In [1]:
from corpus_characterizer import generator_chunker
import numpy as np
import os
# from sklearn.metrics import mean_squared_error,mean_absolute_error, median_absolute_error, mean_squared_log_error, explained_variance_score, r2_score
from sklearn.metrics import mean_squared_error, mean_absolute_error, median_absolute_error, explained_variance_score, \
r2_score
import pandas as pd
from scipy.stats import describe, kurtosistest, skewtest, normaltest
from Conv1D_LSTM_Ensemble import pair_generator_1dconv_lstm_bagged
from Conv1D_ActivationSearch_BigLoop import pair_generator_1dconv_lstm #NOT BAGGED
from AuxRegressor import create_testing_set, create_training_set
import matplotlib.pyplot as plt
# @@@@@@@@@@@@@@ RELATIVE PATHS @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@
Base_Path = "./"
image_path = "./images/"
train_path = "./train/"
test_path = "./test/"
analysis_path = "./analysis/"
chunker_path = analysis_path + "chunker/"
preds_path = analysis_path + "preds/"
#create the data-pair filenames (using zip), use the helper methods
train_set_filenames = create_training_set()
test_set_filenames = create_testing_set()
print(train_set_filenames)
print(test_set_filenames)
Using Theano backend.
after shuffling: [('sequence_3a_709_11_fv1c.npy', 'sequence_3a_709_11_label_fv1c.npy'), ('sequence_3a_613_15_fv1c.npy', 'sequence_3a_613_15_label_fv1c.npy'), ('sequence_1d_225_6_fv1c.npy', 'sequence_1d_225_6_label_fv1c.npy'), ('sequence_1d_126_7_fv1c.npy', 'sequence_1d_126_7_label_fv1c.npy'), ('sequence_3a_577_18_fv1c.npy', 'sequence_3a_577_18_label_fv1c.npy'), ('sequence_1d_124_5_fv1c.npy', 'sequence_1d_124_5_label_fv1c.npy'), ('sequence_1d_251_2_fv1c.npy', 'sequence_1d_251_2_label_fv1c.npy'), ('sequence_1b_55_6_fv1c.npy', 'sequence_1b_55_6_label_fv1c.npy'), ('sequence_1l_384_5_fv1c.npy', 'sequence_1l_384_5_label_fv1c.npy'), ('sequence_1c_72_3_fv1c.npy', 'sequence_1c_72_3_label_fv1c.npy'), ('sequence_1c_102_3_fv1c.npy', 'sequence_1c_102_3_label_fv1c.npy'), ('sequence_1c_87_8_fv1c.npy', 'sequence_1c_87_8_label_fv1c.npy'), ('sequence_1d_174_15_fv1c.npy', 'sequence_1d_174_15_label_fv1c.npy'), ('sequence_2c_541_2_fv1c.npy', 'sequence_2c_541_2_label_fv1c.npy'), ('sequence_1d_252_3_fv1c.npy', 'sequence_1d_252_3_label_fv1c.npy'), ('sequence_1d_144_15_fv1c.npy', 'sequence_1d_144_15_label_fv1c.npy'), ('sequence_1l_432_3_fv1c.npy', 'sequence_1l_432_3_label_fv1c.npy'), ('sequence_1d_123_4_fv1c.npy', 'sequence_1d_123_4_label_fv1c.npy'), ('sequence_1d_242_23_fv1c.npy', 'sequence_1d_242_23_label_fv1c.npy'), ('sequence_2b_490_1_fv1c.npy', 'sequence_2b_490_1_label_fv1c.npy'), ('sequence_1b_23_4_fv1c.npy', 'sequence_1b_23_4_label_fv1c.npy'), ('sequence_1d_210_21_fv1c.npy', 'sequence_1d_210_21_label_fv1c.npy'), ('sequence_3a_605_7_fv1c.npy', 'sequence_3a_605_7_label_fv1c.npy'), ('sequence_3a_662_4_fv1c.npy', 'sequence_3a_662_4_label_fv1c.npy'), ('sequence_1c_84_5_fv1c.npy', 'sequence_1c_84_5_label_fv1c.npy'), ('sequence_3a_626_8_fv1c.npy', 'sequence_3a_626_8_label_fv1c.npy'), ('sequence_2c_542_3_fv1c.npy', 'sequence_2c_542_3_label_fv1c.npy'), ('sequence_2b_494_5_fv1c.npy', 'sequence_2b_494_5_label_fv1c.npy'), ('sequence_3a_591_13_fv1c.npy', 'sequence_3a_591_13_label_fv1c.npy'), ('sequence_1d_190_1_fv1c.npy', 'sequence_1d_190_1_label_fv1c.npy'), ('sequence_2b_452_3_fv1c.npy', 'sequence_2b_452_3_label_fv1c.npy'), ('sequence_1b_52_3_fv1c.npy', 'sequence_1b_52_3_label_fv1c.npy'), ('sequence_1l_371_2_fv1c.npy', 'sequence_1l_371_2_label_fv1c.npy'), ('sequence_3a_691_13_fv1c.npy', 'sequence_3a_691_13_label_fv1c.npy'), ('sequence_1k_337_8_fv1c.npy', 'sequence_1k_337_8_label_fv1c.npy'), ('sequence_3a_574_15_fv1c.npy', 'sequence_3a_574_15_label_fv1c.npy'), ('sequence_1b_4_5_fv1c.npy', 'sequence_1b_4_5_label_fv1c.npy'), ('sequence_1k_324_5_fv1c.npy', 'sequence_1k_324_5_label_fv1c.npy'), ('sequence_3a_696_18_fv1c.npy', 'sequence_3a_696_18_label_fv1c.npy'), ('sequence_1l_425_6_fv1c.npy', 'sequence_1l_425_6_label_fv1c.npy'), ('sequence_1k_303_4_fv1c.npy', 'sequence_1k_303_4_label_fv1c.npy'), ('sequence_1b_31_2_fv1c.npy', 'sequence_1b_31_2_label_fv1c.npy'), ('sequence_1l_421_2_fv1c.npy', 'sequence_1l_421_2_label_fv1c.npy'), ('sequence_3a_711_13_fv1c.npy', 'sequence_3a_711_13_label_fv1c.npy'), ('sequence_3a_637_19_fv1c.npy', 'sequence_3a_637_19_label_fv1c.npy'), ('sequence_3a_595_17_fv1c.npy', 'sequence_3a_595_17_label_fv1c.npy'), ('sequence_1b_24_5_fv1c.npy', 'sequence_1b_24_5_label_fv1c.npy'), ('sequence_1l_377_8_fv1c.npy', 'sequence_1l_377_8_label_fv1c.npy'), ('sequence_1d_234_15_fv1c.npy', 'sequence_1d_234_15_label_fv1c.npy'), ('sequence_3a_664_6_fv1c.npy', 'sequence_3a_664_6_label_fv1c.npy'), ('sequence_1d_256_7_fv1c.npy', 'sequence_1d_256_7_label_fv1c.npy'), ('sequence_3a_600_2_fv1c.npy', 'sequence_3a_600_2_label_fv1c.npy'), ('sequence_1k_280_1_fv1c.npy', 'sequence_1k_280_1_label_fv1c.npy'), ('sequence_1c_112_3_fv1c.npy', 'sequence_1c_112_3_label_fv1c.npy'), ('sequence_1c_105_6_fv1c.npy', 'sequence_1c_105_6_label_fv1c.npy'), ('sequence_3a_635_17_fv1c.npy', 'sequence_3a_635_17_label_fv1c.npy'), ('sequence_2c_544_5_fv1c.npy', 'sequence_2c_544_5_label_fv1c.npy'), ('sequence_1b_57_8_fv1c.npy', 'sequence_1b_57_8_label_fv1c.npy'), ('sequence_1d_156_27_fv1c.npy', 'sequence_1d_156_27_label_fv1c.npy'), ('sequence_1d_151_22_fv1c.npy', 'sequence_1d_151_22_label_fv1c.npy'), ('sequence_1d_219_30_fv1c.npy', 'sequence_1d_219_30_label_fv1c.npy'), ('sequence_3a_653_15_fv1c.npy', 'sequence_3a_653_15_label_fv1c.npy'), ('sequence_1c_107_8_fv1c.npy', 'sequence_1c_107_8_label_fv1c.npy'), ('sequence_2c_552_3_fv1c.npy', 'sequence_2c_552_3_label_fv1c.npy'), ('sequence_3a_659_1_fv1c.npy', 'sequence_3a_659_1_label_fv1c.npy'), ('sequence_3a_670_12_fv1c.npy', 