add test cases

tests/facial/test_api_facial_activity.py

@@ -0,0 +1,42 @@
+# import numpy as np
+import pandas as pd
+from numpy.testing import assert_allclose
+from pytest import mark
+
+
+# @mark.smoke
+# @mark.body
+@mark.facial
+class FacialTest:
+    def test_get_landmark(self, processing_facial_activity):
+        df_act = pd.read_csv("tests/test_data/landmark.csv")
+        res = processing_facial_activity.get_landmark()
+
+        assert_allclose(df_act.mean(), res.mean(), rtol=0.1, atol=1e-8)
+        assert_allclose(df_act.std(), res.std(), rtol=0.1, atol=1e-8)
+
+    def test_get_action_unit(self, processing_facial_activity):
+
+        df_act = pd.read_csv("tests/test_data/action_unit.csv")
+        res = processing_facial_activity.get_action_unit()
+
+        assert_allclose(df_act.mean(), res.mean(), rtol=0.1, atol=1e-8)
+        assert_allclose(df_act.std(), res.std(), rtol=0.1, atol=1e-8)
+
+    def test_get_asymmetry(self, processing_facial_activity):
+        actual_mean = [2.58260995, 3.34416172, 3.0563894, 2.94777878]
+        actual_std = [1.74161635, 2.17995634, 2.19173686, 1.82435901]
+        res = processing_facial_activity.get_asymmetry()
+
+        assert_allclose(actual_mean, res.mean(), rtol=0.1, atol=1e-8)
+        assert_allclose(actual_std, res.std(), rtol=0.1, atol=1e-8)
+
+    def test_get_expressivity(self, processing_facial_activity):
+        df_act = pd.read_csv("tests/test_data/expressivity.csv")
+        res = processing_facial_activity.get_expressivity()
+
+        assert_allclose(df_act.mean(), res.mean(), rtol=0.35, atol=1e-8)
+        assert_allclose(df_act.std(), res.std(), rtol=0.35, atol=1e-8)
+
+    def test_dummy_facial(self):
+        assert True