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/"
load_sequence_aggregation_path = analysis_path + "load_sequence_agg/"
results_aggregation_path = analysis_path + "results_to_aggregate/"

#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_2b_445_6_fv1c.npy', 'sequence_2b_445_6_label_fv1c.npy'), ('sequence_1b_12_3_fv1c.npy', 'sequence_1b_12_3_label_fv1c.npy'), ('sequence_1b_55_6_fv1c.npy', 'sequence_1b_55_6_label_fv1c.npy'), ('sequence_3a_689_11_fv1c.npy', 'sequence_3a_689_11_label_fv1c.npy'), ('sequence_1c_101_2_fv1c.npy', 'sequence_1c_101_2_label_fv1c.npy'), ('sequence_1k_297_8_fv1c.npy', 'sequence_1k_297_8_label_fv1c.npy'), ('sequence_1k_281_2_fv1c.npy', 'sequence_1k_281_2_label_fv1c.npy'), ('sequence_1l_363_4_fv1c.npy', 'sequence_1l_363_4_label_fv1c.npy'), ('sequence_1l_375_6_fv1c.npy', 'sequence_1l_375_6_label_fv1c.npy'), ('sequence_1d_218_29_fv1c.npy', 'sequence_1d_218_29_label_fv1c.npy'), ('sequence_1d_234_15_fv1c.npy', 'sequence_1d_234_15_label_fv1c.npy'), ('sequence_1d_162_3_fv1c.npy', 'sequence_1d_162_3_label_fv1c.npy'), ('sequence_1d_120_1_fv1c.npy', 'sequence_1d_120_1_label_fv1c.npy'), ('sequence_1d_194_5_fv1c.npy', 'sequence_1d_194_5_label_fv1c.npy'), ('sequence_1l_392_3_fv1c.npy', 'sequence_1l_392_3_label_fv1c.npy'), ('sequence_2b_442_3_fv1c.npy', 'sequence_2b_442_3_label_fv1c.npy'), ('sequence_3a_614_16_fv1c.npy', 'sequence_3a_614_16_label_fv1c.npy'), ('sequence_1d_180_21_fv1c.npy', 'sequence_1d_180_21_label_fv1c.npy'), ('sequence_1d_135_6_fv1c.npy', 'sequence_1d_135_6_label_fv1c.npy'), ('sequence_1d_268_19_fv1c.npy', 'sequence_1d_268_19_label_fv1c.npy'), ('sequence_1k_304_5_fv1c.npy', 'sequence_1k_304_5_label_fv1c.npy'), ('sequence_1b_30_1_fv1c.npy', 'sequence_1b_30_1_label_fv1c.npy'), ('sequence_1d_140_11_fv1c.npy', 'sequence_1d_140_11_label_fv1c.npy'), ('sequence_3a_591_13_fv1c.npy', 'sequence_3a_591_13_label_fv1c.npy'), ('sequence_1b_2_3_fv1c.npy', 'sequence_1b_2_3_label_fv1c.npy'), ('sequence_3a_594_16_fv1c.npy', 'sequence_3a_594_16_label_fv1c.npy'), ('sequence_2b_484_5_fv1c.npy', 'sequence_2b_484_5_label_fv1c.npy'), ('sequence_1b_32_3_fv1c.npy', 'sequence_1b_32_3_label_fv1c.npy'), ('sequence_1d_217_28_fv1c.npy', 'sequence_1d_217_28_label_fv1c.npy'), ('sequence_3a_700_2_fv1c.npy', 'sequence_3a_700_2_label_fv1c.npy'), ('sequence_1l_387_8_fv1c.npy', 'sequence_1l_387_8_label_fv1c.npy'), ('sequence_1k_291_2_fv1c.npy', 'sequence_1k_291_2_label_fv1c.npy'), ('sequence_3a_669_11_fv1c.npy', 'sequence_3a_669_11_label_fv1c.npy'), ('sequence_1k_312_3_fv1c.npy', 'sequence_1k_312_3_label_fv1c.npy'), ('sequence_1c_117_8_fv1c.npy', 'sequence_1c_117_8_label_fv1c.npy'), ('sequence_3a_701_3_fv1c.npy', 'sequence_3a_701_3_label_fv1c.npy'), ('sequence_1d_183_24_fv1c.npy', 'sequence_1d_183_24_label_fv1c.npy'), ('sequence_1k_326_7_fv1c.npy', 'sequence_1k_326_7_label_fv1c.npy'), ('sequence_1d_252_3_fv1c.npy', 'sequence_1d_252_3_label_fv1c.npy'), ('sequence_2c_530_1_fv1c.npy', 'sequence_2c_530_1_label_fv1c.npy'), ('sequence_1k_292_3_fv1c.npy', 'sequence_1k_292_3_label_fv1c.npy'), ('sequence_1k_355_6_fv1c.npy', 'sequence_1k_355_6_label_fv1c.npy'), ('sequence_2c_513_4_fv1c.npy', 'sequence_2c_513_4_label_fv1c.npy'), ('sequence_1d_156_27_fv1c.npy', 'sequence_1d_156_27_label_fv1c.npy'), ('sequence_1c_64_5_fv1c.npy', 'sequence_1c_64_5_label_fv1c.npy'), ('sequence_1b_56_7_fv1c.npy', 'sequence_1b_56_7_label_fv1c.npy'), ('sequence_3a_580_2_fv1c.npy', 'sequence_3a_580_2_label_fv1c.npy'), ('sequence_1b_3_4_fv1c.npy', 'sequence_1b_3_4_label_fv1c.npy'), ('sequence_2b_470_1_fv1c.npy', 'sequence_2b_470_1_label_fv1c.npy'), ('sequence_1k_356_7_fv1c.npy', 'sequence_1k_356_7_label_fv1c.npy'), ('sequence_1l_416_7_fv1c.npy', 'sequence_1l_416_7_label_fv1c.npy'), ('sequence_1l_365_6_fv1c.npy', 'sequence_1l_365_6_label_fv1c.npy'), ('sequence_1l_402_3_fv1c.npy', 'sequence_1l_402_3_label_fv1c.npy'), ('sequence_3a_624_6_fv1c.npy', 'sequence_3a_624_6_label_fv1c.npy'), ('sequence_1c_70_1_fv1c.npy', 'sequence_1c_70_1_label_fv1c.npy'), ('sequence_2b_490_1_fv1c.npy', 'sequence_2b_490_1_label_fv1c.npy'), ('sequence_1d_203_14_fv1c.npy', 'sequence_1d_203_14_label_fv1c.npy'), ('sequence_3a_599_1_fv1c.npy', 'sequence_3a_599_1_label_fv1c.npy'), ('sequence_1k_346_7_fv1c.npy', 'sequence_1k_346_7_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_3a_680_2_fv1c.npy', 'sequence_3a_680_2_label_fv1c.npy'), ('sequence_2c_527_8_fv1c.npy', 'sequence_2c_527_8_label_fv1c.npy'), ('sequence_1k_301_2_fv1c.npy', 'sequence_1k_301_2_label_fv1c.npy'), ('sequence_2b_497_8_fv1c.npy', 'sequence_2b_497_8_label_fv1c.npy'), ('sequence_3a_611_13_fv1c.npy', 'sequence_3a_611_13_label_fv1c.npy'), ('sequence_1c_85_6_fv1c.npy', 'sequence_1c_85_6_label_fv1c.npy'), ('sequence_3a_638_20_fv1c.npy', 'sequence_3a_638_20_label_fv1c.npy'), ('sequence_1l_436_7_fv1c.npy', 'sequence_1l_436_7_label_fv1c.npy'), ('sequence_3a_604_6_fv1c.npy', 'sequence_3a_604_6_label_fv1c.npy'), ('sequence_1d_264_15_fv1c.npy', 'sequence_1d_264_15_label_fv1c.npy'), ('sequence_1d_202_13_fv1c.npy', 'sequence_1d_202_13_label_fv1c.npy'), ('sequence_1d_134_5_fv1c.npy', 'sequence_1d_134_5_label_fv1c.npy'), ('sequence_1b_15_6_fv1c.npy', 'sequence_1b_15_6_label_fv1c.npy'), ('sequence_2c_531_2_fv1c.npy', 'sequence_2c_531_2_label_fv1c.npy'), ('sequence_2b_452_3_fv1c.npy', 'sequence_2b_452_3_label_fv1c.npy'), ('sequence_2c_500_1_fv1c.npy', 'sequence_2c_500_1_label_fv1c.npy'), ('sequence_1b_50_1_fv1c.npy', 'sequence_1b_50_1_label_fv1c.npy'), ('sequence_3a_683_5_fv1c.npy', 'sequence_3a_683_5_label_fv1c.npy'), ('sequence_1c_97_8_fv1c.npy', 'sequence_1c_97_8_label_fv1c.npy'), ('sequence_1c_62_3_fv1c.npy', 'sequence_1c_62_3_label_fv1c.npy'), ('sequence_2b_496_7_fv1c.npy', 'sequence_2b_496_7_label_fv1c.npy'), ('sequence_1k_305_6_fv1c.npy', 'sequence_1k_305_6_label_fv1c.npy'), ('sequence_1l_411_2_fv1c.npy', 'sequence_1l_411_2_label_fv1c.npy'), ('sequence_3a_664_6_fv1c.npy', 'sequence_3a_664_6_label_fv1c.npy'), ('sequence_3a_694_16_fv1c.npy', 'sequence_3a_694_16_label_fv1c.npy'), ('sequence_1d_278_29_fv1c.npy', 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('sequence_1l_400_1_fv1c.npy', 'sequence_1l_400_1_label_fv1c.npy'), ('sequence_1d_141_12_fv1c.npy', 'sequence_1d_141_12_label_fv1c.npy'), ('sequence_3a_582_4_fv1c.npy', 'sequence_3a_582_4_label_fv1c.npy'), ('sequence_1l_437_8_fv1c.npy', 'sequence_1l_437_8_label_fv1c.npy'), ('sequence_1d_142_13_fv1c.npy', 'sequence_1d_142_13_label_fv1c.npy'), ('sequence_3a_573_14_fv1c.npy', 'sequence_3a_573_14_label_fv1c.npy'), ('sequence_1d_250_1_fv1c.npy', 'sequence_1d_250_1_label_fv1c.npy'), ('sequence_3a_673_15_fv1c.npy', 'sequence_3a_673_15_label_fv1c.npy'), ('sequence_1d_196_7_fv1c.npy', 'sequence_1d_196_7_label_fv1c.npy'), ('sequence_1d_179_20_fv1c.npy', 'sequence_1d_179_20_label_fv1c.npy'), ('sequence_1k_331_2_fv1c.npy', 'sequence_1k_331_2_label_fv1c.npy'), ('sequence_2b_480_1_fv1c.npy', 'sequence_2b_480_1_label_fv1c.npy'), ('sequence_2c_541_2_fv1c.npy', 'sequence_2c_541_2_label_fv1c.npy'), ('sequence_1d_197_8_fv1c.npy', 'sequence_1d_197_8_label_fv1c.npy'), ('sequence_1l_386_7_fv1c.npy', 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'sequence_1c_95_6_label_fv1c.npy'), ('sequence_3a_566_7_fv1c.npy', 'sequence_3a_566_7_label_fv1c.npy'), ('sequence_3a_652_14_fv1c.npy', 'sequence_3a_652_14_label_fv1c.npy'), ('sequence_2c_556_7_fv1c.npy', 'sequence_2c_556_7_label_fv1c.npy'), ('sequence_1b_16_7_fv1c.npy', 'sequence_1b_16_7_label_fv1c.npy'), ('sequence_2c_534_5_fv1c.npy', 'sequence_2c_534_5_label_fv1c.npy'), ('sequence_1d_201_12_fv1c.npy', 'sequence_1d_201_12_label_fv1c.npy'), ('sequence_3a_659_1_fv1c.npy', 'sequence_3a_659_1_label_fv1c.npy'), ('sequence_1d_126_7_fv1c.npy', 'sequence_1d_126_7_label_fv1c.npy'), ('sequence_1d_243_24_fv1c.npy', 'sequence_1d_243_24_label_fv1c.npy'), ('sequence_3a_619_1_fv1c.npy', 'sequence_3a_619_1_label_fv1c.npy'), ('sequence_1k_293_4_fv1c.npy', 'sequence_1k_293_4_label_fv1c.npy'), ('sequence_1d_165_6_fv1c.npy', 'sequence_1d_165_6_label_fv1c.npy'), ('sequence_1d_232_13_fv1c.npy', 'sequence_1d_232_13_label_fv1c.npy'), ('sequence_3a_676_18_fv1c.npy', 'sequence_3a_676_18_label_fv1c.npy'), ('sequence_1c_87_8_fv1c.npy', 'sequence_1c_87_8_label_fv1c.npy'), ('sequence_1d_220_1_fv1c.npy', 'sequence_1d_220_1_label_fv1c.npy'), ('sequence_2c_552_3_fv1c.npy', 'sequence_2c_552_3_label_fv1c.npy'), ('sequence_2c_543_4_fv1c.npy', 'sequence_2c_543_4_label_fv1c.npy'), ('sequence_3a_597_19_fv1c.npy', 'sequence_3a_597_19_label_fv1c.npy'), ('sequence_1b_20_1_fv1c.npy', 'sequence_1b_20_1_label_fv1c.npy'), ('sequence_1l_366_7_fv1c.npy', 'sequence_1l_366_7_label_fv1c.npy'), ('sequence_1l_420_1_fv1c.npy', 'sequence_1l_420_1_label_fv1c.npy'), ('sequence_1k_344_5_fv1c.npy', 'sequence_1k_344_5_label_fv1c.npy'), ('sequence_1c_76_7_fv1c.npy', 'sequence_1c_76_7_label_fv1c.npy'), ('sequence_1c_104_5_fv1c.npy', 'sequence_1c_104_5_label_fv1c.npy'), ('sequence_1c_96_7_fv1c.npy', 'sequence_1c_96_7_label_fv1c.npy'), ('sequence_1d_248_29_fv1c.npy', 'sequence_1d_248_29_label_fv1c.npy'), ('sequence_1k_325_6_fv1c.npy', 'sequence_1k_325_6_label_fv1c.npy'), ('sequence_2c_511_2_fv1c.npy', 'sequence_2c_511_2_label_fv1c.npy'), ('sequence_2b_477_8_fv1c.npy', 'sequence_2b_477_8_label_fv1c.npy'), ('sequence_3a_585_7_fv1c.npy', 'sequence_3a_585_7_label_fv1c.npy')]
Training data read.
after shuffling: [('sequence_3a_608_10_fv1c.npy', 'sequence_3a_608_10_label_fv1c.npy'), ('sequence_1b_48_9_fv1c.npy', 'sequence_1b_48_9_label_fv1c.npy'), ('sequence_1b_29_10_fv1c.npy', 'sequence_1b_29_10_label_fv1c.npy'), ('sequence_3a_687_9_fv1c.npy', 'sequence_3a_687_9_label_fv1c.npy'), ('sequence_1k_309_10_fv1c.npy', 'sequence_1k_309_10_label_fv1c.npy'), ('sequence_1k_348_9_fv1c.npy', 'sequence_1k_348_9_label_fv1c.npy'), ('sequence_2c_518_9_fv1c.npy', 'sequence_2c_518_9_label_fv1c.npy'), ('sequence_1d_168_9_fv1c.npy', 'sequence_1d_168_9_label_fv1c.npy'), ('sequence_3a_667_9_fv1c.npy', 'sequence_3a_667_9_label_fv1c.npy'), ('sequence_1d_139_10_fv1c.npy', 'sequence_1d_139_10_label_fv1c.npy'), ('sequence_1b_19_10_fv1c.npy', 'sequence_1b_19_10_label_fv1c.npy'), ('sequence_2c_539_10_fv1c.npy', 'sequence_2c_539_10_label_fv1c.npy'), ('sequence_1b_49_10_fv1c.npy', 'sequence_1b_49_10_label_fv1c.npy'), ('sequence_2b_458_9_fv1c.npy', 'sequence_2b_458_9_label_fv1c.npy'), ('sequence_1b_59_10_fv1c.npy', 'sequence_1b_59_10_label_fv1c.npy'), ('sequence_1l_429_10_fv1c.npy', 'sequence_1l_429_10_label_fv1c.npy'), ('sequence_3a_569_10_fv1c.npy', 'sequence_3a_569_10_label_fv1c.npy'), ('sequence_1k_298_9_fv1c.npy', 'sequence_1k_298_9_label_fv1c.npy'), ('sequence_2b_449_10_fv1c.npy', 'sequence_2b_449_10_label_fv1c.npy'), ('sequence_3a_587_9_fv1c.npy', 'sequence_3a_587_9_label_fv1c.npy'), ('sequence_1k_318_9_fv1c.npy', 'sequence_1k_318_9_label_fv1c.npy'), ('sequence_1k_358_9_fv1c.npy', 'sequence_1k_358_9_label_fv1c.npy'), ('sequence_1l_439_10_fv1c.npy', 'sequence_1l_439_10_label_fv1c.npy'), ('sequence_3a_568_9_fv1c.npy', 'sequence_3a_568_9_label_fv1c.npy'), ('sequence_2c_508_9_fv1c.npy', 'sequence_2c_508_9_label_fv1c.npy'), ('sequence_1c_109_10_fv1c.npy', 'sequence_1c_109_10_label_fv1c.npy'), ('sequence_1c_119_10_fv1c.npy', 'sequence_1c_119_10_label_fv1c.npy'), ('sequence_1c_98_9_fv1c.npy', 'sequence_1c_98_9_label_fv1c.npy'), ('sequence_1l_389_10_fv1c.npy', 'sequence_1l_389_10_label_fv1c.npy'), ('sequence_1d_128_9_fv1c.npy', 'sequence_1d_128_9_label_fv1c.npy'), ('sequence_1k_349_10_fv1c.npy', 'sequence_1k_349_10_label_fv1c.npy'), ('sequence_1b_38_9_fv1c.npy', 'sequence_1b_38_9_label_fv1c.npy'), ('sequence_2c_528_9_fv1c.npy', 'sequence_2c_528_9_label_fv1c.npy'), ('sequence_1l_379_10_fv1c.npy', 'sequence_1l_379_10_label_fv1c.npy'), ('sequence_3a_688_10_fv1c.npy', 'sequence_3a_688_10_label_fv1c.npy'), ('sequence_1d_138_9_fv1c.npy', 'sequence_1d_138_9_label_fv1c.npy'), ('sequence_1k_308_9_fv1c.npy', 'sequence_1k_308_9_label_fv1c.npy'), ('sequence_3a_588_10_fv1c.npy', 'sequence_3a_588_10_label_fv1c.npy'), ('sequence_1l_398_9_fv1c.npy', 'sequence_1l_398_9_label_fv1c.npy'), ('sequence_1d_258_9_fv1c.npy', 'sequence_1d_258_9_label_fv1c.npy'), ('sequence_1l_408_9_fv1c.npy', 'sequence_1l_408_9_label_fv1c.npy'), ('sequence_3a_628_10_fv1c.npy', 'sequence_3a_628_10_label_fv1c.npy'), ('sequence_3a_627_9_fv1c.npy', 'sequence_3a_627_9_label_fv1c.npy'), ('sequence_2b_468_9_fv1c.npy', 'sequence_2b_468_9_label_fv1c.npy'), ('sequence_1d_229_10_fv1c.npy', 'sequence_1d_229_10_label_fv1c.npy'), ('sequence_1b_39_10_fv1c.npy', 'sequence_1b_39_10_label_fv1c.npy'), ('sequence_1b_28_9_fv1c.npy', 'sequence_1b_28_9_label_fv1c.npy'), ('sequence_1k_288_9_fv1c.npy', 