'sequence_3a_670_12_label_fv1c.npy'), ('sequence_1k_307_8_fv1c.npy', 'sequence_1k_307_8_label_fv1c.npy'), ('sequence_1d_205_16_fv1c.npy', 'sequence_1d_205_16_label_fv1c.npy'), ('sequence_1d_176_17_fv1c.npy', 'sequence_1d_176_17_label_fv1c.npy'), ('sequence_1d_175_16_fv1c.npy', 'sequence_1d_175_16_label_fv1c.npy'), ('sequence_1b_11_2_fv1c.npy', 'sequence_1b_11_2_label_fv1c.npy'), ('sequence_1b_0_1_fv1c.npy', 'sequence_1b_0_1_label_fv1c.npy'), ('sequence_1k_296_7_fv1c.npy', 'sequence_1k_296_7_label_fv1c.npy'), ('sequence_2c_514_5_fv1c.npy', 'sequence_2c_514_5_label_fv1c.npy'), ('sequence_2b_466_7_fv1c.npy', 'sequence_2b_466_7_label_fv1c.npy'), ('sequence_3a_663_5_fv1c.npy', 'sequence_3a_663_5_label_fv1c.npy'), ('sequence_2b_491_2_fv1c.npy', 'sequence_2b_491_2_label_fv1c.npy'), ('sequence_3a_717_19_fv1c.npy', 'sequence_3a_717_19_label_fv1c.npy'), ('sequence_1k_335_6_fv1c.npy', 'sequence_1k_335_6_label_fv1c.npy'), ('sequence_1b_53_4_fv1c.npy', 'sequence_1b_53_4_label_fv1c.npy'), ('sequence_1d_224_5_fv1c.npy', 'sequence_1d_224_5_label_fv1c.npy'), ('sequence_3a_561_2_fv1c.npy', 'sequence_3a_561_2_label_fv1c.npy'), ('sequence_1c_61_2_fv1c.npy', 'sequence_1c_61_2_label_fv1c.npy'), ('sequence_1k_283_4_fv1c.npy', 'sequence_1k_283_4_label_fv1c.npy'), ('sequence_1d_227_8_fv1c.npy', 'sequence_1d_227_8_label_fv1c.npy'), ('sequence_1d_221_2_fv1c.npy', 'sequence_1d_221_2_label_fv1c.npy'), ('sequence_3a_584_6_fv1c.npy', 'sequence_3a_584_6_label_fv1c.npy'), ('sequence_1k_306_7_fv1c.npy', 'sequence_1k_306_7_label_fv1c.npy'), ('sequence_3a_620_2_fv1c.npy', 'sequence_3a_620_2_label_fv1c.npy'), ('sequence_3a_564_5_fv1c.npy', 'sequence_3a_564_5_label_fv1c.npy'), ('sequence_1b_6_7_fv1c.npy', 'sequence_1b_6_7_label_fv1c.npy'), ('sequence_1b_5_6_fv1c.npy', 'sequence_1b_5_6_label_fv1c.npy'), ('sequence_1d_271_22_fv1c.npy', 'sequence_1d_271_22_label_fv1c.npy'), ('sequence_3a_618_20_fv1c.npy', 'sequence_3a_618_20_label_fv1c.npy'), ('sequence_1d_146_17_fv1c.npy', 'sequence_1d_146_17_label_fv1c.npy'), ('sequence_2c_507_8_fv1c.npy', 'sequence_2c_507_8_label_fv1c.npy'), ('sequence_1k_281_2_fv1c.npy', 'sequence_1k_281_2_label_fv1c.npy'), ('sequence_2b_487_8_fv1c.npy', 'sequence_2b_487_8_label_fv1c.npy'), ('sequence_1c_113_4_fv1c.npy', 'sequence_1c_113_4_label_fv1c.npy'), ('sequence_1c_74_5_fv1c.npy', 'sequence_1c_74_5_label_fv1c.npy'), ('sequence_1k_356_7_fv1c.npy', 'sequence_1k_356_7_label_fv1c.npy'), ('sequence_2b_470_1_fv1c.npy', 'sequence_2b_470_1_label_fv1c.npy'), ('sequence_1c_85_6_fv1c.npy', 'sequence_1c_85_6_label_fv1c.npy'), ('sequence_1l_423_4_fv1c.npy', 'sequence_1l_423_4_label_fv1c.npy'), ('sequence_3a_693_15_fv1c.npy', 'sequence_3a_693_15_label_fv1c.npy'), ('sequence_3a_713_15_fv1c.npy', 'sequence_3a_713_15_label_fv1c.npy'), ('sequence_2b_497_8_fv1c.npy', 'sequence_2b_497_8_label_fv1c.npy'), ('sequence_3a_644_6_fv1c.npy', 'sequence_3a_644_6_label_fv1c.npy'), ('sequence_1k_295_6_fv1c.npy', 'sequence_1k_295_6_label_fv1c.npy'), ('sequence_1l_365_6_fv1c.npy', 'sequence_1l_365_6_label_fv1c.npy'), ('sequence_2b_457_8_fv1c.npy', 'sequence_2b_457_8_label_fv1c.npy'), ('sequence_3a_674_16_fv1c.npy', 'sequence_3a_674_16_label_fv1c.npy'), ('sequence_1d_260_11_fv1c.npy', 'sequence_1d_260_11_label_fv1c.npy'), ('sequence_1k_352_3_fv1c.npy', 'sequence_1k_352_3_label_fv1c.npy'), ('sequence_1c_100_1_fv1c.npy', 'sequence_1c_100_1_label_fv1c.npy'), ('sequence_2b_460_1_fv1c.npy', 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'sequence_1b_22_3_label_fv1c.npy'), ('sequence_3a_702_4_fv1c.npy', 'sequence_3a_702_4_label_fv1c.npy'), ('sequence_2b_442_3_fv1c.npy', 'sequence_2b_442_3_label_fv1c.npy'), ('sequence_1k_282_3_fv1c.npy', 'sequence_1k_282_3_label_fv1c.npy'), ('sequence_1d_140_11_fv1c.npy', 'sequence_1d_140_11_label_fv1c.npy'), ('sequence_2b_455_6_fv1c.npy', 'sequence_2b_455_6_label_fv1c.npy'), ('sequence_1k_340_1_fv1c.npy', 'sequence_1k_340_1_label_fv1c.npy'), ('sequence_1k_293_4_fv1c.npy', 'sequence_1k_293_4_label_fv1c.npy'), ('sequence_2c_500_1_fv1c.npy', 'sequence_2c_500_1_label_fv1c.npy'), ('sequence_3a_692_14_fv1c.npy', 'sequence_3a_692_14_label_fv1c.npy'), ('sequence_1b_45_6_fv1c.npy', 'sequence_1b_45_6_label_fv1c.npy'), ('sequence_1d_270_21_fv1c.npy', 'sequence_1d_270_21_label_fv1c.npy'), ('sequence_1d_180_21_fv1c.npy', 'sequence_1d_180_21_label_fv1c.npy'), ('sequence_1k_292_3_fv1c.npy', 'sequence_1k_292_3_label_fv1c.npy'), ('sequence_1d_183_24_fv1c.npy', 'sequence_1d_183_24_label_fv1c.npy'), ('sequence_1c_93_4_fv1c.npy', 'sequence_1c_93_4_label_fv1c.npy'), ('sequence_1d_201_12_fv1c.npy', 'sequence_1d_201_12_label_fv1c.npy'), ('sequence_2b_474_5_fv1c.npy', 'sequence_2b_474_5_label_fv1c.npy'), ('sequence_1b_33_4_fv1c.npy', 'sequence_1b_33_4_label_fv1c.npy'), ('sequence_1l_400_1_fv1c.npy', 'sequence_1l_400_1_label_fv1c.npy'), ('sequence_3a_601_3_fv1c.npy', 'sequence_3a_601_3_label_fv1c.npy'), ('sequence_1l_360_1_fv1c.npy', 'sequence_1l_360_1_label_fv1c.npy'), ('sequence_1d_277_28_fv1c.npy', 'sequence_1d_277_28_label_fv1c.npy'), ('sequence_3a_578_19_fv1c.npy', 'sequence_3a_578_19_label_fv1c.npy'), ('sequence_3a_706_8_fv1c.npy', 'sequence_3a_706_8_label_fv1c.npy'), ('sequence_3a_625_7_fv1c.npy', 'sequence_3a_625_7_label_fv1c.npy'), ('sequence_1k_353_4_fv1c.npy', 'sequence_1k_353_4_label_fv1c.npy'), ('sequence_1d_153_24_fv1c.npy', 'sequence_1d_153_24_label_fv1c.npy'), ('sequence_1k_311_2_fv1c.npy', 'sequence_1k_311_2_label_fv1c.npy'), ('sequence_3a_671_13_fv1c.npy', 'sequence_3a_671_13_label_fv1c.npy'), ('sequence_1d_269_20_fv1c.npy', 'sequence_1d_269_20_label_fv1c.npy'), ('sequence_3a_632_14_fv1c.npy', 'sequence_3a_632_14_label_fv1c.npy'), ('sequence_3a_694_16_fv1c.npy', 'sequence_3a_694_16_label_fv1c.npy')]
Training data read.
