wassname/catalyst
1
0
Fork 0
mirror of https://github.com/wassname/catalyst.git synced 2026-06-28 20:22:12 +08:00
Code Issues Packages Projects Releases Wiki Activity

Merge pull request #737 from quantopian/remove-random-simulation-params

Browse Source 
Pre-lazy changes to test_perf_tracking
This commit is contained in:
Eddie Hebert
2015-09-29 16:26:22 -04:00
parent b1cb177d45 23e7433635
commit b655a2a592
2 changed files with 56 additions and 61 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/test_perf_tracking.py
+56 -28
View File
@@ -44,7 +44,7 @@ from zipline.finance.trading import SimulationParameters
from zipline.finance.blotter import Order
from zipline.finance.commission import PerShare, PerTrade, PerDollar
from zipline.finance.trading import TradingEnvironment
from zipline.utils.factory import create_random_simulation_parameters
from zipline.utils.factory import create_simulation_parameters
from zipline.utils.serialization_utils import (
loads_with_persistent_ids, dumps_with_persistent_ids
)
@@ -144,7 +144,9 @@ def benchmark_events_in_range(sim_params, env):
]
def calculate_results(host,
def calculate_results(sim_params,
env,
benchmark_events,
trade_events,
dividend_events=None,
splits=None,
@@ -175,7 +177,7 @@ def calculate_results(host,
txns = txns or []
splits = splits or []
perf_tracker = perf.PerformanceTracker(host.sim_params, host.env)
perf_tracker = perf.PerformanceTracker(sim_params, env)
if dividend_events is not None:
dividend_frame = pd.DataFrame(
@@ -190,7 +192,7 @@ def calculate_results(host,
trade_events = sorted(trade_events, key=lambda ev: (ev.dt, ev.source_id))
# Add a benchmark event for each date.
trades_plus_bm = date_sorted_sources(trade_events, host.benchmark_events)
trades_plus_bm = date_sorted_sources(trade_events, benchmark_events)
# Filter out benchmark events that are later than the last trade date.
filtered_trades_plus_bm = (filt_event for filt_event in trades_plus_bm
@@ -262,8 +264,7 @@ class TestSplitPerformance(unittest.TestCase):
def setUp(self):
self.env = TradingEnvironment()
self.env.write_data(equities_identifiers=[1])
self.sim_params, self.dt, self.end_dt = \
create_random_simulation_parameters()
self.sim_params = create_simulation_parameters(num_days=2)
# start with $10,000
self.sim_params.capital_base = 10e3
@@ -294,7 +295,9 @@ class TestSplitPerformance(unittest.TestCase):
),
]
results = calculate_results(self, events, txns=txns, splits=splits)
results = calculate_results(self.sim_params, self.env,
self.benchmark_events,
events, txns=txns, splits=splits)
# should have 33 shares (at $60 apiece) and $20 in cash
self.assertEqual(2, len(results))
@@ -367,11 +370,9 @@ class TestCommissionEvents(unittest.TestCase):
self.env.write_data(
equities_identifiers=[0, 1, 133]
)
self.sim_params, self.dt, self.end_dt = \
create_random_simulation_parameters()
self.sim_params = create_simulation_parameters(num_days=5)
logger.info("sim_params: %s, dt: %s, end_dt: %s" %
(self.sim_params, self.dt, self.end_dt))
logger.info("sim_params: %s" % self.sim_params)
self.sim_params.capital_base = 10e3
@@ -420,7 +421,11 @@ class TestCommissionEvents(unittest.TestCase):
# Insert a purchase order.
txns = [create_txn(events[0], 20, 1)]
results = calculate_results(self, events, txns=txns)
results = calculate_results(self.sim_params,
self.env,
self.benchmark_events,
events,
txns=txns)
# Validate that we lost 320 dollars from our cash pool.
self.assertEqual(results[-1]['cumulative_perf']['ending_cash'],
@@ -479,7 +484,11 @@ class TestCommissionEvents(unittest.TestCase):
events.append(cash_adjustment)
results = calculate_results(self, events, txns=txns)
results = calculate_results(self.sim_params,
self.env,
self.benchmark_events,
events,
txns=txns)
# Validate that we lost 300 dollars from our cash pool.
self.assertEqual(results[-1]['cumulative_perf']['ending_cash'],
9700)
@@ -502,7 +511,10 @@ class TestCommissionEvents(unittest.TestCase):
cash_adjustment = factory.create_commission(1, 300.0, cash_adj_dt)
events.append(cash_adjustment)
results = calculate_results(self, events)
results = calculate_results(self.sim_params,
self.env,
self.benchmark_events,
events)
