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Calculate SMA and EMA in Python
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| # | |
| # See how to use this script and what type of input to use at: | |
| # https://steemit.com/cryptocurrency/@jwyles/moving-averages-sma-ema-how-to-use-and-how-to-calculate-with-spreadsheet-and-code-snippets | |
| # | |
| import csv | |
| import re | |
| from functools import reduce | |
| from dateutil import parser | |
| CSV_FILE = 'input.csv' | |
| EMA_LENGTH = 5 | |
| EMA_SOURCE = 'close' | |
| candles = [] | |
| # Reads the input file and saves to `candles` all the candles found. Each candle is | |
| # a dict with the timestamp and the OHLC values. | |
| def read_candles(): | |
| with open(CSV_FILE, 'r') as csvfile: | |
| reader = csv.reader(csvfile, delimiter=',') | |
| for row in reader: | |
| try: | |
| candles.append({ | |
| 'ts': parser.parse(row[0]), | |
| 'low': float(re.sub(",", "", row[1])), | |
| 'high': float(re.sub(",", "", row[2])), | |
| 'open': float(re.sub(",", "", row[3])), | |
| 'close': float(re.sub(",", "", row[4])) | |
| }) | |
| except: | |
| print('Error parsing {}'.format(row)) | |
| # Calculates the SMA of an array of candles using the `source` price. | |
| def calculate_sma(candles, source): | |
| length = len(candles) | |
| sum = reduce((lambda last, x: { source: last[source] + x[source] }), candles) | |
| sma = sum[source] / length | |
| return sma | |
| # Calculates the EMA of an array of candles using the `source` price. | |
| def calculate_ema(candles, source): | |
| length = len(candles) | |
| target = candles[0] | |
| previous = candles[1] | |
| # if there is no previous EMA calculated, then EMA=SMA | |
| if 'ema' not in previous or previous['ema'] == None: | |
| return calculate_sma(candles, source) | |
| else: | |
| # multiplier: (2 / (length + 1)) | |
| # EMA: (close - EMA(previous)) x multiplier + EMA(previous) | |
| multiplier = 2 / (length + 1) | |
| ema = (target[source] * multiplier) + (previous['ema'] * (1 - multiplier)) | |
| # Formula updated from the original one to be clearer, both give the same results. Old formula: | |
| # ema = ((target[source] - previous['ema']) * multiplier) + previous['ema'] | |
| return ema | |
| def calculate(candles, source): | |
| sma = calculate_sma(candles, source) | |
| ema = calculate_ema(candles, source) | |
| candles[0]['sma'] = sma | |
| candles[0]['ema'] = ema | |
| if __name__ == '__main__': | |
| read_candles() | |
| # progress through the array of candles to calculate the indicators for each | |
| # block of candles | |
| position = 0 | |
| while position + EMA_LENGTH <= len(candles): | |
| current_candles = candles[position:(position+EMA_LENGTH)] | |
| current_candles = list(reversed(current_candles)) | |
| calculate(current_candles, EMA_SOURCE) | |
| position += 1 | |
| for candle in candles: | |
| if 'sma' in candle: | |
| print('{}: sma={} ema={}'.format(candle['ts'], candle['sma'], candle['ema'])) |
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