本文整理汇总了Python中openamos.core.data_array.DataArray.columns方法的典型用法代码示例。如果您正苦于以下问题：Python DataArray.columns方法的具体用法？Python DataArray.columns怎么用？Python DataArray.columns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.columns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: TestReconcileModel
# 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 columns [as 别名]
class TestReconcileModel(unittest.TestCase):
def setUp(self):
self.data = genfromtxt("/home/kkonduri/simtravel/test/mag_zone/schedule_txt.csv", delimiter=",", dtype=int)
colNames = [
"houseid",
"personid",
"scheduleid",
"activitytype",
"locationid",
"starttime",
"endtime",
"duration",
]
self.actSchedules = DataArray(self.data, colNames)
def test_retrieve_loop_ids(self):
houseIdsCol = self.actSchedules.columns(["houseid"]).data
houseIdsUnique = unique(houseIdsCol)
print houseIdsUnique
for hid in houseIdsUnique:
schedulesRowsIndForHh = houseIdsCol == hid
schedulesForHh = self.actSchedules.rowsof(schedulesRowsIndForHh)
pIdsCol = schedulesForHh.columns(["personid"]).data
pIdsUnique = unique(pIdsCol)
for pid in pIdsUnique:
schedulesRowIndForPer = pIdsCol == pid
schedulesForPerson = schedulesForHh.rowsof(schedulesRowIndForPer)
# print 'Raw schedules for hid:%s and pid:%s' %(hid, pid)
# print schedulesForPerson
activityList = []
for sch in schedulesForPerson.data:
scheduleid = sch[2]
activitytype = sch[3]
locationid = sch[4]
starttime = sch[5]
endtime = sch[6]
duration = sch[7]
actepisode = ActivityEpisode(scheduleid, activitytype, locationid, starttime, endtime, duration)
activityList.append(actepisode)
personObject = Person(hid, pid)
personObject.add_and_reconcile_episodes(activityList)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 columns [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