Initial Query

Convert this game of life pattern 26$13b2o$14bo$14bobo$15b2o14$31b2o$30b2o$32bo13$46b2o$45b2o$47bo13$61b 2o$60b2o$62bo4$52b2o$52b2o$71bo$66b2ob3o$66bobobo$68bo$67b2o3$76b2o$ 60b3o12b2o10bobo$52b3o7bo14bo8bo2bo4bo$51bo3bo5bo10b2o11b2o5b2o$50bo5b o15bobo8b2o3bo8b2o$51bo3bo11b2o6bo9b2o10b2o$52b3o8b2obo2bo2bo2bo10bo2b o$52bo2bo7b2o2b2o6bo11bobo$53b3o16bobo$53b2obo15b2o$54bobo$55bo3$52b2o 3b2o$52bobobobo$53b5o$54b3o$55bo7$54b2o$54b2o! to a numpy array. Call the function `rle_to_arr(string, h, w)` which should return a numpy array with .shape (h,w). Fill the array with 1s, and empty with 0.

LLM Generation

Query

Output

Here's the Python code that implements the `rle_to_arr(string, h, w)` function to convert the game of life pattern in run-length encoded format to a numpy array:

import numpy as np

def rle_to_arr(string, h, w):
    arr = np.zeros((h, w), dtype=int)
    lines = string.split("$")
    row = 0
    col = 0

    for line in lines:
        line = line.strip()
        if not line:
            continue

        count = 0
        for char in line:
            if char.isdigit():
                count = count * 10 + int(char)
            else:
                if count == 0:
                    count = 1
                if char == 'b':
                    col += count
                elif char == 'o':
                    arr[row, col:col+count] = 1
                    col += count
                count = 0

        row += 1
        col = 0

    return arr

Explanation: 1. We create a numpy array `arr` of shape `(h, w)` initialized with zeros using `np.zeros((h, w), dtype=int)`. 2. We split the input `string` by the '$' character to get individual lines of the pattern. 3. We initialize variables `row` and `col` to keep track of the current position in the array. 4. We iterate over each line in the pattern: - If the line is empty (after stripping whitespace), we skip it. - We initialize a variable `count` to keep track of the count of consecutive cells. - We iterate over each character in the line: - If the character is a digit, we update the `count` by multiplying it by 10 and adding the current digit. - If the character is 'b' (dead cell), we increment the `col` by the current `count`. - If the character is 'o' (live cell), we set the corresponding elements in `arr` to 1 using `arr[row, col:col+count] = 1` and increment the `col` by the current `count`. - We reset the `count` to 0 after processing each character. 5. After processing each line, we increment the `row` and reset the `col` to 0. 6. Finally, we return the resulting numpy array `arr`. To use the function, you can call it with the game of life pattern string, the desired height `h`, and width `w` of the array:

pattern = "26$13b2o$14bo$14bobo$15b2o14$31b2o$30b2o$32bo13$46b2o$45b2o$47bo13$61b2o$60b2o$62bo4$52b2o$52b2o$71bo$66b2ob3o$66bobobo$68bo$67b2o3$76b2o$60b3o12b2o10bobo$52b3o7bo14bo8bo2bo4bo$51bo3bo5bo10b2o11b2o5b2o$50bo5bo15bobo8b2o3bo8b2o$51bo3bo11b2o6bo9b2o10b2o$52b3o8b2obo2bo2bo2bo10bo2bo$52bo2bo7b2o2b2o6bo11bobo$53b3o16bobo$53b2obo15b2o$54bobo$55bo3$52b2o3b2o$52bobobobo$53b5o$54b3o$55bo7$54b2o$54b2o!"

h = 80
w = 80
arr = rle_to_arr(pattern, h, w)
print(arr)

The code will output the corresponding numpy array representation of the game of life pattern.

