Datasets:
thisisanshgupta
/
Pycode

Dataset card Data Studio Files
xet
 Community
text
stringlengths
0
828
Additional Parameters
----------------------
{0}
""""""
return _make_rank(self, n, mu, sigma, crit=crit, upper=upper,
xtol=xtol)"
3895,"def fit_mle(self, data, b=None):
""""""%(super)s
Additional Parameters
----------------------
b : float
The upper limit of the distribution
""""""
# Take mean of data as MLE of distribution mean, then calculate p
mu = np.mean(data)
if not b:
b = np.sum(data)
lam = _expon_solve_lam_from_mu_vect(mu, b)
# Just return float, not len 1 array
if len(np.atleast_1d(lam)) == 1:
return float(lam), b
else:
return lam, b"
3896,"def fit_mle(self, data, fix_mean=False):
""""""%(super)s
Additional Parameters
----------------------
fix_mean : bool
Default False. If True, fixes mean before optimizing sigma
""""""
if not fix_mean:
sigma, _, scale = stats.lognorm.fit(data, floc=0)
return np.log(scale), sigma
else:
mean = np.mean(data)
# MLE fxn to be optmimized
mle = lambda sigma, x, mean: -1 *\
np.sum(self._pdf_w_mean(x, mean, sigma))
sigma = optim.fmin(mle, np.array([np.std(np.log(data), ddof=1)]),
args=(data, mean), disp=0)[0]
return self.translate_args(mean, sigma)"
3897,"def _pdf_w_mean(self, x, mean, sigma):
""""""
Calculates the pdf of a lognormal distribution with parameters mean
and sigma
Parameters
----------
mean : float or ndarray
Mean of the lognormal distribution
sigma : float or ndarray
Sigma parameter of the lognormal distribution
Returns
-------
: float or ndarray
pdf of x
""""""
# Lognorm pmf with mean for optimization
mu, sigma = self.translate_args(mean, sigma)
return self.logpdf(x, mu, sigma)"
3898,"def union_join(left, right, left_as='left', right_as='right'):
""""""
Join function truest to the SQL style join. Merges both objects together in a sum-type,
saving references to each parent in ``left`` and ``right`` attributes.
>>> Dog = namedtuple('Dog', ['name', 'woof', 'weight'])
>>> dog = Dog('gatsby', 'Ruff!', 15)
>>> Cat = namedtuple('Cat', ['name', 'meow', 'weight'])
>>> cat = Cat('pleo', 'roooowwwr', 12)
>>> catdog = union_join(cat, dog, 'cat', 'dog')
>>> catdog.name
pleo
>>> catdog.woof
Ruff!
>>> catdog.dog.name
gatsby
:param left: left object to be joined with right
:param right: right object to be joined with left
:return: joined object with attrs/methods from both parents available
""""""
attrs = {}
attrs.update(get_object_attrs(right))
attrs.update(get_object_attrs(left))
attrs[left_as] = left
attrs[right_as] = right