Update anomaly_detetction model for new photometry (#329)

astrolabsoftware · Sep 7, 2023 · 9e380a8 · 9e380a8
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commit 9e380a8
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Showing 4 changed files with 37 additions and 37 deletions.
diff --git a/fink_science/anomaly_detection/processor.py b/fink_science/anomaly_detection/processor.py
@@ -106,7 +106,7 @@ def anomaly_score(lc_features) -> float:
     >>> df = df.withColumn("anomaly_score", anomaly_score("lc_features"))
 
     >>> df.filter(df["anomaly_score"] < -0.5).count()
-    15
+    7
 
     >>> df.filter(df["anomaly_score"] == 0).count()
     84

diff --git a/fink_science/data/models/anomaly_detection/anomaly_detection_forest.zip b/fink_science/data/models/anomaly_detection/anomaly_detection_forest.zip
diff --git a/fink_science/data/models/anomaly_detection/g_means.csv b/fink_science/data/models/anomaly_detection/g_means.csv
@@ -1,18 +1,18 @@
-amplitude,0.41531597460760716
-anderson_darling_normal,0.4067328678453102
-beyond_1_std,0.31167917031456865
-chi2,26.183010676886607
-cusum,0.3372425908338281
-kurtosis,0.11335890043033195
-linear_fit_slope,-0.0029444268846185347
-linear_fit_slope_sigma,0.004699655331015345
-linear_trend_noise,0.2647739136746347
-linear_trend_sigma,0.012836145756224564
-magnitude_percentage_ratio_20_10,0.6982004429984008
-magnitude_percentage_ratio_40_5,0.20043624078861752
-maximum_slope,67.36071833535601
-median,17.51758072170111
-median_absolute_deviation,0.17445659574111982
-median_buffer_range_percentage_10,0.1931734723952704
-skew,0.2704374599992532
-stetson_K,0.8434945228025993
+amplitude,0.21948567063093466
+anderson_darling_normal,0.5738338537540897
+beyond_1_std,0.2975957082645236
+chi2,37.704414101216535
+cusum,0.3407494402523421
+kurtosis,0.29150516293433526
+linear_fit_slope,0.0008679869820436599
+linear_fit_slope_sigma,0.002219643796867781
+linear_trend_noise,0.1395519301423175
+linear_trend_sigma,0.006530832951936918
+magnitude_percentage_ratio_20_10,0.7096091060287604
+magnitude_percentage_ratio_40_5,0.21345309681339728
+maximum_slope,20.197335141851806
+median,16.09982754358941
+median_absolute_deviation,0.07874299095497293
+median_buffer_range_percentage_10,0.226612517162576
+skew,0.06777187504700471
+stetson_K,0.853534164617388
diff --git a/fink_science/data/models/anomaly_detection/r_means.csv b/fink_science/data/models/anomaly_detection/r_means.csv
@@ -1,18 +1,18 @@
-amplitude,0.41531597460760716
-anderson_darling_normal,0.4067328678453102
-beyond_1_std,0.31167917031456865
-chi2,26.183010676886607
-cusum,0.3372425908338281
-kurtosis,0.11335890043033195
-linear_fit_slope,-0.0029444268846185347
-linear_fit_slope_sigma,0.004699655331015345
-linear_trend_noise,0.2647739136746347
-linear_trend_sigma,0.012836145756224564
-magnitude_percentage_ratio_20_10,0.6982004429984008
-magnitude_percentage_ratio_40_5,0.20043624078861752
-maximum_slope,67.36071833535601
-median,17.51758072170111
-median_absolute_deviation,0.17445659574111982
-median_buffer_range_percentage_10,0.1931734723952704
-skew,0.2704374599992532
-stetson_K,0.8434945228025993
+amplitude,0.27761581012726816
+anderson_darling_normal,0.6324932481221309
+beyond_1_std,0.2984203432923638
+chi2,47.98632140376363
+cusum,0.3353034770643174
+kurtosis,0.19552357158753803
+linear_fit_slope,0.0004677950689235035
+linear_fit_slope_sigma,0.004115135468353454
+linear_trend_noise,0.17699726764662013
+linear_trend_sigma,0.008118738252789526
+magnitude_percentage_ratio_20_10,0.7110312348018119
+magnitude_percentage_ratio_40_5,0.2119754721716743
+maximum_slope,27.23340912206943
+median,17.306199665913482
+median_absolute_deviation,0.09875090359331291
+median_buffer_range_percentage_10,0.22553694294088789
+skew,0.022823198234573093
+stetson_K,0.8580286805997064
Original file line number	Diff line number	Diff line change
Expand Up		@@ -106,7 +106,7 @@ def anomaly_score(lc_features) -> float:
		>>> df = df.withColumn("anomaly_score", anomaly_score("lc_features"))

		>>> df.filter(df["anomaly_score"] < -0.5).count()
		15
		7

		>>> df.filter(df["anomaly_score"] == 0).count()
		84
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