Add reset

hftbacktest/__init__.py

@@ -29,7 +29,7 @@
            'Stat',
            'validate_data', 'correct_local_timestamp', 'correct_exch_timestamp', 'correct',)
 
-__version__ = '1.4.2'
+__version__ = '1.5.0'
 
 
 def HftBacktest(
@@ -50,79 +50,31 @@ def HftBacktest(
 ):
     cache = Cache()
 
-    if isinstance(data, pd.DataFrame):
+    if isinstance(data, list):
         local_reader = DataReader(cache)
-        local_reader.add_data(data.to_numpy())
-
-        exch_reader = DataReader(cache)
-        exch_reader.add_data(data.to_numpy())
-    elif isinstance(data, np.ndarray):
-        local_reader = DataReader(cache)
-        local_reader.add_data(data)
-
         exch_reader = DataReader(cache)
-        exch_reader.add_data(data)
+        for item in data:
+            if isinstance(item, str):
+                local_reader.add_file(item)
+                exch_reader.add_file(item)
+            elif isinstance(item, pd.DataFrame) or isinstance(item, np.ndarray):
+                local_reader.add_data(item)
+                exch_reader.add_data(item)
+            else:
+                raise ValueError('Unsupported data type')
     elif isinstance(data, str):
         local_reader = DataReader(cache)
         local_reader.add_file(data)
 
         exch_reader = DataReader(cache)
         exch_reader.add_file(data)
-    elif isinstance(data, list):
-        local_reader = DataReader(cache)
-        exch_reader = DataReader(cache)
-        for filepath in data:
-            if isinstance(filepath, str):
-                local_reader.add_file(filepath)
-                exch_reader.add_file(filepath)
-            elif isinstance(filepath, pd.DataFrame) or isinstance(filepath, np.ndarray):
-                local_reader.add_data(filepath)
-                exch_reader.add_data(filepath)
-            else:
-                raise ValueError('Unsupported data type')
     else:
-        raise ValueError('Unsupported data type')
+        data = __load_data(data)
+        local_reader = DataReader(cache)
+        local_reader.add_data(data)
 
-    if isinstance(snapshot, pd.DataFrame):
-        assert (snapshot.columns[:6] == [
-            'event',
-            'exch_timestamp',
-            'local_timestamp',
-            'side',
-            'price',
-            'qty'
-        ]).all()
-        snapshot = snapshot.to_numpy()
-    elif isinstance(snapshot, np.ndarray):
-        assert snapshot.shape[1] >= 6
-    elif isinstance(snapshot, str):
-        if snapshot.endswith('.npy'):
-            snapshot = np.load(snapshot)
-        elif snapshot.endswith('.npz'):
-            tmp = np.load(snapshot)
-            if 'data' in tmp:
-                snapshot = tmp['data']
-                assert snapshot.shape[1] >= 6
-            else:
-                k = list(tmp.keys())[0]
-                print("Snapshot is loaded from %s instead of 'data'" % k)
-                snapshot = tmp[k]
-                assert snapshot.shape[1] >= 6
-        else:
-            df = pd.read_pickle(snapshot, compression='gzip')
-            assert (df.columns[:6] == [
-                'event',
-                'exch_timestamp',
-                'local_timestamp',
-                'side',
-                'price',
-                'qty'
-            ]).all()
-            snapshot = df.to_numpy()
-    elif snapshot is None:
-        pass
-    else:
-        raise ValueError('Unsupported snapshot type')
+        exch_reader = DataReader(cache)
+        exch_reader.add_data(data)
 
     if queue_model is None:
         queue_model = RiskAverseQueueModel()
@@ -131,6 +83,7 @@ def HftBacktest(
     exch_market_depth = MarketDepth(tick_size, lot_size)
 
     if snapshot is not None:
+        snapshot = __load_data(snapshot)
         local_market_depth.apply_snapshot(snapshot)
         exch_market_depth.apply_snapshot(snapshot)
 
