In [1]:

    

import pandas as pd
import numpy as np

# @@@@@@@@@@@@@@ RELATIVE PATHS @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
Base_Path = "./"
image_path = "./images/"
train_path = "./train/"
test_path = "./test/"
analysis_path = "./analysis/"
models_path = analysis_path + "models_to_load/"
results_path = analysis_path + "model_loader_results/"
stats_tests_path = analysis_path + 'stats_tests/'
#@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@

sequence = np.load(test_path + '/data/sequence_1b_59_10_fv1c.npy')
label = np.load(test_path + '/label/sequence_1b_59_10_label_fv1c.npy')
print('sequence shape: ',sequence.shape, 'label shape: ', label.shape)


    

    




('sequence shape: ', (97201, 11), 'label shape: ', (97201, 5))

In [2]:

    

#    train_list = ['StepIndex','percent_damage','delta_K_current_1','ctip_posn_curr_1','delta_K_current_2','ctip_posn_curr_2',
          #'delta_K_current_3','ctip_posn_curr_3','delta_K_current_4','ctip_posn_curr_4','Load_1','Load_2']
print(sequence[100000:100100,[2,4,6,8]])
print(label[100000:100100,:])


    

    




[]
[]

In [3]:

    

sequence_df = pd.DataFrame(sequence)
label_df = pd.DataFrame(label)
print(sequence_df.head(1))
sequence_df.to_csv(stats_tests_path + 'ref_array.csv')
label_df.to_csv(stats_tests_path + 'ref_target.csv')


    

    




    0    1         2    3         4    5         6    7         8      9   \
0  5.0  0.0  0.490625  0.0  1.365625  0.0  1.415625  0.0  2.253125  1.428   

      10  
0  12.28  

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