Extract Code

I extracted the following code from that output:

import numpy as np

def rle_to_arr(string, h, w):
    arr = np.zeros((h, w), dtype=int)
    lines = string.split("$")
    row = 0
    col = 0

    for line in lines:
        line = line.strip()
        if not line:
            continue

        count = 0
        for char in line:
            if char.isdigit():
                count = count * 10 + int(char)
            else:
                if count == 0:
                    count = 1
                if char == 'b':
                    col += count
                elif char == 'o':
                    arr[row, col:col+count] = 1
                    col += count
                count = 0

        row += 1
        col = 0

    return arr

Run Code Interpreter

Running the following program:

import numpy as np

def rle_to_arr(string, h, w):
    arr = np.zeros((h, w), dtype=int)
    lines = string.split("$")
    row = 0
    col = 0

    for line in lines:
        line = line.strip()
        if not line:
            continue

        count = 0
        for char in line:
            if char.isdigit():
                count = count * 10 + int(char)
            else:
                if count == 0:
                    count = 1
                if char == 'b':
                    col += count
                elif char == 'o':
                    arr[row, col:col+count] = 1
                    col += count
                count = 0

        row += 1
        col = 0

    return arr





answer = (np.array(rle_to_arr('''
16b2o3b2o$2o$2o$19b2o$17b5o$21bo$17b3o$o16bo$o17b2o$bo16b2o$b2o$3bo$o
17b2o3b2o$2b2o14bobobobo$11bobo5b5o$11b2o7b3o$2o10bo8bo$b2o$b2o2$2o$bo
2$6bobo$2o3bo$bo3bo$o4bo2bo7bo$5b3o7b2o7bo$15bobo5b3o$22b5o$21b2o3b2o$
22b5o$22b5o$14b2o6bo2bo$14bobo4bo3bo$11b2obobo4bo$11bobobo5bob2o$13bo
8bo$4bobo6b2o$7bo5b3o50bo$7bo5b3o3b2o3b2o40b4o$4bo2bo5b3o3bo5bo41b4o$
5b3o5b2o35bo16bo2bo$13bo6bo3bo24bobo15b4o4b2o$11bobobo5b3o15b2o7bob2o
14b4o5b2o$11b2obobo21bobo6b2ob2o14bo8b2o$14bobo20bo6b3obob2o$14b2o12b
2o7bo2bo2bo2bo2bobo$28b2o7bo6b2o4bo16bobo$38bobo26b2o$39b2o27bo4b2o$
21b2o49bo2bo$21b2o28bobo18b3o$52b2o21b2o$52bo21bo$74b2o$59bo$62bo$59bo
14bo$62bo$61bob3o8bo$59b4o2bo9b2o$64bo$52bo$51b2o$40b2o8b2o4b2o5bo$40b
2o7b3o4b2o3bobo$50b2o4b2o2bobo11b2o$4bobo44b2o6bo2bo11b2o$7bo44bo7bobo
$o6bo53bobo$o3bo2bo55bo$5b3o5$4b4o$3bo3bo$7bo$3bo2bo3$o2b3o2b2o$2b5o2b
o64b3o$9o67bo$9b3o63bo$o7bo2bo$9b2o3$4b2o$o3b3o$o5b2obo5b2o$bo4bo2bo5b
2o$2o4b2obo$o3b3o$4b2o2$59b3o12b2o$61bo12b2o!
''', 101, 77),dtype=np.uint32).flatten() * np.arange(77*101)).sum()
expected = 1563304
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')

And got the output:

Traceback (most recent call last):
  File "/usr/src/app/main.py", line 55, in <module>
    assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
           ^^^^^^^^^^^^^^^^^^
AssertionError: Wrong answer; got 1468671 instead of 1563304

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

LLM Generation

Query

Output

Here's the Python code to convert the Run Length Encoded (RLE) pattern of the Game of Life into a NumPy array:

import numpy as np

def rle_to_arr(rle_string, h, w):
    arr = np.zeros((h, w), dtype=int)
    x, y = 0, 0
    count = 0

    for char in rle_string:
        if char.isdigit():
            count = count * 10 + int(char)
        elif char == 'b':
            x += count if count > 0 else 1
            count = 0
        elif char == 'o':
            for i in range(count if count > 0 else 1):
                arr[y, x] = 1
                x += 1
            count = 0
        elif char == '$':
            y += count if count > 0 else 1
            x = 0
            count = 0
        elif char == '!':
            break

