def test_fetch_window1(self):
df1_1 = self.fetcher.fetch_window('level1', self.dates)
df1_2 = self.fetcher.fetch_window('sector', self.dates)
df2_1 = self.fetcher.fetch_window('level2', self.dates)
df2_2 = self.fetcher.fetch_window('industry', self.dates)
df3_1 = self.fetcher.fetch_window('level3', self.dates)
df3_2 = self.fetcher.fetch_window('subindustry', self.dates)
self.assertTrue(frames_equal(df1_1, df1_2)
& frames_equal(df2_1, df2_2)
& frames_equal(df3_1, df3_2))
def test_fetch(self):
barra1_1 = self.barra.fetch(self.dates[0], self.dates[-1])
barra1_2 = self.barra.fetch_window(self.dates)
barra2_1 = self.barra.fetch('industry', self.dates[0], self.dates[-1])
barra2_2 = self.barra.fetch_window('industry', self.dates)
barra3_1 = self.barra.fetch(['CNE5D_COUNTRY'], self.dates[0], self.dates[-1])
barra3_2 = self.barra.fetch_window(['CNE5D_COUNTRY'], self.dates)
barra4_1 = self.barra.fetch('CNE5D_COUNTRY', self.dates[0], self.dates[-1])
barra4_2 = self.barra.fetch_window('CNE5D_COUNTRY', self.dates)
print pd.concat([barra4_1, barra4_2], axis=1)
self.assertTrue(frames_equal(barra1_1, barra1_2)
& frames_equal(barra2_1, barra2_2)
& frames_equal(barra3_1, barra3_2)
& series_equal(barra4_1, barra4_2))
def test_loader_getitem(self):
self.saver['data'] = self.data
self.loader.configure(parse_dates=True)
data = self.loader['data']
data.index = self.data.index
data.columns = self.data.columns
self.assertTrue(frames_equal(data, self.data))
def test_filter_1(self):
df = self.fetcher.fetch_window('close', DATES[self.si-window: self.ei+1])
df = pd.rolling_sum(df.fillna(0), window) > 2 * pd.rolling_count(df, window)
df1 = df.shift(1).iloc[window:].astype(bool)
df2 = self.filter.filter(self.startdate, self.enddate)
print 'bm', df1.sum(axis=1)
self.assertTrue(frames_equal(df1, df2))
def test_filter_2(self):
df = self.fetcher.fetch_window('close', DATES[self.si-window: self.ei+1])
parent = df.notnull()
df = df.shift(1)
df[~parent] = None
df = pd.rolling_sum(df.fillna(0), window) > 2 * pd.rolling_count(df, window)
df[~parent] = False
df = df.iloc[window:]
self.assertTrue(frames_equal(df, self.filter.filter(self.startdate, self.enddate, parent)))
def test_filter_1(self):
df = self.fetcher.fetch_window('close',
DATES[self.si - window:self.ei + 1])
df = pd.rolling_sum(df.fillna(0),
window) > 2 * pd.rolling_count(df, window)
df1 = df.shift(1).iloc[window:].astype(bool)
df2 = self.filter.filter(self.startdate, self.enddate)
print 'bm', df1.sum(axis=1)
self.assertTrue(frames_equal(df1, df2))
def test_returns_N_eq1_1(self):
df1 = self.fetcher.fetch('returns',
self.dates[5],
self.dates[-1],
backdays=5)
df2 = self.fetcher.fetch('returnsN',
1,
self.dates[5],
self.dates[-1],
backdays=5)
self.assertTrue(frames_equal(df1, df2))
def test_returns_N_eq1_3(self):
df1 = self.fetcher.fetch_history('returns',
self.dates[-1],
45,
delay=5)
df2 = self.fetcher.fetch_history('returnsN',
1,
self.dates[-1],
45,
delay=5)
self.assertTrue(frames_equal(df1, df2))
def test_filter_2(self):
df = self.fetcher.fetch_window('close',
DATES[self.si - window:self.ei + 1])
parent = df.notnull()
df = df.shift(1)
df[~parent] = None
df = pd.rolling_sum(df.fillna(0),
window) > 2 * pd.rolling_count(df, window)
df[~parent] = False
