# 5 Effective Python Methods to Check Block Symmetry Over the X-Y Line

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π‘ Problem Formulation: Checking for symmetry in geometric shapes can be performed algorithmically by analyzing point coordinates. In this article, we explore methods to determine if a given list of block representations, defined by their corner points, are symmetric with respect to the X-Y line. Say we have the input of coordinates `[(1, -1), (-1, 1), (2, -2), (-2, 2)]`, we seek to verify whether these pairs are symmetrically arranged across the X-Y line, which would produce a “True” output.

## Method 1: Direct Comparison

This method entails iterating over each point in the list and checking whether its mirrored point, obtained by swapping the x and y values, exists within the list. It’s an intuitive, brute-force way to verify the symmetry of blocks.

Here’s an example:

```def is_symmetric_direct(blocks):
for (x, y) in blocks:
if (y, x) not in blocks:
return False
return True

blocks = [(1, -1), (-1, 1), (2, -2), (-2, 2)]
print(is_symmetric_direct(blocks))```

Output: `True`

This function iterates over each block’s coordinates and checks for its counterpart. If all blocks have symmetrical partners, the function returns true, indicating symmetry over the XY line.

## Method 2: Using Set

To make the search more efficient, this method converts the block list to a set, which allows for O(1) lookups when checking for the existence of the mirrored points.

Here’s an example:

```def is_symmetric_set(blocks):
block_set = set(blocks)
return all((y, x) in block_set for (x, y) in blocks)

blocks = [(1, -1), (-1, 1), (2, -2), (-2, 2)]
print(is_symmetric_set(blocks))```

Output: `True`

By using a set, we eliminate the need for nested iteration, speeding up the function and still effectively determining if our blocks are symmetric over the x-y line.

## Method 3: Sorting and Pairwise Comparison

This method sorts the points and compares pairs to check for symmetry. It works under the assumption that symmetrical points sort to adjacent positions.

Here’s an example:

```def is_symmetric_sorting(blocks):
sorted_blocks = sorted(blocks, key=lambda block: (block[0], -block[1]))
return all(sorted_blocks[i] == (sorted_blocks[i+1][1], sorted_blocks[i+1][0])
for i in range(0, len(sorted_blocks), 2))

blocks = [(1, -1), (-1, 1), (2, -2), (-2, 2)]
print(is_symmetric_sorting(blocks))```

Output: `True`

After sorting, the function ensures that each point’s mirror is its immediate neighbor in the list. This is a clever approach but requires the list to have an even number of points and the pairs to be precisely adjacent.

## Method 4: Mathematical Approach

This method leverages the mathematical property of symmetric points. For a point (x, y) to be symmetric with respect to the x-y line, its mirrored point must be (-y, -x).

Here’s an example:

```def is_symmetric_math(blocks):
return all((-y, -x) in blocks for (x, y) in blocks)

blocks = [(1, -1), (-1, 1), (2, -2), (-2, 2)]
print(is_symmetric_math(blocks))```

Output: `True`

This code snippet checks if each block point has its negative counterpart in the list, confirming symmetry with respect to the XY line mathematically without swapping x and y values.

## Bonus One-Liner Method 5: Set Comprehension

Simplifying Method 2, this one-liner version uses set comprehension to create the mirrored set and directly compares it to the original set.

Here’s an example:

```blocks = [(1, -1), (-1, 1), (2, -2), (-2, 2)]
print({(y, x) for (x, y) in blocks} == set(blocks))```

Output: `True`

The set comprehension creates a new set of mirrored blocks and compares it with the set of original blocks for equality, thus checking for symmetry in a concise way.

## Summary/Discussion

• Method 1: Direct Comparison. Simple to understand. Can be inefficient for large lists.
• Method 2: Using Set. Improves lookup efficiency. Requires adequate memory for creating a set.
• Method 3: Sorting and Pairwise Comparison. Smart and succinct. Works only for lists with an even number of coordinated pairs and requires sorting.
• Method 4: Mathematical Approach. Leverages mathematical properties for an elegant solution. Must iterate twice if the list to set conversion is used.
• Method 5: Set Comprehension. Extremely compact. The terseness of the code may impact code readability for some.