Use timeframe from within strategy
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@@ -27,7 +27,7 @@ from tests.optimize import (BTContainer, BTrade, _build_backtest_dataframe,
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####################################################################
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tests_start_time = arrow.get(2018, 10, 3)
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ticker_interval_in_minute = 60
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timeframe_in_minute = 60
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_ohlc = {'date': 0, 'buy': 1, 'open': 2, 'high': 3, 'low': 4, 'close': 5, 'sell': 6, 'volume': 7}
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# Helpers for this test file
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@@ -49,7 +49,7 @@ def _build_dataframe(buy_ohlc_sell_matrice):
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'date': tests_start_time.shift(
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minutes=(
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ohlc[0] *
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ticker_interval_in_minute)).timestamp *
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timeframe_in_minute)).timestamp *
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1000,
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'buy': ohlc[1],
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'open': ohlc[2],
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@@ -70,7 +70,7 @@ def _build_dataframe(buy_ohlc_sell_matrice):
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def _time_on_candle(number):
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return np.datetime64(tests_start_time.shift(
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minutes=(number * ticker_interval_in_minute)).timestamp * 1000, 'ms')
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minutes=(number * timeframe_in_minute)).timestamp * 1000, 'ms')
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# End helper functions
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@@ -262,7 +262,7 @@ def mocked_load_data(datadir, pairs=[], timeframe='0m',
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NEOBTC = [
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[
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tests_start_time.shift(minutes=(x * ticker_interval_in_minute)).timestamp * 1000,
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tests_start_time.shift(minutes=(x * timeframe_in_minute)).timestamp * 1000,
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math.sin(x * hz) / 1000 + base,
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math.sin(x * hz) / 1000 + base + 0.0001,
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math.sin(x * hz) / 1000 + base - 0.0001,
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@@ -274,7 +274,7 @@ def mocked_load_data(datadir, pairs=[], timeframe='0m',
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base = 0.002
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LTCBTC = [
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[
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tests_start_time.shift(minutes=(x * ticker_interval_in_minute)).timestamp * 1000,
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tests_start_time.shift(minutes=(x * timeframe_in_minute)).timestamp * 1000,
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math.sin(x * hz) / 1000 + base,
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math.sin(x * hz) / 1000 + base + 0.0001,
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math.sin(x * hz) / 1000 + base - 0.0001,
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