def parse_lutkepohl_data(path): # pragma: no cover
"""
Parse data files from Lutkepohl (2005) book
Source for data files: www.jmulti.de
"""
from collections import deque
from datetime import datetime
import pandas
import pandas.core.datetools as dt
import re
from statsmodels.compatnp.py3k import asbytes
regex = re.compile(asbytes('<(.*) (\w)([\d]+)>.*'))
lines = deque(open(path, 'rb'))
to_skip = 0
while asbytes('*/') not in lines.popleft():
#while '*/' not in lines.popleft():
to_skip += 1
while True:
to_skip += 1
line = lines.popleft()
m = regex.match(line)
if m:
year, freq, start_point = m.groups()
break
data = np.genfromtxt(path, names=True, skip_header=to_skip+1)
n = len(data)
# generate the corresponding date range (using pandas for now)
start_point = int(start_point)
year = int(year)
offsets = {
asbytes('Q') : dt.BQuarterEnd(),
asbytes('M') : dt.BMonthEnd(),
asbytes('A') : dt.BYearEnd()
}
# create an instance
offset = offsets[freq]
inc = offset * (start_point - 1)
start_date = offset.rollforward(datetime(year, 1, 1)) + inc
offset = offsets[freq]
try:
from pandas import DatetimeIndex # pylint: disable=E0611
date_range = DatetimeIndex(start=start_date, freq=offset, periods=n)
except ImportError:
from pandas import DateRange
date_range = DateRange(start_date, offset=offset, periods=n)
return data, date_range
def _null_terminate(self, s, encoding):
if PY3: # have bytes not strings, so must decode
null_byte = asbytes('\x00')
try:
s = s.lstrip(null_byte)[:s.index(null_byte)]
except:
pass
return s.decode(encoding)
else:
null_byte = asbytes('\x00')
try:
return s.lstrip(null_byte)[:s.index(null_byte)]
except:
return s
def _null_terminate(self, s, encoding):
if PY3: # have bytes not strings, so must decode
null_byte = asbytes('\x00')
try:
s = s.lstrip(null_byte)[:s.index(null_byte)]
except:
pass
return s.decode(encoding)
else:
null_byte = asbytes('\x00')
try:
return s.lstrip(null_byte)[:s.index(null_byte)]
except:
return s
def _null_terminate(self, s, encoding):
null_byte = asbytes('\x00')
if PY3:
s += null_byte
return s.encode(encoding)
else:
s += null_byte
return s
def _null_terminate(self, s, encoding):
null_byte = asbytes('\x00')
if PY3:
s += null_byte
return s.encode(encoding)
else:
s += null_byte
return s
def setup_class(self):
#SAS case
self.endog = dta3['Relief']
self.groups = dta3['Brand']
self.alpha = 0.05
self.setup_class_()
#super(self, self).setup_class_()
#CheckTuckeyHSD.setup_class_()
self.meandiff2 = sas_['mean']
self.confint2 = sas_[['lower', 'upper']].view(float).reshape((3, 2))
self.reject2 = sas_['sig'] == asbytes('***')
def setup_class(self):
#SAS case
self.endog = dta3['Relief']
self.groups = dta3['Brand']
self.alpha = 0.05
self.setup_class_()
#super(self, self).setup_class_()
#CheckTuckeyHSD.setup_class_()
self.meandiff2 = sas_['mean']
self.confint2 = sas_[['lower','upper']].view(float).reshape((3,2))
self.reject2 = sas_['sig'] == asbytes('***')
def test_missing_roundtrip():
buf = BytesIO()
dta = np.array([(np.nan, np.inf, "")],
dtype=[("double_miss", float), ("float_miss", np.float32),
("string_miss", "a1")])
writer = StataWriter(buf, dta)
writer.write_file()
buf.seek(0)
dta = genfromdta(buf, missing_flt=np.nan)
assert_(isnull(dta[0][0]))
assert_(isnull(dta[0][1]))
assert_(dta[0][2] == asbytes(""))
dta = genfromdta(os.path.join(curdir, "results/data_missing.dta"),
missing_flt=-999)
assert_(np.all([dta[0][i] == -999 for i in range(5)]))
def _write(self, to_write):
"""
Helper to call asbytes before writing to file for Python 3 compat.
"""
self._file.write(asbytes(to_write))
3 26.1
3 28.3
3 24.3
3 26.2
3 27.8'''
ss5 = '''\
2 - 3\t4.340\t0.691\t7.989\t***
2 - 1\t4.600\t0.951\t8.249\t***
3 - 2\t-4.340\t-7.989\t-0.691\t***
3 - 1\t0.260\t-3.389\t3.909\t-
1 - 2\t-4.600\t-8.249\t-0.951\t***
1 - 3\t-0.260\t-3.909\t3.389\t'''
#accommodate recfromtxt for python 3.2, requires bytes
ss = asbytes(ss)
ss2 = asbytes(ss2)
ss3 = asbytes(ss3)
ss5 = asbytes(ss5)
dta = np.recfromtxt(BytesIO(ss), names=("Rust", "Brand", "Replication"))
dta2 = np.recfromtxt(BytesIO(ss2),
names=("idx", "Treatment", "StressReduction"))
dta3 = np.recfromtxt(BytesIO(ss3), names=("Brand", "Relief"))
dta5 = np.recfromtxt(BytesIO(ss5),
names=('pair', 'mean', 'lower', 'upper', 'sig'),
delimiter='\t')
sas_ = dta5[[1, 3, 2]]
from statsmodels.stats.multicomp import (tukeyhsd, pairwise_tukeyhsd,
MultiComparison)
3 26.1
3 28.3
3 24.3
3 26.2
3 27.8'''
ss5 = '''\
2 - 3 4.340 0.691 7.989 ***
2 - 1 4.600 0.951 8.249 ***
3 - 2 -4.340 -7.989 -0.691 ***
3 - 1 0.260 -3.389 3.909 -
1 - 2 -4.600 -8.249 -0.951 ***
1 - 3 -0.260 -3.909 3.389 '''
#accommodate recfromtxt for python 3.2, requires bytes
ss = asbytes(ss)
ss2 = asbytes(ss2)
ss3 = asbytes(ss3)
ss5 = asbytes(ss5)
dta = np.recfromtxt(BytesIO(ss), names=("Rust","Brand","Replication"))
dta2 = np.recfromtxt(BytesIO(ss2), names = ("idx", "Treatment", "StressReduction"))
dta3 = np.recfromtxt(BytesIO(ss3), names = ("Brand", "Relief"))
dta5 = np.recfromtxt(BytesIO(ss5), names = ('pair', 'mean', 'lower', 'upper', 'sig'), delimiter='\t')
sas_ = dta5[[1,3,2]]
from statsmodels.stats.multicomp import (tukeyhsd, pairwise_tukeyhsd,
MultiComparison)
#import statsmodels.sandbox.stats.multicomp as multi
#print tukeyhsd(dta['Brand'], dta['Rust'])
def _write(self, to_write):
"""
Helper to call asbytes before writing to file for Python 3 compat.
"""
self._file.write(asbytes(to_write))