def _analyse_pattern(self, pattern, macd_hist, zero_crossing_indexes, price_weight,
pattern_move_time, sign_multiplier):
# add pattern's strength
weight = price_weight * PatternAnalyser.get_pattern_strength(pattern)
average_pattern_period = 0.7
if len(zero_crossing_indexes) > 1:
# compute chances to be after average pattern period
patterns = [PatternAnalyser.get_pattern(
macd_hist[zero_crossing_indexes[i]:zero_crossing_indexes[i + 1]])
for i in range(len(zero_crossing_indexes) - 1)
]
if 0 != zero_crossing_indexes[0]:
patterns.append(PatternAnalyser.get_pattern(macd_hist[0:zero_crossing_indexes[0]]))
if len(macd_hist) - 1 != zero_crossing_indexes[-1]:
patterns.append(PatternAnalyser.get_pattern(macd_hist[zero_crossing_indexes[-1]:]))
double_patterns_count = patterns.count("W") + patterns.count("M")
average_pattern_period = TrendAnalysis. \
get_estimation_of_move_state_relatively_to_previous_moves_length(
zero_crossing_indexes,
macd_hist,
pattern_move_time,
double_patterns_count)
# if we have few data but wave is growing => set higher value
if len(zero_crossing_indexes) <= 1 and price_weight == 1:
if self.previous_note is not None:
average_pattern_period = 0.95
self.previous_note = sign_multiplier * weight * average_pattern_period
else:
self.previous_note = None
self.eval_note = sign_multiplier * weight * average_pattern_period
def eval_impl(self):
self.eval_note = START_PENDING_EVAL_NOTE
long_period_length = 26
if len(self.data[PriceIndexes.IND_PRICE_CLOSE.value]) >= long_period_length:
macd, macd_signal, macd_hist = tulipy.macd(self.data[PriceIndexes.IND_PRICE_CLOSE.value], 12,
long_period_length, 9)
# on macd hist => M pattern: bearish movement, W pattern: bullish movement
# max on hist: optimal sell or buy
macd_hist = DataUtil.drop_nan(macd_hist)
zero_crossing_indexes = TrendAnalysis.get_threshold_change_indexes(macd_hist, 0)
last_index = len(macd_hist) - 1
pattern, start_index, end_index = PatternAnalyser.find_pattern(macd_hist, zero_crossing_indexes,
last_index)
if pattern != PatternAnalyser.UNKNOWN_PATTERN:
# set sign (-1 buy or 1 sell)
sign_multiplier = -1 if pattern == "W" or pattern == "V" else 1
# set pattern time frame => W and M are on 2 time frames, others 1
pattern_move_time = 2 if (pattern == "W" or pattern == "M") and end_index == last_index else 1
# set weight according to the max value of the pattern and the current value
current_pattern_start = start_index
price_weight = macd_hist[-1] / macd_hist[current_pattern_start:].max() if sign_multiplier == 1 \
else macd_hist[-1] / macd_hist[current_pattern_start:].min()
if not math.isnan(price_weight):
self._analyse_pattern(pattern, macd_hist, zero_crossing_indexes, price_weight,
pattern_move_time, sign_multiplier)