Starting to investigate the fact that qualitative features with NaN

[predictops.git] / predictops / source / ephemeris.py

diff --git a/predictops/source/ephemeris.py b/predictops/source/ephemeris.py
index d0e4ca06cb14a5a9ec18e17ce626a83498434647..2a343642bdb3f8959365c71f4b4692c33955e527 100644 (file)
--- a/predictops/source/ephemeris.py
+++ b/predictops/source/ephemeris.py
@@ -1,3 +1,5 @@
+from .source import Source
+

 from configparser import ConfigParser
 from csv import DictReader
 from datetime import datetime, timedelta
 from configparser import ConfigParser
 from csv import DictReader
 from datetime import datetime, timedelta


@@ -16,7 +18,7 @@ class Ephemeris:
     def __init__(self, config_file):
 
         # Check for the integrity of feature names
     def __init__(self, config_file):
 
         # Check for the integrity of feature names

-        super(Source, self).__init__()
+        Source.__init__(self)

 
         self._config = ConfigParser()
         self._config.read(config_file)
 
         self._config = ConfigParser()
         self._config.read(config_file)