after shuffling: [('sequence_2b_458_9_fv1c.npy', 'sequence_2b_458_9_label_fv1c.npy'), ('sequence_1l_419_10_fv1c.npy', 'sequence_1l_419_10_label_fv1c.npy'), ('sequence_2b_479_10_fv1c.npy', 'sequence_2b_479_10_label_fv1c.npy'), ('sequence_1c_118_9_fv1c.npy', 'sequence_1c_118_9_label_fv1c.npy'), ('sequence_3a_607_9_fv1c.npy', 'sequence_3a_607_9_label_fv1c.npy'), ('sequence_1d_228_9_fv1c.npy', 'sequence_1d_228_9_label_fv1c.npy'), ('sequence_3a_569_10_fv1c.npy', 'sequence_3a_569_10_label_fv1c.npy'), ('sequence_1b_58_9_fv1c.npy', 'sequence_1b_58_9_label_fv1c.npy'), ('sequence_3a_628_10_fv1c.npy', 'sequence_3a_628_10_label_fv1c.npy'), ('sequence_2c_508_9_fv1c.npy', 'sequence_2c_508_9_label_fv1c.npy'), ('sequence_1l_388_9_fv1c.npy', 'sequence_1l_388_9_label_fv1c.npy'), ('sequence_1l_368_9_fv1c.npy', 'sequence_1l_368_9_label_fv1c.npy'), ('sequence_2b_498_9_fv1c.npy', 'sequence_2b_498_9_label_fv1c.npy'), ('sequence_1k_319_10_fv1c.npy', 'sequence_1k_319_10_label_fv1c.npy'), ('sequence_2c_509_10_fv1c.npy', 'sequence_2c_509_10_label_fv1c.npy'), ('sequence_1c_98_9_fv1c.npy', 'sequence_1c_98_9_label_fv1c.npy'), ('sequence_1l_428_9_fv1c.npy', 'sequence_1l_428_9_label_fv1c.npy'), ('sequence_2b_489_10_fv1c.npy', 'sequence_2b_489_10_label_fv1c.npy'), ('sequence_1b_8_9_fv1c.npy', 'sequence_1b_8_9_label_fv1c.npy'), ('sequence_1l_398_9_fv1c.npy', 'sequence_1l_398_9_label_fv1c.npy'), ('sequence_3a_688_10_fv1c.npy', 'sequence_3a_688_10_label_fv1c.npy'), ('sequence_2c_518_9_fv1c.npy', 'sequence_2c_518_9_label_fv1c.npy'), ('sequence_1k_288_9_fv1c.npy', 'sequence_1k_288_9_label_fv1c.npy'), ('sequence_1k_338_9_fv1c.npy', 'sequence_1k_338_9_label_fv1c.npy'), ('sequence_1c_119_10_fv1c.npy', 'sequence_1c_119_10_label_fv1c.npy'), ('sequence_2c_538_9_fv1c.npy', 'sequence_2c_538_9_label_fv1c.npy'), ('sequence_2b_478_9_fv1c.npy', 'sequence_2b_478_9_label_fv1c.npy'), ('sequence_1b_18_9_fv1c.npy', 'sequence_1b_18_9_label_fv1c.npy'), ('sequence_1l_378_9_fv1c.npy', 'sequence_1l_378_9_label_fv1c.npy'), ('sequence_1c_79_10_fv1c.npy', 'sequence_1c_79_10_label_fv1c.npy'), ('sequence_1k_298_9_fv1c.npy', 'sequence_1k_298_9_label_fv1c.npy'), ('sequence_1l_409_10_fv1c.npy', 'sequence_1l_409_10_label_fv1c.npy'), ('sequence_2c_559_10_fv1c.npy', 'sequence_2c_559_10_label_fv1c.npy'), ('sequence_1b_39_10_fv1c.npy', 'sequence_1b_39_10_label_fv1c.npy'), ('sequence_1k_308_9_fv1c.npy', 'sequence_1k_308_9_label_fv1c.npy'), ('sequence_1k_328_9_fv1c.npy', 'sequence_1k_328_9_label_fv1c.npy'), ('sequence_3a_687_9_fv1c.npy', 'sequence_3a_687_9_label_fv1c.npy'), ('sequence_2b_449_10_fv1c.npy', 'sequence_2b_449_10_label_fv1c.npy'), ('sequence_2c_549_10_fv1c.npy', 'sequence_2c_549_10_label_fv1c.npy'), ('sequence_3a_588_10_fv1c.npy', 'sequence_3a_588_10_label_fv1c.npy'), ('sequence_1l_369_10_fv1c.npy', 'sequence_1l_369_10_label_fv1c.npy'), ('sequence_1l_379_10_fv1c.npy', 'sequence_1l_379_10_label_fv1c.npy'), ('sequence_1b_48_9_fv1c.npy', 'sequence_1b_48_9_label_fv1c.npy'), ('sequence_1c_108_9_fv1c.npy', 'sequence_1c_108_9_label_fv1c.npy'), ('sequence_1d_229_10_fv1c.npy', 'sequence_1d_229_10_label_fv1c.npy'), ('sequence_1c_89_10_fv1c.npy', 'sequence_1c_89_10_label_fv1c.npy'), ('sequence_2b_468_9_fv1c.npy', 'sequence_2b_468_9_label_fv1c.npy'), ('sequence_1b_59_10_fv1c.npy', 'sequence_1b_59_10_label_fv1c.npy'), ('sequence_3a_587_9_fv1c.npy', 'sequence_3a_587_9_label_fv1c.npy'), ('sequence_1d_199_10_fv1c.npy', 'sequence_1d_199_10_label_fv1c.npy'), ('sequence_1k_359_10_fv1c.npy', 'sequence_1k_359_10_label_fv1c.npy'), ('sequence_1c_78_9_fv1c.npy', 'sequence_1c_78_9_label_fv1c.npy'), ('sequence_1c_69_10_fv1c.npy', 'sequence_1c_69_10_label_fv1c.npy'), ('sequence_1l_418_9_fv1c.npy', 'sequence_1l_418_9_label_fv1c.npy'), ('sequence_1k_348_9_fv1c.npy', 'sequence_1k_348_9_label_fv1c.npy'), ('sequence_3a_667_9_fv1c.npy', 'sequence_3a_667_9_label_fv1c.npy'), ('sequence_3a_708_10_fv1c.npy', 'sequence_3a_708_10_label_fv1c.npy'), ('sequence_1d_129_10_fv1c.npy', 'sequence_1d_129_10_label_fv1c.npy'), ('sequence_2c_528_9_fv1c.npy', 'sequence_2c_528_9_label_fv1c.npy'), ('sequence_1k_349_10_fv1c.npy', 'sequence_1k_349_10_label_fv1c.npy'), ('sequence_1l_429_10_fv1c.npy', 'sequence_1l_429_10_label_fv1c.npy'), ('sequence_3a_608_10_fv1c.npy', 'sequence_3a_608_10_label_fv1c.npy'), ('sequence_3a_568_9_fv1c.npy', 'sequence_3a_568_9_label_fv1c.npy'), ('sequence_1l_438_9_fv1c.npy', 'sequence_1l_438_9_label_fv1c.npy'), ('sequence_1k_289_10_fv1c.npy', 'sequence_1k_289_10_label_fv1c.npy'), ('sequence_2c_558_9_fv1c.npy', 'sequence_2c_558_9_label_fv1c.npy'), ('sequence_1k_299_10_fv1c.npy', 'sequence_1k_299_10_label_fv1c.npy'), ('sequence_3a_627_9_fv1c.npy', 'sequence_3a_627_9_label_fv1c.npy'), ('sequence_1k_309_10_fv1c.npy', 'sequence_1k_309_10_label_fv1c.npy'), ('sequence_1l_439_10_fv1c.npy', 'sequence_1l_439_10_label_fv1c.npy'), ('sequence_1l_389_10_fv1c.npy', 'sequence_1l_389_10_label_fv1c.npy'), ('sequence_1b_9_10_fv1c.npy', 'sequence_1b_9_10_label_fv1c.npy'), ('sequence_3a_707_9_fv1c.npy', 'sequence_3a_707_9_label_fv1c.npy'), ('sequence_1d_198_9_fv1c.npy', 'sequence_1d_198_9_label_fv1c.npy'), ('sequence_3a_647_9_fv1c.npy', 'sequence_3a_647_9_label_fv1c.npy'), ('sequence_1b_19_10_fv1c.npy', 'sequence_1b_19_10_label_fv1c.npy'), ('sequence_1d_138_9_fv1c.npy', 'sequence_1d_138_9_label_fv1c.npy'), ('sequence_2b_488_9_fv1c.npy', 'sequence_2b_488_9_label_fv1c.npy'), ('sequence_1c_99_10_fv1c.npy', 'sequence_1c_99_10_label_fv1c.npy'), ('sequence_3a_668_10_fv1c.npy', 'sequence_3a_668_10_label_fv1c.npy'), ('sequence_1k_358_9_fv1c.npy', 'sequence_1k_358_9_label_fv1c.npy'), ('sequence_1l_408_9_fv1c.npy', 'sequence_1l_408_9_label_fv1c.npy'), ('sequence_3a_648_10_fv1c.npy', 'sequence_3a_648_10_label_fv1c.npy'), ('sequence_2c_529_10_fv1c.npy', 'sequence_2c_529_10_label_fv1c.npy'), ('sequence_1b_49_10_fv1c.npy', 'sequence_1b_49_10_label_fv1c.npy'), ('sequence_2b_469_10_fv1c.npy', 'sequence_2b_469_10_label_fv1c.npy'), ('sequence_1k_318_9_fv1c.npy', 'sequence_1k_318_9_label_fv1c.npy'), ('sequence_1d_128_9_fv1c.npy', 'sequence_1d_128_9_label_fv1c.npy'), ('sequence_2b_448_9_fv1c.npy', 'sequence_2b_448_9_label_fv1c.npy'), ('sequence_2c_519_10_fv1c.npy', 'sequence_2c_519_10_label_fv1c.npy'), ('sequence_1k_339_10_fv1c.npy', 'sequence_1k_339_10_label_fv1c.npy'), ('sequence_1k_329_10_fv1c.npy', 'sequence_1k_329_10_label_fv1c.npy'), ('sequence_1d_169_10_fv1c.npy', 'sequence_1d_169_10_label_fv1c.npy'), ('sequence_1d_258_9_fv1c.npy', 'sequence_1d_258_9_label_fv1c.npy'), ('sequence_1c_68_9_fv1c.npy', 'sequence_1c_68_9_label_fv1c.npy'), ('sequence_2c_548_9_fv1c.npy', 'sequence_2c_548_9_label_fv1c.npy'), ('sequence_1c_109_10_fv1c.npy', 'sequence_1c_109_10_label_fv1c.npy'), ('sequence_1b_28_9_fv1c.npy', 'sequence_1b_28_9_label_fv1c.npy'), ('sequence_1d_139_10_fv1c.npy', 'sequence_1d_139_10_label_fv1c.npy'), ('sequence_2b_499_10_fv1c.npy', 'sequence_2b_499_10_label_fv1c.npy'), ('sequence_1d_168_9_fv1c.npy', 'sequence_1d_168_9_label_fv1c.npy'), ('sequence_1l_399_10_fv1c.npy', 'sequence_1l_399_10_label_fv1c.npy'), ('sequence_1b_38_9_fv1c.npy', 'sequence_1b_38_9_label_fv1c.npy'), ('sequence_2c_539_10_fv1c.npy', 'sequence_2c_539_10_label_fv1c.npy'), ('sequence_1b_29_10_fv1c.npy', 'sequence_1b_29_10_label_fv1c.npy'), ('sequence_1c_88_9_fv1c.npy', 'sequence_1c_88_9_label_fv1c.npy'), ('sequence_1d_259_10_fv1c.npy', 'sequence_1d_259_10_label_fv1c.npy'), ('sequence_2b_459_10_fv1c.npy', 'sequence_2b_459_10_label_fv1c.npy')]
Test set read.