# Validate that we lost 300 dollars from our cash pool.
self.assertEqual(results[-1]['cumulative_perf']['ending_cash'],
9700)
@@ -520,8 +532,7 @@ class TestDividendPerformance(unittest.TestCase):
del cls.env
def setUp(self):
self.sim_params, self.dt, self.end_dt = \
create_random_simulation_parameters()
self.sim_params = create_simulation_parameters(num_days=6)
self.sim_params.capital_base = 10e3
self.benchmark_events = benchmark_events_in_range(self.sim_params,
@@ -563,7 +574,9 @@ class TestDividendPerformance(unittest.TestCase):
# Simulate a transaction being filled prior to the ex_date.
txns = [create_txn(events[0], 10.0, 100)]
results = calculate_results(
self,
self.sim_params,
self.env,
self.benchmark_events,
events,
dividend_events=[dividend],
txns=txns,
@@ -617,7 +630,9 @@ class TestDividendPerformance(unittest.TestCase):
txns = [create_txn(events[0], 10.0, 100)]
results = calculate_results(
self,
self.sim_params,
self.env,
self.benchmark_events,
events,
dividend_events=[dividend],
txns=txns,
@@ -663,7 +678,9 @@ class TestDividendPerformance(unittest.TestCase):
txns = [create_txn(events[1], 10.0, 100)]
results = calculate_results(
self,
self.sim_params,
self.env,
self.benchmark_events,
events,
dividend_events=[dividend],
txns=txns,
@@ -706,7 +723,9 @@ class TestDividendPerformance(unittest.TestCase):
txns = [buy_txn, sell_txn]
results = calculate_results(
self,
self.sim_params,
self.env,
self.benchmark_events,
events,
dividend_events=[dividend],
txns=txns,
@@ -748,7 +767,9 @@ class TestDividendPerformance(unittest.TestCase):
txns = [buy_txn, sell_txn]
results = calculate_results(
self,
self.sim_params,
self.env,
self.benchmark_events,
events,
dividend_events=[dividend],
txns=txns,
@@ -792,7 +813,9 @@ class TestDividendPerformance(unittest.TestCase):
txns = [create_txn(events[1], 10.0, 100)]
results = calculate_results(
self,
self.sim_params,
self.env,
self.benchmark_events,
events,
dividend_events=[dividend],
txns=txns,
@@ -837,7 +860,9 @@ class TestDividendPerformance(unittest.TestCase):
txns = [create_txn(events[1], 10.0, -100)]
results = calculate_results(
self,
self.sim_params,
self.env,
self.benchmark_events,
events,
dividend_events=[dividend],
txns=txns,
@@ -875,7 +900,9 @@ class TestDividendPerformance(unittest.TestCase):
)
results = calculate_results(
self,
self.sim_params,
self.env,
self.benchmark_events,
events,
dividend_events=[dividend],
)
@@ -923,7 +950,9 @@ class TestDividendPerformance(unittest.TestCase):
# Simulate a transaction being filled prior to the ex_date.
txns = [create_txn(events[0], 10.0, 100)]
results = calculate_results(
self,
self.sim_params,
self.env,
self.benchmark_events,
events,
dividend_events=[dividend],
txns=txns,
@@ -977,8 +1006,7 @@ class TestPositionPerformance(unittest.TestCase):
del cls.env
def setUp(self):
self.sim_params, self.dt, self.end_dt = \
create_random_simulation_parameters()
self.sim_params = create_simulation_parameters(num_days=4)
self.finder = self.env.asset_finder
self.benchmark_events = benchmark_events_in_range(self.sim_params,
@@ -2079,7 +2107,7 @@ class TestPerformanceTracker(unittest.TestCase):
def test_handle_sid_removed_from_universe(self):
# post some trades in the market
sim_params, _, _ = create_random_simulation_parameters()
sim_params = create_simulation_parameters(num_days=5)
events = factory.create_trade_history(
1,
[10, 10, 10, 10, 10],
zipline/utils/factory.py
-33
View File
@@ -18,7 +18,6 @@
Factory functions to prepare useful data.
"""
import pytz
import random
import pandas as pd
import numpy as np
@@ -69,38 +68,6 @@ def create_simulation_parameters(year=2006, start=None, end=None,
return sim_params
def create_random_simulation_parameters():
env = TradingEnvironment()
treasury_curves = env.treasury_curves
for n in range(100):
random_index = random.randint(
0,
len(treasury_curves) - 1
)
start_dt = treasury_curves.index[random_index]
end_dt = start_dt + timedelta(days=365)
now = datetime.utcnow().replace(tzinfo=pytz.utc)
if end_dt <= now:
break
assert end_dt <= now, """
failed to find a suitable daterange after 100 attempts. please double
check treasury and benchmark data in findb, and re-run the test."""
sim_params = SimulationParameters(
period_start=start_dt,
period_end=end_dt,
env=env,
)
return sim_params, start_dt, end_dt
def get_next_trading_dt(current, interval, env):
next_dt = pd.Timestamp(current).tz_convert(env.exchange_tz)