    return arr

Explanation: 1. We define the function `rle_to_arr` that takes three parameters: `rle_string` (the RLE pattern string), `h` (the desired height of the array), and `w` (the desired width of the array). 2. We create a NumPy array `arr` with shape `(h, w)` initialized with zeros using `np.zeros((h, w), dtype=int)`. 3. We initialize variables `x` and `y` to keep track of the current position in the array, and `count` to store the count of consecutive cells. 4. We iterate over each character `char` in the `rle_string`: - If `char` is a digit, we update the `count` by multiplying it by 10 and adding the digit. - If `char` is 'b' (representing a dead cell), we increment `x` by `count` if `count` is greater than 0, otherwise by 1. We reset `count` to 0. - If `char` is 'o' (representing a live cell), we iterate `count` times (or once if `count` is 0) and set the corresponding positions in `arr` to 1. We increment `x` accordingly and reset `count` to 0. - If `char` is '$' (representing the end of a row), we increment `y` by `count` if `count` is greater than 0, otherwise by 1. We reset `x` to 0 and `count` to 0. - If `char` is '!' (representing the end of the pattern), we break out of the loop. 5. Finally, we return the resulting NumPy array `arr`. To use the function, you can call it with the RLE pattern string and the desired dimensions of the array:

rle_string = "26$13b2o$14bo$14bobo$15b2o14$31b2o$30b2o$32bo13$46b2o$45b2o$47bo13$61b2o$60b2o$62bo4$52b2o$52b2o$71bo$66b2ob3o$66bobobo$68bo$67b2o3$76b2o$60b3o12b2o10bobo$52b3o7bo14bo8bo2bo4bo$51bo3bo5bo10b2o11b2o5b2o$50bo5bo15bobo8b2o3bo8b2o$51bo3bo11b2o6bo9b2o10b2o$52b3o8b2obo2bo2bo2bo10bo2bo$52bo2bo7b2o2b2o6bo11bobo$53b3o16bobo$53b2obo15b2o$54bobo$55bo3$52b2o3b2o$52bobobobo$53b5o$54b3o$55bo7$54b2o$54b2o!"
h, w = 80, 80
arr = rle_to_arr(rle_string, h, w)
print(arr)

The function will convert the RLE pattern string into a NumPy array of the specified dimensions, with live cells represented by 1 and dead cells represented by 0.

Extract Code

I extracted the following code from that output:

import numpy as np

def rle_to_arr(rle_string, h, w):
    arr = np.zeros((h, w), dtype=int)
    x, y = 0, 0
    count = 0

    for char in rle_string:
        if char.isdigit():
            count = count * 10 + int(char)
        elif char == 'b':
            x += count if count > 0 else 1
            count = 0
        elif char == 'o':
            for i in range(count if count > 0 else 1):
                arr[y, x] = 1
                x += 1
            count = 0
        elif char == '$':
            y += count if count > 0 else 1
            x = 0
            count = 0
        elif char == '!':
            break

    return arr

Run Code Interpreter

Running the following program:

import numpy as np

def rle_to_arr(rle_string, h, w):
    arr = np.zeros((h, w), dtype=int)
    x, y = 0, 0
    count = 0

    for char in rle_string:
        if char.isdigit():
            count = count * 10 + int(char)
        elif char == 'b':
            x += count if count > 0 else 1
            count = 0
        elif char == 'o':
            for i in range(count if count > 0 else 1):
                arr[y, x] = 1
                x += 1
            count = 0
        elif char == '$':
            y += count if count > 0 else 1
            x = 0
            count = 0
        elif char == '!':
            break

    return arr





answer = (np.array(rle_to_arr('''
16b2o3b2o$2o$2o$19b2o$17b5o$21bo$17b3o$o16bo$o17b2o$bo16b2o$b2o$3bo$o
17b2o3b2o$2b2o14bobobobo$11bobo5b5o$11b2o7b3o$2o10bo8bo$b2o$b2o2$2o$bo
2$6bobo$2o3bo$bo3bo$o4bo2bo7bo$5b3o7b2o7bo$15bobo5b3o$22b5o$21b2o3b2o$
22b5o$22b5o$14b2o6bo2bo$14bobo4bo3bo$11b2obobo4bo$11bobobo5bob2o$13bo
8bo$4bobo6b2o$7bo5b3o50bo$7bo5b3o3b2o3b2o40b4o$4bo2bo5b3o3bo5bo41b4o$
5b3o5b2o35bo16bo2bo$13bo6bo3bo24bobo15b4o4b2o$11bobobo5b3o15b2o7bob2o
14b4o5b2o$11b2obobo21bobo6b2ob2o14bo8b2o$14bobo20bo6b3obob2o$14b2o12b
2o7bo2bo2bo2bo2bobo$28b2o7bo6b2o4bo16bobo$38bobo26b2o$39b2o27bo4b2o$
21b2o49bo2bo$21b2o28bobo18b3o$52b2o21b2o$52bo21bo$74b2o$59bo$62bo$59bo
14bo$62bo$61bob3o8bo$59b4o2bo9b2o$64bo$52bo$51b2o$40b2o8b2o4b2o5bo$40b
2o7b3o4b2o3bobo$50b2o4b2o2bobo11b2o$4bobo44b2o6bo2bo11b2o$7bo44bo7bobo
$o6bo53bobo$o3bo2bo55bo$5b3o5$4b4o$3bo3bo$7bo$3bo2bo3$o2b3o2b2o$2b5o2b
o64b3o$9o67bo$9b3o63bo$o7bo2bo$9b2o3$4b2o$o3b3o$o5b2obo5b2o$bo4bo2bo5b
2o$2o4b2obo$o3b3o$4b2o2$59b3o12b2o$61bo12b2o!
''', 101, 77),dtype=np.uint32).flatten() * np.arange(77*101)).sum()
expected = 1563304
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')

