def testTrim(self):
S = PiecewiseFunction(fun=lambda x: sin(4*(x-0.5)), breakPoints=[-1, 1]).toInterpolated()
I = S.trimInterpolators(abstol=1e-15)
figure()
subplot(211)
S.plot(color="r")
I.plot(color="k")
r = S-I
subplot(212)
r.plot()
#show()
self.assert_(0 < 1)
def testTrim(self):
S = PiecewiseFunction(fun=lambda x: sin(4 * (x - 0.5)),
breakPoints=[-1, 1]).toInterpolated()
I = S.trimInterpolators(abstol=1e-15)
figure()
subplot(211)
S.plot(color="r")
I.plot(color="k")
r = S - I
subplot(212)
r.plot()
#show()
self.assert_(0 < 1)
def testChebcoef(self):
S = PiecewiseFunction(fun=lambda x: sin(4*(x-0.5)), breakPoints=[-1, 1]).toInterpolated()
seg = S.segments[0]
Xs, Ys = seg.f.Xs, seg.f.Ys
print "Xs=", Xs
print "Ys=", Ys
print "Cs=", chebt2(Ys)
print "Xs=", ichebt2(chebt2(Ys))
figure()
S.plot(color="r")
D = S.diff()
D.plot(color="k")
#show()
self.assert_(0 < 1)
def testChebcoef(self):
S = PiecewiseFunction(fun=lambda x: sin(4 * (x - 0.5)),
breakPoints=[-1, 1]).toInterpolated()
seg = S.segments[0]
Xs, Ys = seg.f.Xs, seg.f.Ys
print "Xs=", Xs
print "Ys=", Ys
print "Cs=", chebt2(Ys)
print "Xs=", ichebt2(chebt2(Ys))
figure()
S.plot(color="r")
D = S.diff()
D.plot(color="k")
#show()
self.assert_(0 < 1)
def plot_regression(F, Ybreaks=None):
assert F.d == 2
X = F.marginals[0]
Y = F.marginals[1]
if Ybreaks is None:
Ybreaks = Y.get_piecewise_pdf().getBreaks()
def cond_pdf(F, Xpdf, x, y):
if not isscalar(y):
x = zeros_like(y) + x
return F.pdf(x, y) / Xpdf
def regfun(type, x):
# value of regression functions at point x
if isscalar(x):
Xpdf = float(X.pdf(x))
if Xpdf == 0:
y = NaN
else:
distr = FunDistr(fun=partial(cond_pdf, F, Xpdf, x),
breakPoints=Ybreaks)
if type == 1: y = distr.mean()
if type == 2: y = distr.median()
if type == 3: y = distr.mode()
if y is None:
y = NaN
else:
y = zeros_like(x)
for i in range(len(x)):
y[i] = regfun(type, x[i])
return y
F.contour()
Xbreaks = X.get_piecewise_pdf().getBreaks()
Xbreaks = concatenate([Xbreaks, [F.a[0], F.b[0]]])
Xbreaks.sort()
Xbreaks = epsunique(Xbreaks)
mreg = PiecewiseFunction(fun=partial(regfun, 1),
breakPoints=Xbreaks).toInterpolated()
mreg.plot(label="mean")
mreg = PiecewiseFunction(fun=partial(regfun, 2),
breakPoints=Xbreaks).toInterpolated()
mreg.plot(label="median", color="g")
mreg = PiecewiseFunction(fun=partial(regfun, 3),
breakPoints=Xbreaks).toInterpolated()
mreg.plot(label="mode", color="r")
legend()
def plot_regression(F, Ybreaks = None):
assert F.d == 2
X = F.marginals[0]
Y = F.marginals[1]
if Ybreaks is None:
Ybreaks = Y.get_piecewise_pdf().getBreaks()
def cond_pdf(F, Xpdf, x, y):
if not isscalar(y):
x = zeros_like(y) + x
return F.pdf(x, y) / Xpdf
def regfun(type, x):
# value of regression functions at point x
if isscalar(x):
Xpdf = float(X.pdf(x))
if Xpdf == 0:
y = NaN
else:
distr = FunDistr(fun = partial(cond_pdf, F, Xpdf, x),
breakPoints = Ybreaks)
if type==1: y = distr.mean()
if type==2: y = distr.median()
if type==3: y = distr.mode()
if y is None:
y = NaN
else:
y = zeros_like(x)
for i in range(len(x)):
y[i] = regfun(type, x[i])
return y
F.contour()
Xbreaks = X.get_piecewise_pdf().getBreaks()
Xbreaks = concatenate([Xbreaks, [F.a[0], F.b[0]]])
Xbreaks.sort()
Xbreaks = epsunique(Xbreaks)
mreg = PiecewiseFunction(fun=partial(regfun, 1), breakPoints=Xbreaks).toInterpolated()
mreg.plot(label = "mean")
mreg = PiecewiseFunction(fun=partial(regfun, 2), breakPoints=Xbreaks).toInterpolated()
mreg.plot(label = "median", color = "g")
mreg = PiecewiseFunction(fun=partial(regfun, 3), breakPoints=Xbreaks).toInterpolated()
mreg.plot(label = "mode", color = "r")
legend()
B = PiecewiseFunction(fun=lambda x:sin(3*x), breakPoints=[-1,0,1])
B = B.toInterpolated()
print(B.segments[0].f.__class__)
#B = B.trimInterpolators(abstol=1e-15)
print(B.segments[0].f.Ys, B.segments[0].f.__class__)
D = B.diff()
D2 = D.diff()
D3 = D2.diff()
D4 = D3.diff()
D5 = D4.diff()
print(D.segments[0].f.Ys, D.segments[0].f.__class__)
print(D2.segments[0].f.Ys)
print(D.roots())
figure()
B.plot()
D.plot()
D2.plot()
D3.plot()
D4.plot()
D5.plot()
show()
0/0
#Xs = [-1,0,1]
#Ys = [0,1,0]
#i = Interpolator(Xs, Ys)
#X = linspace(-1,1,100)
#Y = [i.interp_at(x) for x in X]
#ci = ChebyshevInterpolator(cos, -2, 8)
#print ci.err, len(ci.Xs)
B = PiecewiseFunction(fun=lambda x:sin(3*x), breakPoints=[-1,0,1])
B = B.toInterpolated()
print B.segments[0].f.__class__
#B = B.trimInterpolators(abstol=1e-15)
print B.segments[0].f.Ys, B.segments[0].f.__class__
D = B.diff()
D2 = D.diff()
D3 = D2.diff()
D4 = D3.diff()
D5 = D4.diff()
print D.segments[0].f.Ys, D.segments[0].f.__class__
print D2.segments[0].f.Ys
print D.roots()
figure()
B.plot()
D.plot()
D2.plot()
D3.plot()
D4.plot()
D5.plot()
show()
0/0
#Xs = [-1,0,1]
#Ys = [0,1,0]
#i = Interpolator(Xs, Ys)
#X = linspace(-1,1,100)
#Y = [i.interp_at(x) for x in X]
#ci = ChebyshevInterpolator(cos, -2, 8)
#print ci.err, len(ci.Xs)