[('sequence_3a_709_11_fv1c.npy', 'sequence_3a_709_11_label_fv1c.npy'), ('sequence_3a_613_15_fv1c.npy', 'sequence_3a_613_15_label_fv1c.npy'), ('sequence_1d_225_6_fv1c.npy', 'sequence_1d_225_6_label_fv1c.npy'), ('sequence_1d_126_7_fv1c.npy', 'sequence_1d_126_7_label_fv1c.npy'), ('sequence_3a_577_18_fv1c.npy', 'sequence_3a_577_18_label_fv1c.npy'), ('sequence_1d_124_5_fv1c.npy', 'sequence_1d_124_5_label_fv1c.npy'), ('sequence_1d_251_2_fv1c.npy', 'sequence_1d_251_2_label_fv1c.npy'), ('sequence_1b_55_6_fv1c.npy', 'sequence_1b_55_6_label_fv1c.npy'), ('sequence_1l_384_5_fv1c.npy', 'sequence_1l_384_5_label_fv1c.npy'), ('sequence_1c_72_3_fv1c.npy', 'sequence_1c_72_3_label_fv1c.npy'), ('sequence_1c_102_3_fv1c.npy', 'sequence_1c_102_3_label_fv1c.npy'), ('sequence_1c_87_8_fv1c.npy', 'sequence_1c_87_8_label_fv1c.npy'), ('sequence_1d_174_15_fv1c.npy', 'sequence_1d_174_15_label_fv1c.npy'), ('sequence_2c_541_2_fv1c.npy', 'sequence_2c_541_2_label_fv1c.npy'), ('sequence_1d_252_3_fv1c.npy', 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[('sequence_2b_458_9_fv1c.npy', 'sequence_2b_458_9_label_fv1c.npy'), ('sequence_1l_419_10_fv1c.npy', 'sequence_1l_419_10_label_fv1c.npy'), ('sequence_2b_479_10_fv1c.npy', 'sequence_2b_479_10_label_fv1c.npy'), ('sequence_1c_118_9_fv1c.npy', 'sequence_1c_118_9_label_fv1c.npy'), ('sequence_3a_607_9_fv1c.npy', 'sequence_3a_607_9_label_fv1c.npy'), ('sequence_1d_228_9_fv1c.npy', 'sequence_1d_228_9_label_fv1c.npy'), ('sequence_3a_569_10_fv1c.npy', 'sequence_3a_569_10_label_fv1c.npy'), ('sequence_1b_58_9_fv1c.npy', 'sequence_1b_58_9_label_fv1c.npy'), ('sequence_3a_628_10_fv1c.npy', 'sequence_3a_628_10_label_fv1c.npy'), ('sequence_2c_508_9_fv1c.npy', 'sequence_2c_508_9_label_fv1c.npy'), ('sequence_1l_388_9_fv1c.npy', 'sequence_1l_388_9_label_fv1c.npy'), ('sequence_1l_368_9_fv1c.npy', 'sequence_1l_368_9_label_fv1c.npy'), ('sequence_2b_498_9_fv1c.npy', 'sequence_2b_498_9_label_fv1c.npy'), ('sequence_1k_319_10_fv1c.npy', 'sequence_1k_319_10_label_fv1c.npy'), ('sequence_2c_509_10_fv1c.npy', 'sequence_2c_509_10_label_fv1c.npy'), ('sequence_1c_98_9_fv1c.npy', 'sequence_1c_98_9_label_fv1c.npy'), ('sequence_1l_428_9_fv1c.npy', 'sequence_1l_428_9_label_fv1c.npy'), ('sequence_2b_489_10_fv1c.npy', 'sequence_2b_489_10_label_fv1c.npy'), ('sequence_1b_8_9_fv1c.npy', 'sequence_1b_8_9_label_fv1c.npy'), ('sequence_1l_398_9_fv1c.npy', 'sequence_1l_398_9_label_fv1c.npy'), ('sequence_3a_688_10_fv1c.npy', 'sequence_3a_688_10_label_fv1c.npy'), ('sequence_2c_518_9_fv1c.npy', 'sequence_2c_518_9_label_fv1c.npy'), ('sequence_1k_288_9_fv1c.npy', 'sequence_1k_288_9_label_fv1c.npy'), ('sequence_1k_338_9_fv1c.npy', 'sequence_1k_338_9_label_fv1c.npy'), ('sequence_1c_119_10_fv1c.npy', 'sequence_1c_119_10_label_fv1c.npy'), ('sequence_2c_538_9_fv1c.npy', 'sequence_2c_538_9_label_fv1c.npy'), ('sequence_2b_478_9_fv1c.npy', 'sequence_2b_478_9_label_fv1c.npy'), ('sequence_1b_18_9_fv1c.npy', 'sequence_1b_18_9_label_fv1c.npy'), ('sequence_1l_378_9_fv1c.npy', 'sequence_1l_378_9_label_fv1c.npy'), ('sequence_1c_79_10_fv1c.npy', 'sequence_1c_79_10_label_fv1c.npy'), ('sequence_1k_298_9_fv1c.npy', 'sequence_1k_298_9_label_fv1c.npy'), ('sequence_1l_409_10_fv1c.npy', 'sequence_1l_409_10_label_fv1c.npy'), ('sequence_2c_559_10_fv1c.npy', 'sequence_2c_559_10_label_fv1c.npy'), ('sequence_1b_39_10_fv1c.npy', 'sequence_1b_39_10_label_fv1c.npy'), ('sequence_1k_308_9_fv1c.npy', 'sequence_1k_308_9_label_fv1c.npy'), ('sequence_1k_328_9_fv1c.npy', 'sequence_1k_328_9_label_fv1c.npy'), ('sequence_3a_687_9_fv1c.npy', 'sequence_3a_687_9_label_fv1c.npy'), ('sequence_2b_449_10_fv1c.npy', 'sequence_2b_449_10_label_fv1c.npy'), ('sequence_2c_549_10_fv1c.npy', 'sequence_2c_549_10_label_fv1c.npy'), ('sequence_3a_588_10_fv1c.npy', 'sequence_3a_588_10_label_fv1c.npy'), ('sequence_1l_369_10_fv1c.npy', 'sequence_1l_369_10_label_fv1c.npy'), ('sequence_1l_379_10_fv1c.npy', 'sequence_1l_379_10_label_fv1c.npy'), ('sequence_1b_48_9_fv1c.npy', 'sequence_1b_48_9_label_fv1c.npy'), ('sequence_1c_108_9_fv1c.npy', 'sequence_1c_108_9_label_fv1c.npy'), ('sequence_1d_229_10_fv1c.npy', 'sequence_1d_229_10_label_fv1c.npy'), ('sequence_1c_89_10_fv1c.npy', 'sequence_1c_89_10_label_fv1c.npy'), ('sequence_2b_468_9_fv1c.npy', 'sequence_2b_468_9_label_fv1c.npy'), ('sequence_1b_59_10_fv1c.npy', 'sequence_1b_59_10_label_fv1c.npy'), ('sequence_3a_587_9_fv1c.npy', 'sequence_3a_587_9_label_fv1c.npy'), ('sequence_1d_199_10_fv1c.npy', 'sequence_1d_199_10_label_fv1c.npy'), ('sequence_1k_359_10_fv1c.npy', 'sequence_1k_359_10_label_fv1c.npy'), ('sequence_1c_78_9_fv1c.npy', 'sequence_1c_78_9_label_fv1c.npy'), ('sequence_1c_69_10_fv1c.npy', 'sequence_1c_69_10_label_fv1c.npy'), ('sequence_1l_418_9_fv1c.npy', 'sequence_1l_418_9_label_fv1c.npy'), ('sequence_1k_348_9_fv1c.npy', 'sequence_1k_348_9_label_fv1c.npy'), ('sequence_3a_667_9_fv1c.npy', 'sequence_3a_667_9_label_fv1c.npy'), ('sequence_3a_708_10_fv1c.npy', 'sequence_3a_708_10_label_fv1c.npy'), ('sequence_1d_129_10_fv1c.npy', 'sequence_1d_129_10_label_fv1c.npy'), ('sequence_2c_528_9_fv1c.npy', 'sequence_2c_528_9_label_fv1c.npy'), ('sequence_1k_349_10_fv1c.npy', 'sequence_1k_349_10_label_fv1c.npy'), ('sequence_1l_429_10_fv1c.npy', 'sequence_1l_429_10_label_fv1c.npy'), ('sequence_3a_608_10_fv1c.npy', 'sequence_3a_608_10_label_fv1c.npy'), ('sequence_3a_568_9_fv1c.npy', 'sequence_3a_568_9_label_fv1c.npy'), ('sequence_1l_438_9_fv1c.npy', 'sequence_1l_438_9_label_fv1c.npy'), ('sequence_1k_289_10_fv1c.npy', 'sequence_1k_289_10_label_fv1c.npy'), ('sequence_2c_558_9_fv1c.npy', 'sequence_2c_558_9_label_fv1c.npy'), ('sequence_1k_299_10_fv1c.npy', 'sequence_1k_299_10_label_fv1c.npy'), ('sequence_3a_627_9_fv1c.npy', 'sequence_3a_627_9_label_fv1c.npy'), ('sequence_1k_309_10_fv1c.npy', 'sequence_1k_309_10_label_fv1c.npy'), ('sequence_1l_439_10_fv1c.npy', 'sequence_1l_439_10_label_fv1c.npy'), ('sequence_1l_389_10_fv1c.npy', 'sequence_1l_389_10_label_fv1c.npy'), ('sequence_1b_9_10_fv1c.npy', 'sequence_1b_9_10_label_fv1c.npy'), ('sequence_3a_707_9_fv1c.npy', 'sequence_3a_707_9_label_fv1c.npy'), ('sequence_1d_198_9_fv1c.npy', 'sequence_1d_198_9_label_fv1c.npy'), ('sequence_3a_647_9_fv1c.npy', 'sequence_3a_647_9_label_fv1c.npy'), ('sequence_1b_19_10_fv1c.npy', 'sequence_1b_19_10_label_fv1c.npy'), ('sequence_1d_138_9_fv1c.npy', 'sequence_1d_138_9_label_fv1c.npy'), ('sequence_2b_488_9_fv1c.npy', 'sequence_2b_488_9_label_fv1c.npy'), ('sequence_1c_99_10_fv1c.npy', 'sequence_1c_99_10_label_fv1c.npy'), ('sequence_3a_668_10_fv1c.npy', 'sequence_3a_668_10_label_fv1c.npy'), ('sequence_1k_358_9_fv1c.npy', 'sequence_1k_358_9_label_fv1c.npy'), ('sequence_1l_408_9_fv1c.npy', 'sequence_1l_408_9_label_fv1c.npy'), ('sequence_3a_648_10_fv1c.npy', 'sequence_3a_648_10_label_fv1c.npy'), ('sequence_2c_529_10_fv1c.npy', 'sequence_2c_529_10_label_fv1c.npy'), ('sequence_1b_49_10_fv1c.npy', 'sequence_1b_49_10_label_fv1c.npy'), ('sequence_2b_469_10_fv1c.npy', 'sequence_2b_469_10_label_fv1c.npy'), ('sequence_1k_318_9_fv1c.npy', 'sequence_1k_318_9_label_fv1c.npy'), ('sequence_1d_128_9_fv1c.npy', 'sequence_1d_128_9_label_fv1c.npy'), ('sequence_2b_448_9_fv1c.npy', 'sequence_2b_448_9_label_fv1c.npy'), ('sequence_2c_519_10_fv1c.npy', 'sequence_2c_519_10_label_fv1c.npy'), ('sequence_1k_339_10_fv1c.npy', 'sequence_1k_339_10_label_fv1c.npy'), ('sequence_1k_329_10_fv1c.npy', 'sequence_1k_329_10_label_fv1c.npy'), ('sequence_1d_169_10_fv1c.npy', 'sequence_1d_169_10_label_fv1c.npy'), ('sequence_1d_258_9_fv1c.npy', 'sequence_1d_258_9_label_fv1c.npy'), ('sequence_1c_68_9_fv1c.npy', 'sequence_1c_68_9_label_fv1c.npy'), ('sequence_2c_548_9_fv1c.npy', 'sequence_2c_548_9_label_fv1c.npy'), ('sequence_1c_109_10_fv1c.npy', 'sequence_1c_109_10_label_fv1c.npy'), ('sequence_1b_28_9_fv1c.npy', 'sequence_1b_28_9_label_fv1c.npy'), ('sequence_1d_139_10_fv1c.npy', 'sequence_1d_139_10_label_fv1c.npy'), ('sequence_2b_499_10_fv1c.npy', 'sequence_2b_499_10_label_fv1c.npy'), ('sequence_1d_168_9_fv1c.npy', 'sequence_1d_168_9_label_fv1c.npy'), ('sequence_1l_399_10_fv1c.npy', 'sequence_1l_399_10_label_fv1c.npy'), ('sequence_1b_38_9_fv1c.npy', 'sequence_1b_38_9_label_fv1c.npy'), ('sequence_2c_539_10_fv1c.npy', 'sequence_2c_539_10_label_fv1c.npy'), ('sequence_1b_29_10_fv1c.npy', 'sequence_1b_29_10_label_fv1c.npy'), ('sequence_1c_88_9_fv1c.npy', 'sequence_1c_88_9_label_fv1c.npy'), ('sequence_1d_259_10_fv1c.npy', 'sequence_1d_259_10_label_fv1c.npy'), ('sequence_2b_459_10_fv1c.npy', 'sequence_2b_459_10_label_fv1c.npy')]
