本文整理汇总了Python中openamos.core.data_array.DataArray.setcolumn方法的典型用法代码示例。如果您正苦于以下问题：Python DataArray.setcolumn方法的具体用法？Python DataArray.setcolumn怎么用？Python DataArray.setcolumn使用的例子？那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类openamos.core.data_array.DataArray的用法示例。
在下文中一共展示了DataArray.setcolumn方法的2个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的Python代码示例。
示例1: calc_probabilities
# 需要导入模块: from openamos.core.data_array import DataArray [as 别名]
# 或者: from openamos.core.data_array.DataArray import setcolumn [as 别名]
def calc_probabilities(self, data, choiceset):
"""
The method returns the selection probability associated with the
the different choices.
Inputs:
data - DataArray object
choiceset - DataArray object
"""
exp_expected_utilities = self.calc_exp_choice_utilities(
data, choiceset)
# missing_choices = choiceset.varnames
#spec_dict = self.specification.specification
for parent in self.parent_list:
child_names = self.specification.child_names(parent)
# calculating the sum of utilities across children in a branch
util_sum = 0
for child in child_names:
# For utils with missing values they are converted to zero
# before summing the utils across choices in a parent
# to avoid the case where missing + valid = missing
child_column = exp_expected_utilities.column(child)
child_column = child_column.filled(0)
util_sum = util_sum + child_column
# calculating the probability of children in a branch
for child in child_names:
exp_expected_utilities.setcolumn(child,
exp_expected_utilities.column(child) / util_sum)
# Dummy check to ensure that within any branch the probs add to one
prob_sum = 0
for child in child_names:
prob_sum = prob_sum + exp_expected_utilities.column(child)
for choice in self.specification.actual_choices:
parent_names = self.specification.all_parent_names(choice)
for parent in parent_names:
parent_column = exp_expected_utilities.column(parent)
choice_column = exp_expected_utilities.column(choice)
exp_expected_utilities.setcolumn(choice, choice_column *
parent_column)
self.specification.actual_choices.sort()
rows = exp_expected_utilities.rows
cols = len(self.specification.actual_choices)
probabilities = DataArray(zeros((rows, cols)),
self.specification.actual_choices,
data.index)
for choice in self.specification.actual_choices:
probabilities.setcolumn(
choice, exp_expected_utilities.column(choice))
return probabilities示例2: update_houseids
# 需要导入模块: from openamos.core.data_array import DataArray [as 别名]
# 或者: from openamos.core.data_array.DataArray import setcolumn [as 别名]
def update_houseids(self, hhldSyn, persSyn, hhldVars, persVars, highestHid):
hhldSynDataObj = DataArray(hhldSyn, hhldVars)
persSynDataObj = DataArray(persSyn, persVars)
maxFreqCol = amax(hhldSynDataObj.columns(['frequency']).data)
powFreqCol = floor(log(maxFreqCol, 10)) + 1
coefficients = {'frequency':1, 'hhid':10**powFreqCol}
newHid = hhldSynDataObj.calculate_equation(coefficients)
hhldSynDataObj.setcolumn('hhid', newHid)
newHid = persSynDataObj.calculate_equation(coefficients)
persSynDataObj.setcolumn('hhid', newHid)
hhldSynDataObj.sort([self.idSpec.hidName])
persSynDataObj.sort([self.idSpec.hidName, self.idSpec.pidName])
hidIndex_popgenH = hhldVars.index('hhid')
hidIndex_popgenP = persVars.index('hhid')
self.create_indices(persSynDataObj)
hhldSyn = hhldSynDataObj.data
persSyn = persSynDataObj.data
row = 0
for hhldIndex in self.hhldIndicesOfPersons:
firstPersonRec = hhldIndex[1]
lastPersonRec = hhldIndex[2]
#print hhldIndex[0], highestHid + 1, firstPersonRec, lastPersonRec
hhldSyn[row,hidIndex_popgenH] = highestHid + 1
persSyn[firstPersonRec:lastPersonRec,hidIndex_popgenP] = highestHid + 1
highestHid += 1
row += 1
return hhldSyn, persSyn