'sequence_1k_288_9_label_fv1c.npy'), ('sequence_3a_707_9_fv1c.npy', 'sequence_3a_707_9_label_fv1c.npy'), ('sequence_3a_648_10_fv1c.npy', 'sequence_3a_648_10_label_fv1c.npy'), ('sequence_2b_448_9_fv1c.npy', 'sequence_2b_448_9_label_fv1c.npy'), ('sequence_1l_418_9_fv1c.npy', 'sequence_1l_418_9_label_fv1c.npy'), ('sequence_1b_8_9_fv1c.npy', 'sequence_1b_8_9_label_fv1c.npy'), ('sequence_1c_88_9_fv1c.npy', 'sequence_1c_88_9_label_fv1c.npy'), ('sequence_1k_299_10_fv1c.npy', 'sequence_1k_299_10_label_fv1c.npy'), ('sequence_1c_99_10_fv1c.npy', 'sequence_1c_99_10_label_fv1c.npy'), ('sequence_1b_58_9_fv1c.npy', 'sequence_1b_58_9_label_fv1c.npy'), ('sequence_1l_428_9_fv1c.npy', 'sequence_1l_428_9_label_fv1c.npy'), ('sequence_1l_399_10_fv1c.npy', 'sequence_1l_399_10_label_fv1c.npy'), ('sequence_2b_459_10_fv1c.npy', 'sequence_2b_459_10_label_fv1c.npy'), ('sequence_1b_18_9_fv1c.npy', 'sequence_1b_18_9_label_fv1c.npy'), ('sequence_1c_68_9_fv1c.npy', 'sequence_1c_68_9_label_fv1c.npy'), ('sequence_1c_69_10_fv1c.npy', 'sequence_1c_69_10_label_fv1c.npy'), ('sequence_2b_478_9_fv1c.npy', 'sequence_2b_478_9_label_fv1c.npy'), ('sequence_1c_108_9_fv1c.npy', 'sequence_1c_108_9_label_fv1c.npy'), ('sequence_2b_469_10_fv1c.npy', 'sequence_2b_469_10_label_fv1c.npy'), ('sequence_1l_378_9_fv1c.npy', 'sequence_1l_378_9_label_fv1c.npy'), ('sequence_1d_129_10_fv1c.npy', 'sequence_1d_129_10_label_fv1c.npy'), ('sequence_2c_559_10_fv1c.npy', 'sequence_2c_559_10_label_fv1c.npy'), ('sequence_1k_289_10_fv1c.npy', 'sequence_1k_289_10_label_fv1c.npy'), ('sequence_1l_368_9_fv1c.npy', 'sequence_1l_368_9_label_fv1c.npy'), ('sequence_1d_199_10_fv1c.npy', 'sequence_1d_199_10_label_fv1c.npy'), ('sequence_1d_169_10_fv1c.npy', 'sequence_1d_169_10_label_fv1c.npy'), ('sequence_3a_708_10_fv1c.npy', 'sequence_3a_708_10_label_fv1c.npy'), ('sequence_1l_388_9_fv1c.npy', 'sequence_1l_388_9_label_fv1c.npy'), ('sequence_3a_607_9_fv1c.npy', 'sequence_3a_607_9_label_fv1c.npy'), ('sequence_1b_9_10_fv1c.npy', 'sequence_1b_9_10_label_fv1c.npy'), ('sequence_1k_328_9_fv1c.npy', 'sequence_1k_328_9_label_fv1c.npy'), ('sequence_1k_339_10_fv1c.npy', 'sequence_1k_339_10_label_fv1c.npy'), ('sequence_2b_488_9_fv1c.npy', 'sequence_2b_488_9_label_fv1c.npy'), ('sequence_1l_419_10_fv1c.npy', 'sequence_1l_419_10_label_fv1c.npy'), ('sequence_3a_647_9_fv1c.npy', 'sequence_3a_647_9_label_fv1c.npy'), ('sequence_1d_198_9_fv1c.npy', 'sequence_1d_198_9_label_fv1c.npy'), ('sequence_1l_369_10_fv1c.npy', 'sequence_1l_369_10_label_fv1c.npy'), ('sequence_1k_338_9_fv1c.npy', 'sequence_1k_338_9_label_fv1c.npy'), ('sequence_2b_479_10_fv1c.npy', 'sequence_2b_479_10_label_fv1c.npy'), ('sequence_1d_259_10_fv1c.npy', 'sequence_1d_259_10_label_fv1c.npy'), ('sequence_1d_228_9_fv1c.npy', 'sequence_1d_228_9_label_fv1c.npy'), ('sequence_2c_549_10_fv1c.npy', 'sequence_2c_549_10_label_fv1c.npy'), ('sequence_2b_499_10_fv1c.npy', 'sequence_2b_499_10_label_fv1c.npy'), ('sequence_2c_548_9_fv1c.npy', 'sequence_2c_548_9_label_fv1c.npy'), ('sequence_1c_118_9_fv1c.npy', 'sequence_1c_118_9_label_fv1c.npy'), ('sequence_2c_558_9_fv1c.npy', 'sequence_2c_558_9_label_fv1c.npy'), ('sequence_1k_329_10_fv1c.npy', 'sequence_1k_329_10_label_fv1c.npy'), ('sequence_2b_489_10_fv1c.npy', 'sequence_2b_489_10_label_fv1c.npy'), ('sequence_2c_519_10_fv1c.npy', 'sequence_2c_519_10_label_fv1c.npy'), ('sequence_2b_498_9_fv1c.npy', 'sequence_2b_498_9_label_fv1c.npy'), ('sequence_3a_668_10_fv1c.npy', 'sequence_3a_668_10_label_fv1c.npy'), ('sequence_1k_359_10_fv1c.npy', 'sequence_1k_359_10_label_fv1c.npy'), ('sequence_2c_538_9_fv1c.npy', 'sequence_2c_538_9_label_fv1c.npy'), ('sequence_1c_89_10_fv1c.npy', 'sequence_1c_89_10_label_fv1c.npy'), ('sequence_2c_529_10_fv1c.npy', 'sequence_2c_529_10_label_fv1c.npy'), ('sequence_2c_509_10_fv1c.npy', 'sequence_2c_509_10_label_fv1c.npy'), ('sequence_1l_438_9_fv1c.npy', 'sequence_1l_438_9_label_fv1c.npy'), ('sequence_1c_79_10_fv1c.npy', 'sequence_1c_79_10_label_fv1c.npy'), ('sequence_1l_409_10_fv1c.npy', 'sequence_1l_409_10_label_fv1c.npy'), ('sequence_1k_319_10_fv1c.npy', 'sequence_1k_319_10_label_fv1c.npy'), ('sequence_1c_78_9_fv1c.npy', 'sequence_1c_78_9_label_fv1c.npy')]
Test set read.
[('sequence_2b_445_6_fv1c.npy', 'sequence_2b_445_6_label_fv1c.npy'), ('sequence_1b_12_3_fv1c.npy', 'sequence_1b_12_3_label_fv1c.npy'), ('sequence_1b_55_6_fv1c.npy', 'sequence_1b_55_6_label_fv1c.npy'), ('sequence_3a_689_11_fv1c.npy', 'sequence_3a_689_11_label_fv1c.npy'), ('sequence_1c_101_2_fv1c.npy', 'sequence_1c_101_2_label_fv1c.npy'), ('sequence_1k_297_8_fv1c.npy', 'sequence_1k_297_8_label_fv1c.npy'), ('sequence_1k_281_2_fv1c.npy', 'sequence_1k_281_2_label_fv1c.npy'), ('sequence_1l_363_4_fv1c.npy', 'sequence_1l_363_4_label_fv1c.npy'), ('sequence_1l_375_6_fv1c.npy', 'sequence_1l_375_6_label_fv1c.npy'), ('sequence_1d_218_29_fv1c.npy', 'sequence_1d_218_29_label_fv1c.npy'), ('sequence_1d_234_15_fv1c.npy', 'sequence_1d_234_15_label_fv1c.npy'), ('sequence_1d_162_3_fv1c.npy', 'sequence_1d_162_3_label_fv1c.npy'), ('sequence_1d_120_1_fv1c.npy', 'sequence_1d_120_1_label_fv1c.npy'), ('sequence_1d_194_5_fv1c.npy', 'sequence_1d_194_5_label_fv1c.npy'), ('sequence_1l_392_3_fv1c.npy', 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[('sequence_3a_608_10_fv1c.npy', 'sequence_3a_608_10_label_fv1c.npy'), ('sequence_1b_48_9_fv1c.npy', 'sequence_1b_48_9_label_fv1c.npy'), ('sequence_1b_29_10_fv1c.npy', 'sequence_1b_29_10_label_fv1c.npy'), ('sequence_3a_687_9_fv1c.npy', 'sequence_3a_687_9_label_fv1c.npy'), ('sequence_1k_309_10_fv1c.npy', 'sequence_1k_309_10_label_fv1c.npy'), ('sequence_1k_348_9_fv1c.npy', 'sequence_1k_348_9_label_fv1c.npy'), ('sequence_2c_518_9_fv1c.npy', 'sequence_2c_518_9_label_fv1c.npy'), ('sequence_1d_168_9_fv1c.npy', 'sequence_1d_168_9_label_fv1c.npy'), ('sequence_3a_667_9_fv1c.npy', 'sequence_3a_667_9_label_fv1c.npy'), ('sequence_1d_139_10_fv1c.npy', 'sequence_1d_139_10_label_fv1c.npy'), ('sequence_1b_19_10_fv1c.npy', 'sequence_1b_19_10_label_fv1c.npy'), ('sequence_2c_539_10_fv1c.npy', 'sequence_2c_539_10_label_fv1c.npy'), ('sequence_1b_49_10_fv1c.npy', 'sequence_1b_49_10_label_fv1c.npy'), ('sequence_2b_458_9_fv1c.npy', 'sequence_2b_458_9_label_fv1c.npy'), ('sequence_1b_59_10_fv1c.npy', 'sequence_1b_59_10_label_fv1c.npy'), ('sequence_1l_429_10_fv1c.npy', 'sequence_1l_429_10_label_fv1c.npy'), ('sequence_3a_569_10_fv1c.npy', 'sequence_3a_569_10_label_fv1c.npy'), ('sequence_1k_298_9_fv1c.npy', 'sequence_1k_298_9_label_fv1c.npy'), ('sequence_2b_449_10_fv1c.npy', 'sequence_2b_449_10_label_fv1c.npy'), ('sequence_3a_587_9_fv1c.npy', 'sequence_3a_587_9_label_fv1c.npy'), ('sequence_1k_318_9_fv1c.npy', 'sequence_1k_318_9_label_fv1c.npy'), ('sequence_1k_358_9_fv1c.npy', 'sequence_1k_358_9_label_fv1c.npy'), ('sequence_1l_439_10_fv1c.npy', 'sequence_1l_439_10_label_fv1c.npy'), ('sequence_3a_568_9_fv1c.npy', 'sequence_3a_568_9_label_fv1c.npy'), ('sequence_2c_508_9_fv1c.npy', 'sequence_2c_508_9_label_fv1c.npy'), ('sequence_1c_109_10_fv1c.npy', 'sequence_1c_109_10_label_fv1c.npy'), ('sequence_1c_119_10_fv1c.npy', 'sequence_1c_119_10_label_fv1c.npy'), ('sequence_1c_98_9_fv1c.npy', 'sequence_1c_98_9_label_fv1c.npy'), ('sequence_1l_389_10_fv1c.npy', 'sequence_1l_389_10_label_fv1c.npy'), ('sequence_1d_128_9_fv1c.npy', 'sequence_1d_128_9_label_fv1c.npy'), ('sequence_1k_349_10_fv1c.npy', 'sequence_1k_349_10_label_fv1c.npy'), ('sequence_1b_38_9_fv1c.npy', 'sequence_1b_38_9_label_fv1c.npy'), ('sequence_2c_528_9_fv1c.npy', 'sequence_2c_528_9_label_fv1c.npy'), ('sequence_1l_379_10_fv1c.npy', 'sequence_1l_379_10_label_fv1c.npy'), ('sequence_3a_688_10_fv1c.npy', 'sequence_3a_688_10_label_fv1c.npy'), ('sequence_1d_138_9_fv1c.npy', 'sequence_1d_138_9_label_fv1c.npy'), ('sequence_1k_308_9_fv1c.npy', 'sequence_1k_308_9_label_fv1c.npy'), ('sequence_3a_588_10_fv1c.npy', 'sequence_3a_588_10_label_fv1c.npy'), ('sequence_1l_398_9_fv1c.npy', 'sequence_1l_398_9_label_fv1c.npy'), ('sequence_1d_258_9_fv1c.npy', 'sequence_1d_258_9_label_fv1c.npy'), ('sequence_1l_408_9_fv1c.npy', 'sequence_1l_408_9_label_fv1c.npy'), ('sequence_3a_628_10_fv1c.npy', 'sequence_3a_628_10_label_fv1c.npy'), ('sequence_3a_627_9_fv1c.npy', 'sequence_3a_627_9_label_fv1c.npy'), ('sequence_2b_468_9_fv1c.npy', 'sequence_2b_468_9_label_fv1c.npy'), ('sequence_1d_229_10_fv1c.npy', 'sequence_1d_229_10_label_fv1c.npy'), ('sequence_1b_39_10_fv1c.npy', 'sequence_1b_39_10_label_fv1c.npy'), ('sequence_1b_28_9_fv1c.npy', 'sequence_1b_28_9_label_fv1c.npy'), ('sequence_1k_288_9_fv1c.npy', 'sequence_1k_288_9_label_fv1c.npy'), ('sequence_3a_707_9_fv1c.npy', 'sequence_3a_707_9_label_fv1c.npy'), ('sequence_3a_648_10_fv1c.npy', 'sequence_3a_648_10_label_fv1c.npy'), ('sequence_2b_448_9_fv1c.npy', 'sequence_2b_448_9_label_fv1c.npy'), ('sequence_1l_418_9_fv1c.npy', 'sequence_1l_418_9_label_fv1c.npy'), ('sequence_1b_8_9_fv1c.npy', 'sequence_1b_8_9_label_fv1c.npy'), ('sequence_1c_88_9_fv1c.npy', 'sequence_1c_88_9_label_fv1c.npy'), ('sequence_1k_299_10_fv1c.npy', 'sequence_1k_299_10_label_fv1c.npy'), ('sequence_1c_99_10_fv1c.npy', 'sequence_1c_99_10_label_fv1c.npy'), ('sequence_1b_58_9_fv1c.npy', 'sequence_1b_58_9_label_fv1c.npy'), ('sequence_1l_428_9_fv1c.npy', 'sequence_1l_428_9_label_fv1c.npy'), ('sequence_1l_399_10_fv1c.npy', 'sequence_1l_399_10_label_fv1c.npy'), ('sequence_2b_459_10_fv1c.npy', 'sequence_2b_459_10_label_fv1c.npy'), ('sequence_1b_18_9_fv1c.npy', 'sequence_1b_18_9_label_fv1c.npy'), ('sequence_1c_68_9_fv1c.npy', 'sequence_1c_68_9_label_fv1c.npy'), ('sequence_1c_69_10_fv1c.npy', 'sequence_1c_69_10_label_fv1c.npy'), ('sequence_2b_478_9_fv1c.npy', 'sequence_2b_478_9_label_fv1c.npy'), ('sequence_1c_108_9_fv1c.npy', 'sequence_1c_108_9_label_fv1c.npy'), ('sequence_2b_469_10_fv1c.npy', 'sequence_2b_469_10_label_fv1c.npy'), ('sequence_1l_378_9_fv1c.npy', 'sequence_1l_378_9_label_fv1c.npy'), ('sequence_1d_129_10_fv1c.npy', 'sequence_1d_129_10_label_fv1c.npy'), ('sequence_2c_559_10_fv1c.npy', 'sequence_2c_559_10_label_fv1c.npy'), ('sequence_1k_289_10_fv1c.npy', 'sequence_1k_289_10_label_fv1c.npy'), ('sequence_1l_368_9_fv1c.npy', 'sequence_1l_368_9_label_fv1c.npy'), ('sequence_1d_199_10_fv1c.npy', 'sequence_1d_199_10_label_fv1c.npy'), ('sequence_1d_169_10_fv1c.npy', 'sequence_1d_169_10_label_fv1c.npy'), ('sequence_3a_708_10_fv1c.npy', 'sequence_3a_708_10_label_fv1c.npy'), ('sequence_1l_388_9_fv1c.npy', 'sequence_1l_388_9_label_fv1c.npy'), ('sequence_3a_607_9_fv1c.npy', 'sequence_3a_607_9_label_fv1c.npy'), ('sequence_1b_9_10_fv1c.npy', 'sequence_1b_9_10_label_fv1c.npy'), ('sequence_1k_328_9_fv1c.npy', 'sequence_1k_328_9_label_fv1c.npy'), ('sequence_1k_339_10_fv1c.npy', 'sequence_1k_339_10_label_fv1c.npy'), ('sequence_2b_488_9_fv1c.npy', 'sequence_2b_488_9_label_fv1c.npy'), ('sequence_1l_419_10_fv1c.npy', 'sequence_1l_419_10_label_fv1c.npy'), ('sequence_3a_647_9_fv1c.npy', 'sequence_3a_647_9_label_fv1c.npy'), ('sequence_1d_198_9_fv1c.npy', 'sequence_1d_198_9_label_fv1c.npy'), ('sequence_1l_369_10_fv1c.npy', 'sequence_1l_369_10_label_fv1c.npy'), ('sequence_1k_338_9_fv1c.npy', 'sequence_1k_338_9_label_fv1c.npy'), ('sequence_2b_479_10_fv1c.npy', 'sequence_2b_479_10_label_fv1c.npy'), ('sequence_1d_259_10_fv1c.npy', 'sequence_1d_259_10_label_fv1c.npy'), ('sequence_1d_228_9_fv1c.npy', 'sequence_1d_228_9_label_fv1c.npy'), ('sequence_2c_549_10_fv1c.npy', 'sequence_2c_549_10_label_fv1c.npy'), ('sequence_2b_499_10_fv1c.npy', 'sequence_2b_499_10_label_fv1c.npy'), ('sequence_2c_548_9_fv1c.npy', 'sequence_2c_548_9_label_fv1c.npy'), ('sequence_1c_118_9_fv1c.npy', 'sequence_1c_118_9_label_fv1c.npy'), ('sequence_2c_558_9_fv1c.npy', 'sequence_2c_558_9_label_fv1c.npy'), ('sequence_1k_329_10_fv1c.npy', 'sequence_1k_329_10_label_fv1c.npy'), ('sequence_2b_489_10_fv1c.npy', 'sequence_2b_489_10_label_fv1c.npy'), ('sequence_2c_519_10_fv1c.npy', 'sequence_2c_519_10_label_fv1c.npy'), ('sequence_2b_498_9_fv1c.npy', 'sequence_2b_498_9_label_fv1c.npy'), ('sequence_3a_668_10_fv1c.npy', 'sequence_3a_668_10_label_fv1c.npy'), ('sequence_1k_359_10_fv1c.npy', 'sequence_1k_359_10_label_fv1c.npy'), ('sequence_2c_538_9_fv1c.npy', 'sequence_2c_538_9_label_fv1c.npy'), ('sequence_1c_89_10_fv1c.npy', 'sequence_1c_89_10_label_fv1c.npy'), ('sequence_2c_529_10_fv1c.npy', 'sequence_2c_529_10_label_fv1c.npy'), ('sequence_2c_509_10_fv1c.npy', 'sequence_2c_509_10_label_fv1c.npy'), ('sequence_1l_438_9_fv1c.npy', 'sequence_1l_438_9_label_fv1c.npy'), ('sequence_1c_79_10_fv1c.npy', 'sequence_1c_79_10_label_fv1c.npy'), ('sequence_1l_409_10_fv1c.npy', 'sequence_1l_409_10_label_fv1c.npy'), ('sequence_1k_319_10_fv1c.npy', 'sequence_1k_319_10_label_fv1c.npy'), ('sequence_1c_78_9_fv1c.npy', 'sequence_1c_78_9_label_fv1c.npy')]

In [2]:

    

results_files_list = list(os.listdir(results_aggregation_path))
results_files_list.sort()
metrics_list = ['mae','mape','mse']
i=0
for files in test_set_filenames:
    #print("filename", files)
    i += 1
    temp_results_dict={}
    temp_results_df = pd.DataFrame(columns=metrics_list)
    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:]
    
    #nested for but whatever
    for results_file in results_files_list:
        print("analyzing ", str(files[0][:-4]), "with model ", str(results_file))
        complete_filename = results_aggregation_path + results_file
        interm_results_df = pd.read_csv(complete_filename,index_col='seq_name')
        #print(interm_results_df.index)
        print("does it have .npy in the results?", interm_results_df.index.contains("sequence_1c_89_10_fv1c.npy"))
        
        suffix_check = interm_results_df.index.contains("sequence_1c_89_10_fv1c.npy")
        if suffix_check == True:
            seqname = str(files[0])
        if suffix_check == False:
            seqname = str(files[0])[:-4]
            
        temp_results_dict[str(results_file)]=interm_results_df.loc[seqname,:]
            
        for metric in list(interm_results_df.columns): #.remove('filename'): #make it adaptive to whatever results 
            if metric in temp_results_df.columns:
                temp_results_df.loc[:,[metric]] = interm_results_df.loc[seqname,[metric]]
        
    temp_results_df = pd.DataFrame.from_dict(temp_results_dict,orient='index')
    temp_results_df.sort_values(by=['mae'],inplace=True)
    temp_results_df.to_csv(load_sequence_aggregation_path + str(files[0][:-4]) + ".csv")


    

    




('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_elasticnet__bag_convdblfilters_lstm_nodense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_elasticnet_model__tiny_bidir_20sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_et30_ws___bag_convdblfilters_lstm_nodense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_et5_ws__model__tiny_bidir_20sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_fv1c_elasticnet_50sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_fv1clinreg_50sd.csv')
('does it have .npy in the results?', True)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_fv1crf60_ws__.csv')
('does it have .npy in the results?', True)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_fv1cridgecholesky_50sd.csv')
('does it have .npy in the results?', True)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_fv1cridgesaga_50sd.csv')
('does it have .npy in the results?', True)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_linreg_model__tiny_bidir_1sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_rf30_ws__model__tiny_bidir_.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_rf5_ws___bag_convdblfilters_lstm_nodense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'combi_scores_ridgesaga_model__tiny_bidir_20sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'scores_conv__tree_medbidir_nodense_fv1c_slowlr_relu_ca_sigmoid_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'scores_conv__tree_tinybidir_nodense_fv1c_slowlr_relu_ca_sigmoid_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'scores_conv_lstm_bagged__bag_conv_lstm_dense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'scores_lstm_rerun__bidir100ea_fv1c_.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'scores_lstm_rerun__big_bidir_.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'scores_lstm_rerun__tiny_bidir_.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'scores_sk_conv_lstm_bagged__bag_conv_lstm_dense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_3a_608_10_fv1c', 'with model ', 'scores_sk_conv_lstm_bagged__bag_conv_lstm_nodense_micro_128d_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_elasticnet__bag_convdblfilters_lstm_nodense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_elasticnet_model__tiny_bidir_20sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_et30_ws___bag_convdblfilters_lstm_nodense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_et5_ws__model__tiny_bidir_20sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_fv1c_elasticnet_50sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_fv1clinreg_50sd.csv')
('does it have .npy in the results?', True)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_fv1crf60_ws__.csv')
('does it have .npy in the results?', True)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_fv1cridgecholesky_50sd.csv')
('does it have .npy in the results?', True)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_fv1cridgesaga_50sd.csv')
('does it have .npy in the results?', True)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_linreg_model__tiny_bidir_1sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_rf30_ws__model__tiny_bidir_.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_rf5_ws___bag_convdblfilters_lstm_nodense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'combi_scores_ridgesaga_model__tiny_bidir_20sd.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'scores_conv__tree_medbidir_nodense_fv1c_slowlr_relu_ca_sigmoid_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'scores_conv__tree_tinybidir_nodense_fv1c_slowlr_relu_ca_sigmoid_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'scores_conv_lstm_bagged__bag_conv_lstm_dense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'scores_lstm_rerun__bidir100ea_fv1c_.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'scores_lstm_rerun__big_bidir_.csv')
('does it have .npy in the results?', False)
('analyzing ', 'sequence_1b_48_9_fv1c', 'with model ', 'scores_lstm_rerun__tiny_bidir_.csv')
('does it have .npy in the results?', False)
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('does it have .npy in the results?', False)
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('does it have .npy in the results?', False)
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('does it have .npy in the results?', False)
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('does it have .npy in the results?', False)
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('does it have .npy in the results?', False)
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('does it have .npy in the results?', True)
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('does it have .npy in the results?', True)
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('analyzing ', 'sequence_1k_319_10_fv1c', 'with model ', 'combi_scores_linreg_model__tiny_bidir_1sd.csv')
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('does it have .npy in the results?', False)

In [3]:

    

#load the master_results file
master_results_df = pd.read_csv(analysis_path+"master_results_per_model.csv",index_col=0) #this file is probably created manually...
#declare a list of valid models, cutoff criteria mae < 1
model_ok_list = []
#if it meets the threshold, add to the list
for item in master_results_df.index:
    if master_results_df.loc[item,'mae_avg'] <= 0.50:
        model_ok_list.append(str(item))
#add an if statement to the


    

In [4]:

    

print("model ok list: ",model_ok_list, "length", len(model_ok_list))


    

    




('model ok list: ', ['combi_scores_elasticnet__bag_convdblfilters_lstm_nodense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv', 'combi_scores_elasticnet_model__tiny_bidir_20sd.csv', 'combi_scores_rf30_ws__model__tiny_bidir_.csv', 'combi_scores_ridgesaga_model__tiny_bidir_20sd.csv', 'combi_scores_et5_ws__model__tiny_bidir_20sd.csv', 'combi_scores_linreg_model__tiny_bidir_1sd.csv', 'combi_scores_rf5_ws___bag_convdblfilters_lstm_nodense_tiny_shufstart_relu_ca_tanh_da_3_cbd_standard_per_batch_sclr_l1l2_kr_HLR.csv', 'combi_scores_fv1crf60_ws__.csv', 'combi_scores_fv1cridgesaga_50sd.csv', 'scores_lstm_rerun__tiny_bidir_.csv', 'scores_lstm_rerun__big_bidir_.csv', 'scores_lstm_rerun__bidir100ea_fv1c_.csv', 'combi_scores_fv1clinreg_50sd.csv'], 'length', 13)

In [5]:

    

main_colnames = ['seq_name','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']
# mse_main_df = pd.DataFrame(columns=mse_main_colnames)
# mse_main_df.set_index(keys=['results_filename'], inplace=True)


sequence_results_per_model_list = list(os.listdir(load_sequence_aggregation_path))
#still need subset per model category... 
master_per_loadseq_df = pd.DataFrame(columns=main_colnames)
master_per_loadseq_df.set_index(keys=['seq_name'], inplace=True)

interm_per_loadseq_result_modeloksubset = pd.DataFrame(index=['model_name'])
#@@@@@@@@@@@@@@@@@@@@@@@@@@@
metrics_to_aggregate = ['mae','mse','mape','msle']
#@@@@@@@@@@@@@@@@@@@@@@@@@@@
for seq_results in sequence_results_per_model_list:
    interm_per_loadseq_result_df = pd.read_csv(load_sequence_aggregation_path + str(seq_results),index_col=0)
    interm_per_loadseq_result_modeloksubset = pd.DataFrame(index=['model_name']) 
    #set the index to be called model_name
    interm_per_loadseq_result_df.index.rename(name = 'model_name',inplace=True)
    
    #print('interm_per_loadseq_result_df columns',interm_per_loadseq_result_df.columns)
    
    #master_per_loadseq_df[str(seq_results)]
    for metric in metrics_to_aggregate:
        key_avg_colname = str(metric) + "_" + "avg"
        key_med_colname = str(metric) + "_" + "med"
        key_std_colname = str(metric) + "_" + "stdev"
        #print(interm_per_loadseq_result_df.index.isin([model_ok_list]))
        #print(interm_per_loadseq_result_df.loc[model_ok_list,'mae'])
        #for model in model_ok_list:
            #rint("model: ",model, "seq_results: ",seq_results) #needs two aggregations.. #subset models,THEN go.
        print("the mean", interm_per_loadseq_result_df.loc[model_ok_list,[str(metric)]].mean(skipna=True).values)
        print("the type of mean", type(interm_per_loadseq_result_df.loc[model_ok_list,[str(metric)]].mean(skipna=True)))
        print("the shape of mean", (interm_per_loadseq_result_df.loc[model_ok_list,[str(metric)]].mean(skipna=True)).shape)
        master_per_loadseq_df.loc[str(seq_results)[:-4],[key_avg_colname]] = interm_per_loadseq_result_df.loc[model_ok_list,[str(metric)]].mean(skipna=True).values
        master_per_loadseq_df.loc[str(seq_results)[:-4],[key_med_colname]] = interm_per_loadseq_result_df.loc[model_ok_list,[str(metric)]].median(skipna=True).values
        master_per_loadseq_df.loc[str(seq_results)[:-4],[key_std_colname]] = interm_per_loadseq_result_df.loc[model_ok_list,[str(metric)]].std(skipna=True).values
        
        print("the master df's entry:",master_per_loadseq_df.loc[str(seq_results)[:-4],[key_avg_colname]])
master_per_loadseq_df.sort_values(by=['mae_avg'],inplace=True)        
master_per_loadseq_df.to_csv(analysis_path + 'master_score_per_loadseq.csv')


