def quantile(self, f):
qt_bound = inv_std_norm_cdf(1e-16)
output = self.sigma * np.clip(inv_std_norm_cdf(f), qt_bound,
-qt_bound) + self.mu
assert not (np.isnan(output).any()), 'function returns NaN'
assert not (np.isinf(output).any()), 'function returns inf'
return output
def dquantile_dtheta(self, f):
qt_bound = inv_std_norm_cdf(1e-16)
output = np.array([
1., 0.5 * np.clip(inv_std_norm_cdf(f), qt_bound, -qt_bound) /
self.sigma
])
assert not (np.isnan(output).any().any()), 'function returns NaN'
assert not (np.isinf(output).any().any()), 'function returns inf'
return output
def dquantile_dtheta(self, f):
qt_bound = inv_std_norm_cdf(1e-16)
output = np.array([1., 0.5 * np.clip(inv_std_norm_cdf(f), qt_bound, -qt_bound)/self.sigma])
assert not(np.isnan(output).any().any()), 'function returns NaN'
assert not(np.isinf(output).any().any()), 'function returns inf'
return output
def quantile(self, f):
qt_bound = inv_std_norm_cdf(1e-16)
output = self.sigma * np.clip(inv_std_norm_cdf(f), qt_bound, -qt_bound) + self.mu
assert not(np.isnan(output).any()), 'function returns NaN'
assert not(np.isinf(output).any()), 'function returns inf'
return output
