prompt: You will be provided with a partial code base and an issue statement explaining a problem to resolve.
  <issue>
  returning test statistic in LDT
  some practitioners (read: Vince, cep) only care about the test statistic and not the p-value. obviously one can still extract it if they perform the full test. however, that wastes time and resources. one can set the number of iterations to 1 to minimize that, but we can still do less. i propose to allow the number of permutations to be set to 0 (hyppo allows that, so really it is just a change in argument check). i am happy to do this, but:
  
  this brings up the following questions: what should be happening to the fit_predict in that case? should it return the test statistic instead? or the p-value of 1? or NaN? should we be raising warnings?
  
  and on a larger scale: should we really have this API? should fit predict return p-value, or a tuple of a p-value and a test statistic, like many other tests in python? furthremore, should it really be a class? once again, most tests in python that i have seen (scipy, statsmodels) are functions, not classes.
  
  </issue>
  <code>
  [start of setup.py]
  1 import os
  2 import sys
  3 from setuptools import setup, find_packages
  4 from sys import platform
  5 
  6 PACKAGE_NAME = "graspy"
  7 DESCRIPTION = "A set of python modules for graph statistics"
  8 with open("README.md", "r") as f:
  9     LONG_DESCRIPTION = f.read()
  10 AUTHOR = ("Eric Bridgeford, Jaewon Chung, Benjamin Pedigo, Bijan Varjavand",)
  11 AUTHOR_EMAIL = "j1c@jhu.edu"
  12 URL = "https://github.com/neurodata/graspy"
  13 MINIMUM_PYTHON_VERSION = 3, 6  # Minimum of Python 3.5
  14 REQUIRED_PACKAGES = [
  15     "networkx>=2.1",
  16     "numpy>=1.8.1",
  17     "scikit-learn>=0.19.1",
  18     "scipy>=1.1.0",
  19     "seaborn>=0.9.0",
  20     "matplotlib>=3.0.0",
  21     "hyppo>=0.1.2",
  22 ]
  23 
  24 
  25 # Find GraSPy version.
  26 PROJECT_PATH = os.path.dirname(os.path.abspath(__file__))
  27 for line in open(os.path.join(PROJECT_PATH, "graspy", "__init__.py")):
  28     if line.startswith("__version__ = "):
  29         VERSION = line.strip().split()[2][1:-1]
  30 
  31 
  32 def check_python_version():
  33     """Exit when the Python version is too low."""
  34     if sys.version_info < MINIMUM_PYTHON_VERSION:
  35         sys.exit("Python {}.{}+ is required.".format(*MINIMUM_PYTHON_VERSION))
  36 
  37 
  38 check_python_version()
  39 
  40 setup(
  41     name=PACKAGE_NAME,
  42     version=VERSION,
  43     description=DESCRIPTION,
  44     long_description=LONG_DESCRIPTION,
  45     long_description_content_type="text/markdown",
  46     author=AUTHOR,
  47     author_email=AUTHOR_EMAIL,
  48     install_requires=REQUIRED_PACKAGES,
  49     url=URL,
  50     license="Apache License 2.0",
  51     classifiers=[
  52         "Development Status :: 3 - Alpha",
  53         "Intended Audience :: Science/Research",
  54         "Topic :: Scientific/Engineering :: Mathematics",
  55         "License :: OSI Approved :: Apache Software License",
  56         "Programming Language :: Python :: 3",
  57         "Programming Language :: Python :: 3.6",
  58         "Programming Language :: Python :: 3.7",
  59     ],
  60     packages=find_packages(),
  61     include_package_data=True,
  62 )
  63
  [end of setup.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/setup.py b/setup.py
  --- a/setup.py
  +++ b/setup.py
  @@ -18,7 +18,7 @@
       "scipy>=1.1.0",
       "seaborn>=0.9.0",
       "matplotlib>=3.0.0",
  -    "hyppo>=0.1.2",
  +    "hyppo>=0.1.3",
   ]
  