    

    




('the mean', array([ 0.13648651]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.136487
Name: sequence_2b_449_10_fv1c, dtype: object)
('the mean', array([ 0.08633889]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0863389
Name: sequence_2b_449_10_fv1c, dtype: object)
('the mean', array([ 214.88098251]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    214.881
Name: sequence_2b_449_10_fv1c, dtype: object)
('the mean', array([ 0.05058795]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.050588
Name: sequence_2b_449_10_fv1c, dtype: object)
('the mean', array([ 0.1399199]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.13992
Name: sequence_1k_309_10_fv1c, dtype: object)
('the mean', array([ 0.0876246]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0876246
Name: sequence_1k_309_10_fv1c, dtype: object)
('the mean', array([ 190.2733873]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    190.273
Name: sequence_1k_309_10_fv1c, dtype: object)
('the mean', array([ 0.0519267]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0519267
Name: sequence_1k_309_10_fv1c, dtype: object)
('the mean', array([ 0.1365066]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.136507
Name: sequence_1b_19_10_fv1c, dtype: object)
('the mean', array([ 0.0855664]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0855664
Name: sequence_1b_19_10_fv1c, dtype: object)
('the mean', array([ 184.29510071]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    184.295
Name: sequence_1b_19_10_fv1c, dtype: object)
('the mean', array([ 0.05088758]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0508876
Name: sequence_1b_19_10_fv1c, dtype: object)
('the mean', array([ 0.13881523]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.138815
Name: sequence_1l_399_10_fv1c, dtype: object)
('the mean', array([ 0.08677378]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0867738
Name: sequence_1l_399_10_fv1c, dtype: object)
('the mean', array([ 177.7065387]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    177.707
Name: sequence_1l_399_10_fv1c, dtype: object)
('the mean', array([ 0.05189315]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0518932
Name: sequence_1l_399_10_fv1c, dtype: object)
('the mean', array([ 0.1367235]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.136724
Name: sequence_2b_468_9_fv1c, dtype: object)
('the mean', array([ 0.08633639]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0863364
Name: sequence_2b_468_9_fv1c, dtype: object)
('the mean', array([ 156.72528823]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    156.725
Name: sequence_2b_468_9_fv1c, dtype: object)
('the mean', array([ 0.05137461]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0513746
Name: sequence_2b_468_9_fv1c, dtype: object)
('the mean', array([ 0.1378676]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.137868
Name: sequence_1c_99_10_fv1c, dtype: object)
('the mean', array([ 0.08817625]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0881763
Name: sequence_1c_99_10_fv1c, dtype: object)
('the mean', array([ 282.55271863]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    282.553
Name: sequence_1c_99_10_fv1c, dtype: object)
('the mean', array([ 0.04996937]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0499694
Name: sequence_1c_99_10_fv1c, dtype: object)
('the mean', array([ 0.14174383]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.141744
Name: sequence_1d_168_9_fv1c, dtype: object)
('the mean', array([ 0.09325129]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0932513
Name: sequence_1d_168_9_fv1c, dtype: object)
('the mean', array([ 483.39991393]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    483.4
Name: sequence_1d_168_9_fv1c, dtype: object)
('the mean', array([ 0.06319568]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0631957
Name: sequence_1d_168_9_fv1c, dtype: object)
('the mean', array([ 0.13695229]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.136952
Name: sequence_2b_459_10_fv1c, dtype: object)
('the mean', array([ 0.08610824]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0861082
Name: sequence_2b_459_10_fv1c, dtype: object)
('the mean', array([ 192.23618337]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    192.236
Name: sequence_2b_459_10_fv1c, dtype: object)
('the mean', array([ 0.05114402]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.051144
Name: sequence_2b_459_10_fv1c, dtype: object)
('the mean', array([ 0.23561185]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.235612
Name: sequence_3a_628_10_fv1c, dtype: object)
('the mean', array([ 0.27569836]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.275698
Name: sequence_3a_628_10_fv1c, dtype: object)
('the mean', array([ 413.52581569]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    413.526
Name: sequence_3a_628_10_fv1c, dtype: object)
('the mean', array([ 0.09421434]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0942143
Name: sequence_3a_628_10_fv1c, dtype: object)
('the mean', array([ 0.18748646]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.187486
Name: sequence_1k_338_9_fv1c, dtype: object)
('the mean', array([ 0.14032188]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.140322
Name: sequence_1k_338_9_fv1c, dtype: object)
('the mean', array([ 333.92860293]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    333.929
Name: sequence_1k_338_9_fv1c, dtype: object)
('the mean', array([ 0.06480447]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0648045
Name: sequence_1k_338_9_fv1c, dtype: object)
('the mean', array([ 0.26803347]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.268033
Name: sequence_3a_688_10_fv1c, dtype: object)
('the mean', array([ 0.32492579]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.324926
Name: sequence_3a_688_10_fv1c, dtype: object)
('the mean', array([ 864.56358202]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    864.564
Name: sequence_3a_688_10_fv1c, dtype: object)
('the mean', array([ 0.11426505]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.114265
Name: sequence_3a_688_10_fv1c, dtype: object)
('the mean', array([ 0.27793131]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.277931
Name: sequence_2b_499_10_fv1c, dtype: object)
('the mean', array([ 0.26741937]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.267419
Name: sequence_2b_499_10_fv1c, dtype: object)
('the mean', array([ 479.37340674]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    479.373
Name: sequence_2b_499_10_fv1c, dtype: object)
('the mean', array([ 0.10428191]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.104282
Name: sequence_2b_499_10_fv1c, dtype: object)
('the mean', array([ 0.26830142]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.268301
Name: sequence_3a_687_9_fv1c, dtype: object)
('the mean', array([ 0.32643424]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.326434
Name: sequence_3a_687_9_fv1c, dtype: object)
('the mean', array([ 794.71228436]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    794.712
Name: sequence_3a_687_9_fv1c, dtype: object)
('the mean', array([ 0.11412303]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.114123
Name: sequence_3a_687_9_fv1c, dtype: object)
('the mean', array([ 0.36310687]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.363107
Name: sequence_2c_528_9_fv1c, dtype: object)
('the mean', array([ 0.44729901]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.447299
Name: sequence_2c_528_9_fv1c, dtype: object)
('the mean', array([ 1136.67656947]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    1136.68
Name: sequence_2c_528_9_fv1c, dtype: object)
('the mean', array([ 0.14501276]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.145013
Name: sequence_2c_528_9_fv1c, dtype: object)
('the mean', array([ 0.13880893]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.138809
Name: sequence_1l_398_9_fv1c, dtype: object)
('the mean', array([ 0.08682297]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.086823
Name: sequence_1l_398_9_fv1c, dtype: object)
('the mean', array([ 214.51339904]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    214.513
Name: sequence_1l_398_9_fv1c, dtype: object)
('the mean', array([ 0.0517918]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0517918
Name: sequence_1l_398_9_fv1c, dtype: object)
('the mean', array([ 0.14172982]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.14173
Name: sequence_1d_138_9_fv1c, dtype: object)
('the mean', array([ 0.09336347]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0933635
Name: sequence_1d_138_9_fv1c, dtype: object)
('the mean', array([ 320.79734216]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    320.797
Name: sequence_1d_138_9_fv1c, dtype: object)
('the mean', array([ 0.06284104]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.062841
Name: sequence_1d_138_9_fv1c, dtype: object)
('the mean', array([ 0.13657762]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.136578
Name: sequence_2c_519_10_fv1c, dtype: object)
('the mean', array([ 0.08598899]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.085989
Name: sequence_2c_519_10_fv1c, dtype: object)
('the mean', array([ 131.30576594]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    131.306
Name: sequence_2c_519_10_fv1c, dtype: object)
('the mean', array([ 0.05030897]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.050309
Name: sequence_2c_519_10_fv1c, dtype: object)
('the mean', array([ 0.13658684]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.136587
Name: sequence_1c_69_10_fv1c, dtype: object)
('the mean', array([ 0.08652197]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.086522
Name: sequence_1c_69_10_fv1c, dtype: object)
('the mean', array([ 162.84340099]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    162.843
Name: sequence_1c_69_10_fv1c, dtype: object)
('the mean', array([ 0.05052667]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0505267
Name: sequence_1c_69_10_fv1c, dtype: object)
('the mean', array([ 0.13666723]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.136667
Name: sequence_2b_448_9_fv1c, dtype: object)
('the mean', array([ 0.08670363]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0867036
Name: sequence_2b_448_9_fv1c, dtype: object)
('the mean', array([ 150.04666236]))
('the type of mean', <class 'pandas.core.series.Series'>)
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Name: sequence_2b_448_9_fv1c, dtype: object)
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Name: sequence_2b_448_9_fv1c, dtype: object)
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Name: sequence_2c_549_10_fv1c, dtype: object)
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Name: sequence_2c_549_10_fv1c, dtype: object)
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Name: sequence_2c_549_10_fv1c, dtype: object)
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("the master df's entry:", msle_avg    0.0905505
Name: sequence_2c_549_10_fv1c, dtype: object)
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Name: sequence_1c_119_10_fv1c, dtype: object)
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Name: sequence_1c_119_10_fv1c, dtype: object)
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Name: sequence_1c_119_10_fv1c, dtype: object)
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Name: sequence_1c_119_10_fv1c, dtype: object)
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Name: sequence_1d_259_10_fv1c, dtype: object)
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("the master df's entry:", mse_avg    0.192049
Name: sequence_1d_259_10_fv1c, dtype: object)
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Name: sequence_1d_259_10_fv1c, dtype: object)
('the mean', array([ 0.07881788]))
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Name: sequence_1d_259_10_fv1c, dtype: object)
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Name: sequence_2c_539_10_fv1c, dtype: object)
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Name: sequence_2c_539_10_fv1c, dtype: object)
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Name: sequence_2c_539_10_fv1c, dtype: object)
('the mean', array([ 0.04885432]))
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("the master df's entry:", msle_avg    0.0488543
Name: sequence_2c_539_10_fv1c, dtype: object)
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Name: sequence_3a_608_10_fv1c, dtype: object)
('the mean', array([ 0.27477515]))
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("the master df's entry:", mse_avg    0.274775
Name: sequence_3a_608_10_fv1c, dtype: object)
('the mean', array([ 376.08320245]))
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("the master df's entry:", mape_avg    376.083
Name: sequence_3a_608_10_fv1c, dtype: object)
('the mean', array([ 0.09432899]))
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("the master df's entry:", msle_avg    0.094329
Name: sequence_3a_608_10_fv1c, dtype: object)
('the mean', array([ 0.23586588]))
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("the master df's entry:", mae_avg    0.235866
Name: sequence_3a_588_10_fv1c, dtype: object)
('the mean', array([ 0.27462855]))
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("the master df's entry:", mse_avg    0.274629
Name: sequence_3a_588_10_fv1c, dtype: object)
('the mean', array([ 405.47704626]))
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("the master df's entry:", mape_avg    405.477
Name: sequence_3a_588_10_fv1c, dtype: object)
('the mean', array([ 0.09534651]))
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("the master df's entry:", msle_avg    0.0953465
Name: sequence_3a_588_10_fv1c, dtype: object)
('the mean', array([ 0.28702347]))
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("the master df's entry:", mae_avg    0.287023
Name: sequence_3a_667_9_fv1c, dtype: object)
('the mean', array([ 0.33493419]))
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("the master df's entry:", mse_avg    0.334934
Name: sequence_3a_667_9_fv1c, dtype: object)
('the mean', array([ 535.10058078]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    535.101
Name: sequence_3a_667_9_fv1c, dtype: object)
('the mean', array([ 0.10975759]))
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("the master df's entry:", msle_avg    0.109758
Name: sequence_3a_667_9_fv1c, dtype: object)
('the mean', array([ 0.13660985]))
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("the master df's entry:", mae_avg    0.13661
Name: sequence_1c_79_10_fv1c, dtype: object)
('the mean', array([ 0.08570359]))
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("the master df's entry:", mse_avg    0.0857036
Name: sequence_1c_79_10_fv1c, dtype: object)
('the mean', array([ 134.07230474]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    134.072
Name: sequence_1c_79_10_fv1c, dtype: object)
('the mean', array([ 0.05099065]))
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("the master df's entry:", msle_avg    0.0509906
Name: sequence_1c_79_10_fv1c, dtype: object)
('the mean', array([ 0.21721799]))
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("the master df's entry:", mae_avg    0.217218
Name: sequence_2c_508_9_fv1c, dtype: object)
('the mean', array([ 0.16383739]))
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("the master df's entry:", mse_avg    0.163837
Name: sequence_2c_508_9_fv1c, dtype: object)
('the mean', array([ 591.72667737]))
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("the master df's entry:", mape_avg    591.727
Name: sequence_2c_508_9_fv1c, dtype: object)
('the mean', array([ 0.07177595]))
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("the master df's entry:", msle_avg    0.0717759
Name: sequence_2c_508_9_fv1c, dtype: object)
('the mean', array([ 0.1680918]))
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("the master df's entry:", mae_avg    0.168092
Name: sequence_1k_348_9_fv1c, dtype: object)
('the mean', array([ 0.12658004]))
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("the master df's entry:", mse_avg    0.12658
Name: sequence_1k_348_9_fv1c, dtype: object)
('the mean', array([ 305.47124757]))
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("the master df's entry:", mape_avg    305.471
Name: sequence_1k_348_9_fv1c, dtype: object)
('the mean', array([ 0.06231055]))
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("the master df's entry:", msle_avg    0.0623106
Name: sequence_1k_348_9_fv1c, dtype: object)
('the mean', array([ 0.3043051]))
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("the master df's entry:", mae_avg    0.304305
Name: sequence_1b_58_9_fv1c, dtype: object)
('the mean', array([ 0.31486155]))
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("the master df's entry:", mse_avg    0.314862
Name: sequence_1b_58_9_fv1c, dtype: object)
('the mean', array([ 501.1386037]))
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("the master df's entry:", mape_avg    501.139
Name: sequence_1b_58_9_fv1c, dtype: object)
('the mean', array([ 0.11125858]))
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("the master df's entry:", msle_avg    0.111259
Name: sequence_1b_58_9_fv1c, dtype: object)
('the mean', array([ 0.13980849]))
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("the master df's entry:", mae_avg    0.139808
Name: sequence_1k_308_9_fv1c, dtype: object)
('the mean', array([ 0.08752686]))
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("the master df's entry:", mse_avg    0.0875269
Name: sequence_1k_308_9_fv1c, dtype: object)
('the mean', array([ 231.11410899]))
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("the master df's entry:", mape_avg    231.114
Name: sequence_1k_308_9_fv1c, dtype: object)
('the mean', array([ 0.05183038]))
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("the master df's entry:", msle_avg    0.0518304
Name: sequence_1k_308_9_fv1c, dtype: object)
('the mean', array([ 0.18984284]))
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("the master df's entry:", mae_avg    0.189843
Name: sequence_1d_228_9_fv1c, dtype: object)
('the mean', array([ 0.14484659]))
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("the master df's entry:", mse_avg    0.144847
Name: sequence_1d_228_9_fv1c, dtype: object)
('the mean', array([ 458.48621637]))
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("the master df's entry:", mape_avg    458.486
Name: sequence_1d_228_9_fv1c, dtype: object)
('the mean', array([ 0.06952601]))
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("the master df's entry:", msle_avg    0.069526
Name: sequence_1d_228_9_fv1c, dtype: object)
('the mean', array([ 0.13857843]))
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("the master df's entry:", mae_avg    0.138578
Name: sequence_1k_299_10_fv1c, dtype: object)
('the mean', array([ 0.08636641]))
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("the master df's entry:", mse_avg    0.0863664
Name: sequence_1k_299_10_fv1c, dtype: object)
('the mean', array([ 186.00995416]))
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("the master df's entry:", mape_avg    186.01
Name: sequence_1k_299_10_fv1c, dtype: object)
('the mean', array([ 0.05214065]))
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("the master df's entry:", msle_avg    0.0521407
Name: sequence_1k_299_10_fv1c, dtype: object)
('the mean', array([ 0.31983712]))
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("the master df's entry:", mae_avg    0.319837
Name: sequence_2c_559_10_fv1c, dtype: object)
('the mean', array([ 0.34586131]))
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("the master df's entry:", mse_avg    0.345861
Name: sequence_2c_559_10_fv1c, dtype: object)
('the mean', array([ 555.39151564]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    555.392
Name: sequence_2c_559_10_fv1c, dtype: object)
('the mean', array([ 0.11499103]))
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("the master df's entry:", msle_avg    0.114991
Name: sequence_2c_559_10_fv1c, dtype: object)
('the mean', array([ 0.31971975]))
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("the master df's entry:", mae_avg    0.31972
Name: sequence_2c_558_9_fv1c, dtype: object)
('the mean', array([ 0.34555537]))
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("the master df's entry:", mse_avg    0.345555
Name: sequence_2c_558_9_fv1c, dtype: object)
('the mean', array([ 537.90319468]))
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("the master df's entry:", mape_avg    537.903
Name: sequence_2c_558_9_fv1c, dtype: object)
('the mean', array([ 0.11499744]))
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("the master df's entry:", msle_avg    0.114997
Name: sequence_2c_558_9_fv1c, dtype: object)
('the mean', array([ 0.13659867]))
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("the master df's entry:", mae_avg    0.136599
Name: sequence_1b_8_9_fv1c, dtype: object)
('the mean', array([ 0.08667138]))
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("the master df's entry:", mse_avg    0.0866714
Name: sequence_1b_8_9_fv1c, dtype: object)
('the mean', array([ 150.47882009]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    150.479
Name: sequence_1b_8_9_fv1c, dtype: object)
('the mean', array([ 0.05048619]))
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("the master df's entry:", msle_avg    0.0504862
Name: sequence_1b_8_9_fv1c, dtype: object)
('the mean', array([ 0.36757006]))
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("the master df's entry:", mae_avg    0.36757
Name: sequence_3a_569_10_fv1c, dtype: object)
('the mean', array([ 0.47951361]))
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("the master df's entry:", mse_avg    0.479514
Name: sequence_3a_569_10_fv1c, dtype: object)
('the mean', array([ 638.51640437]))
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("the master df's entry:", mape_avg    638.516
Name: sequence_3a_569_10_fv1c, dtype: object)
('the mean', array([ 0.10535416]))