And got the output: All tests passed

Substring Evaluation

Testing if the previous output contains the string All tests passed: True

Initial Query

LLM Generation

Query

Output

Here's the Python code that defines the `rle_to_arr(string, h, w)` function to convert the Run Length Encoded (RLE) string representation of the Game of Life pattern into a NumPy array:

import numpy as np

def rle_to_arr(string, h, w):
    pattern = np.zeros((h, w), dtype=int)
    x, y = 0, 0
    run_count = 0
    
    for char in string:
        if char.isdigit():
            run_count = run_count * 10 + int(char)
        elif char == '$':
            y += run_count if run_count > 0 else 1
            x = 0
            run_count = 0
        elif char == 'b':
            x += run_count if run_count > 0 else 1
            run_count = 0
        elif char == 'o':
            pattern[y, x:x + (run_count if run_count > 0 else 1)] = 1
            x += run_count if run_count > 0 else 1
            run_count = 0
        elif char == '!':
            break
    
    return pattern

Here's how the `rle_to_arr` function works: 1. It takes three parameters: - `string`: The RLE string representation of the Game of Life pattern. - `h`: The desired height of the resulting NumPy array. - `w`: The desired width of the resulting NumPy array. 2. It initializes a NumPy array called `pattern` with the specified height `h` and width `w`, filled with zeros (representing empty cells). 3. It initializes variables `x` and `y` to keep track of the current position in the pattern array, and `run_count` to store the count of consecutive cells. 4. It iterates over each character in the RLE string: - If the character is a digit, it updates the `run_count` by multiplying the previous value by 10 and adding the current digit. - If the character is '$', it moves to the next row by incrementing `y` by `run_count` (if `run_count` is greater than 0) or by 1 (if `run_count` is 0). It also resets `x` to 0 and `run_count` to 0. - If the character is 'b', it moves the current position `x` to the right by `run_count` (if `run_count` is greater than 0) or by 1 (if `run_count` is 0), and resets `run_count` to 0. - If the character is 'o', it fills the cells in the `pattern` array from the current position `x` to `x + run_count` (if `run_count` is greater than 0) or `x + 1` (if `run_count` is 0) with 1 (representing live cells). It then updates `x` accordingly and resets `run_count` to 0. - If the character is '!', it breaks out of the loop since it marks the end of the RLE string. 5. Finally, it returns the `pattern` array containing the converted Game of Life pattern. You can call the `rle_to_arr` function with the provided RLE string and the desired height and width to obtain the corresponding NumPy array representation of the Game of Life pattern.

Extract Code

I extracted the following code from that output:

import numpy as np

def rle_to_arr(string, h, w):
    pattern = np.zeros((h, w), dtype=int)
    x, y = 0, 0
    run_count = 0
    
    for char in string:
        if char.isdigit():
            run_count = run_count * 10 + int(char)
        elif char == '$':
            y += run_count if run_count > 0 else 1
            x = 0
            run_count = 0
        elif char == 'b':
            x += run_count if run_count > 0 else 1
            run_count = 0
        elif char == 'o':
            pattern[y, x:x + (run_count if run_count > 0 else 1)] = 1
            x += run_count if run_count > 0 else 1
            run_count = 0
        elif char == '!':
            break
    
    return pattern

Run Code Interpreter

Running the following program:

import numpy as np

def rle_to_arr(string, h, w):
    pattern = np.zeros((h, w), dtype=int)
    x, y = 0, 0
    run_count = 0
    