verification_info: {"golden_diff": "diff --git a/setup.py b/setup.py\n--- a/setup.py\n+++ b/setup.py\n@@ -18,7 +18,7 @@\n     \"scipy>=1.1.0\",\n     \"seaborn>=0.9.0\",\n     \"matplotlib>=3.0.0\",\n-    \"hyppo>=0.1.2\",\n+    \"hyppo>=0.1.3\",\n ]\n", "issue": "returning test statistic in LDT\nsome practitioners (read: Vince, cep) only care about the test statistic and not the p-value. obviously one can still extract it if they perform the full test. however, that wastes time and resources. one can set the number of iterations to 1 to minimize that, but we can still do less. i propose to allow the number of permutations to be set to 0 (hyppo allows that, so really it is just a change in argument check). i am happy to do this, but:\r\n\r\nthis brings up the following questions: what should be happening to the fit_predict in that case? should it return the test statistic instead? or the p-value of 1? or NaN? should we be raising warnings?\r\n\r\nand on a larger scale: should we really have this API? should fit predict return p-value, or a tuple of a p-value and a test statistic, like many other tests in python? furthremore, should it really be a class? once again, most tests in python that i have seen (scipy, statsmodels) are functions, not classes.\n", "before_files": [{"content": "import os\nimport sys\nfrom setuptools import setup, find_packages\nfrom sys import platform\n\nPACKAGE_NAME = \"graspy\"\nDESCRIPTION = \"A set of python modules for graph statistics\"\nwith open(\"README.md\", \"r\") as f:\n    LONG_DESCRIPTION = f.read()\nAUTHOR = (\"Eric Bridgeford, Jaewon Chung, Benjamin Pedigo, Bijan Varjavand\",)\nAUTHOR_EMAIL = \"j1c@jhu.edu\"\nURL = \"https://github.com/neurodata/graspy\"\nMINIMUM_PYTHON_VERSION = 3, 6  # Minimum of Python 3.5\nREQUIRED_PACKAGES = [\n    \"networkx>=2.1\",\n    \"numpy>=1.8.1\",\n    \"scikit-learn>=0.19.1\",\n    \"scipy>=1.1.0\",\n    \"seaborn>=0.9.0\",\n    \"matplotlib>=3.0.0\",\n    \"hyppo>=0.1.2\",\n]\n\n\n# Find GraSPy version.\nPROJECT_PATH = os.path.dirname(os.path.abspath(__file__))\nfor line in open(os.path.join(PROJECT_PATH, \"graspy\", \"__init__.py\")):\n    if line.startswith(\"__version__ = \"):\n        VERSION = line.strip().split()[2][1:-1]\n\n\ndef check_python_version():\n    \"\"\"Exit when the Python version is too low.\"\"\"\n    if sys.version_info < MINIMUM_PYTHON_VERSION:\n        sys.exit(\"Python {}.{}+ is required.\".format(*MINIMUM_PYTHON_VERSION))\n\n\ncheck_python_version()\n\nsetup(\n    name=PACKAGE_NAME,\n    version=VERSION,\n    description=DESCRIPTION,\n    long_description=LONG_DESCRIPTION,\n    long_description_content_type=\"text/markdown\",\n    author=AUTHOR,\n    author_email=AUTHOR_EMAIL,\n    install_requires=REQUIRED_PACKAGES,\n    url=URL,\n    license=\"Apache License 2.0\",\n    classifiers=[\n        \"Development Status :: 3 - Alpha\",\n        \"Intended Audience :: Science/Research\",\n        \"Topic :: Scientific/Engineering :: Mathematics\",\n        \"License :: OSI Approved :: Apache Software License\",\n        \"Programming Language :: Python :: 3\",\n        \"Programming Language :: Python :: 3.6\",\n        \"Programming Language :: Python :: 3.7\",\n    ],\n    packages=find_packages(),\n    include_package_data=True,\n)\n", "path": "setup.py"}]}