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import pandas as pd
from keras.utils import np_utils
import numpy as np
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houmath = pd.read_csv("../HouMath/Prediction6.csv", delimiter=",")
houmath_f1 = 0.63
houmath_facies = np_utils.to_categorical(houmath["Facies"]-1, nb_classes=9)
ar4 = pd.read_csv("../ar4/ar4_predicted_facies_submission002.csv", delimiter=",")
ar4_f1 = 0.606
ar4_facies = np_utils.to_categorical(ar4["Facies"]-1, nb_classes=9)
bestagini = pd.read_csv("../ispl/well_data_with_facies_try02.csv", delimiter=",")
bestagini_f1 = 0.604
bestagini_facies = np_utils.to_categorical(bestagini["Facies"]-1, nb_classes=9)
birdteam = pd.read_csv("../Bird_Team/XmasPreds_4.csv", delimiter=",")
birdteam_f1 = 0.598
birdteam_facies = np_utils.to_categorical(birdteam["Facies"]-1, nb_classes=9)
sum_f1 = ar4_f1+bestagini_f1+houmath_f1+birdteam_f1
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print( houmath.head())
print( ar4.head())
print( bestagini.head())
print( birdteam.head())
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meta_facies = (bestagini_f1*bestagini_facies + ar4_f1*ar4_facies
+ birdteam_f1*bestagini_facies + houmath_f1*houmath_facies)/(sum_f1)
print(meta_facies)
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metasubmission = np.argmax(meta_facies, axis=1) + 1
print (metasubmission)
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test_data = pd.read_csv("../validation_data_nofacies.csv", delimiter=",")
print(test_data.head())
test_data["Facies"] = metasubmission
test_data.to_csv("the_meta_submission.csv")
print(test_data.head())
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