def testReplaceMissingValues(self):
eCsvReader = EgoCsvReader()
X = numpy.array([[1,2], [5,6], [0, 3]])
Xnew = eCsvReader.replaceMissingValues(X)
self.assertTrue((Xnew == numpy.array([[1,2], [5,6], [3, 3]])).all())
def testReplaceMissingValues2(self):
eCsvReader = EgoCsvReader()
numpy.random.seed(0)
X = numpy.array([[1,2], [5,6], [0, 3]])
Xnew = eCsvReader.replaceMissingValues2(X)
self.assertTrue((Xnew == numpy.array([[1,2], [5,6], [10, 3]])).all())
def testGenerateReceivers(self):
eCsvReader = EgoCsvReader()
numAlters = 10
numPartialFields = 11
alterFields = numPartialFields + 2
alterFieldIndices = list(range(0, numPartialFields))
egoAlterArray = numpy.zeros((2, 45))
alterArray = numpy.zeros((numAlters, alterFields))
egoAlterArray[0, 0:11] = [2, 12, 1, 0, 0, 0, 0, 0, 0, 0, 1]
egoAlterArray[0, 11:22] = [1, 11, 1, 0, 0, 0, 0, 0, 0, 0, 1]
egoAlterArray[1, 0:11] = [5, 6, 1, 0, 0, 0, 0, 0, 0, 0, 3]
alterArray[0, :] = [2, 12, 1, 0, 0, 0, 0, 0, 0, 0, 1, 12, 13]
alterArray[1, :] = [1, 11, 1, 0, 0, 0, 0, 0, 0, 0, 1, 84, 12]
alterArray[2, :] = [2, 12, 1, 0, 0, 0, 1, 0, 0, 0, 0, 4, 9]
alterArray[4, :] = [5, 6, 1, 0, 0, 0, 0, 0, 0, 0, 3, 34, 12]
generatedAltersArray2 = numpy.zeros((3, alterFields))
generatedAltersArray2[0, :] = alterArray[0, :]
generatedAltersArray2[1, :] = alterArray[1, :]
generatedAltersArray2[2, :] = alterArray[4, :]
(generatedAltersArray, egoIndices, alterIndices) = eCsvReader.generateReceivers(egoAlterArray, alterArray, alterFieldIndices)
self.assertTrue((egoIndices == numpy.array([0,0,1])).all())
self.assertTrue((alterIndices == numpy.array([0,1,4])).all())
self.assertTrue((generatedAltersArray == generatedAltersArray2).all())
#2nd test
egoAlterArray[1, 11:22] = [2, 12, 1, 0, 0, 0, 1, 0, 0, 0, 0]
(generatedAltersArray, egoIndices, alterIndices) = eCsvReader.generateReceivers(egoAlterArray, alterArray, alterFieldIndices)
generatedAltersArray2 = numpy.zeros((4, alterFields))
generatedAltersArray2[0, :] = alterArray[0, :]
generatedAltersArray2[1, :] = alterArray[1, :]
generatedAltersArray2[2, :] = alterArray[4, :]
generatedAltersArray2[3, :] = alterArray[2, :]
self.assertTrue((egoIndices == numpy.array([0,0,1,1])).all())
self.assertTrue((alterIndices == numpy.array([0,1,4,2])).all())
self.assertTrue((generatedAltersArray == generatedAltersArray2).all())
def testReadFile(self):
eCsvReader = EgoCsvReader()
#logging.debug(os.getcwd())
dir = PathDefaults.getDataDir()
fileName = dir + "test/TestData.csv"
questionIds = [("Q14", 0), ("Q12", 1) , ("Q2", 0)]
missing = 1
(X, titles) = eCsvReader.readFile(fileName, questionIds, missing)
X2 = numpy.zeros((10, 3))
X2[0, :] = [0.621903386,0.608560354,0.33290608]
X2[1, :] = [0.318548924,0.402390713,0.129956291]
X2[2, :] = [0.956658404,0.344317772,0.680386616]
X2[3, :] = [0.267607668,0.119647983,0.116893619]
X2[4, :] = [0.686589498,0.402390713,0.426789174]
X2[5, :] = [0.373575769,0.025846789,0.797125005]
X2[6, :] = [0.493793948,0.402390713,0.990507109]
X2[7, :] = [0.524534585,0.525169385,0.772917183]
X2[8, :] = [0.339055395,0.402390713,0.684788001]
X2[9, :] = [0.997774183,0.790801992,0.643252009]
self.assertAlmostEquals(numpy.linalg.norm(X-X2),0, places=6)
def checkDistributions():
matFileName = "../../data/EgoAlterTransmissions.mat"
examplesList = ExamplesList.readFromMatFile(matFileName)
numFeatures = examplesList.getDataFieldSize("X", 1)
X = examplesList.getDataField("X")[:, 0:numFeatures/2]
Z = examplesList.getDataField("X")[:, numFeatures/2:numFeatures]
y = examplesList.getDataField("y")
