From 3f9ab0846d6b5197094fddb50f15c5fdfe409688 Mon Sep 17 00:00:00 2001 From: Matthias Date: Sun, 7 Jun 2020 15:17:35 +0200 Subject: [PATCH] Rename profitperc to profit_percent --- freqtrade/data/btanalysis.py | 15 ++++++++------- freqtrade/plot/plotting.py | 14 +++++++------- tests/data/test_btanalysis.py | 2 +- tests/test_plotting.py | 4 ++-- 4 files changed, 18 insertions(+), 17 deletions(-) diff --git a/freqtrade/data/btanalysis.py b/freqtrade/data/btanalysis.py index f98135c27..6c498a470 100644 --- a/freqtrade/data/btanalysis.py +++ b/freqtrade/data/btanalysis.py @@ -16,7 +16,7 @@ from freqtrade.persistence import Trade logger = logging.getLogger(__name__) # must align with columns in backtest.py -BT_DATA_COLUMNS = ["pair", "profitperc", "open_time", "close_time", "index", "duration", +BT_DATA_COLUMNS = ["pair", "profit_percent", "open_time", "close_time", "index", "duration", "open_rate", "close_rate", "open_at_end", "sell_reason"] @@ -99,7 +99,7 @@ def load_trades_from_db(db_url: str) -> pd.DataFrame: trades: pd.DataFrame = pd.DataFrame([], columns=BT_DATA_COLUMNS) persistence.init(db_url, clean_open_orders=False) - columns = ["pair", "open_time", "close_time", "profit", "profitperc", + columns = ["pair", "open_time", "close_time", "profit", "profit_percent", "open_rate", "close_rate", "amount", "duration", "sell_reason", "fee_open", "fee_close", "open_rate_requested", "close_rate_requested", "stake_amount", "max_rate", "min_rate", "id", "exchange", @@ -190,7 +190,7 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str, """ Adds a column `col_name` with the cumulative profit for the given trades array. :param df: DataFrame with date index - :param trades: DataFrame containing trades (requires columns close_time and profitperc) + :param trades: DataFrame containing trades (requires columns close_time and profit_percent) :param col_name: Column name that will be assigned the results :param timeframe: Timeframe used during the operations :return: Returns df with one additional column, col_name, containing the cumulative profit. @@ -201,7 +201,8 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str, from freqtrade.exchange import timeframe_to_minutes timeframe_minutes = timeframe_to_minutes(timeframe) # Resample to timeframe to make sure trades match candles - _trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_time')[['profitperc']].sum() + _trades_sum = trades.resample(f'{timeframe_minutes}min', on='close_time' + )[['profit_percent']].sum() df.loc[:, col_name] = _trades_sum.cumsum() # Set first value to 0 df.loc[df.iloc[0].name, col_name] = 0 @@ -211,13 +212,13 @@ def create_cum_profit(df: pd.DataFrame, trades: pd.DataFrame, col_name: str, def calculate_max_drawdown(trades: pd.DataFrame, *, date_col: str = 'close_time', - value_col: str = 'profitperc' + value_col: str = 'profit_percent' ) -> Tuple[float, pd.Timestamp, pd.Timestamp]: """ Calculate max drawdown and the corresponding close dates - :param trades: DataFrame containing trades (requires columns close_time and profitperc) + :param trades: DataFrame containing trades (requires columns close_time and profit_percent) :param date_col: Column in DataFrame to use for dates (defaults to 'close_time') - :param value_col: Column in DataFrame to use for values (defaults to 'profitperc') + :param value_col: Column in DataFrame to use for values (defaults to 'profit_percent') :return: Tuple (float, highdate, lowdate) with