Running the code with TimeseriesExtractor tests. Getattr() works the best. Issue with the k_factor extraction

Successfull testing the cross correlation. The scipy.stats.personr is used for correlation calculation. Next is to test for all variables and 4 distinct areas

Debug the ARIMA loop with wrong break point of while condition and pqd loop and some minor LSTM plot output. Now with full scale test of 9var and 10 geo-locations

Switching off some printing output and testing if the loop is redundanct for plot_with_markers() function

Because of recurrent kernel dead issue, reducing the number of var and areas to get the procedure done...

After the test for single data, now running the test for multiple data if the Plotter still works for series plot and marker plots

Plotter test completed. Now the 2D plot with markers integrated into the Plotter class within the untils.py module

The same code but with time split posterior to normalization to avoid biases and jumps between train and test sets

Old code with now reduced norms of 2 and increased sampling of 7. Bug is where train and test are separately normalized, which can lead to biases and jumps. This is addressed in the 927*lstm_time code, where it tries to first construct normalized series and then split the data in order to avoid jumps. Issue is still with the time split component, that does not work. Therefore this code is a test reference if the other 927_time code does not work.