A = Z[y==-1, :]
#Now load directly from the CSV file
#Learn the distribution of the egos
eCsvReader = EgoCsvReader()
egoFileName = "../../data/EgoData.csv"
alterFileName = "../../data/AlterData.csv"
egoQuestionIds = eCsvReader.getEgoQuestionIds()
alterQuestionIds = eCsvReader.getAlterQuestionIds()
(X2, titles) = eCsvReader.readFile(egoFileName, egoQuestionIds)
X2[:, eCsvReader.ageIndex] = eCsvReader.ageToCategories(X2[:, eCsvReader.ageIndex])
(mu, sigma) = Util.computeMeanVar(X)
(mu2, sigma2) = Util.computeMeanVar(X2)
(mu3, sigma3) = Util.computeMeanVar(Z)
(mu4, sigma4) = Util.computeMeanVar(A)
#Seems okay. Next check alters
print(("Mean " + str(mu - mu4)))
print(("Variance " + str(numpy.diag(sigma - sigma4))))
"""
Analysis between the Egos in EgoData.csv and those in EgoAlterTransmissions.mat
reveals that the distributions match closely. The main differences are
in the means and variances in Q44A - D, but this isn't too suprising.
"""
"""
def testCsvRowToVector(self):
eCsvReader = EgoCsvReader()
csvRow = ["1", "5", "2", "12", ""]
csvRow2 = ["2", "4", "8", "2", "1"]
csvTitles = ["A", "B", "C", "D", "E"]
csvErrorTitles1 = ["A", "B", "C", "D", "E" ,"F"]
csvErrorTitles2 = ["A", "B", "C"]
questionIds = [("B", 0), ("A", 0), ("E", 1)]
questionIdsError1 = [("B", 0), ("A", 0), ("E", 0)]
questionIdsError2 = [("B", 0), ("A", 0), ("Z", 1)]
self.assertRaises(ValueError, eCsvReader.csvRowToVector, csvRow, questionIds, csvErrorTitles1)
self.assertRaises(ValueError, eCsvReader.csvRowToVector, csvRow, questionIds, csvErrorTitles2)
v = eCsvReader.csvRowToVector(csvRow, questionIds, csvTitles)
self.assertTrue((v==numpy.array([5, 1, 0])).all())
v = eCsvReader.csvRowToVector(csvRow2, questionIds, csvTitles)
self.assertTrue((v==numpy.array([4, 2, 1])).all())
self.assertRaises(ValueError, eCsvReader.csvRowToVector, csvRow, questionIdsError1, csvTitles)
self.assertRaises(ValueError, eCsvReader.csvRowToVector, csvRow, questionIdsError2, csvTitles)
examplesFileName = SvmInfoExperiment.getExamplesFileName()
sampleSize = 86755
svmEgoSimulator = SvmEgoSimulator(examplesFileName)
preprocessor = svmEgoSimulator.getPreProcessor()
centerValues = preprocessor.getCentreVector()
svmParamsFileName = SvmInfoExperiment.getSvmParamsFileName() + "Linear.mat"
logging.info("Using SVM params from file " + svmParamsFileName)
C, kernel, kernelParamVal, errorCost = SvmInfoExperiment.loadSvmParams(svmParamsFileName)
svmEgoSimulator.trainClassifier(C, kernel, kernelParamVal, errorCost, sampleSize)
weights, b = svmEgoSimulator.getWeights()
numpy.set_printoptions(precision=3)
#Print the weights then their sorted values by indices and then value
sortedWeightsInds = numpy.flipud(numpy.argsort(abs(weights)))
sortedWeights = numpy.flipud(weights[numpy.argsort(abs(weights))])
egoCsvReader = EgoCsvReader()
questionIds = egoCsvReader.getEgoQuestionIds()
questionIds.extend(egoCsvReader.getAlterQuestionIds())
print(weights)
numRankedItems = 20
for i in range(0,numRankedItems):
print((str(centerValues[sortedWeightsInds[i]]) + " & " + questionIds[sortedWeightsInds[i]][0] + " & " + str("%.3f" % sortedWeights[i]) + "\\\\"))
print(b)
#A second set of parameters
p = float(30)/numVertices
generator = ErdosRenyiGenerator(p)
simulationRepetitions = 5
maxIterations = 3
sampleSize = SvmInfoExperiment.getNumSimulationExamples()
#sampleSize = 1000
svmParamsFile = SvmInfoExperiment.getSvmParamsFileName()
CVal, kernel, kernelParamVal, errorCost = SvmInfoExperiment.loadSvmParams(svmParamsFile)
