def getGaussianSobol(num_points, dimension):
""" Sobol Gaussian quasi random points generator based on graycode order.
The generated points follow a normal distribution. """
points = getUniformSobol(num_points, dimension)
for i in range(num_points):
for j in range(dimension):
points[i, j] = norminvcdf(points[i, j])
return points
def test_FinMath():
xValues = np.linspace(-6.0, 6.0, 13)
start = time.time()
testCases.header("FUNCTION", "X", "Y")
for x in xValues:
y = N(x)
testCases.print("NORMCDF1", x, y)
end = time.time()
duration = end - start
testCases.header("LABEL", "TIME")
testCases.print("Fast N(x) takes ", duration)
##########################################################################
testCases.header("FUNCTION", "X", "Y")
start = time.time()
for x in xValues:
y = normcdf_slow(x)
testCases.print("NORMCDF2", x, y)
end = time.time()
duration = end - start
testCases.header("LABEL", "TIME")
testCases.print("Slow N(x) takes ", duration)
##########################################################################
testCases.header("FUNCTION", "X", "Y")
start = time.time()
for x in xValues:
y = normcdf_integrate(x)
testCases.print("NORMCDF INTEGRATE", x, y)
end = time.time()
duration = end - start
testCases.header("LABEL", "TIME")
testCases.print("Trapezium N(x) takes ", duration)
##########################################################################
xValues = np.linspace(-6.0, 6.0, 20)
testCases.header("X", "Y1", "Y2", "Y3", "DIFF1", "DIFF2")
for x in xValues:
y1 = N(x)
y2 = normcdf_slow(x)
y3 = normcdf_integrate(x)
diff1 = y3 - y1
diff2 = y3 - y2
testCases.print(x, y1, y2, y3, diff1, diff2)
##########################################################################
xValues = np.linspace(-6.0, 6.0, 20)
testCases.header("X", "Y1", "Y2", "INV_Y1", "INV_Y2", "DIFF1", "DIFF2")
for x_in in xValues:
y1 = N(x_in)
y2 = normcdf_slow(x_in)
x_out1 = norminvcdf(y1)
x_out2 = norminvcdf(y2)
diff1 = x_out1 - x_in
diff2 = x_out2 - x_in
testCases.print(x, y1, y2, x_out1, x_out2, diff1, diff2)