81 lines
2.5 KiB
Python
Executable File
81 lines
2.5 KiB
Python
Executable File
import pandas as pd
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import numpy as np
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import os
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from statsmodels.tsa.stattools import adfuller
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from arch.unitroot import ADF
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def calculate_ADF(root_path, data_path):
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df_raw = pd.read_csv(os.path.join(root_path, data_path))
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cols = list(df_raw.columns)
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cols.remove("date")
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df_raw = df_raw[cols]
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adf_list = []
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for i in cols:
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df_data = df_raw[i]
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adf = adfuller(df_data, maxlag=1)
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print(adf)
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adf_list.append(adf)
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return np.array(adf_list)
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def calculate_target_ADF(root_path, data_path, target="OT"):
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df_raw = pd.read_csv(os.path.join(root_path, data_path))
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target_cols = target.split(",")
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# df_data = df_raw[target]
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df_raw = df_raw[target_cols]
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adf_list = []
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for i in target_cols:
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df_data = df_raw[i]
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adf = adfuller(df_data, maxlag=1)
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# print(adf)
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adf_list.append(adf)
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return np.array(adf_list)
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def archADF(root_path, data_path):
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df = pd.read_csv(os.path.join(root_path, data_path))
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cols = df.columns[1:]
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stats = 0
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for target_col in cols:
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series = df[target_col].values
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adf = ADF(series)
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stat = adf.stat
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stats += stat
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return stats / len(cols)
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if __name__ == "__main__":
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# * Exchange - result: -1.902402344564288 | report: -1.889
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ADFmetric = archADF(
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root_path="./dataset/exchange_rate/", data_path="exchange_rate.csv"
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)
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print("Exchange ADF metric", ADFmetric)
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# * Illness - result: -5.33416661870624 | report: -5.406
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ADFmetric = archADF(
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root_path="./dataset/illness/", data_path="national_illness.csv"
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)
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print("Illness ADF metric", ADFmetric)
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# * ETTm2 - result: -5.663628743471695 | report: -6.225
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ADFmetric = archADF(root_path="./dataset/ETT-small/", data_path="ETTm2.csv")
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print("ETTm2 ADF metric", ADFmetric)
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# * Electricity - result: -8.44485821939281 | report: -8.483
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ADFmetric = archADF(root_path="./dataset/electricity/", data_path="electricity.csv")
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print("Electricity ADF metric", ADFmetric)
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# * Traffic - result: -15.020978067839014 | report: -15.046
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ADFmetric = archADF(root_path="./dataset/traffic/", data_path="traffic.csv")
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print("Traffic ADF metric", ADFmetric)
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# * Weather - result: -26.681433085204866 | report: -26.661
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ADFmetric = archADF(root_path="./dataset/weather/", data_path="weather.csv")
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print("Weather ADF metric", ADFmetric)
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# print(ADFmetric)
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# mean_ADFmetric = ADFmetric[:,0].mean()
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# print(mean_ADFmetric)
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