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("the master df's entry:", msle_avg    0.105354
Name: sequence_3a_569_10_fv1c, dtype: object)
('the mean', array([ 0.16824404]))
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("the master df's entry:", mae_avg    0.168244
Name: sequence_1k_358_9_fv1c, dtype: object)
('the mean', array([ 0.12549866]))
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("the master df's entry:", mse_avg    0.125499
Name: sequence_1k_358_9_fv1c, dtype: object)
('the mean', array([ 269.33135385]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    269.331
Name: sequence_1k_358_9_fv1c, dtype: object)
('the mean', array([ 0.06113167]))
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("the master df's entry:", msle_avg    0.0611317
Name: sequence_1k_358_9_fv1c, dtype: object)
('the mean', array([ 0.20793159]))
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("the master df's entry:", mae_avg    0.207932
Name: sequence_1k_329_10_fv1c, dtype: object)
('the mean', array([ 0.16022587]))
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("the master df's entry:", mse_avg    0.160226
Name: sequence_1k_329_10_fv1c, dtype: object)
('the mean', array([ 282.50186054]))
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("the master df's entry:", mape_avg    282.502
Name: sequence_1k_329_10_fv1c, dtype: object)
('the mean', array([ 0.06401513]))
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("the master df's entry:", msle_avg    0.0640151
Name: sequence_1k_329_10_fv1c, dtype: object)
('the mean', array([ 0.29502263]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mae_avg    0.295023
Name: sequence_1l_369_10_fv1c, dtype: object)
('the mean', array([ 0.2993332]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mse_avg    0.299333
Name: sequence_1l_369_10_fv1c, dtype: object)
('the mean', array([ 283.61182025]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    283.612
Name: sequence_1l_369_10_fv1c, dtype: object)
('the mean', array([ 0.07821006]))
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("the master df's entry:", msle_avg    0.0782101
Name: sequence_1l_369_10_fv1c, dtype: object)
('the mean', array([ 0.27785196]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mae_avg    0.277852
Name: sequence_2b_498_9_fv1c, dtype: object)
('the mean', array([ 0.267361]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mse_avg    0.267361
Name: sequence_2b_498_9_fv1c, dtype: object)
('the mean', array([ 476.4482272]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    476.448
Name: sequence_2b_498_9_fv1c, dtype: object)
('the mean', array([ 0.10431691]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", msle_avg    0.104317
Name: sequence_2b_498_9_fv1c, dtype: object)
('the mean', array([ 0.23453213]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mae_avg    0.234532
Name: sequence_3a_568_9_fv1c, dtype: object)
('the mean', array([ 0.27209223]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.272092
Name: sequence_3a_568_9_fv1c, dtype: object)
('the mean', array([ 446.32278066]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    446.323
Name: sequence_3a_568_9_fv1c, dtype: object)
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Name: sequence_3a_568_9_fv1c, dtype: object)
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Name: sequence_3a_648_10_fv1c, dtype: object)
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Name: sequence_3a_648_10_fv1c, dtype: object)
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Name: sequence_3a_648_10_fv1c, dtype: object)
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Name: sequence_3a_648_10_fv1c, dtype: object)
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Name: sequence_1l_439_10_fv1c, dtype: object)
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Name: sequence_1l_439_10_fv1c, dtype: object)
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Name: sequence_1l_439_10_fv1c, dtype: object)
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("the master df's entry:", msle_avg    0.0649355
Name: sequence_1l_439_10_fv1c, dtype: object)
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Name: sequence_1c_68_9_fv1c, dtype: object)
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Name: sequence_1c_68_9_fv1c, dtype: object)
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Name: sequence_1c_68_9_fv1c, dtype: object)
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Name: sequence_1c_68_9_fv1c, dtype: object)
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Name: sequence_3a_627_9_fv1c, dtype: object)
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("the master df's entry:", mse_avg    0.273552
Name: sequence_3a_627_9_fv1c, dtype: object)
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Name: sequence_3a_627_9_fv1c, dtype: object)
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Name: sequence_3a_627_9_fv1c, dtype: object)
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Name: sequence_1b_38_9_fv1c, dtype: object)
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Name: sequence_1b_38_9_fv1c, dtype: object)
('the mean', array([ 180.38629205]))
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Name: sequence_1b_38_9_fv1c, dtype: object)
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Name: sequence_1b_38_9_fv1c, dtype: object)
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Name: sequence_1l_379_10_fv1c, dtype: object)
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Name: sequence_1l_379_10_fv1c, dtype: object)
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Name: sequence_1l_379_10_fv1c, dtype: object)
('the mean', array([ 0.05203912]))
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("the master df's entry:", msle_avg    0.0520391
Name: sequence_1l_379_10_fv1c, dtype: object)
('the mean', array([ 0.18582946]))
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Name: sequence_1l_419_10_fv1c, dtype: object)
('the mean', array([ 0.13883547]))
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("the master df's entry:", mse_avg    0.138835
Name: sequence_1l_419_10_fv1c, dtype: object)
('the mean', array([ 306.19537794]))
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("the master df's entry:", mape_avg    306.195
Name: sequence_1l_419_10_fv1c, dtype: object)
('the mean', array([ 0.06217018]))
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("the master df's entry:", msle_avg    0.0621702
Name: sequence_1l_419_10_fv1c, dtype: object)
('the mean', array([ 0.14164734]))
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("the master df's entry:", mae_avg    0.141647
Name: sequence_1d_169_10_fv1c, dtype: object)
('the mean', array([ 0.09321684]))
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("the master df's entry:", mse_avg    0.0932168
Name: sequence_1d_169_10_fv1c, dtype: object)
('the mean', array([ 312.44344764]))
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("the master df's entry:", mape_avg    312.443
Name: sequence_1d_169_10_fv1c, dtype: object)
('the mean', array([ 0.06318581]))
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("the master df's entry:", msle_avg    0.0631858
Name: sequence_1d_169_10_fv1c, dtype: object)
('the mean', array([ 0.18559763]))
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("the master df's entry:", mae_avg    0.185598
Name: sequence_1l_418_9_fv1c, dtype: object)
('the mean', array([ 0.13817613]))
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("the master df's entry:", mse_avg    0.138176
Name: sequence_1l_418_9_fv1c, dtype: object)
('the mean', array([ 286.48351409]))
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("the master df's entry:", mape_avg    286.484
Name: sequence_1l_418_9_fv1c, dtype: object)
('the mean', array([ 0.06226751]))
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("the master df's entry:", msle_avg    0.0622675
Name: sequence_1l_418_9_fv1c, dtype: object)
('the mean', array([ 0.13799978]))
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("the master df's entry:", mae_avg    0.138
Name: sequence_1k_289_10_fv1c, dtype: object)
('the mean', array([ 0.08689134]))
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("the master df's entry:", mse_avg    0.0868913
Name: sequence_1k_289_10_fv1c, dtype: object)
('the mean', array([ 155.53340566]))
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("the master df's entry:", mape_avg    155.533
Name: sequence_1k_289_10_fv1c, dtype: object)
('the mean', array([ 0.05200918]))
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("the master df's entry:", msle_avg    0.0520092
Name: sequence_1k_289_10_fv1c, dtype: object)
('the mean', array([ 0.26616179]))
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Name: sequence_3a_708_10_fv1c, dtype: object)
('the mean', array([ 0.31907766]))
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("the master df's entry:", mse_avg    0.319078
Name: sequence_3a_708_10_fv1c, dtype: object)
('the mean', array([ 1951.02815886]))
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("the master df's entry:", mape_avg    1951.03
Name: sequence_3a_708_10_fv1c, dtype: object)
('the mean', array([ 0.11411626]))
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("the master df's entry:", msle_avg    0.114116
Name: sequence_3a_708_10_fv1c, dtype: object)
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Name: sequence_1c_78_9_fv1c, dtype: object)
('the mean', array([ 0.08557724]))
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("the master df's entry:", mse_avg    0.0855772
Name: sequence_1c_78_9_fv1c, dtype: object)
('the mean', array([ 152.08707122]))
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("the master df's entry:", mape_avg    152.087
Name: sequence_1c_78_9_fv1c, dtype: object)
('the mean', array([ 0.05090457]))
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("the master df's entry:", msle_avg    0.0509046
Name: sequence_1c_78_9_fv1c, dtype: object)
('the mean', array([ 0.15826791]))
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Name: sequence_1l_409_10_fv1c, dtype: object)
('the mean', array([ 0.11245666]))
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("the master df's entry:", mse_avg    0.112457
Name: sequence_1l_409_10_fv1c, dtype: object)
('the mean', array([ 238.7073796]))
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("the master df's entry:", mape_avg    238.707
Name: sequence_1l_409_10_fv1c, dtype: object)
('the mean', array([ 0.05875183]))
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("the master df's entry:", msle_avg    0.0587518
Name: sequence_1l_409_10_fv1c, dtype: object)
('the mean', array([ 0.14232553]))
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("the master df's entry:", mae_avg    0.142326
Name: sequence_1d_198_9_fv1c, dtype: object)
('the mean', array([ 0.09470696]))
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("the master df's entry:", mse_avg    0.094707
Name: sequence_1d_198_9_fv1c, dtype: object)
('the mean', array([ 492.96670282]))
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("the master df's entry:", mape_avg    492.967
Name: sequence_1d_198_9_fv1c, dtype: object)
('the mean', array([ 0.0614582]))
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("the master df's entry:", msle_avg    0.0614582
Name: sequence_1d_198_9_fv1c, dtype: object)
('the mean', array([ 0.13874168]))
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("the master df's entry:", mae_avg    0.138742
Name: sequence_1l_388_9_fv1c, dtype: object)
('the mean', array([ 0.08661525]))
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("the master df's entry:", mse_avg    0.0866153
Name: sequence_1l_388_9_fv1c, dtype: object)
('the mean', array([ 799.26052256]))
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("the master df's entry:", mape_avg    799.261
Name: sequence_1l_388_9_fv1c, dtype: object)
('the mean', array([ 0.05197196]))
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("the master df's entry:", msle_avg    0.051972
Name: sequence_1l_388_9_fv1c, dtype: object)
('the mean', array([ 0.13807346]))
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("the master df's entry:", mae_avg    0.138073
Name: sequence_1k_288_9_fv1c, dtype: object)
('the mean', array([ 0.08644082]))
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("the master df's entry:", mse_avg    0.0864408
Name: sequence_1k_288_9_fv1c, dtype: object)
('the mean', array([ 224.69263511]))
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("the master df's entry:", mape_avg    224.693
Name: sequence_1k_288_9_fv1c, dtype: object)
('the mean', array([ 0.05188797]))
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("the master df's entry:", msle_avg    0.051888
Name: sequence_1k_288_9_fv1c, dtype: object)
('the mean', array([ 0.2352105]))
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("the master df's entry:", mae_avg    0.235211
Name: sequence_1d_258_9_fv1c, dtype: object)
('the mean', array([ 0.19224287]))
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("the master df's entry:", mse_avg    0.192243
Name: sequence_1d_258_9_fv1c, dtype: object)
('the mean', array([ 569.89381]))
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("the master df's entry:", mape_avg    569.894
Name: sequence_1d_258_9_fv1c, dtype: object)
('the mean', array([ 0.07906123]))
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("the master df's entry:", msle_avg    0.0790612
Name: sequence_1d_258_9_fv1c, dtype: object)
('the mean', array([ 0.30436508]))
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("the master df's entry:", mae_avg    0.304365
Name: sequence_1b_59_10_fv1c, dtype: object)
('the mean', array([ 0.3149662]))
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("the master df's entry:", mse_avg    0.314966
Name: sequence_1b_59_10_fv1c, dtype: object)
('the mean', array([ 618.64532527]))
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("the master df's entry:", mape_avg    618.645
Name: sequence_1b_59_10_fv1c, dtype: object)
('the mean', array([ 0.1112592]))
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("the master df's entry:", msle_avg    0.111259
Name: sequence_1b_59_10_fv1c, dtype: object)
('the mean', array([ 0.13657006]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mae_avg    0.13657
Name: sequence_1b_18_9_fv1c, dtype: object)
('the mean', array([ 0.08553193]))
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("the master df's entry:", mse_avg    0.0855319
Name: sequence_1b_18_9_fv1c, dtype: object)
('the mean', array([ 593.80677052]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    593.807
Name: sequence_1b_18_9_fv1c, dtype: object)
('the mean', array([ 0.05090511]))
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("the master df's entry:", msle_avg    0.0509051
Name: sequence_1b_18_9_fv1c, dtype: object)
('the mean', array([ 0.13643717]))
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("the master df's entry:", mae_avg    0.136437
Name: sequence_2b_469_10_fv1c, dtype: object)
('the mean', array([ 0.08579596]))
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("the master df's entry:", mse_avg    0.085796
Name: sequence_2b_469_10_fv1c, dtype: object)
('the mean', array([ 202.92980496]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    202.93
Name: sequence_2b_469_10_fv1c, dtype: object)
('the mean', array([ 0.05135564]))
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("the master df's entry:", msle_avg    0.0513556
Name: sequence_2b_469_10_fv1c, dtype: object)
('the mean', array([ 0.18612566]))
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("the master df's entry:", mae_avg    0.186126
Name: sequence_1l_429_10_fv1c, dtype: object)
('the mean', array([ 0.14048983]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.14049
Name: sequence_1l_429_10_fv1c, dtype: object)
('the mean', array([ 565.14741785]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    565.147
Name: sequence_1l_429_10_fv1c, dtype: object)
('the mean', array([ 0.06425977]))
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("the master df's entry:", msle_avg    0.0642598
Name: sequence_1l_429_10_fv1c, dtype: object)
('the mean', array([ 0.13668433]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mae_avg    0.136684
Name: sequence_1b_9_10_fv1c, dtype: object)
('the mean', array([ 0.08687938]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mse_avg    0.0868794
Name: sequence_1b_9_10_fv1c, dtype: object)
('the mean', array([ 157.90035433]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    157.9
Name: sequence_1b_9_10_fv1c, dtype: object)
('the mean', array([ 0.05048791]))
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("the master df's entry:", msle_avg    0.0504879
Name: sequence_1b_9_10_fv1c, dtype: object)
('the mean', array([ 0.17480596]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mae_avg    0.174806
Name: sequence_1l_378_9_fv1c, dtype: object)
('the mean', array([ 0.11742198]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.117422
Name: sequence_1l_378_9_fv1c, dtype: object)
('the mean', array([ 384.39810572]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    384.398
Name: sequence_1l_378_9_fv1c, dtype: object)
('the mean', array([ 0.05211443]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", msle_avg    0.0521144
Name: sequence_1l_378_9_fv1c, dtype: object)
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Name: sequence_1l_389_10_fv1c, dtype: object)
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Name: sequence_1l_389_10_fv1c, dtype: object)
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("the master df's entry:", mape_avg    175.268
Name: sequence_1l_389_10_fv1c, dtype: object)
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("the master df's entry:", msle_avg    0.0519901
Name: sequence_1l_389_10_fv1c, dtype: object)
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Name: sequence_1c_118_9_fv1c, dtype: object)
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("the master df's entry:", mse_avg    0.314785
Name: sequence_1c_118_9_fv1c, dtype: object)
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Name: sequence_1c_118_9_fv1c, dtype: object)
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("the master df's entry:", msle_avg    0.111049
Name: sequence_1c_118_9_fv1c, dtype: object)
('the mean', array([ 0.1416919]))
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Name: sequence_1d_139_10_fv1c, dtype: object)
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("the master df's entry:", mse_avg    0.0932742
Name: sequence_1d_139_10_fv1c, dtype: object)
('the mean', array([ 663.50565371]))
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("the master df's entry:", mape_avg    663.506
Name: sequence_1d_139_10_fv1c, dtype: object)
('the mean', array([ 0.06288325]))
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("the master df's entry:", msle_avg    0.0628832
Name: sequence_1d_139_10_fv1c, dtype: object)
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Name: sequence_1b_28_9_fv1c, dtype: object)
('the mean', array([ 0.08627156]))
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("the master df's entry:", mse_avg    0.0862716
Name: sequence_1b_28_9_fv1c, dtype: object)
('the mean', array([ 152.27251016]))
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("the master df's entry:", mape_avg    152.273
Name: sequence_1b_28_9_fv1c, dtype: object)
('the mean', array([ 0.05115518]))
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("the master df's entry:", msle_avg    0.0511552
Name: sequence_1b_28_9_fv1c, dtype: object)
('the mean', array([ 0.25739285]))
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Name: sequence_1b_49_10_fv1c, dtype: object)
('the mean', array([ 0.2372357]))
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("the master df's entry:", mse_avg    0.237236
Name: sequence_1b_49_10_fv1c, dtype: object)
('the mean', array([ 669.20492771]))
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("the master df's entry:", mape_avg    669.205
Name: sequence_1b_49_10_fv1c, dtype: object)
('the mean', array([ 0.10005261]))
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("the master df's entry:", msle_avg    0.100053
Name: sequence_1b_49_10_fv1c, dtype: object)
('the mean', array([ 0.13800872]))
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("the master df's entry:", mae_avg    0.138009
Name: sequence_2b_479_10_fv1c, dtype: object)
('the mean', array([ 0.0882089]))
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("the master df's entry:", mse_avg    0.0882089
Name: sequence_2b_479_10_fv1c, dtype: object)
('the mean', array([ 188.50442445]))
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("the master df's entry:", mape_avg    188.504
Name: sequence_2b_479_10_fv1c, dtype: object)
('the mean', array([ 0.05022006]))
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("the master df's entry:", msle_avg    0.0502201
Name: sequence_2b_479_10_fv1c, dtype: object)
('the mean', array([ 0.13681672]))
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("the master df's entry:", mae_avg    0.136817
Name: sequence_1b_29_10_fv1c, dtype: object)
('the mean', array([ 0.08658526]))
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("the master df's entry:", mse_avg    0.0865853
Name: sequence_1b_29_10_fv1c, dtype: object)
('the mean', array([ 165.1012945]))
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("the master df's entry:", mape_avg    165.101
Name: sequence_1b_29_10_fv1c, dtype: object)
('the mean', array([ 0.05122911]))
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("the master df's entry:", msle_avg    0.0512291
Name: sequence_1b_29_10_fv1c, dtype: object)
('the mean', array([ 0.20804256]))
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("the master df's entry:", mae_avg    0.208043
Name: sequence_1k_328_9_fv1c, dtype: object)
('the mean', array([ 0.16075598]))
