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'''
Takes a positional data set (time, x, y, z) and applies the Savintzky Golay filter on it based on the
polynomial and window parameters we input
'''
from math import *
import numpy as np
import sys
import os
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), os.path.pardir)))
from scipy.signal import savgol_filter
from util import read_data
def golay(data, window, degree):
'''
Apply the Savintzky-Golay filter to a positional data set.
Args:
data (numpy array): containing all of the positional data in the format of (time, x, y, z)
window (int): window size of the Savintzky-Golay filter
degree (int): degree of the polynomial in Savintzky-Golay filter
Returns:
numpy array: filtered data in the same format
'''
x = data[:, 1]
y = data[:, 2]
z = data[:, 3]
x_new = savgol_filter(x, window, degree)
y_new = savgol_filter(y, window, degree)
z_new = savgol_filter(z, window, degree)
new_positions = np.zeros((len(data), 4))
new_positions[:, 1] = x_new
new_positions[:, 2] = y_new
new_positions[:, 3] = z_new
new_positions[:, 0] = data[:, 0]
return new_positions
#
# if __name__ == "__main__":
#
# pd.set_option('display.width', 1000)
# my_data = read_data.load_data('orbit.csv')
# window = 21 # its better to select it as the len(data)/3 and it needs to be an odd number
# degree = 6
# positions_filtered = golay(my_data, window, degree)
# print(positions_filtered - my_data)
#