From 9494746ef80a8d21bf0933d8341e7ba3081414aa Mon Sep 17 00:00:00 2001
From: Lalleh Rafeei <lrafeei@newrelic.com>
Date: Fri, 16 Dec 2022 15:53:59 -0800
Subject: [PATCH] Add discriminant analysis model

---
 newrelic/config.py                            |  6 ++
 newrelic/hooks/mlmodel_sklearn.py             |  8 ++
 .../test_discriminant_analysis_models.py      | 91 +++++++++++++++++++
 3 files changed, 105 insertions(+)
 create mode 100644 tests/mlmodel_sklearn/test_discriminant_analysis_models.py

diff --git a/newrelic/config.py b/newrelic/config.py
index 9a22a7a83..e9be83132 100644
--- a/newrelic/config.py
+++ b/newrelic/config.py
@@ -2902,6 +2902,12 @@ def _process_module_builtin_defaults():
         "instrument_sklearn_ensemble_hist_models",
     )
 
+    _process_module_definition(
+        "sklearn.discriminant_analysis",
+        "newrelic.hooks.mlmodel_sklearn",
+        "instrument_sklearn_discriminant_analysis_models",
+    )
+
     _process_module_definition(
         "rest_framework.views",
         "newrelic.hooks.component_djangorestframework",
diff --git a/newrelic/hooks/mlmodel_sklearn.py b/newrelic/hooks/mlmodel_sklearn.py
index de5a8d6f7..e8dcec3e7 100644
--- a/newrelic/hooks/mlmodel_sklearn.py
+++ b/newrelic/hooks/mlmodel_sklearn.py
@@ -201,6 +201,14 @@ def instrument_sklearn_ensemble_hist_models(module):
     _instrument_sklearn_models(module, model_classes)
 
 
+def instrument_sklearn_discriminant_analysis_models(module):
+    model_classes = (
+        "LinearDiscriminantAnalysis",
+        "QuadraticDiscriminantAnalysis",
+    )
+    _instrument_sklearn_models(module, model_classes)
+
+
 def instrument_sklearn_metrics(module):
     for scorer in METRIC_SCORERS:
         if hasattr(module, scorer):
diff --git a/tests/mlmodel_sklearn/test_discriminant_analysis_models.py b/tests/mlmodel_sklearn/test_discriminant_analysis_models.py
new file mode 100644
index 000000000..de1182696
--- /dev/null
+++ b/tests/mlmodel_sklearn/test_discriminant_analysis_models.py
@@ -0,0 +1,91 @@
+# Copyright 2010 New Relic, Inc.
+#
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#      http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+import pytest
+from testing_support.validators.validate_transaction_metrics import (
+    validate_transaction_metrics,
+)
+
+from newrelic.api.background_task import background_task
+from newrelic.packages import six
+
+
+@pytest.mark.parametrize(
+    "discriminant_analysis_model_name",
+    [
+        "LinearDiscriminantAnalysis",
+        "QuadraticDiscriminantAnalysis",
+    ],
+)
+def test_model_methods_wrapped_in_function_trace(discriminant_analysis_model_name, run_discriminant_analysis_model):
+    expected_scoped_metrics = {
+        "LinearDiscriminantAnalysis": [
+            ("Function/MLModel/Sklearn/Named/LinearDiscriminantAnalysis.fit", 1),
+            ("Function/MLModel/Sklearn/Named/LinearDiscriminantAnalysis.predict_log_proba", 1),
+            ("Function/MLModel/Sklearn/Named/LinearDiscriminantAnalysis.predict_proba", 2),
+            ("Function/MLModel/Sklearn/Named/LinearDiscriminantAnalysis.transform", 1),
+        ],
+        "QuadraticDiscriminantAnalysis": [
+            ("Function/MLModel/Sklearn/Named/QuadraticDiscriminantAnalysis.fit", 1),
+            ("Function/MLModel/Sklearn/Named/QuadraticDiscriminantAnalysis.predict", 1),
+            ("Function/MLModel/Sklearn/Named/QuadraticDiscriminantAnalysis.predict_proba", 2),
+            ("Function/MLModel/Sklearn/Named/QuadraticDiscriminantAnalysis.predict_log_proba", 1),
+        ],
+    }
+
+    expected_transaction_name = (
+        "test_discriminant_analysis_models:test_model_methods_wrapped_in_function_trace.<locals>._test"
+        if six.PY3
+        else "test_discriminant_analysis_models:_test"
+    )
+
+    @validate_transaction_metrics(
+        expected_transaction_name,
+        scoped_metrics=expected_scoped_metrics[discriminant_analysis_model_name],
+        rollup_metrics=expected_scoped_metrics[discriminant_analysis_model_name],
+        background_task=True,
+    )
+    @background_task()
+    def _test():
+        run_discriminant_analysis_model(discriminant_analysis_model_name)
+
+    _test()
+
+
+@pytest.fixture
+def run_discriminant_analysis_model():
+    def _run(discriminant_analysis_model_name):
+        import sklearn.discriminant_analysis
+        from sklearn.datasets import load_iris
+        from sklearn.model_selection import train_test_split
+
+        X, y = load_iris(return_X_y=True)
+        x_train, x_test, y_train, y_test = train_test_split(X, y, stratify=y, random_state=0)
+
+        kwargs = {}
+        clf = getattr(sklearn.discriminant_analysis, discriminant_analysis_model_name)(**kwargs)
+
+        model = clf.fit(x_train, y_train)
+        if hasattr(model, "predict"):
+            model.predict(x_test)
+        if hasattr(model, "predict_log_proba"):
+            model.predict_log_proba(x_test)
+        if hasattr(model, "predict_proba"):
+            model.predict_proba(x_test)
+        if hasattr(model, "transform"):
+            model.transform(x_test)
+
+        return model
+
+    return _run