import logging
import sys
import numpy
import random
from apgl.egograph.InfoExperiment import InfoExperiment
from apgl.egograph.SvmEgoSimulator import SvmEgoSimulator
logging.basicConfig(stream=sys.stdout, level=logging.INFO)
numpy.random.seed(21)
random.seed(21)
examplesFileName = SvmInfoExperiment.getExamplesFileName()
folds = 5
cvSampleSize = SvmInfoExperiment.getNumCVExamples()
sampleSize = 75000
svmEgoSimulator = SvmEgoSimulator(examplesFileName)
classifier = svmEgoSimulator.getClassifier()
#classifier.setTermination(0.1)
C, kernel, kernelParamVal, errorCost = SvmInfoExperiment.loadSvmParams(SvmInfoExperiment.getSvmParamsFileName())
logging.info("Training SVM with C=" + str(C) + ", " + kernel + " kernel" + ", param=" + str(kernelParamVal) + ", sampleSize=" + str(sampleSize) + ", errorCost="+str(errorCost))
svmEgoSimulator.sampleExamples(cvSampleSize)
svmEgoSimulator.evaluateClassifier(C, kernel, kernelParamVal, errorCost, folds, sampleSize, True)
