39 add fuv dark monitors

cosmo/monitors/dark_monitors.py

@@ -20,8 +20,7 @@ def dark_filter(df_row, filter_pha, location):
     event_df = df_row[['SEGMENT', 'XCORR', 'YCORR', 'PHA', 'TIME']].to_frame().T
     event_df = explode_df(event_df, ['XCORR', 'YCORR', 'PHA', 'TIME'])
     npix = (location[1] - location[0]) * (location[3] - location[2])
-    index = np.where((event_df['SEGMENT'] == 'FUVA') &
-                     (event_df['XCORR'] > location[0]) &
+    index = np.where((event_df['XCORR'] > location[0]) &
                      (event_df['XCORR'] < location[1]) &
                      (event_df['YCORR'] > location[2]) &
                      (event_df['YCORR'] < location[3]))
@@ -46,7 +45,7 @@ class FUVALeftDarkMonitor(BaseMonitor):
     name = 'FUVA Dark Monitor - Left'
     data_model = FUVDarkDataModel
     labels = ['ROOTNAME']
-    # output = add path
+    output = # path
 
     location = (1060, 1260, 296, 734)
     plottype = 'scatter'
@@ -71,3 +70,34 @@ def store_results(self):
     def track(self):
         # TODO: Define something to track
         pass
+
+
+class FUVABottomDarkMonitor(BaseMonitor):
+    name = 'FUVA Dark Monitor - Bottom'
+    data_model = FUVDarkDataModel
+    labels = ['ROOTNAME']
+    output = # path
+
+    location = (1060, 15250, 296, 375)
+    plottype = 'scatter'
+    x = 'date'
+    y = 'darks'
+
+    def get_data(self) -> Any:
+        filtered_rows = []
+        for _, row in self.model.new_data.iterrows():
+            if row.EXPSTART == 0:
+                continue
+            if row.SEGMENT == 'FUVA':
+                filtered_rows.append(dark_filter(row, True, self.location))
+        filtered_df = pd.concat(filtered_rows).reset_index(drop=True)
+
+        return explode_df(filtered_df, ['darks', 'date'])
+
+    def store_results(self):
+        # TODO: Define results to store
+        pass
+
+    def track(self):
+        # TODO: Define something to track
+        pass

cosmo/monitors/data_models.py

@@ -198,11 +198,10 @@ def get_new_data(self):
 
 class FUVDarkDataModel(BaseDataModel):
     files_source = FILES_SOURCE
-    subdir_pattern = '?????'
     cosmo_layout = False
 
-    # program_id = ['15771/', '15533/', '14940/', '14520/', '14436/', '13968/', '13521/', '13121/', '12716/', '12423/',
-    #               '11895/']
+    program_id = ['15771/', '15533/', '14940/', '14520/', '14436/', '13968/', '13521/', '13121/', '12716/', '12423/',
+                  '11895/']
 
     primary_key = 'ROOTNAME'
 
@@ -217,26 +216,19 @@ def get_new_data(self):
             1: ['PHA', 'XCORR', 'YCORR', 'TIME'],
             3: ['TIME', 'LATITUDE', 'LONGITUDE']
         }
-        """
+
         files = []
 
         for prog_id in self.program_id:
 
             new_files_source = os.path.join(FILES_SOURCE, prog_id)
-            files += find_files('*corrtag*', data_dir=new_files_source, subdir_pattern=self.subdir_pattern)
+            files += find_files('*corrtag*', data_dir=new_files_source, subdir_pattern=None)
 
         if self.model is not None:
             currently_ingested = [item.FILENAME for item in self.model.select(self.model.FILENAME)]
 
             for file in currently_ingested:
                 files.remove(file)
-        """
-        files = []
-        program_ids = ['15771/']
-        for program in program_ids:
-            new_files_source = os.path.join(FILES_SOURCE, program)
-            subfiles = glob(os.path.join(new_files_source, "*corrtag*"))
-            files += subfiles
 
         if not files:   # No new files
             return pd.DataFrame()