    for char in string:
        if char.isdigit():
            run_count = run_count * 10 + int(char)
        elif char == '$':
            y += run_count if run_count > 0 else 1
            x = 0
            run_count = 0
        elif char == 'b':
            x += run_count if run_count > 0 else 1
            run_count = 0
        elif char == 'o':
            pattern[y, x:x + (run_count if run_count > 0 else 1)] = 1
            x += run_count if run_count > 0 else 1
            run_count = 0
        elif char == '!':
            break
    
    return pattern





answer = (np.array(rle_to_arr('''
16b2o3b2o$2o$2o$19b2o$17b5o$21bo$17b3o$o16bo$o17b2o$bo16b2o$b2o$3bo$o
17b2o3b2o$2b2o14bobobobo$11bobo5b5o$11b2o7b3o$2o10bo8bo$b2o$b2o2$2o$bo
2$6bobo$2o3bo$bo3bo$o4bo2bo7bo$5b3o7b2o7bo$15bobo5b3o$22b5o$21b2o3b2o$
22b5o$22b5o$14b2o6bo2bo$14bobo4bo3bo$11b2obobo4bo$11bobobo5bob2o$13bo
8bo$4bobo6b2o$7bo5b3o50bo$7bo5b3o3b2o3b2o40b4o$4bo2bo5b3o3bo5bo41b4o$
5b3o5b2o35bo16bo2bo$13bo6bo3bo24bobo15b4o4b2o$11bobobo5b3o15b2o7bob2o
14b4o5b2o$11b2obobo21bobo6b2ob2o14bo8b2o$14bobo20bo6b3obob2o$14b2o12b
2o7bo2bo2bo2bo2bobo$28b2o7bo6b2o4bo16bobo$38bobo26b2o$39b2o27bo4b2o$
21b2o49bo2bo$21b2o28bobo18b3o$52b2o21b2o$52bo21bo$74b2o$59bo$62bo$59bo
14bo$62bo$61bob3o8bo$59b4o2bo9b2o$64bo$52bo$51b2o$40b2o8b2o4b2o5bo$40b
2o7b3o4b2o3bobo$50b2o4b2o2bobo11b2o$4bobo44b2o6bo2bo11b2o$7bo44bo7bobo
$o6bo53bobo$o3bo2bo55bo$5b3o5$4b4o$3bo3bo$7bo$3bo2bo3$o2b3o2b2o$2b5o2b
o64b3o$9o67bo$9b3o63bo$o7bo2bo$9b2o3$4b2o$o3b3o$o5b2obo5b2o$bo4bo2bo5b
2o$2o4b2obo$o3b3o$4b2o2$59b3o12b2o$61bo12b2o!
''', 101, 77),dtype=np.uint32).flatten() * np.arange(77*101)).sum()
expected = 1563304
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')

And got the output: All tests passed

Substring Evaluation

Testing if the previous output contains the string All tests passed: True

Initial Query

LLM Generation

Query

Output

Here's the Python code that converts the Run Length Encoded (RLE) string to a NumPy array using the `rle_to_arr(string, h, w)` function:

import numpy as np

def rle_to_arr(string, h, w):
    arr = np.zeros((h, w), dtype=int)
    lines = string.strip().split("$")
    x, y = 0, 0

    for line in lines:
        nums = line.split("b")
        for num in nums:
            if "o" in num:
                on_count = int(num.split("o")[0] or 1)
                arr[y, x:x+on_count] = 1
                x += on_count
            else:
                off_count = int(num or 1)
                x += off_count
        y += 1
        x = 0

    return arr

# Example usage
rle_string = '''26$13b2o$14bo$14bobo$15b2o14$31b2o$30b2o$32bo13$46b2o$45b2o$47bo13$61b
2o$60b2o$62bo4$52b2o$52b2o$71bo$66b2ob3o$66bobobo$68bo$67b2o3$76b2o$
60b3o12b2o10bobo$52b3o7bo14bo8bo2bo4bo$51bo3bo5bo10b2o11b2o5b2o$50bo5b
o15bobo8b2o3bo8b2o$51bo3bo11b2o6bo9b2o10b2o$52b3o8b2obo2bo2bo2bo10bo2b
o$52bo2bo7b2o2b2o6bo11bobo$53b3o16bobo$53b2obo15b2o$54bobo$55bo3$52b2o
3b2o$52bobobobo$53b5o$54b3o$55bo7$54b2o$54b2o!'''

height, width = 100, 100  # Adjust the height and width as needed
pattern_array = rle_to_arr(rle_string, height, width)

print(pattern_array)