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("the master df's entry:", mse_avg    0.160756
Name: sequence_1k_328_9_fv1c, dtype: object)
('the mean', array([ 343.43814951]))
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("the master df's entry:", mape_avg    343.438
Name: sequence_1k_328_9_fv1c, dtype: object)
('the mean', array([ 0.06391025]))
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("the master df's entry:", msle_avg    0.0639103
Name: sequence_1k_328_9_fv1c, dtype: object)
('the mean', array([ 0.29511058]))
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("the master df's entry:", mae_avg    0.295111
Name: sequence_1l_368_9_fv1c, dtype: object)
('the mean', array([ 0.2999708]))
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("the master df's entry:", mse_avg    0.299971
Name: sequence_1l_368_9_fv1c, dtype: object)
('the mean', array([ 327.82018508]))
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("the master df's entry:", mape_avg    327.82
Name: sequence_1l_368_9_fv1c, dtype: object)
('the mean', array([ 0.07821925]))
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("the master df's entry:", msle_avg    0.0782192
Name: sequence_1l_368_9_fv1c, dtype: object)
('the mean', array([ 0.13627233]))
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("the master df's entry:", mae_avg    0.136272
Name: sequence_2c_538_9_fv1c, dtype: object)
('the mean', array([ 0.08563423]))
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("the master df's entry:", mse_avg    0.0856342
Name: sequence_2c_538_9_fv1c, dtype: object)
('the mean', array([ 141.86908463]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    141.869
Name: sequence_2c_538_9_fv1c, dtype: object)
('the mean', array([ 0.04883584]))
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("the master df's entry:", msle_avg    0.0488358
Name: sequence_2c_538_9_fv1c, dtype: object)
('the mean', array([ 0.27095425]))
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("the master df's entry:", mae_avg    0.270954
Name: sequence_3a_587_9_fv1c, dtype: object)
('the mean', array([ 0.31126052]))
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("the master df's entry:", mse_avg    0.311261
Name: sequence_3a_587_9_fv1c, dtype: object)
('the mean', array([ 347.00421781]))
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("the master df's entry:", mape_avg    347.004
Name: sequence_3a_587_9_fv1c, dtype: object)
('the mean', array([ 0.10112108]))
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("the master df's entry:", msle_avg    0.101121
Name: sequence_3a_587_9_fv1c, dtype: object)
('the mean', array([ 0.36315294]))
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("the master df's entry:", mae_avg    0.363153
Name: sequence_2c_529_10_fv1c, dtype: object)
('the mean', array([ 0.44761198]))
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("the master df's entry:", mse_avg    0.447612
Name: sequence_2c_529_10_fv1c, dtype: object)
('the mean', array([ 1932.09110511]))
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("the master df's entry:", mape_avg    1932.09
Name: sequence_2c_529_10_fv1c, dtype: object)
('the mean', array([ 0.14497577]))
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("the master df's entry:", msle_avg    0.144976
Name: sequence_2c_529_10_fv1c, dtype: object)
('the mean', array([ 0.28682576]))
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("the master df's entry:", mae_avg    0.286826
Name: sequence_3a_668_10_fv1c, dtype: object)
('the mean', array([ 0.33497486]))
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("the master df's entry:", mse_avg    0.334975
Name: sequence_3a_668_10_fv1c, dtype: object)
('the mean', array([ 588.2343827]))
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("the master df's entry:", mape_avg    588.234
Name: sequence_3a_668_10_fv1c, dtype: object)
('the mean', array([ 0.10958376]))
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("the master df's entry:", msle_avg    0.109584
Name: sequence_3a_668_10_fv1c, dtype: object)
('the mean', array([ 0.13661121]))
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("the master df's entry:", mae_avg    0.136611
Name: sequence_2b_458_9_fv1c, dtype: object)
('the mean', array([ 0.08550107]))
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("the master df's entry:", mse_avg    0.0855011
Name: sequence_2b_458_9_fv1c, dtype: object)
('the mean', array([ 168.76690221]))
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("the master df's entry:", mape_avg    168.767
Name: sequence_2b_458_9_fv1c, dtype: object)
('the mean', array([ 0.05097314]))
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("the master df's entry:", msle_avg    0.0509731
Name: sequence_2b_458_9_fv1c, dtype: object)
('the mean', array([ 0.19004935]))
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("the master df's entry:", mae_avg    0.190049
Name: sequence_1d_229_10_fv1c, dtype: object)
('the mean', array([ 0.14549118]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mse_avg    0.145491
Name: sequence_1d_229_10_fv1c, dtype: object)
('the mean', array([ 571.14708268]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    571.147
Name: sequence_1d_229_10_fv1c, dtype: object)
('the mean', array([ 0.06954151]))
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("the master df's entry:", msle_avg    0.0695415
Name: sequence_1d_229_10_fv1c, dtype: object)
('the mean', array([ 0.1425331]))
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("the master df's entry:", mae_avg    0.142533
Name: sequence_1d_199_10_fv1c, dtype: object)
('the mean', array([ 0.09498852]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mse_avg    0.0949885
Name: sequence_1d_199_10_fv1c, dtype: object)
('the mean', array([ 338.14677849]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    338.147
Name: sequence_1d_199_10_fv1c, dtype: object)
('the mean', array([ 0.06163791]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", msle_avg    0.0616379
Name: sequence_1d_199_10_fv1c, dtype: object)
('the mean', array([ 0.18697722]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mae_avg    0.186977
Name: sequence_1l_438_9_fv1c, dtype: object)
('the mean', array([ 0.14274406]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mse_avg    0.142744
Name: sequence_1l_438_9_fv1c, dtype: object)
('the mean', array([ 387.33662915]))
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("the master df's entry:", mape_avg    387.337
Name: sequence_1l_438_9_fv1c, dtype: object)
('the mean', array([ 0.06499979]))
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("the master df's entry:", msle_avg    0.0649998
Name: sequence_1l_438_9_fv1c, dtype: object)
('the mean', array([ 0.13854688]))
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("the master df's entry:", mae_avg    0.138547
Name: sequence_1k_298_9_fv1c, dtype: object)
('the mean', array([ 0.08625181]))
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("the master df's entry:", mse_avg    0.0862518
Name: sequence_1k_298_9_fv1c, dtype: object)
('the mean', array([ 191.3954669]))
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("the master df's entry:", mape_avg    191.395
Name: sequence_1k_298_9_fv1c, dtype: object)
('the mean', array([ 0.05216313]))
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("the master df's entry:", msle_avg    0.0521631
Name: sequence_1k_298_9_fv1c, dtype: object)
('the mean', array([ 0.23289996]))
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("the master df's entry:", mae_avg    0.2329
Name: sequence_2b_489_10_fv1c, dtype: object)
('the mean', array([ 0.20208221]))
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("the master df's entry:", mse_avg    0.202082
Name: sequence_2b_489_10_fv1c, dtype: object)
('the mean', array([ 401.51993032]))
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("the master df's entry:", mape_avg    401.52
Name: sequence_2b_489_10_fv1c, dtype: object)
('the mean', array([ 0.09250409]))
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("the master df's entry:", msle_avg    0.0925041
Name: sequence_2b_489_10_fv1c, dtype: object)
('the mean', array([ 0.23657415]))
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("the master df's entry:", mae_avg    0.236574
Name: sequence_3a_607_9_fv1c, dtype: object)
('the mean', array([ 0.27593622]))
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('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.275936
Name: sequence_3a_607_9_fv1c, dtype: object)
('the mean', array([ 342.18331213]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    342.183
Name: sequence_3a_607_9_fv1c, dtype: object)
('the mean', array([ 0.09517624]))
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("the master df's entry:", msle_avg    0.0951762
Name: sequence_3a_607_9_fv1c, dtype: object)
('the mean', array([ 0.13682295]))
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("the master df's entry:", mae_avg    0.136823
Name: sequence_1c_88_9_fv1c, dtype: object)
('the mean', array([ 0.08648934]))
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('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0864893
Name: sequence_1c_88_9_fv1c, dtype: object)
('the mean', array([ 171.29455373]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    171.295
Name: sequence_1c_88_9_fv1c, dtype: object)
('the mean', array([ 0.05124169]))
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('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0512417
Name: sequence_1c_88_9_fv1c, dtype: object)
('the mean', array([ 0.25755933]))
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("the master df's entry:", mae_avg    0.257559
Name: sequence_1c_108_9_fv1c, dtype: object)
('the mean', array([ 0.23784341]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.237843
Name: sequence_1c_108_9_fv1c, dtype: object)
('the mean', array([ 1530.90828915]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    1530.91
Name: sequence_1c_108_9_fv1c, dtype: object)
('the mean', array([ 0.09983685]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0998368
Name: sequence_1c_108_9_fv1c, dtype: object)
('the mean', array([ 0.13653881]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mae_avg    0.136539
Name: sequence_2c_518_9_fv1c, dtype: object)
('the mean', array([ 0.08577122]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0857712
Name: sequence_2c_518_9_fv1c, dtype: object)
('the mean', array([ 154.64309204]))
('the type of mean', <class 'pandas.core.series.Series'>)
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("the master df's entry:", mape_avg    154.643
Name: sequence_2c_518_9_fv1c, dtype: object)
('the mean', array([ 0.05034409]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0503441
Name: sequence_2c_518_9_fv1c, dtype: object)
('the mean', array([ 0.15844611]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.158446
Name: sequence_1l_408_9_fv1c, dtype: object)
('the mean', array([ 0.11319727]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.113197
Name: sequence_1l_408_9_fv1c, dtype: object)
('the mean', array([ 278.81759071]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    278.818
Name: sequence_1l_408_9_fv1c, dtype: object)
('the mean', array([ 0.05891677]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0589168
Name: sequence_1l_408_9_fv1c, dtype: object)
('the mean', array([ 0.13793442]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.137934
Name: sequence_1b_39_10_fv1c, dtype: object)
('the mean', array([ 0.08831705]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0883171
Name: sequence_1b_39_10_fv1c, dtype: object)
('the mean', array([ 146.76260807]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    146.763
Name: sequence_1b_39_10_fv1c, dtype: object)
('the mean', array([ 0.05003042]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0500304
Name: sequence_1b_39_10_fv1c, dtype: object)
('the mean', array([ 0.30355752]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.303558
Name: sequence_3a_647_9_fv1c, dtype: object)
('the mean', array([ 0.36021702]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.360217
Name: sequence_3a_647_9_fv1c, dtype: object)
('the mean', array([ 462.59316851]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    462.593
Name: sequence_3a_647_9_fv1c, dtype: object)
('the mean', array([ 0.11587157]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.115872
Name: sequence_3a_647_9_fv1c, dtype: object)
('the mean', array([ 0.16789033]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.16789
Name: sequence_1k_349_10_fv1c, dtype: object)
('the mean', array([ 0.12610692]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.126107
Name: sequence_1k_349_10_fv1c, dtype: object)
('the mean', array([ 286.59440701]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    286.594
Name: sequence_1k_349_10_fv1c, dtype: object)
('the mean', array([ 0.06239086]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0623909
Name: sequence_1k_349_10_fv1c, dtype: object)
('the mean', array([ 0.13791269]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.137913
Name: sequence_1c_98_9_fv1c, dtype: object)
('the mean', array([ 0.08824184]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0882418
Name: sequence_1c_98_9_fv1c, dtype: object)
('the mean', array([ 157.5457482]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    157.546
Name: sequence_1c_98_9_fv1c, dtype: object)
('the mean', array([ 0.05018102]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.050181
Name: sequence_1c_98_9_fv1c, dtype: object)
('the mean', array([ 0.23291909]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.232919
Name: sequence_2b_488_9_fv1c, dtype: object)
('the mean', array([ 0.20221915]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.202219
Name: sequence_2b_488_9_fv1c, dtype: object)
('the mean', array([ 577.85295683]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    577.853
Name: sequence_2b_488_9_fv1c, dtype: object)
('the mean', array([ 0.09259261]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0925926
Name: sequence_2b_488_9_fv1c, dtype: object)
('the mean', array([ 0.13677582]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.136776
Name: sequence_1c_89_10_fv1c, dtype: object)
('the mean', array([ 0.08656281]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0865628
Name: sequence_1c_89_10_fv1c, dtype: object)
('the mean', array([ 175.20400282]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    175.204
Name: sequence_1c_89_10_fv1c, dtype: object)
('the mean', array([ 0.0511886]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0511886
Name: sequence_1c_89_10_fv1c, dtype: object)
('the mean', array([ 0.13794647]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.137946
Name: sequence_1d_129_10_fv1c, dtype: object)
('the mean', array([ 0.08697067]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0869707
Name: sequence_1d_129_10_fv1c, dtype: object)
('the mean', array([ 153.55053034]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    153.551
Name: sequence_1d_129_10_fv1c, dtype: object)
('the mean', array([ 0.05177621]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0517762
Name: sequence_1d_129_10_fv1c, dtype: object)
('the mean', array([ 0.13914623]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.139146
Name: sequence_1k_318_9_fv1c, dtype: object)
('the mean', array([ 0.08834558]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0883456
Name: sequence_1k_318_9_fv1c, dtype: object)
('the mean', array([ 242.7950256]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    242.795
Name: sequence_1k_318_9_fv1c, dtype: object)
('the mean', array([ 0.05134571]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0513457
Name: sequence_1k_318_9_fv1c, dtype: object)
('the mean', array([ 0.2171324]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.217132
Name: sequence_2c_509_10_fv1c, dtype: object)
('the mean', array([ 0.16372738]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.163727
Name: sequence_2c_509_10_fv1c, dtype: object)
('the mean', array([ 614.69651724]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    614.697
Name: sequence_2c_509_10_fv1c, dtype: object)
('the mean', array([ 0.0715726]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0715726
Name: sequence_2c_509_10_fv1c, dtype: object)
('the mean', array([ 0.13776393]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.137764
Name: sequence_2b_478_9_fv1c, dtype: object)
('the mean', array([ 0.08771757]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0877176
Name: sequence_2b_478_9_fv1c, dtype: object)
('the mean', array([ 147.90670804]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    147.907
Name: sequence_2b_478_9_fv1c, dtype: object)
('the mean', array([ 0.05023712]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0502371
Name: sequence_2b_478_9_fv1c, dtype: object)
('the mean', array([ 0.25739799]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.257398
Name: sequence_1b_48_9_fv1c, dtype: object)
('the mean', array([ 0.23714644]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.237146
Name: sequence_1b_48_9_fv1c, dtype: object)
('the mean', array([ 700.15078367]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    700.151
Name: sequence_1b_48_9_fv1c, dtype: object)
('the mean', array([ 0.10009569]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.100096
Name: sequence_1b_48_9_fv1c, dtype: object)
('the mean', array([ 0.18610466]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.186105
Name: sequence_1l_428_9_fv1c, dtype: object)
('the mean', array([ 0.14049897]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.140499
Name: sequence_1l_428_9_fv1c, dtype: object)
('the mean', array([ 735.89533877]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    735.895
Name: sequence_1l_428_9_fv1c, dtype: object)
('the mean', array([ 0.06423451]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0642345
Name: sequence_1l_428_9_fv1c, dtype: object)
('the mean', array([ 0.13906763]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.139068
Name: sequence_1k_319_10_fv1c, dtype: object)
('the mean', array([ 0.08822281]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0882228
Name: sequence_1k_319_10_fv1c, dtype: object)
('the mean', array([ 265.63770258]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    265.638
Name: sequence_1k_319_10_fv1c, dtype: object)
('the mean', array([ 0.05121827]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0512183
Name: sequence_1k_319_10_fv1c, dtype: object)
('the mean', array([ 0.13783772]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.137838
Name: sequence_1d_128_9_fv1c, dtype: object)
('the mean', array([ 0.08672909]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.0867291
Name: sequence_1d_128_9_fv1c, dtype: object)
('the mean', array([ 160.91891198]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    160.919
Name: sequence_1d_128_9_fv1c, dtype: object)
('the mean', array([ 0.05177003]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.05177
Name: sequence_1d_128_9_fv1c, dtype: object)
('the mean', array([ 0.2470255]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.247025
Name: sequence_2c_548_9_fv1c, dtype: object)
('the mean', array([ 0.21687922]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.216879
Name: sequence_2c_548_9_fv1c, dtype: object)
('the mean', array([ 943.78345058]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    943.783
Name: sequence_2c_548_9_fv1c, dtype: object)
('the mean', array([ 0.09052161]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0905216
Name: sequence_2c_548_9_fv1c, dtype: object)
('the mean', array([ 0.26622244]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.266222
Name: sequence_3a_707_9_fv1c, dtype: object)
('the mean', array([ 0.3193238]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.319324
Name: sequence_3a_707_9_fv1c, dtype: object)
('the mean', array([ 1223.23202216]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    1223.23
Name: sequence_3a_707_9_fv1c, dtype: object)
('the mean', array([ 0.11407971]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.11408
Name: sequence_3a_707_9_fv1c, dtype: object)
('the mean', array([ 0.18724451]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.187245
Name: sequence_1k_339_10_fv1c, dtype: object)
('the mean', array([ 0.13988158]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.139882
Name: sequence_1k_339_10_fv1c, dtype: object)
('the mean', array([ 409.76589639]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    409.766
Name: sequence_1k_339_10_fv1c, dtype: object)
('the mean', array([ 0.06502356]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0650236
Name: sequence_1k_339_10_fv1c, dtype: object)
('the mean', array([ 0.25748892]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.257489
Name: sequence_1c_109_10_fv1c, dtype: object)
('the mean', array([ 0.23762329]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.237623
Name: sequence_1c_109_10_fv1c, dtype: object)
('the mean', array([ 650.84824992]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    650.848
Name: sequence_1c_109_10_fv1c, dtype: object)
('the mean', array([ 0.09998135]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0999814
Name: sequence_1c_109_10_fv1c, dtype: object)
('the mean', array([ 0.16840536]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mae_avg    0.168405
Name: sequence_1k_359_10_fv1c, dtype: object)
('the mean', array([ 0.12593377]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mse_avg    0.125934
Name: sequence_1k_359_10_fv1c, dtype: object)
('the mean', array([ 257.45536996]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", mape_avg    257.455
Name: sequence_1k_359_10_fv1c, dtype: object)
('the mean', array([ 0.0613139]))
('the type of mean', <class 'pandas.core.series.Series'>)
('the shape of mean', (1,))
("the master df's entry:", msle_avg    0.0613139
Name: sequence_1k_359_10_fv1c, dtype: object)

