def __init__(self, x, y):
if len(x) != len(y):
raise ValueError("x and y must have the same length.")
if ((x[1:] - x[:-1]) < 0).any():
raise ValueError("x must be a sorted array.")
self.x = numpy.array(x, float, copy=False)
self.y = numpy.array(y, float, copy=False)
self.d = numpy.zeros(len(self.x), float)
spline_construct(self.x,self.y,self.d)
def test_blind2():
# see whether we get segfaults or not.
x = numpy.arange(0, 1.005, 0.1) * numpy.pi * 2
y = numpy.sin(x)
d = numpy.zeros(len(x), float)
spline_construct(x, y, d)
x_new = numpy.arange(0, 1.0005, 0.01) * numpy.pi * 2
y_new = numpy.zeros(len(x_new), float)
spline_eval(x, y, d, x_new, y_new)
yint_spline = numpy.zeros(len(y), float)
spline_cumul_int(x, y, d, yint_spline)
def test_blind1():
# see whether we get segfaults or not.
x = numpy.arange(0, 1, 0.1)
y = numpy.random.normal(0, 1, len(x))
d = numpy.zeros(len(x), float)
spline_construct(x, y, d)
x_new = numpy.random.uniform(-1, 2, 50)
y_new = numpy.zeros(len(x_new), float)
spline_eval(x, y, d, x_new, y_new)
yint = numpy.zeros(len(y), float)
spline_cumul_int(x, y, d, yint)
def _get_weights_aux(self, us, vs):
ys = numpy.zeros(len(us), float)
ds = numpy.zeros(len(us), float)
ws = numpy.zeros(len(us), float)
for i in xrange(len(us)):
ys[:] = 0
if vs is None:
ys[i] = 1
else:
ys[i] = vs[i]
spline_construct(us, ys, ds)
ws[i] = spline_int(us, ys, ds)
return ws
def _get_weights_aux(self, us, vs):
ys = numpy.zeros(len(us), float)
ds = numpy.zeros(len(us), float)
ws = numpy.zeros(len(us), float)
for i in xrange(len(us)):
ys[:] = 0
if vs is None:
ys[i] = 1
else:
ys[i] = vs[i]
spline_construct(us,ys,ds)
ws[i] = spline_int(us,ys,ds)
return ws
