dDot.exportData(dataFolder + '/Run_' + str(runNum) + '.txt', 'data3',
i + 1)
runNum += 1
print "Subsequent " + str(len(order)) + " runs: ", time() - startTime
#Generate CODA capacitive Matrix
codaDataFolder = currentIterationFolder + '/CODA_data'
if not os.path.exists(codaDataFolder):
os.makedirs(codaDataFolder)
outputFile = open(codaDataFolder + '/CODA_data.txt', 'w')
for i in range(len(order) + 1):
density, ts = analyzeDataFile(dataFolder + '/Run_' + str(i) + '.txt')
outputVolts = currentVolts
if i > 0:
outputVolts[i - 1] += 0.001
outputFile.write(
str(outputVolts + density.tolist() + ts.tolist()).replace(
',', '').replace(']', '').replace('[', '') + ' \n')
if i > 0:
outputVolts[i - 1] -= 0.001
outputFile.close()
#Run CODA, select certain solutions
plot, voltageChanges = l1ErrorPlot(codaDataFolder + '/CODA_data.txt',
target)
numTries = 10
#Generate base COMSOL data
dataFolder = currentIterationFolder + '/COMSOL_data'
#Run CODA, select certain solutions
voltageChanges, totalDistance = findDirection(
codaDataFolder + '/CODA_data.txt', target)
solutionL2Norm = norm(voltageChanges, ord=2)
paramMat = []
convergenceData = [[], []]
minDistance = 10.
runNum = 16
for alpha in logspace(-5, 0, 11):
convergenceData[0] += [alpha * solutionL2Norm]
density, ts = analyzeDataFile(dataFolder + '/Run_' + str(runNum) +
'.txt')
predictedDeps = predictDeps(codaDataFolder + '/CODA_data.txt',
alpha * voltageChanges)
differenceFromLinear = abs(density[0:2] -
predictedDeps[0:2]).tolist()
print alpha, density[0:2], predictedDeps[0:2]
print alpha, array(map(log, ts)), predictedDeps[2:]
differenceFromLinear += (
0.5 * abs(array(map(log, ts)) - predictedDeps[2:])).tolist()
differenceFromLinearNorm = norm(array(differenceFromLinear), ord=2)
convergenceData[1] += [differenceFromLinearNorm / totalDistance]
runNum += 1
if plotL1:
import matplotlib
matplotlib.use('Agg')
dDot.runSimulation('std2')
for i in range(numTries[index]):
dDot.exportData(
dataFolder + '/Height_' + str(height) + '/Run_' + str(runNum) +
'.txt', 'data3', i + 1)
runNum += 1
print "Subsequent " + str(numTries[index]) + " runs: ", time() - startTime
for index, heightParams in enumerate(params):
convergenceData = [[], []]
for i, dataIndex in enumerate(dataIndecesUsed[index]):
convergenceData[0] += [data[index][0][dataIndex]]
density, ts = analyzeDataFile(dataFolder + '/Height_' +
str(heightParams[0]) + '/Run_' +
str(i + 1) + '.txt')
print convergenceData[0][-1], density, ts
pointDistance = sum(abs(density[0:2] - target[0:2]))
pointDistance += sum(
abs(array(map(log, ts)) - array(map(log, target[4:]))))
convergenceData[1] += [
pointDistance * data[index][2][dataIndex] /
data[index][1][dataIndex]
]
plt.cla()
plt.clf()
plt.plot(data[index][0], data[index][2], linewidth=2.)
plt.plot(convergenceData[0], convergenceData[1], 's--', linewidth=2.)
labels = ['Predicted Error', 'Actual Error']