In [6]:

    

#create a new df: loadseq vs. score
print(master_per_loadseq_df.index)
print(master_per_loadseq_df.columns)
print(master_per_loadseq_df.head(3))


    

    




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)
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'],
      dtype='object')
                           mse_avg    mse_med mse_stdev   mae_avg    mae_med  \
seq_name                                                                       
sequence_2c_539_10_fv1c  0.0853845  0.0110813  0.119663   0.13615  0.0115718   
sequence_2c_538_9_fv1c   0.0856342  0.0104185  0.119506  0.136272  0.0117056   
sequence_2b_469_10_fv1c   0.085796  0.0127771  0.118114  0.136437  0.0119729   

                        mae_stdev mae_normd_dev mape_avg mape_med mape_stdev  \
seq_name                                                                       
sequence_2c_539_10_fv1c  0.180962           NaN  125.079  133.284    42.5061   
sequence_2c_538_9_fv1c   0.180844           NaN  141.869  151.855    43.5794   
sequence_2b_469_10_fv1c  0.180094           NaN   202.93  220.335    59.8742   

                          msle_avg   msle_med msle_stdev  
seq_name                                                  
sequence_2c_539_10_fv1c  0.0488543  0.0413555  0.0162035  
sequence_2c_538_9_fv1c   0.0488358  0.0413871  0.0161879  
sequence_2b_469_10_fv1c  0.0513556  0.0443636  0.0139685  

In [7]:

    

#load the seqname_loadseqlist csv
#print(master)
complete_sn_lsl_df = pd.read_csv(analysis_path + 'complete_seqname_loadseqlist.csv',index_col=0)
complete_sn_lsl_df.index.rename(name='seq_name',inplace=True)
print(complete_sn_lsl_df.index)
print(complete_sn_lsl_df.columns)


    

    




Index([u'sequence_1d_168_9_fv1c', u'sequence_1b_29_10_fv1c',
       u'sequence_1c_119_10_fv1c', u'sequence_1b_8_9_fv1c',
       u'sequence_2c_538_9_fv1c', u'sequence_3a_628_10_fv1c',
       u'sequence_2b_469_10_fv1c', u'sequence_1l_398_9_fv1c',
       u'sequence_1b_49_10_fv1c', u'sequence_3a_687_9_fv1c',
       ...
       u'sequence_1b_38_9_fv1c', u'sequence_1c_68_9_fv1c',
       u'sequence_1d_198_9_fv1c', u'sequence_1k_359_10_fv1c',
       u'sequence_1k_319_10_fv1c', u'sequence_2b_448_9_fv1c',
       u'sequence_1d_229_10_fv1c', u'sequence_1l_428_9_fv1c',
       u'sequence_1d_259_10_fv1c', u'sequence_1l_388_9_fv1c'],
      dtype='object', name=u'seq_name', length=108)
Index([u'loadseq_id', u'loadseq'], dtype='object')

In [8]:

    

#right df is the one described in the cell above. 
seqname_results_loadseq_df = pd.merge(master_per_loadseq_df,complete_sn_lsl_df,how='inner',left_index=True,right_index=True)
print(seqname_results_loadseq_df.head(2))
print(seqname_results_loadseq_df.columns)
print(seqname_results_loadseq_df.index)


    

    




                           mse_avg    mse_med mse_stdev   mae_avg    mae_med  \
seq_name                                                                       
sequence_2c_539_10_fv1c  0.0853845  0.0110813  0.119663   0.13615  0.0115718   
sequence_2c_538_9_fv1c   0.0856342  0.0104185  0.119506  0.136272  0.0117056   

                        mae_stdev mae_normd_dev mape_avg mape_med mape_stdev  \
seq_name                                                                       
sequence_2c_539_10_fv1c  0.180962           NaN  125.079  133.284    42.5061   
sequence_2c_538_9_fv1c   0.180844           NaN  141.869  151.855    43.5794   

                          msle_avg   msle_med msle_stdev  loadseq_id  \
seq_name                                                               
sequence_2c_539_10_fv1c  0.0488543  0.0413555  0.0162035           7   
sequence_2c_538_9_fv1c   0.0488358  0.0413871  0.0161879           7   

                                                                   loadseq  
seq_name                                                                    
sequence_2c_539_10_fv1c  [  1.028  10.28   10.28    0.75    0.75   10.2...  
sequence_2c_538_9_fv1c   [  1.028  10.28   10.28    0.75    0.75   10.2...  
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'loadseq_id', u'loadseq'],
      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 [9]:

    

seqname_results_loadseq_df.to_csv(analysis_path+"seqname_score_loadseq_TEST.csv")


    

In [10]:

    

columns_to_cast = list(seqname_results_loadseq_df.columns)
columns_to_cast.remove('loadseq')
print(columns_to_cast)
#seqname_results_loadseq_df['mae_avg'].astype(dtype='float64',copy=False)
#pd.to_numeric([columns_to_cast])
for colname in columns_to_cast: #for some reason it's all objects...gotta cast to numeric. 
    seqname_results_loadseq_df[str(colname)] = pd.to_numeric(seqname_results_loadseq_df[str(colname)])
for colname in columns_to_cast:
    print("new", colname, seqname_results_loadseq_df[colname].dtype)
grouped_srls_df = seqname_results_loadseq_df.groupby(by=['loadseq']).mean()
#print(grouped_srls_df['mae_avg'].mean())
#print(grouped_srls_df.median())
#grouped.srls.df.reset_index()
print(grouped_srls_df.head(29))
print(type(grouped_srls_df))
#print(type(grouped_srls_df.groups))
#print(grouped_srls_df.head(1))#print(grouped_srls_df.mae_avg)
#print(grouped_srls_df.agg(np.mean))
#for key,value in grouped_srls_df.groups.iteritems():
    #print(value)
#print(grouped_srls_df.head(2))
pd.DataFrame(grouped_srls_df).to_csv(analysis_path+'srls_grouped_by_ls.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', 'loadseq_id']
('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'))
('new', 'loadseq_id', dtype('int64'))
                                                     mse_avg   mse_med  \
loadseq                                                                  
[  1.028  10.28   10.28    0.75    0.75   10.28...  0.085509  0.010750   
[  1.028  11.28   11.28    1.      1.     10.28...  0.163782  0.014373   
[  1.028  12.28   12.28    1.028   1.028  17.28...  0.345708  0.020512   
[  1.028  13.28   13.28    1.25    1.25   13.28...  0.085880  0.011743   
[  1.028  14.28   14.28    0.75    0.75   16.28...  0.217056  0.014098   
[  1.028  15.28   15.28    1.75    1.75   10.28...  0.447455  0.027409   
[  1.428  12.28   12.28    1.428   1.428  16.28...  0.138506  0.014723   
[  1.428  12.28   12.28    1.428   1.428  16.28...  0.237528  0.070841   
[  1.428  12.28   12.28    1.428   1.428  16.28...  0.272257  0.017531   
[  1.428  14.28   14.28    0.5     0.5    16.28...  0.142645  0.018187   
[  1.428  14.28   14.28    0.5     0.5    16.28...  0.222458  0.056894   
[  1.428  14.28   14.28    0.75    0.75   14.28...  0.149765  0.012314   
[  1.428  14.28   14.28    0.75    0.75   14.28...  0.106247  0.012735   
[  1.428  14.28   14.28    0.75    0.75   16.28...  0.260412  0.086551   
[  1.428  14.28   14.28    0.75    0.75   16.28...  0.112827  0.014082   
[  1.428  14.28   14.28    0.75    0.75   16.28...  0.205561  0.014139   
[  1.428  14.28   14.28    1.      1.     14.28...  0.359606  0.162805   
[  1.428  14.28   14.28    1.      1.     14.28...  0.148475  0.013412   
[  1.428  14.28   14.28    1.      1.     14.28...  0.086713  0.012338   
[  1.428  14.28   14.28    1.25    1.25   14.28...  0.181824  0.035411   
[  1.428  14.28   14.28    1.25    1.25   14.28...  0.149082  0.012003   
[  1.428  14.28   14.28    1.25    1.25   14.28...  0.087578  0.012456   
[  1.428  14.28   14.28    1.428   1.428  14.28...  0.226012  0.061017   
[  1.428  14.28   14.28    1.428   1.428  14.28...  0.140494  0.016769   
[  1.428  14.28   14.28    1.75    1.75   14.28...  0.150363  0.011920   
[  1.428  14.28   14.28    1.75    1.75   14.28...  0.149355  0.013395   
[  1.428  14.28   14.28    1.75    1.75   14.28...  0.088064  0.012490   