df = df.iloc[window:]
self.assertTrue(
frames_equal(
df, self.filter.filter(self.startdate, self.enddate, parent)))
def test_summary(self):
ir1 = self.alpha1.summary(group='ir', by='A')
ir2 = self.alpha1.summary_ir(by='A')
self.assertTrue(frames_equal(ir1, ir2))
def test_components_filter(self):
HS300 = ComponentsFilter('HS300').filter(window[0], window[-1])
self.assertTrue(frames_equal(hs300, HS300))
def test_returns_N_eq1_2(self):
df1 = self.fetcher.fetch_window('returns', self.dates)
df2 = self.fetcher.fetch_window('returnsN', 1, self.dates)
self.assertTrue(frames_equal(df1, df2))
def test_volume4(self):
vol1 = self.adjfetcher.fetch_window('adj_volume', self.dates)
vol2 = self.fetcher.fetch_window('volume', self.dates)
self.assertTrue(frames_equal(vol1.notnull(), vol2.notnull()))
def test_noadjust(self):
ret1 = self.adjfetcher.fetch_window('adj_returns', self.dates)
ret2 = self.fetcher.fetch_window('returns', self.dates)
amt1 = self.adjfetcher.fetch_window('adj_amount', self.dates)
amt2 = self.fetcher.fetch_window('amount', self.dates)
self.assertTrue(frames_equal(ret1, ret2) & frames_equal(amt1, amt2))
def test_volume4(self):
vol1 = self.adjfetcher.fetch_window('adj_volume', self.dates)
vol2 = self.fetcher.fetch_window('volume', self.dates)
self.assertTrue(frames_equal(vol1.notnull(), vol2.notnull()))
def test_get1(self):
self.assertTrue(frames_equal(self.perf.get_long().alpha, self.alpha2.alpha)
and frames_equal(self.perf.get_short().alpha, self.alpha3.alpha))
def test_summary(self):
ir1 = self.alpha1.summary(group='ir', by='A')
ir2 = self.alpha1.summary_ir(by='A')
self.assertTrue(frames_equal(ir1, ir2))
def test_top(self):
df = pd.DataFrame(np.random.randn(20, 40))
top1 = api.top(df, 1)
maxdf = df.max(axis=1)
top2 = df.eq(maxdf, axis=0)
self.assertTrue(frames_equal(top1, top2))
def test_qbottom(self):
df = pd.DataFrame(np.random.randn(50, 500))
bot1 = api.qbottom(df, 0.01)
bot2 = api.bottom(df, 5)
self.assertTrue(frames_equal(bot1, bot2))
def test_industry_filter(self):
finance = IndustryFilter(['480000', '490000']).filter(window[0], window[-1])
self.assertTrue(frames_equal(sector.isin(['480000', '490000']), finance))
def test_components_filter(self):
HS300 = ComponentsFilter('HS300').filter(window[0], window[-1])
self.assertTrue(frames_equal(hs300, HS300))
def test_fetch_window_classmethod(self):
df1 = self.fetcher.fetch_window('close', self.dates)
df2 = QuoteFetcher.fetch_window('close', self.dates)
self.assertTrue(frames_equal(df1, df2))
def test_active_filter(self):
active1 = ActiveFilter().filter(window[0], window[-1])
active2 = ~close.isnull()
self.assertTrue(frames_equal(active1, active2))
def test_loader_getitem(self):
self.saver['data'] = self.data
data = self.loader['data']
self.assertTrue(frames_equal(data, self.data))
def test_history3(self):
cls1 = self.adjfetcher.fetch_history('adj_close', self.dates[-1],
len(self.dates) - 1)
cls2 = self.adjfetcher.fetch_window('adj_close', self.dates[:-1],
self.dates[-1])
self.assertTrue(frames_equal(cls1, cls2))
def test_barra_corr_neut(self):
df = random_alpha(n=20)
neut_df1 = api.barra_corr_neut(df, 'short', 'industry')
neut_df2 = api.barra_corr_neut(neut_df1, 'short', 'industry')
self.assertTrue(frames_equal(neut_df1, neut_df2))
