def calc_errorcomponent(self, variance_norm, variance_halfnorm,
vertex, size, seed):
"""
The method returns the contribution of the error component in the
calculation of the predicted value for the different choices.
Inputs:
variance_norm - numeric value (variance of the normal portion of error)
variance_halfnorm - numeric value (variance of the half normal portion of
error)
vertex - string (the vertext to predict -- start/end)
size - numeric value (number of rows)
"""
dist = RandomDistribution(seed=seed)
err_halfnorm = dist.return_half_normal_variables(location=0, scale=variance_halfnorm**0.5, size=size)
dist = RandomDistribution(seed=seed)
err_norm = dist.return_normal_variables(location=0, scale=variance_norm**0.5, size=size)
if vertex == 'start':
return err_norm + err_halfnorm
if vertex == 'end':
return err_norm - err_halfnorm
def calc_errorcomponent(self, variance_norm, variance_halfnorm, vertex,
size, seed):
"""
The method returns the contribution of the error component in the
calculation of the predicted value for the different choices.
Inputs:
variance_norm - numeric value (variance of the normal portion of error)
variance_halfnorm - numeric value (variance of the half normal portion of
error)
vertex - string (the vertext to predict -- start/end)
size - numeric value (number of rows)
"""
dist = RandomDistribution(seed=seed)
err_halfnorm = dist.return_half_normal_variables(
location=0, scale=variance_halfnorm**0.5, size=size)
dist = RandomDistribution(seed=seed)
err_norm = dist.return_normal_variables(location=0,
scale=variance_norm**0.5,
size=size)
if vertex == 'start':
return err_norm + err_halfnorm
if vertex == 'end':
return err_norm - err_halfnorm
def calc_halfnormal_error(self, threshold, limit, seed, size): """ A draw from a half normal distribution with 3 s.d. = abs(threshold - limit) For smoothing about the boundaries """ dist = RandomDistribution(seed=seed) assu_scale = abs(threshold-limit)/3.0 err_halfnorm = dist.return_half_normal_variables(location=0, scale=assu_scale, size=size) chkRowsMore = err_halfnorm > abs(threshold-limit) err_halfnorm[chkRowsMore] = abs(threshold-limit) return err_halfnorm
