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plot profit: filter multiple pairs, misc fixes

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This commit is contained in:
kryofly 2018-01-12 19:18:31 +01:00
parent d8d46890b3
commit 167483f777
3 changed files with 37 additions and 42 deletions
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2
docs/plotting.md
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@ -11,7 +11,7 @@ script/plot_dataframe.py [-h] [-p pair]
Example
```
python script/plot_dataframe.py -p BTC_ETH
python script/plot_dataframe.py -p BTC_ETH,BTC_LTC
```
The -p pair argument, can be used to specify what

2
freqtrade/misc.py
View File

@ -111,7 +111,7 @@ def common_args_parser(description: str):
metavar='PATH',
)
parser.add_argument(
'-dd', '--datadir',
'--datadir',
help='path to backtest data (default freqdata/tests/testdata',
dest='datadir',
default=os.path.join('freqtrade', 'tests', 'testdata'),

69
scripts/plot_profit.py
View File

@ -14,40 +14,27 @@ import freqtrade.analyze as analyze
def plot_parse_args(args ):
parser = misc.common_args_parser('Graph utility')
# FIX: perhaps delete those backtesting options that are not feasible
# FIX: perhaps delete those backtesting options that are not feasible (shows up in -h)
misc.backtesting_options(parser)
# TODO: Make the pair argument take a comma separated list
parser.add_argument(
'-p', '--pair',
help = 'Show profits for only this pair',
help = 'Show profits for only this pairs. Pairs are comma-separated.',
dest = 'pair',
default = None
)
return parser.parse_args(args)
def make_profit_array(data, filter_pair):
xmin = 0
xmax = 0
# pair profit-% time duration
# ['BTC_XMR', 0.00537847, 5057, 1]
for trade in data:
pair = trade[0]
profit = trade[1]
x = trade[2]
dur = trade[3]
xmax = max(xmax, x + dur)
pg = np.zeros(xmax)
# data:: [ pair, profit-%, time, duration]
# data:: ['BTC_XMR', 0.00537847, 5057, 1]
def make_profit_array(data, px, filter_pairs=[]):
pg = np.zeros(px)
# Go through the trades
# and make an total profit
# array
for trade in data:
pair = trade[0]
if filter_pair and pair != filter_pair:
if filter_pairs and pair not in filter_pairs:
continue
profit = trade[1]
tim = trade[2]
@ -78,13 +65,14 @@ def plot_profit(args) -> None:
# and same timeperiod as used in backtesting
# to match the tickerdata against the profits-results
filter_pair = args.pair
filter_pairs = args.pair
config = misc.load_config(args.config)
pairs = config['exchange']['pair_whitelist']
if filter_pair:
print('Filtering out pair %s' % filter_pair)
pairs = list(filter(lambda pair: pair == filter_pair, pairs))
if filter_pairs:
filter_pairs = filter_pairs.split(',')
pairs = list(set(pairs) & set(filter_pairs))
print('Filter, keep pairs %s' % pairs)
tickers = optimize.load_data(args.datadir, pairs=pairs,
ticker_interval=args.ticker_interval,
@ -99,23 +87,28 @@ def plot_profit(args) -> None:
# But we dont have the date information in the
# backtesting results, this is needed to match the dates
# For now, assume the dataframes are aligned.
max_x = 0
for pair, pair_data in dataframes.items():
n = len(pair_data['close'])
max_x = max(max_x, n)
# if max_x != n:
# raise Exception('Please rerun script. Input data has different lengths %s'
# %('Different pair length: %s <=> %s' %(max_x, n)))
print('max_x: %s' %(max_x))
# We are essentially saying:
# array <- sum dataframes[*]['close'] / num_items dataframes
# FIX: there should be some onliner numpy/panda for this
first = True
avgclose = None
avgclose = np.zeros(max_x)
num = 0
for pair, pair_data in dataframes.items():
close = pair_data['close']
maxprice = max(close) # Normalize price to [0,1]
print('Pair %s has length %s' %(pair, len(close)))
for x in range(0, len(close)):
avgclose[x] += close[x] / maxprice
# avgclose += close
num += 1
if first:
first = False
avgclose = np.copy(close)
else:
avgclose += close
avgclose /= num
# Load the profits results
@ -124,7 +117,7 @@ def plot_profit(args) -> None:
filename = 'backtest-result.json'
with open(filename) as file:
data = json.load(file)
pg = make_profit_array(data, filter_pair)
pg = make_profit_array(data, max_x, filter_pairs)
#
# Plot the pairs average close prices, and total profit growth
@ -134,17 +127,19 @@ def plot_profit(args) -> None:
fig.suptitle('total profit')
ax1.plot(avgclose, label='avgclose')
ax2.plot(pg, label='profit')
ax1.legend()
ax2.legend()
ax1.legend(loc='upper left')
ax2.legend(loc='upper left')
# FIX if we have one line pair in paris
# then skip the plotting of the third graph,
# or change what we plot
# In third graph, we plot each profit separately
for pair in pairs:
pg = make_profit_array(data, pair)
pg = make_profit_array(data, max_x, pair)
ax3.plot(pg, label=pair)
ax3.legend()
ax3.legend(loc='upper left')
# black background to easier see multiple colors
ax3.set_facecolor('black')
# Fine-tune figure; make subplots close to each other and hide x ticks for
# all but bottom plot.