In [2]:
#features_list = ['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']
# train_list = ['StepIndex','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'] #and seq_id,somehow
unique_init_conds = []
training_seqname_initcond_dict = {}
combined_seqname_initcond_dict = {}
for files in train_set_filenames:
data_load_path = train_path + '/data/' + files[0]
label_load_path = train_path + '/label/' + files[1]
# print("data/label load path: {} \n {}".format(data_load_path,label_load_path))
train_array = np.load(data_load_path)
train_label_array = np.load(label_load_path)[:, 1:]
if train_array.shape[1] == 12:
train_array = train_array[:,1:] #skip step_index.
if "fv1c" not in str(files[0]):
print(train_array[0,:])
#init_cond = train_array[0,[3,5,7,9]]
init_cond = train_array[0,[2,4,6,8]]
if "fv1c" in str(files[0]):
init_cond = train_array[0,[2,4,6,8]]
#print(str(files[0])," init cond",init_cond)
print(str(files[0])," init cond2",train_array[0,:])
print(str(files[0])," init cond2",train_array[1,:])
training_seqname_initcond_dict[str(files[0])] = str(init_cond)
array_equality = False
if len(unique_init_conds) == 0:
unique_init_conds.append(init_cond)
if len(unique_init_conds) != 0:
for ic in unique_init_conds:
if np.array_equal(init_cond,ic) == True:
#print("equal array found in list?", np.array_equal(load_seq,load_sequence))
array_equality = True
if array_equality == False:
unique_init_conds.append(init_cond) #the load types
#print("first 6 rows:",train_array[0:2,:])
print("there are ",len(unique_init_conds)," init conds in the training set")
print("unique init conds:",unique_init_conds)
('sequence_3a_709_11_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.610625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_709_11_fv1c.npy', ' init cond2', array([ 27.00025342, 8.24998091, 0.61062629, 8.69953772,
1.33562346, 8.52377605, 1.51562638, 8.21240627,
2.13062373, 14.28 , 0.5 ]))
('sequence_3a_613_15_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.610625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_613_15_fv1c.npy', ' init cond2', array([ 27.00028525, 8.47764173, 0.61062643, 8.47764173,
1.33562357, 8.47764173, 1.51562643, 8.47764173,
2.13062357, 14.28 , 1.75 ]))
('sequence_1d_225_6_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.725 , 0. , 1.475 , 0. ,
1.525 , 0. , 2.2375, 1.428 , 14.28 ]))
('sequence_1d_225_6_fv1c.npy', ' init cond2', array([ 27.00026276, 8.63936652, 0.72499856, 8.37601966,
1.4749986 , 7.73581075, 1.52500103, 8.37198057,
2.23749869, 14.28 , 0.75 ]))
('sequence_1d_126_7_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1d_126_7_fv1c.npy', ' init cond2', array([ 27.00028912, 7.95249087, 0.41062383, 8.14732306,
1.33562373, 8.21808851, 1.51562629, 8.53668439,
2.13062355, 14.28 , 1. ]))
('sequence_3a_577_18_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.610625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_577_18_fv1c.npy', ' init cond2', array([ 27.00033703, 9.24892384, 0.61062689, 7.70874257,
1.33562396, 8.05089178, 1.5156262 , 8.92756943,
2.13062331, 14.28 , 1. ]))
('sequence_1d_124_5_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1d_124_5_fv1c.npy', ' init cond2', array([ 27.00030866, 8.67767974, 0.41062344, 9.00227734,
1.33562329, 7.94564809, 1.51562616, 8.7380473 ,
2.13062346, 14.28 , 1. ]))
('sequence_1d_251_2_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.725 , 0. , 1.475 , 0. ,
1.525 , 0. , 2.2375, 1.428 , 12.28 ]))
('sequence_1d_251_2_fv1c.npy', ' init cond2', array([ 27.00021505, 7.04194881, 0.7249992 , 7.37010203,
1.47499907, 7.38048928, 1.52500094, 7.68352007,
2.23749892, 12.28 , 1.428 ]))
('sequence_1b_55_6_fv1c.npy', ' init cond2', array([ 5. , 0. , 0.490625, 0. , 1.365625,
0. , 1.415625, 0. , 2.253125, 1.428 , 12.28 ]))
('sequence_1b_55_6_fv1c.npy', ' init cond2', array([ 5.00022408, 7.06053672, 0.49062423, 7.12470948,
1.3656242 , 7.9909838 , 1.41562612, 5.94384412,
2.25312457, 12.28 , 1.428 ]))
('sequence_1l_384_5_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1l_384_5_fv1c.npy', ' init cond2', array([ 27.00027553, 8.47764173, 0.41062354, 8.47764173,
1.33562356, 8.47764173, 1.51562648, 8.47764173,
2.13062362, 14.28 , 1.75 ]))
('sequence_1c_72_3_fv1c.npy', ' init cond2', array([ 5. , 0. , 0.490625, 0. , 1.365625,
0. , 1.415625, 0. , 2.253125, 1.428 , 14.28 ]))
('sequence_1c_72_3_fv1c.npy', ' init cond2', array([ 5.0003027 , 8.47764173, 0.49062356, 8.47764173,
1.36562349, 8.47764173, 1.41562646, 8.47764173,
2.2531235 , 14.28 , 1.25 ]))
('sequence_1c_102_3_fv1c.npy', ' init cond2', array([ 5. , 0. , 0.490625, 0. , 1.365625,
0. , 1.415625, 0. , 2.253125, 1.428 , 14.28 ]))
('sequence_1c_102_3_fv1c.npy', ' init cond2', array([ 5.00030401, 8.54642076, 0.49062348, 8.60678527,
1.36562366, 7.31510695, 1.41562592, 7.55358696,
2.2531239 , 14.28 , 0.75 ]))
('sequence_1c_87_8_fv1c.npy', ' init cond2', array([ 5. , 0. , 0.490625, 0. , 1.365625,
0. , 1.415625, 0. , 2.253125, 1.428 , 14.28 ]))
('sequence_1c_87_8_fv1c.npy', ' init cond2', array([ 5.00037844, 8.17257611, 0.49062364, 9.38279546,
1.36562311, 8.27831249, 1.41562629, 8.66682671,
2.25312359, 14.28 , 1.75 ]))
('sequence_1d_174_15_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.725 , 0. , 1.475 , 0. ,
1.525 , 0. , 2.2375, 1.428 , 14.28 ]))
('sequence_1d_174_15_fv1c.npy', ' init cond2', array([ 27.00035794, 8.07822596, 0.72499875, 8.55045344,
1.47499858, 8.09459865, 1.52500124, 9.21674004,
2.23749821, 14.28 , 1.75 ]))
('sequence_2c_541_2_fv1c.npy', ' init cond2', array([ 5. , 0. , 0.490625, 0. , 1.365625,
0. , 1.415625, 0. , 2.253125, 1.028 , 14.28 ]))
('sequence_2c_541_2_fv1c.npy', ' init cond2', array([ 5.00027553, 8.55466232, 0.49062362, 8.18727425,
1.36562378, 8.13931467, 1.41562617, 9.22071059,
2.25312325, 14.28 , 0.75 ]))
('sequence_1d_252_3_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.725 , 0. , 1.475 , 0. ,
1.525 , 0. , 2.2375, 1.428 , 12.28 ]))
('sequence_1d_252_3_fv1c.npy', ' init cond2', array([ 27.00016246, 7.5116035 , 0.72499886, 7.48413767,
1.47499901, 7.68345303, 1.52500111, 7.09340836,
2.23749919, 12.28 , 1.428 ]))
('sequence_1d_144_15_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.725 , 0. , 1.475 , 0. ,
1.525 , 0. , 2.2375, 1.428 , 14.28 ]))
('sequence_1d_144_15_fv1c.npy', ' init cond2', array([ 27.00028798, 8.47764173, 0.72499861, 8.47764173,
1.47499866, 8.47764173, 1.52500148, 8.47764173,
2.23749856, 14.28 , 1.25 ]))
('sequence_1l_432_3_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1l_432_3_fv1c.npy', ' init cond2', array([ 27.00026984, 8.04730796, 0.41062375, 8.23496028,
1.3356237 , 8.7044467 , 1.51562656, 8.32695714,
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1.34562389, 8.31603472, 1.42562633, 8.76319015,
2.21562343, 14.28 , 1.25 ]))
('sequence_1k_340_1_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1k_340_1_fv1c.npy', ' init cond2', array([ 27.00028525, 8.47764173, 0.41062357, 8.47764173,
1.33562357, 8.47764173, 1.51562643, 8.47764173,
2.13062357, 14.28 , 1.428 ]))
('sequence_1k_293_4_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1k_293_4_fv1c.npy', ' init cond2', array([ 27.00031813, 9.06623216, 0.41062327, 8.71011761,
1.33562336, 8.89189117, 1.51562659, 8.67750168,
2.13062341, 14.28 , 1.25 ]))
('sequence_2c_500_1_fv1c.npy', ' init cond2', array([ 5. , 0. , 0.490625, 0. , 1.365625,
