prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  Lesson 10 - numpy.mean(data) and data.mean
  In lesson 10, when the lesson refers to readings_03.py, the code shows that to calculate the mean over 'data' across all days, numpy.mean is used: numpy.mean(data, axis=1). However when looking at the file readings_03.py (at least the version I downloaded recently) uses the instruction  data.mean(axis=1). Both lead to the same result, but for consistency I would suggest to either  modify the readings_*.py to use numpy.mean (as this is what it has been used throughout the entire lesson), or explain explicitly that both expressions lead to the same result (it would be a good time to remind students about object attributes). 
  
  </issue>
  <code>
  [start of code/readings_03.py]
  1 import sys
  2 import numpy
  3 
  4 
  5 def main():
  6     script = sys.argv[0]
  7     for filename in sys.argv[1:]:
  8         data = numpy.loadtxt(filename, delimiter=',')
  9         for m in data.mean(axis=1):
  10             print(m)
  11 
  12 
  13 if __name__ == '__main__':
  14     main()
  15
  [end of code/readings_03.py]
  </code>
  
  I need you to solve this issue by generating a single patch file that I can apply directly to this repository using git apply. Please respond with a single patch file in the following format.
  <patch>
  diff --git a/file.py b/file.py
  --- a/file.py
  +++ b/file.py
  @@ -1,27 +1,35 @@
   def euclidean(a, b):
  -    while b:
  -        a, b = b, a % b
  -    return a
  +    if b == 0:
  +        return a
  +    return euclidean(b, a % b)
   
   
   def bresenham(x0, y0, x1, y1):
       points = []
       dx = abs(x1 - x0)
       dy = abs(y1 - y0)
  -    sx = 1 if x0 < x1 else -1
  -    sy = 1 if y0 < y1 else -1
  -    err = dx - dy
  +    x, y = x0, y0
  +    sx = -1 if x0 > x1 else 1
  +    sy = -1 if y0 > y1 else 1
   
  -    while True:
  -        points.append((x0, y0))
  -        if x0 == x1 and y0 == y1:
  -            break
  -        e2 = 2 * err
  -        if e2 > -dy:
  -            err -= dy
  -            x0 += sx
  -        if e2 < dx:
  -            err += dx
  -            y0 += sy
  +    if dx > dy:
  +        err = dx / 2.0
  +        while x != x1:
  +            points.append((x, y))
  +            err -= dy
  +            if err < 0:
  +                y += sy
  +                err += dx
  +            x += sx
  +    else:
  +        err = dy / 2.0
  +        while y != y1:
  +            points.append((x, y))
  +            err -= dx
  +            if err < 0:
  +                x += sx
  +                err += dy
  +            y += sy
  +
  +    points.append((x, y))
       return points
  
  </patch>
golden_diff: diff --git a/code/readings_03.py b/code/readings_03.py
  --- a/code/readings_03.py
  +++ b/code/readings_03.py
  @@ -6,7 +6,7 @@
       script = sys.argv[0]
       for filename in sys.argv[1:]:
           data = numpy.loadtxt(filename, delimiter=',')
  -        for m in data.mean(axis=1):
  +        for m in numpy.mean(data, axis=1):
               print(m)
  
verification_info: {"golden_diff": "diff --git a/code/readings_03.py b/code/readings_03.py\n--- a/code/readings_03.py\n+++ b/code/readings_03.py\n@@ -6,7 +6,7 @@\n     script = sys.argv[0]\n     for filename in sys.argv[1:]:\n         data = numpy.loadtxt(filename, delimiter=',')\n-        for m in data.mean(axis=1):\n+        for m in numpy.mean(data, axis=1):\n             print(m)\n", "issue": "Lesson 10 - numpy.mean(data) and data.mean\nIn lesson 10, when the lesson refers to readings_03.py, the code shows that to calculate the mean over 'data' across all days, numpy.mean is used: numpy.mean(data, axis=1). However when looking at the file readings_03.py (at least the version I downloaded recently) uses the instruction  data.mean(axis=1). Both lead to the same result, but for consistency I would suggest to either  modify the readings_*.py to use numpy.mean (as this is what it has been used throughout the entire lesson), or explain explicitly that both expressions lead to the same result (it would be a good time to remind students about object attributes). \n", "before_files": [{"content": "import sys\nimport numpy\n\n\ndef main():\n    script = sys.argv[0]\n    for filename in sys.argv[1:]:\n        data = numpy.loadtxt(filename, delimiter=',')\n        for m in data.mean(axis=1):\n            print(m)\n\n\nif __name__ == '__main__':\n    main()\n", "path": "code/readings_03.py"}]}