RepoRover/collect.py at main · CommittedTeam/RepoRover · GitHub

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from reporover import reporover


  plot_confusion_matrix(labels,predicted, display_labels=types,cmap='Blues',normalize="true")
  plt.show()


# list_ = pd.read_csv("data/new_repos.csv")
# urls = list_.url.tolist()

# print(urls)

# for url in urls:
#     commit_data = pd.DataFrame(parse.get_commit_data(url))
#     print(commit_data)
#     commit_data.to_feather("data/repos/{}.ftr".format(commit_data.name[0]))

# def get_repo_path(url):
#     """Get full repository name from the url"""
#     parsed = giturlparse.parse(url)
#     path = parsed.pathname[1:]
#     return path

# @pytest.mark.parametrize(
#     "input_url,expected_path",
#     [
#       ("https://github.com/GatorEducator/gatorgrader", "GatorEducator/gatorgrader"),
#       ("https://github.com/CommittedTeam/CommitCanvas","CommittedTeam/CommitCanvas"),
#       ("https://github.com/rust-lang/rust", "rust-lang/rust")
#     ]
# )
# def test_get_repo_path(input_url, expected_path):
#     path = get_convention.get_repo_path(input_url)
#     assert path == expected_path

      scorers = ['precision','recall','f1']
      score = [get_scorer(score)._score_func(test_labels, predicted,average="weighted",zero_division=0) for score in scorers]

      print(score)
      classification_scores.update({repo:score})

      plot_confusion_matrix(pipeline, test_features, test_labels, cmap='Blues',normalize="true")
      plt.savefig("classification_reports/{}/matrices/{}.jpg".format(save_fig,repo))

  scores = pd.DataFrame.from_dict(classification_scores, orient='index',columns=scorers)
  scores.to_csv("classification_reports/{}/classification_report.csv".format(save_fig))