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from planet4 import io
db = io.DBManager()
data = db.get_all()


    

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from sklearn import preprocessing


    

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le = preprocessing.LabelEncoder()


    

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le.fit(data.user_name)


    

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len(le.classes_)


    

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data.user_name = le.transform(data.user_name)


    

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le.transform(data.tail().user_name)


    

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import pickle


    

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folder = Path('/Users/klay6683/Dropbox/data/planet4/P4_catalog_v1.0')
fname = folder / 'P4_catalog_v1.0_username_encoder.pkl'
with open(fname, 'wb') as f:
    pickle.dump(le, f)


    

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from planet4 import reduction


    

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# storing new database
fname = folder / 'P4_catalog_v1.0_raw_classifications.hdf'
data.to_hdf(fname, 'df', format='t', data_columns=reduction.data_columns)


    

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with open('name_encoder.pkl', 'rb') as f:
    le = pickle.load(f)


    

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le = pickle.load


    

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le.inverse_transform(np.array([15, 15, 49, 16, 53]))


    

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np.argwhere(le.classes_=='Vincep1')


    

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