simulator = SvmEgoSimulator(examplesFileName)
simulator.trainClassifier(CVal, kernel, kernelParamVal, errorCost, sampleSize)
egoCsvReader = EgoCsvReader()
genderIndex = egoCsvReader.genderIndex
ageIndex = egoCsvReader.ageIndex
incomeIndex = egoCsvReader.incomeIndex
townSizeIndex = egoCsvReader.townSizeIndex
foodRiskIndex = egoCsvReader.foodRiskIndex
experienceIndex = egoCsvReader.experienceIndex
internetFreqIndex = egoCsvReader.internetFreqIndex
peopleAtWorkIndex = egoCsvReader.peopleAtWorkIndex
educationIndex = egoCsvReader.educationIndex
professionIndices = numpy.zeros(egoCsvReader.numProfessions)
for i in range(1, egoCsvReader.numProfessions+1):
egoQuestionIds = egoCsvReader.getEgoQuestionIds()
"""
if __name__ == "__main__":
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
numpy.set_printoptions(precision=4, suppress=True)
#checkDistributions()
"""
We will read ego and alters data, and check they have the same values.
"""
egoFileName = "../../data/EgoData.csv"
alterFileName = "../../data/AlterData.csv"
eCsvReader = EgoCsvReader()
egoQuestionIds = eCsvReader.getEgoQuestionIds()
alterQuestionIds = eCsvReader.getAlterQuestionIds()
missing = 0
(egoX, titles) = eCsvReader.readFile(egoFileName, egoQuestionIds, missing)
egoX[:, eCsvReader.ageIndex] = eCsvReader.ageToCategories(egoX[:, eCsvReader.ageIndex])
(alterX, titles) = eCsvReader.readFile(alterFileName, alterQuestionIds, missing)
alterX[:, eCsvReader.ageIndex] = eCsvReader.ageToCategories(alterX[:, eCsvReader.ageIndex])
numFeatures = egoX.shape[1]
numEgoExamples = egoX.shape[0]
numAlterExamples = alterX.shape[0]
for i in range(0, numFeatures):
def testReadFiles(self):
p = 0.5
eCsvReader = EgoCsvReader()
eCsvReader.setP(p)
dataDir = PathDefaults.getDataDir() + "infoDiffusion/"
egoFileName = dataDir + "EgoData3.csv"
alterFileName = dataDir + "AlterData10.csv"
examplesList, egoIndicesR, alterIndices, egoIndicesNR, alterIndicesNR = eCsvReader.readFiles(egoFileName, alterFileName)
#logging.debug(examplesList.getDataField("X"))
#Read in the ego and alter arrays
(egoArray, _) = eCsvReader.readFile(egoFileName, eCsvReader.getEgoQuestionIds())
(alterArray, _) = eCsvReader.readFile(alterFileName, eCsvReader.getAlterQuestionIds())
#Make up the correct results
numFeatures = examplesList.getDataFieldSize("X", 1)
numPersonFeatures = numFeatures/2
#Note: no alters in this case
numTransmissons = 6
X2 = numpy.zeros((numTransmissons, numFeatures))
y2 = numpy.zeros((numTransmissons, 1))
X2[0, 0:numPersonFeatures] = egoArray[0, :]
X2[0, numPersonFeatures:numFeatures] = egoArray[1, :]
y2[0, 0] = -1
X2[1, 0:numPersonFeatures] = egoArray[0, :]
X2[1, numPersonFeatures:numFeatures] = egoArray[2, :]
y2[1, 0] = -1
X2[2, 0:numPersonFeatures] = egoArray[1, :]
X2[2, numPersonFeatures:numFeatures] = egoArray[0, :]
y2[2, 0] = -1
X2[3, 0:numPersonFeatures] = egoArray[1, :]
X2[3, numPersonFeatures:numFeatures] = egoArray[2, :]
y2[3, 0] = -1
X2[4, 0:numPersonFeatures] = egoArray[2, :]
X2[4, numPersonFeatures:numFeatures] = egoArray[0, :]
y2[4, 0] = -1
X2[5, 0:numPersonFeatures] = egoArray[2, :]
X2[5, numPersonFeatures:numFeatures] = egoArray[1, :]
y2[5, 0] = -1
self.assertTrue((X2 == examplesList.getDataField("X")).all())
self.assertTrue((y2 == examplesList.getDataField("y")).all())
#Second test
#================
#I modified EgoData3 so that person 2 is the same age as person 1, and
# hence a homophile of 1. She (2) is excluded from the non-receivers, since
#she is a homophile of person 1.
