source: issm/trunk-jpl/src/m/classes/qmu/uniform_uncertain.py@ 24261

import numpy as np
#from vlist_write import *
from MatlabArray import *


class uniform_uncertain(object):
    '''
  definition for the uniform_uncertain class.

  [uuv] = uniform_uncertain.uniform_uncertain(args)
   uuv = uniform_uncertain()

  where the required args are:
    descriptor    (str, description, '')
    lower         (float, lower bound, -np.Inf)
    upper         (float, upper bound, np.Inf)

  note that zero arguments constructs a default instance, one
  argument of the class copies the instance, and three or more
  arguments constructs a new instance from the arguments.
'''

    def __init__(self):
        self.descriptor = ''
        self.lower = -np.Inf
        self.upper = np.Inf

    @staticmethod
    def uniform_uncertain(*args):
        nargin = len(args)

        # create a default object
        if nargin == 0:
            return uniform_uncertain()

        # copy the object
        elif nargin == 1:
            if isinstance(args[0], uniform_uncertain):
                uuv = args[0]
            else:
                raise RuntimeError('Object ' + str(args[0]) + ' is a ' + str(type(args[0])) + ' class object, not "uniform_uncertain".')

        # not enough arguments
        elif nargin == 2:
            raise RuntimeError('Construction of "uniform_uncertain" class object requires at least 3 inputs.')

        # create the object from the input
        else:
            # leaving this here in case it becomes important in the future
            #asizec = array_size(*args[0:min(nargin, 3)])
            #uuv = [uniform_uncertain() for i in range(asizec[0]) for j in range(asizec[1])]
            uuv = uniform_uncertain()
            uuv.descriptor = str(args[0])
            uuv.lower = args[1]
            uuv.upper = args[2]
        if (nargin > 3):
            print('WARNING: uniform_uncertain:extra_arg: Extra arguments for object of class ' + type(uuv) + '.')

        return [uuv]

    def __repr__(self):
        # display an individual object
        string = '\n'
        string += 'class "uniform_uncertain" object = \n'
        string += '    descriptor: ' + str(self.descriptor) + '\n'
        string += '         lower: ' + str(self.lower) + '\n'
        string += '         upper: ' + str(self.upper) + '\n'

        return string

    # from here on, uuv is either a single, or a 1d vector of, uniform_uncertain

    @staticmethod
    def prop_desc(uuv, dstr):
        if type(uuv) not in [list, np.ndarray]:
            if uuv.descriptor != '' or type(uuv.descriptor) != str:
                desc = str(uuv.descriptor)
            elif dstr != '':
                desc = str(dstr)
            else:
                desc = 'uuv'
            return desc

        desc = ['' for i in range(np.size(uuv))]
        for i in range(np.size(uuv)):
            if uuv[i].descriptor != '' or type(uuv[i].descriptor) != str:
                desc[i] = str(uuv[i].descriptor)
            elif dstr != '':
                desc[i] = str(dstr) + str(string_dim(uuv, i, 'vector'))
            else:
                desc[i] = 'uuv' + str(string_dim(uuv, i, 'vector'))

            desc = allempty(desc)

        return desc

    @staticmethod
    def prop_initpt(uuv):
        initpt = []
        return initpt

    @staticmethod
    def prop_lower(uuv):
        if type(uuv) not in [list, np.ndarray]:
            return uuv.lower

        lower = np.zeros(np.size(uuv))
        for i in range(np.size(uuv)):
            lower[i] = uuv[i].lower

        lower = allequal(lower, -np.Inf)

        return lower

    @staticmethod
    def prop_upper(uuv):
        if type(uuv) not in [list, np.ndarray]:
            return uuv.upper

        upper = np.zeros(np.size(uuv))
        for i in range(np.size(uuv)):
            upper[i] = uuv[i].upper

        upper = allequal(upper, np.Inf)

        return upper

    @staticmethod
    def prop_mean(uuv):
        mean = []
        return mean

    @staticmethod
    def prop_stddev(uuv):
        stddev = []
        return stddev

    @staticmethod
    def prop_initst(uuv):
        initst = []
        return initst

    @staticmethod
    def prop_stype(uuv):
        stype = []
        return stype

    @staticmethod
    def prop_scale(uuv):
        scale = []
        return scale

    @staticmethod
    def dakota_write(fidi, dvar):
        # collect only the variables of the appropriate class
        uuv = [struc_class(i, 'uniform_uncertain', 'uuv') for i in dvar]
        # possible namespace pollution, the above import seems not to work
        from vlist_write import vlist_write
        # write variables
        vlist_write(fidi, 'uniform_uncertain', 'uuv', uuv)