def testDeltaPDF2(self):
print "\n test Delta PDF 2:"
ZPoints = 6
ZmeanPoints = 1
ZvarPoints = 1
ZMin = 0
ZMax = 1
ZmeanMin = 0.25
ZmeanMax = ZmeanMin
ZvarMin = 0
ZvarMax = ZvarMin
# create arrays of type "double *"
Z = np.linspace(ZMin, ZMax, ZPoints)
Zmean = np.linspace(ZmeanMin, ZmeanMax, ZmeanPoints)
Zvar = np.linspace(ZvarMin, ZvarMax, ZvarPoints)
# create instances of PDF class
d = pdf.DeltaPDF(Zmean)
dPdfValM = matrix3d.Matrix3D(ZvarPoints, ZmeanPoints, ZPoints)
# expected PDF values
PDF = np.zeros(ZPoints)
PDF[1] = 0.75 * (ZPoints - 1)
PDF[2] = 0.25 * (ZPoints - 1)
# calculate PDF
test = d.pdfVal(Z, dPdfValM)
PDFCalc = np.zeros(ZPoints)
# test
for k in range(ZPoints):
PDFCalc[k] = dPdfValM.GetVal(0, 0, k)
self.assertAlmostEqual(PDF[k], PDFCalc[k])
def testBetaPDF1(self):
print "\n test Beta PDF 1: Var = 0 --> Delta PDF"
ZPoints = 6
ZmeanPoints = 1
ZvarPoints = 1
ZMin = 0
ZMax = 1
ZmeanMin = 0.25
ZmeanMax = ZmeanMin
ZvarMin = 0
ZvarMax = ZvarMin
# create arrays of type "double *"
Z = np.linspace(ZMin, ZMax, ZPoints)
Zmean = np.linspace(ZmeanMin, ZmeanMax, ZmeanPoints)
Zvar = np.linspace(ZvarMin, ZvarMax, ZvarPoints)
# create instances of PDF class
b = pdf.BetaPDF(Zmean, Zvar)
bPdfValM = matrix3d.Matrix3D(ZvarPoints, ZmeanPoints, ZPoints)
bPDF = np.zeros(ZPoints)
# expected PDF values
d = pdf.DeltaPDF(Zmean)
dPdfValM = matrix3d.Matrix3D(ZvarPoints, ZmeanPoints, ZPoints)
dPDF = np.zeros(ZPoints)
# calculate PDF
bTest = b.pdfVal(Z, bPdfValM)
dTest = d.pdfVal(Z, dPdfValM)
# test
for k in range(ZPoints):
bPDF[k] = bPdfValM.GetVal(0, 0, k)
dPDF[k] = dPdfValM.GetVal(0, 0, k)
self.assertAlmostEqual(bPDF[k], dPDF[k])
self.assertEqual(bTest, 0)
self.assertEqual(dTest, 0)
def testDeltaPDF1(self):
print "\n Delta PDF 1:"
"""
NOTE: Simpson's Rule doesn't work for Delta PDFs; see integrator
test for a proof/explanation
"""
ZPoints = 5
ZmeanPoints = 1
ZvarPoints = 1
ZMin = 0
ZMax = 1
ZmeanMin = 0.25
ZmeanMax = ZmeanMin
ZvarMin = 0
ZvarMax = ZvarMin
Nodes = 50
# create arrays of type "double *"
Z = np.linspace(ZMin, ZMax, ZPoints)
Zmean = np.linspace(ZmeanMin, ZmeanMax, ZmeanPoints)
Zvar = np.linspace(ZvarMin, ZvarMax, ZvarPoints)
# create instances of PDF class
d = pdf.DeltaPDF(Zmean)
dPdfValM = matrix3d.Matrix3D(ZvarPoints, ZmeanPoints, ZPoints)
# expected PDF values
PDF = np.zeros(ZPoints)
PDF[1] = 1 * (ZPoints - 1)
# calculate PDF
test = d.pdfVal(Z, dPdfValM)
PDFCalc = np.zeros(ZPoints)
# test
for k in range(ZPoints):
PDFCalc[k] = dPdfValM.GetVal(0, 0, k)
self.assertAlmostEqual(PDF[k], PDFCalc[k])
# create Integrators
Trapz = integrator.Trapz()
Quadr = integrator.GLQuad(Nodes)
# create Filtered Data Matrices
postTrapz = matrix.Matrix(ZvarPoints, ZmeanPoints)
postQuadr = matrix.Matrix(ZvarPoints, ZmeanPoints)
# create matrix for printing
filterTrapz = np.zeros(ZmeanPoints)
filterQuadr = np.zeros(ZmeanPoints)
# create test data
testData = np.ones(ZPoints)
# calculate filtered reaction rates
c = convolute.convVal_func(Z, testData, dPdfValM, postTrapz, Trapz)
c = convolute.convVal_func(Z, testData, dPdfValM, postQuadr, Quadr)
for j in range(ZmeanPoints):
filterTrapz[j] = postTrapz.GetVal(0, j)
filterQuadr[j] = postQuadr.GetVal(0, j)
self.assertEqual(filterTrapz[j], 1)
self.assertAlmostEqual(filterQuadr[j], 1, 1)
delimiter="\t",
usecols=0)
# if no Z_grid is specified, Z and Zmean will be equivalent
if options["Zmean grid"][0] == 'Z':
Zmean = Z
else:
Zmean = np.linspace(0, 1, int(options["Zmean grid"][0]))
Zpdf = options["Zpdf"]
# Generate pdf objects
print "Generating PDF matrix with", Zpdf[0], "PDF"
if Zpdf[0] == "delta": # delta pdf has variance 0
Zvar_grid = [1]
Zvar_max = [0]
Zvar = np.linspace(0, float(Zvar_max[0]), int(Zvar_grid[0]))
d = pdf.DeltaPDF(Zmean)
elif Zpdf[
0] == "beta": # must include user specified variances for beta pdf # currently not supported
Zvar_max = iof.read_input("Zvar_max:", inputs)
Zvar_grid = iof.read_input("Zvar_grid:", inputs)
Zvar = np.linspace(0, float(Zvar_max[0]), int(Zvar_grid[0]))
d = pdf.BetaPDF(Zmean, Zvar)
else:
raise IOError(
"Incorrect PDF input %s, currently only DELTA and BETA are supported" %
Zpdf[0])
# generate PDF matrix
ZPoints = len(Z)
ZvarPoints = len(Zvar)
ZmeanPoints = len(Zmean)