def test_price4(self):
cls1 = self.adjfetcher.fetch_window('adj_close', self.dates)
cls2 = self.fetcher.fetch_window('close', self.dates)
self.assertTrue(frames_equal(cls1.notnull(), cls2.notnull()))
def test_fetch_window2(self):
df1 = self.fetcher.fetch_window('level1', self.dates)
df2 = self.fetcher.fetch_window('level1', self.dates, standard='ZX')
self.assertFalse(frames_equal(df1, df2))
def test_returns_N_eq1_3(self):
df1 = self.fetcher.fetch_history('returns', self.dates[-1], 45, delay=5)
df2 = self.fetcher.fetch_history('returnsN', 1, self.dates[-1], 45, delay=5)
self.assertTrue(frames_equal(df1, df2))
def test_fetch_daily1(self):
cov1 = self.barra.fetch_daily(self.dates[0])
cov2 = self.barra.fetch_daily(self.dates[1], offset=1)
self.assertTrue(frames_equal(cov1, cov2))
def test_loader_getitem(self):
self.saver['data'] = self.data
data = self.loader['data']
self.assertTrue(frames_equal(data, self.data))
def test_fetch_daily2(self):
cov0 = self.barra.fetch_daily(self.dates[0])
sids = cov0.index[:200]
cov1 = cov0.ix[sids, sids]
cov2 = self.barra.fetch_daily(self.dates[0], sids=sids)
self.assertTrue(frames_equal(cov1, cov2))
def test_active_filter(self):
active1 = ActiveFilter().filter(window[0], window[-1])
active2 = ~close.isnull()
self.assertTrue(frames_equal(active1, active2))
def test_returns_N_eq1_2(self):
df1 = self.fetcher.fetch_window('returns', self.dates)
df2 = self.fetcher.fetch_window('returnsN', 1, self.dates)
self.assertTrue(frames_equal(df1, df2))
def test_industry_filter(self):
finance = IndustryFilter(['480000',
'490000']).filter(window[0], window[-1])
self.assertTrue(
frames_equal(sector.isin(['480000', '490000']), finance))
def test_returns_N_eq1_1(self):
df1 = self.fetcher.fetch('returns', self.dates[5], self.dates[-1], backdays=5)
df2 = self.fetcher.fetch('returnsN', 1, self.dates[5], self.dates[-1], backdays=5)
self.assertTrue(frames_equal(df1, df2))
def test_get1(self):
self.assertTrue(
frames_equal(self.perf.get_long().alpha, self.alpha2.alpha)
and frames_equal(self.perf.get_short().alpha, self.alpha3.alpha))
def test_noadjust(self):
ret1 = self.adjfetcher.fetch_window('adj_returns', self.dates)
ret2 = self.fetcher.fetch_window('returns', self.dates)
amt1 = self.adjfetcher.fetch_window('adj_amount', self.dates)
amt2 = self.fetcher.fetch_window('amount', self.dates)
self.assertTrue(frames_equal(ret1, ret2) & frames_equal(amt1, amt2))
def test_price4(self):
cls1 = self.adjfetcher.fetch_window('adj_close', self.dates)
cls2 = self.fetcher.fetch_window('close', self.dates)
self.assertTrue(frames_equal(cls1.notnull(), cls2.notnull()))
def test_industry_neut1(self):
df = random_alpha(n=20)
neut1_df = api.industry_neut(df, 'level2')
neut2_df = api.industry_neut(neut1_df, 'level1')
self.assertTrue(frames_equal(neut1_df, neut2_df))
def test_history3(self):
cls1 = self.adjfetcher.fetch_history('adj_close', self.dates[-1], len(self.dates)-1)
cls2 = self.adjfetcher.fetch_window('adj_close', self.dates[:-1], self.dates[-1])
self.assertTrue(frames_equal(cls1, cls2))
def test_fetch_window_classmethod(self):
df1 = self.fetcher.fetch_window('close', self.dates)
df2 = QuoteFetcher.fetch_window('close', self.dates)
self.assertTrue(frames_equal(df1, df2))