0. , 1.415625, 0. , 2.253125, 1.028 , 11.28 ]))
('sequence_2c_500_1_fv1c.npy', ' init cond2', array([ 5.00013555, 6.76258816, 0.49062432, 6.76258816,
1.36562433, 6.76258816, 1.41562563, 6.76258816,
2.25312435, 11.28 , 1. ]))
('sequence_3a_692_14_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.610625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_692_14_fv1c.npy', ' init cond2', array([ 27.00037432, 8.18221702, 0.61062627, 8.53362311,
1.33562354, 8.69298076, 1.51562655, 9.22672604,
2.13062313, 14.28 , 1.428 ]))
('sequence_1b_45_6_fv1c.npy', ' init cond2', array([ 5. , 0. , 0.490625, 0. , 1.365625,
0. , 1.415625, 0. , 2.253125, 1.428 , 14.28 ]))
('sequence_1b_45_6_fv1c.npy', ' init cond2', array([ 5.00029802, 8.28231902, 0.49062367, 8.24251638,
1.36562368, 8.618828 , 1.41562649, 8.94278251,
2.25312332, 14.28 , 0.75 ]))
('sequence_1d_270_21_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 12.28 ]))
('sequence_1d_270_21_fv1c.npy', ' init cond2', array([ 27.00009813, 7.06000277, 0.41062423, 7.29537267,
1.33562408, 6.5943801 , 1.51562561, 6.08898224,
2.13062451, 12.28 , 1.428 ]))
('sequence_1d_180_21_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1d_180_21_fv1c.npy', ' init cond2', array([ 27.00033882, 7.99417035, 0.41062382, 8.68243339,
1.33562351, 8.300326 , 1.5156263 , 8.88851951,
2.13062331, 14.28 , 1.75 ]))
('sequence_1k_292_3_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1k_292_3_fv1c.npy', ' init cond2', array([ 27.00038715, 7.59400419, 0.41062385, 8.613802 ,
1.33562348, 8.36365133, 1.51562641, 9.43469874,
2.13062306, 14.28 , 1.25 ]))
('sequence_1d_183_24_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1d_183_24_fv1c.npy', ' init cond2', array([ 27.00023918, 7.89983415, 0.41062392, 8.25418931,
1.33562378, 8.58220018, 1.51562648, 8.26122179,
2.1306238 , 14.28 , 1.75 ]))
('sequence_1c_93_4_fv1c.npy', ' init cond2', array([ 5. , 0. , 0.490625, 0. , 1.365625,
0. , 1.415625, 0. , 2.253125, 1.428 , 14.28 ]))
('sequence_1c_93_4_fv1c.npy', ' init cond2', array([ 5.0003336 , 8.27767676, 0.49062369, 8.06031403,
1.36562379, 8.87051346, 1.41562667, 8.35676908,
2.25312364, 14.28 , 0.75 ]))
('sequence_1d_201_12_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.725 , 0. , 1.475 , 0. ,
1.525 , 0. , 2.2375, 1.428 , 14.28 ]))
('sequence_1d_201_12_fv1c.npy', ' init cond2', array([ 27.00029046, 7.84483492, 0.72499872, 7.75774592,
1.474999 , 8.90592898, 1.52500158, 8.53286904,
2.23749855, 14.28 , 0.75 ]))
('sequence_2b_474_5_fv1c.npy', ' init cond2', array([ 19. , 0. , 0.420625, 0. , 1.345625,
0. , 1.425625, 0. , 2.215625, 1.428 , 14.28 ]))
('sequence_2b_474_5_fv1c.npy', ' init cond2', array([ 19.00029833, 8.63227471, 0.42062351, 8.3555509 ,
1.34562364, 8.71118712, 1.42562657, 8.07634839,
2.21562377, 14.28 , 0.75 ]))
('sequence_1b_33_4_fv1c.npy', ' init cond2', array([ 5. , 0. , 0.490625, 0. , 1.365625,
0. , 1.415625, 0. , 2.253125, 1.428 , 14.28 ]))
('sequence_1b_33_4_fv1c.npy', ' init cond2', array([ 5.0004453 , 9.73496955, 0.49062277, 8.5545846 ,
1.36562353, 9.1475108 , 1.4156268 , 9.06946915,
2.2531232 , 14.28 , 0.75 ]))
('sequence_1l_400_1_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1l_400_1_fv1c.npy', ' init cond2', array([ 27.0002237 , 8.96650686, 0.41062335, 7.77360904,
1.3356239 , 9.49535244, 1.51562702, 7.82613599,
2.13062388, 14.28 , 0.75 ]))
('sequence_3a_601_3_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.620625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_601_3_fv1c.npy', ' init cond2', array([ 27.00025704, 9.49727741, 0.62062694, 10.14323447,
1.33562262, 8.40819403, 1.51562642, 7.99730567,
2.13062371, 14.28 , 1.75 ]))
('sequence_1l_360_1_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1l_360_1_fv1c.npy', ' init cond2', array([ 27.00019597, 7.84963405, 0.4106239 , 8.514666 ,
1.33562357, 8.50888792, 1.51562649, 7.51746688,
2.13062402, 14.28 , 1. ]))
('sequence_1d_277_28_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 12.28 ]))
('sequence_1d_277_28_fv1c.npy', ' init cond2', array([ 27.00012546, 6.9732503 , 0.41062421, 7.4410051 ,
1.33562406, 7.32671634, 1.51562593, 6.52639838,
2.13062437, 12.28 , 1.428 ]))
('sequence_3a_578_19_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.610625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_578_19_fv1c.npy', ' init cond2', array([ 27.00028143, 8.48652511, 0.61062643, 8.07693507,
1.33562376, 8.78212168, 1.51562655, 8.47725691,
2.13062359, 14.28 , 1. ]))
('sequence_3a_706_8_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.620625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_706_8_fv1c.npy', ' init cond2', array([ 27.00028318, 8.47764173, 0.62062646, 8.47764173,
1.33562358, 8.47764173, 1.51562644, 8.47764173,
2.13062358, 14.28 , 0.5 ]))
('sequence_3a_625_7_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.620625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_625_7_fv1c.npy', ' init cond2', array([ 27.00030161, 9.71768008, 0.62062704, 8.3579001 ,
1.33562367, 8.30310792, 1.51562635, 8.75186119,
2.13062349, 14.28 , 0.75 ]))
('sequence_1k_353_4_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1k_353_4_fv1c.npy', ' init cond2', array([ 27.00032136, 9.30778049, 0.41062327, 8.62959377,
1.33562368, 7.80444359, 1.51562618, 8.49242733,
2.13062339, 14.28 , 0.5 ]))
('sequence_1d_153_24_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1d_153_24_fv1c.npy', ' init cond2', array([ 27.00029064, 7.83643887, 0.41062389, 8.56941732,
1.33562356, 7.86362669, 1.51562619, 8.68329908,
2.13062355, 14.28 , 1.25 ]))
('sequence_1k_311_2_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.410625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_1k_311_2_fv1c.npy', ' init cond2', array([ 27.00028525, 8.47764173, 0.41062357, 8.47764173,
1.33562357, 8.47764173, 1.51562643, 8.47764173,
2.13062357, 14.28 , 0.75 ]))
('sequence_3a_671_13_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.610625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 12.28 ]))
('sequence_3a_671_13_fv1c.npy', ' init cond2', array([ 27.000234 , 7.393341 , 0.61062594, 7.4692937 ,
1.33562402, 7.42665622, 1.51562596, 7.88074273,
2.13062383, 12.28 , 1.428 ]))
('sequence_1d_269_20_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.725 , 0. , 1.475 , 0. ,
1.525 , 0. , 2.2375, 1.428 , 12.28 ]))
('sequence_1d_269_20_fv1c.npy', ' init cond2', array([ 27.00015823, 7.14504726, 0.7249991 , 7.11592627,
1.47499911, 7.35209052, 1.5250008 , 7.06228009,
2.23749921, 12.28 , 1.428 ]))
('sequence_3a_632_14_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.610625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_632_14_fv1c.npy', ' init cond2', array([ 27.00026387, 8.23510426, 0.61062637, 8.48712076,
1.33562352, 8.78594652, 1.51562663, 8.51768572,
2.13062368, 14.28 , 0.75 ]))
('sequence_3a_694_16_fv1c.npy', ' init cond2', array([ 27. , 0. , 0.610625, 0. , 1.335625,
0. , 1.515625, 0. , 2.130625, 1.428 , 14.28 ]))
('sequence_3a_694_16_fv1c.npy', ' init cond2', array([ 27.00032673, 8.70121 , 0.61062656, 7.85717792,
1.33562388, 8.04548681, 1.51562619, 8.86903724,
2.13062337, 14.28 , 1.428 ]))
('there are ', 6, ' init conds in the training set')
('unique init conds:', [array([ 0.610625, 1.335625, 1.515625, 2.130625]), array([ 0.725 , 1.475 , 1.525 , 2.2375]), array([ 0.410625, 1.335625, 1.515625, 2.130625]), array([ 0.490625, 1.365625, 1.415625, 2.253125]), array([ 0.420625, 1.345625, 1.425625, 2.215625]), array([ 0.620625, 1.335625, 1.515625, 2.130625])])
In [3]:
unique_init_conds_test = []
test_seqname_initcond_dict = {}
for files in test_set_filenames:
data_load_path = test_path + '/data/' + files[0]
label_load_path = test_path + '/label/' + files[1]
# print("data/label load path: {} \n {}".format(data_load_path,label_load_path))
test_array = np.load(data_load_path)
test_label_array = np.load(label_load_path)[:, 1:]
if test_array.shape[1] == 12:
test_array = test_array[:,1:] #skip step_index.
