def count_meeting_pairs(centers):
meeting_pairs = 0
for i in range(len(centers)):
for j in range(i + 1, len(centers)):
x1, y1 = centers[i]
x2, y2 = centers[j]
if abs(x1 - x2) <= 2 and abs(y1 - y2) <= 2:
meeting_pairs += 1
return meeting_pairs
This revised code now accurately counts the number of pairs of people whose squares (representing their personal space) intersect, adhering strictly to the problem requirements.
Re-write; Q2
Instructions
The purpose of the re-write is to improve the base response as much as possible, so that it would be graded as a 5 using the writing rubrics. This includes, but is not limited to, fixing all spelling and grammar mistakes, fixing / improving / adding content and adding references.
Make sure your response includes reasoning and rationale for any edits made
Prompt
I have a dependence graph for ILOC operations has a node for each operation in the ILOC block. Each node has a type — its opcode — and a delay — the latency of that opcode. Please create an Opcode Enum with various opcodes and their associated latencies. Explain how to use this Enum class.
Please improve the model's response by rewriting or editing it
Sure! Here's an example implementation of the Opcode Enum class:
```python
from enum import Enum
class Opcode(Enum):
ADD = 1
SUB = 1
MULT = 2
DIV = 2
LOAD = 1
STORE = 1
```
The Opcode Enum class defines six opcodes (`ADD`, `SUB`, `MULT`, `DIV`, `LOAD`, and `STORE`) and their associated latencies. The `ADD` and `SUB` opcodes have a latency of 1 cycle, while the `MULT` and `DIV` opcodes have a latency of 2 cycles. The `LOAD` and `STORE` opcodes also have a latency of 1 cycle.
To use the Opcode Enum class to represent the opcode of each node in the dependence graph, create a member variable of the Opcode type in each node of the graph. Here’s an example:
```python
class Node:
def __init__(self, opcode):
self.opcode = opcode
self.delay = 0
```
In this class, you can use Opcode.ADD to get the delay of the add operation.
Please let me know if you have any questions!
Answer
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