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MAINT: Replace iterkv with iteritems.

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iterkv is being deprecated as of pandas 0.14.
This commit is contained in:
Thomas Wiecki
2014-10-22 17:25:37 +02:00
parent 18ad02f6a4
commit 820115f7be
7 changed files with 16 additions and 15 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/risk/test_risk_cumulative.py
+8 -8
View File
@@ -60,28 +60,28 @@ class TestRisk(unittest.TestCase):
def test_algorithm_volatility_06(self):
algo_vol_answers = answer_key.RISK_CUMULATIVE.volatility
for dt, value in algo_vol_answers.iterkv():
for dt, value in algo_vol_answers.iteritems():
np.testing.assert_almost_equal(
self.cumulative_metrics_06.metrics.algorithm_volatility[dt],
value,
err_msg="Mismatch at %s" % (dt,))
def test_sharpe_06(self):
for dt, value in answer_key.RISK_CUMULATIVE.sharpe.iterkv():
for dt, value in answer_key.RISK_CUMULATIVE.sharpe.iteritems():
np.testing.assert_almost_equal(
self.cumulative_metrics_06.metrics.sharpe[dt],
value,
err_msg="Mismatch at %s" % (dt,))
def test_downside_risk_06(self):
for dt, value in answer_key.RISK_CUMULATIVE.downside_risk.iterkv():
for dt, value in answer_key.RISK_CUMULATIVE.downside_risk.iteritems():
np.testing.assert_almost_equal(
value,
self.cumulative_metrics_06.metrics.downside_risk[dt],
err_msg="Mismatch at %s" % (dt,))
def test_sortino_06(self):
for dt, value in answer_key.RISK_CUMULATIVE.sortino.iterkv():
for dt, value in answer_key.RISK_CUMULATIVE.sortino.iteritems():
np.testing.assert_almost_equal(
self.cumulative_metrics_06.metrics.sortino[dt],
value,
@@ -89,28 +89,28 @@ class TestRisk(unittest.TestCase):
err_msg="Mismatch at %s" % (dt,))
def test_information_06(self):
for dt, value in answer_key.RISK_CUMULATIVE.information.iterkv():
for dt, value in answer_key.RISK_CUMULATIVE.information.iteritems():
np.testing.assert_almost_equal(
value,
self.cumulative_metrics_06.metrics.information[dt],
err_msg="Mismatch at %s" % (dt,))
def test_alpha_06(self):
for dt, value in answer_key.RISK_CUMULATIVE.alpha.iterkv():
for dt, value in answer_key.RISK_CUMULATIVE.alpha.iteritems():
np.testing.assert_almost_equal(
self.cumulative_metrics_06.metrics.alpha[dt],
value,
err_msg="Mismatch at %s" % (dt,))
def test_beta_06(self):
for dt, value in answer_key.RISK_CUMULATIVE.beta.iterkv():
for dt, value in answer_key.RISK_CUMULATIVE.beta.iteritems():
np.testing.assert_almost_equal(
value,
self.cumulative_metrics_06.metrics.beta[dt],
err_msg="Mismatch at %s" % (dt,))
def test_max_drawdown_06(self):
for dt, value in answer_key.RISK_CUMULATIVE.max_drawdown.iterkv():
for dt, value in answer_key.RISK_CUMULATIVE.max_drawdown.iteritems():
np.testing.assert_almost_equal(
self.cumulative_metrics_06.max_drawdowns[dt],
value,
tests/test_finance.py
+1 -1
View File
@@ -269,7 +269,7 @@ class FinanceTestCase(TestCase):
'type':
zipline.protocol.DATASOURCE_TYPE.BENCHMARK,
'source_id': 'benchmarks'})
for dt, ret in trading.environment.benchmark_returns.iterkv()
for dt, ret in trading.environment.benchmark_returns.iteritems()
if dt.date() >= sim_params.period_start.date()
and dt.date() <= sim_params.period_end.date()
]
tests/test_perf_tracking.py
+1 -1
View File
@@ -70,7 +70,7 @@ def benchmark_events_in_range(sim_params):
# We explicitly rely on the behavior that benchmarks sort before
# any other events.
'source_id': '1Abenchmarks'})
for dt, ret in trading.environment.benchmark_returns.iterkv()
for dt, ret in trading.environment.benchmark_returns.iteritems()
if dt.date() >= sim_params.period_start.date()
and dt.date() <= sim_params.period_end.date()
]
zipline/algorithm.py
+2 -1
View File
@@ -321,7 +321,8 @@ class TradingAlgorithm(object):
'returns': ret,
'type': zipline.protocol.DATASOURCE_TYPE.BENCHMARK,
'source_id': 'benchmarks'})
for dt, ret in trading.environment.benchmark_returns.iterkv()
for dt, ret in
trading.environment.benchmark_returns.iteritems()
if dt.date() >= sim_params.period_start.date()
and dt.date() <= sim_params.period_end.date()
]
zipline/data/loader.py
+1 -1
View File
@@ -227,7 +227,7 @@ Fetching data from {0}
treasury_curves = saved_curves.tz_localize('UTC')
tr_curves = {}
for tr_dt, curve in treasury_curves.T.iterkv():
for tr_dt, curve in treasury_curves.T.iteritems():
# tr_dt = tr_dt.replace(hour=0, minute=0, second=0, microsecond=0,
# tzinfo=pytz.utc)
tr_curves[tr_dt] = curve.to_dict()
zipline/finance/risk/period.py
+1 -1
View File
@@ -95,7 +95,7 @@ class RiskMetricsPeriod(object):
self.algorithm_returns, self.num_trading_days)
self.mean_algorithm_returns = pd.Series(
index=self.algorithm_returns.index)
for dt, ret in self.algorithm_returns.iterkv():
for dt, ret in self.algorithm_returns.iteritems():
self.mean_algorithm_returns[dt] = (
self.algorithm_returns[:dt].sum()
/
zipline/sources/data_frame_source.py
+2 -2
View File
@@ -67,7 +67,7 @@ class DataFrameSource(DataSource):
def raw_data_gen(self):
for dt, series in self.data.iterrows():
for sid, price in series.iterkv():
for sid, price in series.iteritems():
if sid in self.sids:
event = {
'dt': dt,
@@ -136,7 +136,7 @@ class DataPanelSource(DataSource):
def raw_data_gen(self):
for dt in self.data.major_axis:
df = self.data.major_xs(dt)
for sid, series in df.iterkv():
for sid, series in df.iteritems():
if sid in self.sids:
event = {
'dt': dt,