                                                    mse_stdev   mae_avg  \
loadseq                                                                   
[  1.028  10.28   10.28    0.75    0.75   10.28...   0.119585  0.136211   
[  1.028  11.28   11.28    1.      1.     10.28...   0.200013  0.217175   
[  1.028  12.28   12.28    1.028   1.028  17.28...   0.440522  0.319778   
[  1.028  13.28   13.28    1.25    1.25   13.28...   0.118514  0.136558   
[  1.028  14.28   14.28    0.75    0.75   16.28...   0.271077  0.247080   
[  1.028  15.28   15.28    1.75    1.75   10.28...   0.591137  0.363130   
[  1.428  12.28   12.28    1.428   1.428  16.28...   0.154165  0.185714   
[  1.428  12.28   12.28    1.428   1.428  16.28...   0.340169  0.237145   
[  1.428  12.28   12.28    1.428   1.428  16.28...   0.334893  0.280409   
[  1.428  14.28   14.28    0.5     0.5    16.28...   0.157575  0.186957   
[  1.428  14.28   14.28    0.5     0.5    16.28...   0.343495  0.217258   
[  1.428  14.28   14.28    0.75    0.75   14.28...   0.255456  0.171079   
[  1.428  14.28   14.28    0.75    0.75   14.28...   0.160939  0.147706   
[  1.428  14.28   14.28    0.75    0.75   16.28...   0.357709  0.255782   
[  1.428  14.28   14.28    0.75    0.75   16.28...   0.132264  0.158357   
[  1.428  14.28   14.28    0.75    0.75   16.28...   0.251160  0.234444   
[  1.428  14.28   14.28    1.      1.     14.28...   0.438608  0.319234   
[  1.428  14.28   14.28    1.      1.     14.28...   0.255090  0.170202   
[  1.428  14.28   14.28    1.      1.     14.28...   0.119125  0.136937   
[  1.428  14.28   14.28    1.25    1.25   14.28...   0.267987  0.206757   
[  1.428  14.28   14.28    1.25    1.25   14.28...   0.253943  0.170997   
[  1.428  14.28   14.28    1.25    1.25   14.28...   0.120692  0.137903   
[  1.428  14.28   14.28    1.428   1.428  14.28...   0.340348  0.218079   
[  1.428  14.28   14.28    1.428   1.428  14.28...   0.155887  0.186115   
[  1.428  14.28   14.28    1.75    1.75   14.28...   0.256184  0.172101   
[  1.428  14.28   14.28    1.75    1.75   14.28...   0.254473  0.170966   
[  1.428  14.28   14.28    1.75    1.75   14.28...   0.120922  0.137957   

                                                     mae_med  mae_stdev  \
loadseq                                                                   
[  1.028  10.28   10.28    0.75    0.75   10.28...  0.011639   0.180903   
[  1.028  11.28   11.28    1.      1.     10.28...  0.012915   0.252389   
[  1.028  12.28   12.28    1.028   1.028  17.28...  0.013169   0.372138   
[  1.028  13.28   13.28    1.25    1.25   13.28...  0.012120   0.180482   
[  1.028  14.28   14.28    0.75    0.75   16.28...  0.012088   0.298552   
[  1.028  15.28   15.28    1.75    1.75   10.28...  0.012920   0.424552   
[  1.428  12.28   12.28    1.428   1.428  16.28...  0.012888   0.205412   
[  1.428  12.28   12.28    1.428   1.428  16.28...  0.017193   0.296181   
[  1.428  12.28   12.28    1.428   1.428  16.28...  0.013025   0.321618   
[  1.428  14.28   14.28    0.5     0.5    16.28...  0.012836   0.206196   
[  1.428  14.28   14.28    0.5     0.5    16.28...  0.017656   0.286818   
[  1.428  14.28   14.28    0.75    0.75   14.28...  0.016395   0.247601   
[  1.428  14.28   14.28    0.75    0.75   14.28...  0.013184   0.201558   
[  1.428  14.28   14.28    0.75    0.75   16.28...  0.018748   0.310586   
[  1.428  14.28   14.28    0.75    0.75   16.28...  0.011958   0.183871   
[  1.428  14.28   14.28    0.75    0.75   16.28...  0.012153   0.278089   
[  1.428  14.28   14.28    1.      1.     14.28...  0.023014   0.366923   
[  1.428  14.28   14.28    1.      1.     14.28...  0.015509   0.247873   
[  1.428  14.28   14.28    1.      1.     14.28...  0.012275   0.181010   
[  1.428  14.28   14.28    1.25    1.25   14.28...  0.015239   0.259060   
[  1.428  14.28   14.28    1.25    1.25   14.28...  0.016485   0.247715   
[  1.428  14.28   14.28    1.25    1.25   14.28...  0.012219   0.182079   
[  1.428  14.28   14.28    1.428   1.428  14.28...  0.020387   0.285972   
[  1.428  14.28   14.28    1.428   1.428  14.28...  0.012761   0.205381   
[  1.428  14.28   14.28    1.75    1.75   14.28...  0.016350   0.247427   
[  1.428  14.28   14.28    1.75    1.75   14.28...  0.015946   0.247775   
[  1.428  14.28   14.28    1.75    1.75   14.28...  0.012385   0.182070   

                                                    mae_normd_dev  \
loadseq                                                             
[  1.028  10.28   10.28    0.75    0.75   10.28...            NaN   
[  1.028  11.28   11.28    1.      1.     10.28...            NaN   
[  1.028  12.28   12.28    1.028   1.028  17.28...            NaN   
[  1.028  13.28   13.28    1.25    1.25   13.28...            NaN   
[  1.028  14.28   14.28    0.75    0.75   16.28...            NaN   
[  1.028  15.28   15.28    1.75    1.75   10.28...            NaN   
[  1.428  12.28   12.28    1.428   1.428  16.28...            NaN   
[  1.428  12.28   12.28    1.428   1.428  16.28...            NaN   
[  1.428  12.28   12.28    1.428   1.428  16.28...            NaN   
[  1.428  14.28   14.28    0.5     0.5    16.28...            NaN   
[  1.428  14.28   14.28    0.5     0.5    16.28...            NaN   
[  1.428  14.28   14.28    0.75    0.75   14.28...            NaN   
[  1.428  14.28   14.28    0.75    0.75   14.28...            NaN   
[  1.428  14.28   14.28    0.75    0.75   16.28...            NaN   
[  1.428  14.28   14.28    0.75    0.75   16.28...            NaN   
[  1.428  14.28   14.28    0.75    0.75   16.28...            NaN   
[  1.428  14.28   14.28    1.      1.     14.28...            NaN   
[  1.428  14.28   14.28    1.      1.     14.28...            NaN   
[  1.428  14.28   14.28    1.      1.     14.28...            NaN   
[  1.428  14.28   14.28    1.25    1.25   14.28...            NaN   
[  1.428  14.28   14.28    1.25    1.25   14.28...            NaN   
[  1.428  14.28   14.28    1.25    1.25   14.28...            NaN   
[  1.428  14.28   14.28    1.428   1.428  14.28...            NaN   
[  1.428  14.28   14.28    1.428   1.428  14.28...            NaN   
[  1.428  14.28   14.28    1.75    1.75   14.28...            NaN   
[  1.428  14.28   14.28    1.75    1.75   14.28...            NaN   
[  1.428  14.28   14.28    1.75    1.75   14.28...            NaN   

                                                       mape_avg     mape_med  \
loadseq                                                                        
[  1.028  10.28   10.28    0.75    0.75   10.28...   133.474029   142.569599   
[  1.028  11.28   11.28    1.      1.     10.28...   603.211597   607.994533   
[  1.028  12.28   12.28    1.028   1.028  17.28...   546.647355   555.252961   
[  1.028  13.28   13.28    1.25    1.25   13.28...   142.974429   153.186383   
[  1.028  14.28   14.28    0.75    0.75   16.28...   908.984049   905.131622   
[  1.028  15.28   15.28    1.75    1.75   10.28...  1534.383837  1329.229667   
[  1.428  12.28   12.28    1.428   1.428  16.28...   296.339446   328.577372   
[  1.428  12.28   12.28    1.428   1.428  16.28...   466.757366   467.708316   
[  1.428  12.28   12.28    1.428   1.428  16.28...   588.864774   623.924541   
[  1.428  14.28   14.28    0.5     0.5    16.28...   392.878051   425.721233   
[  1.428  14.28   14.28    0.5     0.5    16.28...   925.261726   920.001704   
[  1.428  14.28   14.28    0.75    0.75   14.28...   268.581918   287.934714   
[  1.428  14.28   14.28    0.75    0.75   14.28...   253.226537   284.611496   
[  1.428  14.28   14.28    0.75    0.75   16.28...   362.992174   376.158606   
[  1.428  14.28   14.28    0.75    0.75   16.28...   258.762485   301.904339   
[  1.428  14.28   14.28    0.75    0.75   16.28...   695.014805   714.588219   
[  1.428  14.28   14.28    1.      1.     14.28...   416.649470   444.221854   
[  1.428  14.28   14.28    1.      1.     14.28...   275.516274   287.139068   
[  1.428  14.28   14.28    1.      1.     14.28...   162.022072   179.528246   
[  1.428  14.28   14.28    1.25    1.25   14.28...   364.288481   365.525074   
[  1.428  14.28   14.28    1.25    1.25   14.28...   260.960822   275.083403   
[  1.428  14.28   14.28    1.25    1.25   14.28...   301.195916   343.946146   
[  1.428  14.28   14.28    1.428   1.428  14.28...   562.835380   605.861836   
[  1.428  14.28   14.28    1.428   1.428  14.28...   650.521378   725.983365   
[  1.428  14.28   14.28    1.75    1.75   14.28...   254.523603   266.804301   
[  1.428  14.28   14.28    1.75    1.75   14.28...   450.203843   389.316627   
[  1.428  14.28   14.28    1.75    1.75   14.28...   227.421352   254.767555   

                                                    mape_stdev  msle_avg  \
loadseq                                                                    
[  1.028  10.28   10.28    0.75    0.75   10.28...   43.042738  0.048845   
[  1.028  11.28   11.28    1.      1.     10.28...   28.246519  0.071674   
[  1.028  12.28   12.28    1.028   1.028  17.28...   46.373630  0.114994   
[  1.028  13.28   13.28    1.25    1.25   13.28...   44.314852  0.050327   
[  1.028  14.28   14.28    0.75    0.75   16.28...  146.344260  0.090536   
[  1.028  15.28   15.28    1.75    1.75   10.28...  414.120119  0.144994   
[  1.428  12.28   12.28    1.428   1.428  16.28...   76.645253  0.062219   
[  1.428  12.28   12.28    1.428   1.428  16.28...  174.384476  0.087292   
[  1.428  12.28   12.28    1.428   1.428  16.28...   90.079300  0.101408   
[  1.428  14.28   14.28    0.5     0.5    16.28...  115.248317  0.064968   
[  1.428  14.28   14.28    0.5     0.5    16.28...  167.311983  0.087660   
[  1.428  14.28   14.28    0.75    0.75   14.28...  116.261520  0.065966   
[  1.428  14.28   14.28    0.75    0.75   14.28...   94.995660  0.056379   
[  1.428  14.28   14.28    0.75    0.75   16.28...   93.781732  0.089944   
[  1.428  14.28   14.28    0.75    0.75   16.28...   93.442610  0.058834   
[  1.428  14.28   14.28    0.75    0.75   16.28...  100.833339  0.090516   
[  1.428  14.28   14.28    1.      1.     14.28...  107.908353  0.087261   
[  1.428  14.28   14.28    1.      1.     14.28...  127.294349  0.066097   
[  1.428  14.28   14.28    1.      1.     14.28...   55.236713  0.050862   
[  1.428  14.28   14.28    1.25    1.25   14.28...   97.834405  0.068425   
[  1.428  14.28   14.28    1.25    1.25   14.28...  110.454441  0.066550   
[  1.428  14.28   14.28    1.25    1.25   14.28...  113.977671  0.053941   
[  1.428  14.28   14.28    1.428   1.428  14.28...  202.694979  0.088272   
[  1.428  14.28   14.28    1.428   1.428  14.28...  194.269713  0.064247   
[  1.428  14.28   14.28    1.75    1.75   14.28...   92.259076  0.066311   
[  1.428  14.28   14.28    1.75    1.75   14.28...  219.607763  0.066097   
[  1.428  14.28   14.28    1.75    1.75   14.28...   73.125272  0.054241   

                                                    msle_med  msle_stdev  \
loadseq                                                                    
[  1.028  10.28   10.28    0.75    0.75   10.28...  0.041371    0.016196   
[  1.028  11.28   11.28    1.      1.     10.28...  0.069191    0.007333   
[  1.028  12.28   12.28    1.028   1.028  17.28...  0.117387    0.024513   
[  1.028  13.28   13.28    1.25    1.25   13.28...  0.042776    0.015487   
[  1.028  14.28   14.28    0.75    0.75   16.28...  0.088636    0.015990   
[  1.028  15.28   15.28    1.75    1.75   10.28...  0.149381    0.028196   
[  1.428  12.28   12.28    1.428   1.428  16.28...  0.064568    0.009128   
[  1.428  12.28   12.28    1.428   1.428  16.28...  0.076226    0.022587   
[  1.428  12.28   12.28    1.428   1.428  16.28...  0.100229    0.022241   
[  1.428  14.28   14.28    0.5     0.5    16.28...  0.065037    0.009962   
[  1.428  14.28   14.28    0.5     0.5    16.28...  0.083880    0.023365   
[  1.428  14.28   14.28    0.75    0.75   14.28...  0.059816    0.017776   
[  1.428  14.28   14.28    0.75    0.75   14.28...  0.050007    0.014295   
[  1.428  14.28   14.28    0.75    0.75   16.28...  0.083357    0.023461   
[  1.428  14.28   14.28    0.75    0.75   16.28...  0.061258    0.008375   
[  1.428  14.28   14.28    0.75    0.75   16.28...  0.090201    0.014395   
[  1.428  14.28   14.28    1.      1.     14.28...  0.088998    0.019196   
[  1.428  14.28   14.28    1.      1.     14.28...  0.059968    0.018370   
[  1.428  14.28   14.28    1.      1.     14.28...  0.043710    0.014597   
[  1.428  14.28   14.28    1.25    1.25   14.28...  0.065168    0.016214   
[  1.428  14.28   14.28    1.25    1.25   14.28...  0.060192    0.018215   
[  1.428  14.28   14.28    1.25    1.25   14.28...  0.046983    0.013795   
[  1.428  14.28   14.28    1.428   1.428  14.28...  0.084330    0.023400   
[  1.428  14.28   14.28    1.428   1.428  14.28...  0.064140    0.009891   
[  1.428  14.28   14.28    1.75    1.75   14.28...  0.060016    0.017571   
[  1.428  14.28   14.28    1.75    1.75   14.28...  0.059983    0.017977   
[  1.428  14.28   14.28    1.75    1.75   14.28...  0.047649    0.012854   

                                                    loadseq_id  
loadseq                                                         
[  1.028  10.28   10.28    0.75    0.75   10.28...           7  
[  1.028  11.28   11.28    1.      1.     10.28...           9  
[  1.028  12.28   12.28    1.028   1.028  17.28...           5  
[  1.028  13.28   13.28    1.25    1.25   13.28...          11  
[  1.028  14.28   14.28    0.75    0.75   16.28...           2  
[  1.028  15.28   15.28    1.75    1.75   10.28...          10  
[  1.428  12.28   12.28    1.428   1.428  16.28...          12  
[  1.428  12.28   12.28    1.428   1.428  16.28...          21  
[  1.428  12.28   12.28    1.428   1.428  16.28...           3  
[  1.428  14.28   14.28    0.5     0.5    16.28...          24  
[  1.428  14.28   14.28    0.5     0.5    16.28...          16  
[  1.428  14.28   14.28    0.75    0.75   14.28...          13  
[  1.428  14.28   14.28    0.75    0.75   14.28...           8  
[  1.428  14.28   14.28    0.75    0.75   16.28...          18  
[  1.428  14.28   14.28    0.75    0.75   16.28...          22  
[  1.428  14.28   14.28    0.75    0.75   16.28...           1  
[  1.428  14.28   14.28    1.      1.     14.28...          20  
[  1.428  14.28   14.28    1.      1.     14.28...          19  
[  1.428  14.28   14.28    1.      1.     14.28...           6  
[  1.428  14.28   14.28    1.25    1.25   14.28...          17  
[  1.428  14.28   14.28    1.25    1.25   14.28...          25  
[  1.428  14.28   14.28    1.25    1.25   14.28...           4  
[  1.428  14.28   14.28    1.428   1.428  14.28...          23  
[  1.428  14.28   14.28    1.428   1.428  14.28...          14  
[  1.428  14.28   14.28    1.75    1.75   14.28...          15  
[  1.428  14.28   14.28    1.75    1.75   14.28...          26  
[  1.428  14.28   14.28    1.75    1.75   14.28...           0  
<class 'pandas.core.frame.DataFrame'>

In [11]:

    

grouped_srls_count_df = seqname_results_loadseq_df.groupby(by=['loadseq']).count()
pd.DataFrame(grouped_srls_count_df).to_csv(analysis_path+'srls_grouped_by_ls_count.csv')


    

In [12]:

    

#group by initial conditions.