absolute max drawdown, high and low time :raise: ValueError if trade-dataframe was found empty. """ diff --git a/freqtrade/plot/plotting.py b/freqtrade/plot/plotting.py index f1d114e2b..d519c5f4e 100644 --- a/freqtrade/plot/plotting.py +++ b/freqtrade/plot/plotting.py @@ -162,7 +162,7 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots: # Trades can be empty if trades is not None and len(trades) > 0: # Create description for sell summarizing the trade - trades['desc'] = trades.apply(lambda row: f"{round(row['profitperc'] * 100, 1)}%, " + trades['desc'] = trades.apply(lambda row: f"{round(row['profit_percent'] * 100, 1)}%, " f"{row['sell_reason']}, {row['duration']} min", axis=1) trade_buys = go.Scatter( @@ -181,9 +181,9 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots: ) trade_sells = go.Scatter( - x=trades.loc[trades['profitperc'] > 0, "close_time"], - y=trades.loc[trades['profitperc'] > 0, "close_rate"], - text=trades.loc[trades['profitperc'] > 0, "desc"], + x=trades.loc[trades['profit_percent'] > 0, "close_time"], + y=trades.loc[trades['profit_percent'] > 0, "close_rate"], + text=trades.loc[trades['profit_percent'] > 0, "desc"], mode='markers', name='Sell - Profit', marker=dict( @@ -194,9 +194,9 @@ def plot_trades(fig, trades: pd.DataFrame) -> make_subplots: ) ) trade_sells_loss = go.Scatter( - x=trades.loc[trades['profitperc'] <= 0, "close_time"], - y=trades.loc[trades['profitperc'] <= 0, "close_rate"], - text=trades.loc[trades['profitperc'] <= 0, "desc"], + x=trades.loc[trades['profit_percent'] <= 0, "close_time"], + y=trades.loc[trades['profit_percent'] <= 0, "close_rate"], + text=trades.loc[trades['profit_percent'] <= 0, "desc"], mode='markers', name='Sell - Loss', marker=dict( diff --git a/tests/data/test_btanalysis.py b/tests/data/test_btanalysis.py index 50cf9db3d..b65db7fd8 100644 --- a/tests/data/test_btanalysis.py +++ b/tests/data/test_btanalysis.py @@ -47,7 +47,7 @@ def test_load_trades_from_db(default_conf, fee, mocker): assert isinstance(trades, DataFrame) assert "pair" in trades.columns assert "open_time" in trades.columns - assert "profitperc" in trades.columns + assert "profit_percent" in trades.columns for col in BT_DATA_COLUMNS: if col not in ['index', 'open_at_end']: diff --git a/tests/test_plotting.py b/tests/test_plotting.py index 5bb113784..150329c52 100644 --- a/tests/test_plotting.py +++ b/tests/test_plotting.py @@ -124,7 +124,7 @@ def test_plot_trades(testdatadir, caplog): trade_sell = find_trace_in_fig_data(figure.data, 'Sell - Profit') assert isinstance(trade_sell, go.Scatter) assert trade_sell.yaxis == 'y' - assert len(trades.loc[trades['profitperc'] > 0]) == len(trade_sell.x) + assert len(trades.loc[trades['profit_percent'] > 0]) == len(trade_sell.x) assert trade_sell.marker.color == 'green' assert trade_sell.marker.symbol == 'square-open' assert trade_sell.text[0] == '4.0%, roi, 15 min' @@ -132,7 +132,7 @@ def test_plot_trades(testdatadir, caplog): trade_sell_loss = find_trace_in_fig_data(figure.data, 'Sell - Loss') assert isinstance(trade_sell_loss, go.Scatter) assert trade_sell_loss.yaxis == 'y' - assert len(trades.loc[trades['profitperc'] <= 0]) == len(trade_sell_loss.x) + assert len(trades.loc[trades['profit_percent'] <= 0]) == len(trade_sell_loss.x) assert trade_sell_loss.marker.color == 'red' assert trade_sell_loss.marker.symbol == 'square-open' assert trade_sell_loss.text[5] == '-10.4%, stop_loss, 720 min'