Update app.py

app.py

@@ -1,3 +1,4 @@
+
 #%%
 from matplotlib.pyplot import title
 import tensorflow as tf
@@ -20,7 +21,7 @@ mytitles = ["Date Time","p (mbar)","T (degC)","Tpot (K)","Tdew (degC)","rh (%)",
 df = pd.DataFrame(columns=mytitles)
 os.environ["CUDA_DEVICE_ORDER"] = "PCI_BUS_ID"   # see issue #152
 os.environ["CUDA_VISIBLE_DEVICES"] = ""
-mybacklogmax = 4
+mybacklogmax = 5
 
 if ("0" == ""):
 	uri = "https://storage.googleapis.com/tensorflow/tf-keras-datasets/jena_climate_2009_2016.csv.zip"
@@ -54,8 +55,8 @@ if ("0" != ""):
 			break
 #	df = adf.reindex(columns=mytitles)
 #	df = adf.reset_index()
-	df = adf.reindex(pd.RangeIndex(0, mybacklogmax).to_series())
-	st.write(pd.RangeIndex(0, mybacklogmax).to_series())
+#	df = adf.reindex(pd.RangeIndex(0, mybacklogmax).to_series())
+#	st.write(pd.RangeIndex(0, mybacklogmax).to_series())
 	st.dataframe(df)
 
 #%%
@@ -172,7 +173,7 @@ val_data = features.loc[train_split:]
 start = past + future
 end = start + train_split
 
-x_train = train_data[[i for i in range(mybacklogmax)]].values
+x_train = train_data[[i for i in range(train_split)]].values
 y_train = features.iloc[start:end][[1]]
 
 sequence_length = int(past / step)
@@ -180,7 +181,7 @@ x_end = len(val_data) - past - future
 
 label_start = train_split + past + future
 
-x_val = val_data.iloc[:x_end][[i for i in range(mybacklogmax)]].values
+x_val = val_data.iloc[:x_end][[i for i in range(train_split)]].values
 y_val = features.iloc[label_start:][[1]]
 
 dataset_val = keras.preprocessing.timeseries_dataset_from_array(