A support and resistence line sample

supres.py

import numpy as np

def supres(ltp, n):
    """
    This function takes a numpy array of last traded price
    and returns a list of support and resistance levels 
    respectively. n is the number of entries to be scanned.
    """
    from scipy.signal import savgol_filter as smooth

    # converting n to a nearest even number
    if n%2 != 0:
        n += 1
    
    n_ltp = ltp.shape[0] # length of ltp

    # smoothening the curve
    # scipy.signal.savgol_filter(x, window_length, polyorder, deriv=0, delta=1.0, axis=- 1, mode='interp', cval=0.0)
    # window_lengthint
    #   The length of the filter window (i.e., the number of coefficients).
    # polyorderint
    #   The order of the polynomial used to fit the samples.
    ltp_s = smooth(ltp, (n+1), 3) # the polynomial is 3 in this sample
    print('length of ltp_s: {}'.format(len(ltp_s)))

    # taking a simple derivative
    ltp_d = np.zeros(n_ltp)
    ltp_d[1:] = np.subtract(ltp_s[1:], ltp_s[:-1])
    print('length of ltp_d: {}'.format(len(ltp_d)))
 
    resistance = []
    support = []
    
    for i in range(n_ltp - n):
        arr_sl = ltp_d[i:(i+n)]
        first = arr_sl[:int((n/2))] # first half
        last = arr_sl[int((n/2)):] # second half
        
        r_1 = np.sum(first > 0)
        r_2 = np.sum(last < 0)

        s_1 = np.sum(first < 0)
        s_2 = np.sum(last > 0)

        # local maxima detection
        if (r_1 == (n/2)) and (r_2 == (n/2)): 
            resistance.append(ltp[i+(int(n/2)-1)])

        # local minima detection
        if (s_1 == (n/2)) and (s_2 == (n/2)): 
            support.append(ltp[i+(int(n/2)-1)])

    return support, resistance