The `rle_to_arr` function takes three arguments: - `string`: The RLE-encoded string representing the Game of Life pattern. - `h`: The desired height of the NumPy array. - `w`: The desired width of the NumPy array. The function performs the following steps: 1. It creates a NumPy array of zeros with the specified height and width using `np.zeros((h, w), dtype=int)`. 2. It splits the RLE string into lines using `string.strip().split("$")`. 3. It iterates over each line and processes the run-length encoded data. 4. For each line, it splits the data into "on" and "off" sections using `line.split("b")`. 5. For each section, if it contains "o", it represents an "on" section. It extracts the count of "on" cells using `int(num.split("o")[0] or 1)` and sets the corresponding elements in the array to 1. 6. If a section doesn't contain "o", it represents an "off" section. It extracts the count of "off" cells using `int(num or 1)` and moves the current position accordingly. 7. After processing each line, it moves to the next row (`y += 1`) and resets the column position (`x = 0`). 8. Finally, it returns the resulting NumPy array. In the example usage, you can adjust the `height` and `width` variables to match the desired dimensions of the output array. The function will convert the RLE-encoded string to a NumPy array, where "on" cells are represented by 1 and empty cells are represented by 0. Note: Make sure to have the NumPy library installed (`pip install numpy`) before running the code.

Extract Code

I extracted the following code from that output:

import numpy as np

def rle_to_arr(string, h, w):
    arr = np.zeros((h, w), dtype=int)
    lines = string.strip().split("$")
    x, y = 0, 0

    for line in lines:
        nums = line.split("b")
        for num in nums:
            if "o" in num:
                on_count = int(num.split("o")[0] or 1)
                arr[y, x:x+on_count] = 1
                x += on_count
            else:
                off_count = int(num or 1)
                x += off_count
        y += 1
        x = 0

    return arr

# Example usage
rle_string = '''26$13b2o$14bo$14bobo$15b2o14$31b2o$30b2o$32bo13$46b2o$45b2o$47bo13$61b
2o$60b2o$62bo4$52b2o$52b2o$71bo$66b2ob3o$66bobobo$68bo$67b2o3$76b2o$
60b3o12b2o10bobo$52b3o7bo14bo8bo2bo4bo$51bo3bo5bo10b2o11b2o5b2o$50bo5b
o15bobo8b2o3bo8b2o$51bo3bo11b2o6bo9b2o10b2o$52b3o8b2obo2bo2bo2bo10bo2b
o$52bo2bo7b2o2b2o6bo11bobo$53b3o16bobo$53b2obo15b2o$54bobo$55bo3$52b2o
3b2o$52bobobobo$53b5o$54b3o$55bo7$54b2o$54b2o!'''

height, width = 100, 100  # Adjust the height and width as needed
pattern_array = rle_to_arr(rle_string, height, width)

print(pattern_array)

Run Code Interpreter

Running the following program:

import numpy as np

def rle_to_arr(string, h, w):
    arr = np.zeros((h, w), dtype=int)
    lines = string.strip().split("$")
    x, y = 0, 0

    for line in lines:
        nums = line.split("b")
        for num in nums:
            if "o" in num:
                on_count = int(num.split("o")[0] or 1)
                arr[y, x:x+on_count] = 1
                x += on_count
            else:
                off_count = int(num or 1)
                x += off_count
        y += 1
        x = 0

    return arr

# Example usage
rle_string = '''26$13b2o$14bo$14bobo$15b2o14$31b2o$30b2o$32bo13$46b2o$45b2o$47bo13$61b
2o$60b2o$62bo4$52b2o$52b2o$71bo$66b2ob3o$66bobobo$68bo$67b2o3$76b2o$
60b3o12b2o10bobo$52b3o7bo14bo8bo2bo4bo$51bo3bo5bo10b2o11b2o5b2o$50bo5b
o15bobo8b2o3bo8b2o$51bo3bo11b2o6bo9b2o10b2o$52b3o8b2obo2bo2bo2bo10bo2b
o$52bo2bo7b2o2b2o6bo11bobo$53b3o16bobo$53b2obo15b2o$54bobo$55bo3$52b2o
3b2o$52bobobobo$53b5o$54b3o$55bo7$54b2o$54b2o!'''

