def test_todataframe_fromdataframe(self):
print 'test on result to/from dataframe...'
df = self.result.to_dataframe()
df_vmaf = df.loc[df['scores_key'] == 'VMAF_legacy_scores']
df_adm = df.loc[df['scores_key'] == 'VMAF_feature_adm_scores']
df_vif = df.loc[df['scores_key'] == 'VMAF_feature_vif_scores']
df_ansnr = df.loc[df['scores_key'] == 'VMAF_feature_ansnr_scores']
df_motion = df.loc[df['scores_key'] == 'VMAF_feature_motion_scores']
df_adm_den = df.loc[df['scores_key'] == 'VMAF_feature_adm_den_scores']
self.assertEquals(len(df), 37)
self.assertEquals(len(df_vmaf), 1)
self.assertEquals(len(df_adm), 1)
self.assertEquals(len(df_vif), 1)
self.assertEquals(len(df_ansnr), 1)
self.assertEquals(len(df_motion), 1)
self.assertAlmostEquals(np.mean(df_vmaf.iloc[0]['scores']), 44.4942308947, places=4)
self.assertAlmostEquals(np.mean(df_adm.iloc[0]['scores']), 0.813856666667, places=4)
self.assertAlmostEquals(np.mean(df_vif.iloc[0]['scores']), 0.156834666667, places=4)
self.assertAlmostEquals(np.mean(df_ansnr.iloc[0]['scores']), 7.92623066667, places=4)
self.assertAlmostEquals(np.mean(df_motion.iloc[0]['scores']), 12.5548366667, places=4)
self.assertAlmostEquals(np.mean(df_adm_den.iloc[0]['scores']), 30814.9100813, places=3)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_legacy_scores', 'scores')), 44.4942308947, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_adm_scores', 'scores')), 0.813856666667, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_vif_scores', 'scores')), 0.156834666667, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_ansnr_scores', 'scores')), 7.92623066667, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_motion_scores', 'scores')), 12.5548366667, places=4)
self.assertEquals(df.iloc[0]['dataset'], 'test')
self.assertEquals(df.iloc[0]['content_id'], 0)
self.assertEquals(df.iloc[0]['asset_id'], 0)
self.assertEquals(df.iloc[0]['ref_name'], 'checkerboard_1920_1080_10_3_0_0.yuv')
self.assertEquals(df.iloc[0]['dis_name'], 'checkerboard_1920_1080_10_3_1_0.yuv')
self.assertEquals(
df.iloc[0]['asset'],
'{"asset_dict": {"height": 1080, "use_path_as_workpath": 1, "width": 1920}, "asset_id": 0, "content_id": 0, "dataset": "test", "dis_path": "checkerboard_1920_1080_10_3_1_0.yuv", "ref_path": "checkerboard_1920_1080_10_3_0_0.yuv", "workdir": ""}')
self.assertEquals(df.iloc[0]['executor_id'], 'VMAF_legacy_V1.2')
Result._assert_asset_dataframe(df)
recon_result = Result.from_dataframe(df)
self.assertEquals(self.result, recon_result)
self.assertTrue(self.result == recon_result)
self.assertFalse(self.result != recon_result)
def test_todataframe_fromdataframe(self):
print 'test on result to/from dataframe...'
df = self.result.to_dataframe()
df_vmaf = df.loc[df['scores_key'] == 'VMAF_legacy_scores']
df_adm = df.loc[df['scores_key'] == 'VMAF_feature_adm_scores']
df_vif = df.loc[df['scores_key'] == 'VMAF_feature_vif_scores']
df_ansnr = df.loc[df['scores_key'] == 'VMAF_feature_ansnr_scores']
df_motion = df.loc[df['scores_key'] == 'VMAF_feature_motion_scores']
df_adm_den = df.loc[df['scores_key'] == 'VMAF_feature_adm_den_scores']
self.assertEquals(len(df), 37)
self.assertEquals(len(df_vmaf), 1)
self.assertEquals(len(df_adm), 1)
self.assertEquals(len(df_vif), 1)
self.assertEquals(len(df_ansnr), 1)
self.assertEquals(len(df_motion), 1)
self.assertAlmostEquals(np.mean(df_vmaf.iloc[0]['scores']), 44.4942308947, places=4)
self.assertAlmostEquals(np.mean(df_adm.iloc[0]['scores']), 0.813856666667, places=4)
self.assertAlmostEquals(np.mean(df_vif.iloc[0]['scores']), 0.156834666667, places=4)
self.assertAlmostEquals(np.mean(df_ansnr.iloc[0]['scores']), 7.92623066667, places=4)
self.assertAlmostEquals(np.mean(df_motion.iloc[0]['scores']), 12.5548366667, places=4)
self.assertAlmostEquals(np.mean(df_adm_den.iloc[0]['scores']), 30814.9100813, places=3)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_legacy_scores', 'scores')), 44.4942308947, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_adm_scores', 'scores')), 0.813856666667, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_vif_scores', 'scores')), 0.156834666667, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_ansnr_scores', 'scores')), 7.92623066667, places=4)
self.assertAlmostEquals(np.mean(Result.get_unique_from_dataframe(df, 'VMAF_feature_motion_scores', 'scores')), 12.5548366667, places=4)
self.assertEquals(df.iloc[0]['dataset'], 'test')
self.assertEquals(df.iloc[0]['content_id'], 0)
self.assertEquals(df.iloc[0]['asset_id'], 0)
self.assertEquals(df.iloc[0]['ref_name'], 'checkerboard_1920_1080_10_3_0_0.yuv')
self.assertEquals(df.iloc[0]['dis_name'], 'checkerboard_1920_1080_10_3_1_0.yuv')
self.assertEquals(
df.iloc[0]['asset'],
'{"asset_dict": {"height": 1080, "use_path_as_workpath": 1, "width": 1920}, "asset_id": 0, "content_id": 0, "dataset": "test", "dis_path": "checkerboard_1920_1080_10_3_1_0.yuv", "ref_path": "checkerboard_1920_1080_10_3_0_0.yuv", "workdir": ""}')
self.assertEquals(df.iloc[0]['executor_id'], 'VMAF_legacy_V1.2')
Result._assert_asset_dataframe(df)
recon_result = Result.from_dataframe(df)
self.assertEquals(self.result, recon_result)
self.assertTrue(self.result == recon_result)
self.assertFalse(self.result != recon_result)