@@ -178,3 +131,103 @@ def HftBacktest(
     )
 
     return SingleAssetHftBacktest(local, exch)
+
+
+def reset(
+        hbt,
+        data,
+        tick_size=None,
+        lot_size=None,
+        maker_fee=None,
+        taker_fee=None,
+        snapshot=None,
+        start_position=0,
+        start_balance=0,
+        start_fee=0,
+        trade_list_size=None,
+):
+    cache = Cache()
+
+    if isinstance(data, list):
+        local_reader = DataReader(cache)
+        exch_reader = DataReader(cache)
+        for item in data:
+            if isinstance(item, str):
+                local_reader.add_file(item)
+                exch_reader.add_file(item)
+            elif isinstance(item, pd.DataFrame) or isinstance(item, np.ndarray):
+                local_reader.add_data(item)
+                exch_reader.add_data(item)
+            else:
+                raise ValueError('Unsupported data type')
+    elif isinstance(data, str):
+        local_reader = DataReader(cache)
+        local_reader.add_file(data)
+
+        exch_reader = DataReader(cache)
+        exch_reader.add_file(data)
+    else:
+        data = __load_data(data)
+        local_reader = DataReader(cache)
+        local_reader.add_data(data)
+
+        exch_reader = DataReader(cache)
+        exch_reader.add_data(data)
+
+    snapshot = __load_data(snapshot) if snapshot is not None else None
+
+    hbt.reset(
+        local_reader,
+        exch_reader,
+        start_position,
+        start_balance,
+        start_fee,
+        maker_fee,
+        taker_fee,
+        tick_size,
+        lot_size,
+        snapshot,
+        trade_list_size,
+    )
+
+
+def __load_data(data):
+    if isinstance(data, pd.DataFrame):
+        assert (data.columns[:6] == [
+            'event',
+            'exch_timestamp',
+            'local_timestamp',
+            'side',
+            'price',
+            'qty'
+        ]).all()
+        data = data.to_numpy()
+    elif isinstance(data, np.ndarray):
+        assert data.shape[1] >= 6
+    elif isinstance(data, str):
+        if data.endswith('.npy'):
+            data = np.load(data)
+        elif data.endswith('.npz'):
+            tmp = np.load(data)
+            if 'data' in tmp:
+                data = tmp['data']
+                assert data.shape[1] >= 6
+            else:
+                k = list(tmp.keys())[0]
+                print("Data is loaded from %s instead of 'data'" % k)
+                data = tmp[k]
+                assert data.shape[1] >= 6
+        else:
+            df = pd.read_pickle(data, compression='gzip')
+            assert (df.columns[:6] == [
+                'event',
+                'exch_timestamp',
+                'local_timestamp',
+                'side',
+                'price',
+                'qty'
+            ]).all()
+            data = df.to_numpy()
+    else:
+        raise ValueError('Unsupported data type')
+    return data

hftbacktest/backtest.py

@@ -217,6 +217,46 @@ def goto(self, timestamp, wait_order_response=WAIT_ORDER_RESPONSE_NONE):
             return False
         return True
 
+    def reset(
+            self,
+            local_reader,
+            exch_reader,
+            start_position,
+            start_balance,
+            start_fee,
+            maker_fee,
+            taker_fee,
+            tick_size,
+            lot_size,
+            snapshot,
+            trade_list_size,
+    ):
+        self.local.reader = local_reader
+        self.exch.reader = exch_reader
+
+        self.local.reset(
+            start_position,
+            start_balance,
+            start_fee,
+            maker_fee,
+            taker_fee,
+            tick_size,
+            lot_size,
+            snapshot,
+            trade_list_size,
+        )
+        self.exch.reset(
+            start_position,
+            start_balance,
+            start_fee,
+            maker_fee,
+            taker_fee,
+            tick_size,
+            lot_size,
+            snapshot
+        )
+        self.current_timestamp = self.local.next_data[0, COL_LOCAL_TIMESTAMP]
+        self.run = True
 
 def SingleAssetHftBacktest(local, exch):
     jitted = jitclass(spec=[

hftbacktest/models/latencies.py

@@ -19,6 +19,9 @@ def entry(self, timestamp, order, proc):
     def response(self, timestamp, order, proc):
         return self.response_latency
 