height, width = 100, 100  # Adjust the height and width as needed
pattern_array = rle_to_arr(rle_string, height, width)

print(pattern_array)





answer = (np.array(rle_to_arr('''
16b2o3b2o$2o$2o$19b2o$17b5o$21bo$17b3o$o16bo$o17b2o$bo16b2o$b2o$3bo$o
17b2o3b2o$2b2o14bobobobo$11bobo5b5o$11b2o7b3o$2o10bo8bo$b2o$b2o2$2o$bo
2$6bobo$2o3bo$bo3bo$o4bo2bo7bo$5b3o7b2o7bo$15bobo5b3o$22b5o$21b2o3b2o$
22b5o$22b5o$14b2o6bo2bo$14bobo4bo3bo$11b2obobo4bo$11bobobo5bob2o$13bo
8bo$4bobo6b2o$7bo5b3o50bo$7bo5b3o3b2o3b2o40b4o$4bo2bo5b3o3bo5bo41b4o$
5b3o5b2o35bo16bo2bo$13bo6bo3bo24bobo15b4o4b2o$11bobobo5b3o15b2o7bob2o
14b4o5b2o$11b2obobo21bobo6b2ob2o14bo8b2o$14bobo20bo6b3obob2o$14b2o12b
2o7bo2bo2bo2bo2bobo$28b2o7bo6b2o4bo16bobo$38bobo26b2o$39b2o27bo4b2o$
21b2o49bo2bo$21b2o28bobo18b3o$52b2o21b2o$52bo21bo$74b2o$59bo$62bo$59bo
14bo$62bo$61bob3o8bo$59b4o2bo9b2o$64bo$52bo$51b2o$40b2o8b2o4b2o5bo$40b
2o7b3o4b2o3bobo$50b2o4b2o2bobo11b2o$4bobo44b2o6bo2bo11b2o$7bo44bo7bobo
$o6bo53bobo$o3bo2bo55bo$5b3o5$4b4o$3bo3bo$7bo$3bo2bo3$o2b3o2b2o$2b5o2b
o64b3o$9o67bo$9b3o63bo$o7bo2bo$9b2o3$4b2o$o3b3o$o5b2obo5b2o$bo4bo2bo5b
2o$2o4b2obo$o3b3o$4b2o2$59b3o12b2o$61bo12b2o!
''', 101, 77),dtype=np.uint32).flatten() * np.arange(77*101)).sum()
expected = 1563304
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')

And got the output:

Traceback (most recent call last):
  File "/usr/src/app/main.py", line 33, in <module>
    pattern_array = rle_to_arr(rle_string, height, width)
                    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/usr/src/app/main.py", line 13, in rle_to_arr
    on_count = int(num.split("o")[0] or 1)
               ^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: invalid literal for int() with base 10: '\n'

Substring Evaluation

Testing if the previous output contains the string All tests passed: False

Initial Query

LLM Generation

Query

Output

Here's the implementation of the `rle_to_arr(string, h, w)` function that converts the Run Length Encoded (RLE) pattern of the Game of Life into a NumPy array:

import numpy as np

def rle_to_arr(string, h, w):
    arr = np.zeros((h, w), dtype=int)
    rows = string.split('$')
    row_index = 0

    for row in rows:
        col_index = 0
        i = 0
        while i < len(row):
            if row[i].isdigit():
                num = int(row[i])
                while i + 1 < len(row) and row[i + 1].isdigit():
                    num = num * 10 + int(row[i + 1])
                    i += 1
                if i + 1 < len(row) and row[i + 1] == 'b':
                    col_index += num
                elif i + 1 < len(row) and row[i + 1] == 'o':
                    arr[row_index, col_index:col_index + num] = 1
                    col_index += num
            i += 1
        row_index += 1

    return arr

Here's how the function works: 1. We create a NumPy array `arr` of shape `(h, w)` filled with zeros using `np.zeros((h, w), dtype=int)`. 2. We split the RLE string by the `'$'` character to separate the rows. 3. We initialize `row_index` to keep track of the current row in the array. 4. We iterate over each row in the `rows` list: - Initialize `col_index` to keep track of the current column in the array. - Initialize `i` to keep track of the current position in the row string. - While `i` is less than the length of the row: - If the character at index `i` is a digit, we extract the complete number by concatenating consecutive digits. - If the next character after the number is `'b'`, it represents empty cells, so we increment `col_index` by the number. - If the next character after the number is `'o'`, it represents live cells, so we fill the corresponding elements in `arr` with 1 and increment `col_index` by the number. - Increment `i` to move to the next character in the row. - Increment `row_index` to move to the next row in the array. 5. Finally, we return the `arr` containing the converted pattern. You can call the function by providing the RLE string, the desired height `h`, and the desired width `w` of the array. The function will return a NumPy array representing the Game of Life pattern. Note: Make sure to replace the `!` character at the end of the RLE string with an empty string before passing it to the function.