p = 0
eCsvReader = EgoCsvReader()
eCsvReader.setP(p)
examplesList, egoIndicesR, alterIndices, egoIndicesNR, alterIndicesNR = eCsvReader.readFiles(egoFileName, alterFileName)
numTransmissons = 5
X2 = numpy.zeros((numTransmissons, numFeatures))
y2 = numpy.zeros((numTransmissons, 1))
X2[0, 0:numPersonFeatures] = egoArray[0, :]
X2[0, numPersonFeatures:numFeatures] = egoArray[2, :]
y2[0, 0] = -1
X2[1, 0:numPersonFeatures] = egoArray[1, :]
X2[1, numPersonFeatures:numFeatures] = egoArray[0, :]
y2[1, 0] = -1
X2[2, 0:numPersonFeatures] = egoArray[1, :]
X2[2, numPersonFeatures:numFeatures] = egoArray[2, :]
y2[2, 0] = -1
X2[3, 0:numPersonFeatures] = egoArray[2, :]
X2[3, numPersonFeatures:numFeatures] = egoArray[0, :]
y2[3, 0] = -1
X2[4, 0:numPersonFeatures] = egoArray[2, :]
X2[4, numPersonFeatures:numFeatures] = egoArray[1, :]
y2[4, 0] = -1
self.assertTrue((X2 == examplesList.getDataField("X")).all())
self.assertTrue((y2 == examplesList.getDataField("y")).all())
def testGenerateNonReceivers(self):
numEgos = 3
numFeatures = 5
p = 1
eCsvReader = EgoCsvReader()
eCsvReader.setP(p)
numContactsIndices = [0, 1]
homophileIndexPairs = [(2,3)]
receiverCounts = numpy.zeros(numEgos)
#First test a very simple example with 1 homophile pair
egoArray = numpy.zeros((numEgos, numFeatures))
egoArray[0, :] = [0, 1, 1, 5, 4]
egoArray[1, :] = [0, 1, 1, 5, 8]
egoArray[2, :] = [0, 0, 1, 3, 6]
(contactsArray, egoIndices, alterIndices) = eCsvReader.generateNonReceivers(egoArray, numContactsIndices, homophileIndexPairs, receiverCounts)
numContacts = 4
contactsArray2 = numpy.zeros((numContacts, numFeatures))
contactsArray2[0, :] = [0, 1, 1, 5, 8]
contactsArray2[1, :] = [0, 0, 1, 3, 6]
contactsArray2[2, :] = [0, 1, 1, 5, 4]
contactsArray2[3, :] = [0, 0, 1, 3, 6]
egoIndices2 = numpy.zeros(numContacts)
egoIndices2[0] = 0
egoIndices2[1] = 0
egoIndices2[2] = 1
egoIndices2[3] = 1
self.assertTrue((contactsArray == contactsArray2).all())
self.assertTrue((egoIndices == egoIndices2).all())
#Test the case when there are some receivers already
receiverCounts = numpy.array([1,1,1])
(contactsArray, egoIndices, alterIndices) = eCsvReader.generateNonReceivers(egoArray, numContactsIndices, homophileIndexPairs, receiverCounts)
numContacts = 2
contactsArray2 = numpy.zeros((numContacts, numFeatures))
contactsArray2[0, :] = [0, 1, 1, 5, 8]
contactsArray2[1, :] = [0, 1, 1, 5, 4]
egoIndices2 = numpy.zeros(numContacts)
egoIndices2[0] = 0
egoIndices2[1] = 1
self.assertTrue((contactsArray == contactsArray2).all())
self.assertTrue((egoIndices == egoIndices2).all())
#A more complex example
numEgos = 6
egoArray = numpy.zeros((numEgos, numFeatures))
egoArray[0, :] = [1, 1, 1, 5, 4]
egoArray[1, :] = [0, 0, 1, 5, 8]
egoArray[2, :] = [0, 0, 1, 3, 6]
egoArray[3, :] = [0, 0, 1, 5, 1]
egoArray[4, :] = [0, 0, 1, 5, 2]
egoArray[5, :] = [0, 0, 1, 5, 3]
receiverCounts = numpy.zeros(numEgos)
(contactsArray, egoIndices, alterIndices) = eCsvReader.generateNonReceivers(egoArray, numContactsIndices, homophileIndexPairs, receiverCounts)
