BLD: polishing a sample algorithm

catalyst/examples/mean_reversion.py

@@ -70,7 +70,7 @@ def handle_data(context, data):
     # volume arrays.
 
     # In this example, we are comp
-    rsi = talib.RSI(prices.values, timeperiod=4)
+    rsi = talib.RSI(prices.values, timeperiod=14)
     sma200 = talib.SMA(prices.values, timeperiod=200)
 
     # We need a variable for the current price of the security to compare to
@@ -78,11 +78,6 @@ def handle_data(context, data):
     # returns a DataFrame with
     current = data.current(context.eth_btc, fields=['close', 'volume'])
     price = current['close']
-    log.info(
-        '{}: price: {}, rsi: {}, sma: {}'.format(
-            data.current_dt, price, rsi[-1], sma200[-1]
-        )
-    )
 
     # If base_price is not set, we use the current value. This is the
     # price at the first bar which we reference to calculate price_change.
@@ -107,14 +102,12 @@ def handle_data(context, data):
     # We are trying to avoid over-trading by limiting our trades to
     # one per day.
     if context.traded_today:
-        log.info('skipping because we\'ve already trader today')
         return
 
     # Since we are using limit orders, some orders may not execute immediately
     # we wait until all orders are executed before considering more trades.
     orders = get_open_orders(context.eth_btc)
     if len(orders) > 0:
-        log.info('skipping until all open orders execute')
         return
 
     # Another powerful built-in feature of the Catalyst backtester is the
@@ -124,14 +117,22 @@ def handle_data(context, data):
     pos_amount = context.portfolio.positions[context.eth_btc].amount
 
     # Determining the entry and exit signals based on RSI and SMA
-    if rsi[-1] <= 30 and data.can_trade(context.eth_btc) \
-            and pos_amount == 0:
-        # and price > sma200[-1] and pos_amount == 0:
+    if (rsi[-1] <= 30 and price > sma200[-1]) \
+            and data.can_trade(context.eth_btc) and pos_amount == 0:
+        log.info(
+            '{}: buying - price: {}, rsi: {}, sma: {}'.format(
+                data.current_dt, price, rsi[-1], sma200[-1]
+            )
+        )
         order_target_percent(context.eth_btc, 1)
         context.traded_today = True
 
-    elif (rsi[-1] >= 90 or crossunder(prices, sma200)) \
-            and data.can_trade(context.eth_btc) and pos_amount > 0:
+    elif rsi[-1] >= 80 and data.can_trade(context.eth_btc) and pos_amount > 0:
+        log.info(
+            '{}: selling - price: {}, rsi: {}, sma: {}'.format(
+                data.current_dt, price, rsi[-1], sma200[-1]
+            )
+        )
         order_target_percent(context.eth_btc, 0)
         context.traded_today = True
 
@@ -157,24 +158,25 @@ def analyze(context=None, perf=None):
     ))
 
     transaction_df = extract_transactions(perf)
-    buy_df = transaction_df[transaction_df['amount'] > 0]
-    sell_df = transaction_df[transaction_df['amount'] < 0]
-    ax2.scatter(
-        buy_df.index,
-        perf.loc[buy_df.index, 'price'],
-        marker='^',
-        s=100,
-        c='green',
-        label=''
-    )
-    ax2.scatter(
-        sell_df.index,
-        perf.loc[sell_df.index, 'price'],
-        marker='v',
-        s=100,
-        c='red',
-        label=''
-    )
+    if not transaction_df.empty:
+        buy_df = transaction_df[transaction_df['amount'] > 0]
+        sell_df = transaction_df[transaction_df['amount'] < 0]
+        ax2.scatter(
+            buy_df.index.to_pydatetime(),
+            perf.loc[buy_df.index, 'price'],
+            marker='^',
+            s=100,
+            c='green',
+            label=''
+        )
+        ax2.scatter(
+            sell_df.index.to_pydatetime(),
+            perf.loc[sell_df.index, 'price'],
+            marker='v',
+            s=100,
+            c='red',
+            label=''
+        )
 
     ax4 = plt.subplot(613, sharex=ax1)
     perf.loc[:, 'cash'].plot(
@@ -192,22 +194,24 @@ def analyze(context=None, perf=None):
     perf.loc[:, 'rsi'].plot(ax=ax6, label='RSI')
     ax6.axhline(70, color='darkgoldenrod')
     ax6.axhline(30, color='darkgoldenrod')
-    ax6.scatter(
-        buy_df.index,
-        perf.loc[buy_df.index, 'rsi'],
-        marker='^',
-        s=100,
-        c='green',
-        label=''
-    )
-    ax6.scatter(
-        sell_df.index,
-        perf.loc[sell_df.index, 'rsi'],
-        marker='v',
-        s=100,
-        c='red',
-        label=''
-    )
+
+    if not transaction_df.empty:
+        ax6.scatter(
+            buy_df.index.to_pydatetime(),
+            perf.loc[buy_df.index, 'rsi'],
+            marker='^',
+            s=100,
+            c='green',
+            label=''
+        )
+        ax6.scatter(
+            sell_df.index.to_pydatetime(),
+            perf.loc[sell_df.index, 'rsi'],
+            marker='v',
+            s=100,
+            c='red',
+            label=''
+        )
     plt.legend(loc=3)
 
     # Show the plot.
@@ -231,8 +235,8 @@ if __name__ == '__main__':
             algo_namespace=algo_namespace,
             base_currency='usdt',
             start=pd.to_datetime('2017-7-1', utc=True),
-            end=pd.to_datetime('2017-9-30', utc=True),
-            # end=pd.to_datetime('2017-7-7', utc=True),
+            end=pd.to_datetime('2017-10-31', utc=True),
+            # end=pd.to_datetime('2017-7-5', utc=True),
         )
 
     elif MODE == 'live':

catalyst/exchange/exchange_algorithm.py

@@ -10,13 +10,11 @@
 # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 # See the License for the specific language governing permissions and
 # limitations under the License.
-import os
 import pickle
 import signal
 import sys
 from collections import deque
 from datetime import timedelta
-from itertools import chain
 from os import listdir
 from os.path import isfile, join
 from time import sleep
@@ -24,7 +22,6 @@ from time import sleep
 import logbook
 import pandas as pd
 from catalyst.assets._assets import TradingPair
-from six import itervalues
 
 import catalyst.protocol as zp
 from catalyst.algorithm import TradingAlgorithm
@@ -38,8 +35,8 @@ from catalyst.exchange.exchange_errors import (
     OrphanOrderError)
 from catalyst.exchange.exchange_execution import ExchangeStopLimitOrder, \
     ExchangeLimitOrder, ExchangeStopOrder
-from catalyst.exchange.exchange_utils import get_exchange_minute_writer_root, \
-    save_algo_object, get_algo_object, get_algo_folder, get_algo_df, \
+from catalyst.exchange.exchange_utils import save_algo_object, get_algo_object, \
+    get_algo_folder, get_algo_df, \
     save_algo_df
 from catalyst.exchange.live_graph_clock import LiveGraphClock
 from catalyst.exchange.simple_clock import SimpleClock

catalyst/exchange/stats_utils.py

@@ -194,8 +194,7 @@ def extract_transactions(perf):
     all_trans = [t for sublist in trans_list for t in sublist]
     all_trans.sort(key=lambda t: t['dt'])
 
-    # transactions = perf.loc[[t['dt'] for t in all_trans], :]
-
     transactions = pd.DataFrame(all_trans)
-    transactions.set_index('dt', inplace=True, drop=True)
+    if not transactions.empty:
+        transactions.set_index('dt', inplace=True, drop=True)
     return transactions