+    def reset(self):
+        pass
+
 
 @jitclass
 class FeedLatency:
@@ -71,6 +74,9 @@ def entry(self, timestamp, order, proc):
     def response(self, timestamp, order, proc):
         return self.response_latency + self.resp_latency_mul * self.__latency(proc)
 
+    def reset(self):
+        pass
+
 
 @jitclass
 class ForwardFeedLatency:
@@ -105,6 +111,9 @@ def entry(self, timestamp, order, proc):
     def response(self, timestamp, order, proc):
         return self.response_latency + self.resp_latency_mul * self.__latency(proc)
 
+    def reset(self):
+        pass
+
 
 @jitclass
 class BackwardFeedLatency:
@@ -139,6 +148,9 @@ def entry(self, timestamp, order, proc):
     def response(self, timestamp, order, proc):
         return self.response_latency + self.resp_latency_mul * self.__latency(proc)
 
+    def reset(self):
+        pass
+
 
 @jitclass
 class IntpOrderLatency:
@@ -199,3 +211,7 @@ def response(self, timestamp, order, proc):
                 lat2 = next_resp_local_timestamp - next_exch_timestamp
                 return self.__intp(timestamp, exch_timestamp, lat1, next_exch_timestamp, lat2)
         raise ValueError
+
+    def reset(self):
+        self.entry_rn = 0
+        self.resp_rn = 0

hftbacktest/models/queue.py

@@ -27,6 +27,9 @@ def depth(self, order, prev_qty, new_qty, proc):
     def is_filled(self, order, proc):
         return round(order.q[0] / proc.lot_size) < 0
 
+    def reset(self):
+        pass
+
 
 class ProbQueueModel:
     def __init__(self):
@@ -69,6 +72,9 @@ def is_filled(self, order, proc):
     def prob(self, front, back):
         return np.divide(self.f(back), self.f(back) + self.f(front))
 
+    def reset(self):
+        pass
+
 
 @jitclass
 class LogProbQueueModel(ProbQueueModel):

hftbacktest/order.py

@@ -147,6 +147,11 @@ def get(self, order_id):
                 return recv_timestamp
         raise KeyError
 
+    def reset(self):
+        self.order_list.clear()
+        self.orders.clear()
+        self.frontmost_timestamp = 0
+
     def __getitem__(self, key):
         return self.order_list[key]
 

hftbacktest/proc/local.py

@@ -31,6 +31,35 @@ def __init__(
         self.last_trades = np.full((trade_list_size, self.data.shape[1]), np.nan, np.float64)
         self.user_data = np.full((20, self.data.shape[1]), np.nan, np.float64)
 
+    def reset(
+            self,
+            start_position,
+            start_balance,
+            start_fee,
+            maker_fee,
+            taker_fee,
+            tick_size,
+            lot_size,
+            snapshot,
+            trade_list_size,
+    ):
+        self._proc_reset(
+            start_position,
+            start_balance,
+            start_fee,
+            maker_fee,
+            taker_fee,
+            tick_size,
+            lot_size,
+            snapshot
+        )
+        self.trade_len = 0
+        if trade_list_size is not None:
+            self.last_trades = np.full((trade_list_size, self.data.shape[1]), np.nan, np.float64)
+        else:
+            self.last_trades[:, :] = np.nan
+        self.user_data[:, :] = np.nan
+
     def _next_data_timestamp(self):
         return self._next_data_timestamp_column(COL_LOCAL_TIMESTAMP)