import yfinance as yf
import datetime
import matplotlib.pylab as pl
import numpy as np
from scipy import stats

def get_ticker(symbol, startDate = datetime.datetime(2022, 2, 1), endDate = datetime.datetime(2022, 2, 8)):

    ticker = yf.Ticker(symbol)
    data = ticker.history(start=startDate, end=endDate, interval="1m")
    return data

def get_gap_p(name):

    delta = datetime.timedelta(days=1)
    num_days = 40
    start_week = datetime.datetime(2022, 2, 7)

    date_list = [start_week - datetime.timedelta(days=x) for x in reversed(range(num_days))]

    start_date_list = []
    gap_p = []

    for date in date_list:
        try:
            ticker_data = get_ticker(name, startDate=date, endDate=date+delta)

            high = np.array(ticker_data['High'])
            low = np.array(ticker_data['Low'])

            count_gap = 0
            count_not_gap = 0
            for i in range(high.shape[0])[:-1]:

                gap_found = False
                if high[i+1] < low[i] and low[i+1] < low[i]:

                    count_gap += 1
                    gap_found = True

                if high[i+1] > high[i] and low[i+1] > high[i]:

                    count_gap += 1
                    gap_found = True

                if not gap_found:

                    count_not_gap += 1

            if count_gap+count_not_gap > 0:
                gap_p.append(count_gap/(count_gap+count_not_gap)*100)
                start_date_list.append(date)
        except:
            pass

    return [start_date_list, gap_p]



fig, ax1 = pl.subplots()




ax1.set_title('Percentage of gaps in 1 minute candles')
ax1.set_xlabel('date')
ax1.set_ylabel('Percentage of gaps (%)')

color = 'tab:red'
start_date_list, gap_p = get_gap_p('GME')
ax1.plot(start_date_list, gap_p,'x-', color=color, label='GME')

color = 'tab:orange'
start_date_list, gap_p = get_gap_p('TSLA')
ax1.plot(start_date_list, gap_p,'o-', color=color, label='TSLA')

color = 'tab:blue'
start_date_list, gap_p = get_gap_p('AAPL')
ax1.plot(start_date_list, gap_p,'o-', color=color, label='AAPL')


ax1.legend()
fig.tight_layout()
pl.show()