[f] added instantanious values Pinst for RAINLINK

FHSTP/prep.py

@@ -2,8 +2,8 @@
 # Title: Data Preparation for LINK Configs and Transmissions
 # Author: Fabian Kovac <ds191008@fhstp.ac.at>
 # Team: University of Applied Sciences St. Pölten
-# Version: 1.5
-# Last changed: 2021-06-28
+# Version: 2.1
+# Last changed: 2021-07-05
 #
 
 import sys
@@ -253,9 +253,9 @@ def lambert_to_inca_idx(x: np.array, y: np.array) -> tuple:
     x /= 1000
     y /= 1000
     
-    # convert coordinates to INCA index (coordinates as int)
-    ix = x.astype(int)
-    iy = y.astype(int)
+    # convert coordinates to INCA index (nearest coordinates as int)
+    ix = np.round(x, decimals = 0).astype(int)
+    iy = np.round(y, decimals = 0).astype(int)
     
     return ix, iy
 
@@ -431,10 +431,10 @@ def prep() -> None:
     # convert RXFREQUENCY and TXFREQUENCY to float and from MHz to GHz
     # check if columns exists (only present with 2021-05)
     if 'TXFREQUENCY' in df_config.columns and 'RXFREQUENCY' in df_config.columns:
-        df_config['TXFREQUENCY'] = df_config['TXFREQUENCY'].astype('float')
-        df_config['TXFREQUENCY'] = df_config['TXFREQUENCY']/1000
         df_config['RXFREQUENCY'] = df_config['RXFREQUENCY'].astype('float')
         df_config['RXFREQUENCY'] = df_config['RXFREQUENCY']/1000
+        df_config['TXFREQUENCY'] = df_config['TXFREQUENCY'].astype('float')
+        df_config['TXFREQUENCY'] = df_config['TXFREQUENCY']/1000
         _log('Converted RXFREQUENCY and TXFREQUENCY to float and GHz')
     
     
@@ -470,13 +470,13 @@ def prep() -> None:
     # convert 3min windows to 15min windows
     group_cols = [df_link['BEGINTIME'].dt.floor('15Min'), 'RADIOLINKID']
     agg_cols = {
-        'TXLEVEL' : 'mean',
-        'REMOTERXLEVEL' : 'mean',
         'PMIN' : 'min',
         'PMAX' : 'max',
+        'REMOTERXLEVEL' : 'mean',
+        'TXLEVEL' : 'mean',
         'SPEED' : 'mean',
-        'CURRTXBITRATE' : 'mean',
-        'CURRRXBITRATE' : 'mean'
+        'CURRRXBITRATE' : 'mean',
+        'CURRTXBITRATE' : 'mean'
     }
     df_link = df_link.groupby(group_cols).agg(agg_cols).reset_index()
     _log('Converted 3min windows to 15min windows')
@@ -488,17 +488,24 @@ def prep() -> None:
     
     # build df with differences of sending and receiving levels
     df_diff = df_link[['RADIOLINKID', 'TXLEVEL', 'REMOTERXLEVEL']].copy()
-    df_diff['MEANLINKDIFFLEVEL'] = df_diff['TXLEVEL'] - df_diff['REMOTERXLEVEL']
+    df_diff['PINSTMEAN'] = df_diff['TXLEVEL'] - df_diff['REMOTERXLEVEL']
     _log('Built dataframe with mean link difference levels of TXLEVEL and REMOTERXLEVEL')
     
-    # get mean of differences
-    df_diff = df_diff.groupby(['RADIOLINKID']).agg({'MEANLINKDIFFLEVEL' : 'mean'}).reset_index()
+    # get mean of differences per link
+    df_diff = df_diff.groupby(['RADIOLINKID']).agg({'PINSTMEAN' : 'mean'}).reset_index()
     _log('Merged mean link difference levels back to link dataframe')
     
     # merge differences to transmission dataframe
     df_link = pd.merge(df_link, df_diff, how = 'inner', left_on = 'RADIOLINKID', right_on = 'RADIOLINKID')
-    df_link['DIFFLEVEL'] = df_link['TXLEVEL'] - df_link['REMOTERXLEVEL'] - df_link['MEANLINKDIFFLEVEL']
-    _log('Calculated DIFFLEVEL as TXLEVEL - REMOTERXLEVEL - MEANLINKDIFFLEVEL')
+
+    
+    # calculate instantaneous values from transmitted and received signal strength
+    df_link['PINST'] = df_link['TXLEVEL'] - df_link['REMOTERXLEVEL']
+    _log('Calculated instantaneous values PINST from transmitted and received signal strength')
+    
+    # calculate differences from instantaneous values and mean link diff. levels
+    df_link['PDIFF'] = df_link['PINST'] - df_link['PINSTMEAN']
+
     
     
     # merge config and link dataframe
@@ -513,12 +520,13 @@ def prep() -> None:
         'PMIN' : 'Pmin',
         'PMAX' : 'Pmax',
         'REMOTERXLEVEL' : 'Pmean',
+        'PINST' : 'Pinst',
+        'PINSTMEAN' : 'PinstMean',
+        'PDIFF' : 'Pdiff',
         'TXLEVEL' : 'TxLevel',
-        'MEANLINKDIFFLEVEL' : 'MeanLinkDiffLevel',
-        'DIFFLEVEL' : 'DiffLevel',
         'SPEED' : 'Speed',
-        'CURRTXBITRATE' : 'TxBitrate',
         'CURRRXBITRATE' : 'RxBitrate',
+        'CURRTXBITRATE' : 'TxBitrate',
         'LONGITUDE_A' : 'XStart',
         'LATITUDE_A' : 'YStart',
         'LONGITUDE_MID' : 'XMid',
@@ -532,8 +540,8 @@ def prep() -> None:
     # check if RXFREQUENCY and TXFREQUENCY exists (only present with 2021-05)
     if 'TXFREQUENCY' in df_link.columns and 'RXFREQUENCY' in df_link.columns:
         name_cols.update({
-            'TXFREQUENCY' : 'TxFrequency',
-            'RXFREQUENCY' : 'RxFrequency'
+            'RXFREQUENCY' : 'RxFrequency',
+            'TXFREQUENCY' : 'TxFrequency'
         })
     
     df_link = df_link.rename(columns = name_cols).reindex(columns = list(name_cols.values()))