if "fv1b" not in str(files[0]):
print(test_array[0,:])
#init_cond = train_array[0,[3,5,7,9]]
init_cond = test_array[0,[2,4,6,8]]
if "fv1b" in str(files[0]):
init_cond = test_array[0,[2,4,6,8]]
print(str(files[0])," init cond",init_cond)
test_seqname_initcond_dict[str(files[0])] = str(init_cond)
array_equality = False
if len(unique_init_conds_test) == 0:
unique_init_conds_test.append(init_cond)
if len(unique_init_conds_test) != 0:
for ic in unique_init_conds_test:
if np.array_equal(init_cond,ic) == True:
#print("equal array found in list?", np.array_equal(load_seq,load_sequence))
array_equality = True
if array_equality == False:
unique_init_conds_test.append(init_cond) #the load types
#print("first 6 rows:",train_array[0:2,:])
print("there are ",len(unique_init_conds_test)," init conds in the TESTING set.", unique_init_conds_test)
print("and ", len(unique_init_conds_test), "in the TRAINING set.",unique_init_conds)
#print("unique init conds:",unique_init_conds_test)
#any(item.shape != (24,) for item in flattened_eq_len_loadseq_list)
#print("any non overlapping init conds?", cmp(unique_init_conds,unique_init_conds_test))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_458_9_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 12.28 ]
('sequence_1l_419_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_479_10_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 12.28 ]
('sequence_1c_118_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_607_9_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 14.28 ]
('sequence_1d_228_9_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 27. 0. 0.610625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_569_10_fv1c.npy', ' init cond', array([ 0.610625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 12.28 ]
('sequence_1b_58_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.610625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_628_10_fv1c.npy', ' init cond', array([ 0.610625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 11.28 ]
('sequence_2c_508_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_388_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_368_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 12.28 ]
('sequence_2b_498_9_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_319_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 11.28 ]
('sequence_2c_509_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_98_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_428_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_489_10_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_8_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_398_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_688_10_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 13.28 ]
('sequence_2c_518_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_288_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 12.28 ]
('sequence_1k_338_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 12.28 ]
('sequence_1c_119_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 10.28 ]
('sequence_2c_538_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_478_9_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_18_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_378_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_79_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_298_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_409_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 12.28 ]
('sequence_2c_559_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_39_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_308_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_328_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_687_9_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_449_10_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 14.28 ]
('sequence_2c_549_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_588_10_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_369_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_379_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_48_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_108_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 14.28 ]
('sequence_1d_229_10_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_89_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_468_9_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 12.28 ]
('sequence_1b_59_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.610625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_587_9_fv1c.npy', ' init cond', array([ 0.610625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 14.28 ]
('sequence_1d_199_10_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_359_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_78_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_69_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 12.28 ]
('sequence_1l_418_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_348_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 12.28 ]
('sequence_3a_667_9_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_708_10_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1d_129_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 15.28 ]
('sequence_2c_528_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_349_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_429_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.610625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_608_10_fv1c.npy', ' init cond', array([ 0.610625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_568_9_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_438_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_289_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 12.28 ]
('sequence_2c_558_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_299_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_627_9_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_309_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_439_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_389_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_9_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_707_9_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 14.28 ]
('sequence_1d_198_9_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_647_9_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_19_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 14.28 ]
('sequence_1d_138_9_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_488_9_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_99_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 12.28 ]
('sequence_3a_668_10_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_358_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_408_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.620625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_3a_648_10_fv1c.npy', ' init cond', array([ 0.620625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 15.28 ]
('sequence_2c_529_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_49_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_469_10_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_318_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1d_128_9_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_448_9_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 13.28 ]
('sequence_2c_519_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 12.28 ]
('sequence_1k_339_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1k_329_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 14.28 ]
('sequence_1d_169_10_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 12.28 ]
('sequence_1d_258_9_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_68_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 14.28 ]
('sequence_2c_548_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_109_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_28_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 14.28 ]
('sequence_1d_139_10_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 12.28 ]
('sequence_2b_499_10_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 14.28 ]
('sequence_1d_168_9_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 27. 0. 0.410625 0. 1.335625 0. 1.515625
0. 2.130625 1.428 14.28 ]
('sequence_1l_399_10_fv1c.npy', ' init cond', array([ 0.410625, 1.335625, 1.515625, 2.130625]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_38_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.028 10.28 ]
('sequence_2c_539_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1b_29_10_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 5. 0. 0.490625 0. 1.365625 0. 1.415625
0. 2.253125 1.428 14.28 ]
('sequence_1c_88_9_fv1c.npy', ' init cond', array([ 0.490625, 1.365625, 1.415625, 2.253125]))
[ 27. 0. 0.725 0. 1.475 0. 1.525 0.
2.2375 1.428 12.28 ]
('sequence_1d_259_10_fv1c.npy', ' init cond', array([ 0.725 , 1.475 , 1.525 , 2.2375]))
[ 19. 0. 0.420625 0. 1.345625 0. 1.425625
0. 2.215625 1.428 14.28 ]
('sequence_2b_459_10_fv1c.npy', ' init cond', array([ 0.420625, 1.345625, 1.425625, 2.215625]))
('there are ', 6, ' init conds in the TESTING set.', [array([ 0.420625, 1.345625, 1.425625, 2.215625]), array([ 0.410625, 1.335625, 1.515625, 2.130625]), array([ 0.490625, 1.365625, 1.415625, 2.253125]), array([ 0.620625, 1.335625, 1.515625, 2.130625]), array([ 0.725 , 1.475 , 1.525 , 2.2375]), array([ 0.610625, 1.335625, 1.515625, 2.130625])])
('and ', 6, 'in the TRAINING set.', [array([ 0.610625, 1.335625, 1.515625, 2.130625]), array([ 0.725 , 1.475 , 1.525 , 2.2375]), array([ 0.410625, 1.335625, 1.515625, 2.130625]), array([ 0.490625, 1.365625, 1.415625, 2.253125]), array([ 0.420625, 1.345625, 1.425625, 2.215625]), array([ 0.620625, 1.335625, 1.515625, 2.130625])])
In [4]:
seqname_initcond_dict_initcondkey = {}
#combined_seqname_initcond_dict = {}
#do this twice. once for the training and once for the testing set
for key,value in training_seqname_initcond_dict.iteritems():
print("key",key,"value",value)
combined_seqname_initcond_dict[key[:-4]]=value
#load_sequence_aslist = str(unique_load_sequences_aslists[value])
#this arrangement below is necessary because dict has to have a list as its value.
if seqname_initcond_dict_initcondkey.get(value) != None:
seqname_initcond_dict_initcondkey[value].append(key)
if seqname_initcond_dict_initcondkey.get(value) == None:
content_list = []
content_list.append(key[:-4])
seqname_initcond_dict_initcondkey[value] = content_list
for key,value in test_seqname_initcond_dict.iteritems():
print("key",key,"value",value)
combined_seqname_initcond_dict[key[:-4]]=value
#load_sequence_aslist = str(unique_load_sequences_aslists[value])
#this arrangement below is necessary because dict has to have a list as its value.
if seqname_initcond_dict_initcondkey.get(value) != None:
seqname_initcond_dict_initcondkey[value].append(key)
if seqname_initcond_dict_initcondkey.get(value) == None:
content_list = []
content_list.append(key[:-4])
seqname_initcond_dict_initcondkey[value] = content_list
#print(filename_loadseq_dict_loadlistposkey)
sn_ic_ick_df = pd.DataFrame.from_dict(seqname_initcond_dict_initcondkey,orient='index')
sn_ic_ick_df.index.rename(name='init_cond',inplace=True)
sn_ic_snk_df = pd.DataFrame.from_dict(combined_seqname_initcond_dict,orient='index')
sn_ic_snk_df.index.rename(name='seq_name',inplace=True)
sn_ic_snk_df.columns=['init_cond']
sn_ic_ick_df.to_csv(analysis_path + "seqname_initcond_dict_initcondkey.csv") #the 3 init conds are index
sn_ic_snk_df.to_csv(analysis_path + "combined_seqname_initcond_dict.csv") #seq_name is index. to join later.
