remove price utils & small bugfixes

Merge pull request #43 from auto-trading-temp-name/fixed-lot-of-things

algorithms/bollinger_bands.py

@@ -1,15 +1,9 @@
 from talib import BBANDS
-from price import get_periods, get_max_periods
 import matplotlib.pyplot as plt
 import plots.colors as colors
 
-def algorithm(prices, window_size=(20, 'days'), standard_deviations=2):
-	periods = get_periods(*window_size)
-
-	if get_max_periods() < periods:
-		raise Exception(f'Not Enough Datapoints for this Interval')
-
-	return BBANDS(prices, timeperiod=periods, nbdevup=standard_deviations, nbdevdn=standard_deviations)
+def algorithm(prices, window_size=20, standard_deviations=2):
+	return BBANDS(prices, timeperiod=window_size, nbdevup=standard_deviations, nbdevdn=standard_deviations)
 
 def signal(prices, data):
 	upper_band, middle_band, lower_band = data
@@ -22,7 +16,7 @@ def signal(prices, data):
 	return 'no_action', 0
 
 def plot(prices, timestamps, **kwargs):
-	upper_band, middle_band, lower_band = algorithm(prices, window_size=(20, 'days'), **kwargs)
+	upper_band, middle_band, lower_band = algorithm(prices, **kwargs)
 
 	plt.fill_between(timestamps, upper_band, lower_band, color='grey', alpha=0.3)
 

algorithms/custom_bollinger_rsi.py

@@ -6,7 +6,7 @@
 from algorithms.rsi import plot as rsi_plot
 from algorithms.bollinger_bands import plot as bollinger_bands_plot
 
-def algorithm(prices, window_size_rsi=(13, 'days'), window_size_bollinger_bands=(1, 'month')):
+def algorithm(prices, window_size_rsi=13, window_size_bollinger_bands=30):
 	bb_data = bollinger_bands(prices, window_size=window_size_bollinger_bands)
 	rsi_line = rsi(prices, window_size=window_size_rsi)
 
@@ -16,7 +16,7 @@ def signal(prices, data):
 	price = prices[-1]
 	upper_band, lower_band, middle_band, rsi_line = data
 
-	if price >= lower_band[-1] and 30 >= rsi_line[-1]:
+	if lower_band[-1] >= price and 30 >= rsi_line[-1]:
 		return 'buy', 0.5
 
 	if price >= upper_band[-1] and rsi_line[-1] >= 70:
@@ -34,7 +34,7 @@ def plot(prices, timestamps, **kwargs):
 	sliced_prices = prices[:min(upper_band.shape[0], rsi_line.shape[0])]
 
 	upper_condition = (prices >= upper_band) & (rsi_line >= 70)
-	lower_condition = (prices >= lower_band) & (30 >= rsi_line)
+	lower_condition = (lower_band >= prices) & (30 >= rsi_line)
 	plt.scatter(timestamps[upper_condition], sliced_prices[upper_condition], color=colors.upper())
 	plt.scatter(timestamps[lower_condition], sliced_prices[lower_condition], color=colors.lower())
 

algorithms/rsi.py

@@ -1,16 +1,10 @@
 from talib import RSI
-from price import get_periods, get_max_periods
 import numpy as np
 import matplotlib.pyplot as plt
 import plots.colors as colors
 
-def algorithm(prices, window_size=(14, 'days')):
-	periods = get_periods(*window_size)
-
-	if get_max_periods() < periods:
-		raise Exception(f'Not Enough Datapoints for this Interval')
-
-	return RSI(prices, timeperiod=get_periods(*window_size))
+def algorithm(prices, window_size=14):
+	return RSI(prices, timeperiod=window_size)
 
 def signal(prices, data, high=70, low=30):
 	rsi = data

price.py

@@ -74,30 +74,6 @@ def get_cached_prices(interval='default'):
 
 	return np.array(prices).astype(float), np.array(timestamps).astype(float), float(last_complete_point)
 
-def get_periods(period_size, period_type, interval='default'):
-	if interval == 'default':
-		interval = get_default_interval()
-
-	if 'month' in period_type:
-		period_multiplier = 30 * 24 * 60
-	elif 'week' in period_type:
-		period_multiplier = 7 * 24 * 60
-	elif 'day' in period_type:
-		period_multiplier = 24 * 60
-	elif 'hour' in period_type:
-		period_multiplier = 60
-	elif 'minute' in period_type:
-		period_multiplier = 1
-	period_seconds = period_size * period_multiplier
-
-	return ceil(period_seconds / interval)
-
-def get_max_periods(interval='default'):
-	if interval == 'default':
-		interval = get_default_interval()
-
-	return ceil(point_count * interval)
-
 # Price Caching
 def update_cached_prices():
 	for interval in cached_intervals: