My Attempt :)
awesome and cool:)
Python help me understand such questions easily
Even I thought of the same solution but it doesnt pass a lot of test cases
To save space, you can check for max sum with every calculation of the hourglass sum. So instead of having an array with all values and then comparing the max, we can get the result as we traverse :)
Nice simple solution! I feel stupid that I solved it with a 4D array now...
prefect pythonian solution
Why is range(len(arr)-2) ?
A similar NodeJS solution:
Oh, cool. I did something similar but forgot Math.max(). I had to do a sort then get the final element in the array. Thanks!
amazing !
my approch has -1 calculation on each glass and no additional array sum. Look on it. . '''