Lars Bogner
30 lines
701 B
Python
30 lines
701 B
Python
# %%
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import torch
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import torch.nn.functional as F
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import pandas as pd
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import numpy as np
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from aiRNN import preprocessors
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# %%
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df = pd.read_csv("../all_second_lines.csv", header=None, names=["icao", "r", "t", "timestamp", "lat", "lon", "alt", "ias"])
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_ = preprocessors.create_category_mappings(df)
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# %%
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df = preprocessors.map_categories(df, _)
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# %%
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X_a_1 = F.one_hot(torch.tensor(df["R_1_IDX"].values)).float()
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X_a_2 = F.one_hot(torch.tensor(df["R_2_IDX"].values)).float()
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X_t = F.one_hot(torch.tensor(df["T_IDX"].values)).float()
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# %%
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print(X_a_1.shape, X_a_2.shape, X_t.shape)
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# %%
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preprocessors.train_autoencoder(X_a_1=X_a_1, X_a_2=X_a_2, X_b=X_t, num_epochs=500, learning_rate=0.011)
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# %%
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