('key', 'sequence_3a_651_13_fv1c.npy', 'value', '[ 0.610625 1.335625 1.515625 2.130625]')
('key', 'sequence_1l_363_4_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_3a_664_6_fv1c.npy', 'value', '[ 0.620625 1.335625 1.515625 2.130625]')
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('key', 'sequence_1d_228_9_fv1c.npy', 'value', '[ 0.725 1.475 1.525 2.2375]')
('key', 'sequence_3a_688_10_fv1c.npy', 'value', '[ 0.620625 1.335625 1.515625 2.130625]')
('key', 'sequence_1c_108_9_fv1c.npy', 'value', '[ 0.490625 1.365625 1.415625 2.253125]')
('key', 'sequence_1l_399_10_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_1k_298_9_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_1d_258_9_fv1c.npy', 'value', '[ 0.725 1.475 1.525 2.2375]')
('key', 'sequence_1k_319_10_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_2b_478_9_fv1c.npy', 'value', '[ 0.420625 1.345625 1.425625 2.215625]')
('key', 'sequence_1k_339_10_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_1k_309_10_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_1c_119_10_fv1c.npy', 'value', '[ 0.490625 1.365625 1.415625 2.253125]')
('key', 'sequence_2c_558_9_fv1c.npy', 'value', '[ 0.490625 1.365625 1.415625 2.253125]')
('key', 'sequence_1l_418_9_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_1l_439_10_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_2b_459_10_fv1c.npy', 'value', '[ 0.420625 1.345625 1.425625 2.215625]')
('key', 'sequence_1c_98_9_fv1c.npy', 'value', '[ 0.490625 1.365625 1.415625 2.253125]')
('key', 'sequence_1d_168_9_fv1c.npy', 'value', '[ 0.725 1.475 1.525 2.2375]')
('key', 'sequence_1b_18_9_fv1c.npy', 'value', '[ 0.490625 1.365625 1.415625 2.253125]')
('key', 'sequence_1b_48_9_fv1c.npy', 'value', '[ 0.490625 1.365625 1.415625 2.253125]')
('key', 'sequence_2c_548_9_fv1c.npy', 'value', '[ 0.490625 1.365625 1.415625 2.253125]')
('key', 'sequence_1k_358_9_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_1l_379_10_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_1d_138_9_fv1c.npy', 'value', '[ 0.725 1.475 1.525 2.2375]')
('key', 'sequence_1k_348_9_fv1c.npy', 'value', '[ 0.410625 1.335625 1.515625 2.130625]')
('key', 'sequence_3a_647_9_fv1c.npy', 'value', '[ 0.620625 1.335625 1.515625 2.130625]')
('key', 'sequence_1d_198_9_fv1c.npy', 'value', '[ 0.725 1.475 1.525 2.2375]')
In [5]:
#right df is the one described in the cell above.
master_per_loadseq_df = pd.read_csv(analysis_path + 'master_score_per_loadseq.csv',index_col=0) #left. seq_name is the index.
results_seqname_initcond_df = pd.merge(master_per_loadseq_df,sn_ic_snk_df,how='inner',left_index=True,right_index=True)
print(results_seqname_initcond_df.head(2))
print(results_seqname_initcond_df.columns)
print(results_seqname_initcond_df.index)
mse_avg mse_med mse_stdev mae_avg mae_med \
seq_name
sequence_2c_539_10_fv1c 0.085384 0.011081 0.119663 0.136150 0.011572
sequence_2c_538_9_fv1c 0.085634 0.010419 0.119506 0.136272 0.011706
mae_stdev mae_normd_dev mape_avg mape_med \
seq_name
sequence_2c_539_10_fv1c 0.180962 NaN 125.078974 133.284079
sequence_2c_538_9_fv1c 0.180844 NaN 141.869085 151.855119
mape_stdev msle_avg msle_med msle_stdev \
seq_name
sequence_2c_539_10_fv1c 42.506095 0.048854 0.041356 0.016204
sequence_2c_538_9_fv1c 43.579381 0.048836 0.041387 0.016188
init_cond
seq_name
sequence_2c_539_10_fv1c [ 0.490625 1.365625 1.415625 2.253125]
sequence_2c_538_9_fv1c [ 0.490625 1.365625 1.415625 2.253125]
Index([u'mse_avg', u'mse_med', u'mse_stdev', u'mae_avg', u'mae_med',
u'mae_stdev', u'mae_normd_dev', u'mape_avg', u'mape_med', u'mape_stdev',
u'msle_avg', u'msle_med', u'msle_stdev', u'init_cond'],
dtype='object')
Index([u'sequence_2c_539_10_fv1c', u'sequence_2c_538_9_fv1c',
u'sequence_2b_469_10_fv1c', u'sequence_2b_449_10_fv1c',
u'sequence_1b_19_10_fv1c', u'sequence_2c_518_9_fv1c',
u'sequence_1c_78_9_fv1c', u'sequence_1b_18_9_fv1c',
u'sequence_2c_519_10_fv1c', u'sequence_1c_69_10_fv1c',
...
u'sequence_3a_648_10_fv1c', u'sequence_1c_119_10_fv1c',
u'sequence_1c_118_9_fv1c', u'sequence_1b_58_9_fv1c',
u'sequence_1b_59_10_fv1c', u'sequence_2c_558_9_fv1c',
u'sequence_2c_559_10_fv1c', u'sequence_2c_528_9_fv1c',
u'sequence_2c_529_10_fv1c', u'sequence_3a_569_10_fv1c'],
dtype='object', name=u'seq_name', length=108)
In [6]:
columns_to_cast = list(results_seqname_initcond_df.columns)
columns_to_cast.remove('init_cond')
print(columns_to_cast)
for colname in columns_to_cast: #for some reason it's all objects...gotta cast to numeric.
results_seqname_initcond_df[str(colname)] = pd.to_numeric(results_seqname_initcond_df[str(colname)],errors='coerce')
for colname in columns_to_cast:
print("new!", colname, results_seqname_initcond_df[colname].dtype)
grouped_sn_ic_df = results_seqname_initcond_df.groupby(by=['init_cond']).mean()
print(grouped_sn_ic_df.head(2))
#print(type(grouped_sn_ic_df))
pd.DataFrame(grouped_sn_ic_df).to_csv(analysis_path+'sn_ic_grouped_by_ic.csv')
['mse_avg', 'mse_med', 'mse_stdev', 'mae_avg', 'mae_med', 'mae_stdev', 'mae_normd_dev', 'mape_avg', 'mape_med', 'mape_stdev', 'msle_avg', 'msle_med', 'msle_stdev']
('new!', 'mse_avg', dtype('float64'))
('new!', 'mse_med', dtype('float64'))
('new!', 'mse_stdev', dtype('float64'))
('new!', 'mae_avg', dtype('float64'))
('new!', 'mae_med', dtype('float64'))
('new!', 'mae_stdev', dtype('float64'))
('new!', 'mae_normd_dev', dtype('float64'))
('new!', 'mape_avg', dtype('float64'))
('new!', 'mape_med', dtype('float64'))
('new!', 'mape_stdev', dtype('float64'))
('new!', 'msle_avg', dtype('float64'))
('new!', 'msle_med', dtype('float64'))
('new!', 'msle_stdev', dtype('float64'))
mse_avg mse_med mse_stdev \
init_cond
[ 0.410625 1.335625 1.515625 2.130625] 0.124295 0.019757 0.148329
[ 0.420625 1.345625 1.425625 2.215625] 0.135983 0.013930 0.173708
mae_avg mae_med mae_stdev \
init_cond
[ 0.410625 1.335625 1.515625 2.130625] 0.169974 0.012976 0.201070
[ 0.420625 1.345625 1.425625 2.215625] 0.176438 0.012398 0.218193
mae_normd_dev mape_avg \
init_cond
[ 0.410625 1.335625 1.515625 2.130625] NaN 306.219183
[ 0.420625 1.345625 1.425625 2.215625] NaN 279.765956
mape_med mape_stdev msle_avg \
init_cond
[ 0.410625 1.335625 1.515625 2.130625] 330.419275 94.701581 0.058580
[ 0.420625 1.345625 1.425625 2.215625] 302.747911 64.213537 0.066683
msle_med msle_stdev
init_cond
[ 0.410625 1.335625 1.515625 2.130625] 0.056357 0.011693
[ 0.420625 1.345625 1.425625 2.215625] 0.061444 0.015201
In [7]:
grouped_sn_ic_df2 = results_seqname_initcond_df.groupby(by=['init_cond']).count()
pd.DataFrame(grouped_sn_ic_df2).to_csv(analysis_path+'sn_ic_grouped_by_ic_count.csv')
In [ ]:
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Content source: samnashi/howdoflawsgetlonger
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