def test_stitch():
stitch_points = ["2015-03-13", "2015-04-15"]
dfs = []
ctd = {}
base = "test/data_stitch/vix%s.csv"
for f in ["may", "june", "july"]:
tmp = pd.read_csv(base % f, index_col=0, parse_dates=True)
dfs.append(tmp)
ctd[f] = tmp
res = futures.stitch_prices(dfs, "Settle", stitch_points, ctd)
exp = pd.read_csv("test/data_stitch/stitch_expected.csv", index_col=0, parse_dates=True)
exp["res"] = res
assert np.sum(exp.res - exp.Settle) < 1
def test_stitch():
stitch_points = ['2015-03-13', '2015-04-15']
dfs = []
ctd = {}
base = 'test/data_stitch/vix%s.csv'
for f in ['may', 'june', 'july']:
tmp = pd.read_csv(base % f, index_col=0, parse_dates=True)
dfs.append(tmp)
ctd[f] = tmp
res = futures.stitch_prices(dfs, 'Settle', stitch_points, ctd)
exp = pd.read_csv('test/data_stitch/stitch_expected.csv',
index_col=0,
parse_dates=True)
exp['res'] = res
assert (np.sum(exp.res - exp.Settle) < 1)
def stitch_contracts(cts_assigned, ctd, price_col):
"""
Using a date indexed contracts series and a dictionary of contracts,
creates a continuous time series.
Input
cts_assigned: Date indexed series with each date mapped to a contract in YYYYMM format
ctd: Dictionary of contracts, key is a string 'YYYYMM'. This is the universe of contracts for that instrument.
Returns
Pandas Series
"""
rolls = rolldates(cts_assigned)
rolldates2 = []
for (rolldate, from_con, to_con) in rolls:
if str(from_con) in ctd.keys() and str(to_con) in ctd.keys():
rolldates2.append((rolldate, from_con, to_con))
rolldates3 = []
for i,(rolldate, from_con, to_con) in enumerate(rolldates2):
# it is possible the rollover date is not present in both
# contracts. This rolldate is calculated arithmetically,
# remember, so it could fall on a weekend, etc. So we need to
# seek a date that is in both contracts, starting from the
# calculated rollover date. The algorithm is go back 0, go
# forward 1, back 2, so an expanding window of possible dates
# centered around the first suggestion are all tried. Since
# the first try is 0, that represents no change i.e. is the
# first suggestion itself. Whichever date works, the loop will
# exit immediately and no other tries need to be made.
for j in range(300):
rolldate += np.power(-1,j)*datetime.timedelta(days=j)
if rolldate in ctd[str(from_con)].index and rolldate in ctd[str(to_con)].index:
break
assert (j != 299)
rolldates3.append((rolldate, from_con, to_con))
rolldates4 = []; contract_ids = []
for d,f,t in rolldates3:
contract_ids.append(f)
contract_ids.append(t)
rolldates4.append(d)
contracts = [ctd[x].copy() for x in list(np.unique(contract_ids))]
df_stitched = futures.stitch_prices(contracts, 's', rolldates4, ctd)
return df_stitched
