diff --git a/PEUQSE/InverseProblem.py b/PEUQSE/InverseProblem.py index d027f304..a81cba21 100644 --- a/PEUQSE/InverseProblem.py +++ b/PEUQSE/InverseProblem.py @@ -1704,6 +1704,9 @@ def doSinglePoint(self, discreteParameterVector=None, objectiveFunction='logP'): #objectiveFunction can be 'logP' or 'SSR' if type(discreteParameterVector)==type(None): #If somebody did not feed a specific vector, we take the initial guess. discreteParameterVector = self.UserInput.InputParameterInitialGuess + if self.reducedParameterSpaceOn: #if reduced parameter space is on, we need to use a reduced discreteParameterVector + reducedIndices = self.UserInput.model['reducedParameterSpace'] + discreteParameterVector = returnReducedIterable(discreteParameterVector, reducedIndices) if objectiveFunction=='logP': self.map_parameter_set = discreteParameterVector self.map_logP = self.getLogP(discreteParameterVector) diff --git a/PEUQSE/UserInput.py b/PEUQSE/UserInput.py index 774871d0..7a0b1511 100644 --- a/PEUQSE/UserInput.py +++ b/PEUQSE/UserInput.py @@ -13,7 +13,7 @@ responses['responses_observed_uncertainties'] = [] #Normally should not be blank, and should be provided with the same structure as responses_observed. One standard deviation of uncertainty should be provided for each response value. To set the responses_observed_uncertainties to zero, this variable or the values inside must really be set equal to 0. A blank list will not result in zeros and will autogenerate uncertainties relative to the responses_observed. A full covariance matrix can alternatively be used, but not all features are compatible with a full covariance matrix. If using a full covariance matrix, like in example 7j, please note that only the 'bottom left' of the covariance matrix is used, such that np.array([[2,1],[1,3]]) is actually the same as np.array([[2,-500],[1,3]]). Here, the -500 would be ignored. responses['responses_observed_max_covmat_size'] = 100 #The user should nor normally change this. if any response has more datapoints than this, that response will have variances evaluated separately (only the diagonal of the covmat) in a way which changes the computational cost to linear scaling. For most regular computers around Jan 25 2020, the crossover happens after a few hundred points, so this variable has been set to have a default value of 100. responses['responses_observed_weighting'] = [] #This feature is not recommended for normal use. If used, the input should be the same shape as responses_observed_uncertainties. This adds coefficients to responses_observed_uncertainties based on 1/(weighting)^0.5 to 'back propagate' any additional weighting terms (in analogy to variance weighted SSR). If the responses_observed_uncertainties are appropriately defined, this should generally not be needed. This feature is only compatible when responses_observed_uncertainties consists of standard deviations rather than a covariance matrix. -responses['reducedResponseSpace'] = [] #If there are multiple responses, the user can ignore some of the responses during parameter estimation. +responses['reducedResponseSpace'] = [] #If there are multiple responses, the user can ignore some of the responses during parameter estimation. All parameters are still used as inputs, and some of the output files will only reflect the reduced parameters. When this feature is on, doSinglePoint will still take the full set of parameters. However, getLogP should not be called directly when this feature is on (as it would require receiving a reduced parmeter vector). responses['independent_variables_values'] = [] #This field is mainly for design of experiments, but can be used as a type of connected variables for other cases also. responses['independent_variables_names'] = [] #names associated with independent_variables_values. responses['num_responses'] = 'auto' #'auto' is recommended, though an integer can be put in directly. diff --git a/setup.py b/setup.py index 04204b33..409c0c84 100644 --- a/setup.py +++ b/setup.py @@ -21,7 +21,7 @@ EMAIL = 'AditySavara2008@u.northwestern.edu' #Eric A. Walker is a co-author and can be reached at WALKER, ERIC AUTHOR = 'Aditya Savara' REQUIRES_PYTHON = '>=3.5.0' -VERSION = '1.1.7' +VERSION = '1.1.8' LICENSE = 'BSD-3-Clause' # What packages are required for this module to be executed?