numContacts = 4
contactsArray2 = numpy.zeros((numContacts, numFeatures))
contactsArray2[0, :] = [0, 0, 1, 5, 8]
contactsArray2[1, :] = [0, 0, 1, 5, 1]
contactsArray2[2, :] = [0, 0, 1, 5, 2]
contactsArray2[3, :] = [0, 0, 1, 5, 3]
egoIndices2 = numpy.zeros(numContacts)
egoIndices2[0] = 0
egoIndices2[1] = 0
egoIndices2[2] = 0
egoIndices2[3] = 0
self.assertTrue((contactsArray == contactsArray2).all())
self.assertTrue((egoIndices == egoIndices2).all())
#Test picking non-homophiles
egoArray[0, :] = [2, 1, 2, 5, 4]
(contactsArray, egoIndices, alterIndices) = eCsvReader.generateNonReceivers(egoArray, numContactsIndices, homophileIndexPairs, receiverCounts)
numContacts = 5
contactsArray2 = numpy.zeros((numContacts, numFeatures))
contactsArray2[0, :] = [0, 0, 1, 5, 8]
contactsArray2[1, :] = [0, 0, 1, 3, 6]
contactsArray2[2, :] = [0, 0, 1, 5, 1]
contactsArray2[3, :] = [0, 0, 1, 5, 2]
contactsArray2[4, :] = [0, 0, 1, 5, 3]
egoIndices2 = numpy.zeros(numContacts)
egoIndices2[0] = 0
egoIndices2[1] = 0
egoIndices2[2] = 0
egoIndices2[3] = 0
egoIndices2[4] = 0
self.assertTrue((contactsArray == contactsArray2).all())
self.assertTrue((egoIndices == egoIndices2).all())
#Choose different p
p = 0.5
eCsvReader.setP(p)
egoArray[0, :] = [1, 1, 1, 5, 4]
egoArray[1, :] = [0, 0, 1, 5, 8]
egoArray[2, :] = [0, 0, 1, 3, 6]
egoArray[3, :] = [0, 0, 1, 5, 8]
egoArray[4, :] = [0, 0, 1, 5, 8]
egoArray[5, :] = [0, 0, 1, 5, 8]
(contactsArray, egoIndices, alterIndices) = eCsvReader.generateNonReceivers(egoArray, numContactsIndices, homophileIndexPairs, receiverCounts)
numContacts = 3
contactsArray2 = numpy.zeros((numContacts, numFeatures))
contactsArray2[0, :] = [0, 0, 1, 5, 8]
contactsArray2[1, :] = [0, 0, 1, 5, 8]
contactsArray2[2, :] = [0, 0, 1, 3, 6]
egoIndices2 = numpy.zeros(numContacts)
egoIndices2[0] = 0
egoIndices2[1] = 0
egoIndices2[2] = 0
self.assertTrue((contactsArray == contactsArray2).all())
self.assertTrue((egoIndices == egoIndices2).all())
#Test 2 different homophile fields
p = 1
eCsvReader.setP(p)
numEgos = 6
numFeatures = 7
homophileIndexPairs = [(2,3), (4,5)]
egoArray = numpy.zeros((numEgos, numFeatures))
egoArray[0, :] = [0, 0, 1, 5, 1, 2, 1]
egoArray[1, :] = [0, 0, 1, 5, 1, 3, 2]
egoArray[2, :] = [0, 0, 1, 4, 1, 2, 3]
egoArray[3, :] = [1, 0, 1, 5, 1, 2, 4]
egoArray[4, :] = [0, 0, 1, 2, 1, 1, 5]
egoArray[5, :] = [0, 0, 1, 5, 1, 2, 6]
(contactsArray, egoIndices, alterIndices) = eCsvReader.generateNonReceivers(egoArray, numContactsIndices, homophileIndexPairs, receiverCounts)
numContacts = 2
contactsArray2 = numpy.zeros((numContacts, numFeatures))
contactsArray2[0, :] = [0, 0, 1, 5, 1, 2, 1]
contactsArray2[1, :] = [0, 0, 1, 5, 1, 2, 6]
egoIndices2 = numpy.zeros(numContacts)
egoIndices2[0] = 3
egoIndices2[1] = 3
self.assertTrue((contactsArray == contactsArray2).all())
self.assertTrue((egoIndices == egoIndices2).all())
def testInit(self):
eCsv = EgoCsvReader()
self.assertEquals(len(eCsv.getEgoQuestionIds()), 62)
self.assertEquals(len(eCsv.getAlterQuestionIds()), 62)
