setup ...

data/gan.py

@@ -607,7 +607,7 @@ class Predict(GNet):
                         # r = np.zeros((self.ROW_COUNT,len(columns)))
                         # r = np.zeros(self.ROW_COUNT)
                         if self.logger :
-                                info = {"found":len(found),"selected":INDEX, "ratio": ratio[INDEX],"rows":df.shape[0],"cols":df.shape[1]}
+                                info = {"found":len(found),"selected":INDEX, "ratio": ratio[INDEX],"rows":df.shape[0],"cols":df.shape[1],"expected":len(self.values)}
                                 self.logger.write({"module":"gan-generate","action":"generate","input":info})
                         df.columns = self.values
                         if len(found):

setup.py

@@ -4,7 +4,7 @@ import sys
 
 def read(fname):
     return open(os.path.join(os.path.dirname(__file__), fname)).read() 
-args = {"name":"data-maker","version":"1.1.9","author":"Vanderbilt University Medical Center","author_email":"steve.l.nyemba@vanderbilt.edu","license":"MIT",
+args = {"name":"data-maker","version":"1.2.0","author":"Vanderbilt University Medical Center","author_email":"steve.l.nyemba@vanderbilt.edu","license":"MIT",
         "packages":find_packages(),"keywords":["healthcare","data","transport","protocol"]}
 args["install_requires"] = ['data-transport@git+https://dev.the-phi.com/git/steve/data-transport.git','tensorflow==1.15','pandas','pandas-gbq','pymongo']
 args['url'] = 'https://hiplab.mc.vanderbilt.edu/git/aou/data-maker.git'