From f27f5561ddab2c3163cc20f3297f53f2f53b3884 Mon Sep 17 00:00:00 2001
From: rozetko <rozetko@corpglory.com>
Date: Tue, 29 May 2018 20:31:49 +0300
Subject: [PATCH] 151 fix error on second learning (#5)

---
 README.md                      |  5 +++++
 analytics/anomaly_model.py     | 10 ++++------
 analytics/data_preprocessor.py |  3 +--
 analytics/data_provider.py     |  4 ++--
 4 files changed, 12 insertions(+), 10 deletions(-)

diff --git a/README.md b/README.md
index 1654637..5b8fa1e 100644
--- a/README.md
+++ b/README.md
@@ -66,3 +66,8 @@ export HASTIC_PORT=<port_you_want_to_run_server_on>
 cd ./hastic-server/server
 npm start
 ```
+
+#### Known bugs & issues
+
+- If you add labeled segments while learning - it fails
+- Dataset doesn't get updated after 1st learning
diff --git a/analytics/anomaly_model.py b/analytics/anomaly_model.py
index 30cf7b3..a42de7f 100644
--- a/analytics/anomaly_model.py
+++ b/analytics/anomaly_model.py
@@ -64,14 +64,12 @@ class AnomalyModel:
         if len(anomalies) > 0:
             confidence = 0.0
             min_time, max_time = self.anomalies_box(anomalies)
-            start_index = dataframe[dataframe['timestamp'] >= min_time].index[0]
-            stop_index = dataframe[dataframe['timestamp'] > max_time].index[0]
-            start_index, stop_index = self.preprocessor.expand_indexes(start_index, stop_index)
-        dataframe = dataframe[start_index:stop_index]
+            dataframe = dataframe[dataframe['timestamp'] <= max_time]
+            dataframe = dataframe[dataframe['timestamp'] >= min_time]
 
         train_augmented = self.preprocessor.get_augmented_data(
-            start_index,
-            stop_index,
+            dataframe.index[0],
+            dataframe.index[-1],
             anomalies
         )
 
diff --git a/analytics/data_preprocessor.py b/analytics/data_preprocessor.py
index 6fac01a..9728c56 100644
--- a/analytics/data_preprocessor.py
+++ b/analytics/data_preprocessor.py
@@ -83,8 +83,7 @@ class data_preprocessor:
                 anomaly_index = current_index
 
         rows = dataframe[anomaly_index]
-        indexes = np.floor_divide(rows.index, self.frame_size)
-        # indexes = np.unique(rows.index)
+        indexes = np.unique(rows.index)
         return indexes
 
     def inverse_transform_anomalies(self, prediction):
diff --git a/analytics/data_provider.py b/analytics/data_provider.py
index 167aee3..bc47465 100644
--- a/analytics/data_provider.py
+++ b/analytics/data_provider.py
@@ -28,7 +28,7 @@ class DataProvider:
             if after_time is None or after_time <= last_chunk_time:
                 chunk = self.__load_chunk(chunk_index)
                 if after_time is not None:
-                    chunk = chunk[chunk['timestamp'] > after_time]
+                    chunk = chunk[chunk['timestamp'] >= after_time]
                 result = pd.concat([result, chunk])
         return result
 
@@ -36,7 +36,7 @@ class DataProvider:
         for chunk_index, last_chunk_time in self.chunk_last_times.items():
             if after_time < last_chunk_time:
                 chunk = self.__load_chunk(chunk_index)
-                chunk = chunk[chunk['timestamp'] > after_time]
+                chunk = chunk[chunk['timestamp'] >= after_time]
                 return chunk.index[0]
         return self.size()