def _get_ewmcorr(X, Y):
# X and Y have the same structure (and NaNs) when called from _flex_binary_moment()
return_hook, x_values = _process_data_structure(X)
return_hook, y_values = _process_data_structure(Y)
cov = algos.ewmcov(x_values, y_values, com, int(adjust), int(ignore_na), int(min_periods), 1)
x_var = algos.ewmcov(x_values, x_values, com, int(adjust), int(ignore_na), int(min_periods), 1)
y_var = algos.ewmcov(y_values, y_values, com, int(adjust), int(ignore_na), int(min_periods), 1)
corr = cov / _zsqrt(x_var * y_var)
return return_hook(corr)
def _get_ewmcorr(X, Y):
# X and Y have the same structure (and NaNs) when called from _flex_binary_moment()
return_hook, x_values = _process_data_structure(X)
return_hook, y_values = _process_data_structure(Y)
cov = algos.ewmcov(x_values, y_values, com, int(adjust), int(ignore_na), int(min_periods), 1)
x_var = algos.ewmcov(x_values, x_values, com, int(adjust), int(ignore_na), int(min_periods), 1)
y_var = algos.ewmcov(y_values, y_values, com, int(adjust), int(ignore_na), int(min_periods), 1)
corr = cov / _zsqrt(x_var * y_var)
return return_hook(corr)
def _get_cov(X, Y):
X = self._shallow_copy(X)
Y = self._shallow_copy(Y)
cov = algos.ewmcov(X._prep_values(), Y._prep_values(), self.com,
int(self.adjust), int(self.ignore_na),
int(self.min_periods), int(bias))
return X._wrap_result(cov)
def _get_cov(X, Y):
X = self._shallow_copy(X)
Y = self._shallow_copy(Y)
cov = algos.ewmcov(X._prep_values(), Y._prep_values(), self.com,
int(self.adjust), int(self.ignore_na),
int(self.min_periods), int(bias))
return X._wrap_result(cov)
def f(arg):
return algos.ewmcov(arg,
arg,
self.com,
int(self.adjust),
int(self.ignore_na),
int(self.min_periods),
int(bias))
def _ewmvar(v):
return algos.ewmcov(v, v, com, int(adjust), int(ignore_na),
int(min_periods), int(bias))
def _ewmvar(v):
return algos.ewmcov(v, v, com, int(adjust), int(ignore_na), int(min_periods), int(bias))
def _cov(x, y):
return algos.ewmcov(x, y, self.com, int(self.adjust),
int(self.ignore_na), int(self.min_periods),
1)
def _cov(x, y):
return algos.ewmcov(x, y, self.com, int(self.adjust),
int(self.ignore_na), int(self.min_periods),
1)
def f(arg):
return algos.ewmcov(arg, arg, self.com, int(self.adjust),
int(self.ignore_na), int(self.min_periods),
int(bias))