class_docstr: Test the PrecisionRecallCurve visualizer
class_docstr_tok: ["Test","the","PrecisionRecallCurve","visualizer"]
docstr: Test if both per_class and micro set to True, user gets micro ignored warning
docstr_tok: ["Test","if","both","per_class","and","micro","set","to","True",",","user","gets","micro","ignored","warning"]
code: def test_per_class_and_micro(self):
      """
      Test if both per_class and micro set to True, user gets micro ignored warning
      """
      msg = (
          "micro=True is ignored;"
          "specify per_class=False to draw a PR curve after micro-averaging"
      )
      with pytest.warns(YellowbrickWarning, match=msg):
          PrecisionRecallCurve(
              RidgeClassifier(random_state=13),
              micro=True,
              per_class=True,
              show=False,
          )
  
imports: import sys
  import pytest
  import matplotlib
  from yellowbrick.exceptions import *
  from yellowbrick.classifier.prcurve import *
  from yellowbrick.datasets import load_occupancy
  from tests.base import IS_WINDOWS_OR_CONDA, VisualTestCase
  from .test_rocauc import FakeClassifier
  from sklearn.svm import LinearSVC, SVC
  from sklearn.naive_bayes import GaussianNB
  from sklearn.datasets import make_regression
  from sklearn.tree import DecisionTreeClassifier
  from sklearn.linear_model import RidgeClassifier
  from sklearn.model_selection import train_test_split
  from sklearn.ensemble import RandomForestClassifier, AdaBoostClassifier
  from sklearn.pipeline import Pipeline
  from sklearn.preprocessing import MinMaxScaler
label_desc: Use image node_id 15 for calling the TestPrecisionRecallCurve obj's underlying member method code with example usage: obj.test_per_class_and_micro() without return types