Extract Code

I extracted the following code from that output:

import numpy as np

def rle_to_arr(string, h, w):
    arr = np.zeros((h, w), dtype=int)
    rows = string.split('$')
    row_index = 0

    for row in rows:
        col_index = 0
        i = 0
        while i < len(row):
            if row[i].isdigit():
                num = int(row[i])
                while i + 1 < len(row) and row[i + 1].isdigit():
                    num = num * 10 + int(row[i + 1])
                    i += 1
                if i + 1 < len(row) and row[i + 1] == 'b':
                    col_index += num
                elif i + 1 < len(row) and row[i + 1] == 'o':
                    arr[row_index, col_index:col_index + num] = 1
                    col_index += num
            i += 1
        row_index += 1

    return arr

Run Code Interpreter

Running the following program:

import numpy as np

def rle_to_arr(string, h, w):
    arr = np.zeros((h, w), dtype=int)
    rows = string.split('$')
    row_index = 0

    for row in rows:
        col_index = 0
        i = 0
        while i < len(row):
            if row[i].isdigit():
                num = int(row[i])
                while i + 1 < len(row) and row[i + 1].isdigit():
                    num = num * 10 + int(row[i + 1])
                    i += 1
                if i + 1 < len(row) and row[i + 1] == 'b':
                    col_index += num
                elif i + 1 < len(row) and row[i + 1] == 'o':
                    arr[row_index, col_index:col_index + num] = 1
                    col_index += num
            i += 1
        row_index += 1

    return arr





answer = (np.array(rle_to_arr('''
16b2o3b2o$2o$2o$19b2o$17b5o$21bo$17b3o$o16bo$o17b2o$bo16b2o$b2o$3bo$o
17b2o3b2o$2b2o14bobobobo$11bobo5b5o$11b2o7b3o$2o10bo8bo$b2o$b2o2$2o$bo
2$6bobo$2o3bo$bo3bo$o4bo2bo7bo$5b3o7b2o7bo$15bobo5b3o$22b5o$21b2o3b2o$
22b5o$22b5o$14b2o6bo2bo$14bobo4bo3bo$11b2obobo4bo$11bobobo5bob2o$13bo
8bo$4bobo6b2o$7bo5b3o50bo$7bo5b3o3b2o3b2o40b4o$4bo2bo5b3o3bo5bo41b4o$
5b3o5b2o35bo16bo2bo$13bo6bo3bo24bobo15b4o4b2o$11bobobo5b3o15b2o7bob2o
14b4o5b2o$11b2obobo21bobo6b2ob2o14bo8b2o$14bobo20bo6b3obob2o$14b2o12b
2o7bo2bo2bo2bo2bobo$28b2o7bo6b2o4bo16bobo$38bobo26b2o$39b2o27bo4b2o$
21b2o49bo2bo$21b2o28bobo18b3o$52b2o21b2o$52bo21bo$74b2o$59bo$62bo$59bo
14bo$62bo$61bob3o8bo$59b4o2bo9b2o$64bo$52bo$51b2o$40b2o8b2o4b2o5bo$40b
2o7b3o4b2o3bobo$50b2o4b2o2bobo11b2o$4bobo44b2o6bo2bo11b2o$7bo44bo7bobo
$o6bo53bobo$o3bo2bo55bo$5b3o5$4b4o$3bo3bo$7bo$3bo2bo3$o2b3o2b2o$2b5o2b
o64b3o$9o67bo$9b3o63bo$o7bo2bo$9b2o3$4b2o$o3b3o$o5b2obo5b2o$bo4bo2bo5b
2o$2o4b2obo$o3b3o$4b2o2$59b3o12b2o$61bo12b2o!
''', 101, 77),dtype=np.uint32).flatten() * np.arange(77*101)).sum()
expected = 1563304
assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
print('All tests passed')

And got the output:

Traceback (most recent call last):
  File "/usr/src/app/main.py", line 49, in <module>
    assert answer == expected, f'Wrong answer; got {answer} instead of {expected}'
           ^^^^^^^^^^^^^^^^^^
AssertionError: Wrong answer; got 945587 instead of 1563304

Substring Evaluation

Testing if the previous output contains the string All tests passed: False