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cosmetic: rename interval, tick_interval, etc --> ticker_interval

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This commit is contained in:
hroff-1902
2019-04-07 16:14:40 +03:00
parent d6d16b4696
commit ebf1126351
9 changed files with 83 additions and 83 deletions
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16
scripts/plot_profit.py
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@@ -76,7 +76,7 @@ def plot_profit(args: Namespace) -> None:
in helping out to find a good algorithm.
"""
# We need to use the same pairs, same tick_interval
# We need to use the same pairs, same ticker_interval
# and same timeperiod as used in backtesting
# to match the tickerdata against the profits-results
timerange = Arguments.parse_timerange(args.timerange)
@@ -112,7 +112,7 @@ def plot_profit(args: Namespace) -> None:
else:
filter_pairs = config['exchange']['pair_whitelist']
tick_interval = strategy.ticker_interval
ticker_interval = strategy.ticker_interval
pairs = config['exchange']['pair_whitelist']
if filter_pairs:
@@ -122,7 +122,7 @@ def plot_profit(args: Namespace) -> None:
tickers = history.load_data(
datadir=Path(str(config.get('datadir'))),
pairs=pairs,
ticker_interval=tick_interval,
ticker_interval=ticker_interval,
refresh_pairs=False,
timerange=timerange
)
@@ -134,7 +134,7 @@ def plot_profit(args: Namespace) -> None:
dates = common_datearray(dataframes)
min_date = int(min(dates).timestamp())
max_date = int(max(dates).timestamp())
num_iterations = define_index(min_date, max_date, tick_interval) + 1
num_iterations = define_index(min_date, max_date, ticker_interval) + 1
# Make an average close price of all the pairs that was involved.
# this could be useful to gauge the overall market trend
@@ -154,7 +154,7 @@ def plot_profit(args: Namespace) -> None:
avgclose /= num
# make an profits-growth array
pg = make_profit_array(data, num_iterations, min_date, tick_interval, filter_pairs)
pg = make_profit_array(data, num_iterations, min_date, ticker_interval, filter_pairs)
#
# Plot the pairs average close prices, and total profit growth
@@ -178,7 +178,7 @@ def plot_profit(args: Namespace) -> None:
fig.append_trace(profit, 2, 1)
for pair in pairs:
pg = make_profit_array(data, num_iterations, min_date, tick_interval, [pair])
pg = make_profit_array(data, num_iterations, min_date, ticker_interval, [pair])
pair_profit = go.Scattergl(
x=dates,
y=pg,
@@ -189,11 +189,11 @@ def plot_profit(args: Namespace) -> None:
plot(fig, filename=str(Path('user_data').joinpath('freqtrade-profit-plot.html')))
def define_index(min_date: int, max_date: int, interval: str) -> int:
def define_index(min_date: int, max_date: int, ticker_interval: str) -> int:
"""
Return the index of a specific date
"""
interval_seconds = timeframe_to_seconds(interval)
interval_seconds = timeframe_to_seconds(ticker_interval)
return int((max_date - min_date) / interval_seconds)