本文整理汇总了Python中SSUtilities.writeText方法的典型用法代码示例。如果您正苦于以下问题：Python SSUtilities.writeText方法的具体用法？Python SSUtilities.writeText怎么用？Python SSUtilities.writeText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SSUtilities的用法示例。
在下文中一共展示了SSUtilities.writeText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: report
# 需要导入模块: import SSUtilities [as 别名]
# 或者: from SSUtilities import writeText [as 别名]
def report(self, fileName = None):
"""Generate Text and Graphical Output."""
if fileName:
f = UTILS.openFile(fileName, "w")
UTILS.writeText(f, "{0}\n".format(self.coefTable))
UTILS.writeText(f, "{0}\n".format(self.diagTable))
UTILS.writeText(f, "{0}".format(self.interpretTable))
f.close()
else:
ARCPY.AddMessage(self.coefTable)
ARCPY.AddMessage(self.diagTable)
ARCPY.AddMessage(self.interpretTable)
#### Report if Bad Probabilities Found ####
if self.badProbs:
ARCPY.AddIDMessage("WARNING", 738)示例2: runModels
# 需要导入模块: import SSUtilities [as 别名]
# 或者: from SSUtilities import writeText [as 别名]
#.........这里部分代码省略.........
#### Loop Through All Combinations ####
modelCount = 0
emptyTabValues = [""] * ( self.maxIndVars - choose )
perfectMultiModels = []
for combo in comboGenerator:
#### Create Design Matrix for Given Combination ####
columns = [0] + list(combo)
comboX = self.x[0:,columns]
#### Get Model Info for given Combination ####
N, K = comboX.shape
varNameList = [ self.independentVars[j-1] for j in combo ]
varNameListInt = ["Intercept"] + varNameList
modelAll = self.dependentVar + " ~ "
modelAll += " + ".join(varNameListInt)
modelID = str(K) + ":" + str(modelCount)
#### Run Linear Regression ####
runModel = self.calculate(comboX)
#### Set Near/Perfect Multicoll Bool ####
nearPerfectBool = False
if K > 2 and runModel:
nearPerfectBool = NUM.any(abs(self.vifVal) >= 1000)
if (not runModel) or nearPerfectBool:
#### Perfect Multicollinearity ####
#### Unable to Invert the Matrix ####
perfectMultiModels.append(modelAll)
else:
#### Keep Track of Total Number of Models Ran ####
modelCount += 1
self.sumRuns += 1
residuals = self.residuals.flatten()
#### Evaluate p-values ####
if self.BPProb < .1:
#### Use Robust Coefficients ####
pValsOut = self.pValsRob[1:]
else:
pValsOut = self.pVals[1:]
coefOut = self.coef[1:]
#### Process Largest VIF Values ####
if K > 2:
for ind, varName in enumerate(varNameList):
vif = self.vifVal[ind]
previousVIF = self.globalVifVals[varName]
if vif > previousVIF:
self.globalVifVals[varName] = vif
#### Set OLS Result ####
res = OLSResult(modelID, varNameList, coefOut, pValsOut,
self.vifVal, self.r2Adj, self.aicc,
self.JBProb, self.BPProb,
allMIPass = self.allMIPass)
#### Evaluate Jarque-Bera Stat ####
keep = self.pushPopJB(res, self.residuals.flatten())
boolReport = rh.evaluateResult(res, residuals, keep = keep)
r2Bool, pvBool, vifBool, jbBool, giBool, keepBool = boolReport
#### Add Booleans for End Total Summary ####
boolResult = [r2Bool, pvBool, vifBool, jbBool]
self.boolResults += boolResult
#### Delete OLS Instance if Not Necessary For Summary ####
if not keepBool:
del res
#### Run Moran's I for Highest Adj. R2 ####
r2ResultList = rh.runR2Moran()
self.neighborWarn = True
#### Add Results to Report File ####
result2Print = rh.report()
UTILS.writeText(fo, result2Print)
if len(perfectMultiModels):
self.perfectMultiWarnBool = True
ARCPY.AddIDMessage("WARNING", 1304)
for modelStr in perfectMultiModels:
ARCPY.AddIDMessage("WARNING", 1176, modelStr)
#### Add Choose Run to Result Dictionary ####
self.resultDict[choose] = rh
#### Run Moran's I on Best Jarque-Bera ####
self.createJBReport()
#### Final Moran Stats ####
self.getMoranStats()
#### Ending Summary ####
self.endSummary()
UTILS.writeText(fo, self.fullReport)
fo.close()